Spatial–Temporal Changes and Prediction of Carbon Storage in the Tibetan Plateau Based on PLUS-InVEST Model

Abstract

The changes in the recent and future spatial–temporal patterns of carbon storage of the Tibetan Plateau and its dominant factors in different periods were unclear, and were conducive to optimizing the spatial layout of land. Exploring the spatial and temporal changes in terrestrial ecosystem carbon storage and their influencing factors during a long study period had important theoretical and practical significance for achieving the goal of carbon neutrality. In this study, the Integrated Valuation of Ecosystem Services and Trade-offs model (InVEST) was used to analyze the changes in carbon storage based on vegetation-type data during 2000–2020. The Path-generating Land-Use Simulation model (PLUS) was then used to predict the spatial distribution of carbon storage in the Tibetan Plateau in 2030 and 2060 under inertial development, farmland protection and ecology priority scenarios. The results showed that: (1) The degradation of vegetation types reduced the carbon storage during the study period. During 2000–2020, the desert shrub and non-vegetation area expanded by 63.21% and 13.35%, respectively, while the deciduous scrub, mixed forest and low coverage grassland decreased accordingly. The carbon storage of the Tibetan Plateau showed a decreasing trend by 0.37 × 106 t. (2) The spatial distribution patterns of carbon storage were consistent with that of the vegetation types. (3) In 2030 and 2060, under the constraint of the ecological priority development, the reduction in carbon storage was the smallest, at 0.01 × 106 t and 0.16 × 106 t, respectively. Under the constraint of the inertial development, carbon storage had the largest reduction, at 0.12 × 106 t and 0.43 × 106 t, respectively. (4) During 2000–2020, the dominant single factor that had the greatest impacts on the changes in carbon storage was FVC (vegetation coverage), with q values of 0.616, 0.619 and 0.567, respectively. The interactive dominant effects were mainly nonlinear enhancement and double-factor enhancement. The interactive dominant factors that had the greatest impact were FVC and the DEM (Digital Elevation Model), with q values of 0.94, 0.92 and 0.90, respectively. Therefore, ecological land with a high FVC should be protected and the expansion of non-vegetation areas should be restricted in future planning to improve the carbon storage level of the Tibetan Plateau and achieve the goal of carbon neutrality.