MORPHOLOGY: FISH

Deakos M. H. (2010): Paired-laser photogrammetry as a simple and accurate system for measuring the body size of free-ranging manta rays Manta alfredi. Aquatic Biology 10: 1-10.
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Morphometrics are useful for describing and managing animal populations, but measurements can be difficult to obtain, especially on large free-ranging aquatic animals. The accuracy and precision of paired-laser photogrammetry were tested as a simple and non-invasive remote sensing system for measuring the body size of free-ranging, resident manta rays Manta alfredi, a newly described species that is poorly understood. Based on repeated measurements of a pipe of known size, the paired-laser system proved accurate (mean error of 0.39%) and precise (CV = 0.54%). Repeated measurements on 154 different manta rays visiting a cleaning station off Maui, Hawaii, produced a mean CV of 1.46%. Disc length (DL) measurements were more precise than disc width (DW) measurements, and an empirically derived disc ratio (DR) function was applied to convert DL to DW measurements for standard comparison with other studies. Sexual dimorphism was present with the largest female (3.64 m DW) 18% larger than the largest male (3.03 m DW). Sexual maturity in females, based on evidence of pregnancy and mating scars, was conservatively determined to be 3.37 m DW. The DW at which 50% of the males were likely to be mature (based on clasper length) was between 2.7 and 2.8 m. The absence of individuals < 2.5 m DW suggests that age class segregation occurs in this population. Paired-laser photogrammetry proved to be a simple, non-invasive, accurate, and precise method for sizing free-ranging manta rays. Repeated measurements on known individuals over time could provide population growth parameters needed for adequate management of this poorly understood species.

Bower M. R., Gaines D. B., Wilson K. P., Wullschleger J. G., Dzul M. C., Quist M. C., Dinsmore S. J. (2011): Accuracy and precision of visual estimates and photogrammetric measurements of the length of a small-bodied fish. North American Journal of Fisheries Management 31: 138-143.
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We assessed the accuracy and precision of visual estimates from two divers and photogrammetric measurements from a diver-operated stereo-video camera system for determining the length of Saratoga Springs pupfish Cyprinodon nevadensis nevadensis (12–36 mm total length) under controlled conditions. Visual estimates by two divers differed significantly from true fish length (P < 0.001) but were not significantly different from each other (P = 0.42). Levels of accuracy and precision were similar to those previously reported for visual estimates by divers. On average, the two divers underestimated fish length by 2.74 mm (11%) and 2.93 mm (12%). The magnitude of underestimation error increased with fish length. Photogrammetric measurements from a stereo-video camera system were more accurate and precise than diver estimates of fish length. Little to no bias was evident (mean error = 0.05 mm), and the level of precision (coefficient of variation of the difference between observed length and true length) was 4.5% for the photogrammetric measurements compared with 10% and 11% for the two divers’ estimates. In comparison with underwater visual surveys, surveys that use a stereo-video camera system may increase the consistency of long-term data sets and improve resolution to detect important length differences in small-bodied fishes. Managers must remain careful to avoid or correct sampling biases, which can affect underwater visual surveys and stereo-video surveys alike.

Rohner C. A., Richardson A. J., Marshall A. D., Weeks S. J., Pierce S. J. (2011): How large is the world’s largest fish? Measuring whale sharks Rhincodon typus with laser photogrammetry. Journal of Fish Biology 78: 378-385.
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Laser photogrammetry was found to be a promising new cost-effective technique for measuring free-swimming whale sharks Rhincodon typus. Photogrammetric measurements were more precise than visual size estimates by experienced researchers, with results from the two methods differing by 9· 8 ± 1· 1% (mean ±s.e.). A new metric of total length and the length between the fifth gill and first dorsal fin (r2 = 0· 93) is proposed to facilitate easy, accurate length measurements of whale sharks in the field.

Richardson J. R., Shears N. T., Taylor R. B. (2015): Using relative eye size to estimate the length of fish from a single camera image. Marine Ecology Progress Series 538: 213-219.
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Estimating fish sizes from camera images is an important requirement of many fish monitoring programs, typically involving complex and expensive technology such as stereo-video. However, as a fish grows, the relative size of its eye typically decreases, providing a potential means of estimating fish size from a single image. We show that the ratio of head height to eye diameter is a good predictor of body length for 6 species of common New Zealand reef fish representing 6 different families. The regression equations describing such relationships can be used to estimate lengths of individual fish from single photographs or video frames, which in turn can be used to estimate the distance of each fish from the camera (by determining the proportion of the image frame occupied by an object of known length at known distances) in order to standardize the survey area. In a field test, lengths of 90% of 511 individual snapper Pagrus auratus recorded by unbaited video cameras could be estimated from their head height:eye diameter ratios. This method enables fish lengths to be estimated from single still or video images, allowing fish to be monitored with small inexpensive cameras. While this simple and cost-effective approach will increase the accessibility of video monitoring techniques, it will be best suited to areas where fish diversity is low enough to enable equations to be obtained for all common species, or where the focus is on a subset of species (e.g. harvested species).

