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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/10867
Ver los metadatos del registro completo
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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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1844613645267369984 |
score |
13.070432 |