A Stochastic Dynamic Methodology (SDM) to the modelling of trophic interactions, with a focus on estuarine eutrophication scenarios

Detalhes bibliográficos
Autor(a) principal: Silva-Santos, Pedro
Data de Publicação: 2006
Outros Autores: Pardal, Miguel Ângelo, Lopes, Ricardo Jorge, Múrias, Tiago, 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/10316/5350
https://doi.org/10.1016/j.ecolind.2005.05.001
Resumo: In the face of global change, declines in environmental quality are of increasing concern, especially in shallow coastal areas, densely populated and commonly affected by nutrient enrichment. The warm temperate Mondego estuary (Western Portugal), in common with many other shallow estuarine areas, is exhibiting increased macroalgal growth due to nutrient enrichment. The increase of macroalgal biomass and possible shift of other primary producers resulting from eutrophication, may have profound effects on estuarine trophic chain. The present paper examined the performance of a holistic Stochastic Dynamic Methodology (SDM) in predicting the tendencies of three representative trophic levels as a response to the increase of nutrient concentrations. Therefore, the proposed methodology has been developed by focusing on the interactions between conceptually isolated key-components, such as primary producers (macroalgae and seagrass), some relevant benthic macroinvertebrates, wading birds and changes in local physicochemical conditions. The dynamic model developed was preceded by a conventional multivariate statistical procedure (stepwise multiple regression analysis) performed to discriminate the significant relationships between prevailing biological and environmental variables. Since this statistical analysis is static, the dataset recorded from the field included true gradients of habitat changes. The data used in the model construction was sampled between January 1993 and September 1995 in three areas of the estuary mudflats for benthic macroinvertebrates, macroalgae, environmental and physicochemical factors and from October 1993 to October 1994 for wading birds. The model validation was based on independent data collected in two different periods, from January 1996 to January 1997 and from February 1999 to April 2000 for all the variables selected. Overall, the simulation results are encouraging since they seem to demonstrate the model reliability in capturing the trophic dynamics of the studied estuary by predicting the behavioural pattern for the most part of the components selected under a very complex and variable environmental scenario.
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spelling A Stochastic Dynamic Methodology (SDM) to the modelling of trophic interactions, with a focus on estuarine eutrophication scenariosStochastic dynamic modellingEcological integrityEutrophicationMondego estuaryTrophic interactionsIn the face of global change, declines in environmental quality are of increasing concern, especially in shallow coastal areas, densely populated and commonly affected by nutrient enrichment. The warm temperate Mondego estuary (Western Portugal), in common with many other shallow estuarine areas, is exhibiting increased macroalgal growth due to nutrient enrichment. The increase of macroalgal biomass and possible shift of other primary producers resulting from eutrophication, may have profound effects on estuarine trophic chain. The present paper examined the performance of a holistic Stochastic Dynamic Methodology (SDM) in predicting the tendencies of three representative trophic levels as a response to the increase of nutrient concentrations. Therefore, the proposed methodology has been developed by focusing on the interactions between conceptually isolated key-components, such as primary producers (macroalgae and seagrass), some relevant benthic macroinvertebrates, wading birds and changes in local physicochemical conditions. The dynamic model developed was preceded by a conventional multivariate statistical procedure (stepwise multiple regression analysis) performed to discriminate the significant relationships between prevailing biological and environmental variables. Since this statistical analysis is static, the dataset recorded from the field included true gradients of habitat changes. The data used in the model construction was sampled between January 1993 and September 1995 in three areas of the estuary mudflats for benthic macroinvertebrates, macroalgae, environmental and physicochemical factors and from October 1993 to October 1994 for wading birds. The model validation was based on independent data collected in two different periods, from January 1996 to January 1997 and from February 1999 to April 2000 for all the variables selected. Overall, the simulation results are encouraging since they seem to demonstrate the model reliability in capturing the trophic dynamics of the studied estuary by predicting the behavioural pattern for the most part of the components selected under a very complex and variable environmental scenario.http://www.sciencedirect.com/science/article/B6W87-4GKW799-1/1/ab5142848de94cfd92f687763783f2af2006info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleaplication/PDFhttp://hdl.handle.net/10316/5350http://hdl.handle.net/10316/5350https://doi.org/10.1016/j.ecolind.2005.05.001engEcological Indicators. 6:2 (2006) 394-408Silva-Santos, PedroPardal, Miguel ÂngeloLopes, Ricardo JorgeMúrias, TiagoCabral, João Alexandreinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2021-10-07T11:51:03ZPortal AgregadorONG
