A critical review of methods, principles and progress for estimating the gross primary productivity of terrestrial ecosystems

Abstract

The gross primary productivity (GPP) of terrestrial ecosystems reflects the total amount of organic carbon assimilated by vegetation through photosynthesis per given unit of time and area, which represents the largest carbon flux in carbon budget and plays a fundamental part in the carbon cycle. However, challenges such as determining how to select appropriate methods to improve GPP estimation accuracy at the regional/global scale remain. Therefore, it is of great importance to comprehensively review the research progress on the methods for estimating the GPP of terrestrial ecosystems and to summarize their flaws, merits and application fields. In this study, we reviewed studies of GPP estimation at different spatiotemporal scales, and systematically reviewed the principles, formulas, representative methods (Ground observations, Model simulations, SIF based GPP, and NIRv based GPP) at different scales and models (Statistical/Ecological process/Machine learning/Light use efficiency models), as well as the advantages and limitations of each research method/models. A comprehensive comparison of GPP research methods was performed. We expect that this work will provide some straightforward references for researchers to further understand and to choose appropriate models for assessing forest ecosystem GPP according to the research objectives and area. Thus, critical and effective GPP estimation methods can be established for the terrestrial carbon cycle, carbon neutralization accounting and local carbon emission reduction policy formulation and implementation.