Simulating multiple scenarios of carbon stocks for driving mechanisms using MOP-PLUS-InVest model

Carbon stock is one of the most important components of terrestrial ecosystems. It is of great significance for the spatial and temporal distribution and driving mechanisms in the regional sustainable agriculture. Existing studies have focused mainly on the historical and current carbon stocks. But it is still lacking on the future carbon stocks, especially under multiple scenarios of land use. In this study, MOP-PLUS coupled model was constructed to quantitatively predict the spatial and temporal distribution patterns of land use under four scenarios, namely, the Natural Development Scenarios (NDS), Ecological Protection Scenarios (EPS), Economic Development Scenarios (EDS), and Sustainable Development Scenarios (SDS) of the Central Yunnan Urban Agglomeration (CYUA). The carbon stock was then simulated and assessed using Integrated Valuation of Ecosystem Services and Trade-offs (InVEST). The spatial and temporal evolution of carbon stock was characterized using visualization mapping. Finally, the Optimal Parameters Geographical Detector (OPGD) was used to explore the driving mechanism for the spatial differentiation of carbon stocks. The results show that: 1) The carbon stock lost 1.95×10⁷ t cumulatively from 2000 to 2020, particularly the serious from 2010 to 2020, due to the accelerated urbanization; Furthermore, the grassland shared the highest loss of carbon stock among different types of land use; 2) There was the continuous growth trend of construction land in all four scenarios, whereas, the carbon stock decreased in the future scenario. Among them, the ecological protection scenario showed the smallest decrease in the carbon stock, with a decrease of 2.84×10⁶ t, whereas, the economic development scenario showed the largest decrease, with a decrease of 1.678×10⁷ t. There were the similar spatial distributions of carbon stock under the four scenarios. The high-value areas were concentrated mainly in the western and southern parts of the study area, whereas, the low-value areas were located mainly in the central; 3) Carbon stock was driven by a variety of influencing factors, such as the normalized vegetative cover. Among them, the Normalized Vegetation Index and the Nighttime Lighting Index were the dominant factors in the spatial variability of carbon stock, while the natural and social factors shared the different degrees of influence on the spatial variability of carbon stock, and human activities played a crucial role in carbon stock changes. The finding can provide a theoretical basis for the carbon peaking and carbon neutrality in the sustainable development of the urban agglomeration in central Yunnan of China.