SPECIES DETECTION: MAMMALS
BATS
Zielinski W. J., Mazurek M. J., Zinck J. (2007): Identifying the species of bats roosting in redwood basal hollows using genetic methods. Northwest Science 81: 155-162.
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Bats frequently use basal hollows in trees to gain access to interior roost sites but it has been challenging to verify which species do so because it is difficult to capture bats or identify bats using acoustic methods at these locations. We employed noninvasive genetic sampling of guano to identify the species of bats that use basal hollows in redwood (Sequoia sempervirens) trees in coastal northern California. Guano was collected using screen traps suspended within the hollows of trees in the northern and central range of the redwood, in Del Norte and Mendocino County, California, respectively. A representative sample of 231 guano pellets from 104 trees was selected for analysis; 149 pellets from 63 trees amplified sufficiently for genetic sequencing. Species identification is possible for 8 of the 11 species that were assumed to occur in the study area, based on previous studies using two 190 bp regions of the 16S ribosomal subunit gene. Seven distinct species, subspecies or species groups were identified; all 7 were represented from samples in the northern study area whereas only 5 of these occurred within the central study area. The long-legged bat (Myotis volans) was the most frequent taxa identified. Genetic sampling to identify the species using roosts will be an important contribution to the conservation of bats. This method is noninvasive and appears more efficient than other methods, such as following radio-marked bats to basal hollows or attempting to capture bats as they enter or leave a hollow. New laboratory developments in this field, such as microarrays, when combined with sequencing, will open up domains of research on individual species and species composition at various temporal and geographic scales.
Walker F. M., Williamson C. H., Sanchez D. E., Sobek C. J., Chambers C. L. (2016): Species from feces: order-wide identification of Chiroptera from guano and other non-invasive genetic samples. Plos One 11: e0162342.
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Bat guano is a relatively untapped reservoir of information, having great utility as a DNA source because it is often available at roosts even when bats are not and is an easy type of sample to collect from a difficult-to-study mammalian order. Recent advances from microbial community studies in primer design, sequencing, and analysis enable fast, accurate, and cost-effective species identification. Here, we borrow from this discipline to develop an order-wide DNA mini-barcode assay (Species from Feces) based on a segment of the mitochondrial gene cytochrome c oxidase I (COI). The assay works effectively with fecal DNA and is conveniently transferable to low-cost, high-throughput Illumina MiSeq technology that also allows simultaneous pairing with other markers. Our PCR primers target a region of COI that is highly discriminatory among Chiroptera (92% species-level identification of barcoded species), and are sufficiently degenerate to allow hybridization across diverse bat taxa. We successfully validated our system with 54 bat species across both suborders. Despite abundant arthropod prey DNA in guano, our primers were highly specific to bats; no arthropod DNA was detected in thousands of feces run on Sanger and Illumina platforms. The assay is extendable to fecal pellets of unknown age as well as individual and pooled guano, to allow for individual (using singular fecal pellets) and community (using combined pellets collected from across long-term roost sites) analyses. We developed a searchable database (http://nau.edu/CEFNS/Forestry/Research/Bats/Search-Tool/) that allows users to determine the discriminatory capability of our markers for bat species of interest. Our assay has applications worldwide for examining disease impacts on vulnerable species, determining species assemblages within roosts, and assessing the presence of bat species that are vulnerable or facing extinction. The development and analytical pathways are rapid, reliable, and inexpensive, and can be applied to ecology and conservation studies of other taxa.
Bennett V. J., Hale A. M., Williams D. A. (2017): When the excrement hits the fan: Fecal surveys reveal species-specific bat activity at wind turbines. Mammalian Biology 87: 125-129.
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The reasons why bats are coming into contact with wind turbines are not yet well understood. One hypothesis is that bats are attracted to wind turbines and this attraction may be because bats perceive or misperceive the turbines to provide a resource, such as a foraging or roosting site. During post-construction fatality searches at a wind energy facility in the southern Great Plains, U.S., we discovered bat feces near the base of a wind turbine tower, which led us to hypothesize that bats were actively roosting and/or foraging at turbines. Thus over 2 consecutive years, we conducted systematic searches for bat feces on turbines at this site. We collected 72 bat fecal samples from turbines and successfully extracted DNA from 56 samples. All 6 bat species known to be in the area were confirmed and the majority (59%) were identified as Lasiurus borealis; a species that also comprised the majority of the fatalities (60%) recorded at the site. The presence of bat feces provides further evidence that bats were conducting activities in close proximity to wind turbines. Moreover, feces found in areas such as turbine door slats indicated that bats were using turbines as night or foraging roosts, and further provided evidence that bats were active near the turbines. Future research should therefore aim to identify those features of wind turbines that bats perceive or misperceive as a resource, which in turn may lead to new minimization strategies that effectively reduce bat fatalities at wind farms.
Patrick L. E., Just J. M., Vonhof M. J. (2017): Non-invasive bat species identification from mixed-species samples using a microarray. Conservation Genetics Resources 9: 139-149.
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Identifying species from non-invasively collected, mixed species samples for biodiversity monitoring can be difficult and expensive using typical molecular methods because samples are often degraded. This is the case when identifying the species of bats present in roosts where guano may be the only means of assessment without disturbing the bats themselves. To aid in such studies, we developed species-specific DNA probes and a microarray capable of identifying most bat species in the United States and Canada using our existing database of 16S mitochondrial DNA sequences. The microarray was sensitive enough to detect DNA diluted 1:500 for several species combinations and was able to detect the presence of more species in mixed guano samples collected from roosts than did direct sequencing from individual fecal pellets. We suggest that these DNA probes and the microarray could be a valuable tool with which to non-invasively monitor bat populations and roost use.
Mac Aodha O., Gibb R., Barlow K. E., Browning E., Firman M., Freeman R., Harder B., Kinsey L., Mead G. R., Newson S. E., Pandourski I., Parsons S., Russ J., Szodoray-Paradi A., Szodoray-Paradi F., Tilova E., Girolami M., Brostow G., Jones K. E. (2018): Bat detective – Deep learning tools for bat acoustic signal detection. Plos Computational Biology 14: e1005995.
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Passive acoustic sensing has emerged as a powerful tool for quantifying anthropogenic impacts on biodiversity, especially for echolocating bat species. To better assess bat population trends there is a critical need for accurate, reliable, and open source tools that allow the detection and classification of bat calls in large collections of audio recordings. The majority of existing tools are commercial or have focused on the species classification task, neglecting the important problem of first localizing echolocation calls in audio which is particularly problematic in noisy recordings. We developed a convolutional neural network based open-source pipeline for detecting ultrasonic, full-spectrum, search-phase calls produced by echolocating bats. Our deep learning algorithms were trained on full-spectrum ultrasonic audio collected along road-transects across Europe and labelled by citizen scientists from www.batdetective.org. When compared to other existing algorithms and commercial systems, we show significantly higher detection performance of search-phase echolocation calls with our test sets. As an example application, we ran our detection pipeline on bat monitoring data collected over five years from Jersey (UK), and compared results to a widely-used commercial system. Our detection pipeline can be used for the automatic detection and monitoring of bat populations, and further facilitates their use as indicator species on a large scale. Our proposed pipeline makes only a small number of bat specific design decisions, and with appropriate training data it could be applied to detecting other species in audio. A crucial novelty of our work is showing that with careful, non-trivial, design and implementation considerations, state-of-the-art deep learning methods can be used for accurate and efficient monitoring in audio.
Li H., Petric R., Alazzawi Z., Kauzlarich J., Mahmoud R. H., McFadden R., Perslow N., Rodriguez Flores A., Soufi H., Morales K., Kalcounis-Rueppell M. C., Schug M. D., Zarecky L. A. (2021): Four years continuous monitoring reveals different effects of urban constructed wetlands on bats. Land 10: 1087.
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Proactive artificial wetland constructions have been implemented to mitigate the loss of wetlands and their ecosystem services. As wetlands are habitats for bats, short-term (one or two years) studies find that constructed wetlands can immediately increase local bat activity and diversity. However, it is not clear how constructed wetlands affect bats through time while the wetlands are aging. We collected four years of continuous bat acoustic monitoring data at two constructed wetlands in an urban park in Greensboro, NC, USA. We examined bat activity and community composition patterns at these wetlands and compared them with reference sites in the city. With four years of data, we found that the effects of constructed wetlands were both habitat- and species-specific. The wetland in forests significantly increased bat activity, while the wetland in the open grass altered bat community composition. Specifically, in terms of species, we found that over time, constructed wetlands no longer attracted more big brown, silver-haired, or evening bats than control sites while the wetlands aged, highlighting the need to study broadly how each bat species uses natural and artificial wetlands. We emphasize the importance of long-term monitoring and the periodical evaluation of wildlife conservation actions.
Serrao N. R., Weckworth J. K., McKelvey K. S., Dysthe J. C., Schwartz M. K. (2021): Molecular genetic analysis of air, water, and soil to detect big brown bats in North America. Biological Conservation 261: 109252.
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Cave-hibernating bats are widespread in North America but are facing precipitous population declines due to the impacts of white-nose syndrome (WNS). It is in winter hibernacula that bats are most vulnerable to the fungus that causes WNS, but the locations of over-wintering sites in western North America are largely unknown. This poses a significant challenge for bat monitoring, disease surveillance, and management efforts at the disease front. To advance initiatives to locate bats on the landscape, we developed real-time PCR assays to detect big brown bats (Eptesicus fuscus) from environmental DNA samples (eDNA). Three assays were designed, one each for eastern, western, and southern North America, to account for the high intra-specific genetic variability within big brown bats. We demonstrate that these assays can detect bat DNA in environmental samples, including air, water, and soil, and are able to detect target DNA at concentrations as low as 2 copies per reaction. Although the assays are highly sensitive, detections from samples collected in field samples were modest. Our findings suggest that eDNA may provide a much-needed, non-invasive alternative to conventional tools used to detect bats on the landscape but require further research to optimize their field application.
Armstrong A. J., Walker F. M., Sobek C. J., Sanville C. J., Martin S. L., Szewczak J. M. (2022): Bat use of hollows in California’s old-growth redwood forests: From DNA to ecology. Animals 12: 2950.
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The loss of roosting resources, either through disturbance or removal, negatively affects bats. Identifying sensitive species and determining roost requirements are critical components in conserving their habitat. Cavity-roosting bats on the North Coast of California are known to use hollows in large redwood trees. In this study, we examined the factors determining the use of basal tree hollows by different bat species at eight redwood forest sites in Del Norte, Humboldt, and Mendocino Counties, California. Bat guano was collected from 179 basal hollow roosts from 2017 to 2018, and guano mass was used as an index of roosting activity. Nine bat species and one species group were identified by analysis of DNA in guano. We made a total of 253 identifications from 83 hollows into the 10 species categories. The most prevalent species were Myotis californicus (California myotis; 28.5% of all identifications), the Myotis evotis–Myotis thysanodes group (17.4%), Corynorhinus townsendii (17.0%), and Myotis volans (15.0%). We evaluated the extent to which habitat variables at the scales of the hollow, vicinity, and site influenced the level of roost use. The correlations between guano mass and habitat variables were examined using generalized additive mixed models. At the hollow scale, guano mass increased with ceiling height above the opening. At the vicinity scale, guano mass increased with less cover of small trees. At the site scale, there was no association between guano mass and distance to foraging areas, elevation, or the number of nearby hollows. These tree hollow roost preferences can inform land managers when planning the management and conservation of redwood forests.
Krivek G., Schulze B., Poloskei P. Z., Frankowski K., Mathgen X., Douwes A., van Schaik J. (2022): Camera traps with white flash are a minimally invasive method for long‐term bat monitoring. Remote Sensing in Ecology and Conservation 8: 284-296.
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Camera traps are an increasingly popular survey tool for ecological research and biodiversity conservation, but studies investigating their impact on focal individuals have been limited to only a few mammal species. In this context, echolocating bats are particularly interesting as they rely less on vision for navigation, yet show a strong negative reaction to constant illumination. At hibernacula, camera traps with white flash could offer an efficient alternative method for monitoring threatened bat species, but the potential negative impact of white flash on bat behavior is unknown. Here, we investigate the effect of camera traps emitting white flash at four hibernation sites fitted with infrared light barriers, infrared video cameras, and acoustic recorders over 16 weeks. At each site, the flash was turned off every second week. We quantified whether flash affected (1) nightly bat passes using generalized linear mixed models, (2) flight direction of entering bats using permutational multivariate analyses, and (3) latency of the first echolocation call after the camera trap trigger using randomization tests. Additionally, we quantified and corrected for the potential impact of confounding factors, such as weather and social interactions. Overall, white flash did not influence short- or long-term bat activity, flight direction or echolocation behavior. A decrease in nightly bat activity was observed with an increasing proportion of hours with rain. Moreover, flight direction was affected by the presence of other bats, likely due to chasing and avoidance behavior. Our findings highlight the potential of camera traps with white flash triggered by infrared light barriers as a minimally invasive method for long-term bat population monitoring and observation of species-specific phenology. Such automated monitoring technologies can improve our understanding of long-term population dynamics across a wide range of spatial-temporal scales and taxa and consequently, contribute to data-driven wildlife conservation and management.
Rydell J., Russo D., Sewell P., Seamark E. C., Francis C. M., Fenton S. L., Fenton M. B. (2022): Bat selfies: photographic surveys of flying bats. Mammalian Biology 102: 793-809.
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The recent pandemic and other environmental concerns have resulted in restrictions on research and surveys involving capture and handling bats. While acoustic surveys have been widely used as an alternative survey method, in this study, we show how photographic surveys can offer an important contribution to study and survey bats. We outline approaches, using high speed flash and automated trip beams to obtain photos of flying bats of sufficient quality for reliable identification of species. We show, through a series of examples of setups and photographs, that photography is effective for surveying bats at a variety of sites, where bats roost, drink, and forage. We note, however, that photographic surveys cannot replace capture in all situations. In addition, although photographing bats is less invasive than capturing them, it can involve disturbance, so we stress the importance of minimizing the impact of such operations on bats.
Walker F. M., Sanchez D. E., Froehlich E. M., Federman E. L., Lyman J. A., Owens M., Lear K. (2022): Endangered nectar-feeding bat detected by environmental DNA on flowers. Animals 12: 3075.
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Leptonycteris nivalis (the Mexican long-nosed bat) is an endangered nectar-feeding bat species that follows “nectar corridors” as it migrates from Mexico to the southwestern United States. Locating these nectar corridors is key to their conservation and may be possible using environmental DNA (eDNA) from these bats. Hence, we developed and tested DNA metabarcoding and qPCR eDNA assays to determine whether L. nivalis could be detected by sampling the agave flowers on which it feeds. We sampled plants with known bat visitations in the Sierra Madre Oriental in Laguna de Sanchez (LS), Nuevo León, Mexico, and in the Chisos Mountains in Big Bend National Park, TX, USA (CB). A total of 13 samples included both swabs of agave umbels and cuttings of individual flowers. DNA metabarcoding was performed as a PCR multiplex that targeted bats (SFF-COI), arthropods (ANML-COI), and plants (ITS2 and rbcL). We targeted arthropods and plants in parallel with bats because future metabarcoding studies may wish to examine all the pollinators and plants within the nectar corridor. We developed and tested the sensitivity and specificity of two qPCR assays. We found that both DNA metabarcoding and qPCR were highly successful at detecting L. nivalis (11 of 13 for DNA metabarcoding and 12 of 13 for qPCR). Swabs and flower cuttings and both qPCR assays detected the species over four replicates. We suggest that L. nivalis leaves substantial DNA behind as it forages for nectar. We also suggest that future studies examine the time since sampling to determine its effect on detection success. The DNA metabarcoding multiplex will be useful for parallel questions regarding pollination ecology, while, with further testing, the qPCR assays will be effective for large-scale sampling for the detection of migration corridors and foraging areas. This work may be relevant to other nectar-feeding bat species, which can likely be detected with similar methodologies.
Garrett N. R., Watkins J., Francis C. M., Simmons N. B., Ivanova N., Naaum A., Clare E. L. (2023): Out of thin air: surveying tropical bat roosts through air sampling of eDNA. PeerJ 11: e14772.
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Understanding roosting behaviour is essential to bat conservation and biomonitoring, often providing the most accurate methods of assessing bat population size and health. However, roosts can be challenging to survey, e.g., physically impossible to access or presenting risks for researchers. Disturbance during monitoring can also disrupt natural bat behaviour and present material risks to the population such as disrupting hibernation cycles. One solution to this is the use of non-invasive monitoring approaches. Environmental (e)DNA has proven especially effective at detecting rare and elusive species particularly in hard-to-reach locations. It has recently been demonstrated that eDNA from vertebrates is carried in air. When collected in semi-confined spaces, this airborne eDNA can provide remarkably accurate profiles of biodiversity, even in complex tropical communities. In this study, we deploy novel airborne eDNA collection for the first time in a natural setting and use this approach to survey difficult to access potential roosts in the neotropics. Using airborne eDNA, we confirmed the presence of bats in nine out of 12 roosts. The identified species matched previous records of roost use obtained from photographic and live capture methods, thus demonstrating the utility of this approach. We also detected the presence of the white-winged vampire bat (Diaemus youngi) which had never been confirmed in the area but was long suspected based on range maps. In addition to the bats, we detected several non-bat vertebrates, including the big-eared climbing rat (Ototylomys phyllotis), which has previously been observed in and around bat roosts in our study area. We also detected eDNA from other local species known to be in the vicinity. Using airborne eDNA to detect new roosts and monitor known populations, particularly when species turnover is rapid, could maximize efficiency for surveyors while minimizing disturbance to the animals. This study presents the first applied use of airborne eDNA collection for ecological analysis moving beyond proof of concept to demonstrate a clear utility for this technology in the wild.
Yoh N., Seaman D. J., Deere N. J., Bernard H., Bicknell J. E., Struebig M. J. (2023): Benign effects of logging on aerial insectivorous bats in Southeast Asia revealed by remote sensing technologies. Journal of Applied Ecology 60: 1210-1222.
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Logging is the most widespread disturbance in tropical forests, altering ecological communities and functions. However, many species can persist in logged forests, particularly where disturbance is low. Despite a growing understanding of how logging affects wildlife, there remains little information for Southeast Asia’s bats—in part due to major challenges in monitoring. We integrated remote sensing data from passive acoustic bat detectors with LiDAR-derived measures of forest structure from a human-modified landscape in Sabah, Borneo. Our appraisal of logging effects benefitted from a semi-automated classifier of bat calls that vastly speeds up the analysis of acoustic recording data. We recorded 105,576 bat passes from 21 phonic groups across a habitat disturbance gradient, comprising old-growth forest, repeatedly logged forest and tree plantations. We show that logging pressure (as depicted by changes to habitat quality, e.g. canopy height or shape) had negligible impact on the acoustic activity of bats. However, bat activity was higher in areas with a greater extent of high-biomass forest, as well as areas with greater topographical ruggedness. Logged forest supported higher levels of activity for several common bat phonic groups compared to old-growth forest. Across the landscape, plantations supported the lowest levels of bat activity, representing a threefold decrease compared to old-growth forest, and several species were not recorded in this habitat. We found different call groups demonstrated different responses to forest disturbance. Sheath-tailed bats (Emballonura spp.) were active across all habitat types and were the most resilient to logging. Edge/open foragers were more prevalent in highly forested and topographically rugged areas. Horseshoe and leaf-nosed bats (flutter clutter foragers) demonstrated idiosyncratic responses to logging but were consistently absent from plantations. Logged forests can provide an important refuge for many common bat species in Southeast Asia, but do not capture the full breadth of forest-specialist species. Nevertheless, logged forests provide substantially better habitat for bats than tree plantations. While aerial insectivorous bats sampled via acoustic methods are poor indicators of forest disturbance overall, several species that respond predictably to logging could be targeted for biodiversity monitoring using acoustic and capture-based methods.
Thibault M., Garnier L. K., Kauffmann C., Bas Y., Kerbiriou C. (2024): Listening to the response of bat and bush‐cricket communities to management regimes of powerline clearings. Conservation Science and Practice 6: e13127.
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Linear transportation infrastructures (LTIs) are established drivers of habitat fragmentation and barrier effects. Yet, they represent an increasing surface of managed seminatural habitats where increased consideration of biodiversity outputs is needed in an era of global biodiversity decline. A combined effort by both scientists and stakeholders is, therefore, needed to evaluate the promises and limits of these alternatives so that they best achieve their conservation potential. Our study explores the effects of forest powerline clearings on biodiversity, as well as the potential benefits of integrated vegetation management (IVM) as alternatives to clear-cuts. We recorded the acoustic activity at 35 pairs of forest/clearing stations in two forested regions of France in 2021. Our results suggest that powerline clearings represent increased movement opportunities for bats and, most particularly, edge-foraging species. They also provide suitable habitats for bush-cricket species, particularly species requiring thermophilic conditions. We detected no direct benefit from IVM on bat communities. However, bush-cricket communities appeared richer, more acoustically active, and statistically different from adjacent forests in clearings favoring secondary vegetation compared with clear-cut ones. This collaborative study provides data on understudied taxa in the context of LTIs and sheds light on conservation promises and limits associated with their management.
CARNIVORES
Dalén L., Götherström A., Meijer T., Shapiro B. (2007): Recovery of DNA from footprints in the snow. The Canadian Field-Naturalist 121: 321-324.
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The recovery of trace amounts of DNA has been demonstrated to be a reliable tool in conservation genetics and has become a key component of modern forensic casework. To date, genetic data have been successfully recovered from a variety of sources, including biological fluids, faeces, clothing, and even directly from fingerprints. However, to our knowledge and despite their widespread occurrence and clear potential as a source of DNA, genetic information has not previously been recovered directly from footprints. Here, we extract and amplify mitochondrial DNA from a snow footprint, <48-hours old, made by a Swedish Arctic Fox (Alopex lagopus). Our results demonstrate that it is possible to recover sufficient DNA from recent footprints to accurately type the source of the print, with implications for conservation biology and forensic science.
Castro-Arellano I., Madrid-Luna C., Lacher Jr, T. E., León-Paniagua L. (2008): Hair‐trap efficacy for detecting mammalian carnivores in the tropics. The Journal of Wildlife Management 72: 1405-1412.
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Direct studies of mammalian carnivores are challenging due to the animals’ secretive nature and the high costs associated with their capture and handling. Use of noninvasive hair sampling to survey these reclusive species has great potential as an alternative, with wide applicability in ecology and conservation. Hair‐trapping has been extensively used for focal studies of temperate mammals, but its use and applicability as a means to survey mammals in tropical environs has never been addressed. We evaluated the effectiveness of 2 hair‐trap types and 2 scents along an elevational gradient within El Cielo Biosphere Reserve (ECBR, Mexico) to detect presence of carnivores. Hair‐traps that used roofing nails as a hair‐collecting surface collected more hairs and detected a greater number of species than did hair‐traps that used velcro strips. Different scent treatments (commercial fragrance and catnip oil) did not differ for these same variables. Of successful nail hair‐traps, 60% collected ≥20 hairs (max. = 439), providing enough material for DNA analyses. Hair‐trap surveys detected 74% of the potential target mammal species at ECBR with only 19 days of field effort. Developing countries have limited budgets for biodiversity monitoring and hair‐traps compare favorably with other methods with a high cost‐benefit ratio. Hair‐traps are inexpensive, portable, can be made with over‐the‐counter materials, and can be successfully used to collect data applicable to population and genetic studies of tropical carnivores.
Lyra-Jorge M. C., Ciocheti G., Pivello V. R. (2008): Carnivore mammals in a fragmented landscape in northeast of São Paulo State, Brazil. Biodiversity and Conservation 17: 1573-1580.
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São Paulo is the most developed state in Brazil and little of its native vegetation remains. In Luiz Antonio and Santa Rita do Passa Quatro municipalities, only small fragments of cerrado (Brazilian savanna) physiognomies (cerradão, cerrado sensu stricto) and of semideciduous forest have been left, surrounded by eucalyptus silviculture and sugar-cane agriculture. However, that vegetation mosaic still shelters large mammals, including several carnivore species. To detect the carnivores present in such a mosaic area (50,000 ha), and to find out how they use the landscape, we recorded them through 21 camera traps and 21 track plots, during 18 months. Species richness, diversity and relative frequency were evaluated according to the habitat. Ten species were recorded, some of them locally threatened to extinction (Puma concolor, Leopardus pardalis, Chrysocyon brachyurus). Species diversity did not significantly differ among fragments, and although most species preferred one or another habitat, the carnivore community as a whole explored all the study area regardless of the vegetation cover; eucalyptus plantations were as used by the carnivores as the native fragments. Therefore, it seems possible to maintain such animals in agricultural landscapes, where some large native fragments are left and the matrix is permeable to native fauna.
Davidson G. A., Clark D. A., Johnson B. K., Waits L. P., Adams J. R. (2014): Estimating cougar densities in northeast Oregon using conservation detection dogs. The Journal of Wildlife Management 78: 1104-1114.
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Estimating densities of cougar (Puma concolor) is important for managing cougars and their prey but remains challenging because of cougar’s elusive and solitary behavior. To evaluate a non-invasive, genetic capture–recapture method to estimate cougar population size and density, we surveyed a 220-km2 area using conservation detection dogs trained to locate scat over a 4-week sampling period in northeast Oregon. We collected 272 scat samples and conducted DNA analysis on 249 samples from which we determined individual identification from 73 samples that represented 21 cougars (9 males and 12 females). We evaluated 4 models to estimate cougar densities: Huggins closed population capture–recapture (Huggins), CAPWIRE, multiple detections with Poisson (MDP), and spatially explicit capture–recapture (SECR). Population estimates for cougars using our study area were 26 (95% CI = 22–35, 9 males and 17 females) from Huggins models, 24 (95% CI = 21–30, 9 males and 15 females) from CAPWIRE, and 27 (95% CI = 24–42, 9 males and 18 females) from the MDP model. We accounted for the edge effect in density estimates caused by individuals whose home ranges included only a portion of the survey grid by buffering the study area using the mean home range radius of 8 cougars equipped with global positioning system collars on or near the study area. We estimated densities of 4.6 cougars/100 km2 (95% CI = 3.8–8.3) for the Huggins model, 4.8 cougars/100 km2 (95% CI = 4.2–7.8) for the MDP model, 4.2 cougars/100 km2 (95% CI = 3.3–5.3) for the CAPWIRE model, and 5.0 cougars/100 km2 (95% CI = 3.2–7.7) for the SECR model. Our results suggested estimating cougar densities using scat detection dogs could be feasible at a broader scale with less effort than other methods currently being used.
Monterroso P., Rich L. N., Serronha A., Ferreras P., Alves P. C. (2014): Efficiency of hair snares and camera traps to survey mesocarnivore populations. European Journal of Wildlife Research 60: 279-289.
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Mammalian carnivore communities affect entire ecosystem functioning and structure. However, their large spatial requirements, preferred habitats, low densities, and elusive behavior deem them difficult to study. In recent years, noninvasive techniques have become much more common as they can be used to monitor multiple carnivore species across large areas at a relatively modest cost. Hair snares have the potential to fulfill such requirements, but have rarely been tested in Europe. Our objective was to quantitatively assess the effectiveness of hair snares for surveying mesocarnivores in the Iberian Peninsula (Southwestern Europe), by comparison with camera-trapping. We used an occupancy modeling framework to assess method-specific detectability and occupancy estimates and hypothesized that detection probabilities would be influenced by season, sampling method, and habitat-related variables. A total of 163 hair samples were collected, of which 136 potentially belonged to mesocarnivores. Genetic identification success varied with diagnostic method: 25.2 % using mitochondrial CR, and 9.9 % using the IRBP nuclear gene. Naïve occupancy estimates were, in average, 5.3 ± 1.2 times higher with camera-trapping than with hair-snaring, and method-specific detection probabilities revealed that camera traps were, in average, 6.7 ± 1.1 times more effective in detecting target species. Overall, few site-specific covariates revealed significant effects on mesocarnivore detectability. Camera traps were a more efficient method for detecting mesocarnivores and estimating their occurrence when compared to hair snares. To improve hair snares’ low detection probabilities, we suggest increasing the number of sampling occasions and the frequency at which hair snares are checked. With some refinements to increase detection rates and the success of genetic identification, hair-snaring methods may be valuable for providing deeper insights into population parameters, attained through adequate analysis of genetic information, that is not possible with camera traps.
Caragiulo A., Kang Y., Rabinowitz S., Dias-Freedman I., Loss S., Zhou X. W., Bao W. D., Amato G. (2015): Presence of the Endangered Amur tiger Panthera tigris altaica in Jilin Province, China, detected using non-invasive genetic techniques. Oryx 49: 632-635.
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China is home to three subspecies of tiger Panthera tigris but there are no estimates of the size of any of the populations. We detected a population of the Endangered Amur tiger Panthera tigris altaica in Hunchun Nature Reserve in Jilin Province using both mitochondrial DNA and nuclear microsatellite loci. Four male and one female tigers were detected, indicating the potential for a small breeding group. However, genetic diversity was low overall, with six loci showing a heterozygote deficiency and a mean of 2.55 alleles per locus. This study is the first estimate of the wild Amur tiger population in China to use non-invasive techniques, and the presence of a female tiger indicates this is a potentially viable population. We provide baseline genetic diversity estimates to support monitoring of the population. The small number of tiger scats located indicates the importance of continuing the current conservation efforts for this tiger subspecies in Hunchun Nature Reserve. Such efforts include reducing poaching of tigers and their prey, and implementation of management plans to encourage the persistence and recovery of tigers in this area.
Kilshaw K., Johnson P. J., Kitchener A. C., Macdonald D. W. (2015): Detecting the elusive Scottish wildcat Felis silvestris silvestris using camera trapping. Oryx 49: 207-215.
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Population monitoring is important for conservation management but difficult to achieve for rare, cryptic species. Reliable information about the Critically Endangered Scottish wildcat Felis silvestris silvestris is lacking because of difficulties in morphological and genetic identification, resulting from extensive hybridization with feral domestic cats Felis catus. We carried out camera-trap surveys in the Cairngorms National Park, UK, to examine the feasibility of camera trapping, combined with a pelage identification method, to monitor Scottish wildcats. Camera trapping detected individually identifiable wildcats. Of 13 individual wild-living cats, four scored as wildcats based on pelage characters and the rest were wildcat × domestic cat hybrids. Spatially explicit capture–recapture density estimation methods generated a density of wild-living cats (wildcats and hybrids) of 68.17 ± SE 9.47 per 100 km2. The impact of reducing trapping-grid size, camera-trap numbers and survey length on density estimates was investigated using spatially explicit capture–recapture models. Our findings indicate camera trapping is more effective for monitoring wildcats than other methods currently used and capture success could be increased by using bait, placing camera stations ⩽ 1.5 km apart, increasing the number of camera stations, and surveying for 60–70 days. This study shows that camera trapping is effective for confirming the presence of the wildcat in potential target areas for conservation management.
Kluever B. M., Gese E. M., Dempsey S. J. (2015): The influence of road characteristics and species on detection probabilities of carnivore faeces. Wildlife Research 42: 75-82.
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Determining reliable estimates of carnivore population size and distributions are paramount for developing informed conservation and management plans. Traditionally, invasive sampling has been employed to monitor carnivores, but non-invasive sampling has the advantage of not needing to capture the animal and is generally less expensive. Faeces sampling is a common non-invasive sampling technique and future use is forecasted to increase due to the low costs and logistical ease of sampling, and more advanced techniques in landscape and conservation genetics. For many species, faeces sampling often occurs on or alongside roads. Despite the commonality of road-based faeces sampling, detectability issues are often not addressed. We sought to test whether faeces detection probabilities varied by species – coyote (Canis latrans) versus kit fox (Vulpes macrotis) – and to test whether road characteristics influenced faeces detection probabilities. We placed coyote and kit fox faeces along roads, quantified road characteristics, and then subsequently conducted ‘blind’ road-based faeces detection surveys in Utah during 2012 and 2013. Technicians that surveyed the faeces deposition transects had no knowledge of the locations of the placed faeces. Faeces detection probabilities for kit foxes and coyotes were 45% and 74%, respectively; larger faeces originated from coyotes and were more readily detected. Misidentification of placed faeces was rare and did not differ by species. The width of survey roads and the composition of a road’s surface influenced detection probabilities. We identified factors that can influence faeces detection probabilities. Not accounting for variable detection probabilities of different species or not accounting for or reducing road-based variables influencing faeces detection probabilities could hamper reliable counts of mammalian faeces, and could potentially reduce precision of population estimates derived from road-based faeces deposition surveys. We recommend that wildlife researchers acknowledge and account for imperfect faeces detection probabilities during faecal sampling. Steps can be taken during study design to improve detection probabilities, and during the analysis phase to account for variable detection probabilities.
