Converting conventional ecological datasets in dynamic and dynamic
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , |
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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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 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10348/4298 |
url |
http://hdl.handle.net/10348/4298 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
doi: 10.1016/j.ecolmodel.2013.02.028 |
dc.rights.driver.fl_str_mv |
metadata only access info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
metadata only access |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799137121555972096 |