Using niche-based models to improve the sampling of rare species

Détails

ID Serval
serval:BIB_D6A5425556D7
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Using niche-based models to improve the sampling of rare species
Périodique
Conservation Biology
Auteur(s)
Guisan A., Broennimann O., Engler R., Vust M., Yoccoz N. G., Lehmann A., Zimmermann N. E.
ISSN
0888-8892 (Print)
Statut éditorial
Publié
Date de publication
2006
Peer-reviewed
Oui
Volume
20
Numéro
2
Pages
501-11
Langue
anglais
Résumé
Because data on rare species usually are sparse, it is important to have efficient ways to sample additional data. Traditional sampling approaches are of limited value for rare species because a very large proportion of randomly chosen sampling sites are unlikely to shelter the species. For these species, spatial predictions from niche-based distribution models can be used to stratify the sampling and increase sampling efficiency. New data sampled are then used to improve the initial model. Applying this approach repeatedly is an adaptive process that may allow increasing the number of new occurrences found. We illustrate the approach with a case study of a rare and endangered plant species in Switzerland and a simulation experiment. Our field survey confirmed that the method helps in the discovery of new populations of the target species in remote areas where the predicted habitat suitability is high. In our simulations the model-based approach provided a significant improvement (by a factor of 1.8 to 4 times, depending on the measure) over simple random sampling. In terms of cost this approach may save up to 70% of the time spent in the field.
Mots-clé
Algorithms Computer Simulation Conservation of Natural Resources/*methods *Ecosystem *Models, Biological Switzerland
Pubmed
Web of science
Création de la notice
24/01/2008 20:05
Dernière modification de la notice
03/03/2018 21:47
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