Accelerating Biodiversity And Ecosystem Reporting
Microsoft
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Abstract: This white paper introduces a scalable, cost-effective framework for biodiversity and ecosystem service reporting tailored for companies responding to emerging nature-related disclosure regulations such as CSRD and TNFD. It formalizes five core indicators: ecosystem conversion, ecosystem management, extent/condition/connectivity, invasive species, and species status. Leveraging Earth observation (EO) and artificial intelligence (AI), it demonstrates how remote sensing, camera trap data, and geospatial modeling can substitute for costly field surveys. Case examples include Amazonian biodiversity tracking and AI-powered species detection using PlanetScope satellites. The report highlights data standardization, metric attribution, and materiality mapping, enabling companies to align ecosystem dynamics with financial decision-making. A technical appendix maps EO methods to sustainability reporting criteria. The paper positions EO-AI integration as essential for evidence-based restoration, net-positive nature targets, and policy-aligned ecosystem governance.