Unified process model-based assessment of environmental interactions and ecosystem services of a managed fishpond-reed agroecosystem

Le résumé fourni par la source

To support better management of agroecosystems, this work presents a novel approach by considering a quantitative dynamic model-based and holistic background of environmental interactions. Recognizing the increasing importance of coupled systems in environmental management, the methodology is illustrated by a case study of a managed fishpond, partially covered by reed vegetation, and surrounded by reed beds. The unified elements of Programmable Process Structures (PPS) are used to analyze the underlying processes (physical, chemical, biological, ecological, technological, and managerial) and to determine the effects of management interventions on the environmental interactions of the fishpond agroecosystem. Simplified sub-process models have been implemented to calculate the dynamic environmental interactions of the example system studied. The sub-models exploit the approximate stoichiometries and causal relationships behind the environmental interactions with a transparent insight into the structured functionalities of the complex system. These features provide holistic model-based simulations from which the impacts of different management scenarios can be assessed. It is also discussed how the calculated quantitative environmental interactions can be used for a more rigorous assessment of ecosystem services (ES) and dis-services (EDS). It is concluded that many categories of ES (such as provisioning and regulatory services) can be derived directly from the quantitative environmental interactions. Other categories, such as habitat maintenance for biodiversity and cultural services, can be derived by combining the simulated quantitative data with expert-defined qualitative rules. The generalizable results and the reusable computational method outline the basis for a case-specific decision support tool based on a process model in further work.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.