Increasing the uptake of ecological model results in policy decisions to improve biodiversity outcomes. (March 2022)

• Record Type: Journal Article
• Authors: Weiskopf, Sarah R.; Harmáčková, Zuzana V.; Johnson, Ciara G.; Londoño-Murcia, María Cecilia; Miller, Brian W.; Myers, Bonnie J.E.; Pereira, Laura; Arce-Plata, Maria Isabel; Blanchard, Julia L.; Ferrier, Simon; Fulton, Elizabeth A.; Harfoot, Mike; Isbell, Forest; Johnson, Justin A.; Mori, Akira S.; Weng, Ensheng; Rosa, Isabel M.D.
• Is Part Of: Environmental modelling & software. Volume 149(2022)
• Publication Date: 2022-03
• Subjects: Biodiversity-ecosystem function relationships -- Co-production -- Ecological modeling -- Policy relevance -- Stakeholder engagement; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2022.105318
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Models help decision-makers anticipate the consequences of policies for ecosystems and people; for instance, improving our ability to represent interactions between human activities and ecological systems is essential to identify pathways to meet the 2030 Sustainable Development Goals. However, use of modeling outputs in decision-making remains uncommon. We share insights from a multidisciplinary National Socio-Environmental Synthesis Center working group on technical, communication, and process-related factors that facilitate or hamper uptake of model results. We emphasize that it is not simply technical model improvements, but active and iterative stakeholder involvement that can lead to more impactful outcomes. In particular, trust- and relationship-building with decision-makers are key for knowledge-based decision making. In this respect, nurturing knowledge exchange on the interpersonal (e.g., through participatory processes) and institutional level (e.g., through science-policy interfaces across scales) represents a promising approach. To this end, we offer a generalized approach for linking modeling and decision-making.