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Legume Diversity Patterns in West Central Africa: Influence of Species Biology on Distribution Models

OBJECTIVES: Species Distribution Models (SDMs) are used to produce predictions of potential Leguminosae diversity in West Central Africa. Those predictions are evaluated subsequently using expert opinion. The established methodology of combining all SDMs is refined to assess species diversity within...

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Autores principales: de la Estrella, Manuel, Mateo, Rubén G., Wieringa, Jan J., Mackinder, Barbara, Muñoz, Jesús
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3402427/
https://www.ncbi.nlm.nih.gov/pubmed/22911808
http://dx.doi.org/10.1371/journal.pone.0041526
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author de la Estrella, Manuel
Mateo, Rubén G.
Wieringa, Jan J.
Mackinder, Barbara
Muñoz, Jesús
author_facet de la Estrella, Manuel
Mateo, Rubén G.
Wieringa, Jan J.
Mackinder, Barbara
Muñoz, Jesús
author_sort de la Estrella, Manuel
collection PubMed
description OBJECTIVES: Species Distribution Models (SDMs) are used to produce predictions of potential Leguminosae diversity in West Central Africa. Those predictions are evaluated subsequently using expert opinion. The established methodology of combining all SDMs is refined to assess species diversity within five defined vegetation types. Potential species diversity is thus predicted for each vegetation type respectively. The primary aim of the new methodology is to define, in more detail, areas of species richness for conservation planning. METHODOLOGY: Using Maxent, SDMs based on a suite of 14 environmental predictors were generated for 185 West Central African Leguminosae species, each categorised according to one of five vegetation types: Afromontane, coastal, non-flooded forest, open formations, or riverine forest. The relative contribution of each environmental variable was compared between different vegetation types using a nonparametric Kruskal-Wallis analysis followed by a post-hoc Kruskal-Wallis Paired Comparison contrast. Legume species diversity patterns were explored initially using the typical method of stacking all SDMs. Subsequently, five different ensemble models were generated by partitioning SDMs according to vegetation category. Ecological modelers worked with legume specialists to improve data integrity and integrate expert opinion in the interpretation of individual species models and potential species richness predictions for different vegetation types. RESULTS/CONCLUSIONS: Of the 14 environmental predictors used, five showed no difference in their relative contribution to the different vegetation models. Of the nine discriminating variables, the majority were related to temperature variation. The set of variables that played a major role in the Afromontane species diversity model differed significantly from the sets of variables of greatest relative important in other vegetation categories. The traditional approach of stacking all SDMs indicated overall centers of diversity in the region but the maps indicating potential species richness by vegetation type offered more detailed information on which conservation efforts can be focused.
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spelling pubmed-34024272012-07-30 Legume Diversity Patterns in West Central Africa: Influence of Species Biology on Distribution Models de la Estrella, Manuel Mateo, Rubén G. Wieringa, Jan J. Mackinder, Barbara Muñoz, Jesús PLoS One Research Article OBJECTIVES: Species Distribution Models (SDMs) are used to produce predictions of potential Leguminosae diversity in West Central Africa. Those predictions are evaluated subsequently using expert opinion. The established methodology of combining all SDMs is refined to assess species diversity within five defined vegetation types. Potential species diversity is thus predicted for each vegetation type respectively. The primary aim of the new methodology is to define, in more detail, areas of species richness for conservation planning. METHODOLOGY: Using Maxent, SDMs based on a suite of 14 environmental predictors were generated for 185 West Central African Leguminosae species, each categorised according to one of five vegetation types: Afromontane, coastal, non-flooded forest, open formations, or riverine forest. The relative contribution of each environmental variable was compared between different vegetation types using a nonparametric Kruskal-Wallis analysis followed by a post-hoc Kruskal-Wallis Paired Comparison contrast. Legume species diversity patterns were explored initially using the typical method of stacking all SDMs. Subsequently, five different ensemble models were generated by partitioning SDMs according to vegetation category. Ecological modelers worked with legume specialists to improve data integrity and integrate expert opinion in the interpretation of individual species models and potential species richness predictions for different vegetation types. RESULTS/CONCLUSIONS: Of the 14 environmental predictors used, five showed no difference in their relative contribution to the different vegetation models. Of the nine discriminating variables, the majority were related to temperature variation. The set of variables that played a major role in the Afromontane species diversity model differed significantly from the sets of variables of greatest relative important in other vegetation categories. The traditional approach of stacking all SDMs indicated overall centers of diversity in the region but the maps indicating potential species richness by vegetation type offered more detailed information on which conservation efforts can be focused. Public Library of Science 2012-07-23 /pmc/articles/PMC3402427/ /pubmed/22911808 http://dx.doi.org/10.1371/journal.pone.0041526 Text en de la Estrella et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
de la Estrella, Manuel
Mateo, Rubén G.
Wieringa, Jan J.
Mackinder, Barbara
Muñoz, Jesús
Legume Diversity Patterns in West Central Africa: Influence of Species Biology on Distribution Models
title Legume Diversity Patterns in West Central Africa: Influence of Species Biology on Distribution Models
title_full Legume Diversity Patterns in West Central Africa: Influence of Species Biology on Distribution Models
title_fullStr Legume Diversity Patterns in West Central Africa: Influence of Species Biology on Distribution Models
title_full_unstemmed Legume Diversity Patterns in West Central Africa: Influence of Species Biology on Distribution Models
title_short Legume Diversity Patterns in West Central Africa: Influence of Species Biology on Distribution Models
title_sort legume diversity patterns in west central africa: influence of species biology on distribution models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3402427/
https://www.ncbi.nlm.nih.gov/pubmed/22911808
http://dx.doi.org/10.1371/journal.pone.0041526
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