Principles for satellite monitoring of vegetation carbon uptake - Prentice,IC; Balzarolo,M; Bloomfield,KJ; Chen,JM; Dechant,B; Ghent,D; Janssens,IA; Luo,X; Morfopoulos,C; Ryu,Y; Vicca,S; van,Hoolst R (Nature Reviews Earth & Environment, 2024)
Remote sensing-based numerical models harness satellite-borne measurements of light absorption by vegetation to estimate global patterns and trends in gross primary production (GPP)—the basis of the terrestrial carbon cycle. In this Perspective, we discuss the challenges in estimating GPP using these models and explore ways to improve their reliability. Current models vary substantially in their structure and produce differing results, especially as regards temporal trends in GPP. Many models invoke the light use efficiency (LUE) principle, which links light absorption to photosynthesis and plant biomass production, to estimate GPP. But these models vary in their assumptions about the controls of LUE and typically depend on many, poorly known parameters. Eco-evolutionary optimality principles can greatly reduce parameter requirements, and can improve the accuracy and consistency of GPP estimates and interpretations of their relationships with environmental drivers. Integrating data across different satellites and sensors, and utilising auxiliary optical band retrievals, could enhance spatiotemporal resolution and improve models' ability to detect aspects of vegetation physiology, including drought stress. Extending and harmonizing the eddy-covariance flux tower network will support systematic evaluation of GPP models. Enhancing the reliability of GPP and biomass production estimates will better characterise temporal variation and improve understanding of the terrestrial carbon cycle’s response to environmental change.