Cargando…

Quantifying heterogeneous responses of fish community size structure using novel combined statistical techniques

To understand changes in ecosystems, the appropriate scale at which to study them must be determined. Large marine ecosystems (LMEs) cover thousands of square kilometres and are a useful classification scheme for ecosystem monitoring and assessment. However, averaging across LMEs may obscure intrica...

Descripción completa

Detalles Bibliográficos
Autores principales: Marshall, Abigail M., Bigg, Grant R., van Leeuwen, Sonja M., Pinnegar, John K., Wei, Hua‐Liang, Webb, Thomas J., Blanchard, Julia L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4991301/
https://www.ncbi.nlm.nih.gov/pubmed/26667981
http://dx.doi.org/10.1111/gcb.13190
_version_ 1782448836866736128
author Marshall, Abigail M.
Bigg, Grant R.
van Leeuwen, Sonja M.
Pinnegar, John K.
Wei, Hua‐Liang
Webb, Thomas J.
Blanchard, Julia L.
author_facet Marshall, Abigail M.
Bigg, Grant R.
van Leeuwen, Sonja M.
Pinnegar, John K.
Wei, Hua‐Liang
Webb, Thomas J.
Blanchard, Julia L.
author_sort Marshall, Abigail M.
collection PubMed
description To understand changes in ecosystems, the appropriate scale at which to study them must be determined. Large marine ecosystems (LMEs) cover thousands of square kilometres and are a useful classification scheme for ecosystem monitoring and assessment. However, averaging across LMEs may obscure intricate dynamics within. The purpose of this study is to mathematically determine local and regional patterns of ecological change within an LME using empirical orthogonal functions (EOFs). After using EOFs to define regions with distinct patterns of change, a statistical model originating from control theory is applied (Nonlinear AutoRegressive Moving Average with eXogenous input – NARMAX) to assess potential drivers of change within these regions. We have selected spatial data sets (0.5° latitude × 1°longitude) of fish abundance from North Sea fisheries research surveys (spanning 1980–2008) as well as of temperature, oxygen, net primary production and a fishing pressure proxy, to which we apply the EOF and NARMAX methods. Two regions showed significant changes since 1980: the central North Sea displayed a decrease in community size structure which the NARMAX model suggested was linked to changes in fishing; and the Norwegian trench region displayed an increase in community size structure which, as indicated by NARMAX results, was primarily linked to changes in sea‐bottom temperature. These regions were compared to an area of no change along the eastern Scottish coast where the model determined the community size structure was most strongly associated to net primary production. This study highlights the multifaceted effects of environmental change and fishing pressures in different regions of the North Sea. Furthermore, by highlighting this spatial heterogeneity in community size structure change, important local spatial dynamics are often overlooked when the North Sea is considered as a broad‐scale, homogeneous ecosystem (as normally is the case within the political Marine Strategy Framework Directive).
format Online
Article
Text
id pubmed-4991301
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-49913012016-09-06 Quantifying heterogeneous responses of fish community size structure using novel combined statistical techniques Marshall, Abigail M. Bigg, Grant R. van Leeuwen, Sonja M. Pinnegar, John K. Wei, Hua‐Liang Webb, Thomas J. Blanchard, Julia L. Glob Chang Biol Primary Research Articles To understand changes in ecosystems, the appropriate scale at which to study them must be determined. Large marine ecosystems (LMEs) cover thousands of square kilometres and are a useful classification scheme for ecosystem monitoring and assessment. However, averaging across LMEs may obscure intricate dynamics within. The purpose of this study is to mathematically determine local and regional patterns of ecological change within an LME using empirical orthogonal functions (EOFs). After using EOFs to define regions with distinct patterns of change, a statistical model originating from control theory is applied (Nonlinear AutoRegressive Moving Average with eXogenous input – NARMAX) to assess potential drivers of change within these regions. We have selected spatial data sets (0.5° latitude × 1°longitude) of fish abundance from North Sea fisheries research surveys (spanning 1980–2008) as well as of temperature, oxygen, net primary production and a fishing pressure proxy, to which we apply the EOF and NARMAX methods. Two regions showed significant changes since 1980: the central North Sea displayed a decrease in community size structure which the NARMAX model suggested was linked to changes in fishing; and the Norwegian trench region displayed an increase in community size structure which, as indicated by NARMAX results, was primarily linked to changes in sea‐bottom temperature. These regions were compared to an area of no change along the eastern Scottish coast where the model determined the community size structure was most strongly associated to net primary production. This study highlights the multifaceted effects of environmental change and fishing pressures in different regions of the North Sea. Furthermore, by highlighting this spatial heterogeneity in community size structure change, important local spatial dynamics are often overlooked when the North Sea is considered as a broad‐scale, homogeneous ecosystem (as normally is the case within the political Marine Strategy Framework Directive). John Wiley and Sons Inc. 2016-02-15 2016-05 /pmc/articles/PMC4991301/ /pubmed/26667981 http://dx.doi.org/10.1111/gcb.13190 Text en © 2015 The Authors. Global Change Biology Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Primary Research Articles
Marshall, Abigail M.
Bigg, Grant R.
van Leeuwen, Sonja M.
Pinnegar, John K.
Wei, Hua‐Liang
Webb, Thomas J.
Blanchard, Julia L.
Quantifying heterogeneous responses of fish community size structure using novel combined statistical techniques
title Quantifying heterogeneous responses of fish community size structure using novel combined statistical techniques
title_full Quantifying heterogeneous responses of fish community size structure using novel combined statistical techniques
title_fullStr Quantifying heterogeneous responses of fish community size structure using novel combined statistical techniques
title_full_unstemmed Quantifying heterogeneous responses of fish community size structure using novel combined statistical techniques
title_short Quantifying heterogeneous responses of fish community size structure using novel combined statistical techniques
title_sort quantifying heterogeneous responses of fish community size structure using novel combined statistical techniques
topic Primary Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4991301/
https://www.ncbi.nlm.nih.gov/pubmed/26667981
http://dx.doi.org/10.1111/gcb.13190
work_keys_str_mv AT marshallabigailm quantifyingheterogeneousresponsesoffishcommunitysizestructureusingnovelcombinedstatisticaltechniques
AT bigggrantr quantifyingheterogeneousresponsesoffishcommunitysizestructureusingnovelcombinedstatisticaltechniques
AT vanleeuwensonjam quantifyingheterogeneousresponsesoffishcommunitysizestructureusingnovelcombinedstatisticaltechniques
AT pinnegarjohnk quantifyingheterogeneousresponsesoffishcommunitysizestructureusingnovelcombinedstatisticaltechniques
AT weihualiang quantifyingheterogeneousresponsesoffishcommunitysizestructureusingnovelcombinedstatisticaltechniques
AT webbthomasj quantifyingheterogeneousresponsesoffishcommunitysizestructureusingnovelcombinedstatisticaltechniques
AT blanchardjulial quantifyingheterogeneousresponsesoffishcommunitysizestructureusingnovelcombinedstatisticaltechniques