Delacy C. R., Olsen A., Howey L. A., Chapman D. D., Brooks E. J., Bond M. E. (2017). Affordable and accurate stereo-video system for measuring dimensions underwater: a case study using oceanic whitetip sharks Carcharhinus longimanus. Marine Ecology Progress Series 574: 75-84.
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Non-intrusive and non-destructive acquisition of length measurements for marine megafauna is increasingly valuable given growing threats to many species’ long-term survival. Stereo videography provides a means of obtaining length data with minimal impact on the organism and minimal observer bias. However, for many researchers, there are still significant financial barriers to employing stereo videography. Small-action cameras have reduced costs, but camera calibration still requires significant investment in software and equipment. Here, we trial open source calibration procedures using the R package StereoMorph and a simple 2D checkerboard as a calibration object to test if this approach yields accurate length data. We used a stereo-video system comprising 2 GoPro™ cameras to estimate the lengths of known targets in a pool and the lengths of oceanic whitetip sharks Carcharhinus longimanus in situ. Sharks were restrained in water alongside a boat and measured with a tape measure for comparison with the stereo-video lengths. Both pool and field trials yielded accurate results comparable to previous studies using 3D calibration cubes. Stereo-video measurements of lengths >1 m had proportional errors of <1% in the pool and <3.0% (64.2 mm) in comparison with tape-measured lengths of sharks in the field. Our open source calibration methods and affordable GoPro™-based stereo-video system yielded measurements that are comparable to other systems that use 3D calibration techniques and more expensive cameras. Additionally, we improve on previous attempts of 2D calibration approaches.

Rogers T. D., Cambiè G., Kaiser M. J. (2017): Determination of size, sex and maturity stage of free swimming catsharks using laser photogrammetry. Marine Biology 164: 213.
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The lack of detailed life history (LH) information (e.g. age, growth, size at maturity, sex composition etc.) for many species of conservation importance limits the implementation of appropriate conservation measures. Typically, LH information is acquired using lethal sampling techniques, which undermines the goal of conservation. This is particularly problematic for many shark species that have low fecundity and slow growth rates. Here we tested the use of non-invasive laser photogrammetry to measure body morphometry in vivo. We used random forest classification models to identify allometric relationships (ratios between body measurements) that discriminated between the sex and stage of sexual maturity of Scyliorhinus canicula. We coupled the use of allometric ratios (determined from cadavers) with parallel laser photogrammetry, in order to collect total length (TL) and finer scale morphometrics from 37 free-swimming individuals. TL measurements proved to be accurate (SE = 5.2%) and precise (CV = 1.8%), and did not differ significantly from the known TL of the respective animal (t36 = 0.7, P = 0.5). Conditional Inference tree model predictions of free-swimming sharks correctly predicted 100% of mature males and 79% of immature males. Our results suggest that when used together, allometric ratios and parallel laser photogrammetry have the potential to be a promising alternative to collect essential life history information from free swimming animals and avoids the need for destructive sampling.

Perry C. T., Figueiredo J., Vaudo J. J., Hancock J., Rees R., Shivji M. (2018): Comparing length-measurement methods and estimating growth parameters of free-swimming whale sharks (Rhincodon typus) near the South Ari Atoll, Maldives. Marine and Freshwater Research 69: 1487-1495.
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Whale sharks (Rhincodon typus) are an endangered species whose growth and reproductive biology are poorly understood. Given their conservation concern, estimating growth parameters, as traditionally derived from vertebral samples of dead animals, is challenging. We used a non-invasive approach to investigate growth parameters of whale sharks frequenting the South Ari Atoll, Maldives, by analysing repeat measurements of free-swimming sharks over a 10-year period. Total lengths of the sharks were estimated by three measurement methods. Visual estimates underestimated the sizes of large sharks, whereas laser and tape measurements yielded results that were similar to one another. The Maldives aggregation consisted of primarily male (91%) juvenile (total length = 3.16–8.00 m) sharks and sharks new to the area were significantly smaller than were returning sharks, which suggests that this site may constitute a secondary nursery ground. Estimates of von Bertalanffy (VBG) growth parameters for combined sexes (L = 19.6 m, k = 0.021 year–1) were calculated from 186 encounters with 44 sharks. For males, VBG parameters (L = 18.1 m, k = 0.023 year–1) were calculated from 177 encounters with 40 sharks and correspond to a male age at maturity of ~25 years and longevity of ~130 years. Differences between these estimates and those from other studies underscore the need for regional studies.

