HEALTH MONITORING: CNIDARIANS
CORALS
Guppy R., Bythell J. C. (2006): Environmental effects on bacterial diversity in the surface mucus layer of the reef coral Montastraea faveolata. Marine Ecology Progress Series 328: 133-142.
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Abstract
Spatial and temporal variation in bacterial 16S rDNA diversity from healthy coral Montastraea faveolata (Ellis & Solander, 1786) was investigated using denaturing gradient gel electrophoresis (DGGE). The microbial communities of the surface mucus layer (SML) were investigated at 5 sites in Tobago of varying water quality and proximity to the mainland. Presence/absence and band intensity data from DGGE profiles were used as a relative measure of diversity of the microbial community structure. Multivariate analyses using PRIMER software Version 6.1.5 (multidimensional scaling and analysis of similarity) showed that microbial communities associated with corals from within the same reef area were very similar (p = 0.093), that there were significant differences between sites (p = 0.001), and that SML communities were significantly different from the microbial community within the water column (p = 0.001). No strong correlations between the SML bacterial community structure and measured water quality parameters were observed using a biota-environment matching routine within PRIMER (BIOENV). Strong seasonal effects were observed on tagged corals from sites that were re-sampled 6 times covering the wet and dry seasons. Although the SML of M. faveolata appears to support a distinct microbial community, this study shows that intraspecific temporal and spatial variation also exists, and reasons for these differences are explored.
Lange I. D., Perry C. T. (2020): A quick, easy and non‐invasive method to quantify coral growth rates using photogrammetry and 3D model comparisons. Methods in Ecology and Evolution 11: 714-726.
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Abstract
Coral growth rates vary significantly with environmental conditions and are thus important indicators of coral health and reef carbonate production. Despite the importance of this metric, data are sparse for most coral genera and species globally, including for many key reef-building species. Traditional methods to obtain growth rates, such as coral coring or staining with Alizarin are destructive and only work for a limited number of species and morphological growth forms. Emerging approaches, using underwater photogrammetry to create digital models of coral colonies, are providing novel and non-invasive ways to explore colony-scale growth patterns and to address existing knowledge gaps. We developed an easy-to-follow workflow to construct three-dimensional (3D) models from overlapping photographs and to measure linear, radial and vertical extension rates of branching, massive and encrusting corals after aligning colony models from subsequent years. The method presented here was applied to measure extension rates for 46 colonies of nine coral species in the remote Chagos Archipelago, Indian Ocean. Proposed image acquisition and software settings produced 3D models of consistently high resolution and detail (precision ≤ 0.2 mm) and variability in growth measurements was small despite manual alignment, clipping and ruler placement (SD ≤ 0.9 mm). Measured extension rates for the Chagos Archipelago are similar to published rates in the Indo-Pacific where comparable data are available, and provide the first published rates for several species. For encrusting corals, the results emphasize the importance of differentiating between radial and vertical growth. Photogrammetry and 3D model comparisons provide a fast, easy, inexpensive and non-invasive method to quantify coral growth rates for a range of species and morphological growth forms. The simplicity of the presented workflow encourages its repeatability and permits non-specialists to learn photogrammetry with the goal of obtaining linear coral growth rates. Coral growth rates are essential metrics to quantify functional consequences of ongoing community changes on coral reefs and expanded datasets for key coral taxa will aid predictions of geographic variations in coral reef response to increasing global stressors.