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Environmental controls on the global distribution of shallow‐water coral reefs
Author(s) -
Couce Elena,
Ridgwell Andy,
Hendy Erica J.
Publication year - 2012
Publication title -
journal of biogeography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.7
H-Index - 158
eISSN - 1365-2699
pISSN - 0305-0270
DOI - 10.1111/j.1365-2699.2012.02706.x
Subject(s) - environmental science , coral , reef , sea surface temperature , coral reef , climate change , regression , coral bleaching , environmental change , climatology , physical geography , ecology , geography , statistics , mathematics , biology , geology
Aim  Elucidating the environmental limits of coral reefs is central to projecting future impacts of climate change on these ecosystems and their global distribution. Recent developments in species distribution modelling (SDM) and the availability of comprehensive global environmental datasets have provided an opportunity to reassess the environmental factors that control the distribution of coral reefs at the global scale as well as to compare the performance of different SDM techniques. Location  Shallow waters world‐wide. Methods  The SDM methods used were maximum entropy (Maxent) and two presence/absence methods: classification and regression trees (CART) and boosted regression trees (BRT). The predictive variables considered included sea surface temperature (SST), salinity, aragonite saturation state (Ω Arag ), nutrients, irradiance, water transparency, dust, current speed and intensity of cyclone activity. For many variables both mean and SD were considered, and at weekly, monthly and annually averaged time‐scales. All were transformed to a global 1° × 1° grid to generate coral reef probability maps for comparison with known locations. Model performance was compared in terms of receiver operating characteristic (ROC) curves and area under the curve (AUC) scores. Potential geographical bias was explored via misclassification maps of false positive and negative errors on test data. Results  Boosted regression trees consistently outperformed other methods, although Maxent also performed acceptably. The dominant environmental predictors were the temperature variables (annual mean SST, and monthly and weekly minimum SST), followed by, and with their relative importance differing between regions, nutrients, light availability and Ω Arag . No systematic bias in SDM performance was found between major coral provinces, but false negatives were more likely for cells containing ‘marginal’ non‐reef‐forming coral communities, e.g. Bermuda. Main conclusions  Agreement between BRT and Maxent models gives predictive confidence for exploring the environmental limits of coral reef ecosystems at a spatial scale relevant to global climate models ( c . 1° × 1°). Although SST‐related variables dominate the coral reef distribution models, contributions from nutrients, Ω Arag and light availability were critical in developing models of reef presence in regions such as the Bahamas, South Pacific and Coral Triangle. The steep response in SST‐driven probabilities at low temperatures indicates that latitudinal expansion of coral reef habitat is very sensitive to global warming.

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