Cargando…

Estimating species pools for a single ecological assemblage

BACKGROUND: The species pool concept was formulated over the past several decades and has since played an important role in explaining multi-scale ecological patterns. Previous statistical methods were developed to identify species pools based on broad-scale species range maps or community similarit...

Descripción completa

Detalles Bibliográficos
Autores principales: Shen, Tsung-Jen, Chen, Youhua, Chen, You-Fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5741966/
https://www.ncbi.nlm.nih.gov/pubmed/29273049
http://dx.doi.org/10.1186/s12898-017-0155-7
_version_ 1783288292384440320
author Shen, Tsung-Jen
Chen, Youhua
Chen, You-Fang
author_facet Shen, Tsung-Jen
Chen, Youhua
Chen, You-Fang
author_sort Shen, Tsung-Jen
collection PubMed
description BACKGROUND: The species pool concept was formulated over the past several decades and has since played an important role in explaining multi-scale ecological patterns. Previous statistical methods were developed to identify species pools based on broad-scale species range maps or community similarity computed from data collected from many areas. No statistical method is available for estimating species pools for a single local community (sampling area size may be very small as ≤ 1 km(2)). In this study, based on limited local abundance information, we developed a simple method to estimate the area size and richness of a species pool for a local ecological community. The method involves two steps. In the first step, parameters from a truncated negative trinomial model characterizing the distributional aggregation of all species (i.e., non-random species distribution) in the local community were estimated. In the second step, we assume that the unseen species in the local community are most likely the rare species, only found in the remaining part of the species pool, and vice versa, if the remaining portion of the pool was surveyed and was contrasted with the sampled area. Therefore, we can estimate the area size of the pool, as long as an abundance threshold for defining rare species is given. Since the size of the pool is dependent on the rarity threshold, to unanimously determine the pool size, we developed an optimal method to delineate the rarity threshold based on the balance of the changing rates of species absence probabilities in the sampled and unsampled areas of the pool. RESULTS: For a 50 ha (0.5 km(2)) forest plot in the Barro Colorado Island of central Panama, our model predicted that the local, if not regional, species pool for the 0.5 km(2) forest plot was nearly the entire island. Accordingly, tree species richness in this pool was estimated as around 360. When the sampling size was smaller, the upper bound of the 95% confidence interval could reach 418, which was very close to the flora record of tree richness for the island. A numerical test further demonstrated the power and reliability of the proposed method, as the true values of area size and species richness for the hypothetical species pool have been well covered by the 95% confidence intervals of the true values. CONCLUSIONS: Our method fills the knowledge gap on estimating species pools for a single local ecological assemblage with little information. The method is statistically robust and independent of sampling size, as proved by both empirical and numerical tests. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12898-017-0155-7) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-5741966
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-57419662018-01-03 Estimating species pools for a single ecological assemblage Shen, Tsung-Jen Chen, Youhua Chen, You-Fang BMC Ecol Research Article BACKGROUND: The species pool concept was formulated over the past several decades and has since played an important role in explaining multi-scale ecological patterns. Previous statistical methods were developed to identify species pools based on broad-scale species range maps or community similarity computed from data collected from many areas. No statistical method is available for estimating species pools for a single local community (sampling area size may be very small as ≤ 1 km(2)). In this study, based on limited local abundance information, we developed a simple method to estimate the area size and richness of a species pool for a local ecological community. The method involves two steps. In the first step, parameters from a truncated negative trinomial model characterizing the distributional aggregation of all species (i.e., non-random species distribution) in the local community were estimated. In the second step, we assume that the unseen species in the local community are most likely the rare species, only found in the remaining part of the species pool, and vice versa, if the remaining portion of the pool was surveyed and was contrasted with the sampled area. Therefore, we can estimate the area size of the pool, as long as an abundance threshold for defining rare species is given. Since the size of the pool is dependent on the rarity threshold, to unanimously determine the pool size, we developed an optimal method to delineate the rarity threshold based on the balance of the changing rates of species absence probabilities in the sampled and unsampled areas of the pool. RESULTS: For a 50 ha (0.5 km(2)) forest plot in the Barro Colorado Island of central Panama, our model predicted that the local, if not regional, species pool for the 0.5 km(2) forest plot was nearly the entire island. Accordingly, tree species richness in this pool was estimated as around 360. When the sampling size was smaller, the upper bound of the 95% confidence interval could reach 418, which was very close to the flora record of tree richness for the island. A numerical test further demonstrated the power and reliability of the proposed method, as the true values of area size and species richness for the hypothetical species pool have been well covered by the 95% confidence intervals of the true values. CONCLUSIONS: Our method fills the knowledge gap on estimating species pools for a single local ecological assemblage with little information. The method is statistically robust and independent of sampling size, as proved by both empirical and numerical tests. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12898-017-0155-7) contains supplementary material, which is available to authorized users. BioMed Central 2017-12-22 /pmc/articles/PMC5741966/ /pubmed/29273049 http://dx.doi.org/10.1186/s12898-017-0155-7 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Shen, Tsung-Jen
Chen, Youhua
Chen, You-Fang
Estimating species pools for a single ecological assemblage
title Estimating species pools for a single ecological assemblage
title_full Estimating species pools for a single ecological assemblage
title_fullStr Estimating species pools for a single ecological assemblage
title_full_unstemmed Estimating species pools for a single ecological assemblage
title_short Estimating species pools for a single ecological assemblage
title_sort estimating species pools for a single ecological assemblage
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5741966/
https://www.ncbi.nlm.nih.gov/pubmed/29273049
http://dx.doi.org/10.1186/s12898-017-0155-7
work_keys_str_mv AT shentsungjen estimatingspeciespoolsforasingleecologicalassemblage
AT chenyouhua estimatingspeciespoolsforasingleecologicalassemblage
AT chenyoufang estimatingspeciespoolsforasingleecologicalassemblage