How good are the ecological assumptions and predictions made in the past? Insights from a dynamic modelling approach applied to changing landscapes
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Data
2018
Autores
Santos, Mario Gabriel Santiago Dos
Cabral, João Alexandre Ferreira Abel Dos ...
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Resumo
Worldwide landscape changes and the uncertainty about its impacts on species abundances, distributions and on ecosystems structure and functioning, have been increasing the value of modelling tools in a very obvious way. Thirteen years ago, the first holistic stochastic dynamic methodology (StDM) application was published (Ecological Indicators 3(4), 285–303 by Santos and Cabral (2004)) intended for predicting ecological indicators trends in face of realistic scenarios of land use/land cover changes. The application of this StDM framework provided some basis to simulate landscape changes and predict the subsequent response of pertinent ecological indicators. Nevertheless, the results reliability could only be evaluated with subsequent independent information checking. In this work, based on independent data obtained thirteen years after, we compare the simulated land use changes and predicted responses of the selected ecological indicators with the respective real trends. The comparisons made confirmed that the implemented scenario was realistic and the ecological indicators’ response mostly accurate. This allowed for demonstrating the proposed frameworks potential and its use in landscape planning and managing of agro-environmental measures. Our approach also provides a promising and intuitive baseline to support risk assessments for land use changes, derived from ecological models linked with ecological monitoring, crucial to guide decision makers and environmental managers.
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Palavras-chave
Passerines , Landscape , Stochastic dynamic methodology , Ecological indicators , Ecological models’ evaluation
Citação
Santos, Mário; Silva, Sara; Bastos, Rita; Carvalho, Diogo; Cabral, João Alexandre. How good are the ecological assumptions and predictions made in the past? Insights from a dynamic modelling approach applied to changing landscapes, Ecological Indicators, 90, 90, 226-230, 2018.