A bayesian network to inform the management of key species in Kosterhavet National Park under contrasting storylines of environmental change

Abstract

Global climate change and related land use changes are expected to impose unprecedented pressures on coastal biodiversity and ecosystem processes. To sustainably manage coastal ecosystems, it is crucial to predict the consequences of human activities for coastal ecosystems and identify areas for directed abatement measures. Empirical data together with expert knowledge and evidence from the literature were integrated into a Bayesian Belief Network (BBN) for a marine protected area, the Kosterhavet National Park off the Swedish west coast. The variability and interactions of anthropogenic pressures and two key ecosystem components, eelgrass meadows and northern shrimp stock, were tested under four storylines of environmental change. The results show that of the influential drivers of environmental change, only three variables (bottom trawling, leisure boating and aquaculture) are manageable within the national park itself. Scenario analysis suggested that notable gains of both ecosystem components were most likely under a storyline of sustainable development, assuming a radiative forcing of 4.5 W/m2 by 2100 in concert with a preventive cooperation among neighboring countries and a tighter restriction of commercial and recreational uses in the park area. The findings suggest that the sustainable management of eelgrass meadows and northern shrimp stock in Kosterhavet National Park requires both local measures at the scale of the park's water bodies and, to a greater part, also regional measures, e.g., to reduce nutrient influx from adjacent water bodies. In conclusion, this approach can help practitioners to make more informed management decisions and foresee the effects of routes of socio-economic development.