Wetlands provide important ecosystem services, such as water conservation, biodiversity protection, and carbon sequestration. The Zoige alpine wetland is the largest high-altitude swamp in the world and plays a critical role in regional ecological balance and climate change. However, little is known about the fate of its soil organic carbon (SOC) storage. In this study, we estimated the degradation status of the wetland over the past 35 years and used machine learning to investigate the dynamics and driving factors of SOC at different soil depths of the Zoige wetland in 1985, 2000, and 2020. We also simulated the future SOC balance under different scenarios. The results showed that the area of Zoige wetland has degraded by 378.71 km² in the past 35 years. Increased precipitation and solar radiation offset the adverse effects of global warming, making the soil act as a carbon sink in the past 35 years. The total SOC storage of the wetland soils in 1985, 2000, and 2020 was estimated to be 2.03 Pg, 2.05 Pg, and 2.21 Pg, respectively, with 46.95% of SOC distributed in the subsoil layers. Climate change was the most important driving factor controlling the SOC storage of the Zoige wetland, explaining 51.33% of the SOC changes in the soil. Temperature change was always the most important factor controlling wetland SOC, and precipitation had a greater impact on the topsoil. Under the temperature control targets of 1.5 °C and 2 °C, the SOC pool of the Zoige wetland will decrease by 60.21 Tg C and 69.19 Tg C, respectively. Under scenarios of a 10% and 20% increase in precipitation, the wetland soil will accumulate an additional 46.53 Tg C and 118.89 Tg C, respectively. The study results provide important references for the sustainable management of the Zoige wetland under the background of global climate change.

China’s prioritization of food self-sufficiency is likely to reconfigure global agricultural trade and associated GHG emissions, yet its climate compatibility remains uncertain. Here, we employ a well-established food system integrated assessment model (GLOBIOM-China) to quantify how self-sufficiency targets alter domestic and trade-embodied GHG emissions through 2060. Our findings indicate that solely increasing food self-sufficiency rate would reduce China’s trade embodied GHG emissions by 50% (107 Mt CO2-eq yr-1), but increase domestic emissions by 7% (55 Mt CO2-eq yr-1). This results in a net reduction of 52 Mt CO2-eq yr-1 in overall emissions while intensifying domestic land competition. We uncover a market-mediated mitigation feedback that higher soybean self-sufficiency raises domestic feed costs, acting as an implicit constraint that limits the expansion of the high-emitting livestock sector. This upstream intervention delivers emission reduction elasticities comparable to directly targeting ruminant production. However, to prevent such passive mitigation, self-sufficiency must be coupled with production efficiency gains and dietary shifts. This combined pathway reduces overall GHG emissions by 211 (162-259) Mt CO2-eq yr-1 (20%) by 2060, aligning national food security with global climate targets.

Purpose: Using Landsat OLI remote sensing images in the two phases of 2015 and 2020. Taking Nanjing as the research area. Based on RS and GIS technology, adopting maximum likelihood method for supervised classification, extracting and producing a land use classification map for the two phases of Nanjing from 2015 to 2020. And further, using the land use change transfer matrix to analyze and summarize the characteristics and laws of the dynamic changes of land use in Nanjing. Result: From 2015 to 2020 in Nanjing, the overall land use change showed “two reductions and four increases”. The area of arable land and bare land decreased by 729.46 km², 332.31 km²; the area of u rban construction land, woodland, grassland, and water area increased by 448.39 km², 231.67 km², 216.87 km² and 164.84 km². And each land use type has a different amount of area conversion. Conclusion: The analysis of land use change based on Landsat remote sensing image research area can effectively predict the change trend of regional land use. It can provide a basis for the research on the driving forces of land use change in the region, and it can also provide decision-making support for the formulation of land-related policies in the region.

China’s demand for wood and forest products continues to grow with the booming papermaking industry and residence use, leading to a dramatic increase in imports of wood products. Meanwhile, woody biomass for bioenergy with carbon capture and storage (BECCS) has been projected as a pivotal negative emission strategy in meeting climate goals in the future. However, the imposition of natural forest ban and the pursuit of future climate targets may create additional gaps in the availability of forestry products. Here, we use the GLOBIOM-China model to assess the impacts of diverse woody biomass demands, national programs for afforestation and forest plantation, and management measures in China under climate targets. The results indicate an increase in domestic roundwood consumption by 20.3~50.3 million m3 in 2050 under 1.5℃ scenario compared to that under the baseline scenario (BAU) without BECCS demand, with increased proportion for wood fuel uses and less for pulp and sawn wood consumption. Domestic production fails to meet the energy and material demands for woody products by 2060, necessitating an additional import of 63~144 million m3 of roundwood compared with the BAU, approximately accounting for 29~46% of domestic production. Enhancing logging potential can help prevent the continued transformation of natural forests into managed forests and forest plantations on cropland, as well as reduce roundwood imports by 55-89 million m3, when compared to the management of forests under normal increments. Moreover, such productivity enhancement could contribute to an additional sequestration in forestry of 0.1-1.26 Gt CO2 by 2060. This study underscores the imperative for enhanced forestry system management in China to effectively meet its ambitious climate commitments.

As the most active component of soil TOC (Total Organic Carbon), DOC (Dissolved Organic Carbon) is either adsorbed by the soil and used by plants or transported by soil water into the water column, where it participates in the broader carbon cycle. As a substantial "mobile carbon pool" in soils, its leaching process is an essential pathway for the loss of soil TOC. This paper analysed the investigated the leaching characteristics of soil DOC by simulating leaching in an indoor soil column based on the spatial distribution of soil TOC and DOC contents in order to reveal the leaching and migration characteristics of soil DOC at different depths and its main influencing factors. The DOC content of soil leachate varies somewhat under conditions such as PH and soil phosphorous content. However, the overall trend is that the DOC content of soil leachate generally increases with the depth of the soil layer. The DOC content in the soil leachate gradually decreased with increasing leaching time. In the absence of exogenous carbon recharge, the loss of TOC from the upper layers of the soil was significantly more remarkable due to the prolonged leaching. In addition, soil TOC loss declined after leaching and decreased significantly with increasing soil depth. Because the soil DOC is adsorbed and trapped in other layers during leaching, the DOC in the upper layer was always lost during the leaching test. The experiments used highly concentrated DOC solutions as drench solutions. According to the analysis of the intensity of the fluorescence centres of each soil layer in the three-dimensional fluorescence pattern of the drench solution of each soil layer, the ability of different soil layers to adsorb and retain organic matter of different fractions differs. In addition, the selected soil layers planted with Saline seepweed show a general decreasing trend in the ability to adsorb and retain organic matter as the depth increases.