Legume diversity patterns in West Central Africa: influence of species biology on distribution models.

<h4>Objectives</h4>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 speci...

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Autores principales:	Manuel de la Estrella, Rubén G Mateo, Jan J Wieringa, Barbara Mackinder, Jesús Muñoz
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/dfbb69518f744ed99bb47c8610f68967
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spelling	oai:doaj.org-article:dfbb69518f744ed99bb47c8610f689672021-11-18T07:11:25ZLegume diversity patterns in West Central Africa: influence of species biology on distribution models.1932-620310.1371/journal.pone.0041526https://doaj.org/article/dfbb69518f744ed99bb47c8610f689672012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22911808/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Objectives</h4>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.<h4>Methodology</h4>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.<h4>Results/conclusions</h4>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.Manuel de la EstrellaRubén G MateoJan J WieringaBarbara MackinderJesús MuñozPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 7, p e41526 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Manuel de la Estrella Rubén G Mateo Jan J Wieringa Barbara Mackinder Jesús Muñoz Legume diversity patterns in West Central Africa: influence of species biology on distribution models.
description	<h4>Objectives</h4>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.<h4>Methodology</h4>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.<h4>Results/conclusions</h4>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.
format	article
author	Manuel de la Estrella Rubén G Mateo Jan J Wieringa Barbara Mackinder Jesús Muñoz
author_facet	Manuel de la Estrella Rubén G Mateo Jan J Wieringa Barbara Mackinder Jesús Muñoz
author_sort	Manuel de la Estrella
title	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_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_sort	legume diversity patterns in west central africa: influence of species biology on distribution models.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/dfbb69518f744ed99bb47c8610f68967
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Legume diversity patterns in West Central Africa: influence of species biology on distribution models.

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