Monkman G. G., Hyder K., Kaiser M. J., Vidal F. P. (2019): Using machine vision to estimate fish length from images using regional convolutional neural networks. Methods in Ecology and Evolution 10: 2045-2056.
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An image can encode date, time, location and camera information as metadata and implicitly encodes species information and data on human activity, for example the size distribution of fish removals. Accurate length estimates can be made from images using a fiducial marker; however, their manual extraction is time-consuming and estimates are inaccurate without control over the imaging system. This article presents a methodology which uses machine vision to estimate the total length (TL) of a fusiform fish (European sea bass). Three regional convolutional neural networks (R-CNN) were trained from public images. Images of European sea bass were captured with a fiducial marker with three non-specialist cameras. Images were undistorted using the intrinsic lens properties calculated for the camera in OpenCV; then TL was estimated using machine vision (MV) to detect both marker and subject. MV performance was evaluated for the three R-CNNs under downsampling and rotation of the captured images. Each R-CNN accurately predicted the location of fish in test images (mean intersection over union, 93%) and estimates of TL were accurate, with percent mean bias error (%MBE [95% CIs]) = 2.2% [2.0, 2.4]). Detections were robust to horizontal flipping and downsampling. TL estimates at absolute image rotations >20° became increasingly inaccurate but %MBE [95% CIs] was reduced to −0.1% [−0.2, 0.1] using machine learning to remove outliers and model bias. Machine vision can classify and derive measurements of species from images without specialist equipment. It is anticipated that ecological researchers and managers will make increasing use of MV where image data are collected (e.g. in remote electronic monitoring, virtual observations, wildlife surveys and morphometrics) and MV will be of particular utility where large volumes of image data are gathered.

Jech J. M., Johnson J. J., Lutcavage M., Vanderlaan A. S., Rzhanov Y., LeRoi D. (2020): Measurements of juvenile Atlantic bluefin tuna (Thunnus thynnus) size using an unmanned aerial system. Journal of Unmanned Vehicle Systems 8: 140-160.
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An APH-22 vertical-takeoff-and-landing hexacopter was used to collect aerial images of schools and individuals of juvenile Atlantic bluefin tuna (ABFT; Thunnus thynnus) at the sea surface in the southern Gulf of Maine. Quantitative measures of fish length, width, and inter-fish spacing were obtained from these images by applying calibration settings and performance measures from calibrating, testing, and evaluating the onboard motion and altimeter sensors and the digital camera and lenses. The accuracy and precision of the onboard motion sensors, camera, and lens calibrations were sufficient to provide length measurements to sub-centimeter precision, but the altimeter performance was least reliable and required additional information, such as images of known-sized objects during each flight, to provide measurements at the accuracy and precision needed for data to be incorporated in fisheries management. The APH-22 was ideal for acquiring images of ABFT individuals and schools and may be a useful tool for remotely monitoring the behavior and body condition of these elusive animals.

Monkman G. G., Hyder K., Kaiser M. J., Vidal F. P. (2020): Accurate estimation of fish length in single camera photogrammetry with a fiducial marker. ICES Journal of Marine Science 77: 2245-2254.
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Videogrammetry and photogrammetry are increasingly being used in marine science for unsupervised data collection. The camera systems employed are complex, in contrast to “consumer” digital cameras and smartphones carried by potential citizen scientists. However, using consumer cameras in photogrammetry will introduce unknown length estimation errors through both the image acquisition process and lens distortion. This study presents a methodology to achieve accurate 2-dimensional (2-D) total length (TL) estimates of fish without specialist equipment or proprietary software. Photographs of fish were captured with an action camera using a background fiducial marker, a foreground fiducial marker and a laser marker. The geometric properties of the lens were modelled with OpenCV to correct image distortion. TL estimates were corrected for parallax effects using an algorithm requiring only the initial length estimate and known fish morphometric relationships. Correcting image distortion decreased RMSE by 96% and the percentage mean bias error (%MBE) by 50%. Correcting for parallax effects achieved a %MBE of −0.6%. This study demonstrates that the morphometric measurement of different species can be accurately estimated without the need for complex camera equipment, making it particularly suitable for deployment in citizen science and other volunteer-based data collection endeavours.

