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Descripción
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| tThe planning and management of river ecosystems affects a variety of social groups (i.e., managers,stakeholders, professionals and users) who have different interests about water uses. To avoid conflictsand reach an environmentally sustainable management, various methods have been devised to enable theparticipation of these actors. Mathematical modelling of river systems is highly recommended to forecast,but we do not always have enough information to do it. In these cases, the soft and meta-models can bevalid alternatives to simulate these complex systems.The Fuzzy Cognitive Maps (FCMs) are presented as a tool that facilitates the modelling of ecologicalsystems, functions and services. FCM networking concepts are intertwined through causal relationships.The FCM concept spatial arrangement and the use of fuzzy logic facilitate the integration of differentexpert opinions. In our study, from a panel of seven experts from representatives of different social sectors,an aggregated FCM was obtained. The most central concept in the aggregated map was cross barriers, damsand weirs. Using our FCM expert model, we performed a number of simulations from different possiblescenarios, such as the continuous degradation of natural conditions and the improvement of river naturalconditions. A regular increment in the natural conditions generates a substantial enhance in variables asnatural water flow and sediment transport. Conversely, the increment in human activities as agro-forestryproduction addresses to a deterioration of river banks among other variables.In the Esla River, the FCM indicators showed an ecosystem that was greatly influenced by humanactivity, especially by the presence of barriers, in which the economic variables presented high networkinfluence even though their centrality indices were relatively low. Meanwhile, the essential elements forthe proper functioning of this ecosystem, as a natural flow regime, showed very low values that werevisibly affected by anthropogenic variables.FCM methodology enabled us not only to understand the perception of current fluvial ecosystems butalso to generate plausible management scenarios based on expert knowledge in this field. | |
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Internacional
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Si |
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JCR del ISI
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Si |
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Título de la revista
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Ecological Modelling |
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ISSN
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0304-3800 |
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Factor de impacto JCR
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2,275 |
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Información de impacto
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Datos JCR del año 2015 |
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Volumen
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360 |
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DOI
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10.1016/j.ecolmodel.2017.07.010 |
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Número de revista
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360 |
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Desde la página
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260 |
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Hasta la página
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269 |
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Mes
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SIN MES |
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Ranking
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