Establishing an Evidentiary Basis for Nature-Based Climate Solutions | Novick et al. 2024

An image of the Niger River in Western Africa flowing through a sea of sand. Source: USGS via Unsplash

Nature-based climate solutions (NbCS) are considered an important component of the world’s response to our climate crisis. Nations, corporations, and nonprofits are increasingly investing in NbCS. Yet a critical challenge has emerged – how do we rigorously quantify and verify their long-term climate mitigation potential? Without a robust scientific foundation, the credibility and durability of ambitious NbCS programs could be undermined by failure to deliver tangible climate impact insights. In a recent PNAS perspective, Kimberly A. Novick et al. outline a framework to establish this much-needed evidentiary basis. Their strategy centers on three key principles: prioritizing open data sharing, creating a hierarchical, multiscale monitoring framework, and accurately mapping land cover and use.

On open data sharing, Novick et al. suggest that all datasets, code, and protocols should be freely accessible to drive scientific progress and ensure equivalency of carbon credits across systems. While protecting privacy for private lands, alternatives should be explored to enable the sharing of precise coordinates from public lands, allowing researchers to verify carbon budgets against high-resolution satellite data. Novick et al. also propose a hierarchical monitoring network integrating observations across scales – from eddy covariance flux towers providing ecosystem-level greenhouse gas flux data, to soil/biomass inventories and remote sensing. Locating new monitoring plots near flux towers could create "gold-standard" datasets for comprehensively assessing NbCS impacts on carbon pools, fluxes, and drivers. This approach would shed light on mechanisms, benchmark models, and certify verification protocols. Lastly, Novick et al. also stress the importance of accurate land cover mapping:  integrating aerial surveys, forest inventories, satellite data, and machine learning to monitor disturbances and management practices. They recommend consistent national-scale databases documenting historic activities coupled with tree-ring data to enhance temporal resolution. By prioritizing open data sharing, this multi-scale monitoring approach aims to build a robust scientific foundation for implementing effective NbCS, reducing risks of failures and fostering public confidence.