Liao Y. H., Zhou C. W., Liu W. Z., Jin J. Y., Li D. Y., Liu F., Fan D. D., Zou Y., Mu Z. B., Shen J., Liu C. N., Xiao S. J., Yuan X. H., Liu H. P. (2021): 3DPhenoFish: Application for two-and three-dimensional fish morphological phenotype extraction from point cloud analysis. Zoological Research 42: 492.
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Fish morphological phenotypes are important resources in artificial breeding, functional gene mapping, and population-based studies in aquaculture and ecology. Traditional morphological measurement of phenotypes is rather expensive in terms of time and labor. More importantly, manual measurement is highly dependent on operational experience, which can lead to subjective phenotyping results. Here, we developed 3DPhenoFish software to extract fish morphological phenotypes from three-dimensional (3D) point cloud data. Algorithms for background elimination, coordinate normalization, image segmentation, key point recognition, and phenotype extraction were developed and integrated into an intuitive user interface. Furthermore, 18 key points and traditional 2D morphological traits, along with 3D phenotypes, including area and volume, can be automatically obtained in a visualized manner. Intuitive fine-tuning of key points and customized definitions of phenotypes are also allowed in the software. Using 3DPhenoFish, we performed high-throughput phenotyping for four endemic Schizothoracinae species, including Schizopygopsis younghusbandi, Oxygymnocypris stewartii, Ptychobarbus dipogon, and Schizothorax oconnori. Results indicated that the morphological phenotypes from 3DPhenoFish exhibited high linear correlation (>0.94) with manual measurements and offered informative traits to discriminate samples of different species and even for different populations of the same species. In summary, we developed an efficient, accurate, and customizable tool, 3DPhenoFish, to extract morphological phenotypes from point cloud data, which should help overcome traditional challenges in manual measurements. 3DPhenoFish can be used for research on morphological phenotypes in fish, including functional gene mapping, artificial selection, and conservation studies. 3DPhenoFish is an open-source software and can be downloaded for free at https://github.com/lyh24k/3DPhenoFish/tree/master.

Petrellis N. (2021): Measurement of fish morphological features through image processing and deep learning techniques. Applied Sciences 11: 4416.
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Noninvasive morphological feature monitoring is essential in fish culture, since these features are currently measured manually with a high cost. These morphological parameters can concern the size or mass of the fish, or its health as indicated, for example, by the color of the eyes or the gills. Several approaches have been proposed, based either on image processing or machine learning techniques. In this paper, both of these approaches have been combined in a unified environment with novel techniques (e.g., edge or corner detection and pattern stretching) to estimate the fish’s relative length, height and the area it occupies in the image. The method can be extended to estimate the absolute dimensions if a pair of cameras is used for obscured or slanted fish. Moreover, important fish parts such as the caudal, spiny and soft dorsal, pelvic and anal fins are located. Four species popular in fish cultures have been studied: Dicentrarchus labrax (sea bass), Diplodus puntazzo, Merluccius merluccius (cod fish) and Sparus aurata (sea bream). Taking into consideration that there are no large public datasets for the specific species, the training and testing of the developed methods has been performed using 25 photographs per species. The fish length estimation error ranges between 1.9% and 13.2%, which is comparable to the referenced approaches that are trained with much larger datasets and do not offer the full functionality of the proposed method.

Rasmussen J. H., Moyano M., Fuiman L. A., Oomen R. A. (2022): FishSizer: Software solution for efficiently measuring larval fish size. Ecology and Evolution 12: e8672.
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Length and depth of fish larvae are part of the fundamental measurements in many marine ecology studies involving early fish life history. Until now, obtaining these measurements has required intensive manual labor and the risk of inter- and intra-observer variability. We developed an open-source software solution to semi-automate the measurement process and thereby reduce both time consumption and technical variability. Using contrast-based edge detection, the software segments images of a fish larva into “larva” and “background.” Length and depth are extracted from the “larva” segmentation while taking curvature of the larva into consideration. The graphical user interface optimizes workflow and ease of usage, thereby reducing time consumption for both training and analysis. The software allows for visual verification of all measurements. A comparison of measurement methods on a set of larva images showed that this software reduces measurement time by 66%–78% relative to commonly used software. Using this software instead of the commonly used manual approach has the potential to save researchers from many hours of monotonous work. No adjustment was necessary for 89% of the images regarding length (70% for depth). Hence, the only workload on most images was the visual inspection. As the visual inspection and manual dimension extraction works in the same way as currently used software, we expect no loss in accuracy.