dc.title.none.fl_str_mv A Stochastic Dynamic Methodology (SDM) to the modelling of trophic interactions, with a focus on estuarine eutrophication scenarios
title A Stochastic Dynamic Methodology (SDM) to the modelling of trophic interactions, with a focus on estuarine eutrophication scenarios
spellingShingle A Stochastic Dynamic Methodology (SDM) to the modelling of trophic interactions, with a focus on estuarine eutrophication scenarios
Silva-Santos, Pedro
Stochastic dynamic modelling
Ecological integrity
Eutrophication
Mondego estuary
Trophic interactions
title_short A Stochastic Dynamic Methodology (SDM) to the modelling of trophic interactions, with a focus on estuarine eutrophication scenarios
title_full A Stochastic Dynamic Methodology (SDM) to the modelling of trophic interactions, with a focus on estuarine eutrophication scenarios
title_fullStr A Stochastic Dynamic Methodology (SDM) to the modelling of trophic interactions, with a focus on estuarine eutrophication scenarios
title_full_unstemmed A Stochastic Dynamic Methodology (SDM) to the modelling of trophic interactions, with a focus on estuarine eutrophication scenarios
title_sort A Stochastic Dynamic Methodology (SDM) to the modelling of trophic interactions, with a focus on estuarine eutrophication scenarios
author Silva-Santos, Pedro
author_facet Silva-Santos, Pedro
Pardal, Miguel Ângelo
Lopes, Ricardo Jorge
Múrias, Tiago
Cabral, João Alexandre
author_role author
author2 Pardal, Miguel Ângelo
Lopes, Ricardo Jorge
Múrias, Tiago
Cabral, João Alexandre
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Silva-Santos, Pedro
Pardal, Miguel Ângelo
Lopes, Ricardo Jorge
Múrias, Tiago
Cabral, João Alexandre
dc.subject.por.fl_str_mv Stochastic dynamic modelling
Ecological integrity
Eutrophication
Mondego estuary
Trophic interactions
topic Stochastic dynamic modelling
Ecological integrity
Eutrophication
Mondego estuary
Trophic interactions
description In the face of global change, declines in environmental quality are of increasing concern, especially in shallow coastal areas, densely populated and commonly affected by nutrient enrichment. The warm temperate Mondego estuary (Western Portugal), in common with many other shallow estuarine areas, is exhibiting increased macroalgal growth due to nutrient enrichment. The increase of macroalgal biomass and possible shift of other primary producers resulting from eutrophication, may have profound effects on estuarine trophic chain. The present paper examined the performance of a holistic Stochastic Dynamic Methodology (SDM) in predicting the tendencies of three representative trophic levels as a response to the increase of nutrient concentrations. Therefore, the proposed methodology has been developed by focusing on the interactions between conceptually isolated key-components, such as primary producers (macroalgae and seagrass), some relevant benthic macroinvertebrates, wading birds and changes in local physicochemical conditions. The dynamic model developed was preceded by a conventional multivariate statistical procedure (stepwise multiple regression analysis) performed to discriminate the significant relationships between prevailing biological and environmental variables. Since this statistical analysis is static, the dataset recorded from the field included true gradients of habitat changes. The data used in the model construction was sampled between January 1993 and September 1995 in three areas of the estuary mudflats for benthic macroinvertebrates, macroalgae, environmental and physicochemical factors and from October 1993 to October 1994 for wading birds. The model validation was based on independent data collected in two different periods, from January 1996 to January 1997 and from February 1999 to April 2000 for all the variables selected. Overall, the simulation results are encouraging since they seem to demonstrate the model reliability in capturing the trophic dynamics of the studied estuary by predicting the behavioural pattern for the most part of the components selected under a very complex and variable environmental scenario.
publishDate 2006
dc.date.none.fl_str_mv 2006
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/5350
http://hdl.handle.net/10316/5350
https://doi.org/10.1016/j.ecolind.2005.05.001
url http://hdl.handle.net/10316/5350
https://doi.org/10.1016/j.ecolind.2005.05.001
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Ecological Indicators. 6:2 (2006) 394-408
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv aplication/PDF
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