Comparing the information content of coral reef geomorphological and biological habitat maps, Amirantes Archipelago (Seychelles), Western Indian Ocean

Increasing the use of geomorphological map products in marine spatial planning has the potential to greatly enhance return on mapping investment as they are commonly two orders of magnitude cheaper to produce than biologically-focussed maps of benthic communities and shallow substrates. The efficacy of geomorphological maps derived from remotely sensed imagery as surrogates for habitat diversity is explored by comparing two map sets of the platform reefs and atolls of the Amirantes Archipelago (Seychelles), Western Indian Ocean. One mapping campaign utilised Compact Airborne Spectrographic Imagery (19 wavebands, 1 m spatial resolution) to classify 11 islands and associated reefs into 25 biological habitat classes while the other campaign used Landsat 7 þ ETM imagery (7 bands, 30 m spatial resolution) to generate maps of 14 geomorphic classes. The maps were compared across a range of characteristics, including habitat richness (number of classes mapped), diversity (ShannoneWeiner statistic) and thematic content (Cramer’s V statistic). Between maps, a strong relationship was revealed for habitat richness (R2 ¼ 0.76), a moderate relationship for class diversity and evenness (R2 ¼ 0.63) and a variable relationship for thematic content, dependent on site complexity (V range 0.43 e0.93). Geomorphic maps emerged as robust predictors of the habitat richness in the Amirantes. Such maps therefore demonstrate high potential value for informing coastal management activities and conservation planning by drawing on information beyond their own thematic content and thus maximizing the return on mapping investment

Multi-scale marine biodiversity patterns inferred efficiently from habitat image processing

Cost-effective proxies of biodiversity and species abundance, applicable across a range of spatial scales, are needed for setting conservation priorities and planning action. We outline a rapid, efficient, and low-cost measure of spectral signal from digital habitat images that, being an effective proxy for habitat complexity, correlates with species diversity and requires little image processing or interpretation. We validated this method for coral reefs of the Great Barrier Reef (GBR), Australia, across a range of spatial scales (1 m to 10 km), using digital photographs of benthic communities at the transect scale and high-resolution Landsat satellite images at the reef scale. We calculated an index of image-derived spatial heterogeneity, the mean information gain (MIG), for each scale and related it to univariate (species richness and total abundance summed across species) and multivariate (species abundance matrix) measures of fish community structure, using two techniques that account for the hierarchical structure of the data: hierarchical (mixed-effect) linear models and distance-based partial redundancy analysis. Over the length and breadth of the GBR, MIG alone explained up to 29% of deviance in fish species richness, 33% in total fish abundance, and 25% in fish community structure at multiple scales, thus demonstrating the possibility of easily and rapidly exploiting spatial information contained in digital images to complement existing methods for inferring diversity and abundance patterns among fish communities. Thus, the spectral signal of unprocessed remotely sensed images provides an efficient and low-cost way to optimize the design of surveys used in conservation planning. In data-sparse situations, this simple approach also offers a viable method for rapid assessment of potential local biodiversity, particularly where there is little local capacity in terms of skills or resources for mounting in-depth biodiversity surveys.Camille Mellin, Lael Parrott, Serge Andréfouët, Corey J. A. Bradshaw, M. Aaron MacNeil, and M. Julian Cale

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Evaluation of large-scale unsupervised classification of New Caledonia reef ecosystems using Landsat 7 ETM+ imagery

The capacity of the Landsat 7 Enhanced Thematic Mapper Plus sensor to classify the shallow benthic ecosytems of New Caledonia (South Pacific) is tested using a novel unsupervised classification method. The classes are defined by using a set of multiple spectral decision rules based on the image spectral bands. A general model is applied to the entire Southwest lagoon (5500 km(2)) and tested on three representative sites: a section of the barrier reef, a cay reef flat rich in corals, and a cay reef flat rich in algae and seagrass beds. In the latter one, the classification results are compared with a locally optimized model, with aerial color photographs and extensive ground-truthed observations. Results show that a reconnaissance of the main benthic habitats in shallow areas (<5 m depth) is possible, at a geomorphological scale for coral reef structure and at a habitat scale for seagrass beds. However, results directly issued from the model must be cautiously interpreted according to empirical spatial rules, especially to avoid confusion between coral slopes and shallow dense seagrass.Le but de cette étude est de tester la capacité des images Landsat 7 Enhanced Thematic Mapper Plus à discriminer les principales classes d’habitats benthiques rencontrées dans les parties peu profondes du système récifal et lagonaire de Nouvelle-Calédonie (Pacifique Sud). Une méthode originale de classification non-supervisée est proposée. Les habitats benthiques correspondent à une combinaison de plusieurs règles de décision établies à partir des bandes radiométriques Landsat. Cette modélisation statistique des habitats benthiques est appliquée au lagon sud-ouest de Nouvelle-Calédonie (5500 km2). Les résultats sont testés sur trois sites témoins contrastés: un platier de récif barrière, un platier d’îlot riche en corail et un platier d’îlot riche en herbiers/algueraies. Pour ce dernier, le résultat est comparé à celui d’un modèle optimisé, construit à échelle locale et validé à partir de photographies aériennes et d’observations de terrain. Les résultats montrent qu’une reconnaissance des différentes classes benthiques est possible pour des fonds peu profonds (< 5 m de profondeur), à l’échelle géomorphologique pour les structures récifales et à l’échelle des habitats pour les herbiers. Toutefois, les résultats bruts du modèle doivent être interprétés en fonction de critères spatiaux pour corriger les confusions entre certaines classes, notamment entre les pentes coralliennes et les herbiers denses

Spectral reflectance of coral reef benthos and substrate assemblages on Heron Reef, Australia

Studies investigating the spectral reflectance of coral reef benthos and substrates have focused on the measurement of pure endmembers, where the entire field of view (FOV) of a spectrometer is focused on a single benthos or substrate type. At the spatial scales of the current satellite sensors, the heterogeneity of coral reefs even at a sub-metre scale means that many individual image pixels will be made up of a mixture of benthos and substrate types. If pure endmember spectra are used as training data for image classification, there is a spatial discrepancy, because many pixels will have a mixed endmember spectral reflectance signature. This study investigated the spectral reflectance of coral reef benthos and substrates at a spatial scale directly linked to the pixel size of high spatial resolution imaging systems, by incorporating multiple benthos and substrate types into the spectrometer FOV in situ. A total of 334 spectral reflectance signatures were measured of 19 assemblages of the coral reef benthos and substrate types. The spectra were analysed for separability using first derivative values, and a discrimination decision tree was designed to identify the assemblages. Using the decision tree, it was possible to identify 15 assemblages with a mean overall classification accuracy of 62.6%