Rodgers T. W., Mock K. E. (2015): Drinking water as a source of environmental DNA for the detection of terrestrial wildlife species. Conservation Genetics Resources 7: 693-696.
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Use of environmental DNA for wildlife species detection is a field of research that has seen rapid growth in recent years, however, the majority of research to date has been focused on aquatic species. Here, we propose and test a novel source for the detection of terrestrial species with environmental DNA: drinking water from watering holes and wildlife water developments. We hypothesized that when terrestrial animals drink from a water source, DNA from saliva and buccal cells is shed and can be isolated for species identification. We tested this hypothesis in a pilot study by filtering drinking water supplied to coyotes (Canis latrans) at a captive coyote research facility. DNA was successfully extracted from filters, amplified by the polymerase chain reaction, and sequenced, and sequences were positively identified as belonging to coyotes. We believe this environmental DNA based approach holds great promise for the detection of terrestrial species of conservation concern.
Rodrigues D. C., Simões L., Mullins J., Lampa S., Mendes R. C., Fernandes C., Rebelo R., Santos-Reis M. (2015): Tracking the expansion of the American mink (Neovison vison) range in NW Portugal. Biological Invasions 17: 13-22.
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Invasive in many European countries, the American mink (Neovison vison) was introduced in Portugal in the late 1980’s, presumably escaping from Spanish fur farms close to the border. In spite of the biological richness of the invaded area, no study ever addressed the evolution of the invasion process. We aimed to investigate the current distribution and status of the mink in NW Portugal and discuss some contributing factors to explain the rate of invasion. We detected mink presence using floating rafts as footprint tracking devices, and scats as a molecular tool aiding in species identification. Results demonstrate a clear range expansion southwards, with mink already occupying most of the region’s hydrographic basins. After a first phase of slow expansion (55 km in 20 years), mink seems to have expanded its range quite rapidly in only 2 years (45 km). The initial delay could be due to local thriving otter populations, whereas the recent establishment of red swamp crayfish (Procambarus clarkii) in the area could be a plausible explanation for the acceleration in the mink’s expansion. Being a key food resource, crayfish may be playing an important role as an expansion facilitator. Mink eradication is probably no longer feasible since well established populations near the border continue to function as sources for the Portuguese population. Therefore, a control program should start immediately in the NW region, preferably in conjunction with Spanish authorities.
Glen A. S., Anderson D., Veltman C. J., Garvey P. M., Nichols M. (2016): Wildlife detector dogs and camera traps: a comparison of techniques for detecting feral cats. New Zealand Journal of Zoology 43: 127-137.
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A major challenge in controlling overabundant wildlife is monitoring their populations, particularly as they decline to very low density. Camera traps and wildlife detector dogs are increasingly being used for this purpose. We compared the cost-effectiveness of these two approaches for detecting feral cats (Felis catus) on two pastoral properties in Hawke’s Bay, North Island, New Zealand. One property was subject to intensive pest removal, while the other had no recent history of pest control. Camera traps and wildlife detector dogs detected cats at similar rates at both sites. The operating costs of each method were also comparable. We identify a number of advantages and disadvantages of each technique, and suggest priorities for further research.
Seymour A. C., Dale J., Hammill M., Halpin P. N., Johnston D. W. (2017): Automated detection and enumeration of marine wildlife using unmanned aircraft systems (UAS) and thermal imagery. Scientific Reports 7: 45127.
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Estimating animal populations is critical for wildlife management. Aerial surveys are used for generating population estimates, but can be hampered by cost, logistical complexity, and human risk. Additionally, human counts of organisms in aerial imagery can be tedious and subjective. Automated approaches show promise, but can be constrained by long setup times and difficulty discriminating animals in aggregations. We combine unmanned aircraft systems (UAS), thermal imagery and computer vision to improve traditional wildlife survey methods. During spring 2015, we flew fixed-wing UAS equipped with thermal sensors, imaging two grey seal (Halichoerus grypus) breeding colonies in eastern Canada. Human analysts counted and classified individual seals in imagery manually. Concurrently, an automated classification and detection algorithm discriminated seals based upon temperature, size, and shape of thermal signatures. Automated counts were within 95–98% of human estimates; at Saddle Island, the model estimated 894 seals compared to analyst counts of 913, and at Hay Island estimated 2188 seals compared to analysts’ 2311. The algorithm improves upon shortcomings of computer vision by effectively recognizing seals in aggregations while keeping model setup time minimal. Our study illustrates how UAS, thermal imagery, and automated detection can be combined to efficiently collect population data critical to wildlife management.
Suter S. M., Giordano M., Nietlispach S., Apollonio M., Passilongo D. (2017): Non-invasive acoustic detection of wolves. Bioacoustics 26: 237-248.
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Monitoring wolves (Canis lupus) is a difficult and often expensive task due to high mobility, pack dynamic, shyness and nocturnal activity of this species. Wolves communicate acoustically through howling, within pack and with packs of the neighbourhood. A wolf howl is a low-frequency vocalization that can be transmitted over long distances and thus it can be used for monitoring. Elicited howling survey is a current method to monitor wolves in different areas all over the world. Elicited howling, however, may be invasive to residential wolf packs and could create possible negative reactions from the human population. Here we show that it is possible to detect wolves by recording spontaneous howling events. We measured the sound pressure level of wolf howls by captive individuals and we further found that elicited howling may be recorded and clearly identified up to a distance of 3 km. We finally conducted a non-invasive acoustic detection of wolves in a free-ranging population. The use of passive sound recorders may provide a powerful non-invasive tool for future wolf monitoring and could help to establish sustainable management plans for this species.
Azevedo F. C., Lemos F. G., Freitas‐Junior M. C., Rocha D. G., Azevedo F. C. C. (2018): Puma activity patterns and temporal overlap with prey in a human‐modified landscape at Southeastern Brazil. Journal of Zoology 305: 246-255.
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Animal activity patterns correspond to the individual diel cycle time and is an important attribute of species coexistence in ecological communities. However, activity patterns of most Neotropical species are still poorly understood. Based on an 8-year camera-trapping survey conducted between 2009 and 2017, we evaluated puma (Puma concolor) activity patterns in a human-modified landscape in Southeastern Brazil. Our objectives were to determine the activity pattern of pumas and to verify the influence of main prey species and anthropogenic factors on their behavior. We categorized activity patterns of all assessed species based on the proportion of independent records during night and day times. We tested for sex differences in activity patterns of pumas, and measured their overlap with most consumed prey, people, cattle and domestic dogs. Our results suggested that males engaged in mostly nocturnal behavior while females were active both at night and day hours. Pumas exhibited higher coefficient of overlapping with prey species that were most often included in their diet, suggesting that prey availability might influence puma activity or that pumas opportunistically prey upon species with similar activity pattern. Female pumas seem to be more exposed to anthropogenic threats due to higher activity pattern overlap with people and domestic dogs. Our findings provide insights into puma-prey temporal behavior, highlighting the relevance of intrasexual dissimilarity in the activity patterns of a top predator living in a disturbed landscape.
Anabalón L., Encina‐Montoya F., Sánchez P., Solano J., Benavente F., Guiñez B., Olivares F., Oberti C., Vega R. (2019): High‐resolution melting of the cytochrome B gene in fecal DNA: A powerful approach for fox species identification of the Lycalopex genus in Chile. Ecology and Evolution 9: 7448-7454.
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Easy, economic, precise species authentication is currently necessary in many areas of research and diagnosis in molecular biology applied to conservation studies of endangered species. Here, we present a new method for the identification of three fox species of the Lycalopex genus in Chile. We developed an assay based on high‐resolution melt analysis of the mitochondrial cytochrome B gene, allowing a simple, low cost, fast, and accurate species determination. To validate the assay applicability for noninvasive samples, we collected fecal samples in the Atacama Desert, finding unexpectedly one species outside of its known distribution range. We conclude that the assay has a potential to become a valuable tool for a standardized genetic monitoring of the Lycalopex species in Chile.
Franklin T. W., McKelvey K. S., Golding J. D., Mason D. H., Dysthe J. C., Pilgrim K. L., Squires J. R., Aubry K. B., Long R. A., Greaves S. E., Raley C. M. (2019): Using environmental DNA methods to improve winter surveys for rare carnivores: DNA from snow and improved noninvasive techniques. Biological Conservation 229: 50-58.
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The management of rare species is a conservation priority worldwide, but this task is made difficult by detection errors in population surveys. Both false positive (misidentification) and false negative (missed detection) errors are prevalent in surveys for rare species and can affect resulting inferences about their population status or distribution. Environmental DNA (eDNA)—DNA shed from an organism in its environment—coupled with quantitative PCR (qPCR) analyses, has become a reliable and extremely sensitive mean for identifying rare species in aquatic systems. Due to the demonstrated effectiveness of these methods, we tested their efficacy in surveys for rare species in terrestrial settings to reduce detection errors for three rare forest carnivores of conservation concern: Canada lynx (Lynx canadensis), fisher (Pekania pennanti), and wolverine (Gulo gulo). We specifically investigated our ability to reliably: 1) identify species directly from snow samples collected within tracks; 2) identify species by collecting snow in locations where an animal had been photographed; and 3) identify species from hair samples collected during the summer after being deployed throughout the winter (i.e., overwinter surveys). Our findings indicated that qPCR assays can effectively detect DNA of all three species, including from snow-track surveys, snow collected at camera stations, and overwinter samples that failed to amplify with conventional PCR techniques. All results indicate that the sources of targeted DNA collection provided adequate quantities of DNA for robust species detection. We suggest that using qPCR methods to detect DNA has the potential to revolutionize winter surveys for rare species in terrestrial settings by reducing or eliminating misidentifications and missed detections.
Kinoshita G., Yonezawa S., Murakami S., Isagi Y. (2019): Environmental DNA collected from snow tracks is useful for identification of mammalian species. Zoological Science 36: 198-207.
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Noninvasive genetic analysis is being used increasingly in field surveys. However, detecting large and middle-sized mammals, such as Carnivora species, using noninvasive samples, such as scat or hair, is time- and labor-intensive due to their low densities and elusive behaviors. As snow tracks are the most frequently encountered natural signs of terrestrial mammals in winter, we employed several methods to recover environmental DNA (eDNA) from snow tracks. We performed both DNA metabarcoding and Sanger sequence analyses, in combination with universal primers on the mitochondrial 12S rRNA gene for mammals and taxon-specific primers on the mitochondrial NADH dehydrogenase subunit 2 gene for Martes species (martens and sables in Mustelidae). Snow samples of four Martes melampus tracks, one Cervus nippon track, one Vulpes vulpes track, and the track of an unidentified Carnivora species were collected from a snowfall area in Kyoto, Japan, in February 2018. Regarding DNA metabarcoding analyses, the sequences of three Carnivora species (M. melampus, V. vulpes, and Canis lupus familiaris) and a deer (C. nippon) were obtained from their respective snow tracks. Using Sanger sequencing, eDNA on snow tracks was recovered at the species level except for M. melampus using universal primers, while eDNA of M. melampus was sequenced using Martes-specific primers. Snow track surveys in combination with eDNA techniques could dramatically improve the efficiency of monitoring and conservation of mammals.
Garland L., Crosby A., Hedley R., Boutin S., Bayne E. (2020): Acoustic vs. photographic monitoring of gray wolves (Canis lupus): a methodological comparison of two passive monitoring techniques. Canadian Journal of Zoology 98: 219-228.
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Remote camera traps are often used in large-mammal research and monitoring programs because they are cost-effective, allow for repeat surveys, and can be deployed for long time periods. Statistical advancements in calculating population densities from camera-trap data have increased the popularity of camera usage in mammal studies. However, drawbacks to camera traps include their limited sampling area and tendency for animals to notice the devices. In contrast, autonomous recording units (ARUs) record the sounds of animals with a much larger sampling area but are dependent on animals producing detectable vocalizations. In this study, we compared estimates of occupancy and detectability between ARUs and remote cameras for gray wolves (Canis lupus Linnaeus, 1758) in northern Alberta, Canada. We found ARUs to be comparable with cameras in their detectability and occupancy of wolves, despite only operating for 3% of the time that cameras were active. However, combining cameras and ARUs resulted in the highest detection probabilities for wolves. These advances in survey technology and statistical methods provide innovative avenues for large-mammal monitoring that, when combined, can be applied to a broad spectrum of conservation and management questions, provided assumptions for these methods are rigorously tested and met.
O’Gara J. R., Wieder C. A., Mallinger E. C., Simon A. N., Wydeven A. P., Olson E. R. (2020): Efficacy of acoustic triangulation for gray wolves. Wildlife Society Bulletin 44: 351-361.
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Acoustic triangulation is a unique, relatively noninvasive monitoring approach that can inform our understanding of a species’ distribution in time and space. Acoustic triangulation relies on standard triangulation techniques to determine the location of an acoustic event. Howl surveys are frequently used to survey wolves (Canis lupus) and other canids. We evaluated the efficacy of acoustic triangulation for estimating the location of wolves. We measured precision and accuracy of acoustic triangulation using an experimental mock howl survey and field data collected with wild wolves in northern Wisconsin, USA (2014–2018). Precision of acoustic triangulation was similar to triangulation with ground-based radiotelemetry for both pooled data and individual wolves at specific times, although the 2 techniques did not result in similar predicted locations. Distance from the howl source was the most consistently significant factor influencing the efficacy of acoustic triangulation. Error ellipse size was 33 times smaller at distances <1 km. Wind speed also reduced the accuracy of acoustic triangulation for mock howl surveys. Precision for modified howl surveys with wild wolves improved with the number of bearings. We estimated a mean bearing error of 13.2° (±2.1, 95% CI) for single bearings and a maximum distance of 1.76 km (range = 0.96–1.76 km; x = 1.41 km) detection for audible anthropogenic howls. Such information can be applied to howl survey data to generate more fine-scale location information for wolf-pack home sites. Acoustic triangulation of wolves can provide high-quality location information in areas where wolves are not monitored with radiocollars.
Cozzi G., Hollerbach L., Suter S. M., Reiners T. E., Kunz F., Tettamanti F., Ozgul A. (2021): Eyes, ears, or nose? Comparison of three non-invasive methods to survey wolf recolonisation. Mammalian Biology 101: 881-893.
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The development and use of cost-effective and appropriate survey methods to assess species distribution and to monitor range expansion and contraction of wild populations is crucial due to the limited financial resources for conservation. Of particular importance, yet little studied, is the ability to collect information before a wild population is well established, i.e. at the early stages of recolonisation. During 2018 and 2019, we used camera traps, audio recorders, and scat detection dogs simultaneously to investigate composition, detection probability, and territorial extent of a pack of wolves in the Swiss Alps. We compared the efficacy of these survey methods by assessing sampling effort, data obtained, and costs. We show that, under the presented setup, camera traps and scat detection dogs substantially outperformed audio recorders in detecting wolves, representing the packs’ territorial extent, and revealing the number of adult wolves. The detection dogs did not detect pups but, unlike the other methods, allowed the identification of single individuals. The use of four camera traps during 13 weeks, a 24-km-long transect walked with the detection dog, or the use of one audio recorder during 148 weeks were necessary to obtain a comparable wolf detection probability. Our results show that no single method was able to return all information that we hoped to collect. Comprehensive and cost-effective information was best obtained by combining data from camera traps and detection dogs. We suggest both methods to be simultaneously used to successfully investigate wolf recolonisation into historical range.
Schenekar T., Karrer M., Karner I., Weiss S. J. (2021): Non-invasive diagnostic PCRs for rapid detection of golden jackal, red fox, and gray wolf/domestic dog and application to validate golden jackal presence in Styria, Austria. European Journal of Wildlife Research 67: 42.
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Human-predator conflicts are frequently caused by livestock and/or game depredation. The golden jackal’s (Canis aureus) range expansion in Europe, as well as the recent re-expansion of several gray wolf (Canis lupus) populations, might increase risk of such conflicts. In Austria, golden jackal presence has been increasing since the 1990s including reports of wildlife and livestock kills, frequently occurring in the provinces Styria and Burgenland. We developed a rapid, two-step genetic screening protocol to (1) detect canid mtDNA from non-invasively collected samples like swabs from kills using diagnostic PCRs, and (2) assign this DNA to red fox (Vulpes vulpes), golden jackal, or gray wolf/dog. To monitor golden jackal presence in the region, a total of 167 signs of presence were collected over a period of 30 months throughout the Styrian province. Among these, 14 non-invasive genetic samples (13 swabs from kill sites and one scat) were screened with the developed protocol. Four of these samples revealed golden jackal mtDNA and six samples red fox mtDNA. The developed genetic screening protocol represents a quick and inexpensive method to assess canid presence, e.g., at kill sites, and therefore possesses high value for the conservation and wildlife management community.
Sentilles J., Vanpe C., Quenette P. Y. (2021): Benefits of incorporating a scat-detection dog into wildlife monitoring: a case study of Pyrenean brown bear. Journal of Vertebrate Biology 69: 20096.
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In the Pyrenees, brown bear population abundance is estimated from non-invasive genetic analyses of scat and hair samples. Although such analyses are highly beneficial for population monitoring and research, it can be especially difficult for humans to locate bear scats in the field. To address this, we have incorporated a dog (trained from an early age to detect bear scats) into these efforts since 2014. Here, we compared the effectiveness of the scat-detection dog/handler and human-only teams to locate bear scats using our work in the Pyrenees as a case study. A species validation was systematically carried out, either genetically or visually using a microscope, based on the presence of bear hair, for all scats collected from 2010 to 2019. From 2014 to 2019, the use of the dog/handler team in addition to human-only teams increased the average number of bear scats collected annually by four times in comparison with the 2010-2013 period when only humans were searching for scats. This temporal augmentation could not be explained by the increase in bear population size. From 2014 to 2019, the annual percentage of outings during which at least one bear scat was found was 17 times higher for the dog than for humans. The use of the dog also resulted indirectly in a better genotyping success and genetic identification of more individuals due to a larger choice of viable samples that could be sent to the molecular laboratory, as well as a larger number of cub scats detected by the dog. We found that even the use of a single scat-detection dog can greatly improve the efficiency of detecting target scats in challenging monitoring conditions.
Wilcox T. M., Caragiulo A., Dysthe J. C., Franklin T. W., Mason D. H., McKelvey K. S., Zarn K. E., Schwartz M. K. (2021): Detection of jaguar (Panthera onca) from genetic material in drinking water. Frontiers in Ecology and Evolution 9: 613200.
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Jaguar (Panthera onca) are of conservation concern and occur at very low densities in the northern portion of their range in northern Mexico and the southwestern United States. Environmental DNA sampling to detect genetic material from drinking water may be an effective approach for jaguar detection in these arid landscapes. Here we develop a qPCR assay for the detection of jaguar mitochondrial DNA, show that large quantities of DNA (mean 66,820 copies/L) can be found in the drinking water of captive animals, and observe detectable levels of DNA (80 copies/L) in a wild habitat with known jaguar populations. We suggest that environmental DNA sampling may represent a useful, complementary sampling tool for detection of rare jaguars, although effective application would require careful consideration of DNA persistence time in the environment.
Wang H., Zhong J., Xu Y., Luo G., Jiang B., Hu Q., Lin Y., Ran J. (2022): Automatically detecting the wild giant panda using deep learning with context and species distribution model. Ecological Informatics 72: 101868.
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The giant panda is a flagship species in ecological conservation. The infrared camera trap is an effective tool for monitoring the giant panda. Images captured by infrared camera traps must be accurately recognized before further statistical analyses can be implemented. Previous research has demonstrated that spatiotemporal and positional contextual information and the species distribution model (SDM) can improve image detection accuracy, especially for difficult-to-see images. Difficult-to-see images include those in which individual animals are only partially observed and it is challenging for the model to detect those individuals. By utilizing the attention mechanism, we developed a unique method based on deep learning that incorporates object detection, contextual information, and the SDM to achieve better detection performance in difficult-to-see images. We obtained 1169 images of the wild giant panda and divided them into a training set and a test set in a 4:1 ratio. Model assessment metrics showed that our proposed model achieved an overall performance of 98.1% in mAP0.5 and 82.9% in recall on difficult-to-see images. Our research demonstrated that the fine-grained multimodal-fusing method applied to monitoring giant pandas in the wild can better detect the difficult-to-see panda images to enhance the wildlife monitoring system.
Gil-Sánchez J. M., Herrera-Sánchez F. J., Rodríguez-Siles J., Díaz-Portero M. Á., Arredondo Á., Sáez J. M., Álvarez B., Cancio I., de Lucas J., McCain E., Pérez J., Valenzuela G., Valderrama J. M., Sánchez-Cerdá M., Lahlafi T., Martin J. M., Burgos T., Jimenez J., Qninba A., Virgós E. (2023): Applications of non-intrusive methods to study the sand cat: a field study in the Sahara Desert. European Journal of Wildlife Research 69: 20.
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Surveys based on indirect signs and camera trapping are two non-invasive methods extensively used for monitoring elusive mammals. Both approaches can be useful to obtain key information on wildlife in remote areas, since they may allow for the logistically viable design of optimal field frameworks. The sand cat (Felis margarita) is a feline that inhabits the Sahara Desert, the Arabian Peninsula, and western Asian deserts. Its basic ecology is poorly known and the status and impacts of threats are difficult to assess. Some local population declines have been detected, and more research is needed. Based on field surveys carried out in the Atlantic Sahara, we have evaluated the applications of both methods to study this species. Our results show that (a) camera trapping provided reliable data on several key aspects of its ecology, (b) walking surveys to collect feces for molecular data failed completely, and (c) for footprints, identification problems and the marked effects of the absence of optimal substrates and the prevalence of wind are relevant handicaps. Beyond this evaluation, we provide for the first time some key aspects of the ecology of sand cats in the Sahara Desert, including habitat selection, density, diel activity, and predator–prey relationships.
Koda S. A., McCauley M., Farrell J. A., Duffy I. J., Duffy F. G., Loesgen S., Whilde J., Duffy D. J. (2023): A novel eDNA approach for rare species monitoring: Application of long-read shotgun sequencing to Lynx rufus soil pawprints. Biological Conservation 287: 110315.
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Environmental DNA (eDNA) sampling is a relatively new technique that has been employed in biodiversity surveys around the world. Environmental DNA can be an effective, non-invasive method of identifying the presence of target host species. Furthermore, advances in DNA deep sequencing technologies are enabling in-depth information to be recovered from eDNA. Here we report the development of a bobcat (Lynx rufus) species-specific probe-based qPCR assay for eDNA studies, which was validated on wild samples and those from a bobcat housed at the Jacksonville Zoo in Florida. Furthermore, we show that long-read shotgun sequencing of eDNA extracted from pawprint soil samples, using an Oxford Nanopore Technologies MinION, could successfully detect bobcat DNA, including enabling correct species level identification and phylogenetic placement within regionally distanced bobcats. This was all achieved without utilizing any DNA enrichment approaches. The long read shotgun sequencing simultaneously recovered genetic information from microbes known to be part of the bobcat microbiome, indicating that potential health-status-related microbial information can be obtained alongside wildlife eDNA. This study revealed that non-targeted (no metabarcoding or enrichment) long-read shotgun sequencing of eDNA samples can be sufficient for species identification, phylogenetic analyses, and population genetics applications. This paves the way for the rapid deployment of eDNA approaches for any species of interest, without requiring laborious development of targeted approaches, thereby increasing the ease and utility of eDNA research for endangered species conservation and management.
Tucker J. M., King C., Lekivetz R., Murdoch R., Jewell Z. C., Alibhai S. K. (2024): Development of a non-invasive method for species and sex identification of rare forest carnivores using footprint identification technology. Ecological Informatics 79: 102431.
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Many wildlife species have sex specific habitat requirements. Due to the unique requirements for birthing and raising offspring, female reproductive habitat is often a limiting factor for a population and has been identified as a priority for conservation. Therefore, the ability to detect where females persist on the landscape and identify these potential reproductive areas is essential in creating effective conservation strategies. Here we describe the development of a non-invasive method to identify species and sex based on track images collected at track plate stations using footprint identification technology (FIT). We developed this technique using data from the southern Sierra Nevada fisher (Pekania pennanti) population and a co-occurring species of conservation concern the Pacific marten (Martes caurina). We coupled track plate footprints with non-invasive genetic samples and camera trap images to create a reference dataset of known species for fisher and marten and known sex for fisher. We used FIT to geo-reference 167 marten and 367 fisher tracks (34 males, 27 females) using 7 landmark points and then extracted 124 morphometric variables (distances, angles, and areas) for use in identifying species and sex for fisher using linear discriminant analyses. Using a single variable, we found species classification accuracy >99% in distinguishing fisher from marten. For fisher sex identification our most parsimonious model consisting of only 2 variables achieved an accuracy of 94.0% for the training set and 89.4% for the test set. We also report a method to quantify classification uncertainty for each track. This method provides a rapid, cost effective, entirely non-invasive method to accurately identify sex that can easily be implemented in field studies.
Lauer A., Alame S., Calvillo J. A., Gaytan M. E., Juarez J. R., Lopez J. J., Medina K., Owens I., Romero A. Sheppard J. (2025): Detecting the endangered San Joaquin kit fox (Vulpes macrotis mutica) and other canine species in Kern County, CA: Applying a non-invasive PCR-based method to four case study sites. Conservation 5: 8.
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The endangered San Joaquin kit fox (SJKF) (Vulpes macrotis mutica), which is endemic to the San Joaquin Valley in California, has lost most of its natural habitat due to urban sprawl and change in land use over time. Many studies have been conducted to restore and protect the remaining habitat, involving presence/absence surveys prior to urban development using camera monitoring, tracking dogs, tracking plates, spotlighting, and trapping. While these traditional methods work well, they can be invasive, expensive, labor-intensive, and require permits to perform. In our study, we used a non-invasive method based on DNA extraction from scat collected in the environment, followed by a diagnostic Polymerase Chain Reaction (PCR)-based approach on mitochondrial DNA fragments and investigated the presence of the SJKF on four case study sites that shared a high SJKF habitat suitability index but are under the threat of development. We found that the diagnostic PCR was able to accurately differentiate between different canids present at the sites, in a time- and cost-effective manner. Including this non-invasive method in the Department of Fish and Wildlife’s standardized recommendations for survey methods would help to improve future environmental assessments for SJKF populations in the Central Valley of California.
CETACEANS
Foote A. D., Thomsen P. F., Sveegaard S., Wahlberg M., Kielgast J., Kyhn L. A., Salling A. B., Galatius A., Orlando L., Gilbert M. T. P. (2012): Investigating the potential use of environmental DNA (eDNA) for genetic monitoring of marine mammals. Plos One 7: e41781.
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The exploitation of non-invasive samples has been widely used in genetic monitoring of terrestrial species. In aquatic ecosystems, non-invasive samples such as feces, shed hair or skin, are less accessible. However, the use of environmental DNA (eDNA) has recently been shown to be an effective tool for genetic monitoring of species presence in freshwater ecosystems. Detecting species in the marine environment using eDNA potentially offers a greater challenge due to the greater dilution, amount of mixing and salinity compared with most freshwater ecosystems. To determine the potential use of eDNA for genetic monitoring we used specific primers that amplify short mitochondrial DNA sequences to detect the presence of a marine mammal, the harbor porpoise, Phocoena phocoena, in a controlled environment and in natural marine locations. The reliability of the genetic detections was investigated by comparing with detections of harbor porpoise echolocation clicks by static acoustic monitoring devices. While we were able to consistently genetically detect the target species under controlled conditions, the results from natural locations were less consistent and detection by eDNA was less successful than acoustic detections. However, at one site we detected long-finned pilot whale, Globicephala melas, a species rarely sighted in the Baltic. Therefore, with optimization aimed towards processing larger volumes of seawater this method has the potential to compliment current visual and acoustic methods of species detection of marine mammals.
Ponce D., Thode A. M., Guerra M., Urbán R. J., Swartz S. (2012): Relationship between visual counts and call detection rates of gray whales (Eschrichtius robustus) in Laguna San Ignacio, Mexico. The Journal of the Acoustical Society of America 131: 2700-2713.
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Daily acoustic calling rates of Eastern North Pacific (ENP) gray whales were measured on 6 days during 1 mo of their 2008 breeding season in the sheltered coastal lagoon of Laguna San Ignacio in Baja California, Mexico. Visual counts of whales determined that the numbers of single animals in the lower lagoon more than tripled over the observation period. All call types showed production peaks in the early morning and evening with minimum rates generally detected in the early afternoon. For four of the five observation days, the daily number of “S1”-type calls increased roughly as the square of the number of the animals in the lower lagoon during both daytime and nighttime. This relationship persisted when raw call counts were adjusted for variations in background noise level, using a simple propagation law derived from empirical measurements. The one observation day that did not fit the square-law relationship occurred during a week when the group size in the lagoon increased rapidly. These results suggest that passive acoustic monitoring does not measure gray whale group size directly but monitors the number of connections in the social network, which rises as roughly M2/2 for a group size M.
Matthews L. P., McCordic J. A., Parks S. E. (2014): Remote acoustic monitoring of North Atlantic right whales (Eubalaena glacialis) reveals seasonal and diel variations in acoustic behavior. Plos One 9: e91367.
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Remote acoustic monitoring is a non-invasive tool that can be used to study the distribution, behavior, and habitat use of sound-producing species. The North Atlantic right whale (Eubalaena glacialis) is an endangered baleen whale species that produces a variety of stereotyped acoustic signals. One of these signals, the “gunshot” sound, has only been recorded from adult male North Atlantic right whales and is thought to function for reproduction, either as reproductive advertisement for females or as an agonistic signal toward other males. This study uses remote acoustic monitoring to analyze the presence of gunshots over a two-year period at two sites on the Scotian Shelf to determine if there is evidence that North Atlantic right whales may use these locations for breeding activities. Seasonal analyses at both locations indicate that gunshot sound production is highly seasonal, with an increase in the autumn. One site, Roseway West, had significantly more gunshot sounds overall and exhibited a clear diel trend in production of these signals at night. The other site, Emerald South, also showed a seasonal increase in gunshot production during the autumn, but did not show any significant diel trend. This difference in gunshot signal production at the two sites indicates variation either in the number or the behavior of whales at each location. The timing of the observed seasonal increase in gunshot sound production is consistent with the current understanding of the right whale breeding season, and our results demonstrate that detection of gunshots with remote acoustic monitoring can be a reliable way to track shifts in distribution and changes in acoustic behavior including possible mating activities.
Baker C. S., Steel D., Nieukirk S., Klinck H. (2018): Environmental DNA (eDNA) from the wake of the whales: Droplet digital PCR for detection and species identification. Frontiers in Marine Science 5: 133.
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Genetic sampling for identification of species, subspecies or stock of whales, dolphins and porpoises at sea remains challenging. Most samples have been collected with some form of a biopsy dart requiring a close approach of a vessel while the individual is at the surface. Here we have adopted droplet digital (dd)PCR technology for detection and species identification of cetaceans using environmental (e)DNA collected from seawater. We conducted a series of eDNA sampling experiments during 25 encounters with killer whales, Orcinus orca, in Puget Sound (the Salish Sea). The regular habits of killer whales in these inshore waters allowed us to locate pods and collect seawater, at an initial distance of 200 m and at 15-min intervals, for up to 2 h after the passage of the whales. To optimize detection, we designed a set of oligonucleotide primers and probes to target short fragments of the mitochondrial (mt)DNA control region, with a focus on identification of known killer whale ecotypes. We confirmed the potential to detect eDNA in the wake of the whales for up to 2 h, despite movement of the water mass by several kilometers due to tidal currents. Re-amplification and sequencing of the eDNA barcode confirmed that the ddPCR detection included the “southern resident community” of killer whales, consistent with the calls from hydrophone recordings and visual observations.
Gray P. C., Bierlich K. C., Mantell S. A., Friedlaender A. S., Goldbogen J. A., Johnston D. W. (2019): Drones and convolutional neural networks facilitate automated and accurate cetacean species identification and photogrammetry. Methods in Ecology and Evolution 10: 1490-1500.
