Revealing perturbation responses with limited observations of biological communities

Restrictions in empirical research of biological communities have limited our understanding of the combined influence of environmental variability and system structure on community composition. Spatial patterns of community composition in less accessible systems, such as marine benthos, can often no...

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Autores principales:	Nikolaos Alexandridis, Cédric Bacher, Fred Jean, Jeffrey M. Dambacher
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Biological traits Biotic interactions Community structure Ecological perturbation Environmental variability Qualitative modelling Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/6e1068e966134289971720a668124848
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spelling	oai:doaj.org-article:6e1068e966134289971720a6681248482021-12-01T04:54:17ZRevealing perturbation responses with limited observations of biological communities1470-160X10.1016/j.ecolind.2021.107840https://doaj.org/article/6e1068e966134289971720a6681248482021-09-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21005057https://doaj.org/toc/1470-160XRestrictions in empirical research of biological communities have limited our understanding of the combined influence of environmental variability and system structure on community composition. Spatial patterns of community composition in less accessible systems, such as marine benthos, can often not be explained by many factors beyond the direct impact of the environment on community members. We present a method that combines commonly collected data of community composition with analyses of qualitative mathematical models, to assess not only direct impacts of environmental variability, but also the propagation of impacts through complex interaction networks. Transformed spatial data of community composition describe the community members’ observed similarity of response to an external input. The output of qualitative mathematical models describes the community members’ predicted similarity of response to input entering the system through any of its variables. A statistically significant agreement between the observed and any of the predicted response similarities indicates the respective system variable as a likely gateway for environmental variability into the system. The method is applied to benthic macroinvertebrate communities in the Rance estuary (Brittany, France). Organisms identified as likely gateways have traits that agree with their predicted response to documented spatially and temporally structured environmental variability. We suggest use of this novel framework for more comprehensive identification of environmental drivers of community change, including gateway community members and cascades of environmentally driven change through community structure.Nikolaos AlexandridisCédric BacherFred JeanJeffrey M. DambacherElsevierarticleBiological traitsBiotic interactionsCommunity structureEcological perturbationEnvironmental variabilityQualitative modellingEcologyQH540-549.5ENEcological Indicators, Vol 128, Iss , Pp 107840- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biological traits Biotic interactions Community structure Ecological perturbation Environmental variability Qualitative modelling Ecology QH540-549.5
spellingShingle	Biological traits Biotic interactions Community structure Ecological perturbation Environmental variability Qualitative modelling Ecology QH540-549.5 Nikolaos Alexandridis Cédric Bacher Fred Jean Jeffrey M. Dambacher Revealing perturbation responses with limited observations of biological communities
description	Restrictions in empirical research of biological communities have limited our understanding of the combined influence of environmental variability and system structure on community composition. Spatial patterns of community composition in less accessible systems, such as marine benthos, can often not be explained by many factors beyond the direct impact of the environment on community members. We present a method that combines commonly collected data of community composition with analyses of qualitative mathematical models, to assess not only direct impacts of environmental variability, but also the propagation of impacts through complex interaction networks. Transformed spatial data of community composition describe the community members’ observed similarity of response to an external input. The output of qualitative mathematical models describes the community members’ predicted similarity of response to input entering the system through any of its variables. A statistically significant agreement between the observed and any of the predicted response similarities indicates the respective system variable as a likely gateway for environmental variability into the system. The method is applied to benthic macroinvertebrate communities in the Rance estuary (Brittany, France). Organisms identified as likely gateways have traits that agree with their predicted response to documented spatially and temporally structured environmental variability. We suggest use of this novel framework for more comprehensive identification of environmental drivers of community change, including gateway community members and cascades of environmentally driven change through community structure.
format	article
author	Nikolaos Alexandridis Cédric Bacher Fred Jean Jeffrey M. Dambacher
author_facet	Nikolaos Alexandridis Cédric Bacher Fred Jean Jeffrey M. Dambacher
author_sort	Nikolaos Alexandridis
title	Revealing perturbation responses with limited observations of biological communities
title_short	Revealing perturbation responses with limited observations of biological communities
title_full	Revealing perturbation responses with limited observations of biological communities
title_fullStr	Revealing perturbation responses with limited observations of biological communities
title_full_unstemmed	Revealing perturbation responses with limited observations of biological communities
title_sort	revealing perturbation responses with limited observations of biological communities
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/6e1068e966134289971720a668124848
work_keys_str_mv	AT nikolaosalexandridis revealingperturbationresponseswithlimitedobservationsofbiologicalcommunities AT cedricbacher revealingperturbationresponseswithlimitedobservationsofbiologicalcommunities AT fredjean revealingperturbationresponseswithlimitedobservationsofbiologicalcommunities AT jeffreymdambacher revealingperturbationresponseswithlimitedobservationsofbiologicalcommunities
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Revealing perturbation responses with limited observations of biological communities

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