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Upscaling species richness and abundances in tropical forests

The quantification of tropical tree biodiversity worldwide remains an open and challenging problem. More than two-fifths of the number of worldwide trees can be found either in tropical or in subtropical forests, but only ≈0.000067% of species identities are known. We introduce an analytical framewo...

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Autores principales: Tovo, Anna, Suweis, Samir, Formentin, Marco, Favretti, Marco, Volkov, Igor, Banavar, Jayanth R., Azaele, Sandro, Maritan, Amos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5647133/
https://www.ncbi.nlm.nih.gov/pubmed/29057324
http://dx.doi.org/10.1126/sciadv.1701438
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author Tovo, Anna
Suweis, Samir
Formentin, Marco
Favretti, Marco
Volkov, Igor
Banavar, Jayanth R.
Azaele, Sandro
Maritan, Amos
author_facet Tovo, Anna
Suweis, Samir
Formentin, Marco
Favretti, Marco
Volkov, Igor
Banavar, Jayanth R.
Azaele, Sandro
Maritan, Amos
author_sort Tovo, Anna
collection PubMed
description The quantification of tropical tree biodiversity worldwide remains an open and challenging problem. More than two-fifths of the number of worldwide trees can be found either in tropical or in subtropical forests, but only ≈0.000067% of species identities are known. We introduce an analytical framework that provides robust and accurate estimates of species richness and abundances in biodiversity-rich ecosystems, as confirmed by tests performed on both in silico–generated and real forests. Our analysis shows that the approach outperforms other methods. In particular, we find that upscaling methods based on the log-series species distribution systematically overestimate the number of species and abundances of the rare species. We finally apply our new framework on 15 empirical tropical forest plots and quantify the minimum percentage cover that should be sampled to achieve a given average confidence interval in the upscaled estimate of biodiversity. Our theoretical framework confirms that the forests studied are comprised of a large number of rare or hyper-rare species. This is a signature of critical-like behavior of species-rich ecosystems and can provide a buffer against extinction.
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spelling pubmed-56471332017-10-22 Upscaling species richness and abundances in tropical forests Tovo, Anna Suweis, Samir Formentin, Marco Favretti, Marco Volkov, Igor Banavar, Jayanth R. Azaele, Sandro Maritan, Amos Sci Adv Research Articles The quantification of tropical tree biodiversity worldwide remains an open and challenging problem. More than two-fifths of the number of worldwide trees can be found either in tropical or in subtropical forests, but only ≈0.000067% of species identities are known. We introduce an analytical framework that provides robust and accurate estimates of species richness and abundances in biodiversity-rich ecosystems, as confirmed by tests performed on both in silico–generated and real forests. Our analysis shows that the approach outperforms other methods. In particular, we find that upscaling methods based on the log-series species distribution systematically overestimate the number of species and abundances of the rare species. We finally apply our new framework on 15 empirical tropical forest plots and quantify the minimum percentage cover that should be sampled to achieve a given average confidence interval in the upscaled estimate of biodiversity. Our theoretical framework confirms that the forests studied are comprised of a large number of rare or hyper-rare species. This is a signature of critical-like behavior of species-rich ecosystems and can provide a buffer against extinction. American Association for the Advancement of Science 2017-10-18 /pmc/articles/PMC5647133/ /pubmed/29057324 http://dx.doi.org/10.1126/sciadv.1701438 Text en Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (http://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.
spellingShingle Research Articles
Tovo, Anna
Suweis, Samir
Formentin, Marco
Favretti, Marco
Volkov, Igor
Banavar, Jayanth R.
Azaele, Sandro
Maritan, Amos
Upscaling species richness and abundances in tropical forests
title Upscaling species richness and abundances in tropical forests
title_full Upscaling species richness and abundances in tropical forests
title_fullStr Upscaling species richness and abundances in tropical forests
title_full_unstemmed Upscaling species richness and abundances in tropical forests
title_short Upscaling species richness and abundances in tropical forests
title_sort upscaling species richness and abundances in tropical forests
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5647133/
https://www.ncbi.nlm.nih.gov/pubmed/29057324
http://dx.doi.org/10.1126/sciadv.1701438
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