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Insights into coral reef benthic dynamics from nonlinear spatial forecasting

Nonlinear time-series forecasting, or empirical dynamic modelling, has been used extensively in the past two decades as a tool for distinguishing between random temporal behaviour and nonlinear deterministic dynamics. Previous authors have extended nonlinear time-series forecasting to continuous spa...

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Autores principales: McNamara, Dylan E., Cortale, Nick, Edwards, Clinton, Eynaud, Yoan, Sandin, Stuart A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6505552/
https://www.ncbi.nlm.nih.gov/pubmed/30966951
http://dx.doi.org/10.1098/rsif.2019.0047
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author McNamara, Dylan E.
Cortale, Nick
Edwards, Clinton
Eynaud, Yoan
Sandin, Stuart A.
author_facet McNamara, Dylan E.
Cortale, Nick
Edwards, Clinton
Eynaud, Yoan
Sandin, Stuart A.
author_sort McNamara, Dylan E.
collection PubMed
description Nonlinear time-series forecasting, or empirical dynamic modelling, has been used extensively in the past two decades as a tool for distinguishing between random temporal behaviour and nonlinear deterministic dynamics. Previous authors have extended nonlinear time-series forecasting to continuous spatial data. Here, we adjust spatial forecasting to handle discrete data and apply the technique to explore the ubiquity of nonlinear determinism in irregular spatial configurations of coral and algal taxa from Palmyra Atoll, a relatively pristine reef in the central Pacific Ocean. We find that the spatial distributions of coral and algal taxa show signs of nonlinear determinism in some locations and that these signals can change through time. We introduce the hypothesis that nonlinear spatial determinism may be a signal of systems in intermediate developmental (i.e. successional) stages, with spatial randomness characterizing early (i.e. recruitment dominated) and late-successional (i.e. ‘climax’ or attractor) phases. Common state-based metrics that sum community response to environmental forcing lack resolution to detect dynamics of (potential) recovery phases; incorporating signal of spatial patterning among sessile taxa holds unique promise to elucidate dynamical characters of complex ecological systems, thereby enhancing study and response efforts.
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spelling pubmed-65055522019-05-21 Insights into coral reef benthic dynamics from nonlinear spatial forecasting McNamara, Dylan E. Cortale, Nick Edwards, Clinton Eynaud, Yoan Sandin, Stuart A. J R Soc Interface Life Sciences–Physics interface Nonlinear time-series forecasting, or empirical dynamic modelling, has been used extensively in the past two decades as a tool for distinguishing between random temporal behaviour and nonlinear deterministic dynamics. Previous authors have extended nonlinear time-series forecasting to continuous spatial data. Here, we adjust spatial forecasting to handle discrete data and apply the technique to explore the ubiquity of nonlinear determinism in irregular spatial configurations of coral and algal taxa from Palmyra Atoll, a relatively pristine reef in the central Pacific Ocean. We find that the spatial distributions of coral and algal taxa show signs of nonlinear determinism in some locations and that these signals can change through time. We introduce the hypothesis that nonlinear spatial determinism may be a signal of systems in intermediate developmental (i.e. successional) stages, with spatial randomness characterizing early (i.e. recruitment dominated) and late-successional (i.e. ‘climax’ or attractor) phases. Common state-based metrics that sum community response to environmental forcing lack resolution to detect dynamics of (potential) recovery phases; incorporating signal of spatial patterning among sessile taxa holds unique promise to elucidate dynamical characters of complex ecological systems, thereby enhancing study and response efforts. The Royal Society 2019-04 2019-04-10 /pmc/articles/PMC6505552/ /pubmed/30966951 http://dx.doi.org/10.1098/rsif.2019.0047 Text en © 2019 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Life Sciences–Physics interface
McNamara, Dylan E.
Cortale, Nick
Edwards, Clinton
Eynaud, Yoan
Sandin, Stuart A.
Insights into coral reef benthic dynamics from nonlinear spatial forecasting
title Insights into coral reef benthic dynamics from nonlinear spatial forecasting
title_full Insights into coral reef benthic dynamics from nonlinear spatial forecasting
title_fullStr Insights into coral reef benthic dynamics from nonlinear spatial forecasting
title_full_unstemmed Insights into coral reef benthic dynamics from nonlinear spatial forecasting
title_short Insights into coral reef benthic dynamics from nonlinear spatial forecasting
title_sort insights into coral reef benthic dynamics from nonlinear spatial forecasting
topic Life Sciences–Physics interface
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6505552/
https://www.ncbi.nlm.nih.gov/pubmed/30966951
http://dx.doi.org/10.1098/rsif.2019.0047
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