Utilize este identificador para referenciar este registo: http://hdl.handle.net/10348/4298
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dc.contributor.authorSantos, Mário-
dc.contributor.authorBastos, Rita-
dc.contributor.authorCabral, João Alexandre-
dc.date.accessioned2015-03-17T14:04:02Z-
dc.date.available2015-03-17T14:04:02Z-
dc.date.issued2013-
dc.identifier.citationSantos M. et al, 2013pt
dc.identifier.otherdoi: 10.1016/j.ecolmodel.2013.02.028-
dc.identifier.urihttp://hdl.handle.net/10348/4298-
dc.description.abstractThe 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.pt
dc.language.isoengpt
dc.relation.ispartofCITAB - Centro de Investigação e de Tecnologias Agro-Ambientais e Biológicaspt
dc.rightsclosedAccesspt
dc.subjectStochastic Dynamic Methodologypt
dc.subjectEcological trendspt
dc.subjectStDM reviewpt
dc.subjectSpatially explicit StDM frameworkpt
dc.subjectEcological modelspt
dc.titleConverting conventional ecological datasets in dynamic and dynamicpt
dc.typearticlept
degois.publication.firstPage91pt
degois.publication.issue258pt
degois.publication.lastPage100pt
degois.publication.locationElsevierpt
degois.publication.titleEcological Modellingpt
dc.peerreviewedyespt
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