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AI has been proposed as an important tool to support several efforts relatedto nature-based climate solutions such as the detection of wildfires thataffect forests and vegetation-based offsets. While this and other use-casesprovide important demonstrative value of the power of AI in climate changemitigation, such efforts have typically been undertaken in silos, withoutawareness of the integrative nature of real-world climate policy-making. Inthis paper, we propose a novel overarching framework for AI-aided integratedand comprehensive decision support for various aspects of nature-based climatedecision-making. Focusing on vegetation-based solutions such as forests, wedemonstrate how different AI-aided decision support models such as AI-aidedwildfire detection, AI-aided vegetation carbon stock assessment, reversal riskmitigation, and disaster response planning can be integrated into acomprehensive framework. Rather than being disparate elements, we posit thatthe exchange of data and analytical results across elements of the framework,and careful mitigation of uncertainty propagation will provide tremendous valuerelative to the status-quo for real-world climate policy-making.

Towards AI-driven Integrative Emissions Monitoring & Management for Nature-Based Climate Solutions