• A new interdisciplinary framework addresses biodiversity loss in the Triple Planetary Crisis. • It integrates deep-time data and AI to forecast biodiversity change under complex pressures. • It introduces functional biodiversity metrics linking species to ecosystem resilience. • A Hybrid Biodiversity Forecasting Engine combines ecological theory with explainable AI. • The approach connects biodiversity to economic planning, regulation, and corporate decision-making. Climate change, pollution, and biodiversity loss constitute the Triple Planetary Crisis , eroding the ecological foundations of economies, public health, and human wellbeing. Yet among these threats, biodiversity remains the least understood and least integrated into policy and decision-making. Monitoring efforts are fragmented and often fail to capture how multiple pressures—chemical pollution, invasive species, habitat degradation, eutrophication, and climate extremes—interact to drive non-linear ecosystem decline. This gap leaves societies poorly equipped to anticipate and mitigate ecological risks. We outline an interdisciplinary framework that combines deep-time ecological and environmental records with emerging forecasting tools to reconstruct long-term baselines and predict complex biodiversity responses to interacting stressors. We further identify pathways to embed these diagnostics into economic and governance systems, linking biodiversity directly to risk assessment, investment decisions, and regulatory frameworks. Together, these advances point toward a decision-support platform that enables governments, businesses, and communities to anticipate risks, evaluate interventions, and design strategies that align biodiversity protection with resilience in economies and societies
Zhou et al. (Sun,) studied this question.