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The flourishing application of drones within marine science provides more opportunity to conduct photogrammetric studies on large and varied populations of many different species. While these new platforms are increasing the size and availability of imagery datasets, established photogrammetry methods require considerable manual input, allowing individual bias in techniques to influence measurements, increasing error and magnifying the time required to apply these techniques. Here, we introduce the next generation of photogrammetry methods utilizing a convolutional neural network to demonstrate the potential of a deep learning-based photogrammetry system for automatic species identification and measurement. We then present the same data analysed using conventional techniques to validate our automatic methods. Our results compare favorably across both techniques, correctly predicting whale species with 98% accuracy (57/58) for humpback whales, minke whales, and blue whales. Ninety percent of automated length measurements were within 5% of manual measurements, providing sufficient resolution to inform morphometric studies and establish size classes of whales automatically. The results of this study indicate that deep learning techniques applied to survey programs that collect large archives of imagery may help researchers and managers move quickly past analytical bottlenecks and provide more time for abundance estimation, distributional research, and ecological assessments.
Tang Y., Wu Y., Liu K., Li J., Li H., Wang Q., Yu J., Xu P. (2019): Investigating the distribution of the Yangtze finless porpoise in the Yangtze River using environmental DNA. Plos One 14: e0221120.
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Determining the distribution of the Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis, YFP) in the Yangtze River has to date relied on traditional visual and counting methods, but such field surveys are time-consuming and expensive. Analyses using environmental DNA (eDNA) to investigate the presence and range of endangered aquatic species have proven to be more economical and effective detection methods, and are a non-invasive approach to sampling. A challenge of relying on eDNA for YFP monitoring is that the Yangtze River is characterized by high turbidity and a strong current. Here, we used an eDNA-based approach to estimate the presence of YFP at 18 sites in the Yangtze River in August 2017 and at an additional 11 sites in January 2018. At each sampling site, we filtered six 1 L water samples with 5 µm pore size filter paper and quantified the amount of YFP eDNA in each water sample using quantitative real-time polymerase chain reaction (qPCR). In addition, YFP eDNA was successfully detected in locations where we visually observed YFP, as well as in locations where YFP were not observed directly. We found that our eDNA-based method had higher detection rates than traditional field survey methods. Although YFP was visually observed in the Yangtze River in winter, water samples collected during the summer contained significantly higher YFP eDNA than winter water samples. Our results demonstrate the potential effectiveness of eDNA detection methods in determining the distribution of YFP in the Yangtze River.
Caruso F., Dong L., Lin M., Liu M., Gong Z., Xu W., Alonge G., Li S. (2020): Monitoring of a nearshore small dolphin species using passive acoustic platforms and supervised machine learning techniques. Frontiers in Marine Science 7: 267.
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Passive acoustic monitoring (PAM) is increasingly being adopted as a non-invasive method for the assessment of ocean ecological dynamics. PAM is an important sampling approach for acquiring critical information about marine mammals, especially in areas where data are lacking and where evaluations of threats for vulnerable populations are required. The Indo-Pacific humpback dolphin (IPHD, Sousa chinensis) is a coastal species which inhabits tropical and warm-temperate waters from the eastern Indian Ocean throughout Southeast Asia to central China. A new population of this species was recently discovered in waters southwest of Hainan Island, China. An array of passive acoustic platforms was deployed at depths of 10–20 m (the preferred habitat of humpback dolphins), across sites covering more than 100 km of coastline. In this study, we explored whether the acoustic data recorded by the array could be used to classify IPHD echolocation clicks, with the aim of investigating the spatiotemporal patterns of distribution and acoustic behavior of this species. A number of supervised machine learning algorithms were trained to automatically classify echolocation clicks from the different types of short-broadband pulses recorded. The best performance was reported by a cubic support vector machine (Cubic SVM), which was applied to 19,215 5-min recordings (∼4.2 TB), collected over a period of 75 days at six locations. Subsequently, using spectrogram visualization and audio listening, human operators confirmed the presence of clicks within the selected files. Additionally, other dolphin vocalizations (including whistles, buzzes, and burst pulses) and different sound sources (soniferous fishes, snapping shrimps, human activities) were also reported. The detection range of IPHD clicks was estimated using a transmission loss (TL) model and the performance of the trained classifier was compared with data synchronously collected by an acoustic data logger (A-tag). This study demonstrates that the distribution and habitat use of a coastal and resident dolphin species can be monitored over a large spatiotemporal scale, using an array of passive acoustic platforms and a data analysis protocol that includes both machine learning techniques and spectrogram inspection.
Alter S. E., King C. D., Chou E., Chin S. C., Rekdahl M., Rosenbaum H. C. (2022): Using environmental DNA to detect whales and dolphins in the New York Bight. Frontiers in Conservation Science 3: 820377.
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Determining how cetaceans and other threatened marine animals use coastal habitats is critical to the effective conservation of these species. Environmental DNA (eDNA) is an emerging tool that can potentially be used to detect cetaceans over broad spatial and temporal scales. In particular, eDNA may present a useful complementary method for monitoring their presence during visual surveys in nearshore areas, and for co-detecting prey. In conjunction with ongoing visual surveys, we tested the ability of eDNA metabarcoding to detect the presence and identity of cetaceans in the New York Bight (NYB), and to identify fish species (potential prey) present in the area. In almost all cases in which humpback whales and dolphins were visually observed, DNA from these species was also detected in water samples. To assess eDNA degradation over time, we took samples in the same location 15 and 30 min after a sighting in seven instances, and found that eDNA often, but not always, dropped to low levels after 30 min. Atlantic menhaden were detected in all samples and comprised the majority of fish sequences in most samples, in agreement with observations of large aggregations of this important prey species in the NYB. While additional data are needed to better understand how factors such as behavior and oceanographic conditions contribute to the longevity of eDNA signals, these results add to a growing body of work indicating that eDNA is a promising tool to complement visual and acoustic surveys of marine megafauna.
Baille L. M., Zitterbart D. P. (2022): Effectiveness of surface-based detection methods for vessel strike mitigation of North Atlantic right whales. Endangered Species Research 49: 57-69.
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Increasing commercial and recreational use of the world’s oceans has led to growing concerns about vessel and marine mammal encounters. For endangered species such as the North Atlantic right whale Eubalaena glacialis, reducing the number of vessel strikes is key to improving their protection. In this study, we developed an agent-based model to assess the efficacy of thermal imaging systems as a surface-based whale detection method for vessel strike mitigation. We found that the detection range of such systems is the determining factor for their efficacy and needs to be chosen according to vessel characteristics, such as speed and maneuverability. Furthermore, we found that combining large-scale (e.g. protected zones) and small-scale (e.g. on-board detection systems) mitigation strategies increases protection. Finally, technological improvements are needed to achieve reliable detection ranges beyond what is currently possible so that fast and poorly maneuverable vessels such as ultra-large container ships could benefit from on-board detection systems.
Grist E. P., McKinley T. J., Das S., Tregenza T., Jeffries A., Tregenza N. (2022): Estimating cetacean population trends from static acoustic monitoring data using Paired Year Ratio Assessment (PYRA). Plos One 17: e0264289.
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The cetacean conservationist is often faced with evaluating population trends from abundance data that are either sparse or recorded at different times in different years. The presence of diel or seasonal patterns in the data together with unplanned gaps is often problematic. Such data are typical of those obtained from static acoustic monitoring. We present a simple and transparent non-parametric trend evaluation method, ‘Paired Year Ratio Assessment (PYRA)’ that uses only whole days of data wherever they are present in each of successive pairs of periods of 365 days. We provide a quantitative comparison of the performance of PYRA with traditional generalised additive models (GAMS) and nonparametric randomisation tests that require a greater level of skill and experience for both application and interpretation. We conclude that PYRA is a powerful tool, particularly in the context of identifying population trends which is often the main aim of conservation-targeted acoustic monitoring.
Macaulay J., Kingston A., Coram A., Oswald M., Swift R., Gillespie D., Northridge S. (2022): Passive acoustic tracking of the three‐dimensional movements and acoustic behaviour of toothed whales in close proximity to static nets. Methods in Ecology and Evolution 13: 1250-1264.
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Entanglement in net fisheries (static and drift) is the largest known cause of direct anthropogenic mortality to many small cetacean species, including harbour porpoise (Phocoena phocoena), in UK waters. Despite this, little is known about the behaviour of small cetaceans in proximity to nets. We have developed a passive acoustic monitoring (PAM) system for tracking the fine-scale three-dimensional (3D) movements of echolocating cetaceans around actively fishing nets by localising their acoustic clicks. The system consists of two compact four-channel acoustic recorders with sample-synchronised sensor packages that use 3D motion tracking technology to accurately log orientation, depth, water temperature and ambient light level. Two recorders were used in tandem, with each one attached to and floating above the net floatline. The system can be deployed during normal fishing operations by a trained researcher or experienced fisheries observer. Recordings were analysed in PAMGuard software and the 3D positions of echolocating animals in the vicinity of the system were calculated using an acoustic particle filter-based localisation method. We present findings from four deployments in UK waters (each 1–2 days in duration) in which 12 distinct harbour porpoise encounters yielded a sufficient number of detected clicks to track their movements around the net. The tracks show a variety of behaviours, including multiple instances of animals actively foraging in close proximity to the fishing net. We show that a relatively inexpensive PAM system, which is practical to deploy from active fishing vessels, is capable of providing highly detailed data on harbour porpoise behaviour around nets. As harbour porpoises are the one of the most difficult species to localise, this methodology is likely to be suitable for elucidating the behaviour of many other toothed whale species in a variety of situations.
Crowe L. M., Rayment W., Stanley J. A. (2023): If these walls could talk: Investigating bottlenose dolphin habitat use in fiord ecosystems. The Journal of the Acoustical Society of America 154: A276-A276.
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Effective management of protected species requires a comprehensive understanding of their ecology. Within the Te Moana o Atawhenua-Fiordland Marine Area (FMA), Aotearoa-New Zealand, two of the four recognized bottlenose dolphin (Tursiops truncatus) sub-populations are considered to exclusively inhabit discrete fiord systems. Opportunistic sightings outside the Patea-Doubtful and Tamatea-Dusky fiord complexes, however, suggest they occupy a larger space than currently recognized. To investigate the presence of bottlenose dolphins in five neighboring fiord systems, passive acoustic monitoring (PAM) was conducted from February 2022 to November 2023. PAM effort included two instrumentation approaches: F-PODs to continuously detect click trains of odontocetes, and SoundTraps to provide broad spectrum recordings (15 of every 30 min, sampling rate: 96kHz). This study discusses the trade-offs between approaches in terms of cost, recording duration, and data collected. In addition, photo-identification of bottlenose dolphins in these neighboring fiords was used to identify the sub-population of individuals. The results demonstrate that bottlenose dolphins are regularly using fiords that are not formally considered part of their range within the FMA. A greater understanding of the spatial ecology of Fiordland bottlenose dolphin sub-populations necessitates consideration of threats and resources both inside and outside of their namesake fiord complexes.
Hauer C., Nöth E., Barnhill A., Maier A., Guthunz J., Hofer H., Bergler C. (2023): Orca-spy enables killer whale sound source simulation, detection, classification and localization using an integrated deep learning-based segmentation. Scientific Reports 13: 11106.
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Acoustic identification of vocalizing individuals opens up new and deeper insights into animal communications, such as individual-/group-specific dialects, turn-taking events, and dialogs. However, establishing an association between an individual animal and its emitted signal is usually non-trivial, especially for animals underwater. Consequently, a collection of marine species-, array-, and position-specific ground truth localization data is extremely challenging, which strongly limits possibilities to evaluate localization methods beforehand or at all. This study presents ORCA-SPY, a fully-automated sound source simulation, classification and localization framework for passive killer whale (Orcinus orca) acoustic monitoring that is embedded into PAMGuard, a widely used bioacoustic software toolkit. ORCA-SPY enables array- and position-specific multichannel audio stream generation to simulate real-world ground truth killer whale localization data and provides a hybrid sound source identification approach integrating ANIMAL-SPOT, a state-of-the-art deep learning-based orca detection network, followed by downstream Time-Difference-Of-Arrival localization. ORCA-SPY was evaluated on simulated multichannel underwater audio streams including various killer whale vocalization events within a large-scale experimental setup benefiting from previous real-world fieldwork experience. Across all 58,320 embedded vocalizing killer whale events, subject to various hydrophone array geometries, call types, distances, and noise conditions responsible for a signal-to-noise ratio varying from 14.2 dB to 3 dB, a detection rate of 94.0 % was achieved with an average localization error of 7.01. ORCA-SPY was field-tested on Lake Stechlin in Brandenburg Germany under laboratory conditions with a focus on localization. During the field test, 3889 localization events were observed with an average error of 29.19 and a median error of 17.54. ORCA-SPY was deployed successfully during the DeepAL fieldwork 2022 expedition (DLFW22) in Northern British Columbia, with a mean average error of 20.01 and a median error of 11.01 across 503 localization events. ORCA-SPY is an open-source and publicly available software framework, which can be adapted to various recording conditions as well as animal species.
Robinson C. V., Dracott K., Glover R. D., Warner A., Migneault A. (2024): DNA from dives: Species detection of humpback whales (Megaptera novaeangliae) from flukeprint eDNA. Environmental DNA 6: e524.
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Northern British Columbia has been identified as an important habitat for several coastal cetacean species, including humpback whales (Megaptera novaeangliae). This species is listed as being of “Special Concern” under Canada’s Species at Risk Act, partly due to data deficiencies concerning genetic population structure and demographics in British Columbia. Anthropogenic activities threaten North Coast humpback whale populations, with particular concern for the impact of vessel noise, entanglement, and ship strikes. Current methodology (i.e., biopsy sampling) for obtaining cetacean genetic data is invasive, challenging, and costly; therefore, there is an urgency to develop effective and minimally invasive methodologies for efficiently collecting this data. Environmental DNA (eDNA) has been identified as an ideal tool for monitoring the presence and distribution of numerous species within marine ecosystems; however, the feasibility for cetaceans is not yet well established. In this study, we opportunistically collected targeted 1 L seawater eDNA samples from flukeprints when individual humpback whales were observed diving between the years of 2020 and 2022. A total of 93 samples were collected from individual humpback whales identified using a photographic identification catalogue. We successfully detected humpback whale eDNA in 28 samples using novel species-specific qPCR primers (~500 mL of sample), with relatively equal successful detection between immediate (0 days) and delayed (up to 10 days) sample filtration. Here, we have validated a qPCR assay for detecting humpback whale DNA from flukeprints and highlighted the future optimizations required to improve the potential application of flukeprint eDNA for conservation management.
ELEPHANTS
Barnes R. F. W., Beardsley K., Michelmore F., Barnes K. L., Alers M. P. T., Blom A. (1997): Estimating forest elephant numbers with dung counts and a geographic information system. The Journal of Wildlife Management 61: 1384-1393.
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Dung counts are the most practical means of estimating numbers and distribution of forest-dwelling elephants. In the forests of Gabon, which have a sparse human population, the density of elephant dung piles increased with distance from roads. Human influences (roads and density of human habitation) accounted for half the variation in dung-pile density. Ninety-five percent of the dung piles were estimated to occur in the low human density stratum that covers two-thirds of Gabon. We present a new method of estimating the dung-pile population using the gradient of dung density in relation to roads. Estimates of the gradient were combined with estimates from a geographic information system (GIS) of the area of forest in bands at different distances (e.g., 0-5, 5-10 km) from roads. This process gave an estimate of the dung-pile population for the whole forest zone; the standard error and confidence limits were found by bootstrapping. We argue that estimates of forest elephant abundance in central Africa will be both more accurate and more precise if one accounts for the gradient. Simulation showed that the optimum sample for Gabon is 40 transects, each 5 km in length.
Payne K. B., Thompson M., Kramer L. (2003): Elephant calling patterns as indicators of group size and composition: the basis for an acoustic monitoring system. African Journal of Ecology 41: 99-107.
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The paper gives evidence that the vocal activity of elephants varies with group size, composition and reproductive status, and that elephants’ calling patterns could therefore provide the basis for a remote monitoring system. We examined a 3-week set of array-based audio recordings of savanna elephants (Loxodonta africana), searching for diagnostic acoustic parameters. An acoustic array made it possible to locate recorded sounds and attribute the calls to particular elephants or elephant groups. Simultaneous video recordings made it possible to document visible behaviour and roughly correlate it with vocalizations. We compared several measures of call density in elephant groups containing up to 59 individuals, and found that rates of calling increased with increasing numbers of elephants. We divided all call events into three structural types (single-voice low-frequency calls, multiple-voice clustered low-frequency calls, and single-voice high frequency calls), and found that the incidence of these varies predictably with group composition. These results suggest the value of a network of listening systems in remote areas for the collection of information on elephant abundance and population structure.
Wood J. D., O’Connell-Rodwell C. E., Klemperer S. L. (2005): Using seismic sensors to detect elephants and other large mammals: a potential census technique. Journal of Applied Ecology 42: 587-594.
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Large mammal populations are difficult to census and monitor in remote areas. In particular, elephant populations in Central Africa are difficult to census due to dense forest, making aerial surveys impractical. Conservation management would be improved by a census technique that was accurate and precise, did not require large efforts in the field, and could record numbers of animals over a period of time. We report a new detection technique that relies on sensing the footfalls of large mammals. A single geophone was used to record the footfalls of elephants and other large mammal species at a waterhole in Etosha National Park, Namibia. Temporal patterning of footfalls is evident for some species, but this pattern is lost when there is more than one individual present. We were able to discriminate between species using the spectral content of their footfalls with an 82% accuracy rate. An estimate of the energy created by passing elephants (the area under the amplitude envelope) can be used to estimate the number of elephants passing the geophone. Our best regression line explained 55% of the variance in the data. This could be improved upon by using an array of geophones. This technique, when calibrated to specific sites, could be used to census elephants and other large terrestrial species that are difficult to count. It could also be used to monitor the temporal use of restricted resources, such as remote waterholes, by large terrestrial species.
Thompson M. E., Schwager S. J., Payne K. B. (2010): Heard but not seen: an acoustic survey of the African forest elephant population at Kakum Conservation Area, Ghana. African Journal of Ecology 48: 224-231.
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This study, designed to survey forest elephants (Loxodonta africana cyclotis) at Kakum Conservation Area, Ghana, is the first to apply acoustic methods to elephant abundance estimation and to compare results with independent survey estimates. Nine acoustic sensors gathered sound continuously for 38 days. Low-frequency calling rates have been established as useful elephant abundance indices at a Namibian watering hole and a central African forest clearing. In this study, we estimated elephant population size by applying an abundance index model and detection function developed in central Africa to data from simultaneous sampling periods on Kakum sensors. The sensor array recorded an average of 1.81 calls per 20-min sampling period from an effective detection area averaging 10.27 km2. The resulting estimate of 294 elephants (95% CI: 259–329) falls within confidence bounds of recent dung-based surveys. An extended acoustic model, estimating the frequency with which elephants are silent when present, yields an estimate of 350 elephants (95% CI: 315–384). Acoustic survey confidence intervals are at least half as wide as those from dung-based surveys. This study demonstrates that acoustic surveying is a valuable tool for estimating elephant abundance, as well as for detecting other vocal species and anthropogenic noises that may be associated with poaching.
Zeppelzauer M. (2013): Automated detection of elephants in wildlife video. EURASIP Journal on Image and Video Processing 2013: 46.
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Biologists often have to investigate large amounts of video in behavioral studies of animals. These videos are usually not sufficiently indexed which makes the finding of objects of interest a time-consuming task. We propose a fully automated method for the detection and tracking of elephants in wildlife video which has been collected by biologists in the field. The method dynamically learns a color model of elephants from a few training images. Based on the color model, we localize elephants in video sequences with different backgrounds and lighting conditions. We exploit temporal clues from the video to improve the robustness of the approach and to obtain spatial and temporal consistent detections. The proposed method detects elephants (and groups of elephants) of different sizes and poses performing different activities. The method is robust to occlusions (e.g., by vegetation) and correctly handles camera motion and different lighting conditions. Experiments show that both near- and far-distant elephants can be detected and tracked reliably. The proposed method enables biologists efficient and direct access to their video collections which facilitates further behavioral and ecological studies. The method does not make hard constraints on the species of elephants themselves and is thus easily adaptable to other animal species.
Keen S. C., Shiu Y., Wrege P. H., Rowland E. D. (2017): Automated detection of low-frequency rumbles of forest elephants: A critical tool for their conservation. The Journal of the Acoustical Society of America 141: 2715-2726.
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African forest elephants (Loxodonta cyclotis) occupy large ranges in dense tropical forests and often use far-reaching vocal signals to coordinate social behavior. Elephant populations in Central Africa are in crisis, having declined by more than 60% in the last decade. Methods currently used to monitor these populations are expensive and time-intensive, though acoustic monitoring technology may offer an effective alternative if signals of interest can be efficiently extracted from the sound stream. This paper proposes an automated elephant call detection algorithm that was tested on nearly 4000 h of field recordings collected from five forest clearings in Central Africa, including sites both inside protected areas and in logging concessions. Recordings were obtained in different seasons, years, and under diverse weather conditions. The detector achieved an 83.2% true positive rate when the false positive rate is 5.5% (approximately 20 false positives per hour). These results suggest that this algorithm can enable analysis of long-term recording datasets or facilitate near-real-time monitoring of elephants in a wide range of settings and conditions.
Duporge I., Isupova O., Reece S., Macdonald D. W., Wang T. (2021): Using very‐high‐resolution satellite imagery and deep learning to detect and count African elephants in heterogeneous landscapes. Remote Sensing in Ecology and Conservation 7: 369-381.
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Satellites allow large-scale surveys to be conducted in short time periods with repeat surveys possible at intervals of <24 h. Very-high-resolution satellite imagery has been successfully used to detect and count a number of wildlife species in open, homogeneous landscapes and seascapes where target animals have a strong contrast with their environment. However, no research to date has detected animals in complex heterogeneous environments or detected elephants from space using very-high-resolution satellite imagery and deep learning. In this study, we apply a Convolution Neural Network (CNN) model to automatically detect and count African elephants in a woodland savanna ecosystem in South Africa. We use WorldView-3 and 4 satellite data –the highest resolution satellite imagery commercially available. We train and test the model on 11 images from 2014 to 2019. We compare the performance accuracy of the CNN against human accuracy. Additionally, we apply the model on a coarser resolution satellite image (GeoEye-1) captured in Kenya, without any additional training data, to test if the algorithm can generalize to an elephant population outside of the training area. Our results show that the CNN performs with high accuracy, comparable to human detection capabilities. The detection accuracy (i.e., F2 score) of the CNN models was 0.78 in heterogeneous areas and 0.73 in homogenous areas. This compares with the detection accuracy of the human labels with an averaged F2 score 0.77 in heterogeneous areas and 0.80 in homogenous areas. The CNN model can generalize to detect elephants in a different geographical location and from a lower resolution satellite. Our study demonstrates the feasibility of applying state-of-the-art satellite remote sensing and deep learning technologies for detecting and counting African elephants in heterogeneous landscapes. The study showcases the feasibility of using high resolution satellite imagery as a promising new wildlife surveying technique. Through creation of a customized training dataset and application of a Convolutional Neural Network, we have automated the detection of elephants in satellite imagery with accuracy as high as human detection capabilities. The success of the model to detect elephants outside of the training data site demonstrates the generalizability of the technique.
Dissanayake I., Piyathilake V., Sayakkara A. P., Hettiarachchi E., Perera I. (2024): Eloc-Web: Uncertainty visualization and real-time detection of wild elephant locations. Journal of Geovisualization and Spatial Analysis 8: 7.
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The substantial decline in elephant population, primarily caused by human-elephant conflict, necessitates the proactive engagement of conservationists to devise and implement effective monitoring strategies. Monitoring elephants is essential for gaining insights into their movements and ensuring the preservation of habitat corridors. Conservationists have increasingly shifted towards adopting passive acoustic monitoring as an affordable and non-invasive method for determining the spatial distribution of wild elephants through acoustic localization. The main challenge with remote sensing techniques like passive acoustic monitoring is the time-consuming data analysis, which hinders real-time tracking of elephant whereabouts. To address this issue, the study presents Eloc-Web, a web application that visualizes real-time elephant locations using elephant vocalizations recorded by acoustic sensors in the wild, which utilize machine learning to classify the captured audio. Eloc-Web has taken into account the uncertainties associated with classifying captured audio using machine learning models. This ensures that the potential uncertainty of whether the captured sound truly belongs to an elephant is appropriately considered during the visualization process. By following the user-centered design process, the study integrates expert knowledge from elephant ecologists to inform the design and functionality of the application, ensuring its relevance and usability. Eloc-Web, assessed through the System Usability Scale, ranked it in the top 10% of scores, demonstrating above-average user experience and promising potential in assisting elephant ecologists in studying and conserving elephant populations with real-time data visualization.
HEDGEHOGS, SHREWS, AND DESMANS
Rovero F., Collett L., Ricci S., Martin E., Spitale D. (2013): Distribution, occupancy, and habitat associations of the gray-faced sengi (Rhynchocyon udzungwensis) as revealed by camera traps. Journal of Mammalogy 94: 792-800.
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Three of the 4 species of giant sengis or elephant shrews (genus Rhynchocyon) have restricted geographic distributions in eastern Africa and are threatened by anthropogenic habitat loss. However, little is known about their ecology and habitat relationships. We used remotely triggered cameras to detect the gray-faced sengi (Rhynchocyon udzungwensis), which is endemic in the Udzungwa Mountains of Tanzania, with the aim of defining distributional limits, estimating occupancy patterns, and determining habitat requirements. We deployed 183 camera stations over 6 years and accumulated 4,600 camera trapping days. We refined the area of known occurrence to be 390 km2, thus confirming the species’ restricted range and vulnerability. We estimated the average occupancy at 56% of sites occupied on sites sampled, and found that occupancy was best predicted by the forest habitat type, with interior, closed-canopy forest supporting highest estimated sengi occupancy. Terrain slope and distance to the nearest park boundary were less important covariates, but nevertheless included among the best models. Camera-trapping rate (photographic events by day) was significantly correlated with subcanopy tree coverage. Combined, these habitat features may provide optimal conditions for antipredation vigilance (vegetation cover), and for nest-building and/or foraging on invertebrates in the thicker leaf litter on gentle slopes. Our results offer new insights into the ecology of giant sengis and confirm the potential utility of camera trapping for occupancy analysis of small, forest-dwelling mammals.
González-Esteban J., Esnaola A., Aihartza J. (2018): A new sampling method to detect the Pyrenean desman (Galemys pyrenaicus). Hystrix 29: 190-194.
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The Pyrenean desman (Galemys pyrenaicus) is a small semi-aquatic mammal whose populations have suffered a severe decline in recent decades. Its conservation requires a monitoring program to quantify changes in their populations and distribution. Scat surveys have usually been carried out for this purpose, but they tend to yield a low success rate, which depends on local environmental conditions such as channel form and lithology. This methodological constraint causes that part of the population goes unnoticed. In this study a new method for the detection of this elusive species is tested. The research has been done in the Basque Country (Northern Iberian Peninsula), in Elama and Leitzaran streams, where desmans have been recently recorded. Artificial shelters have been placed, regularly distributed in both streams, offering desmans suitable places to rest and defecate while foraging. The desmans used quickly and repeatedly the artificial shelters, significantly increasing their detection rate. The field identification of scats, based on their shape, colour, size and odour, was subsequently confirmed by DNA analyses with metabarcoding. This new non-invasive method allows obtaining fresh faecal samples of known age, making them available for further studies on genomics, population genetics, dietary studies, reproductive analyses, etc. The low cost of the materials used and the possibility of identifying desman scats after basic training, make this method optimal for synchronic, regional-scale and/or volunteer-based surveys. Thus, the use of artificial shelters results in a substantial improvement over traditional desman scat surveys, and greatly enhance the means for future monitoring of the populations of this endangered species.
Bearman-Brown L. E., Wilson L. E., Evans L. C., Baker P. J. (2020): Comparing non-invasive surveying techniques for elusive, nocturnal mammals: a case study of the West European hedgehog (Erinaceus europaeus). Journal of Vertebrate Biology 69: 20075-1.
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Monitoring changes in populations is fundamental for effective management. The West European hedgehog (Erinaceus europeaus) is of conservation concern in the UK because of recent substantial declines. Surveying hedgehogs is, however, problematic because of their nocturnal, cryptic behaviour. We compared the effectiveness of three methods (infra-red thermal camera, specialist search dog, spotlight) for detecting hedgehogs in three different habitats. Significantly more hedgehogs were detected, and at greater distance, using the camera and dog than the spotlight in amenity grassland and pasture; no hedgehogs were detected in woodland. Increasing ground cover reduced detection distances, with most detections (59.6%) associated with bare soil or mown grass; the dog was the only method that detected hedgehogs in vegetation taller than the target species’ height. The additional value of surveying with a detection dog is most likely to be realised in areas where badgers (Meles meles), an intra-guild predator, are and/or where sufficient ground cover is present; both would allow hedgehogs to forage further from refuge habitats such as hedgerows. Further consideration of the effectiveness of detection dogs for finding hedgehogs in nests, as well as developing techniques for monitoring this species in woodland, is warranted.
Tennant E. N., Cypher B. L., Saslaw L. R., Westall T. L., Mohay J. L., Kelly E. C., Van Horn Job C. L. (2020): Evaluation of noninvasive survey methods for detecting endangered shrews. Wildlife Society Bulletin 44: 610-616.
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Using traditional capture methods, shrews typically have low capture and high trap-mortality rates. To reduce effects from live-trapping and attempt to increase detection success, we investigated 3 potential noninvasive survey methods for shrews (Soricidae): track tubes, scat tubes, and camera traps. These 3 techniques were tested in areas of the San Joaquin Valley, California, USA, with high detection rates of shrews during previous live-trapping surveys. We found that Reconyx camera traps specifically modified with a close focal distance resulted in the greatest number of positive detections and outperformed all other survey methods. Scat tubes also resulted in positive detections but were less reliable and required more expertise. Track tubes resulted in no positive detections. Use of camera traps is highly recommended for conducting presence–absence surveys for shrews.
Yonezawa S., Ushio M., Yamanaka H., Miya M., Takayanagi A., Isagi Y. (2020): Environmental DNA metabarcoding reveals the presence of a small, quick-moving, nocturnal water shrew in a forest stream. Conservation Genetics 21: 1079-1084.
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Chimarrogale platycephala (Japanese water shrew) is an endangered, semi-aquatic mammal species in Japan, and understanding the C. platycephala habitat is vital for conservation planning. However, the species is difficult to locate using conventional methods, like visual observations and camera/video traps, due to its small size, nocturnal behavior, and low population densities in semi-aquatic environments. Environmental DNA (eDNA) analysis has been used to survey distributions of macro-organisms, with the advantage of non-invasiveness, high sensitivity, and cost-effectiveness. In this study, we analyzed the eDNA in flowing water from possible C. platycephala habitats, using a metabarcoding approach that allows simultaneous multi-species detection. The eDNA of this species was detected at 2 of the 16 study sites. Based on eDNA screening data, camera trap surveys confirmed the presence of shrews at both locations. This study successfully discovered a previously unknown habitat of an endangered semi-aquatic mammal, using eDNA metabarcoding and camera traps. Wide ranging use of eDNA surveys will facilitate detection and appropriate conservation of C. platycephala, and can be applied to other critically endangered semi-aquatic mammals.
Littlewood N. A., Hancock M. H., Newey S., Shackelford G., Toney R. (2021): Use of a novel camera trapping approach to measure small mammal responses to peatland restoration. European Journal of Wildlife Research 67: 12.
