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Sensitivity of migratory connectivity estimates to spatial sampling design

BACKGROUND: The use of statistical methods to quantify the strength of migratory connectivity is commonplace. However, little attention has been given to their sensitivity to spatial sampling designs and scales of inference. METHODS: We examine sources of bias and imprecision in the most widely used...

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Autores principales: Vickers, Stephen H., Franco, Aldina M. A., Gilroy, James J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8019184/
https://www.ncbi.nlm.nih.gov/pubmed/33810815
http://dx.doi.org/10.1186/s40462-021-00254-w
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author Vickers, Stephen H.
Franco, Aldina M. A.
Gilroy, James J.
author_facet Vickers, Stephen H.
Franco, Aldina M. A.
Gilroy, James J.
author_sort Vickers, Stephen H.
collection PubMed
description BACKGROUND: The use of statistical methods to quantify the strength of migratory connectivity is commonplace. However, little attention has been given to their sensitivity to spatial sampling designs and scales of inference. METHODS: We examine sources of bias and imprecision in the most widely used methodology, Mantel correlations, under a range of plausible sampling regimes using simulated migratory populations. RESULTS: As Mantel correlations depend fundamentally on the spatial scale and configuration of sampling, unbiased inferences about population-scale connectivity can only be made under certain sampling regimes. Within a contiguous population, samples drawn from smaller spatial subsets of the range generate lower connectivity metrics than samples drawn from the range as a whole, even when the underlying migratory ecology of the population is constant across the population. Random sampling of individuals from contiguous subsets of species ranges can therefore underestimate population-scale connectivity. Where multiple discrete sampling sites are used, by contrast, overestimation of connectivity can arise due to samples being biased towards larger between-individual pairwise distances in the seasonal range where sampling occurs (typically breeding). Severity of all biases was greater for populations with lower levels of true connectivity. When plausible sampling regimes were applied to realistic simulated populations, accuracy of connectivity measures was maximised by increasing the number of discrete sampling sites and ensuring an even spread of sites across the full range. CONCLUSIONS: These results suggest strong potential for bias and imprecision when making quantitative inferences about migratory connectivity using Mantel statistics. Researchers wishing to apply these methods should limit inference to the spatial extent of their sampling, maximise their number of sampling sites, and avoid drawing strong conclusions based on small sample sizes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40462-021-00254-w.
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spelling pubmed-80191842021-04-05 Sensitivity of migratory connectivity estimates to spatial sampling design Vickers, Stephen H. Franco, Aldina M. A. Gilroy, James J. Mov Ecol Research BACKGROUND: The use of statistical methods to quantify the strength of migratory connectivity is commonplace. However, little attention has been given to their sensitivity to spatial sampling designs and scales of inference. METHODS: We examine sources of bias and imprecision in the most widely used methodology, Mantel correlations, under a range of plausible sampling regimes using simulated migratory populations. RESULTS: As Mantel correlations depend fundamentally on the spatial scale and configuration of sampling, unbiased inferences about population-scale connectivity can only be made under certain sampling regimes. Within a contiguous population, samples drawn from smaller spatial subsets of the range generate lower connectivity metrics than samples drawn from the range as a whole, even when the underlying migratory ecology of the population is constant across the population. Random sampling of individuals from contiguous subsets of species ranges can therefore underestimate population-scale connectivity. Where multiple discrete sampling sites are used, by contrast, overestimation of connectivity can arise due to samples being biased towards larger between-individual pairwise distances in the seasonal range where sampling occurs (typically breeding). Severity of all biases was greater for populations with lower levels of true connectivity. When plausible sampling regimes were applied to realistic simulated populations, accuracy of connectivity measures was maximised by increasing the number of discrete sampling sites and ensuring an even spread of sites across the full range. CONCLUSIONS: These results suggest strong potential for bias and imprecision when making quantitative inferences about migratory connectivity using Mantel statistics. Researchers wishing to apply these methods should limit inference to the spatial extent of their sampling, maximise their number of sampling sites, and avoid drawing strong conclusions based on small sample sizes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40462-021-00254-w. BioMed Central 2021-04-02 /pmc/articles/PMC8019184/ /pubmed/33810815 http://dx.doi.org/10.1186/s40462-021-00254-w Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.
spellingShingle Research
Vickers, Stephen H.
Franco, Aldina M. A.
Gilroy, James J.
Sensitivity of migratory connectivity estimates to spatial sampling design
title Sensitivity of migratory connectivity estimates to spatial sampling design
title_full Sensitivity of migratory connectivity estimates to spatial sampling design
title_fullStr Sensitivity of migratory connectivity estimates to spatial sampling design
title_full_unstemmed Sensitivity of migratory connectivity estimates to spatial sampling design
title_short Sensitivity of migratory connectivity estimates to spatial sampling design
title_sort sensitivity of migratory connectivity estimates to spatial sampling design
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8019184/
https://www.ncbi.nlm.nih.gov/pubmed/33810815
http://dx.doi.org/10.1186/s40462-021-00254-w
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