Converting conventional ecological datasets in dynamic and dynamic

Detalhes bibliográficos
Autor(a) principal: Santos, Mário
Data de Publicação: 2013
Outros Autores: Bastos, Rita, Cabral, João Alexandre
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10348/4298
Resumo: The Stochastic Dynamic Methodology (StDM) is a mechanistic framework for simulating ecological processes, based on statistical parameter estimation methods. This methodology is a sequential modelling process primarily developed to predict impacts of anthropogenic activities in the ecological status of ecosystems. Over the last years, this approach was increasingly tested and advances as well as limitations have clearly emerged from the different ecological contexts, scales and target organisms, guilds and/or communities studied. We review the performance of the StDM applications, by system types and upgraded innovation. Most published papers with StDM models were dedicated to assess anthropogenic pressures in the scope of the ecological integrity problematic by using the state variables as ecological indicators. We discuss the StDM concepts, requirements, ecological relevance, universality and the current spatial integration with Geographic Information Systems (GIS) and other types of modelling approaches. Additionally, we describe a simple demonstrative application in order to illustrate the framework methodological steps, supporting the theoretic concepts previously presented with a study case background.
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spelling Converting conventional ecological datasets in dynamic and dynamicStochastic Dynamic MethodologyEcological trendsStDM reviewSpatially explicit StDM frameworkEcological modelsThe Stochastic Dynamic Methodology (StDM) is a mechanistic framework for simulating ecological processes, based on statistical parameter estimation methods. This methodology is a sequential modelling process primarily developed to predict impacts of anthropogenic activities in the ecological status of ecosystems. Over the last years, this approach was increasingly tested and advances as well as limitations have clearly emerged from the different ecological contexts, scales and target organisms, guilds and/or communities studied. We review the performance of the StDM applications, by system types and upgraded innovation. Most published papers with StDM models were dedicated to assess anthropogenic pressures in the scope of the ecological integrity problematic by using the state variables as ecological indicators. We discuss the StDM concepts, requirements, ecological relevance, universality and the current spatial integration with Geographic Information Systems (GIS) and other types of modelling approaches. Additionally, we describe a simple demonstrative application in order to illustrate the framework methodological steps, supporting the theoretic concepts previously presented with a study case background.2015-03-17T14:04:02Z2013-01-01T00:00:00Z2013info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10348/4298engdoi: 10.1016/j.ecolmodel.2013.02.028metadata only accessinfo:eu-repo/semantics/openAccessSantos, MárioBastos, RitaCabral, João Alexandrereponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-02T12:44:02Zoai:repositorio.utad.pt:10348/4298Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:03:37.752728Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Converting conventional ecological datasets in dynamic and dynamic
title Converting conventional ecological datasets in dynamic and dynamic
spellingShingle Converting conventional ecological datasets in dynamic and dynamic
Santos, Mário
Stochastic Dynamic Methodology
Ecological trends
StDM review
Spatially explicit StDM framework
Ecological models
title_short Converting conventional ecological datasets in dynamic and dynamic
title_full Converting conventional ecological datasets in dynamic and dynamic
title_fullStr Converting conventional ecological datasets in dynamic and dynamic
title_full_unstemmed Converting conventional ecological datasets in dynamic and dynamic
title_sort Converting conventional ecological datasets in dynamic and dynamic
author Santos, Mário
author_facet Santos, Mário
Bastos, Rita
Cabral, João Alexandre
author_role author
author2 Bastos, Rita
Cabral, João Alexandre
author2_role author
author
dc.contributor.author.fl_str_mv Santos, Mário
Bastos, Rita
Cabral, João Alexandre
dc.subject.por.fl_str_mv Stochastic Dynamic Methodology
Ecological trends
StDM review
Spatially explicit StDM framework
Ecological models
topic Stochastic Dynamic Methodology
Ecological trends
StDM review
Spatially explicit StDM framework
Ecological models
description The Stochastic Dynamic Methodology (StDM) is a mechanistic framework for simulating ecological processes, based on statistical parameter estimation methods. This methodology is a sequential modelling process primarily developed to predict impacts of anthropogenic activities in the ecological status of ecosystems. Over the last years, this approach was increasingly tested and advances as well as limitations have clearly emerged from the different ecological contexts, scales and target organisms, guilds and/or communities studied. We review the performance of the StDM applications, by system types and upgraded innovation. Most published papers with StDM models were dedicated to assess anthropogenic pressures in the scope of the ecological integrity problematic by using the state variables as ecological indicators. We discuss the StDM concepts, requirements, ecological relevance, universality and the current spatial integration with Geographic Information Systems (GIS) and other types of modelling approaches. Additionally, we describe a simple demonstrative application in order to illustrate the framework methodological steps, supporting the theoretic concepts previously presented with a study case background.
publishDate 2013
dc.date.none.fl_str_mv 2013-01-01T00:00:00Z
2013
2015-03-17T14:04:02Z
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dc.relation.none.fl_str_mv doi: 10.1016/j.ecolmodel.2013.02.028
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