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Small mammals, such as small rodents (Rodentia: Muroidea) and shrews (Insectivora: Soricidae), present particular challenges in camera trap surveys. Their size is often insufficient to trigger infra-red sensors, whilst resultant images may be of inadequate quality for species identification. The conventional survey method for small mammals, live-trapping, can be both labour-intensive and detrimental to animal welfare. Here, we describe a method for using camera traps for monitoring small mammals. We show that by attaching the camera trap to a baited tunnel, fixing a close-focus lens over the camera trap lens, and reducing the flash intensity, pictures or videos can be obtained of sufficient quality for identifying species. We demonstrate the use of the method by comparing occurrences of small mammals in a peatland landscape containing (i) plantation forestry (planted on drained former blanket bog), (ii) ex-forestry areas undergoing bog restoration, and (iii) unmodified blanket bog habitat. Rodents were detected only in forestry and restoration areas, whilst shrews were detected across all habitat. The odds of detecting small mammals were 7.6 times higher on camera traps set in plantation forestry than in unmodified bog, and 3.7 times higher on camera traps in restoration areas than in bog. When absolute abundance estimates are not required, and camera traps are available, this technique provides a low-cost survey method that is labour-efficient and has minimal animal welfare implications.
Verhees J. J., van der Putten T. A., van Hoof P. H., Heijkers D., Lemmers P., Esser H. J., de Boer W. F. (2024): Comparing the effectiveness of short-focal camera trapping, live trapping, and soil eDNA for surveying small mammals: A case study on Eurasian water shrew (Neomys fodiens). European Journal of Wildlife Research 70: 13.
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Small mammals are potential bio-indicators of various ecosystems and their populations are often studied. However, many small mammal species are difficult to detect due to their small size and elusive behaviour. Camera trapping and live trapping are commonly employed survey techniques, but they both have their limitations. Recently developed techniques such as adjusted short-focal camera trapping and environmental DNA (eDNA) are promising new approaches, but their relative performance remains poorly quantified. We compared the effectiveness of three survey protocols for detecting a semi-aquatic and elusive small mammal, the Eurasian water shrew (Neomys fodiens), by (1) short-focal camera trapping, (2) live trapping, and (3) soil eDNA. During September and October 2022, we surveyed 20 transects of each 100 m in length alongside the Kleine Dommel, a lowland brook in the Netherlands. The effectiveness of the three survey protocols was compared based on detection probabilities. Short-focal camera trapping yielded a significantly higher detection probability than the eDNA protocol. Detection probabilities between short-focal camera trapping and live trapping and, between the eDNA protocol and live trapping, were not significantly different. Short-focal camera trapping is an effective technique to survey Eurasian water shrews. Furthermore, this method detected additional species compared to live trapping and is non-invasive and less labour-intensive. Short-focal camera trapping showed a promising method for small mammal surveys in general and we recommend further evaluation of its applicability for other small mammal species.
MANATEES AND DUGONGS
Hunter M. E., Meigs-Friend G., Ferrante J. A., Kamla A. T., Dorazio R. M., Diagne L. K., Luna F., Lanyon J. M., Reid J. P. (2018): Surveys of environmental DNA (eDNA): a new approach to estimate occurrence in vulnerable manatee populations. Endangered Species Research 35: 101-111.
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Environmental DNA (eDNA) detection is a technique used to non-invasively detect cryptic, low density, or logistically difficult-to-study species, such as imperiled manatees. For eDNA measurement, genetic material shed into the environment is concentrated from water samples and analyzed for the presence of target species. Cytochrome b quantitative PCR and droplet digital PCR eDNA assays were developed for the 3 Vulnerable manatee species: African, Amazonian, and both subspecies of the West Indian (Florida and Antillean) manatee. Environmental DNA assays can help to delineate manatee habitat ranges, high use areas, and seasonal population changes. To validate the assay, water was analyzed from Florida’s east coast containing a high-density manatee population and produced 31564 DNA molecules l-1 on average and high occurrence (ψ) and detection (p) estimates (ψ = 0.84 [0.40-0.99]; p = 0.99 [0.95-1.00]; limit of detection 3 copies µl-1). Similar occupancy estimates were produced in the Florida Panhandle (ψ = 0.79 [0.54-0.97]) and Cuba (ψ = 0.89 [0.54-1.00]), while occupancy estimates in Cameroon were lower (ψ = 0.49 [0.09-0.95]). The eDNA-derived detection estimates were higher than those generated using aerial survey data on the west coast of Florida and may be effective for population monitoring. Subsequent eDNA studies could be particularly useful in locations where manatees are (1) difficult to identify visually (e.g. the Amazon River and Africa), (2) are present in patchy distributions or are on the verge of extinction (e.g. Jamaica, Haiti), and (3) where repatriation efforts are proposed (e.g. Brazil, Guadeloupe). Extension of these eDNA techniques could be applied to other imperiled marine mammal populations such as African and Asian dugongs.
de Souza D. A., Gonçalves A. L. S., von Muhlen E. M., da Silva V. M. F. (2021): Estimating occupancy and detection probability of the Amazonian manatee (Trichechus inunguis), in Central Amazon, Brazil. Perspectives in Ecology and Conservation 19: 354-361.
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Understanding the distribution and abundance of threatened species is crucial to elaborate effective management plans for wild populations; however, elusive species prove difficult to detect. To support conservation strategies for the Vulnerable Amazonian manatee (Trichechus inunguis), the only freshwater sirenian, we analyzed presence/absence data with hierarchical models based on imperfect detection to assess T. inunguis occupancy in a Sustainable Development Reserve, Brazilian Central Amazon. In parallel, we compared the effectiveness of direct and indirect sampling methods to provide occupancy (ψ) and detection (p) estimates. Combining both sampling methods’ presence datasets provided higher accuracy estimates. The Amazonian manatee’s detection probability had never been estimated before: surprisingly, it was high (p = 0.50, SD = 0.05) and positively related with macrophyte coverage. Results suggest that the studied communities resident impact is not affecting the manatee occupancy, with greatest probabilities closer to human settlements. The final occupancy estimate obtained (ψ = 0.85, SD = 0.12) can be a baseline to Amazonian manatee long-term monitoring studies, and provide support for decision makers and local communities to establish effective protection zones for the species. Our approach highlights the potential of hierarchical models to understand the distribution not only of T. inunguis in different habitats, but also of other threatened Amazonian aquatic mammals.
Tol S. J., Harrison M., Groom R., Gilbert J., Blair D., Coles R., Congdon B. C. (2021): Using DNA to distinguish between faeces of Dugong dugon and Chelonia mydas: non-invasive sampling for IUCN-listed marine megafauna. Conservation Genetics Resources 13: 115-117.
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The Dugong dugon (dugong) and Chelonia mydas (green sea turtle) are economically and culturally significant marine mega-herbivores whose populations are declining globally. Capture of these animals for study is challenging and stressful for the animals. Ecological questions can be answered using faeces, which can be collected floating on the water’s surface. However, green turtle and dugong faeces are visually indistinguishable. Specific PCR primer pairs were developed based on the mitochondrial control region of each species. We were able to determine species of origin using DNA extracted, amplified and sequenced from faeces. This provides a valuable tool for non-invasive taxonomic identification to assist the conservation of these vulnerable and endangered species.
Factheu C., Rycyk A. M., Kekeunou S., Keith-Diagne L. W., Ramos E. A., Kikuchi M., Takoukam Kamla A. (2023): Acoustic methods improve the detection of the endangered African manatee. Frontiers in Marine Science 9: 1032464.
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The African manatee (Trichechus senegalensis) is an elusive, data-deficient, and endangered species which inhabits marine and freshwater systems throughout Western and Central Africa. A major challenge in understanding the species ecology and distribution is the difficulty in detecting it using traditional visual surveys. The recent invasion of Giant Salvinia (Salvinia molesta) at the most important site for the species in Cameroon further limits their detectability and may restrict their movements and habitat use. To investigate methods’ effectiveness in detecting African manatees, we conducted monthly vessel surveys from which visual point scans, 360° sonar scans, and passive acoustic monitoring were conducted simultaneously at ten locations and over 12 months in Lake Ossa, Cameroon. Manatee detection frequency was calculated for each method and the influence of some environmental conditions on the methods’ effectiveness and manatee detection likelihood was assessed by fitting a binary logistic regression to our data. Detection frequencies were significantly different between methods (p < 0.01) with passive acoustics being the most successful (24.17%; n = 120), followed by the 360° sonar scan (11.67%; n = 120), and the visual point scan (3.33%; n = 120). The likelihood of detecting manatees in Lake Ossa was significantly influenced by water depth (p = 0.02) and transparency (p < 0.01). It was more likely to detect manatees in shallower water depths and higher water transparency. Passive acoustic detections were more effective in uninvaded areas of the Lake. We recommend using passive acoustics to enhance African manatee detections in future surveys.
MARSUPIALS
Vargas M. L., Cruickshank R. H., Ross J. G., Holyoake A. J., Ogilvie S. C., Paterson A. M. (2009): Noninvasive recovery and detection of possum Trichosurus vulpecula DNA from bitten bait interference devices (WaxTags). Molecular Ecology Resources 9: 505-515.
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The brushtail possum is a major agricultural and ecological pest in New Zealand. A novel noninvasive DNA sampling tool for detecting its presence (WaxTags, or WT) was tested. DNA was recovered from saliva left on WT, and two lengths (407 bp and 648 bp) of the cytochrome c oxidase I (COI) barcoding region were amplified by polymerase chain reaction (PCR). PCR products were considered (+) when a DNA band was clearly visible by electrophoresis. Different factors that might affect PCR (+) were investigated with captive possums: (i) both extraction protocols of the QIAGEN DNeasy Blood and Tissue Kit, (ii) effect of an overnight or longer delay of up to 3 weeks before DNA extraction on both COI amplicons, and (iii) effect of the individual, order and magnitude of the bite. Extraction protocols were not significantly different. The effect of the overnight delay was not significant, and amplification of the short amplicon was significantly higher (100%) than for the long fragment (48%). After a two or 3‐week delay, the short amplicon had 94% and 56% PCR (+), success rates, respectively. Individual, order and magnitude of a bite had no significant effect. The delay trial was repeated with WT from the wild, for which PCR (+) rate of the short amplicon was 63%, regardless of freshness. Four microsatellites were amplified from captive WT samples. We conclude that DNA from saliva traces can be recovered from WT, a potential new tool for noninvasive monitoring of possums and other wildlife.
Wadley J. J., Austin J. J., Fordham D. A. (2013): Rapid species identification of eight sympatric northern Australian macropods from faecal-pellet DNA. Wildlife Research 40: 241-249.
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Conservation of vulnerable and endangered species requires a comprehensive understanding of their distribution and habitat requirements, so as to implement effective management strategies. Visual scat surveys are a common non-invasive method for monitoring populations. However, morphological similarity of scats among sympatric species presents a problem for accurate identification. Visual misidentifications of scats can have major impacts on the accuracy of abundance and distribution surveys of target species, wasting resources and misdirecting management and conservation actions. DNA identification of scats can overcome this issue, while simultaneously providing a rich source of genetic information for population and dietary studies. We developed a simple and reliable method to identify morphologically similar macropod scats from eight sympatric species in north-eastern Australia, using polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) of a portion of the mtDNA ND2 gene. We identified a short (275-bp) polymorphic region of ND2, which is easily amplifiable from degraded DNA, developed a primer set, and identified a set of three restriction endonucleases (AluI, BstNI and HphI) which, in combination, can discriminate among the eight target species. So as to test the effectiveness of this protocol, we collected 914 macropod scats from 53 sites in the north-eastern Australia. In total, 406 of these scats were extracted, with 398 (98%) containing amplifiable macropod DNA. All 398 scats were subsequently identified to species by using our RFLP protocol. Sequencing of a subset of these samples confirmed the accuracy of the test. Species identification of scats by using DNA identified eight species of macropods, five of which were outside their documented distributions, one of which was ~400 km. Our PCR–RFLP method is a simple and efficient means to identify macropod scats to species, eliminating the need for sequencing, which is costly, time-consuming and requires additional laboratory equipment. The method allows for rapid and non-invasive assessment of macropod species and is particularly useful for surveying populations across multiple sites.
Swinbourne M. J., Taggart D. A., Sparrow E., Hatch M., Ostendorf B. (2016): Ground penetrating radar as a non-invasive tool to better understand the population dynamics of a fossorial species: mapping the warrens of southern hairy-nosed wombats (Lasiorhinus latifrons). Wildlife Research 42: 678-688.
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Management of wildlife that may simultaneously be of conservation concern and pose problems for humans is difficult, particularly when knowledge of their population dynamics is elusive. Culling of southern hairy-nosed wombats (Lasiorhinus latifrons) is often carried out in agricultural areas, with no understanding of potential impacts on the species as a whole. Monitoring fossorial species via non-invasive means (that do not adversely impact animals by damaging their burrows) has always represented a challenge for wildlife researchers. The aim of this research was to map the areal extent of different types of L. latifrons warrens to gain a better understanding of the relationship between the external warren signs and its subterranean structure. The findings will be used in the development of more accurate indices of population abundance to better inform management decisions. Ground penetrating radar (GPR) was used to map warrens at four locations in the western regions of South Australia. Radar data were collected using a Mala X3M GPR system with 250 MHz and 500 MHZ antennas. 3D models of each site were then produced using the ReflexW GPR software processing package. Subterranean warren structure varied from a mix of tunnel types in sandy-loam soil to a complex array of tunnels and caverns under sheet calcrete limestone. This was the first non-invasive mapping of wombat warrens and the first mapping of a warren under a layer of calcrete limestone. In sandy-loam soil, the size and extent of the external spoil mound provided some indication of warren complexity. However, there were no external signs of the extent of the calcrete warren. The lack of external cues regarding the extent of the calcrete limestone warren suggests that the current method of estimating population abundance based on a single index of wombats per active burrow is flawed. As a result, any management decisions in regard to culling may be based on inaccurate information. It is apparent that further research needs to be undertaken to develop a range of abundance indices that take into account local conditions such as soil type.
Gray E. L., Dennis T. E., Baker A. M. (2017): Can remote infrared cameras be used to differentiate small, sympatric mammal species? A case study of the black-tailed dusky antechinus, Antechinus arktos and co-occurring small mammals in southeast Queensland, Australia. Plos One 12: e0181592.
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The black-tailed dusky antechinus (Antechinus arktos) is an endangered, small carnivorous marsupial endemic to Australia, which occurs at low population density along with abundant sympatric populations of other small mammals: Antechinus stuartii, Rattus fuscipes and Melomys cervinipes. Using A. arktos as a model species, we aimed to evaluate the effectiveness of infrared digital camera traps for detecting and differentiating small mammals and to comment on the broad applicability of this methodology. We also sought to understand how the detection probabilities of our target species varied over time and characterize their activity patterns. We installed 11 infrared cameras at one of only three known sites where A. arktos occurs for five consecutive deployments. Cameras were fixed to wooden stakes and oriented vertically, 35 cm above ground, directly facing bait containers. Using this method, we successfully recorded and identified individuals from all four species of small mammal known previously in the area from live trapping, including A. arktos. This validates the effectiveness of the infrared camera type and orientation for small mammal studies. Periods of activity for all species were highly coincident, showing a strong peak in activity during the same two-hour period immediately following sunset. A. arktos, A. stuartii and M. cervinipes also displayed a strong negative linear relationship between detection probability and days since deployment. This is an important finding for camera trapping generally, indicating that routine camera deployment lengths (of one-to-two weeks) between baiting events may be too long when targeting some small mammals.
Lethbridge M., Stead M., Wells C. (2019): Estimating kangaroo density by aerial survey: A comparison of thermal cameras with human observers. Wildlife Research 46: 639-648.
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Aerial surveys provide valuable information about the population status and distribution of many native and pest vertebrate species. They are vital for evidence-based monitoring, budget planning and setting management targets. Despite aircraft running costs, they remain one of the most cost-effective ways to capture distribution and abundance data over a broad area. In Australia, annual surveys of large macropods are undertaken in several states to inform management, and in some jurisdictions, to help set commercial kangaroo harvest quotas. Improvements in the cost efficiencies of these surveys are continually sought. Aerial thermal imaging techniques are increasingly being tested for wildlife surveys, but to date no studies have directly compared population data derived from thermal imaging with data collected by human observers during the same flight. During an aerial survey of western grey kangaroos (Macropus fuliginosus), eastern grey kangaroos (M. giganteus) and red kangaroos (Osphranter rufus) across the state of Victoria, Australia, the objective was to conduct a direct comparison of the effectiveness of thermal camera technology and human observers for estimating kangaroo populations from aerial surveys. A thermal camera was mounted alongside an aerial observer on one side of the aircraft for a total of 1360 km of transect lines. All thermal footage was reviewed manually. Population density estimates and distance sampling models were compared with human observer counts. Overall, the kangaroo density estimates obtained from the thermal camera data were around 30% higher than estimates derived from aerial observer counts. This difference was greater in wooded habitats. Conversely, human-derived counts were greater in open habitats, possibly due to interference from sunlight and flushing. It was not possible to distinguish between species of macropod in the thermal imagery. Thermal survey techniques require refining, but the results of the present study suggest that with careful selection of time of day for surveys, more accurate population estimates may be possible than with conventional aerial surveys. Conventional aerial surveys may be underestimating animal populations in some habitats. Further studies that directly compare the performance of aerial observers and thermal imaging are required across a range of species and habitats.
Augusteyn J., Pople A., Rich M. (2020): Evaluating the use of thermal imaging cameras to monitor the endangered greater bilby at Astrebla Downs National Park. Australian Mammalogy 42: 329-340.
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Spotlight surveys are widely used to monitor arid-zone-dwelling species such as the greater bilby (Macrotis lagotis). These surveys require a sufficient sample size to adequately model detection probability. Adequate sample sizes can be difficult to obtain for low-density populations and for species that avoid light and or have poor eyeshine like the bilby. Abundance estimates based on burrow counts can be problematic because of the variable relationship between the number of burrows used and bilby abundance. In 2013, feral predators devastated a Queensland bilby population and a method was required that could locate and monitor the remaining bilbies. We report on a study that compared density estimates derived from spotlighting and thermal cameras. Bilbies were surveyed annually over three years, using spotlights and thermal cameras on different nights but using the same transects to compare the methods. On average, thermal cameras detected twice the number of bilbies per kilometre surveyed than spotlighting. Despite this difference in the number of bilbies detected, density estimates (bilbies km−2) were similar (thermal camera versus spotlight: 0.6 versus 0.2 (2014), 3.4 versus 3.4 (2015) and 4.8 versus 3.3 (2016)). Nevertheless, the larger sample size obtained using thermal cameras gave greater confidence in modelling detection probability.
Brunton E. A., Leon J. X., Burnett S. E. (2020): Evaluating the efficacy and optimal deployment of thermal infrared and true-colour imaging when using drones for monitoring kangaroos. Drones 4: 20.
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Advances in drone technology have given rise to much interest in the use of drone-mounted thermal imagery in wildlife monitoring. This research tested the feasibility of monitoring large mammals in an urban environment and investigated the influence of drone flight parameters and environmental conditions on their successful detection using thermal infrared (TIR) and true-colour (RGB) imagery. We conducted 18 drone flights at different altitudes on the Sunshine Coast, Queensland, Australia. Eastern grey kangaroos (Macropus giganteus) were detected from TIR (n=39) and RGB orthomosaics (n=33) using manual image interpretation. Factors that predicted the detection of kangaroos from drone images were identified using unbiased recursive partitioning. Drone-mounted imagery achieved an overall 73.2% detection success rate using TIR imagery and 67.2% using RGB imagery when compared to on-ground counts of kangaroos. We showed that the successful detection of kangaroos using TIR images was influenced by vegetation type, whereas detection using RGB images was influenced by vegetation type, time of day that the drone was deployed, and weather conditions. Kangaroo detection was highest in grasslands, and kangaroos were not successfully detected in shrublands. Drone-mounted TIR and RGB imagery are effective at detecting large mammals in urban and peri-urban environments.
Seidlitz A., Bryant K. A., Armstrong N. J., Calver M., Wayne A. F. (2020): Optimising camera trap height and model increases detection and individual identification rates for a small mammal, the numbat (Myrmecobius fasciatus). Australian Mammalogy 43: 226-234.
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Camera traps are widely used to collect data for wildlife management, but species-specific testing is crucial. We conducted three trials to optimise camera traps for detecting numbats (Myrmecobius fasciatus), a 500–700-g mammal. We compared detection rates from (1) Reconyx PC900 camera traps installed at heights ranging from 10–45 cm, and (2) Reconyx PC900, Swift 3C standard and wide-angle camera traps with differing detection zone widths. Finally, we compared elevated, downward-angled time-lapse cameras installed at heights ranging from 1–2 m to obtain dorsal images for individual numbat identification. Camera traps set at 25 cm had the highest detection rates but missed 40% of known events. During model comparison, Swift 3C wide-angle camera traps recorded 89%, Swift 3C standard 51%, and Reconyx PC900 37% of known events. The number of suitable images from elevated, downward-angled cameras, depicting dorsal fur patterns, increased with increasing camera height. The use of well regarded camera trap brands and generic recommendations for set-up techniques cannot replace rigorous, species-specific testing. For numbat detection, we recommend the Swift 3C wide-angle model installed at 25-cm height. For individual numbat identification, elevated, downward-angled time-lapse cameras were useful; however, more research is needed to optimise this technique.
Thompson S. A., Thompson G. G., Withers P. C., Bennett E. M. (2020): Conservation detection dog is better than human searcher in finding bilby (Macrotis lagotis) scats. Australian Zoologist 41: 86-93.
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Conservation detection dogs have been widely used for finding scats, retreat sites and specific plant and animal species for a variety of purposes, including monitoring, management, biosecurity and eradication programs. Their cost-effectiveness appears well established in finding cryptic and rare animals, yet they are not included in the Department of Biodiversity, Conservation and Attractions’ published search protocol for bilbies. In this study a human searcher located six of 90 scats (6.7%) compared to the conservation detection dog that located 89 of 90 bilby scats (98.9%). The dog’s time to locate the first scat in a 25m × 25m site with a ground cover of leaves, sticks and grasses was 72.8 sec (± se 8.10, n = 60) and, when a second scat was present, the mean time to locate the second scat was 186.5 sec (± se 186.517, n = 29). We strongly recommend that conservation detection dogs are incorporated into the State government’s search protocol for bilbies, as they are more accurate and faster than human searchers, and provide development proponents with greater confidence in searches undertaken as part of an environmental impact assessment.
Pocknee C. A., Lahoz-Monfort J. J., Martin R. W., Wintle B. A. (2021): Cost-effectiveness of thermal imaging for monitoring a cryptic arboreal mammal. Wildlife Research 48: 625-634.
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The development of reliable and cost-efficient survey techniques is key to the monitoring of all wildlife. One group of species that presents particular challenges for monitoring is the arboreal mammals. Traditional techniques for detecting these species often yield low detection probabilities (detectability) and are time-consuming, suggesting the potential for novel methods to enhance our understanding of their distribution, abundance and population trajectories. One technique that has been shown to increase detectability in a range of terrestrial species is thermal imaging, although it has rarely been applied to arboreal species. The true conservation status of Lumholtz’s tree-kangaroo (Dendrolagus lumholtzi) is uncertain because of low detectability under typical survey techniques, and a more suitable method is required to enable effective monitoring of the species, making it an ideal candidate for the present study. We aimed to compare the success and cost-effectiveness of surveys utilising thermal imaging with two traditional methods, namely, spotlighting and daytime surveys, so as to optimise monitoring of D. lumholtzi. We conducted surveys at 10 sites in Queensland (Australia) where D. lumholtzi was known to occur, by using each method, and modelled both the detectability of D. lumholtzi and the cost-effectiveness of each technique. Detectability of D. lumholtzi was significantly higher with the use of thermal imaging than it was with the other survey methods, and thermal detection is more cost-effective. In average survey conditions with a trained observer, the single-visit estimated detectability of D. lumholtzi was 0.28 [0.04, 0.79] in a transect through rainforest, by using thermal imaging. Using only spotlights, the detection probability was 0.03 [0, 0.28] under the same conditions. These results show that incorporating thermal technology into monitoring surveys will greatly increase detection probability for D. lumholtzi, a cryptic arboreal mammal. Our study highlighted the potential utility of thermal detection in monitoring difficult-to-detect species in complex habitats, including species that exist mainly in dense forest canopy.
Campbell C. D., MacDonald A. J., Sarre S. D. (2024): Evaluation of genetic markers for the metabarcoding of Australian marsupials from predator scats. Wildlife Research 51: WR23134.
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DNA recovered from predator faeces (scats) can be used to determine the presence of fauna and shed light on their life histories and inter-species interactions. DNA metabarcoding, which involves concurrent amplification and sequencing of DNA from multiple taxa, represents an important advance by enabling the simultaneous detection of multiple species from such samples. Although an attractive proposition, metabarcoding requires ‘universally’ applicable genetic markers that can discriminate among a broad range of taxa, while also targeting sequences that are sufficiently short to be amplified from degraded DNA. To identify, evaluate, and test metabarcoding DNA markers suitable for the detection of marsupials and other Australian fauna from terrestrial predator scats found in nature. We apply a bioinformatic approach using publicly available DNA databases and a locally derived and marker-specific reference-DNA database to evaluate the diagnostic ability and likelihood of amplification of candidate metabarcoding markers for marsupials and other taxa that may be consumed by predators. We identify two markers (12SV5 and 16SMam) that are suitable for use and successfully identify marsupial sequences at a high level of resolution. These markers work best in combination because they bring complementary levels of primer specificity and diagnostic ability in detecting multiple prey species as well as the predator. We also show that these samples work well in predator scats sampled from the wild in Tasmania. These markers provide a useful tool for surveying mammalian predators and their prey and could also be applied to eDNA analyses from other sample types. Improvements to the reference database and further development of markers targeting different taxonomic groups will improve the resolution and usefulness of this approach. Metabarcoding of predator scats provides a potent approach to non-invasive wildlife survey that offers the opportunity for the detection of multiple species across all vertebrates.
Frere C., Jackson N., Moreno J., Oliveros Sandino A., Ball S., Powell D. (2023): Koalas, friends and foes—The application of airborne eDNA for the biomonitoring of threatened species. Journal of Applied Ecology 61: 2837-2847.
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Curbing global wildlife population declines will necessitate the protection of their habitat, and subsequent robust baseline information about wildlife that use and occupy it. Collating such information, however, remains a challenging and costly endeavour. Little did we know that traces of wildlife presence float in the air and can be detected through traces of DNA. Here, we deployed samplers to test the applicability of collecting airborne eDNA for the detection of a threatened species, the koala, and its co-occurring terrestrial mammalian community. We develop a novel species specific qPCR assay to detect the presence of koalas and applied this in concert with a meta-barcoding approach to detect the co-occurring mammalian community. Through sampling of airborne particles, we successfully detected koala presence accurately to habitat patch level, alongside 16 unique taxonomic assignments, successfully assigning 11 of these to species level including detections belonging to the wallaby, antechinus, members of possum family and invasive species such as foxes, domestic dogs and hares. We demonstrate the potential of airborne eDNA for the detection of threatened terrestrial wildlife and their surrounding ecological community under natural conditions. With achievable optimisations we detail how airborne eDNA may be applied for the management and monitoring of threated species for enhanced conservation efforts.
Al-Shimaysawee L. A., Finn A., Weber D., Schebella M. F., Brinkworth R. S. (2024): Evaluation of automated object-detection algorithms for koala detection in infrared aerial imagery. Sensors 24: 7048.
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Effective detection techniques are important for wildlife monitoring and conservation applications and are especially helpful for species that live in complex environments, such as arboreal animals like koalas (Phascolarctos cinereus). The implementation of infrared cameras and drones has demonstrated encouraging outcomes, regardless of whether the detection was performed by human observers or automated algorithms. In the case of koala detection in eucalyptus plantations, there is a risk to spotters during forestry operations. In addition, fatigue and tedium associated with the difficult and repetitive task of checking every tree means automated detection options are particularly desirable. However, obtaining high detection rates with minimal false alarms remains a challenging task, particularly when there is low contrast between the animals and their surroundings. Koalas are also small and often partially or fully occluded by canopy, tree stems, or branches, or the background is highly complex. Biologically inspired vision systems are known for their superior ability in suppressing clutter and enhancing the contrast of dim objects of interest against their surroundings. This paper introduces a biologically inspired detection algorithm to locate koalas in eucalyptus plantations and evaluates its performance against ten other detection techniques, including both image processing and neural-network-based approaches. The nature of koala occlusion by canopy cover in these plantations was also examined using a combination of simulated and real data. The results show that the biologically inspired approach significantly outperformed the competing neural-network- and computer-vision-based approaches by over 27%. The analysis of simulated and real data shows that koala occlusion by tree stems and canopy can have a significant impact on the potential detection of koalas, with koalas being fully occluded in up to 40% of images in which koalas were known to be present. Our analysis shows the koala’s heat signature is more likely to be occluded when it is close to the centre of the image (i.e., it is directly under a drone) and less likely to be occluded off the zenith. This has implications for flight considerations. This paper also describes a new accurate ground-truth dataset of aerial high-dynamic-range infrared imagery containing instances of koala heat signatures. This dataset is made publicly available to support the research community.
MONOTREMES
Lugg W. H., Griffiths J., van Rooyen A. R., Weeks A. R., Tingley R. (2018): Optimal survey designs for environmental DNA sampling. Methods in Ecology and Evolution 9: 1049-1059.
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Environmental DNA (eDNA) sampling is a promising tool for monitoring cryptic species. Numerous studies have demonstrated that eDNA sampling can achieve higher detection rates than traditional monitoring techniques, such as trapping; however, the consequences of that sensitivity for survey design requirements and resulting survey costs have not been investigated. We demonstrate how site occupancy detection models and optimal survey design methods can be used to evaluate the cost‐efficiency of eDNA sampling vs. traditional survey methods. We apply these approaches to two datasets—one in which eDNA sampling and trapping were conducted simultaneously (paired dataset), and another in which sampling methods were independently deployed (unpaired dataset)—to assess the cost‐efficiency of eDNA sampling for detecting a freshwater mammal: the platypus Ornithorhynchus anatinus. Conditional probabilities of platypus eDNA being captured in a single water sample (paired dataset: 0.838, unpaired: 0.879), and detected in a single water sample by qPCR (paired: 0.892, unpaired: 0.858), were higher than the conditional probability of detecting a platypus with a single trapping visit (paired: 0.470, unpaired: 0.219). eDNA sampling was more cost‐efficient than trapping, regardless of whether the management objective was to (1) minimize the survey budget needed to achieve a particular asymptotic variance of the occupancy estimator, or (2) minimize the survey budget needed to detect a change in occupancy over time. Site occupancy detection models coupled with optimal survey design methods provide a powerful means with which to compare the sensitivity and cost‐efficiency of eDNA sampling vs. traditional sampling methods.
McColl-Gausden E. F., Griffiths J., Collins L., Weeks A. R., Tingley R. (2023): The power of eDNA sampling to investigate the impact of Australian mega-fires on platypus occupancy. Biological Conservation 286: 110219.
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Fire plays an important role in many ecosystems, but megafires are increasing the area burnt in forested regions globally. The 2019–2020 megafires in south-eastern Australia were unprecedented with respect to area burnt and the spatial extent of high-severity fire. Yet, there is limited knowledge regarding the impact of these megafires on biodiversity, especially aquatic fauna. Here we investigate the impact of the 2019–2020 megafires on the distribution of a semi-aquatic monotreme thought to be in decline: the platypus, Ornithorhynchus anatinus. We leveraged extensive pre-fire environmental DNA (eDNA) sampling and coupled this with additional sampling at two timepoints post-fire, to conduct a Before-After-Control-Impact (BACI) study. We used site occupancy-detection modelling to estimate platypus occupancy across fire affected and non-fire affected sites over time as well as the interaction between occupancy, high rainfall, and fire severity. We detected a negative effect of fire presence on platypus occupancy in both post-fire time periods. Platypus occupancy was also predicted to be lower at sites that experienced high rainfall post-fire and were situated within watersheds that had a large proportion burnt at high-severity. With area burnt and the extent of high-severity fire increasing globally, and predictions of more extreme rainfall events in south-eastern Australia in the future, the impact of fire on aquatic fauna requires greater consideration in post-fire assessments and biodiversity management more generally. The use of eDNA sampling and detection methods in a BACI framework provides a promising means to fill these knowledge gaps but does require pre-emptive sampling.
Khodaparast M., Sharley D., Marshall S., Beddoe T. (2024): Rapid and cost‐effective platypus eDNA detection in waterways using loop‐mediated isothermal amplification assay: Advancing conservation efforts. Environmental DNA 6: e70003.
