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Predicting alpha diversity of African rain forests: models based on climate and satellite-derived data do not perform better than a purely spatial model

Abstract:

Aim: Our aim was to evaluate the extent to which we can predict and map tree alpha diversity across broad spatial scales either by using climate and remote sensing data or by exploiting spatial autocorrelation patterns.

Location: Tropical rain forest, West Africa and Atlantic Central Africa.

Methods: Alpha diversity estimates were compiled for trees with diameter at breast height ≥ 10 cm in 573 inventory plots. Linear regression (ordinary least squares, OLS) and random forest (...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
Université Libre de Bruxelles, Brussels, Belgium
Department:
Evolutionary Biology & Ecology
Role:
Author
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Institution:
University of California, Los Angeles, CA, USA
Department:
Center for Tropical Research,Institute of the Environment
Role:
Author
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Institution:
University of California, Los Angeles, CA, USA
Department:
Center for Tropical Research,Institute of the Environment
Role:
Author
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Institution:
University of Edinburgh
Department:
School of Geosciences
Role:
Author
More by this author
Institution:
University of California, Los Angeles, CA, USA
Department:
Center for Tropical Research,Institute of the Environment
Role:
Author
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Publisher:
Wiley-Blackwell Publisher's website
Journal:
Journal of Biogeography Journal website
Volume:
38
Issue:
6
Pages:
1164-1176
Publication date:
2011-01-01
DOI:
EISSN:
1365-2699
URN:
uuid:f9338c99-2b2c-445d-9559-1b77bc3beac4
Local pid:
ora:5783

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