How good are the ecological assumptions and predictions made in the past? Insights from a dynamic modelling approach applied to changing landscapes. (July 2018)

• Record Type: Journal Article
• Authors: Santos, Mário; Silva, Sara; Bastos, Rita; Carvalho, Diogo; Cabral, João Alexandre
• Is Part Of: Ecological indicators. Volume 90(2018)
• Page Start: 226
• Page End: 230
• Publication Date: 2018-07
• Subjects: Passerines -- Landscape -- Stochastic dynamic methodology -- Ecological indicators -- Ecological models' evaluation; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2018.03.023
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: A 2004 publication (P) predicted changes in the ecological status of agroecosystems. P simulations were evaluated using chronosequential and independent information. P simulated landscape changes and passerine trends were considered accurate. Passerines could be used as ecological indicators in changing agroecosystems. Abstract: 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.