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Freshwater ecosystems, home to a remarkable diversity of species, are facing severe threats from human activities such as climate change, habitat degradation, over-extraction of water for irrigation, and pollution. The platypus, an iconic species in freshwater ecosystems around Australia, is threatened by all these activities, both singly and in combination. The scale and complexity of these intersecting and reinforcing threats makes cost-effective monitoring tools essential to better understand how platypus populations are responding. In this study, we optimized a loop-mediated isothermal amplification (LAMP) assay for the rapid and cost-effective detection of platypus DNA in environmental water samples, offering an attractive alternative to quantitative polymerase chain reaction (qPCR). We improved a water filtration protocol for in-field use, employing suitable filter membranes for processing large volumes of water, thereby maximizing DNA recovery from dilute samples. The limit of detection for the platypus LAMP (Plat-LAMP) assay was determined to be 12.4 copies/μL using a standard plasmid positive reference and 7 × 10−6 ng/μL when applied to DNA extracted from platypus tissue, with improved sensitivity achieved through the incorporation of locked nucleic acid primers. In comparative testing against qPCR, the Plat-LAMP assay exhibited greater sensitivity in detecting platypus DNA in known positive water samples collected from platypus habitat at Healesville Sanctuary. Furthermore, the Plat-LAMP assay demonstrated 100% specificity when performed on water samples collected from non-platypus habitats. In field testing across waterways in Victoria and New South Wales, the Plat-LAMP assay detected platypus in 36.96% of samples, compared to 54.35% of samples using qPCR. These findings underscore the Plat-LAMP assay’s potential as a faster and more cost-effective complementary method to qPCR, rendering it suitable for point-of-application water testing. The ability to conduct eDNA surveys without the need for cold-chain logistics would significantly assist conservation organizations and water managers map platypus distributions and facilitate conservation efforts around Australia.
Musser A., Grant T., Turak E. (2024): Movements of platypuses around and through instream structures and natural barriers in the Jenolan Karst Conservation Reserve, New South Wales. Australian Mammalogy 46: AM23031.
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Severe flooding in early 2020 and 2021 necessitated major desedimentation works at the iconic Blue Lake in the Jenolan Karst Conservation Reserve (JKCR). Movements and behaviour of platypuses were monitored before, during and after these works, using direct observations, remote cameras and environmental DNA (eDNA) sampling. Platypuses were observed along a 3 km reach of the Jenolan River, including the areas where works occurred, although in low numbers. In their use of the available waterways, platypuses negotiated artificial barriers, including a 10 m high dam, two smaller weirs and natural waterfalls and cascades. Overland movements were detected through vegetation tunnels, drainage pipes and culverts, and individuals were seen entering the cave system, where eDNA was also detected. Platypuses responded to the works activity by foraging outside the affected areas but also continued to traverse these areas from time to time. We describe movements around and through instream infrastructure and past natural barriers and report on other species detected by remote cameras. These observations could help planning and deployment of bypasses suitable for movement of platypuses around anthropogenic barriers and provide insights into impediments to dispersal and gene flow within stream systems.
Roberts S., Serena M. (2024): Use of consolidated time-lapse camera imagery to detect and monitor platypus (Ornithorhynchus anatinus) activity. Australian Mammalogy 46: AM23045.
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The platypus is a challenging species to survey and monitor. We investigated the use of time-lapse cameras to detect platypus activity in a Tasmanian creek by deploying three camera models diurnally at a single site over 6 months, and deploying one model both nocturnally and diurnally at two sites over 12 months. Variation in camera attributes and settings (camera view angle, length of time-lapse intervals) contributed to a 10-fold difference in the mean number of platypus images recorded in a given behavioural sequence (or ‘event’) and an approximately 50% difference in median event duration among the three models. Results also varied between sites and at diel and bimonthly time scales due to pool topography, day length (affecting site illumination) and likely temporal differences in platypus activity and population size. However, even the least-effective camera model reliably captured ≥1 platypus image within the first 24 h of deployment at the two study sites throughout the year. Time-lapse cameras are a suitable tool to assess platypus occurrence and measure activity, as long as appropriate equipment is selected for the intended purpose and sources of spatial and temporal variation are carefully considered when designing studies and interpreting results.
PRIMATES
Kalan A. K., Mundry R., Wagner O. J., Heinicke S., Boesch C., Kühl H. S. (2015): Towards the automated detection and occupancy estimation of primates using passive acoustic monitoring. Ecological Indicators 54: 217-226.
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Recent advancements in technology have made possible the use of novel, cost-efficient biomonitoring techniques which facilitate monitoring animal populations at larger spatial and temporal scales. Here, we investigated using passive acoustic monitoring (PAM) for wild primate populations living in the forest of Taï National Park, Côte d’Ivoire. We assessed the potential of using a customized algorithm for the automated detection of multiple primate species to obtain reliable estimates of species occurrence from acoustic data. First, we applied the algorithm on continuous rainforest recordings collected using autonomous recording units (ARUs) to detect and classify three sound signals: chimpanzee buttress drumming, and the loud calls of the diana and king colobus monkey. Using an occupancy modelling approach we then investigated to what extent the automated, probabilistic output needs to be listened to, and thus manually cleaned, by a human expert, to approach occupancy probabilities derived from ARU data fully verified by a human. To do this we explored the robustness of occupancy probability estimates by simulating ARU datasets with various degrees of cleaning for false positives and false negative detections. We further validated the approach by comparing it to data collected by human observers on point transects located within the same study area. Our study demonstrates that occurrence estimates from ARU data, combined with automated processing methods such as our algorithm, can provide results comparable to data collected by humans and require less effort. We show that occupancy probabilities are quite robust to cleaning effort, particularly when occurrence is high, and suggest that for some species even naïve occupancy, as derived from ARU data without any cleaning, could provide a quick and reliable indicator to guide monitoring efforts. We found detection probabilities to be most influenced by time of day for chimpanzee drums while temperature and, likely, poaching pressure, affected detection of diana monkey loud calls. None of the covariates investigated appeared to have strongly affected king colobus loud call detection. Finally, we conclude that the semi-automated approach presented here could be used as an early-warning system for poaching activity and suggest additional techniques for improving its performance.
Torti V., Valente D., De Gregorio C., Comazzi C., Miaretsoa L., Ratsimbazafy J., Giacoma C., Gamba M. (2018): Call and be counted! Can we reliably estimate the number of callers in the indri’s (Indri indri) song?. Plos One 13: e0201664.
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Estimating the number of animals participating in a choral display may contribute reliable information on animal population estimates, particularly when environmental or behavioral factors restrict the possibility of visual surveys. Difficulties in providing a reliable estimate of the number of singers in a chorus are many (e.g., background noise masking, overlap). In this work, we contributed data on the vocal chorusing of the indri lemurs (Indri indri), which emit howling cries, known as songs, uttered by two to five individuals. We examined whether we could estimate the number of emitters in a chorus by screening the fundamental frequency in the spectrograms and the total duration of the songs, and the reliability of those methods when compared to the real chorus size. The spectrographic investigation appears to provide reliable information on the number of animals participating in the chorusing only when this number is limited to two or three singers. We also found that the Acoustic Complexity Index positively correlated with the real chorus size, showing that an automated analysis of the chorus may provide information about the number of singers. We can state that song duration shows a correlation with the number of emitters but also shows a remarkable variation that remains unexplained. The accuracy of the estimates can reflect the high variability in chorus size, which could be affected by group composition, season and context. In future research, a greater focus on analyzing frequency change occurring during these collective vocal displays should improve our ability to detect individuals and allow a finer tuning of the acoustic methods that may serve for monitoring chorusing mammals.
Crunchant A. S., Borchers D., Kühl H., Piel A. (2020): Listening and watching: Do camera traps or acoustic sensors more efficiently detect wild chimpanzees in an open habitat?. Methods in Ecology and Evolution 11: 542-552.
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With one million animal species at risk of extinction, there is an urgent need to regularly monitor threatened species. However, in practice this is challenging, especially with wide-ranging, elusive and cryptic species or those that occur at low density. Here we compare two non-invasive methods, passive acoustic monitoring (n = 12) and camera trapping (n = 53), to detect chimpanzees Pan troglodytes in a savanna-woodland mosaic habitat at the Issa Valley, Tanzania. With occupancy modelling we evaluate the efficacy of each method, using the estimated number of sampling days needed to establish chimpanzee absence with 95% probability, as our measure of efficacy. Passive acoustic monitoring was more efficient than camera trapping in detecting wild chimpanzees. Detectability varied over seasons, likely due to social and ecological factors that influence party size and vocalization rate. The acoustic method can infer chimpanzee absence with less than 10 days of recordings in the field during the late dry season, the period of highest detectability, which was five times faster than the visual method. Despite some technical limitations, we demonstrate that passive acoustic monitoring is a powerful tool for species monitoring. Its applicability in evaluating presence/absence, especially but not exclusively for loud call species, such as cetaceans, elephants, gibbons or chimpanzees provides a more efficient way of monitoring populations and inform conservation plans to mediate species-loss.
Anders F., Kalan A. K., Kühl H. S., Fuchs M. (2021): Compensating class imbalance for acoustic chimpanzee detection with convolutional recurrent neural networks. Ecological Informatics 65: 101423.
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Automatic detection systems are important in passive acoustic monitoring (PAM) systems, as these record large amounts of audio data which are infeasible for humans to evaluate manually. In this paper we evaluated methods for compensating class imbalance for deep-learning based automatic detection of acoustic chimpanzee calls. The prevalence of chimpanzee calls in natural habitats is very rare, i.e. databases feature a heavy imbalance between background and target calls. Such imbalances can have negative effects on classifier performances. We employed a state-of-the-art detection approach based on convolutional recurrent neural networks (CRNNs). We extended the detection pipeline through various stages for compensating class imbalance. These included (1) spectrogram denoising, (2) alternative loss functions, and (3) resampling. Our key findings are: (1) spectrogram denoising operations significantly improved performance for both target classes, (2) standard binary cross entropy reached the highest performance, and (3) manipulating relative class imbalance through resampling either decreased or maintained performance depending on the target class. Finally, we reached detection performances of 33% F1 for drumming and 5% F1 for vocalization, which is a >7 fold increase compared to previously published results. We conclude that supporting the network to learn decoupling noise conditions from foreground classes is of primary importance for increasing performance.
Dufourq E., Durbach I., Hansford J. P., Hoepfner A., Ma H., Bryant J. V., Stender C. S., Li W., Liu Z., Chen Q., Zhou Z., Turvey S. T. (2021): Automated detection of Hainan gibbon calls for passive acoustic monitoring. Remote Sensing in Ecology and Conservation 7: 475-487.
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Extracting species calls from passive acoustic recordings is a common preliminary step to ecological analysis. For many species, particularly those occupying noisy, acoustically variable habitats, the call extraction process continues to be largely manual, a time-consuming and increasingly unsustainable process. Deep neural networks have been shown to offer excellent performance across a range of acoustic classification applications, but are relatively underused in ecology. We describe the steps involved in developing an automated classifier for a passive acoustic monitoring project, using the identification of calls of the Hainan gibbon Nomascus hainanus, one of the world’s rarest mammal species, as a case study. This includes preprocessing—selecting a temporal resolution, windowing and annotation; data augmentation; processing—choosing and fitting appropriate neural network models; and post-processing—linking model predictions to replace, or more likely facilitate, manual labelling. Our best model converted acoustic recordings into spectrogram images on the mel frequency scale, using these to train a convolutional neural network. Model predictions were highly accurate, with per-second false positive and false negative rates of 1.5% and 22.3%. Nearly all false negatives were at the fringes of calls, adjacent to segments where the call was correctly identified, so that very few calls were missed altogether. A post-processing step identifying intervals of repeated calling reduced an 8-h recording to, on average, 22 min for manual processing, and did not miss any calling bouts over 72 h of test recordings. Gibbon calling bouts were detected regularly in multi-month recordings from all selected survey points within Bawangling National Nature Reserve, Hainan. We demonstrate that passive acoustic monitoring incorporating an automated classifier represents an effective tool for remote detection of one of the world’s rarest and most threatened species. Our study highlights the viability of using neural networks to automate or greatly assist the manual labelling of data collected by passive acoustic monitoring projects. We emphasize that model development and implementation be informed and guided by ecological objectives, and increase accessibility of these tools with a series of notebooks that allow users to build and deploy their own acoustic classifiers.
Pérez‐Granados C., Schuchmann K. L. (2021): Passive acoustic monitoring of the diel and annual vocal behavior of the Black and Gold Howler Monkey. American Journal of Primatology 83: e23241.
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Passive acoustic monitoring, when coupled with automated signal recognition software, allows researchers to perform simultaneous monitoring at large spatial and temporal scales. This technique has been widely used to monitor cetaceans, bats, birds, and anurans but rarely applied to monitor primates. Here, we evaluated the effectiveness of passive acoustic monitoring and automated signal recognition software for detecting the presence and monitoring the roaring behavior of the Black and Gold Howler Monkey (Alouatta caraya) over a complete annual cycle at one site in the Brazilian Pantanal. The diel pattern of roaring activity was unimodal, with high vocal activity around dawn. The howler monkey showed a clear seasonal pattern of roaring activity, with most of the roars detected during the wet season (74.9%, peak activity during November and December). The maximum vocal activity occurred during the period of maximum flowering and fruit production in the study area, suggesting a potential role of roaring in defending major feeding sites, which is in agreement with the findings of previous studies on the species. However, we cannot rule out the possibility that roaring may serve different purposes. Vocal activity was negatively associated with relative air humidity, which might be related to lower vocal activity on wetter and rainy days, while vocal activity was not related to minimum air temperature. Automated signal recognition software allowed us to detect the species in 89% of the recordings in which it was vocally active, but with a reduced time cost, since the time investment for data analyses was 2% of recording time. The good performance of the recognizer might be related to the long and loud roars of the howler monkey. Further research should be performed to evaluate the effectiveness of automated signal recognition for detecting the calls of different species of primates and under different environmental conditions.
Spaan D., Di Fiore A., Rangel-Rivera C. E., Hutschenreiter A., Wich S., Aureli F. (2022): Detecting spider monkeys from the sky using a high-definition RGB camera: a rapid-assessment survey method?. Biodiversity and Conservation 31: 479-496.
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Commercial, off-the-shelf, multirotor drones are increasingly employed to survey wildlife due to their relative ease of use and ability to cover areas quicker than traditional methods. Such drones fitted with high-resolution visual spectrum (RGB) cameras are an appealing tool for wildlife biologists. However, evaluations of the application of drones with RGB cameras for monitoring large-bodied arboreal mammals are largely lacking. We aimed to assess whether Geoffroy’s spider monkeys (Ateles geoffroyi) could be detected in RGB videos collected by drones in tropical forests. We performed 77 pre-programmed grid flights with a DJI Mavic 2 Pro drone at a height of 10 m above the maximum canopy height covering 45% of a 1-hectare polygon per flight. We flew the drone directly over spider monkeys who had just been sighted from the ground, detecting monkeys in 85% of 20 detection test flights. Monkeys were detected in 17% of 18 trial flights over areas of known high relative abundance. We never detected monkeys in 39 trial flights over areas of known low relative abundance. Proportion of spider monkey detections during drone flights was lower than other commonly employed survey methods. Agreement between video-coders was high. Overall, our results suggest that with some changes in our research design, multirotor drones with RGB cameras might be a viable survey method to determine spider monkey presence in closed-canopy forest, although its applicability for rapid assessments of arboreal mammal species′ distributions seems currently unfeasible. We provide recommendations to improve survey design using drones to monitor arboreal mammal populations.
Lawson J., Rizos G., Jasinghe D., Whitworth A., Schuller B., Banks-Leite C. (2023): Automated acoustic detection of Geoffroy’s spider monkey highlights tipping points of human disturbance. Proceedings of the Royal Society B 290: 20222473.
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As more land is altered by human activity and more species become at risk of extinction, it is essential that we understand the requirements for conserving threatened species across human-modified landscapes. Owing to their rarity and often sparse distributions, threatened species can be difficult to study and efficient methods to sample them across wide temporal and spatial scales have been lacking. Passive acoustic monitoring (PAM) is increasingly recognized as an efficient method for collecting data on vocal species; however, the development of automated species detectors required to analyse large amounts of acoustic data is not keeping pace. Here, we collected 35 805 h of acoustic data across 341 sites in a region over 1000 km2 to show that PAM, together with a newly developed automated detector, is able to successfully detect the endangered Geoffroy’s spider monkey (Ateles geoffroyi), allowing us to show that Geoffroy’s spider monkey was absent below a threshold of 80% forest cover and within 1 km of primary paved roads and occurred equally in old growth and secondary forests. We discuss how this methodology circumvents many of the existing issues in traditional sampling methods and can be highly successful in the study of vocally rare or threatened species. Our results provide tools and knowledge for setting targets and developing conservation strategies for the protection of Geoffroy’s spider monkey.
Ravaglia D., Ferrario V., De Gregorio C., Carugati F., Raimondi T., Cristiano W., Torti V., Hardenberg A. V., Ratsimbazafy J., Valente D., Giacoma C. (2023): There you are! Automated detection of indris’ songs on features extracted from passive acoustic recordings. Animals 13: 241.
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The growing concern for the ongoing biodiversity loss drives researchers towards practical and large-scale automated systems to monitor wild animal populations. Primates, with most species threatened by extinction, face substantial risks. We focused on the vocal activity of the indri (Indri indri) recorded in Maromizaha Forest (Madagascar) from 2019 to 2021 via passive acoustics, a method increasingly used for monitoring activities in different environments. We first used indris’ songs, loud distinctive vocal sequences, to detect the species’ presence. We processed the raw data (66,443 10-min recordings) and extracted acoustic features based on the third-octave band system. We then analysed the features extracted from three datasets, divided according to sampling year, site, and recorder type, with a convolutional neural network that was able to generalise to recording sites and previously unsampled periods via data augmentation and transfer learning. For the three datasets, our network detected the song presence with high accuracy (>90%) and recall (>80%) values. Once provided the model with the time and day of recording, the high-performance values ensured that the classification process could accurately depict both daily and annual habits of indris’ singing pattern, critical information to optimise field data collection. Overall, using this easy-to-implement species-specific detection workflow as a preprocessing method allows researchers to reduce the time dedicated to manual classification.
Zambolli A. H., Manzano M. C. R., Honda L. K., Rezende G. C., Culot L. (2023): Performance of autonomous recorders to detect a cryptic and endangered primate species, the black lion‐tamarin (Leontopithecus chrysopygus). American Journal of Primatology 85: e23454.
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Information about species distribution is important for conservation but the monitoring of populations can demand a high sampling effort with traditional methods (e.g., line transects, sound playback) that are poorly efficient for cryptic primates, such as the black lion tamarin (Leontopithecus chrysopygus). Here we investigated the effectiveness of passive acoustic monitoring (PAM) as an alternative method to identify the presence of vocalizing lion tamarins in the wild. We aimed to: (1) determine the maximum distance at which autonomous recorders (Song Meter 3) and Raven Pro acoustic software can respectively detect and identify lion tamarin long calls emitted by two captive subjects (ex situ study); and (2) determine the sampling effort required to confirm the presence of the species in the wild (in situ study). In captive settings, we recorded lion tamarin long calls with one to two autonomous recorders operating at increasing distances from the animals’ enclosure (8−202 m). In a 515 ha forest fragment, we deployed 12 recorders in a grid, 300 m apart from each other, within the estimated 100 ha home range of one group, and let them record for 10 consecutive days, totaling 985 h. In the ex situ study, hand-browsing of spectrograms yielded 298 long calls emitted from 8 to 194 m, and Raven’s Template Detector identified 54.6% of them, also emitted from 8 to 194 m. In the in situ study, we manually counted 1115 long calls, and the Raven’s Template Detector identified 44.75% of them. Furthermore, the presence of lion tamarins was confirmed within 1 day using four randomly sorted recorders, whereas 5 days on average were necessary with only one device. While specific protocols still need to be developed to determine primate population size using this technology, we concluded that PAM is a promising tool when considering long term costs and benefits.
RABBITS, HARES, AND PIKAS
Adams J. R., Goldberg C. S., Bosworth W. R., Rachlow J. L., Waits L. P. (2011): Rapid species identification of pygmy rabbits (Brachylagus idahoensis) from faecal pellet DNA. Molecular Ecology Resources 11: 808-812.
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The pygmy rabbit (Brachylagus idahoensis) is a small lagomorph of the western United States that specializes in sagebrush (Artemisia spp.) habitat. Intensive habitat loss and modification have increased the vulnerability of pygmy rabbit populations, but the current geographic distribution and population status remain unclear. To aid in detection and population monitoring, we developed a species identification test that uses mitochondrial DNA species-specific primers to distinguish among six sympatric lagomorph species using DNA isolated from faecal pellets. Applying this test, we successfully identified the species of origin for all pellet samples that produced a positive PCR result (77% of 283 pellets collected). Pellets collected during the winter (December–February) had higher PCR success rate (93%) than pellets collected at other times of the year (72%). This test, using non-invasive genetic sampling of faecal pellets, provides an efficient method for assessing site occupancy and distribution of pygmy rabbits and other lagomorphs across large geographic areas.
McCarthy J. L., Fuller T. K., McCarthy K. P., Wibisono H. T., Livolsi M. C. (2012): Using camera trap photos and direct sightings to identify possible refugia for the Vulnerable Sumatran striped rabbit Nesolagus netscheri. Oryx 46: 438-441.
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The endemic Sumatran striped rabbit Nesolagus netscheri, categorized as Vulnerable on the IUCN Red List, is one of the rarest lagomorphs and little is known about its ecology, status or distribution. After nearly a decade with no published sightings, new camera-trap photos have been taken and observations made in Bukit Barisan Seletan and Kerinci Seblat National Parks, renewing interest in this rare species. We suggest that Bukit Barisan Seletan National Park is an ideal location to initiate a much needed ecological study of the species. Documentation and protection of a population in this Park would facilitate refinement of study techniques applicable to other areas in Sumatra, including Kerinci Seblat National Park, and thus facilitate an assessment of the status and distribution of the species. We believe that in light of ongoing encroachment and deforestation in many of Sumatra’s protected areas it is important to implement immediate conservation initiatives in both parks to ensure the persistence of these known populations.
Torstrom S. M., Adams J. R., Waits L. P. (2013): Detecting pygmy rabbits (Brachylagus idahoensis) using DNA extracted from fecal pellets of mixed‐species groups. Wildlife Society Bulletin 37: 603-607.
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Noninvasive genetic sampling is an essential tool for studying elusive and endangered species. However, the DNA from noninvasive genetic sampling tends to be low in quantity and quality, which leads to poor DNA amplification. Using fecal pellets of pygmy rabbits (Brachylagus idahoensis) collected in February, March, and November 2011, we tested a possible solution of increasing the amount of sample by combining multiple pellet groups during DNA extraction. One potential drawback of this approach is accidental mixing of samples from multiple species. This study evaluates the mitochondrial DNA (mtDNA) species identification success rate for pygmy rabbit (PY) fecal DNA when mixed with eastern cottontail (Sylvilagus floridanus; EC) fecal pellet DNA at lower frequencies (1PY:3EC and 2PY:6EC) and eastern cottontail or mountain cottontail (S. nuttalli) pellet samples at an equal frequency (4:4). We found that successful detection of pygmy rabbit DNA using a species-specific mtDNA polymerase chain reaction (PCR) test varies from 0% to 95% depending on the competing species and PCR protocol. From these results, we conclude that if samples are unintentionally mixed, the species with a greater number of pellets within the sample will be more likely to be detected. Also, if pellet piles are intentionally mixed to reduce sampling cost, the protocol should be optimized to maximize DNA amplification for the focal species; however, there will be reduced detection rates depending on the quality and quantity of the focal species DNA within the sample.
Buglione M., Petrelli S., Notomista T., de Filippo G., Gregorio R., Fulgione D. (2020): Who is who? High Resolution Melting analysis to discern between hare species using non-invasive sampling. Conservation Genetics Resources 12: 727-732.
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Identification of the species is a crucial step in many ecological studies. Sometimes, this could become a challenge, because of animal elusive behavior, low density population or for sympatric species leaving similar signs that are impossible to discriminate based only on their morphology. Here, we set up non-invasive molecular method to discern between the Italian hare (Lepus corsicanus) and the European hare (Lepus europaeus) using High Resolution Melting assay on fecal DNA, for the first time on these species. The Italian hare is endemic of the Central-Southern Italy and Sicily and it is classified vulnerable by the International Union for Conservation of Nature. Our procedure could be a useful tool to help conservation and management strategies, mainly in areas where the Italian hare and the European hare live in sympatry. The 9.5% of the peninsular range distribution of the European hare is took up by the range of the Italian hare. Our workflow allows sure species discrimination, rapidly and inexpensively (in one day at least 36 samples could be processed at costs of about 259 euros, including both DNA extractions and HRM run), also when large numbers of samples have to be processed. Moreover, our method could be widely applicable to other Lepus and/or mammalian species with similar concerns, by small adjustments to the protocol and its further validation, focusing on primes and corresponding HRM annealing temperature.
Cox T. E., Matthews R., Halverson G., Morris S. (2021): Hot stuff in the bushes: Thermal imagers and the detection of burrows in vegetated sites. Ecology and Evolution 11: 6406-6414.
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Thermal imaging technology is a developing field in wildlife management. Most thermal imaging work in wildlife science has been limited to larger ungulates and surface-dwelling mammals. Little work has been undertaken on the use of thermal imagers to detect fossorial animals and/or their burrows. Survey methods such as white-light spotlighting can fail to detect the presence of burrows (and therefore the animals within), particularly in areas where vegetation obscures burrows. Thermal imagers offer an opportunity to detect the radiant heat from these burrows, and therefore the presence of the animal, particularly in vegetated areas. Thermal imaging technology has become increasingly available through the provision of smaller, more cost-effective units. Their integration with drone technology provides opportunities for researchers and land managers to utilize this technology in their research/management practices. We investigated the ability of both consumer (<AUD$20,000) and professional imagers (>AUD$65,000) mounted on drones to detect rabbit burrows (warrens) and entrances in the landscape as compared to visual assessment. Thermal imagery and visual inspection detected active rabbit warrens when vegetation was scarce. The presence of vegetation was a significant factor in detecting entrances (p < .001, α = 0.05). The consumer imager did not detect as many warren entrances as either the professional imager or visual inspection (p = .009, α = 0.05). Active warren entrances obscured by vegetation could not be accurately identified on exported imagery from the consumer imager and several false-positive detections occurred when reviewing this footage. We suggest that the exportable frame rate (Hz) was the key factor in image quality and subsequent false-positive detections. This feature should be considered when selecting imagers and suggest that a minimum export rate of 30 Hz is required. Thermal imagers are a useful additional tool to aid in identification of entrances for active warrens and professional imagers detected more warrens and entrances than either consumer imagers or visual inspection.
Psiroukis V., Malounas I., Mylonas N., Grivakis K. E., Fountas S., Hadjigeorgiou I. (2021): Monitoring of free-range rabbits using aerial thermal imaging. Smart Agricultural Technology 1: 100002.
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Unmanned Aerial Vehicles (UAV) imagery is a mature technology, which has found use in a number of applications in agriculture and environmental sciences. However, its application for monitoring and classification of livestock and wild animals has not yet been developed. This study presents a robust methodology to count wild and free-range rabbits and monitor their population. The aims of this study were to 1) test the capacity of the methodology in counting small nocturnal animals such as rabbits in the field, 2) assess the rabbit’s density at different sites and different periods of the year and 3) record the temporal pattern of rabbits’ activity during the night hours, with the overall aim to provide a reliable and accurate tool in management studies. For this purpose, a UAV equipped with a thermal camera was used to perform night flights on the island of Lemnos, scanning selected sites and collecting aerial nadir thermal imagery data of the ground. The derived thermal images were analysed using deep learning techniques towards counting the individual animals in each image and the results were compared with manual counting conducted by a researcher. The results revealed that the deep learning approach for automated counting and rabbit recognition overall achieved comparable results to physical counting, with the final model yielding an F1-score of 0.87. However, there were differences between seasons in the methods’ accuracy. This method could be a helpful tool in assessing populations of small nocturnal animals and other free-range livestock animals.
Millar C. I., Smith A. T. (2022). Return of the pika: American pikas re‐occupy long‐extirpated, warm locations. Ecology and Evolution 12: e9295.
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American pikas (Ochotona princeps), small mammals related to rabbits, occur in mountainous regions of western North America, where they live in shattered-rock habitats (talus). Aspects of their physiology and life history create situations that appear to put pikas at risk from warming climates. Some low-elevation, warm sites that historically harbored pikas have become extirpated, and the assumption is that these will not be re-colonized under current climate trends. Unexpectedly, in 2021, we found that pikas had re-colonized two very warm, low-elevation, dry sites in eastern California, USA, in the Bodie Mountains and Mono Craters. Resident pikas appear to have been absent at both sites for ≥10 years. These findings suggest that pikas, which are normally diurnally active, are able to overcome thermal dispersal barriers and re-colonize long-extirpated sites, perhaps by moving during cool nights. Our data also highlight the often unrecognized suitability of pika habitat in warm regions where the interiors of taluses can remain stably cool even when external air temperatures are hot.
Povlsen P., Linder A. C., Larsen H. L., Durdevic P., Arroyo D. O., Bruhn D., Pertoldi C., Pagh S. (2022): Using drones with thermal imaging to estimate population counts of European hare (Lepus europaeus) in Denmark. Drones 7: 5.
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Drones equipped with thermal cameras have recently become readily available, broadening the possibilities for monitoring wildlife. The European hare (Lepus europaeus) is a nocturnal mammal that is closely monitored in Denmark due to populations declining since the mid-1900s. The limitations of current population-assessment methods, such as, spotlight counts and hunting game statistics, could be overcome by relying on drone surveys with thermal imaging for population counts. The aim of this study was to investigate the use of a DJI Mavic 2 Enterprise Advanced drone with thermal imaging as a tool for monitoring the Danish hare population. Multiple test flights were conducted over agricultural areas in Denmark in spring 2022, testing various flight altitudes, camera settings, and recording methods. The test flights were used to suggest a method for identifying and counting hares. The applied use of this methodology was then evaluated through a case survey that had the aim of identifying and counting hares over an agricultural area of 242 ha. Hares could be detected with thermal imaging at flight altitudes up to 80 m, and it was possible to fly as low as 40 m without observing direct behaviorial changes. Thermal images taken at these altitudes also provided enough detail to differentiate between species, and animal body size proved to be a good species indicator. The case study supported the use of thermal imaging-based drone surveys to identify hares and conduct population counts, thus indicating the suggested methodology as a viable alternative to traditional counting methods.
Bentze C., Burningham H., Magee E. (2023): Down the rabbit-hole: satellite-based analysis of spatiotemporal patterns in wild European rabbit burrows for better coastal dune management. Journal of Coastal Conservation 27: 61.
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Coastal dune systems in northwest Europe are facing conflicting challenges associated with climate change and human interventions in landuse and landscape management. Research over the last decade has highlighted a global stabilisation pattern in coastal dunes, fuelling long-standing debates surrounding conservation approaches. Dune erosion can be considered an important process within a naturally functioning dune system, but also a management challenge. The fossorial behaviour of burrowing mammals within coastal dunes is one driver of erosion that has long tested our perspectives on natural processes within dunes, but is understudied in coastal dune conservation and research. This is particularly the case for the wild European rabbit, a common naturalised invader of dune systems. In this study, the spatial distribution of wild European rabbits inhabiting a coastal dune system in Ireland is explored through geospatial mapping approaches using satellite and drone imagery, supported by spatial analyses and statistics. This reproducible approach has shown that rabbit activity fluctuates at inter-annual time scales that infer aligned changes in population, and that burrows clearly cluster in fixed dune habitats on landward slopes toward the rear of the dune system.
RODENTS
Rosell F., Cross H. B., Johnsen C. B., Sundell J., Zedrosser A. (2019): Scent-sniffing dogs can discriminate between native Eurasian and invasive North American beavers. Scientific Reports 9: 15952.
