Predictive systems ecology

Autores
Evans, Matthew; Bithell, Mike; Cornell, Stephen; Dall, Sasha; Diaz, Sandra Myrna; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J.; Lewis, Simon L.; Mace, Georgina M.; Morecroft, Micheal; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K. J; Petchey, Owen; Smith, Matthew; Travis, Justin; Benton, Tim
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.
Fil: Evans, Matthew. Queen Mary University of London. School of Biological and Chemical Sciences; Reino Unido
Fil: Bithell, Mike. University of Liverpool. Institute of Integrative Biology; Reino Unido
Fil: Cornell, Stephen. University of Liverpool. Institute of Integrative Biology; Reino Unido
Fil: Dall, Sasha. University of Exeter. College of Life and Environmental Sciences.Centre for Ecology and Conservation; Reino Unido
Fil: Diaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Instituto Multidisciplinario de Biología Vegetal (p); Argentina
Fil: Emmott, Stephen. Computational Science Laboratory, Cambridge; Reino Unido
Fil: Ernande, Bruno. IFREMER. Laboratorie Ressources Halieutiques; Francia
Fil: Grimm, Volker. Helmhotz Center for Environmental Research, Department of Ecological Modelling, Leipzig; Alemania
Fil: Hodgson, David J.. University of Exeter. College of Life and Environmental Sciences. Centre for Ecology and Conservation; Reino Unido
Fil: Lewis, Simon L.. University of Leeds. Earth and Biosphere Institute; Reino Unido
Fil: Mace, Georgina M.. University College London. Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment; Reino Unido
Fil: Morecroft, Micheal. Cromwell House; Reino Unido
Fil: Moustakas, Aristides. Queen Mary University of London. School of Biological and Chemical Sciences; Reino Unido
Fil: Murphy, Eugene. British Antarctic Survey, Cambridge; Reino Unido
Fil: Newbold, Tim. United Nations Environment Programme World Conservation Monitoring, Cambridge; Reino Unido
Fil: Norris, K. J. The University of Reading, Centre for Agri-Environmental Research, School of Agriculture, Policy and Development; Reino Unido
Fil: Petchey, Owen. University of Zurich . Institute of Evolutionary Biology and Environmental Studies; Reino Unido
Fil: Smith, Matthew. Computational Science Laboratory; Reino Unido
Fil: Travis, Justin. Institute of Biological and Environmental Sciences, Aberdeen; Reino Unido
Fil: Benton, Tim. University of Leeds. School of Biology; Reino Unido
Materia
MODELLING
SYSTEMS ECOLOGY
CLIMATE CHANGE
ECOSYSTEM ASSESSMENT
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/10867

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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Predictive systems ecologyEvans, MatthewBithell, MikeCornell, StephenDall, SashaDiaz, Sandra MyrnaEmmott, StephenErnande, BrunoGrimm, VolkerHodgson, David J.Lewis, Simon L.Mace, Georgina M.Morecroft, MichealMoustakas, AristidesMurphy, EugeneNewbold, TimNorris, K. JPetchey, OwenSmith, MatthewTravis, JustinBenton, TimMODELLINGSYSTEMS ECOLOGYCLIMATE CHANGEECOSYSTEM ASSESSMENThttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.Fil: Evans, Matthew. Queen Mary University of London. School of Biological and Chemical Sciences; Reino UnidoFil: Bithell, Mike. University of Liverpool. Institute of Integrative Biology; Reino UnidoFil: Cornell, Stephen. University of Liverpool. Institute of Integrative Biology; Reino UnidoFil: Dall, Sasha. University of Exeter. College of Life and Environmental Sciences.Centre for Ecology and Conservation; Reino UnidoFil: Diaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Instituto Multidisciplinario de Biología Vegetal (p); ArgentinaFil: Emmott, Stephen. Computational Science Laboratory, Cambridge; Reino UnidoFil: Ernande, Bruno. IFREMER. Laboratorie Ressources Halieutiques; FranciaFil: Grimm, Volker. Helmhotz Center for Environmental Research, Department of Ecological Modelling, Leipzig; AlemaniaFil: Hodgson, David J.. University of Exeter. College of Life and Environmental Sciences. Centre for Ecology and Conservation; Reino UnidoFil: Lewis, Simon L.. University of Leeds. Earth and Biosphere Institute; Reino UnidoFil: Mace, Georgina M.. University College London. Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment; Reino UnidoFil: Morecroft, Micheal. Cromwell House; Reino UnidoFil: Moustakas, Aristides. Queen Mary University of London. School of Biological and Chemical Sciences; Reino UnidoFil: Murphy, Eugene. British Antarctic Survey, Cambridge; Reino UnidoFil: Newbold, Tim. United Nations Environment Programme World Conservation Monitoring, Cambridge; Reino UnidoFil: Norris, K. J. The University of Reading, Centre for Agri-Environmental Research, School of Agriculture, Policy and Development; Reino UnidoFil: Petchey, Owen. University of Zurich . Institute of Evolutionary Biology and Environmental Studies; Reino UnidoFil: Smith, Matthew. Computational Science Laboratory; Reino UnidoFil: Travis, Justin. Institute of Biological and Environmental Sciences, Aberdeen; Reino UnidoFil: Benton, Tim. University of Leeds. School of Biology; Reino UnidoThe Royal Society2013-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/10867Evans, Matthew; Bithell, Mike; Cornell, Stephen; Dall, Sasha; Diaz, Sandra Myrna; et al.; Predictive systems ecology; The Royal Society; Proceedings Of The Royal Society Of London Series A-mathematical Physical And Engineering Sciences; 280; 10-2013; 1-101364-5021enginfo:eu-repo/semantics/altIdentifier/url/http://rspb.royalsocietypublishing.org/content/280/1771/20131452info:eu-repo/semantics/altIdentifier/doi/10.1098/rspb.2013.1452info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:54:04Zoai:ri.conicet.gov.ar:11336/10867instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:54:04.517CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Predictive systems ecology
title Predictive systems ecology
spellingShingle Predictive systems ecology
Evans, Matthew
MODELLING
SYSTEMS ECOLOGY
CLIMATE CHANGE
ECOSYSTEM ASSESSMENT
title_short Predictive systems ecology
title_full Predictive systems ecology
title_fullStr Predictive systems ecology
title_full_unstemmed Predictive systems ecology
title_sort Predictive systems ecology
dc.creator.none.fl_str_mv Evans, Matthew
Bithell, Mike
Cornell, Stephen
Dall, Sasha
Diaz, Sandra Myrna
Emmott, Stephen
Ernande, Bruno
Grimm, Volker
Hodgson, David J.
