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Generalised Extreme Value Distributions Provide a Natural Hypothesis for the Shape of Seed Mass Distributions

Among co-occurring species, values for functionally important plant traits span orders of magnitude, are uni-modal, and generally positively skewed. Such data are usually log-transformed “for normality” but no convincing mechanistic explanation for a log-normal expectation exists. Here we propose a...

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Detalles Bibliográficos
Autores principales: Edwards, Will, Moles, Angela T., Chong, Caroline
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382290/
https://www.ncbi.nlm.nih.gov/pubmed/25830773
http://dx.doi.org/10.1371/journal.pone.0121724
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author Edwards, Will
Moles, Angela T.
Chong, Caroline
author_facet Edwards, Will
Moles, Angela T.
Chong, Caroline
author_sort Edwards, Will
collection PubMed
description Among co-occurring species, values for functionally important plant traits span orders of magnitude, are uni-modal, and generally positively skewed. Such data are usually log-transformed “for normality” but no convincing mechanistic explanation for a log-normal expectation exists. Here we propose a hypothesis for the distribution of seed masses based on generalised extreme value distributions (GEVs), a class of probability distributions used in climatology to characterise the impact of event magnitudes and frequencies; events that impose strong directional selection on biological traits. In tests involving datasets from 34 locations across the globe, GEVs described log10 seed mass distributions as well or better than conventional normalising statistics in 79% of cases, and revealed a systematic tendency for an overabundance of small seed sizes associated with low latitudes. GEVs characterise disturbance events experienced in a location to which individual species’ life histories could respond, providing a natural, biological explanation for trait expression that is lacking from all previous hypotheses attempting to describe trait distributions in multispecies assemblages. We suggest that GEVs could provide a mechanistic explanation for plant trait distributions and potentially link biology and climatology under a single paradigm.
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spelling pubmed-43822902015-04-09 Generalised Extreme Value Distributions Provide a Natural Hypothesis for the Shape of Seed Mass Distributions Edwards, Will Moles, Angela T. Chong, Caroline PLoS One Research Article Among co-occurring species, values for functionally important plant traits span orders of magnitude, are uni-modal, and generally positively skewed. Such data are usually log-transformed “for normality” but no convincing mechanistic explanation for a log-normal expectation exists. Here we propose a hypothesis for the distribution of seed masses based on generalised extreme value distributions (GEVs), a class of probability distributions used in climatology to characterise the impact of event magnitudes and frequencies; events that impose strong directional selection on biological traits. In tests involving datasets from 34 locations across the globe, GEVs described log10 seed mass distributions as well or better than conventional normalising statistics in 79% of cases, and revealed a systematic tendency for an overabundance of small seed sizes associated with low latitudes. GEVs characterise disturbance events experienced in a location to which individual species’ life histories could respond, providing a natural, biological explanation for trait expression that is lacking from all previous hypotheses attempting to describe trait distributions in multispecies assemblages. We suggest that GEVs could provide a mechanistic explanation for plant trait distributions and potentially link biology and climatology under a single paradigm. Public Library of Science 2015-04-01 /pmc/articles/PMC4382290/ /pubmed/25830773 http://dx.doi.org/10.1371/journal.pone.0121724 Text en © 2015 Edwards et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Edwards, Will
Moles, Angela T.
Chong, Caroline
Generalised Extreme Value Distributions Provide a Natural Hypothesis for the Shape of Seed Mass Distributions
title Generalised Extreme Value Distributions Provide a Natural Hypothesis for the Shape of Seed Mass Distributions
title_full Generalised Extreme Value Distributions Provide a Natural Hypothesis for the Shape of Seed Mass Distributions
title_fullStr Generalised Extreme Value Distributions Provide a Natural Hypothesis for the Shape of Seed Mass Distributions
title_full_unstemmed Generalised Extreme Value Distributions Provide a Natural Hypothesis for the Shape of Seed Mass Distributions
title_short Generalised Extreme Value Distributions Provide a Natural Hypothesis for the Shape of Seed Mass Distributions
title_sort generalised extreme value distributions provide a natural hypothesis for the shape of seed mass distributions
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382290/
https://www.ncbi.nlm.nih.gov/pubmed/25830773
http://dx.doi.org/10.1371/journal.pone.0121724
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