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The invasion of a species can cause population reduction or extinction of a similar native species due to replacement competition. There is a potential risk that the native Eurasian beaver (Castor fiber) may eventually be competitively excluded by the invasive North American beaver (C. canadensis) from areas where they overlap in Eurasia. Yet currently available methods of census and population estimates are costly and time-consuming. In a laboratory environment, we investigated the potential of using dogs (Canis lupus familiaris) as a conservation tool to determine whether the Eurasian or the North American beaver is present in a specific beaver colony. We hypothesized that dogs can discriminate between the two beaver species, via the odorant signal of castoreum from males and females, in two floor platform experiments. We show that dogs detect scent differences between the two species, both from dead beaver samples and from scent marks collected in the field. Our results suggest that dogs can be used as an “animal biosensor” to discriminate olfactory signals of beaver species, however more tests are needed. Next step should be to test if dogs discern between beaver species in the field under a range of weather conditions and habitat types and use beaver samples collected from areas where the two species share the same habitat. So far, our results show that dogs can be used as a promising tool in the future to promote conservation of the native beaver species and eradication of the invasive one. We therefore conclude that dogs may be an efficient non-invasive tool to help conservationist to manage invasive species in Europe, and advocate for European wildlife agencies to invest in this new tool.
Diggins C. A., Gilley L. M., Kelly C. A., Ford W. M. (2020): Using ultrasonic acoustics to detect cryptic flying squirrels: effects of season and habitat quality. Wildlife Society Bulletin 44: 300-308.
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New technologies allow for more efficient and effective monitoring of rare or elusive species. However, standardizing protocol to ensure high detection rates is important prior to widespread use of a new technique. The use of ultrasonic acoustic detectors to survey for flying squirrels (Glaucomys spp.) is a novel method that is more efficient than traditional methods. However, certain methodologies for this technique still need to be refined. During 2015, we conducted a seasonal and habitat quality study on the endangered Carolina northern flying squirrel (G. sabrinus coloratus) in western North Carolina, USA. Our seasonal study examined differences in probability of detection (POD) and latency to detection (LTD) at 30 high-quality sites across 10 survey nights in spring, summer, and autumn. The habitat quality study focused on POD and LTD among 15 sites with varying habitat quality (5 High, 5 Medium, 5 Low) across 20 survey nights. We found POD similar between seasons, with POD 15–20% greater during spring. The LTD was comparable among seasons. We found that POD and LTD varied at sites with different habitat quality. The POD was similar between High and Medium sites (0.26 ± 0.04 SE and 0.29 ± 0.05, respectively), but greater than Low sites (0.02 ± 0.02). The LTD was not different among sites with differing habitat quality, although LTD at High sites was 2.7 and 4.5 times lower than Medium and Low sites, respectively. Trill calls, the most distinctive species-specific call type produced by species of flying squirrels, was recorded at greater rates in spring versus other times of the year. Our results indicate flying squirrels can be surveyed during any season, although habitat quality needs to be considered when determining survey length. For Carolina northern flying squirrel, the optimal time to perform acoustic surveys is during the spring season for 6–10 survey nights at sites with high or medium habitat quality.
Roviani D., Artioli P., Bertolino S. (2020): Evaluating the effectiveness of footprint platforms to detect invasive mammals: coypu (Myocastor coypus) as a case study. Mammalian Biology 100: 213-218.
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Effective and easy-to-apply monitoring techniques are necessary to detect alien species at their first stage of invasion, allowing rapid removal or delimitation of the invaded range for eradication or control actions. Monitoring tools should be effective in detecting the target species, reduce false absences and allow an early detection. The coypu (Myocastor coypus) is a large semi-aquatic rodent native to subtropical and temperate South America, introduced all over the world for its valuable fur. We tested tracking plates in the framework of a coypu occupancy study to take into account false absences and define a standardized monitoring protocol for the species with a limited engagement of staff. We set 60 linear transects, each with 3 tracking plates, along artificial water bodies within the rice district in northwestern Italy and checked them for six consecutive days. For the analyses, we fitted single-season occupancy models to our detection history data. We detected coypu presence at least once in 29 out of the 60 investigated transects (48%). When modeling occupancy and detection probability constant in time and space, the estimate Ψ was 0.48 and detection probability p was 0.60. A minimum of four consecutive visits to the transects provided reliable detection. Coypu’s probability of presence was significantly driven by the amount of surface covered by rice plantations around the investigated water courses. The proposed method may function as a tool for the rapid detection of coypu on large-scale monitoring projects and in case of new colonization, and as a basis for subsequent prompt control actions.
Iso-Touru T., Tabell J., Virta A., Kauhala K. (2021): A non-invasive, DNA-based method for beaver species identification in Finland. Wildlife Biology 2021: wlb.00808.
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For the ability to control an invasive species and to protect an ecologically similar native species it is essential to map the exact distributions of both species. This is difficult if the species are so morphologically similar that their identification in the field is almost impossible. In Finland, the invasive North American beaver Castor canadensis is spreading towards the range of the native Eurasian beaver Castor fiber and at present, these species are partly sympatric. Effective management of these morphologically similar species requires an efficient method for species identification, ideally one that is non-invasive. Non-invasive genetic methods are used in a wide variety of wildlife species, for example in the research of large carnivores. Feces are a good source of DNA for terrestrial animals, but for the semi-aquatic animals like beavers, feces are not the best option. However, environmental DNA (eDNA) has been successfully used to detect species non-invasively in aquatic and terrestrial environments. We developed a non-invasive, eDNA-based method to map the distribution of the beaver species in Finland and to investigate within-species genetic diversity. The eDNA was obtained from the feed remains (wood chips) from beaver forage sites. With the help of Citizen science, wood chip samples were collected from different parts of Finland. We used our eDNA method to identify the ranges of both beaver species. Additionally, the presence of Eurasian beavers in south-east Finland was proven for the first time. Our non-invasive eDNA method is an effective way to accurately identify the ranges of both beaver species and will allow for the control of the invasive North American beaver and conservation of the native Eurasian beaver in Finland.
Priestley V., Allen R., Binstead M., Arnold R., Savolainen V. (2021): Quick detection of a rare species: forensic swabs of survey tubes for hazel dormouse Muscardinus avellanarius urine. Methods in Ecology and Evolution 12: 818-827.
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Effective conservation decisions rely on accurate survey data, but methods can be resource‐intensive and risk false negative results. Presence of the threatened hazel dormouse (England, UK) is typically confirmed by looking for its nest in survey tubes, over a 6‐month period. As an alternative, environmental DNA (eDNA) surveys have proven benefits in efficiency and accuracy for other taxa, but generally rely on the extraction and amplification of DNA from water, soil or sediment, which are not yet dependable samples for rare terrestrial mammals like the hazel dormouse. At a known occupancy site, paper‐lined survey tubes were used to capture a DNA sample. Like other species of rodent, the hazel dormouse excretes urine freely, and this was highlighted by ultraviolet torch, swabbed from the paper, extracted and hazel dormouse eDNA amplified by quantitative polymerase chain reaction (qPCR). Hazel dormouse presence was confirmed in this way in three out of 50 tubes within 8 days. Detection by conventional nest survey occurred on day 63 when a hazel dormouse nest was found in a single survey tube. We calculate that amplification of eDNA left behind in tubes increased survey efficiency here at least 12‐fold. In this study we demonstrate that eDNA swabbed from a clean substrate placed in survey apparatus can significantly hasten the detection of a rare species. This method has the potential to broaden the application of eDNA to other terrestrial vertebrates, including surveys at large spatiotemporal scales. Beyond presence/absence, the non‐invasive DNA sample could also offer insights into sex ratio, abundance, behaviour and population genetics.
Aylward C. M., Grahn R. A., Barthman-Thompson L. M., Kelt D. A., Sacks B. N., Statham M. J. (2022): A novel noninvasive genetic survey technique for small mammals. Journal of Mammalogy 103: 1441-1447.
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Noninvasive genetic surveys, often conducted by collecting fecal samples, have become a popular tool for surveying wildlife, but have primarily been applied to species with large and conspicuous scat. Although many small mammals are threatened, endangered, or data deficient, noninvasive genetic surveys have rarely been applied due to the challenges of detecting their inconspicuous fecal pellets. As part of a broader study of the endangered salt marsh harvest mouse (Reithrodontomys raviventris), we developed a noninvasive genetic survey technique for the community of small mammals in their putative range. We designed bait stations to passively collect fecal samples from rodents, and developed a multiplex primer set that amplified unique fragment sizes for salt marsh harvest mice and four other sympatric species. We tested the primer set on positive controls and on fecal pellets collected from bait stations at two regularly monitored field sites known to have very different densities of salt marsh harvest mice. The multiplex amplified DNA from all five species, even when all five species were present in a single sample. A positive species identification was made for all field-collected samples, and 43% of these field-collected samples had multispecies detections. The combination of bait stations and genetic species identification proved to be an effective means of noninvasively surveying small mammals in potential salt marsh harvest mouse habitat. The sampling technique should be applicable to a wide variety of small mammals in other systems.
Diggins C. A., Lipford A., Farwell T., Eline D. V., Larose S. H., Kelly C. A., Clucas B. (2022): Can camera traps be used to differentiate species of North American flying squirrels?. Wildlife Society Bulletin 46: e1323.
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Camera traps are becoming an increasingly important tool to survey wildlife populations. However, the application of camera trapping for reliable species identification between nondistinctive, morphologically similar sympatric species is untested for most small mammals, including North American flying squirrels (Glaucomys spp.). Camera traps are a successful monitoring technique where flying squirrel species are allopatric, however there are zones of sympatry between Humboldt’s flying squirrel (HFS, G. oregonensis) and northern flying squirrel (NFS, G. sabrinus) in the Pacific Northwest and NFS and southern flying squirrels (SFS, G. volans) in eastern North America. We used camera trap data collected during flying squirrel surveys in 2013–2020 at 59 sites in California, North Carolina, and Virginia, USA, to determine if a reliable method could be used to differentiate the species. With a subset of 100 high-quality, independent capture events per species (50 of dorsal views, 50 of lateral views), we used body measurements and pelage characteristics to differentiate species using random forest classification models. Our models predicted species identification accuracy rates of 90.9% for dorsal views and 68.2% for lateral views. Species misclassification rates between HFS and NFS were 23.5% for dorsal views and 26.5% for lateral views, whereas misclassification rates between NFS and SFS were 16.6% for dorsal views and 5.7% for lateral views. Although misclassification rates were lower than we expected between NFS and SFS, we are cautious about recommending camera trapping as opposed to ultrasonic acoustics for North American flying squirrel species identification, especially in areas of species sympatry due to potential false positive rates and high numbers of unusable images. However, camera trap settings and white-flash photography should be explored to determine their potential for improving flying squirrel species classification rates and the percentage of usable photos.
Lyman J. A., Sanchez D. E., Hershauer S. N., Sobek C. J., Chambers C. L., Zahratka J., Walker F. M. (2022): Mammalian eDNA on herbaceous vegetation? Validating a qPCR assay for detection of an endangered rodent. Environmental DNA 4: 1187-1197.
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Vegetation is an underutilized medium for environmental DNA (eDNA) sampling. eDNA methods leveraging water as a substrate exclude application to many terrestrial species. The use of eDNA to detect small mammals can complement current survey approaches (live capturing, track plating, and camera trapping) while reducing risks to the animals. The endangered New Mexico meadow jumping mouse (Zapus hudsonius luteus) is specialized to herbaceous riparian zones, making it an ideal candidate for developing a terrestrial eDNA detection method. We developed a species-specific assay for quantitative real-time PCR, then tested the long-term persistence of jumping mouse eDNA on plant material using four herbaceous day nests collected three to six months after occupancy. We conducted a field trial using sterile cotton swabs at six locations along two occupied streams to evaluate our assay’s capability to detect present-day eDNA. Each of 60 swabs was used to swab a 0.50 m2 area along streamside transects that included vegetation such as forbs, grasses, and sedges. We also opportunistically swabbed plants (n = 9) following visual observation of jumping mice. We determined the limit of detection for both assays are fewer than eight copies per reaction. We detected eDNA in three of four nests. From field trial samples, we successfully detected the species from randomly swabbed vegetation (N = 3), and four of nine swabs from vegetation recently used by individuals. Further work is required to develop a robust survey method using this eDNA detection approach. Our study demonstrated that mammalian eDNA can persist on nest vegetation long after the animal was present, highlighting the promise of using eDNA from plants to detect rare or endangered terrestrial species.
Meheretu Y., Tilahun T., Engdayehu G., Bosma L., Mulualem G., Craig E. W., Bryja J., Steenbergen F. (2022): A snapshot of rodents and shrews of agroecosystems in Ethiopian highlands using camera traps. Mammalia 86: 230-238.
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Considering climate change and high population increase, the conversion of natural habitats into arable land is rising at an alarming rate in the Ethiopian highlands. The impact on the diversity of rodents and shrews is difficult to measure since historical data are often unavailable. However, the relative effects of such land-use changes could be contemplated by comparing with data from similar natural habitats in adjacent areas. Between October to November 2018, we randomly setup 20 infrared camera traps in wheat fields located near Mount Guna at about 3350 m elevation, as part of a large research project investigating the efficacy of rodent repellent botanicals. We recorded six rodent species (Arvicanthis abyssinicus, Dendromus lovati, Dendromus mystacalis, Hystrix cristata, Mus mahomet and Stenocephalemys albipes) and two shrew species (Crocidura cf. baileyi and Crocidura olivieri). A. abyssinicus, H. cristata and S. albipes are known to occur in agricultural fields. D. lovati was recorded from anthropogenic habitat for the first time in this study. The species has been described as rare or difficult to capture with conventional traps. We call for rigorous biodiversity studies and conservation measures in agroecosystems in the Ethiopian highlands to avert further losses in biodiversity and ecosystem services.
Aylward C. M., Barthman-Thompson L., Bean W. T., Kelt D. A., Sacks B. N., Statham M. J. (2023): Patch size and connectivity predict remnant habitat occupancy by an endangered wetland specialist, the salt marsh harvest mouse. Landscape Ecology 38: 2053-2067.
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The area-isolation paradigm of metapopulation theory predicts that larger and more connected patches have a higher probability of occupancy. Although it may be too simplistic for generalist terrestrial mammals, the area-isolation paradigm may be an effective tool for assessing patch-occupancy for habitat specialists. We tested predictions of the area-isolation paradigm for the endangered salt marsh harvest mouse (Reithrodontomys raviventris), a habitat specialist living in highly fragmented salt marsh habitat in the San Francisco Estuary (California, USA). We surveyed for salt marsh harvest mice at 47 marsh patches throughout their range using a non-invasive genetic survey technique. We used occupancy modeling to estimate the effects of patch size, patch connectivity, matrix urbanization, and several habitat characteristics on occupancy probabilities. We evaluated occupancy at both coarse (e.g., among patches) and fine (e.g., within patches) spatial scales. Patch size, connectivity, and matrix urbanization had significant effects on patch-occupancy. Within patches, occupancy was positively related to the presence of high-tide escape vegetation. Our data also revealed the extirpation of several geographically distinct populations, consistent with expectations due to reduced patch sizes and connectivity over the past century. Patterns of salt marsh harvest mouse patch-occupancy were consistent with the area-isolation paradigm. In addition, our models provide important guidelines of patch size and connectivity that can inform habitat conservation and restoration for this endangered species. Specifically, our data suggests that selecting restoration sites that are well-connected may be more beneficial than selecting larger, isolated sites.
Mangan A. M., Kronenberger J. A., Plummer I. H., Wilcox T. M., Piaggio A. J. (2023): Validation of a nutria (Myocastor coypus) environmental DNA assay highlights considerations for sampling methodology. Environmental DNA 5: 391-402.
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Nutria (Myocastor coypus) is a semiaquatic rodent species that is invasive across multiple regions within the United States. Here, we evaluated a qPCR assay previously described for use in Japan for application across invasive populations in the United States. We also compared two environmental DNA sampling methodologies for this assay: field filtration of large volumes of water passed through filters versus direct sampling of small volumes of water. We validated assay specificity, generality, and sensitivity, compared assay performance between two independent laboratories, and successfully tested the assay in situ on a known wild population. The filtration method required fewer samples for environmental DNA detection than direct sampling, but the choice of methods should be assessed based on specific field conditions and time and budget considerations. Our extensive assay validation and comparison across laboratories suggest that the assay is ready to be applied in environmental DNA monitoring of nutria throughout the United States.
Oliveira A., Medinas D., Craveiro J., Milhinhas C., Sabino-Marques H., Mendes T., Spadoni G., Oliveira A., Sousa L. G., Tapisso J. T., Santos S. (2023): Large-scale grid-based detection in occupancy surveys of a threatened small mammal: A comparison of two non-invasive methods. Journal for Nature Conservation 72: 126362.
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Monitoring the status and trends of wildlife is key to understand how species respond to natural and human-derived threats, and to evaluate and improve conservation planning and management. Large-scale, grid-based assessment of species distribution, abundance, and population trends over time is an important component of biodiversity monitoring. However, such assessments still present important challenges related, for instance, to how the choice of the sampling method may affect species detectability and thus, overall data accuracy. Here, we address this issue, focusing on the Cabrera vole (Microtus cabrerae), a threatened small mammal, listed in the Habitats Directive (Annexes II and IV), hence requiring regular evaluation of its population status and trends. We used occupancy modelling to estimate method-specific detection probability of the species over large-scale, grid-based (10 × 10 km2) surveys relying on two non-invasive sampling techniques: sign surveys and owl pellet analysis. Results provided evidence for a greater cost-effectiveness of sign surveys compared to owl pellet analysis for detecting the species in occupancy surveys, suggesting that large-scale population monitoring of Cabrera voles (or other species also producing easily identifiable signs of their presence) may fairly rely on sign-surveys. Overall, our study supported the view that while owl pellet analysis provides a valuable option when the aim is to assess small mammal assemblages (i.e. multiple species) in a region, other complementary methods may be required to increase the detection probability of certain species that because of their secretive behaviour or rarity remain less predated by owls. We thus argue that the choice of the sampling method should be context-dependent and evaluated based on the study aims, the surveyed area (i.e. local factors), the target species (i.e. life history traits) and the available resources. Based on our results we recommend that researchers and managers explore survey-design trade-offs to ensure the proposed designs have sufficient power to detect real population trends.
Peralta D., Vaz-Freire T., Ferreira C., Mendes T., Mira A., Santos S., Alves P. C., Lambin X., Beja P., Paupério J., Pita R. (2023): From species detection to population size indexing: the use of sign surveys for monitoring a rare and otherwise elusive small mammal. European Journal of Wildlife Research 69: 9.
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Monitoring the occupancy and abundance of wildlife populations is key to evaluate their conservation status and trends. However, estimating these parameters often involves time and resource-intensive techniques, which are logistically challenging or even unfeasible for rare and elusive species that occur patchily and in small numbers. Hence, surveys based on field identification of signs (e.g. faeces, footprints) have long been considered a cost-effective alternative in wildlife monitoring, provided they produce reliable detectability and meaningful indices of population abundance. We tested the use of sign surveys for monitoring rare and otherwise elusive small mammals, focusing on the Cabrera vole (Microtus cabrerae) in Portugal. We asked how sampling intensity affects true positive detection of the species, and whether sign abundance is related to population size. We surveyed Cabrera voles’ latrines in 20 habitat patches known to be occupied, and estimated ‘true’ population size at each patch using DNA-based capture-recapture techniques. We found that a searching rate of ca. 3 min/250m2 of habitat based on adaptive guided transects was sufficient to provide true positive detection probabilities > 0.85. Sign-based abundance indices were at best moderately correlated with estimates of ‘true’ population size, and even so only for searching rates > 12 min/250m2. Our study suggests that surveys based on field identification of signs should provide a reliable option to estimate occupancy of Cabrera voles, and possibly for other rare or elusive small mammals, but cautions should be exercised when using this approach to infer population size. In case of practical constraints to the use of more accurate methods, a considerable sampling intensity is needed to reliably index Cabrera voles’ abundance from sign surveys.
Tuomi M. W., Murguzur F. J., Hoset K. S., Soininen E. M., Vesterinen E., Utsi T. A., Kaino S., Bråthen K. A. (2023): Novel frontier in wildlife monitoring: identification of small rodent species from faecal pellets using Near-Infrared Reflectance Spectroscopy (NIRS). Ecology and Evolution 13: e9857.
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Small rodents are prevalent and functionally important across the world’s biomes, making their monitoring salient for ecosystem management, conservation, forestry, and agriculture. There is a growing need for cost-effective and noninvasive methods for large-scale, intensive sampling. Fecal pellet counts readily provide relative abundance indices, and given suitable analytical methods, feces could also allow for the determination of multiple ecological and physiological variables, including community composition. In this context, we developed calibration models for rodent taxonomic determination using fecal near-infrared reflectance spectroscopy (fNIRS). Our results demonstrate fNIRS as an accurate and robust method for predicting genus and species identity of five coexisting subarctic microtine rodent species. We show that sample exposure to weathering increases the method’s accuracy, indicating its suitability for samples collected from the field. Diet was not a major determinant of species prediction accuracy in our samples, as diet exhibited large variation and overlap between species. fNIRS could also be applied across regions, as calibration models including samples from two regions provided a good prediction accuracy for both regions. We show fNIRS as a fast and cost-efficient high-throughput method for rodent taxonomic determination, with the potential for cross-regional calibrations and the use on field-collected samples. Importantly, appeal lies in the versatility of fNIRS. In addition to rodent population censuses, fNIRS can provide information on demography, fecal nutrients, stress hormones, and even disease. Given the development of such calibration models, fNIRS analytics could complement novel genetic methods and greatly support ecosystem- and interaction-based approaches to monitoring.
Palencia P., Zanet S., Barroso P., Vada R., Benatti F., Occhibove F., Meriggi F., Ferroglio E. (2024): How abundant is a species at the limit of its distribution range? Crested porcupine Hystrix cristata and its northern population. Ecology and Evolution 14: e10793.
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The crested porcupine (Hystrix cristata) is a rodent present in Africa and southern Europe (Italy exclusively). The Italian population is expanding from the centre to the north and south, but little is known about the species’ abundance. Reliable population density estimates are important for monitoring trends in wildlife populations and for developing effective conservation and management strategies. In this context, we aimed to first report crested porcupine population density on the northern limit of its current distribution range using a non-invasive approach. Specifically, we randomly placed 38 camera traps in an area of 242 km2 in north Italy (Lombardy region), and we applied camera trap distance sampling. We estimated a porcupine density of 0.49 ind·km−2 (±0.33, standard error). The results presented here are the first crested porcupine density estimate accounting for imperfect detection (i.e. species present but not detected). The abundance estimate reported here is fundamental for a better understanding of the species status in Europe and for implementing conservation and management plans.
Stuhler J. D., Portillo‐Quintero C., Goetze J. R., Stevens R. D. (2024): Efficacy of remote sensing technologies for burrow count estimates of a rare kangaroo rat. Wildlife Society Bulletin 48: e1510.
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Effective management of rare species requires an understanding of spatial variation in abundance, which is challenging to estimate. We tested the efficacy of high-resolution imagery to detect burrows of the Texas kangaroo rat (TKR; Dipodomys elator) as a means of estimating abundance across its geographic range. Specifically, we estimated burrow counts using an Unmanned Aerial System (UAS) to collect data from very high-resolution Red–Green–Blue (RGB) imagery and estimate digital elevation (2.5-mm pixel resolution) over active and inactive burrows located on mesquite mounds and anthropogenic features (roadsides, fences, etc.). In 2018, we identified 26 burrow locations on a private ranch in Wichita County, Texas, USA, and characterized burrows based on topography and vegetation density. We found that TKR burrows can only be identified with data of <5 cm pixel resolution, thus eliminating the possibility of using high-resolution imagery data currently available for Texas. Alternatively, we propose that the use of National Agriculture Imagery Program (NAIP) imagery at 0.5- and 0.6-m pixel resolution, in combination with resampled digital elevation data, can provide an effective means for identifying potential TKR burrow locations at the county level. We present 3 different approaches at the county and local scale that combine topographic and vegetation fractional cover information using a weighted overlay approach. The modeling approaches have strong predictive capabilities and can be integrated with UAS data for visual confirmation of active and inactive burrows. We concluded that very high-resolution imagery and topographic information at pixel resolutions <5 cm collected by airborne systems can effectively help locate active TKR burrows. However, to remain cost effective, upscaling to the county level will require reducing the sampling area to the most suitable habitat. Modeling approaches, such as those proposed in this study, can help effectively locate these sampling areas.
Piaggio A. J., Robinson S. J., Shiels A. B., Taylor D. R., Spock D. R., Allira M., Serr M., Klein C. M., Godwin J., Russell J. C., Wilkinson S. (2025): Evaluation of environmental DNA as a surveillance tool for invasive house mice (Mus musculus). Environmental DNA 7: e70069.
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Increasing the success of invasive species management depends on the development, testing, and deployment of new tools. Environmental DNA (eDNA) is an effective tool for monitoring invasive species that can help identify presence/absence, geographical boundaries of invasion, risk pathways, and population connectivity. In particular, understanding the sensitivity of eDNA detection rates to target species density allows calibration of sampling rates. In this study, we take a lab-validated eDNA assay for Mus musculus (house mouse) and test its detection rates at different populations densities for wild-caught, free-ranging M. musculus in a controlled laboratory and an outdoor mesocosm. The goal was to understand both eDNA accumulation after M. musculus is introduced and the persistence of the accumulated eDNA signal in the environment after animals were removed. We found that eDNA signal was detectable within 1 h of a single mouse being introduced and that the signal was detectable for months after in the controlled environment but largely undetectable after 4 days in an outdoor mesocosm. We suggest sampling strategies for post-eradication deployment of eDNA and highlight other uses for this assay, which are important to the deployment of this tool for invasive M. musculus management.
UNGULATES
Nichols R. V., Königsson H., Danell K., Spong G. (2012): Browsed twig environmental DNA: diagnostic PCR to identify ungulate species. Molecular Ecology Resources 12: 983.
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Ungulate browsing can have a strong effect on ecological processes by affecting plant community structure and composition, with cascading effects on nutrient cycling and animal communities. However, in the absence of direct observations of foraging, species‐specific foraging behaviours are difficult to quantify. We therefore know relatively little about foraging competition and species‐specific browsing patterns in systems with several browsers. However, during browsing, a small amount of saliva containing buccal cells is deposited at the bite site, providing a source of environmental DNA (eDNA) that can be used for species identification. Here, we describe extraction and PCR protocols for a browser species diagnostic kit. Species‐specific primers for mitochondrial DNA were optimized and validated using twigs browsed by captive animals. A time series showed that about 50% of the samples will amplify up to 12 weeks after the browsing event and that some samples amplify up to 24 weeks after browsing (12.5%). Applied to samples of natural browsing from an area where moose (Alces alces), roe deer (Capreolus capreolus), fallow deer (Cervus dama) and red deer (Cervus elaphus) are sympatric, amplification success reached 75%. This method promises to greatly improve our understanding of multispecies browsing systems without the need for direct observations.
Keiter D. A., Cunningham F. L., Rhodes Jr O. E., Irwin B. J., Beasley J. C. (2016): Optimization of scat detection methods for a social ungulate, the wild pig, and experimental evaluation of factors affecting detection of scat. Plos One 11: e0155615.
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Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocols with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig (Sus scrofa) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. Knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.
Pfeffer S. E., Spitzer R., Allen A. M., Hofmeester T. R., Ericsson G., Widemo F., Singh N. J., Cromsigt J. P. (2018): Pictures or pellets? Comparing camera trapping and dung counts as methods for estimating population densities of ungulates. Remote Sensing in Ecology and Conservation 4: 173-183.
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Across the northern hemisphere, land use changes and, possibly, warmer winters are leading to more abundant and diverse ungulate communities causing increased socioeconomic and ecological consequences. Reliable population estimates are crucial for sustainable management, but it is currently unclear which monitoring method is most suitable to track changes in multi-species assemblages. We compared dung counts and camera trapping as two non-invasive census methods to estimate population densities of moose Alces alces and roe deer Capreolus capreolus in Northern Sweden. For camera trapping, we tested the random encounter model (REM) which can estimate densities without the need to recognize individual animals. We evaluated different simplification options of the REM in terms of estimates of detection distance and angle (raw data vs. modelled) and of daily movement rate (camera trap based vs. telemetry based). In comparison to density estimates from camera traps, we found that, dung counts appeared to underestimate population density for roe deer, but not for moose. Estimates of detection distance and angle from modelled versus raw camera data resulted in nearly identical outcomes. The telemetry-derived daily movement rate for moose and roe deer resulted in much higher density estimates than the camera trap-derived estimates. We suggest that camera trapping may be a robust complement to dung counts when monitoring ungulate communities, particularly when similarities between dung pellets from sympatric deer species make unambiguous assignment difficult. Moreover, we show that a simplified use of the REM method holds great potential for large-scale citizen science-based programmes (e.g. involving hunters) that can track the rapidly changing European wildlife landscape. We suggest to include camera trapping in management programmes, where the analysis can be verified via web-based applications.
Williams K. E., Huyvaert K. P., Vercauteren K. C., Davis A. J., Piaggio A. J. (2018): Detection and persistence of environmental DNA from an invasive, terrestrial mammal. Ecology and Evolution 8: 688-695.
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Invasive Sus scrofa, a species commonly referred to as wild pig or feral swine, is a destructive invasive species with a rapidly expanding distribution across the United States. We used artificial wallows and small waterers to determine the minimum amount of time needed for pig eDNA to accumulate in the water source to a detectable level. We removed water from the artificial wallows and tested eDNA detection over the course of 2 weeks to understand eDNA persistence. We show that our method is sensitive enough to detect very low quantities of eDNA shed by a terrestrial mammal that has limited interaction with water. Our experiments suggest that the number of individuals shedding into a water system can affect persistence of eDNA. Use of an eDNA detection technique can benefit management efforts by providing a sensitive method for finding even small numbers of individuals that may be elusive using other methods.
Spitzer R., Churski M., Felton A., Heurich M., Kuijper D. P., Landman M., Rodriguez E., Singh N. J., Taberlet P., van Beeck Calkoen S. T., Widemo F. (2019): Doubting dung: eDNA reveals high rates of misidentification in diverse European ungulate communities. European Journal of Wildlife Research 65: 28.
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Pellet counts are widely used to monitor ungulates but rely on the assumption that pellets of different species are correctly identified in the field. Recent studies question this assumption using DNA barcoding techniques to check field identification rates. For Europe, which is undergoing a rapid shift towards more diverse ungulate assemblages, such an assessment is still missing. Using DNA barcoding on 3889 fecal samples from nine ungulate species in four European countries, we found average field misidentification rates varied from 0.6% for horse (Equus ferus) to 41.1% for roe deer (Capreolus capreolus). Most identification errors occurred between similar-sized species from the same taxonomic family. For a subset of samples from Sweden, we looked at the effect of dung morphometry, observer experience, and season on species identification success. Dung morphometry clearly distinguished moose (Alces alces) but not red (Cervus elaphus), roe, and fallow deer (Dama dama). Experienced observers performed better than novices for red and fallow deer although still making significant identification errors (26% and 17% incorrectly identified). Identification success was higher during spring and winter (x = 86%) than summer and autumn (x = 74%). We question pellet counts as an accurate monitoring tool where similar-sized species coexist and monitoring relates to the whole community. For this increasingly common situation across Europe, DNA testing or camera traps may be a better alternative. Pellet counts remain useful where only few species with clearly different dung morphology coexist (e.g., moose and roe deer) or when focused on species with distinctive dung morphology (e.g., moose).
Hennig J. D., Schoenecker K. A., Terwilliger M. L., Holm G. W., Laake J. L. (2021): Comparison of aerial thermal infrared imagery and helicopter surveys of bison (Bison bison) in Grand Canyon National Park, USA. Sensors 21: 5087.
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Aerial thermal infrared (TIR) surveys are an attractive option for estimating abundances of large mammals inhabiting extensive and heterogeneous terrain. Compared to standard helicopter or fixed-wing aerial surveys, TIR flights can be conducted at higher altitudes translating into greater spatial coverage and increased observer safety; however, monetary costs are much greater. Further, there is no consensus on whether TIR surveys offer improved detection. Consequently, we performed a study to compare results of a TIR and helicopter survey of bison (Bison bison) on the Powell Plateau in Grand Canyon National Park, USA. We also compared results of both surveys to estimates obtained using a larger dataset of bison helicopter detections along the entire North Rim of the Grand Canyon. Observers in the TIR survey counted fewer individual bison than helicopter observers (101 to 127) and the TIR survey cost was 367% higher. Additionally, the TIR estimate was 18.8% lower than the estimate obtained using a larger dataset, while the comparative helicopter survey was 9.3% lower. Despite our small sample size, we found that helicopter surveys are currently the best method for estimating bison abundances in dense canopy cover sites due to ostensibly more accurate estimates and lower cost compared to TIR surveys. Additional research will be needed to evaluate the efficacy of these methods, as well as very high resolution satellite imagery, for bison populations in more open landscapes.
