Prospective sampling based on model ensembles improves the detection of rare species

Details

Serval ID
serval:BIB_CB43008622FD
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Prospective sampling based on model ensembles improves the detection of rare species
Journal
Ecography
Author(s)
Le Lay G., Engler R., Franc E., Guisan A.
ISSN
0906-7590
Publication state
Published
Issued date
2010
Peer-reviewed
Oui
Volume
33
Number
6
Pages
1015-1027
Language
english
Abstract
Identifying the geographic distribution of populations is a basic, yet crucial step in many fundamental and applied ecological projects, as it provides key information on which many subsequent analyses depend. However, this task is often costly and time consuming, especially where rare species are concerned and where most sampling designs generally prove inefficient. At the same time, rare species are those for which distribution data are most needed for their conservation to be effective. To enhance fieldwork sampling, model-based sampling (MBS) uses predictions from species distribution models: when looking for the species in areas of high habitat suitability, chances should be higher to find them. We thoroughly tested the efficiency of MBS by conducting an important survey in the Swiss Alps, assessing the detection rate of three rare and five common plant species. For each species, habitat suitability maps were produced following an ensemble modeling framework combining two spatial resolutions and two modeling techniques. We tested the efficiency of MBS and the accuracy of our models by sampling 240 sites in the field (30 sitesx8 species). Across all species, the MBS approach proved to be effective. In particular, the MBS design strictly led to the discovery of six sites of presence of one rare plant, increasing chances to find this species from 0 to 50%. For common species, MBS doubled the new population discovery rates as compared to random sampling. Habitat suitability maps coming from the combination of four individual modeling methods predicted well the species' distribution and more accurately than the individual models. As a conclusion, using MBS for fieldwork could efficiently help in increasing our knowledge of rare species distribution. More generally, we recommend using habitat suitability models to support conservation plans.
Web of science
Create date
07/09/2010 19:19
Last modification date
20/08/2019 16:46
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