Gross primary productivity of terrestrial ecosystems: a review of observations, remote sensing, and modelling studies over South Asia

• Published in: Theoretical and applied climatology 2024-09, Vol.155 (9), p.8461-8491
• Main Authors: Pandey, Varsha, Harde, Sakshi, Rajasekaran, Eswar, Deb Burman, Pramit Kumar
• Format: Article
• Language: English
• Subjects: Agricultural land; Anthropogenic factors; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Atmospheric Sciences; Boreal ecosystems; Carbon; Carbon emissions; Carbon fixation; Carbon sequestration; Carbon sinks; Climate change; Climate change mitigation; Climatology; Datasets; Earth and Environmental Science; Earth observations (from space); Earth Sciences; Ecosystem management; Ecosystems; Eddy covariance; Emissions control; Environmental conditions; Environmental impact; Environmental management; Glass; Grasslands; Ground stations; Human influences; Land cover; Management methods; MODIS; Parameter modification; Photosynthesis; Primary production; Productivity; Remote sensing; Review; Reviews; Satellite data; Satellite observation; Satellites; Spatiotemporal data; Spectroradiometers; Terrestrial ecosystems; Vegetation; Waste Water Technology; Water Management; Water Pollution Control
• ISSN: 0177-798X; 1434-4483
• DOI: 10.1007/s00704-024-05158-4

The terrestrial ecosystem stores a huge amount of carbon in biomass and acts as a major carbon sink. Gross primary productivity (GPP) measures the carbon assimilation rate in terrestrial ecosystems. Accurate quantification and spatiotemporal analysis of GPP have become the essential indicators of various management, policy developments, and restoration activities in recent decades with the installation of new ground stations, development of robust models, and use of Earth Observation satellite data. The model-estimated and satellite data-derived GPP values greatly differ from ground observations due to model structure and approach, input driving data, coefficients and parameters, and various assumptions. Consequently, considerable ambiguity prevails among datasets and their benchmarking. Moreover, the productivity of ecosystems is regulated by physiological traits coupled with the local environmental conditions. This review provides an overview of the environmental and anthropogenic variables that regulate productivity and pose challenges in GPP estimation and evaluation of the available GPP products. It also evaluates the various available GPP datasets/ products and estimation methods/ models and compares the ecosystem productivity in broad natural and human-modified ecosystems in South Asia. Moreover, this study includes a case study on evaluating five globally available GPP products with variable spatiotemporal resolutions, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), the Vegetation Photosynthesis Model (VPM), the Global Land Surface Satellite (GLASS), Global OCO-2-based SIF product (GOSIF), and the Penman-Monteith-Leuning (PML) in three major land cover type of South Asia (forest, cropland, and grassland) comparing with eddy covariance (EC) flux tower data. Results showed a better performance of GOSIF and GLASS data than other GPP products. The study aims to provide an overview of the prevailing environmental conditions and carbon sequestration in different ecosystems and assist in developing sustainable landscape management strategies to reduce carbon emissions and mitigate climate change impact. Article highlights • A critical review of the methods employed for GPP estimation and their limitations. • Impact of various management practices, extreme events, and climate change on GPP. • Comparison among available GPP datasets.