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How to describe species richness patterns for bryophyte conservation?

A large amount of data for inconspicuous taxa is stored in natural history collections; however, this information is often neglected for biodiversity patterns studies. Here, we evaluate the performance of direct interpolation of museum collections data, equivalent to the traditional approach used in...

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Autores principales: Hespanhol, Helena, Cezón, Katia, Felicísimo, Ángel M., Muñoz, Jesús, Mateo, Rubén G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4813098/
https://www.ncbi.nlm.nih.gov/pubmed/27069596
http://dx.doi.org/10.1002/ece3.1796
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author Hespanhol, Helena
Cezón, Katia
Felicísimo, Ángel M.
Muñoz, Jesús
Mateo, Rubén G.
author_facet Hespanhol, Helena
Cezón, Katia
Felicísimo, Ángel M.
Muñoz, Jesús
Mateo, Rubén G.
author_sort Hespanhol, Helena
collection PubMed
description A large amount of data for inconspicuous taxa is stored in natural history collections; however, this information is often neglected for biodiversity patterns studies. Here, we evaluate the performance of direct interpolation of museum collections data, equivalent to the traditional approach used in bryophyte conservation planning, and stacked species distribution models (S‐SDMs) to produce reliable reconstructions of species richness patterns, given that differences between these methods have been insufficiently evaluated for inconspicuous taxa. Our objective was to contrast if species distribution models produce better inferences of diversity richness than simply selecting areas with the higher species numbers. As model species, we selected Iberian species of the genus Grimmia (Bryophyta), and we used four well‐collected areas to compare and validate the following models: 1) four Maxent richness models, each generated without the data from one of the four areas, and a reference model created using all of the data and 2) four richness models obtained through direct spatial interpolation, each generated without the data from one area, and a reference model created with all of the data. The correlations between the partial and reference Maxent models were higher in all cases (0.45 to 0.99), whereas the correlations between the spatial interpolation models were negative and weak (−0.3 to −0.06). Our results demonstrate for the first time that S‐SDMs offer a useful tool for identifying detailed richness patterns for inconspicuous taxa such as bryophytes and improving incomplete distributions by assessing the potential richness of under‐surveyed areas, filling major gaps in the available data. In addition, the proposed strategy would enhance the value of the vast number of specimens housed in biological collections.
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spelling pubmed-48130982016-04-11 How to describe species richness patterns for bryophyte conservation? Hespanhol, Helena Cezón, Katia Felicísimo, Ángel M. Muñoz, Jesús Mateo, Rubén G. Ecol Evol Original Research A large amount of data for inconspicuous taxa is stored in natural history collections; however, this information is often neglected for biodiversity patterns studies. Here, we evaluate the performance of direct interpolation of museum collections data, equivalent to the traditional approach used in bryophyte conservation planning, and stacked species distribution models (S‐SDMs) to produce reliable reconstructions of species richness patterns, given that differences between these methods have been insufficiently evaluated for inconspicuous taxa. Our objective was to contrast if species distribution models produce better inferences of diversity richness than simply selecting areas with the higher species numbers. As model species, we selected Iberian species of the genus Grimmia (Bryophyta), and we used four well‐collected areas to compare and validate the following models: 1) four Maxent richness models, each generated without the data from one of the four areas, and a reference model created using all of the data and 2) four richness models obtained through direct spatial interpolation, each generated without the data from one area, and a reference model created with all of the data. The correlations between the partial and reference Maxent models were higher in all cases (0.45 to 0.99), whereas the correlations between the spatial interpolation models were negative and weak (−0.3 to −0.06). Our results demonstrate for the first time that S‐SDMs offer a useful tool for identifying detailed richness patterns for inconspicuous taxa such as bryophytes and improving incomplete distributions by assessing the potential richness of under‐surveyed areas, filling major gaps in the available data. In addition, the proposed strategy would enhance the value of the vast number of specimens housed in biological collections. John Wiley and Sons Inc. 2015-10-28 /pmc/articles/PMC4813098/ /pubmed/27069596 http://dx.doi.org/10.1002/ece3.1796 Text en © 2015 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Hespanhol, Helena
Cezón, Katia
Felicísimo, Ángel M.
Muñoz, Jesús
Mateo, Rubén G.
How to describe species richness patterns for bryophyte conservation?
title How to describe species richness patterns for bryophyte conservation?
title_full How to describe species richness patterns for bryophyte conservation?
title_fullStr How to describe species richness patterns for bryophyte conservation?
title_full_unstemmed How to describe species richness patterns for bryophyte conservation?
title_short How to describe species richness patterns for bryophyte conservation?
title_sort how to describe species richness patterns for bryophyte conservation?
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4813098/
https://www.ncbi.nlm.nih.gov/pubmed/27069596
http://dx.doi.org/10.1002/ece3.1796
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