Identifying restoration priorities: Exploring robust and dynamic strategies for improving ecosystem condition.

Conservation and restoration planning increasingly need to account for the potential for reduced feasibility and effectiveness of restoration actions under climate and socio-economic change. However, many large-scale spatial prioritisation and area-based planning approaches are structured around a single point in time or apply decisions in a stepwise manner, which limits their capacity to anticipate changing conditions. This limitation is reinforced by treating restoration only as a land use allocation problem, which masks within-class variation in ecosystem condition. Whilst accounting for this variation is challenging, it is essential for representing realistic ecosystem trajectories and identifying priority areas that remain robust over time across varied future scenarios.

In this work, we propose a multi-objective optimisation framework that incorporates spatially continuous ecosystem condition metrics into restoration prioritisation. The framework allows to explore potential trade-offs among restoration strategies and find solutions that account for ecosystem management goals such as cost efficiency and connectivity. By translating information on ecosystem condition into a range of feasible sets of interventions, the framework can support the adaptive allocation of actions across heterogeneous landscapes. Using a case study area in Switzerland, the analysis will examine how a prioritisation based on condition shapes the spatial distribution of priority areas.

Building on this foundation, ongoing research develops the framework toward a dynamic spatial optimisation model that represents multiple recovery pathways and potential ecosystem states. This extension aims to capture how restoration outcomes and priorities evolve under different assumptions of climate change and land-use dynamics and to explore how uncertainty in future conditions influences spatial decisions. Through the integration of approaches that allow for incremental improvements in components of ecosystem condition, this research seeks to provide a more realistic basis for restoration planning under uncertainty and to demonstrate how the inclusion of temporal ecosystem dynamics can shape conservation outcomes across short to long term time scales.