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Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula

The major intention of the present study was to investigate whether an approach combining the use of niche-based palaeodistribution modeling and phylo-geography would support or modify hypotheses about the Quaternary distributional history derived from phylogeographic methods alone. Our study system...

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Autores principales: Schorr, G, Holstein, N, Pearman, P B, Guisan, A, Kadereit, J W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3402199/
https://www.ncbi.nlm.nih.gov/pubmed/22833799
http://dx.doi.org/10.1002/ece3.100
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author Schorr, G
Holstein, N
Pearman, P B
Guisan, A
Kadereit, J W
author_facet Schorr, G
Holstein, N
Pearman, P B
Guisan, A
Kadereit, J W
author_sort Schorr, G
collection PubMed
description The major intention of the present study was to investigate whether an approach combining the use of niche-based palaeodistribution modeling and phylo-geography would support or modify hypotheses about the Quaternary distributional history derived from phylogeographic methods alone. Our study system comprised two closely related species of Alpine Primula. We used species distribution models based on the extant distribution of the species and last glacial maximum (LGM) climate models to predict the distribution of the two species during the LGM. Phylogeographic data were generated using amplified fragment length polymorphisms (AFLPs). In Primula hirsuta, models of past distribution and phylogeographic data are partly congruent and support the hypothesis of widespread nunatak survival in the Central Alps. Species distribution models (SDMs) allowed us to differentiate between alpine regions that harbor potential nunatak areas and regions that have been colonized from other areas. SDMs revealed that diversity is a good indicator for nunataks, while rarity is a good indicator for peripheral relict populations that were not source for the recolonization of the inner Alps. In P. daonensis, palaeo-distribution models and phylogeographic data are incongruent. Besides the uncertainty inherent to this type of modeling approach (e.g., relatively coarse 1-km grain size), disagreement of models and data may partly be caused by shifts of ecological niche in both species. Nevertheless, we demonstrate that the combination of palaeo-distribution modeling with phylogeographical approaches provides a more differentiated picture of the distributional history of species and partly supports (P. hirsuta) and partly modifies (P. daonensis and P. hirsuta) hypotheses of Quaternary distributional history. Some of the refugial area indicated by palaeodistribution models could not have been identified with phylogeographic data.
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spelling pubmed-34021992012-07-25 Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula Schorr, G Holstein, N Pearman, P B Guisan, A Kadereit, J W Ecol Evol Original Research The major intention of the present study was to investigate whether an approach combining the use of niche-based palaeodistribution modeling and phylo-geography would support or modify hypotheses about the Quaternary distributional history derived from phylogeographic methods alone. Our study system comprised two closely related species of Alpine Primula. We used species distribution models based on the extant distribution of the species and last glacial maximum (LGM) climate models to predict the distribution of the two species during the LGM. Phylogeographic data were generated using amplified fragment length polymorphisms (AFLPs). In Primula hirsuta, models of past distribution and phylogeographic data are partly congruent and support the hypothesis of widespread nunatak survival in the Central Alps. Species distribution models (SDMs) allowed us to differentiate between alpine regions that harbor potential nunatak areas and regions that have been colonized from other areas. SDMs revealed that diversity is a good indicator for nunataks, while rarity is a good indicator for peripheral relict populations that were not source for the recolonization of the inner Alps. In P. daonensis, palaeo-distribution models and phylogeographic data are incongruent. Besides the uncertainty inherent to this type of modeling approach (e.g., relatively coarse 1-km grain size), disagreement of models and data may partly be caused by shifts of ecological niche in both species. Nevertheless, we demonstrate that the combination of palaeo-distribution modeling with phylogeographical approaches provides a more differentiated picture of the distributional history of species and partly supports (P. hirsuta) and partly modifies (P. daonensis and P. hirsuta) hypotheses of Quaternary distributional history. Some of the refugial area indicated by palaeodistribution models could not have been identified with phylogeographic data. Blackwell Publishing Ltd 2012-06 /pmc/articles/PMC3402199/ /pubmed/22833799 http://dx.doi.org/10.1002/ece3.100 Text en © 2012 The Authors. Published by Blackwell Publishing Ltd.
spellingShingle Original Research
Schorr, G
Holstein, N
Pearman, P B
Guisan, A
Kadereit, J W
Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula
title Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula
title_full Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula
title_fullStr Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula
title_full_unstemmed Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula
title_short Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula
title_sort integrating species distribution models (sdms) and phylogeography for two species of alpine primula
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3402199/
https://www.ncbi.nlm.nih.gov/pubmed/22833799
http://dx.doi.org/10.1002/ece3.100
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