Depletion models can predict shorebird distribution at different spatial scales

Gill, Jennifer A., Sutherland, William J. and Norris, Ken (2001) Depletion models can predict shorebird distribution at different spatial scales. Proceedings of the Royal Society B: Biological Sciences, 268 (1465). pp. 369-376. ISSN 0962-8452

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Abstract

Predicting the impact of habitat change on populations requires an understanding of the number of animals that a given area can support. Depletion models enable predictions of the numbers of individuals an area can support from prey density and predator searching efficiency and handling time. Depletion models have been successfully employed to predict patterns of abundance over small spatial scales, but most environmental change occurs over large spatial scales. We test the ability of depletion models to predict abundance at a range of scales with black-tailed godwits, Limosa limosa islandica. From the type II functional response of godwits to their prey, we calculated the handling time and searching efficiency associated with these prey. These were incorporated in a depletion model, together with the density of available prey determined from surveys, in order to predict godwit abundance. Tests of these predictions with Wetland Bird Survey data from the British Trust for Ornithology showed significant correlations between predicted and observed densities at three scales: within mudflats, within estuaries and between estuaries. Depletion models can thus be powerful tools for predicting the population size that can be supported on sites at a range of scales. This greatly enhances our confidence in predictions of the consequences of environmental change.

Item Type:	Article
Faculty \ School:	Faculty of Science > School of Biological Sciences
UEA Research Groups:	Faculty of Science > Research Centres > Centre for Ecology, Evolution and Conservation Faculty of Science > Research Groups > Organisms and the Environment
Depositing User:	EPrints Services
Date Deposited:	01 Oct 2010 13:36
Last Modified:	25 May 2023 13:31
URI:	https://ueaeprints.uea.ac.uk/id/eprint/376
DOI:	10.1098/rspb.2000.1386

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