Lewis, Simon L.
Mace, Georgina M.
Morecroft, Micheal
Moustakas, Aristides
Murphy, Eugene
Newbold, Tim
Norris, K. J
Petchey, Owen
Smith, Matthew
Travis, Justin
Benton, Tim
author Evans, Matthew
author_facet Evans, Matthew
Bithell, Mike
Cornell, Stephen
Dall, Sasha
Diaz, Sandra Myrna
Emmott, Stephen
Ernande, Bruno
Grimm, Volker
Hodgson, David J.
Lewis, Simon L.
Mace, Georgina M.
Morecroft, Micheal
Moustakas, Aristides
Murphy, Eugene
Newbold, Tim
Norris, K. J
Petchey, Owen
Smith, Matthew
Travis, Justin
Benton, Tim
author_role author
author2 Bithell, Mike
Cornell, Stephen
Dall, Sasha
Diaz, Sandra Myrna
Emmott, Stephen
Ernande, Bruno
Grimm, Volker
Hodgson, David J.
Lewis, Simon L.
Mace, Georgina M.
Morecroft, Micheal
Moustakas, Aristides
Murphy, Eugene
Newbold, Tim
Norris, K. J
Petchey, Owen
Smith, Matthew
Travis, Justin
Benton, Tim
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv MODELLING
SYSTEMS ECOLOGY
CLIMATE CHANGE
ECOSYSTEM ASSESSMENT
topic MODELLING
SYSTEMS ECOLOGY
CLIMATE CHANGE
ECOSYSTEM ASSESSMENT
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.
Fil: Evans, Matthew. Queen Mary University of London. School of Biological and Chemical Sciences; Reino Unido
Fil: Bithell, Mike. University of Liverpool. Institute of Integrative Biology; Reino Unido
Fil: Cornell, Stephen. University of Liverpool. Institute of Integrative Biology; Reino Unido
Fil: Dall, Sasha. University of Exeter. College of Life and Environmental Sciences.Centre for Ecology and Conservation; Reino Unido
Fil: Diaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Instituto Multidisciplinario de Biología Vegetal (p); Argentina
Fil: Emmott, Stephen. Computational Science Laboratory, Cambridge; Reino Unido
Fil: Ernande, Bruno. IFREMER. Laboratorie Ressources Halieutiques; Francia
Fil: Grimm, Volker. Helmhotz Center for Environmental Research, Department of Ecological Modelling, Leipzig; Alemania
Fil: Hodgson, David J.. University of Exeter. College of Life and Environmental Sciences. Centre for Ecology and Conservation; Reino Unido
Fil: Lewis, Simon L.. University of Leeds. Earth and Biosphere Institute; Reino Unido
Fil: Mace, Georgina M.. University College London. Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment; Reino Unido
Fil: Morecroft, Micheal. Cromwell House; Reino Unido
Fil: Moustakas, Aristides. Queen Mary University of London. School of Biological and Chemical Sciences; Reino Unido
Fil: Murphy, Eugene. British Antarctic Survey, Cambridge; Reino Unido
Fil: Newbold, Tim. United Nations Environment Programme World Conservation Monitoring, Cambridge; Reino Unido
Fil: Norris, K. J. The University of Reading, Centre for Agri-Environmental Research, School of Agriculture, Policy and Development; Reino Unido
Fil: Petchey, Owen. University of Zurich . Institute of Evolutionary Biology and Environmental Studies; Reino Unido
Fil: Smith, Matthew. Computational Science Laboratory; Reino Unido
Fil: Travis, Justin. Institute of Biological and Environmental Sciences, Aberdeen; Reino Unido
Fil: Benton, Tim. University of Leeds. School of Biology; Reino Unido
description Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.
publishDate 2013
dc.date.none.fl_str_mv 2013-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/10867
Evans, Matthew; Bithell, Mike; Cornell, Stephen; Dall, Sasha; Diaz, Sandra Myrna; et al.; Predictive systems ecology; The Royal Society; Proceedings Of The Royal Society Of London Series A-mathematical Physical And Engineering Sciences; 280; 10-2013; 1-10
1364-5021
url http://hdl.handle.net/11336/10867
identifier_str_mv Evans, Matthew; Bithell, Mike; Cornell, Stephen; Dall, Sasha; Diaz, Sandra Myrna; et al.; Predictive systems ecology; The Royal Society; Proceedings Of The Royal Society Of London Series A-mathematical Physical And Engineering Sciences; 280; 10-2013; 1-10
1364-5021
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://rspb.royalsocietypublishing.org/content/280/1771/20131452
info:eu-repo/semantics/altIdentifier/doi/10.1098/rspb.2013.1452
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv The Royal Society
publisher.none.fl_str_mv The Royal Society
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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