Climate change poses escalating challenges across the globe, including intensifying heatwaves, erratic rainfall, and accelerating sea level rise. The land sector plays a pivotal role in both the vulnerability to and mitigation of these impacts: land-use emissions account for about 22% of global greenhouse gases, surpassing those from electricity, transport, or industry. Despite this significance, the responses and feedbacks of large-scale land-use changes associated with nature-based mitigation strategies, such as forestation and bioenergy expansion, remain poorly understood. This presentation will discuss the integration of Earth system models, hydrological models, ecosystem demography models, integrated assessment models, field observations, remote sensing datasets, and modern optimization and ML/AI techniques to evaluate ecosystem services, resilience, robustness, and risks associated with diverse nature-based climate solutions, with the goal of unlocking land-based mitigation potential for climate adaptation, decarbonization, and sustainable development.

nature-based climate solutions,earth system modeling,AI