Maximizing Nature‐Based Solutions Using Artificial Intelligence to Align Global Biodiversity, Climate, and Water Targets

Abstract Nature‐based Solutions (NbS) encompass a spectrum of conservation and restoration actions aimed at improving biodiversity, climate, and water outcomes. Considerable research exists that focuses on prioritizing either conservation or restoration, or specific environmental outcomes. Yet, there is a need to develop integrated frameworks that align multiple outcomes and enable comprehensive environmental and economic assessments. Here, we present an integrated framework leveraging an AI agent that interprets species' habitat and connectivity changes along with climate and water co‐benefits to select optimal conservation and restoration priority areas. We implement this framework through scenarios maximizing biodiversity protection with ecological integrity, carbon storage, and water co‐benefits to achieve Canada's 30 × 30 conservation and restoration targets. Our results suggest that prioritizing the protection of threatened biodiversity and irrecoverable carbon storage would optimally enhance existing Protected Areas outcomes and conserve 30% of lands by 2030. However, effectively restoring 30% of degraded land will require targeted actions in existing natural and transformed ecosystems. The assessment of current anthropogenic pressures suggests that conservation and restoration actions may enhance climate resilience for forestry in natural lands and potentially benefit agricultural production and public health in transformed lands. Moreover, the mining sector represents the largest growing pressure on both conservation and restoration priorities in the upcoming decade. Overall, this integrated framework reveals strategic conservation and restoration priorities to align environmental targets, while identifying opportunities to coordinate NbS interventions across sectors.