The utility of relative environmental suitability (RES) modelling for predicting distributions of seabirds in the North Atlantic

Marine Ecology Progress Series

Hannah Watson¹  Michael J. Tetley¹  Matthew J. Hobbs¹  Tom M. Brereton¹  Jan G. Hiddink¹ 

关键词: Ecological niche modelling;    Habitat suitability;    Seabird;    Relative environmental suitability;    Geographic range;    Distribution;    AquaMaps;    Species distribution model;    SDM;   

DOI  :  10.3354/meps10334

学科分类：海洋学与技术

来源: Inter-Research

【 摘 要 】

ABSTRACT: Understanding spatial and temporal variability in the distribution of seabirds is fundamental for the conservation and management of marine ecosystems. In the absence of large-scale systematic survey data, the application of standard habitat modelling techniques to predict the at-sea distributions of seabirds at large spatial scales has been limited. In this study, we examine the utility of relative environmental suitability (RES) modelling to predict large-scale distributions and habitat suitability for 6 seabirds in the North Atlantic. An index of habitat suitability was derived by relating niche characteristics to environmental attributes. Predictive performance of models was evaluated with Receiver Operating Characteristic plots, using independent survey data from the Bay of Biscay. RES models performed significantly better than null models at predicting relative likelihood of occurrence for 5 out of 6 species. Qualitative assessment showed that model outputs corresponded well with published range maps, though a common discrepancy was the inclusion of enclosed seas in which species are not known to regularly occur. This study demonstrates that RES modelling can be used to predict large-scale habitat suitability for wide-ranging marine animals for which occurrence data are limited and biased in geographical extent. RES predictions represent simple, testable hypotheses concerning a species’ potential niche in respect of a few environmental predictors. RES modelling can help to identify biodiversity hotspots, predict effects of climate change and develop criteria for designating marine protected areas.

【 授权许可】

Unknown