Comparison of five modelling techniques to predict the spatial distribution and abundance of seabirds

Biological Conservation
By: , and 



Knowledge about the spatial distribution of seabirds at sea is important for conservation. During marine conservation planning, logistical constraints preclude seabird surveys covering the complete area of interest and spatial distribution of seabirds is frequently inferred from predictive statistical models. Increasingly complex models are available to relate the distribution and abundance of pelagic seabirds to environmental variables, but a comparison of their usefulness for delineating protected areas for seabirds is lacking. Here we compare the performance of five modelling techniques (generalised linear models, generalised additive models, Random Forest, boosted regression trees, and maximum entropy) to predict the distribution of Balearic Shearwaters (Puffinus mauretanicus) along the coast of the western Iberian Peninsula. We used ship transect data from 2004 to 2009 and 13 environmental variables to predict occurrence and density, and evaluated predictive performance of all models using spatially segregated test data. Predicted distribution varied among the different models, although predictive performance varied little. An ensemble prediction that combined results from all five techniques was robust and confirmed the existence of marine important bird areas for Balearic Shearwaters in Portugal and Spain. Our predictions suggested additional areas that would be of high priority for conservation and could be proposed as protected areas. Abundance data were extremely difficult to predict, and none of five modelling techniques provided a reliable prediction of spatial patterns. We advocate the use of ensemble modelling that combines the output of several methods to predict the spatial distribution of seabirds, and use these predictions to target separate surveys assessing the abundance of seabirds in areas of regular use.
Publication type Article
Publication Subtype Journal Article
Title Comparison of five modelling techniques to predict the spatial distribution and abundance of seabirds
Series title Biological Conservation
DOI 10.1016/j.biocon.2011.11.013
Volume 156
Year Published 2012
Language English
Publisher Elsevier
Publisher location Amsterdam, Netherlands
Contributing office(s) Patuxent Wildlife Research Center
Description 11 p.
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Biological Conservation
First page 94
Last page 104
Country Portugal;Spain
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