4.7 Article

Testing the habitat amount hypothesis for South American small mammals

Journal

BIOLOGICAL CONSERVATION
Volume 209, Issue -, Pages 304-314

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.biocon.2017.02.031

Keywords

Island biogeography theory; Patch isolation; Patch size; Scale of effect; Species-area relationship

Funding

  1. Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES) [470324/2011-2]
  2. Conselho Nacional de Desenvolvimento Cientifico e Tecnologico(CNPq) [470324/2011-2]

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According to the habitat amount hypothesis the species richness in a sample site should increase with the habitat amount in the local landscape around the sample site. On the other hand, size and isolation of the patch containing the sample site should have no effect on species richness if the habitat amount in the local landscape remains constant. We tested these predictions using a small mammal dataset recorded in 100 transects in a savanna region of Brazil. We used generalized linear models considering the predictors - habitat amount, patch size, and patch isolation - together and singly, using subsets of data to control for correlations between them. We measured the habitat amount in 10 nested circles ranging in radius from 250 m to 6000 m around each transect. The scale of effect was the radius with the strongest estimated correlation between habitat amount and species richness. Our results indicate that habitat amount is the most important single predictor of species richness. The habitat amount effect was always positive and large. In general, patch size and patch isolation had no effect on species richness after controlling for the effect of habitat amount. The results are consistent with the habitat amount hypothesis, and suggest that habitat amount can be used in place of patch size and isolation in predicting small mammal species richness. This simplifies information needs by landscape managers as it replaces two predictors with one. Our results also support the use of estimated dispersal distance as a way of determining the appropriate landscape scale of effect. (C) 2017 Elsevier Ltd. All rights reserved.

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