Journal Article

Multi-Scale Approach for Predicting Fish Species Distributions across Coral Reef Seascapes

Pittman, Simon J., Brown, Kerry A.

2011

Overview

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.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Algorithms / Analysis / Animal behavior / Animals / Area Under Curve / Bathymetry / Biodiversity / Biogeography / Biology / Caribbean Region / Conservation / Coral reef ecosystems / Coral Reefs / Cost analysis / Crustacea / Crustaceans / Data mining / Earth Sciences / Ecology / Ecosystem biology / Ecosystem management / Ecosystems / Entropy / Environmental changes / Environmental planning / Fish / Fish conservation / Fisheries / Fisheries management / Fishery management / Fishes / Fishes - growth & development / Geographical distribution / Geography / Grasses / Heterogeneity / Influence / Landscape ecology / Learning algorithms / Machine learning / Marine biology / Marine ecology / Marine ecosystems / Marine protected areas / Marine resources / Mathematical morphology / Maximum entropy / Methods / Model accuracy / Modelling / Models, Biological / Multiscale analysis / Ocean floor / Oceans and Seas / Predictions / Protected areas / Puerto Rico / Regression Analysis / Remote sensing / Scales / Scarus taeniopterus / Spatial analysis / Spatial distribution / Species / Species Specificity / Stegastes planifrons / Strategic management / Topography