McMahon M. C., Ditmer M. A., Forester J. D. (2021): Comparing unmanned aerial systems with conventional methodology for surveying a wild white-tailed deer population. Wildlife Research 49: 54-65.
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Ungulate populations are subject to fluctuations caused by extrinsic factors and require efficient and frequent surveying to monitor population sizes and demographics. Unmanned aerial systems (UAS) have become increasingly popular for ungulate research; however, little is understood about how this novel technology compares with conventional methodologies for surveying wild populations. We examined the feasibility of using a fixed-wing UAS equipped with a thermal infrared sensor for estimating the population density of wild white-tailed deer (Odocoileus virginianus) at the Cedar Creek Ecosystem Science Reserve (CCESR), Minnesota, USA. We compared UAS density estimates with those derived from faecal pellet-group counts. We conducted UAS thermal survey flights from March to April of 2018 and January to March of 2019. Faecal pellet-group counts were conducted from April to May in 2018 and 2019. We modelled deer counts and detection probabilities and used these results to calculate point estimates and bootstrapped prediction intervals for deer density from UAS and pellet-group count data. We compared results of each survey approach to evaluate the relative efficacy of these two methodologies. Our best-fitting model of certain deer detections derived from our UAS-collected thermal imagery produced deer density estimates (X = 9.40, 95% prediction interval = 4.32–17.84 deer km−2) that overlapped with the pellet-group count model when using our mean pellet deposition rate assumption (X = 7.01, 95% prediction interval = 4.14–11.29 deer km−2). Estimates from our top UAS model using both certain and potential deer detections resulted in a mean density of 13.77 deer km−2 (95% prediction interval = 6.64–24.35 deer km−2), which was similar to our pellet-group count model that used a lower rate of pellet deposition (X = 10.95, 95% prediction interval = 6.46–17.65 deer km−2). The mean point estimates from our top UAS model predicted a range of 136.68–273.81 deer, and abundance point estimates using our pellet-group data ranged from 112.79 to 239.67 deer throughout the CCESR. Overall, UAS yielded results similar to pellet-group counts for estimating population densities of wild ungulates; however, UAS surveys were more efficient and could be conducted at multiple times throughout the winter. We demonstrated how UAS could be applied for regularly monitoring changes in population density. We encourage researchers and managers to consider the merits of UAS and how they could be used to enhance the efficiency of wildlife surveys.
Avots E., Vecvanags A., Filipovs J., Brauns A., Skudrins G., Done G., Ozolins J., Anbarjafari G., Jakovels D. (2022): Towards automated detection and localization of red deer Cervus elaphus using passive acoustic sensors during the rut. Remote Sensing 14: 2464.
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Passive acoustic sensors have the potential to become a valuable complementary component in red deer Cervus elaphus monitoring providing deeper insight into the behavior of stags during the rutting period. Automation of data acquisition and processing is crucial for adaptation and wider uptake of acoustic monitoring. Therefore, an automated data processing workflow concept for red deer call detection and localization was proposed and demonstrated. The unique dataset of red deer calls during the rut in September 2021 was collected with four GPS time-synchronized microphones. Five supervised machine learning algorithms were tested and compared for the detection of red deer rutting calls where the support-vector-machine-based approach demonstrated the best performance of −96.46% detection accuracy. For sound source location, a hyperbolic localization approach was applied. A novel approach based on cross-correlation and spectral feature similarity was proposed for sound delay assessment in multiple microphones resulting in the median localization error of 16 m, thus providing a solution for automated sound source localization—the main challenge in the automation of the data processing workflow. The automated approach outperformed manual sound delay assessment by a human expert where the median localization error was 43 m. Artificial sound records with a known location in the pilot territory were used for localization performance testing.
De Kock M. E., Pohůnek V., Hejcmanová P. (2022). Semi-automated detection of ungulates using UAV imagery and reflective spectrometry. Journal of Environmental Management 320: 115807.
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In the field of species conservation, the use of unmanned aerial vehicles (UAV) is increasing in popularity as wildlife observation and monitoring tools. With large datasets created by UAV-based species surveying, the need arose to automate the detection process of the species. Although the use of computer learning algorithms for wildlife detection from UAV-derived imagery is an increasing trend, it depends on a large amount of imagery of the species to train the object detector effectively. However, there are alternatives like object-based image analysis (OBIA) software available if a large amount of imagery of the species is not available to develop a computer-learned object detector. The study tested the semi-automated detection of reintroduced Arabian Oryx (O. leucoryx), using the specie’s coat sRGB-colour profiles as input for OBIA to identify adult O. leucoryx, applied to UAV acquired imagery. Our method uses lab-measured spectral reflection of hair sample values, collected from captive O. leucoryx as an input for OBIA ruleset to identify adult O. leucoryx from UAV survey imagery using semi-automated supervised classification. The converted mean CIE Lab reflective spectrometry colour values of n = 50 hair samples of adult O. leucoryx to 8-bit sRGB-colour profiles of the species resulted in the red-band value of 157.450, the green-band value of 151.390 and blue-band value of 140.832. The sRGB values and a minimum size permitter were added as the input of the OBIA ruleset identified adult O. leucoryx with a high degree of efficiency when applied to three UAV census datasets. Using species sRGB-colour profiles to identify re-introduced O. leucoryx and extract location data using a non-invasive UAV-based tool is a novel method with enormous application possibilities. Coat refection sRGB-colour profiles can be developed for a range of species and customised to autodetect and classify the species from remote sensing data.
Hua A., Martin K., Shen Y., Chen N., Mou C., Sterk M., Reinhard B., Reinhard F. F., Lee S., Alibhai S., Jewell Z. C. (2022): Protecting endangered megafauna through AI analysis of drone images in a low-connectivity setting: a case study from Namibia. PeerJ 10: e13779.
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Assessing the numbers and distribution of at-risk megafauna such as the black rhino (Diceros bicornis) is key to effective conservation, yet such data are difficult to obtain. Many current monitoring technologies are invasive to the target animals and expensive. Satellite monitoring is emerging as a potential tool for very large animals (e.g., elephant) but detecting smaller species requires higher resolution imaging. Drones can deliver the required resolution and speed of monitoring, but challenges remain in delivering automated monitoring systems where internet connectivity is unreliable or absent. This study describes a model built to run on a drone to identify in situ images of megafauna. Compared with previously reported studies, this automated detection framework has a lower hardware cost and can function with a reduced internet bandwidth requirement for local network communication. It proposes the use of a Jetson Xavier NX, onboard a Parrot Anafi drone, connected to the internet throughout the flight to deliver a lightweight web-based notification system upon detection of the target species. The GPS location with the detected target species images is sent using MQ Telemetry Transport (MQTT), a lightweight messaging protocol using a publisher/subscriber architecture for IoT devices. It provides reliable message delivery when internet connection is sporadic. We used a YOLOv5l6 object detection architecture trained to identify a bounding box for one of five objects of interest in a frame of video. At an intersection over union (IoU) threshold of 0.5, our model achieved an average precision (AP) of 0.81 for black rhino (our primary target) and 0.83 for giraffe (Giraffa giraffa). The model was less successful at identifying the other smaller objects which were not our primary targets: 0.34, 0.25, and 0.42 for ostrich (Struthio camelus australis), springbok (Antidorcas marsupialis) and human respectively. We used several techniques to optimize performance and overcome the inherent challenge of small objects (animals) in the data. Although our primary focus for the development of the model was rhino, we included other species classes to emulate field conditions where many animal species are encountered, and thus reduce the false positive occurrence rate for rhino detections. To constrain model overfitting, we trained the model on a dataset with varied terrain, angle and lighting conditions and used data augmentation techniques (i.e., GANs). We used image tiling and a relatively larger (i.e., higher resolution) image input size to compensate for the difficulty faced in detecting small objects when using YOLO. In this study, we demonstrated the potential of a drone-based AI pipeline model to automate the detection of free-ranging megafauna detection in a remote setting and create alerts to a wildlife manager in a relatively poorly connected field environment.
Ito T. Y., Miyazaki A., Koyama L. A., Kamada K., Nagamatsu D. (2022): Antler detection from the sky: deer sex ratio monitoring using drone‐mounted thermal infrared sensors. Wildlife Biology 2022: e01034.
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Sex differences in large mammals with sexual dimorphism are important ecological and evolutionary issues and key factors for wildlife management. To examine the potential use of drone (unmanned aerial vehicle; UAV) observation using thermal infrared images for sex ratio monitoring of deer, we conducted UAV surveys at night in a sparse forest located on the distribution periphery of sika deer Cervus nippon and wild boar Sus scrofa local populations during summer and winter. Of the 163 thermal infrared images of large mammals detected, 132 (81.0%) and 16 (9.8%) were identified for deer and wild boar, respectively. In addition, velvet antlers of deer were visually recognized during summer, and 92% of the detected deer were antlered. This biased sex ratio would be a characteristic in the distribution periphery of local deer populations. Therefore, monitoring abundance and sex ratio using thermal infrared sensors on UAVs can improve deer management especially in the distribution periphery of local populations.
Lenzi J., Barnas A. F., ElSaid A. A., Desell T., Rockwell R. F., Ellis-Felege S. N. (2023): Artificial intelligence for automated detection of large mammals creates path to upscale drone surveys. Scientific Reports 13: 947.
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Imagery from drones is becoming common in wildlife research and management, but processing data efficiently remains a challenge. We developed a methodology for training a convolutional neural network model on large-scale mosaic imagery to detect and count caribou (Rangifer tarandus), compare model performance with an experienced observer and a group of naïve observers, and discuss the use of aerial imagery and automated methods for large mammal surveys. Combining images taken at 75 m and 120 m above ground level, a faster region-based convolutional neural network (Faster-RCNN) model was trained in using annotated imagery with the labels: “adult caribou”, “calf caribou”, and “ghost caribou” (animals moving between images, producing blurring individuals during the photogrammetry processing). Accuracy, precision, and recall of the model were 80%, 90%, and 88%, respectively. Detections between the model and experienced observer were highly correlated (Pearson: 0.96–0.99, P value < 0.05). The model was generally more effective in detecting adults, calves, and ghosts than naïve observers at both altitudes. We also discuss the need to improve consistency of observers’ annotations if manual review will be used to train models accurately. Generalization of automated methods for large mammal detections will be necessary for large-scale studies with diverse platforms, airspace restrictions, and sensor capabilities.
Zabel F., Findlay M. A., White P. J. (2023): Assessment of the accuracy of counting large ungulate species (red deer Cervus elaphus) with UAV‐mounted thermal infrared cameras during night flights. Wildlife Biology 2023: e01071.
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Unmanned aerial vehicles (UAVs) are increasingly used in wildlife surveying, including estimation of population densities. It is essential that we evaluate and test new survey methods to guide optimal sampling strategies. This study aimed to assess the accuracy of using a UAV-mounted thermal infrared (TIR) camera to count red deer Cervus elaphus populations, and how this was influenced by flight season, height and velocity, in order to help guide future census design. We flew 57 flights across a captive population of red deer in a 13 ha deer park enclosure of semi-natural habitat, representative of the species’ range in northern Germany. Flights and image assessments were performed with no prior knowledge of actual population size. Accuracy was quantified by comparing real population size (known only to deer park staff) and independently estimated population sizes from UAV TIR images. Accuracy was significantly influenced by ecological season (early and late winter, spring and early summer) and height. Across all seasons, lower flights (100 m) performed better than higher ones (120 m), with lower flights in early winter and early summer being on average accurate to within 1% of actual population counts. For the season where we had the largest range of temperatures between flights (late winter) we found that accuracy was highest when temperatures were lowest. Flights were also able to identify all five stags (defined as a male deer ≥ 2 years old) present in early summer, but not in spring. Deer appeared to avoid the landing/take-off area, but there were no noted behavioural responses to drones flying over animals when at constant height and velocity during surveys. Our results indicate that UAV-mounted TIR camera have the potential to accurately count populations of large ungulate species, but that flight season, height and potentially temperature need to be taken into account to maximise accuracy. This approach has the potential to be scaled up to more accurately estimate densities of wild populations compared to existing approaches.
Ma G., Li W., Bao H., Roberts N. J., Li Y., Zhang W., Yang K., Jiang G. (2024): UAV equipped with infrared imaging for Cervidae monitoring: Improving detection accuracy by eliminating background information interference. Ecological Informatics 81: 102651.
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Wild Cervidae (deer and their relatives) play a crucial role in maintaining ecological balance and are integral components of ecosystems. However, factors such as environmental changes and poaching behaviors have resulted in habitat degradation for Cervidae. The protection of wild Cervidae has become urgent, and Cervidae monitoring is one of the key means to ensure the effectiveness of wild Cervidae protection. Object detection algorithms based on deep learning offer promising potential for automatically detecting and identifying animals. However, when those algorithms are used for inference in unseen background environments, there will be a significant decrease in accuracy, especially in the situation that a certain type of Cervidae images are collected from single scene for algorithm training. In this paper, a two-stage localization and classification pipeline for Cervidae monitoring is proposed. The pipeline effectively reduces background interference in Cervidae monitoring and enhances monitoring accuracy. In the first stage, the YOLOv7 network is designed to automatically locate Cervidae in UAV infrared images, while implementing improved bounding box regression through the α-IoU loss function enables the network to locate Cervidae more accurately. Then, Cervidae objects are extracted to eliminate the background information. In the second stage, a classification network named CA-Hybrid, based on Convolutional Neural Networks (CNN) and Vision Transformer (ViT), as well as Channel Attention Mechanism (CAM) enhances the expression of key features, is constructed to accurately identify Cervidae categories. Experimental results indicate that this method achieves an Average Precision (AP) of 95.9% for Cervidae location and a top-1 accuracy of 77.73% for Cervidae identification. This research contributes to a more comprehensive and accurate monitoring of wild Cervidae, and provides valuable references for subsequent UAV-based wildlife monitoring.
Schütz A. K., Louton H., Fischer M., Probst C., Gethmann J. M., Conraths F. J., Homeier-Bachmann T. (2024): Automated detection and counting of wild boar in camera trap images. Animals 14: 1408.
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Camera traps are becoming widely used for wildlife monitoring and management. However, manual analysis of the resulting image sets is labor-intensive, time-consuming and costly. This study shows that automated computer vision techniques can be extremely helpful in this regard, as they can rapidly and automatically extract valuable information from the images. Specific training with a set of 1600 images obtained from a study where wild animals approaching wild boar carcasses were monitored enabled the model to detect five different classes of animals automatically in their natural environment with a mean average precision of 98.11%, namely ‘wild boar’, ‘fox’, ‘raccoon dog’, ‘deer’ and ‘bird’. In addition, sequences of images were automatically analyzed and the number of wild boar visits and respective group sizes were determined. This study may help to improve and speed up the monitoring of the potential spread of African swine fever virus in areas where wild boar are affected.
MULTIPLE SPECIES
Andersen K., Bird K. L., Rasmussen M., Haile J., Breuning‐Madsen H., Kjaer K. H., Orlando L., Gilbert M. T. P., Willerslev E. (2012): Meta‐barcoding of ‘dirt’ DNA from soil reflects vertebrate biodiversity. Molecular Ecology 21: 1966-1979.
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DNA molecules originating from animals and plants can be retrieved directly from sediments and have been used for reconstructing both contemporary and past ecosystems. However, the extent to which such ‘dirt’ DNA reflects taxonomic richness and structural diversity remains contentious. Here, we couple second generation high‐throughput sequencing with 16S mitochondrial DNA (mtDNA) meta‐barcoding, to explore the accuracy and sensitivity of ‘dirt’ DNA as an indicator of vertebrate diversity, from soil sampled at safari parks, zoological gardens and farms with known species compositions. PCR amplification was successful in the full pH range of the investigated soils (6.2 ± 0.2 to 8.3 ± 0.2), but inhibition was detected in extracts from soil of high organic content. DNA movement (leaching) through strata was evident in some sporadic cases and is influenced by soil texture and structure. We find that DNA from the soil surface reflects overall taxonomic richness and relative biomass of individual species. However, one species that was recently introduced was not detected. Furthermore, animal behaviour was shown to influence DNA deposition rates. The approach potentially provides a quick methodological alternative to classical ecological surveys of biodiversity, and most reliable results are obtained with spatial sample replicates, while relative amounts of soil processed per site is of less importance.
Mann G. K., O’Riain M. J., Parker D. M. (2015): The road less travelled: assessing variation in mammal detection probabilities with camera traps in a semi-arid biodiversity hotspot. Biodiversity and Conservation 24: 531-545.
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Camera traps are an increasingly popular tool for monitoring medium to large mammals, but the influence of camera trap placement on the detection probabilities of different species has seldom been investigated. In this study we explore the influence of roads on the detection probability of medium to large mammals in three vegetation types in the Little Karoo, an arid biodiversity hotspot. We placed cameras in nine 100 m-long transects, running perpendicular from roads within a conservation area. The camera traps were spaced at ~25 m intervals, and were active for an average of 88 days each. Detection probabilities relative to distance from roads showed extensive variation between species and habitat types. There was no clear relationship between distance from the road and the detection probability of most species and guilds, although carnivore detection probability declined significantly as distance from roads increased in all vegetation types. Our results suggest that there is considerable inter-specific variation in detection probability that is significantly influenced by camera trap location relative to roads. Therefore studies that seek to maximise the detection rates of particular species or guilds (e.g. carnivores) by placing cameras on prominent roads and trails are unlikely to provide reliable estimates of the relative abundance of the broader range of sympatric species; a trend observed elsewhere but hitherto untested in arid environments. We recommend that future studies employ a mixed design of cameras located on- and off-roads to provide better estimates of biodiversity in general and predators specifically.
Soininen E. M., Jensvoll I., Killengreen S. T., Ims R. A. (2015): Under the snow: a new camera trap opens the white box of subnivean ecology. Remote Sensing in Ecology and Conservation 1: 29-38.
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Snow covers the ground over large parts of the world for a substantial portion of the year. Yet very few methods are available to quantify biotic variables below the snow, with most studies of subnivean ecological processes relying on comparisons of data before and after the snow cover season. We developed a camera trap prototype to quantify subnivean small mammal activity. The trap consists of a camera that is attached facing downward from the ceiling of a box, which is designed to function as a snow-free tunnel. We tested it by placing nine traps with passive infrared sensors in a subarctic habitat where snow cover lasted for about 6 months. The traps were functional for the whole winter, permitting continuous data collection of site-specific presence and temporal activity patterns of all three small mammal species present (the insectivorous common shrew, Sorex araneus, the herbivorous tundra vole, Microtus oeconomus, and the carnivorous stoat, Mustela erminea) as well as abiotic conditions (presence/absence of snow cover and subnivean temperature). Based on their successful functioning (only 6% of the photographs appeared empty or were of poor quality, whereas ca 80% were of small mammals and the remaining of birds and invertebrates), we discuss how the new camera trap can enable subnivean studies of small mammal communities. This greatly increases the temporal resolution and extent of data collection and thereby provides unpreceded opportunities to understand population and food web dynamics in ecosystems with snow cover.
Ishige T., Miya M., Ushio M., Sado T., Ushioda M., Maebashi K., Yonechi R., Lagan P., Matsubayashi H. (2017): Tropical-forest mammals as detected by environmental DNA at natural saltlicks in Borneo. Biological Conservation 210: 281-285.
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Although tropical forests are among the most species-rich ecosystems on earth, 42% of mammal species in tropical forests are endangered because of overhunting and/or unsustainable exploitation. Camera-trap surveys have shown that natural saltlicks can be used to determine mammalian fauna, especially medium to large endangered species in tropical forests; establishment of camera traps, however, is time and effort intensive. Furthermore, the photographic range and detectable size of species are often restricted. Environmental DNA (eDNA) metabarcoding is a powerful approach that might provide a better way to study terrestrial animals in tropical forests. In this study, we examined whether eDNA from natural saltlicks comprehensively represented species composition in a Bornean tropical forest. We collected 100–150-mL water samples from natural saltlicks in Sabah, Malaysian Borneo. We constructed amplicon libraries for MiSeq sequencing using eDNA extracted from the water samples. Six endangered species were detected using this method, including Bornean orangutan (Pongo pygmaeus), Bornean banteng (Bos javanicus lowi), Asian elephant (Elephas maximus), Sunda pangolin (Manis javanica), sambar deer (Rusa unicolor) and bearded pig (Sus barbatus). However, most small and minor species were not detected, with low sequence identity (80–96%). Therefore, we propose that more species of tropical forest mammals should have their sequences deposited in DNA databases. This study is the first to report the endangered mammals of a tropical forest detected using eDNA from natural saltlicks.
Ushio M., Fukuda H., Inoue T., Makoto K., Kishida O., Sato K., Murata K., Nikaido M., Sado T., Sato Y., Takeshita M. (2017): Environmental DNA enables detection of terrestrial mammals from forest pond water. Molecular Ecology Resources 17: e63-e75.
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Terrestrial animals must have frequent contact with water to survive, implying that environmental DNA (eDNA) originating from those animals should be detectable from places containing water in terrestrial ecosystems. Aiming to detect the presence of terrestrial mammals using forest water samples, we applied a set of universal PCR primers (MiMammal, a modified version of fish universal primers) for metabarcoding mammalian eDNA. The versatility of MiMammal primers was tested in silico and by amplifying DNA s extracted from tissues. The results suggested that MiMammal primers are capable of amplifying and distinguishing a diverse group of mammalian species. In addition, analyses of water samples from zoo cages of mammals with known species composition suggested that MiMammal primers could successfully detect mammalian species from water samples in the field. Then, we performed an experiment to detect mammals from natural ecosystems by collecting five 500‐ml water samples from ponds in two cool‐temperate forests in Hokkaido, northern Japan. MiMammal amplicon libraries were constructed using eDNA extracted from water samples, and sequences generated by Illumina MiSeq were subjected to data processing and taxonomic assignment. We thereby detected multiple species of mammals common to the sampling areas, including deer (Cervus nippon), mouse (Mus musculus), vole (Myodes rufocanus), raccoon (Procyon lotor), rat (Rattus norvegicus) and shrew (Sorex unguiculatus). Many previous applications of the eDNA metabarcoding approach have been limited to aquatic/semiaquatic systems, but the results presented here show that the approach is also promising even for forest mammal biodiversity surveys.
Shiels A. B., Piaggio A. J., Bogardus T., Lombard C. D., Angeli N. F., Hopken M. W. (2018): Non-trapping, non-invasive, rapid surveillance sampling using tracking tunnels, trail cameras, and eDNA to determine presence of pest predator species. Proceedings of the Vertebrate Pest Conference 28: 287-294.
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A common challenge for land managers is knowing which vertebrate pest species are present in areas they manage, especially if such areas are remote like isolated habitats, rugged terrain, or infrequently traveled islands. Most invasive predator species, such as feral dogs, cats, mongoose, and commensal rodents pose great threat to human health and key resources such as native species. Animal trapping to determine the presence of a pest species can be expensive and dangerous, requiring permits, experienced personnel, multiple days, and multiple trapping methods. Furthermore, many invasive pest species may go unnoticed because they are nocturnal, secretive, or leave little evidence of their presence. Tracking tunnels, trail cameras, and environmental DNA (eDNA) are non-trapping methods that can be used to rapidly assess if vertebrate pest species are present in a given habitat or ecosystem, including before, during, and after pest suppression techniques are implemented. We share tracking tunnel dimensions and specifications so readers can make their own tracking tunnels for rodent and other small mammal sampling, and we provide some common distributers where tracking tunnels can be purchased. A brief overview of trail camera technology and eDNA forensic uses are described, as well as their applications for vertebrate pest identification, surveillance, and damage management. To demonstrate these methods, we share example case studies from the Caribbean, including first time records of house mouse presence at Sandy Point National Wildlife Refuge in St. Croix (US Virgin Islands) and along a rainforest elevation gradient in the Luquillo National Forest, Puerto Rico. Additionally, we describe case studies of trail camera use on Desecheo Island (Puerto Rico) to determine brodifacoum bait consumption, and eDNA use in Wyoming to determine native bird depredation events. Tracking tunnels and trail cameras are recommended as quick and inexpensive ways to reveal the vertebrate pest species that are present at a site or habitat. These non-trapping, non-invasive techniques can provide quick and efficient methods of surveillance, detection, and monitoring of vertebrate pests, and otherwise may be used as effective tools to aid in wildlife damage management.
Enari H., Enari H. S., Okuda K., Maruyama T., Okuda K. N. (2019): An evaluation of the efficiency of passive acoustic monitoring in detecting deer and primates in comparison with camera traps. Ecological Indicators 98: 753-762.
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In recent years, camera traps have rapidly become popular for the large-scale monitoring of wildlife distribution and population; however, we should not ignore the uncertainty regarding the reliability of camera-based monitoring by inexperienced data gatherers. This study introduces passive acoustic monitoring (PAM) as an easier technique for monitoring terrestrial mammals that uses the sound cues that they produce. To validate the efficacy of PAM, we quantitatively compared the detection areas and rates between sound cues (from PAM) and visual cues (from camera traps) of two mammals – the sika deer Cervus nippon and the Japanese macaque Macaca fuscata – across seven study sites in eastern Japan with different population densities. To collect sound cues, we set up multiple autonomous recording units at the sites and continuously recorded ambient sounds, following a pre-determined schedule. The total recording time reached 9081 h for deer and 8235 h for macaques. We then built sound recognizers to automatically detect eight target call types from the recorded data. To collect visual cues, we also set multiple camera traps at the same sites and for the same observation periods. The key findings were as follows: (1) the fully automated procedures that only used the recognizers to detect sound cues produced numerous false positive detections when the call type possessed vocal plasticity and variations; (2) the semi-automated procedures, which included an additional step to validate the automated detections by manual screening, exhibited a great improvement in the detectability and recall rates of the half of the target calls, reaching >0.70; (3) when using the semi-automated procedures, the frequency of deer and macaque detections per trap-day derived from the sound cues were in most cases approximately dozens of times and several times, respectively, higher than that derived from the visual cues; (4) the main advantage of PAM may be its superior detection areas, which were 100–7000 times wider than those of camera traps; and (5) the current success of the recognition of different call types of each species could broaden the use of PAM, which is not possible for camera traps. PAM could provide socio-behavioral data (i.e., the frequencies and types of inter-individual vocal communications) that could help understand the status of population dynamics and the group compositions, in addition to information related to the presence or absence of species.
Harper L. R., Handley L. L., Carpenter A. I., Ghazali M., Di Muri C., Macgregor C. J., Logan T. W., Law A., Breithaupt T., Read D. S., McDevitt A. D. (2019): Environmental DNA (eDNA) metabarcoding of pond water as a tool to survey conservation and management priority mammals. Biological Conservation 238: 108225.
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Environmental DNA (eDNA) metabarcoding can identify terrestrial taxa utilising aquatic habitats alongside aquatic communities, but terrestrial species’ eDNA dynamics are understudied. We evaluated eDNA metabarcoding for monitoring semi-aquatic and terrestrial mammals, specifically nine species of conservation or management concern, and examined spatiotemporal variation in mammal eDNA signals. We hypothesised eDNA signals would be stronger for semi-aquatic than terrestrial mammals, and at sites where individuals exhibited behaviours. In captivity, we sampled waterbodies at points where behaviours were observed (‘directed’ sampling) and at equidistant intervals along the shoreline (‘stratified’ sampling). We surveyed natural ponds (N = 6) where focal species were present using stratified water sampling, camera traps, and field signs. eDNA samples were metabarcoded using vertebrate-specific primers. All focal species were detected in captivity. eDNA signal strength did not differ between directed and stratified samples across or within species, between semi-aquatic or terrestrial species, or according to behaviours. eDNA was evenly distributed in artificial waterbodies, but unevenly distributed in natural ponds. Survey methods deployed at natural ponds shared three species detections. Metabarcoding missed badger and red fox recorded by cameras and field signs, but detected small mammals these tools overlooked, e.g. water vole. Terrestrial mammal eDNA signals were weaker and detected less frequently than semi-aquatic mammal eDNA signals. eDNA metabarcoding could enhance mammal monitoring through large-scale, multi-species distribution assessment for priority and difficult to survey species, and provide early indication of range expansions or contractions. However, eDNA surveys need high spatiotemporal resolution and metabarcoding biases require further investigation before routine implementation.
Kinoshita G., Yonezawa S., Murakami S., Isagi Y. (2019): Environmental DNA collected from snow tracks is useful for identification of mammalian species. Zoological Science 36: 198-207.
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Noninvasive genetic analysis is being used increasingly in field surveys. However, detecting large and middle-sized mammals, such as Carnivora species, using noninvasive samples, such as scat or hair, is time- and labor-intensive due to their low densities and elusive behaviors. As snow tracks are the most frequently encountered natural signs of terrestrial mammals in winter, we employed several methods to recover environmental DNA (eDNA) from snow tracks. We performed both DNA metabarcoding and Sanger sequence analyses, in combination with universal primers on the mitochondrial 12S rRNA gene for mammals and taxon-specific primers on the mitochondrial NADH dehydrogenase subunit 2 gene for Martes species (martens and sables in Mustelidae). Snow samples of four Martes melampus tracks, one Cervus nippon track, one Vulpes vulpes track, and the track of an unidentified Carnivora species were collected from a snowfall area in Kyoto, Japan, in February 2018. Regarding DNA metabarcoding analyses, the sequences of three Carnivora species (M. melampus, V. vulpes, and Canis lupus familiaris) and a deer (C. nippon) were obtained from their respective snow tracks. Using Sanger sequencing, eDNA on snow tracks was recovered at the species level except for M. melampus using universal primers, while eDNA of M. melampus was sequenced using Martes-specific primers. Snow track surveys in combination with eDNA techniques could dramatically improve the efficiency of monitoring and conservation of mammals.
Seeber P. A., McEwen G. K., Löber U., Förster D. W., East M. L., Melzheimer J., Greenwood A. D. (2019): Terrestrial mammal surveillance using hybridization capture of environmental DNA from African waterholes. Molecular Ecology Resources 19: 1486-1496.
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Determining species distributions can be extremely challenging but is crucial to ecological and conservation research. Environmental DNA (eDNA) approaches have shown particular promise in aquatic systems for several vertebrate and invertebrate species. For terrestrial animals, however, eDNA‐based surveys are considerably more difficult due to the lack of or difficulty in obtaining appropriate sampling substrate. In water‐limited ecosystem where terrestrial mammals are often forced to congregate at waterholes, water and sediment from shared water sources may be a suitable substrate for noninvasive eDNA approaches. We characterized mitochondrial DNA sequences from a broad range of terrestrial mammal species in two different African ecosystems (in Namibia and Tanzania) using eDNA isolated from native water, sediment and water filtered through glass fibre filters. A hybridization capture enrichment with RNA probes targeting the mitochondrial genomes of 38 mammal species representing the genera/families expected at the respective ecosystems was employed, and 16 species were identified, with a maximum mitogenome coverage of 99.8%. Conventional genus‐specific PCRs were tested on environmental samples for two genera producing fewer positive results than hybridization capture enrichment. An experiment with mock samples using DNA from non‐African mammals showed that baits covering 30% of nontarget mitogenomes produced 91% mitogenome coverage after capture. In the mock samples, over‐representation of DNA of one species still allowed for the detection of DNA of other species that was at a 100‐fold lower concentration. Hybridization capture enrichment of eDNA is therefore an effective method for monitoring terrestrial mammal species from shared water sources.
Carl C., Schönfeld F., Profft I., Klamm A., Landgraf D. (2020): Automated detection of European wild mammal species in camera trap images with an existing and pre-trained computer vision model. European Journal of Wildlife Research 66: 62.
