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Multi-Scale Approach for Predicting Fish Species Distributions across Coral Reef Seascapes
- Source :
- PLoS ONE, Vol 6, Iss 5, p e20583 (2011), PLoS ONE
- Publication Year :
- 2011
- Publisher :
- Public Library of Science (PLoS), 2011.
-
Abstract
- Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5–300 m radii) surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT) and Maximum Entropy Species Distribution Modelling (MaxEnt). The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided ‘outstanding’ model predictions (AUC = >0.9) for three of five fish species. MaxEnt provided ‘outstanding’ model predictions for two of five species, with the remaining three models considered ‘excellent’ (AUC = 0.8–0.9). In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy) than BRT (68% map accuracy). We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support conservation prioritization in marine protected area design, zoning in marine spatial planning, and ecosystem-based fisheries management.
- Subjects :
- Ecological Metrics
Oceans and Seas
Marine and Aquatic Sciences
lcsh:Medicine
Marine Biology
Spatial distribution
Models, Biological
Essential fish habitat
Species Specificity
Geoinformatics
Relative Abundance Distribution
Animals
Spatial and Landscape Ecology
Marine ecosystem
Macroecology
lcsh:Science
Biology
geography
Remote Sensing Imagery
Multidisciplinary
geography.geographical_feature_category
Geography
Ecology
Coral Reefs
Puerto Rico
lcsh:R
Fishes
Marine Ecology
Geomorphology
Marine spatial planning
Biodiversity
Marine Technology
Coral reef
Environmental niche modelling
Caribbean Region
Biogeography
Area Under Curve
Earth Sciences
Regression Analysis
lcsh:Q
Marine protected area
Physical geography
Landscape ecology
Zoology
Algorithms
Coastal Ecology
Ichthyology
Research Article
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....2bec9f726329f5879b8b67463efad17e