Setyawan E., Stevenson B. C., Izuan M., Constantine R., Erdmann M. V. (2022): How big is that manta ray? A novel and non-invasive method for measuring reef manta rays using small drones. Drones 6: 63.
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This study explores the application of small, commercially available drones to determine morphometric the measurements and record key demographic parameters of reef manta rays (Mobula alfredi) in Raja Ampat, Indonesia. DJI Mavic 2 Pro drones were used to obtain videos of surface-feeding M. alfredi with a floating, known-length PVC pipe as a reference scale—thus avoiding the need to utilize altitude readings, which are known to be unreliable in small drones, in our photogrammetry approach. Three dimensions (disc length (DL), disc width (DW), and cranial width (CW)) from 86 different individuals were measured. A hierarchical multivariate model was used to estimate the true measurements of these three dimensions and their population-level multivariate distributions. The estimated true measurements of these dimensions were highly accurate and precise, with the measurement of CW more accurate than that of DL and, especially, of DW. Each pairing of these dimensions exhibited strong linear relationships, with estimated correlation coefficients ranging from 0.98–0.99. Given these, our model allows us to accurately calculate DW (as the standard measure of body size for mobulid rays) using the more accurate CW and DL measurements. We estimate that the smallest mature M. alfredi of each sex we measured were 274.8 cm (males, n = 30) and 323.5 cm DW (females, n = 8). We conclude that small drones are useful for providing an accurate “snapshot” of the size distribution of surface-feeding M. alfredi aggregations and for determining the sex and maturity of larger individuals, all with minimal impact on this vulnerable species.

Whitehead D. A., Ayres K. A., Gayford J. H., Ketchum J. T., Galván-Magana F., Christiansen F. (2022): Aerial photogrammetry of whale sharks (Rhincodon typus) in the Bay of La Paz, using an unoccupied aerial vehicle. Marine Biology 169: 94.
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Measurements obtained from aerial imagery can be used to calculate body shape, condition and growth rates of large surface-associated marine megafauna. In this study, an unoccupied aerial vehicle (UAV) was used to obtain aerial images of an elasmobranch species, the whale shark (Rhincodon typus). Pre-caudal length (PCL) and multiple body width measurements were taken from aerial images of 26 juvenile whale sharks, obtained between November 2020 and February 2021 in the La Paz Bay, Mexico. PCL ranged from 2.98 to 6.43 m, with a mean of 4.93 m (SD = 1.00). Body width was found to be greatest in the region by the snout and anterior contacts of the pectoral fins. Body width decreased in a near-linear manner from ~ 18% PCL at the midpoint to ~ 10% PCL at the posterior end of the body. There was a significant linear relationship between whale shark dorsal surface area (SA) and PCL on the log–log scale (LM: F1,24 = 647.7, P < 0.001), showing that whale sharks increase exponentially in overall body size as they increase in body length. However, there was no effect of PCL on the relative body width at the different measurement sites, suggesting that body shape of whale sharks was similar across the size range measured in this study. Finally, the body condition of the sharks, measured as the residual of the relationship between SA and PCL, varied between − 21.6% and  + 14.0%. This study highlights the benefits of using UAV photogrammetry to measure large marine fauna, to obtain valuable morphometric data to study their physiology and bioenergetics.

Luzzatto D., Cussac V. (2023): A novel non-invasive efficient photography-based technique for length measuring and individual identification of seahorses. Scientific Reports 13: 18017.
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This study aimed to develop a non-invasive and efficient method for measuring and identifying individual seahorses (Hippocampus patagonicus) in their natural habitat. A total of 976 seahorses were captured and photographed on a measuring board to obtain standard length (Ls) measurements. Head photographs were also taken for individual recognition, and a set of 100 seahorses were tagged with visible implant elastomers (VIE) to verify the correspondence between photograph recognition and the applied tags. The analysis showed no significant difference between left and right Ls measurements. The unique pattern of white dots on the heads served as individual fingerprints, consistent with VIE tagging. The recapture rate was 12%, with 89 individuals observed multiple times. Two distinct growth patterns were identified: males exhibited higher growth rates and a negative correlation with Ls compared to females. Released seahorses exhibited significantly different behaviors that were related to their sizes (Ls). Smaller seahorses tended to swim slowly towards nearby holdfasts, while larger seahorses escaped further or remained rigid before grasping a holdfast. The proposed methodology allowed for estimating individual seahorse growth rates, and the measurements were objective and precise. The results were obtained through quick and minimally invasive manipulation of the observed individuals.