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The use of camera traps is a nonintrusive monitoring method to obtain valuable information about the appearance and behavior of wild animals. However, each study generates thousands of pictures and extracting information remains mostly an expensive, time-consuming manual task. Nevertheless, image recognition and analyzing technologies combined with machine learning algorithms, particularly deep learning models, improve and speed up the analysis process. Therefore, we tested the usability of a pre-trained deep learning model available on the TensorFlow hub–FasterRCNN+InceptionResNet V2 network applied to images of ten different European wild mammal species such as wild boar (Sus scrofa), roe deer (Capreolus capreolus), or red fox (Vulpes vulpes) in color as well as black and white infrared images. We found that the detection rate of the correct region of interest (region of the animal) was 94%. The classification accuracy was 71% for the correct species’ name as mammals and 93% for the correct species or higher taxonomic ranks such as “carnivore” as order. In 7% of cases, the classification was incorrect as the wrong species’ name was classified. In this technical note, we have shown the potential of an existing and pre-trained image classification model for wildlife animal detection, classification, and analysis. A specific training of the model on European wild mammal species could further increase the detection and classification accuracy of the models. Analysis of camera trap images could thus become considerably faster, less expensive, and more efficient.
Lamprey R., Ochanda D., Brett R., Tumwesigye C., Douglas‐Hamilton I. (2020): Cameras replace human observers in multi‐species aerial counts in Murchison Falls, Uganda. Remote Sensing in Ecology and Conservation 6: 529-545.
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Wildlife counts in Africa and elsewhere are often implemented using light aircraft with ‘rear-seat-observer’ (RSO) counting crews. Previous research has indicated that RSOs often fail to detect animals, and that population estimates are therefore biased. We conducted aerial wildlife surveys in Murchison Falls Protected Area, Uganda, in which we replaced RSOs with high-definition ‘oblique camera count’ (OCC) systems. The survey area comprises forests, woodlands and grasslands. Four counts were conducted in 2015–2016 using a systematic-reconnaissance-flight (SRF) strip-transect design. Camera inclination angles, focal lengths, altitude and frame interval were calibrated to provide imaged strips of known sample size on the left and right sides of the aircraft. Using digital cameras, 24 000 high-definition images were acquired for each count, which were visually interpreted by four airphoto interpreters. We used the standard Jolly II SRF analysis to derive population estimates. Our OCC estimates of the antelopes – hartebeest, Uganda kob, waterbuck and oribi – were, respectively, 25%, 103%, 97% and 2100% higher than in the most recent RSO count conducted in 2014. The OCC surveys doubled the 2014 RSO estimate of 58 000 Uganda kob to over 118 000. Population size estimates of elephants and giraffes did not differ significantly. Although all four OCC buffalo estimates were higher than the RSO estimates – in one count by 60% – these differences were not significant due to the clumped distribution and high variation in herd sizes, resulting in imprecise estimation by sampling. We conclude that RSO wildlife counts in Murchison have been effective in enumerating elephants and giraffe, but that many smaller species have not been well detected. We emphasize the importance of 60 years of RSO-based surveys across Africa, but suggest that new imaging technologies are embraced to improve accuracy.
Leempoel K., Hebert T., Hadly E. A. (2020): A comparison of eDNA to camera trapping for assessment of terrestrial mammal diversity. Proceedings of the Royal Society B 287: 20192353.
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Before environmental DNA (eDNA) can establish itself as a robust tool for biodiversity monitoring, comparison with existing approaches is necessary, yet is lacking for terrestrial mammals. Moreover, much is unknown regarding the nature, spread and persistence of DNA shed by animals into terrestrial environments, or the optimal experimental design for understanding these potential biases. To address some of these challenges, we compared the detection of terrestrial mammals using eDNA analysis of soil samples against confirmed species observations from a long-term (approx. 9-year) camera-trapping study. At the same time, we considered multiple experimental parameters, including two sampling designs, two DNA extraction kits and two metabarcodes of different sizes. All mammals regularly recorded with cameras were detected in eDNA. In addition, eDNA reported many unrecorded small mammals whose presence in the study area is otherwise documented. A long metabarcode (≈220 bp) offering a high taxonomic resolution, achieved a similar efficiency as a shorter one (≈70 bp) and a phosphate buffer-based extraction gave similar results as a total DNA extraction method, for a fraction of the price. Our results support that eDNA-based monitoring should become a valuable part of ecosystem surveys, yet mitochondrial reference databases need to be enriched first.
Rößler D. C., Lötters S., Veith M., Fugmann M., Peters C., Künzel S., Krehenwinkel H. (2020): An amplicon sequencing protocol for attacker identification from DNA traces left on artificial prey. Methods in Ecology and Evolution 11: 1338-1347.
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Clay model studies are a popular tool to identify predator–prey interactions that are challenging to observe directly in the field. But despite its wide use, the method’s applicability is limited by its low taxonomic resolution. Attack marks on clay models are usually identified visually, which only allows classification into higher taxonomic levels of predators. Thus, the method is often biased, lacks proof and, above all, standardization. Here, we tested whether precise identification of attackers can be provided by amplification and sequencing of mitochondrial DNA left in bite marks on clay models. We validated our approach in a controlled laboratory study as well as in a field experiment using clay models of a common European amphibian, the European fire salamander Salamandra salamandra. DNA-based taxonomic assignments were additionally compared to visual assessments of bite marks. We show that trace DNA of attackers can be routinely isolated and sequenced from bite marks, providing accurate species-level classification. In contrast, visual identification alone yielded a high number of unassigned predator taxa. We also highlight the sensitivity of the method and show likely sources of contamination as well as probable cases of secondary and indirect predation. Our standardized approach for species-level attacker identification opens up new possibilities far beyond the standard use of clay models to date, including food web studies at unprecedented detail, invasive species monitoring as well as biodiversity inventories.
Sales N. G., McKenzie M. B., Drake J., Harper L. R., Browett S. S., Coscia I., Wangensteen O. S., Baillie C., Bryce E., Dawson D. A., Ochu E. (2020): Fishing for mammals: Landscape‐level monitoring of terrestrial and semi‐aquatic communities using eDNA from riverine systems. Journal of Applied Ecology 57: 707-716.
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Environmental DNA (eDNA) metabarcoding has revolutionized biomonitoring in both marine and freshwater ecosystems. However, for semi‐aquatic and terrestrial animals, the application of this technique remains relatively untested. We first assess the efficiency of eDNA metabarcoding in detecting semi‐aquatic and terrestrial mammals in natural lotic ecosystems in the UK by comparing sequence data recovered from water and sediment samples to the mammalian communities expected from historical data. Secondly, using occupancy modelling we compared the detection efficiency of eDNA metabarcoding to multiple conventional non‐invasive survey methods (latrine surveys and camera trapping). eDNA metabarcoding detected a large proportion of the expected mammalian community within each area. Common species in the areas were detected at the majority of sites. Several key species of conservation concern in the UK were detected by eDNA sampling in areas where authenticated records do not currently exist, but potential false positives were also identified. Water‐based eDNA metabarcoding provided comparable results to conventional survey methods in per unit of survey effort for three species (water vole, field vole and red deer) using occupancy models. The comparison between survey ‘effort’ to reach a detection probability of ≥.95 revealed that 3–6 water replicates would be equivalent to 3–5 latrine surveys and 5–30 weeks of single camera deployment, depending on the species. eDNA metabarcoding can be used to generate an initial ‘distribution map’ of mammalian diversity at the landscape level. If conducted during times of peak abundance, carefully chosen sampling points along multiple river courses provide a reliable snapshot of the species that are present in a catchment area. In order to fully capture solitary, rare and invasive species, we would currently recommend the use of eDNA metabarcoding alongside other non‐invasive surveying methods (i.e. camera traps) to maximize monitoring efforts.
Boukhdoud L., Saliba C., Kahale R., Bou Dagher Kharrat M. (2021): Tracking mammals in a Lebanese protected area using environmental DNA‐based approach. Environmental DNA 3: 792-799.
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Mediterranean forest mammals are still poorly known, and few localities have been properly studied in the East Mediterranean Region (EMR). According to the IUCN Red List, many recorded species in this region are listed as threatened or endangered. Despite all threats, better management and more investments in species monitoring would surely improve the efficiency of biodiversity conservation projects to protect Mediterranean forest mammals. Protected reserves are of utmost importance for the conservation of native flora and fauna. Hereby, we provide a survey of mammals through a noninvasive technique based on environmental DNA extracted from scats. Samples were collected over 1 year covering all seasons from an important site for biodiversity conservation and scientific researches, the Horsh Ehden Nature Reserve. A total of 18 vertebrate species were recorded, many of them are endemic for the region and/or threatened especially in Lebanon. The use of noninvasive sampling method combined with genetic analysis of scats proved to be a powerful tool for species detection in a highly biodiverse protected area and can be easily replicated in any region around the world to rapidly assess species richness and therefore to apply direct conservation and management strategies toward species of interest.
Lyet A., Pellissier L., Valentini A., Dejean T., Hehmeyer A., Naidoo R. (2021): eDNA sampled from stream networks correlates with camera trap detection rates of terrestrial mammals. Scientific Reports 11: 11362.
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Biodiversity monitoring delivers vital information to those making conservation decisions. Comprehensively measuring terrestrial biodiversity usually requires costly methods that can rarely be deployed at large spatial scales over multiple time periods, limiting conservation efficiency. Here we investigated the capacity of environmental DNA (eDNA) from stream water samples to survey terrestrial mammal diversity at multiple spatial scales within a large catchment. We compared biodiversity information recovered using an eDNA metabarcoding approach with data from a dense camera trap survey, as well as the sampling costs of both methods. Via the sampling of large volumes of water from the two largest streams that drained the study area, eDNA metabarcoding provided information on the presence and detection probabilities of 35 mammal taxa, 25% more than camera traps and for half the cost. While eDNA metabarcoding had limited capacity to detect felid species and provide individual-level demographic information, it is a cost-efficient method for large-scale monitoring of terrestrial mammals that can offer sufficient information to solve many conservation problems.
Clare E. L., Economou C. K., Bennett F. J., Dyer C. E., Adams K., McRobie B., Drinkwater R., Littlefair J. E. (2022): Measuring biodiversity from DNA in the air. Current Biology 32: 693-700.e5
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The crisis of declining biodiversity exceeds our current ability to monitor changes in ecosystems. Rapid terrestrial biomonitoring approaches are essential to quantify the causes and consequences of global change. Environmental DNA has revolutionized aquatic ecology, permitting population monitoring4 and remote diversity assessments matching or outperforming conventional methods of community sampling. Despite this model, similar methods have not been widely adopted in terrestrial ecosystems. Here, we demonstrate that DNA from terrestrial animals can be filtered, amplified, and then sequenced from air samples collected in natural settings representing a powerful tool for terrestrial ecology. We collected air samples at a zoological park, where spatially confined non-native species allowed us to track DNA sources. We show that DNA can be collected from air and used to identify species and their ecological interactions. Air samples contained DNA from 25 species of mammals and birds, including 17 known terrestrial resident zoo species. We also identified food items from air sampled in enclosures and detected taxa native to the local area, including the Eurasian hedgehog, endangered in the United Kingdom. Our data demonstrate that airborne eDNA concentrates around recently inhabited areas but disperses away from sources, suggesting an ecology to airborne eDNA and the potential for sampling at a distance. Our findings demonstrate the profound potential of air as a source of DNA for global terrestrial biomonitoring.
Gracanin A., Minchinton T. E., Mikac K. M. (2022): Estimating the density of small mammals using the selfie trap is an effective camera trapping method. Mammal Research 67: 467-482.
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Camera trapping to study wildlife allows for data collection, without the need to capture animals. Traditionally, camera traps have been used to target larger terrestrial mammal species, though recently novel methods and adjustments in procedures have meant camera traps can be used to study small mammals. The selfie trap (a camera trapping method) may present robust sampling and ecological study of small mammals. This study aimed to evaluate the selfie trap method in terms of its ability to detect species and estimate population density. To address this aim, standard small mammal live trapping was undertaken, immediately followed by camera trapping using the selfie trap. Both methods were set to target the arboreal sugar glider (Petaurus breviceps) and semi-arboreal brown antechinus (Antechinus stuartii). The more ground-dwelling bush rat (Rattus fuscipes) was also live trapped and recorded on camera. Across four survey areas, the probability of detection for each of the three species was higher for selfie traps than for live trapping. Spatially explicit capture-recapture models showed that selfie traps were superior at estimating density for brown antechinus and sugar gliders, when compared to simulated live trapping data. Hit rates (number of videos per various time intervals) were correlated with abundance. When correlating various hit rate intervals with abundance, the use of 10-min hit rate was best for predicting sugar glider abundance (R2 = 0.94). The abundance of brown antechinus was estimated from selfie traps using a 24-h hit rate as a predictor (R2 = 0.85). For sugar gliders, the selfie trap can replace live trapping as individuals can be identified through their unique facial stripes and natural ear scars, and thus used in capture-recapture analysis. This method may be useful for monitoring the abundance of other small mammal species that can also be individually recognized from photographs.
Lynggaard C., Bertelsen M. F., Jensen C. V., Johnson M. S., Frøslev T. G., Olsen M. T., Bohmann K. (2022): Airborne environmental DNA for terrestrial vertebrate community monitoring. Current Biology 32: 701-707.
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Biodiversity monitoring at the community scale is a critical element of assessing and studying species distributions, ecology, diversity, and movements, and it is key to understanding and tracking environmental and anthropogenic effects on natural ecosystems. Vertebrates in terrestrial ecosystems are experiencing extinctions and declines in both population numbers and sizes due to increasing threats from human activities and environmental change. Terrestrial vertebrate monitoring using existing methods is generally costly and laborious, and although environmental DNA (eDNA) is becoming the tool of choice to assess biodiversity, few sample types effectively capture terrestrial vertebrate diversity. We hypothesized that eDNA captured from air could allow straightforward collection and characterization of terrestrial vertebrate communities. We filtered air at three localities in the Copenhagen Zoo: a stable, outside between the outdoor enclosures, and in the Rainforest House. Through metabarcoding of airborne eDNA, we detected 49 vertebrate species spanning 26 orders and 37 families: 30 mammal, 13 bird, 4 fish, 1 amphibian, and 1 reptile species. These spanned animals kept at the zoo, species occurring in the zoo surroundings, and species used as feed in the zoo. The detected species comprise a range of taxonomic orders and families, sizes, behaviors, and abundances. We found shorter distance to the air sampling device and higher animal biomass to increase the probability of detection. We hereby show that airborne eDNA can offer a fundamentally new way of studying and monitoring terrestrial communities.
Mas‐Carrió E., Schneider J., Nasanbat B., Ravchig S., Buxton M., Nyamukondiwa C., Stoffel C., Augugliaro C., Ceacero F., Taberlet P., Glaizot O., Christe P., Fumagalli L. (2022): Assessing environmental DNA metabarcoding and camera trap surveys as complementary tools for biomonitoring of remote desert water bodies. Environmental DNA 4: 580-595.
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Biodiversity assessments are indispensable tools for planning and monitoring conservation strategies. Camera traps (CT) are widely used to monitor wildlife and have proven their usefulness. Environmental DNA (eDNA)-based approaches are increasingly implemented for biomonitoring, combining sensitivity, high taxonomic coverage and resolution, non-invasiveness and easiness of sampling, but remain challenging for terrestrial fauna. However, in remote desert areas where scattered water bodies attract terrestrial species, which release their DNA into the water, this method presents a unique opportunity for their detection. In order to identify the most efficient method for a given study system, comparative studies are needed. Here, we compare CT and DNA metabarcoding of water samples collected from two desert ecosystems, the Trans-Altai Gobi in Mongolia and the Kalahari in Botswana. We recorded with CT the visiting patterns of wildlife and studied the correlation with the biodiversity captured with the eDNA approach. The aim of the present study was threefold: (a) to investigate how well waterborne eDNA captures signals of terrestrial fauna in remote desert environments, which have been so far neglected in terms of biomonitoring efforts; (b) to compare two distinct approaches for biomonitoring in such environments; and (c) to draw recommendations for future eDNA-based biomonitoring. We found significant correlations between the two methodologies and describe a detectability score based on variables extracted from CT data and the visiting patterns of wildlife. This supports the use of eDNA-based biomonitoring in these ecosystems and encourages further research to integrate the methodology in the planning and monitoring of conservation strategies.
Newton J. P., Bateman P. W., Heydenrych M. J., Mousavi‐Derazmahalleh M., Nevill P. (2022): Home is where the hollow is: Revealing vertebrate tree hollow user biodiversity with eDNA metabarcoding. Environmental DNA 4: 1078-1091.
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Tree hollows are essential for many vertebrate species, providing both nesting sites and shelter. Globally, old hollow-bearing trees are in decline resulting in many dependent species being under threat. It is, therefore, imperative that vital hollow-bearing trees are preserved, but it is logistically difficult to rapidly determine which hollows are being used and by which taxa. Here, we investigate the efficacy of eDNA metabarcoding as a survey tool for vertebrate hollow users. We compared the identity and richness of hollow-inhabiting vertebrate taxa using eDNA metabarcoding of both sediment from the tree hollows, and material collected using roller swabs. Samples (n = 138) were collected from hollow-bearing tuart trees (Eucalyptus gomphocephala; N = 28), within both an urban remnant and a relatively undisturbed forested area of South-West Western Australia. We detected a wide range of vertebrate taxa, including cryptic species such as the brush-tailed phascogale (Phascogale tapoatafa), while also providing ecologically informative data, such as hollow use by invasive Rainbow Lorikeet (Trichoglossus moluccanus) within the study areas. Our results showed variation in the species detected between methods, with the roller swab method detecting a greater number of species and a higher mean species richness per sample than hollow sediment did. The species detected from both methods did not perfectly overlap, highlighting the value of using multiple methods or substrates to detect a greater number of taxa. Our results suggest eDNA metabarcoding from tree hollow samples offers a sensitive and resource-efficient method of monitoring vertebrate hollow users, if enough hollows are sampled. This provides not only a broad biodiversity assessment tool, but also an effective method for detecting taxa that may be elusive using other methods.
Tan M., Chao W., Cheng J. K., Zhou M., Ma Y., Jiang X., Ge J., Yu L., Feng L. (2022): Animal detection and classification from camera trap images using different mainstream object detection architectures. Animals 12: 1976.
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Camera traps are widely used in wildlife surveys and biodiversity monitoring. Depending on its triggering mechanism, a large number of images or videos are sometimes accumulated. Some literature has proposed the application of deep learning techniques to automatically identify wildlife in camera trap imagery, which can significantly reduce manual work and speed up analysis processes. However, there are few studies validating and comparing the applicability of different models for object detection in real field monitoring scenarios. In this study, we firstly constructed a wildlife image dataset of the Northeast Tiger and Leopard National Park (NTLNP dataset). Furthermore, we evaluated the recognition performance of three currently mainstream object detection architectures and compared the performance of training models on day and night data separately versus together. In this experiment, we selected YOLOv5 series models (anchor-based one-stage), Cascade R-CNN under feature extractor HRNet32 (anchor-based two-stage), and FCOS under feature extractors ResNet50 and ResNet101 (anchor-free one-stage). The experimental results showed that performance of the object detection models of the day-night joint training is satisfying. Specifically, the average result of our models was 0.98 mAP (mean average precision) in the animal image detection and 88% accuracy in the animal video classification. One-stage YOLOv5m achieved the best recognition accuracy. With the help of AI technology, ecologists can extract information from masses of imagery potentially quickly and efficiently, saving much time.
Allen M. C., Kwait R., Vastano A., Kisurin A., Zoccolo I., Jaffe B. D., Angle J. C., Maslo B., Lockwood J. L. (2023): Sampling environmental DNA from trees and soil to detect cryptic arboreal mammals. Scientific Reports 13: 180.
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Environmental DNA (eDNA) approaches to monitoring biodiversity in terrestrial environments have largely focused on sampling water bodies, potentially limiting the geographic and taxonomic scope of eDNA investigations. We assessed the performance of two strictly terrestrial eDNA sampling approaches to detect arboreal mammals, a guild with many threatened and poorly studied taxa worldwide, within two central New Jersey (USA) woodlands. We evaluated species detected with metabarcoding using two eDNA collection methods (tree bark vs. soil sampling), and compared the performance of two detection methods (qPCR vs. metabarcoding) within a single species. Our survey, which included 94 sampling events at 21 trees, detected 16 species of mammals, representing over 60% of the diversity expected in the area. More DNA was found for the 8 arboreal versus 8 non-arboreal species detected (mean: 2466 vs. 289 reads/sample). Soil samples revealed a generally similar composition, but a lower diversity, of mammal species. Detection rates for big brown bat were 3.4 × higher for qPCR over metabarcoding, illustrating the enhanced sensitivity of single-species approaches. Our results suggest that sampling eDNA from on and around trees could serve as a useful new monitoring tool for cryptic arboreal mammal communities globally.
Garrett N. R., Watkins J., Simmons N. B., Fenton B., Maeda‐Obregon A., Sanchez D. E., Froehlich E. M., Walker F. M., Littlefair J. E., Clare E. L. (2023): Airborne eDNA documents a diverse and ecologically complex tropical bat and other mammal community. Environmental DNA 5: 350-362.
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Environmental (e)DNA has rapidly become a powerful biomonitoring tool, particularly in aquatic ecosystems. This approach has not been as widely adopted in terrestrial communities where the methods of vertebrate eDNA collection have varied from the use of secondary collectors such as blood feeding parasites and spider webs, to washing surfaces of leaves and soil sampling. Recent studies have demonstrated the potential of direct collection of eDNA from air sampling, but none have tested how effective airborne eDNA sampling might be in a biodiverse environment. We used three prototype samplers to actively sample a mixed neotropical bat community in a partially controlled environment. We assess whether airborne eDNA can accurately characterize a high diversity community with skewed abundances and to determine if filter design impacts DNA collection and taxonomic recovery. Our study provides evidence for the accuracy of airborne eDNA as a detection tool and highlights its potential for monitoring high density, diverse assemblages such as bat roosts. Analysis of air samples recovered >91% of the species present and some limited relationship between species abundance and read count. Our data suggests this method can accurately depict a diverse mixed-mammal community, particularly when the location is contained (e.g., a roost, den or burrow) but also highlights the potential for secondary transfer of eDNA material on clothing and equipment. Our results also demonstrate that simple, inexpensive, battery-operated homemade air samplers can collect an abundance of eDNA from the air, opening the opportunity for sampling in remote environments.
Johnson M. D., Barnes M. A., Garrett N. R., Clare E. L. (2023): Answers blowing in the wind: Detection of birds, mammals, and amphibians with airborne environmental DNA in a natural environment over a yearlong survey. Environmental DNA 5: 375-387.
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Analysis of environmental DNA (eDNA) from passively collected airborne dust has demonstrated broad success for sensitive and robust detection of plants. Recent experiments at small spatial scales have suggested that animals can also be detected using airborne eDNA. However, airborne eDNA analysis has never been used for a long-term whole-community assessment of a natural terrestrial community or with passive dust collectors. We conducted a metabarcoding survey targeting vertebrate eDNA from dust carried in the air on an approximately 130-acre shortgrass prairie passively collected over the course of a year. Our survey detected a wide variety of animal forms including an amphibian species, several bird species, and both small and large mammals. We found that airborne eDNA signals changed with known patterns of animal activity, wind speed, and rainfall. Overall, we demonstrate that passively collected airborne dust carries eDNA from terrestrial animals and could be used to detect a wide variety of terrestrial vertebrate species in a natural environment with minimal effort. To develop this as a valuable monitoring tool, research needs to focus on the ecology of eDNA carried in the air, which includes the origin, state, transport, dispersal, and fate of eDNA in the environment.
Roy A. M., Bhaduri J., Kumar T., Raj K. (2023): WilDect-YOLO: An efficient and robust computer vision-based accurate object localization model for automated endangered wildlife detection. Ecological Informatics 75: 101919.
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With climatic instability, various ecological disturbances, and human actions threaten the existence of various endangered wildlife species. Therefore, an up-to-date accurate and detailed detection process plays an important role in protecting biodiversity losses, conservation, and ecosystem management. Current state-of-the-art wildlife detection models, however, often lack superior feature extraction capability in complex environments, limiting the development of accurate and reliable detection models. To this end, we present WilDect-YOLO, a deep learning (DL)-based automated high-performance detection model for real-time endangered wildlife detection. In the model, we introduce a residual block in the CSPDarknet53 backbone for strong and discriminating deep spatial features extraction and integrate DenseNet blocks to improve in preserving critical feature information. To enhance receptive field representation, preserve fine-grain localized information, and improve feature fusion, a Spatial Pyramid Pooling (SPP) and modified Path Aggregation Network (PANet) have been implemented that results in superior detection under various challenging environments. Evaluating the model performance in a custom endangered wildlife dataset considering high variability and complex backgrounds, WilDect-YOLO obtains a mean average precision (mAP) value of 96.89%, F1-score of 97.87%, and precision value of 97.18% at a detection rate of 59.20 FPS outperforming current state-of-the-art models. The present research provides an effective and efficient detection framework addressing the shortcoming of existing DL-based wildlife detection models by providing highly accurate species-level localized bounding box prediction. Current work constitutes a step toward a non-invasive, fully automated animal observation system in real-time in-field applications.
Liu L., Mou C., Xu F. (2024): Improved wildlife recognition through fusing camera trap images and temporal metadata. Diversity 16: 139.
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Camera traps play an important role in biodiversity monitoring. An increasing number of studies have been conducted to automatically recognize wildlife in camera trap images through deep learning. However, wildlife recognition by camera trap images alone is often limited by the size and quality of the dataset. To address the above issues, we propose the Temporal-SE-ResNet50 network, which aims to improve wildlife recognition accuracy by exploiting the temporal information attached to camera trap images. First, we constructed the SE-ResNet50 network to extract image features. Second, we obtained temporal metadata from camera trap images, and after cyclical encoding, we used a residual multilayer perceptron (MLP) network to obtain temporal features. Finally, the image features and temporal features were fused in wildlife identification by a dynamic MLP module. The experimental results on the Camdeboo dataset show that the accuracy of wildlife recognition after fusing the image and temporal information is about 93.10%, which is an improvement of 0.53%, 0.94%, 1.35%, 2.93%, and 5.98%, respectively, compared with the ResNet50, VGG19, ShuffleNetV2-2.0x, MobileNetV3-L, and ConvNeXt-B models. Furthermore, we demonstrate the effectiveness of the proposed method on different national park camera trap datasets. Our method provides a new idea for fusing animal domain knowledge to further improve the accuracy of wildlife recognition, which can better serve wildlife conservation and ecological research.
Newton J. P., Nevill P., Bateman P. W., Campbell M. A., Allentoft M. E. (2024): Spider webs capture environmental DNA from terrestrial vertebrates. iScience 27: 108904.
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Environmental DNA holds significant promise as a non-invasive tool for tracking terrestrial biodiversity. However, in non-homogenous terrestrial environments, the continual exploration of new substrates is crucial. Here we test the hypothesis that spider webs can act as passive biofilters, capturing eDNA from vertebrates present in the local environment. Using a metabarcoding approach, we detected vertebrate eDNA from all analyzed spider webs (N = 49). Spider webs obtained from an Australian woodland locality yielded vertebrate eDNA from 32 different species, including native mammals and birds. In contrast, webs from Perth Zoo, less than 50 km away, yielded eDNA from 61 different vertebrates and produced a highly distinct species composition, largely reflecting exotic species hosted in the zoo. We show that higher animal biomass and proximity to animal enclosures increased eDNA detection probability in the zoo. Our results indicate a tremendous potential for using spider webs as a cost-effective means to monitor terrestrial vertebrates.
Polling M., Buij R., Laros I., de Groot G. A. (2024): Continuous daily sampling of airborne eDNA detects all vertebrate species identified by camera traps. Environmental DNA 6: e591.
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Ongoing pressures on global biodiversity require conservation action that is not possible without effective biomonitoring. Terrestrial vertebrate surveys are commonly performed using camera traps, a time-intensive method known to miss many small or arboreal species and birds. Recent advances have shown airborne eDNA to be a potentially suitable technique to more effectively monitor vertebrate communities in a time- and cost-effective manner. Here, we test whether commercially available air samplers that collect air particles 24/7 during a 1-week period can be used to detect the presence of vertebrates through airborne eDNA. The results are compared to camera trap records at three locations with differing habitats in the Netherlands. Simultaneous sampling with three different air samplers for 3 weeks resulted in detection of 154 vertebrate taxa, of which the majority were birds or mammals (113 and 33 species, respectively), along with four fish and four amphibian species. All species observed using camera traps were also retrieved via airborne eDNA, although not on every day of sampling. The Burkard spore trap, used routinely for pollen monitoring, showed the highest number of vertebrate species, and only in three samples when a mammal species was detected using a camera trap it remained undetected via eDNA. We also detected unique species at the three locations using airborne eDNA, indicative of the habitat in which they were living. However, we also detected species that we could not account for. The multitude of species found using airborne eDNA compared to camera traps indicate the sensitivity of the method; however, subsequent studies should prioritize validation of these findings through alternative biomonitoring approaches.
Sohn H., Song Y. (2024): Monitoring of mammal and bird species in an urban ecological park using environmental DNA metabarcoding. Urban Ecosystems 27: 1891-1904.
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Monitoring species distribution and abundance accurately and efficiently are vital for conservation efforts. Next-generation sequencing and DNA metabarcoding using environmental DNA (eDNA) allow for the simultaneous identification of multiple species in one sample, enabling swift biodiversity assessment in complex ecosystems. However, most eDNA studies focus on aquatic organisms and ecosystems. This study’s main objective was to use eDNA metabarcoding to monitor mammal and bird species in an urban ecological park. The chosen study site was Gildong Ecological Park, Seoul, South Korea, with a total area of 80,000 m2 divided into three marsh area, a forested mountain area, and a rural experience learning center. Water sampling occurred five times from August to September, yielding 65 samples from three park sections. We employed MiMammal and MiBird primers targeting mitochondrial 12 S to investigate mammals and birds, serving as pivotal biological indicators within urban ecosystems. Metabarcoding revealed the presence of 73% (11/15) and 67% (represented 67% of the total 6268 individual) of the dominant mammalian and avian species, respectively, known to inhabit the park, compared to the results of traditional surveys. The mountain samples (1.51) and marsh samples (2.32) had significantly different median read counts when including all species; however, the same comparison within each taxonomic group yielded no statistically significant differences. Though we detected species differences using eDNA across summer, autumn, and winter monitoring, no statistically significant differences were found among seasons within the park. However, the park’s area is relatively small for detecting variations in eDNA. This might be because there is a lot of animal activity throughout the study site and/or a limited influence of microhabitats. These results could provide valuable insights for using eDNA to monitor animals in urban ecological parks.
Tetzlaff S. J., Katz A. D., Wolff P. J., Kleitch M. E. (2024): Comparison of soil eDNA to camera traps for assessing mammal and bird community composition and site use. Ecology and Evolution 14: e70022.
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Species detections often vary depending on the survey methods employed. Some species may go undetected when using only one approach in community-level inventory and monitoring programs, which has management and conservation implications. We conducted a comparative study of terrestrial mammal and bird detections in the spring and summer of 2021 by placing camera traps at 30 locations across a large military installation in northern Michigan, USA and testing replicate soil samples from these sites for environmental DNA (eDNA) using an established vertebrate metabarcoding assay. We detected a total of 48 taxa from both survey methods: 26 mammalian taxa (excluding humans, 24 to species and two to genus) and 22 avian taxa (21 to species and one to genus). We detected a relatively even distribution of mammalian taxa on cameras (17) and via eDNA analysis (15), with seven taxa detected from both methods. Most medium-to-large carnivores were detected only on cameras, whereas semi-fossorial small mammals were detected only via eDNA analysis. We detected higher bird diversity with camera traps (18 taxa) compared to eDNA analysis (eight taxa; four taxa were detected with both methods), but cameras alone were most effective at detecting smaller birds that frequently occupy arboreal environments. We also used Bayesian spatial occupancy models for two widely distributed game species (white-tailed deer, Odocoileus virginianus, and ruffed grouse, Bonasa umbellus) that were moderately detected with both survey methods and found species-specific site use (occupancy) estimates were similar between cameras and eDNA analysis. Concordant with similar studies, our findings suggest that a combination of camera trap and eDNA surveys could be most useful for assessing the composition of terrestrial mammal communities. Camera traps may be most efficient for assessing bird diversity but can be complemented with eDNA analysis, particularly for species that spend considerable time on the ground.