Assessing ecosystem services provision using Bayesian Belief Network in Southern Europe marine forests

Abstract

Marine forests are vital ecosystems that underpin biodiversity and human well-being. Despite their ecological significance, these habitats remain underrepresented in policy frameworks and are increasingly threatened by anthropogenic pressures. Effective conservation and restoration efforts require a system-level understanding of the dynamic interactions between human activities and ecological components. We use Bayesian Belief Networks to simulate and predict changes in ecosystem service provision within southern European marine forests, with a focus on the continental Portuguese coast. Our approach integrates field measurements and expert knowledge to assess how shifts in anthropogenic drivers and biological components affect ecosystem functionality in data-limited settings. Major concerns include climate-driven herbivory, invasive species patterns, and their combined impact with other existing drivers. Nonetheless, results indicate restoration initiatives could enhance ecosystem services provision by up to 40 percentage points. Availability, reliability, and size of observations significantly influenced the choice between expert-based data and field measurements. The findings provide an initial step toward applying a Bayesian Network approach to assess ecosystem service provision in European marine forests and evaluating the potential benefits of restoration interventions. This work identifies key leverage points for enhancing ecosystem resilience and offers a decision-support tool to inform targeted conservation strategies across southern European coastal regions.