No ‘au doigt mouillé’: A Framework for Optimizing Barrier Prioritization Under Contrasting Governance and Cost Scenarios

ABSTRACT Restoring river connectivity through barrier removal is a key objective of contemporary river restoration policies, including the EU Nature Restoration Regulation. However, prioritizing which barriers to remove remains challenging because of limited resources, fragmented governance and uncertainty around costs and feasibility. While spatial optimization tools are increasingly applied to river restoration, few studies explicitly examine how alternative cost structures and governance constraints influence prioritization outcomes. Here, we present a transferable spatial optimization framework for prioritizing the removal of freshwater barriers under contrasting cost and governance scenarios. Using Marxan, we compare seven scenarios that vary in their representation of monetary, technical and opportunity costs, as well as governance constraints. We demonstrate the approach using Vallée de la Semois National Park (Belgium) as a case study, where 420 barriers were identified across the river network. Scenarios incorporating opportunity costs selected fewer barriers (79) but produced longer, more spatially cohesive restored river stretches (average 7 km), whereas monetary‐cost scenarios selected more barriers (up to 178) but resulted in shorter, more fragmented connectivity gains (average 3–4 km). Despite these differences, several river segments were consistently selected across all scenarios, indicating robust, no‐regret restoration opportunities. Our findings demonstrate that no single prioritization strategy can simultaneously minimize costs, maximize connectivity and satisfy governance constraints. Instead, explicitly testing alternative assumptions through spatial optimization supports more transparent, strategic and implementable restoration planning. The proposed framework is readily transferable to other river systems and policy contexts where connectivity restoration must navigate ecological, economic and institutional trade‐offs.