The Grain-for-Green Project (GFGP), one of the largest ecological restoration projects in China, has made a significant contribution to carbon neutrality. However, the quantitative contribution to climate change and the driving forces of the carbon sequestration of retired farmlands remains unclear. To analyze the carbon dynamics of the retired farmlands and their driving forces, GlobeLand30 databases were used to identify retired farmlands from 2001 to 2020; in addition, net primary productivity (NPP) of the identified lands was estimated with the Carnegie–Ames–Stanford Approach (CASA). Results showed that 131,298 km² of farmlands were retired from 2001 to 2010 (L01–10), and 130,225 km² were retired from 2011 to 2020 (L11–20). The largest areas of retired farmlands were South Central China (24%) in L01–10 and Northwest China (22%) in L11–20. The annual NPP increment of retired farmlands was the highest and most significant in Southwest China (26,455–28,783 GgC·year⁻¹ for retired farmlands in L01–10 and 21,320–23,303 GgC·year⁻¹ in L11–20). In this study, NPP had significantly positive correlations with temperature and precipitation as well as significant constraint relationships with rural population density and animal husbandry output value. The findings could provide suggestions for the further implementation of the GFGP and other restoration projects.

Biofuel is encouraged because of its low impact on climate change. A new framework was developed to accurately assess the climate change impacts (CCI) of biofuel by integrating the atmospheric carbon cycle model and vegetation carbon dynamic models. Forests with different growth rates (fast, medium, slow) and three collection intensities (71%, 52%, 32%) of logging residues were presumed to test the performance of this framework. The CCI of biofuel was analyzed under two functional units: 1 GJ of biofuels and 1 ha of forests to supply biofuels. According to this study, increasing the forest growth rate could decrease the CCI in both functional units. Increasing the collection intensity could decrease the CCI of 1 GJ of biofuel but increase the CCI of 1 ha of forest land (unless the impacts were negative in fast-growth forests with high and medium collection intensities). Producing bioethanol resulted in a lower CCI (−3.1–67.7 kg CO₂ eq/GJ) compared to bio-diesel (29.3–94.7 kg CO₂ eq/GJ). Hence, collecting all available logging residues (without inhibiting forest regrowth) to produce low CCI biofuels such as bioethanol was found to be the optimal option for achieving high mitigation effects.

Leaf C:N:P stoichiometry provides a functional link between plant nutrient composition and environmental adaptation. However, whether widely distributed tree species maintain consistent leaf stoichiometric patterns across contrasting vegetation zones remains unclear. Here, we investigated the leaf C:N:P stoichiometry of Quercus variabilis, a widely distributed tree species in China, across the subtropical evergreen broad-leaved forest zone (SEF) and the warm-temperate deciduous broad-leaved forest zone (WDF). We aimed to clarify between-zone differences in leaf stoichiometric traits and the role of climate and soil constraints in shaping vegetation-zone-dependent stoichiometric variation. Our results showed that leaf C:N:P stoichiometry of Q. variabilis differed between the SEF and WDF, with significant differences detected only for leaf N and leaf C:N. Overall, leaf C varied little across zones (CV = 3.13–3.42%), leaf N and leaf C:N showed moderate variation (CV = 10.07–13.26%), whereas leaf P, leaf C:P, and leaf N:P showed greater variability (CV = 33.28–39.93%). Environmental analyses further indicated contrasting patterns between zones: leaf stoichiometry in the SEF was jointly associated with climate and soil factors and showed a positive leaf C–N relationship, whereas that in the WDF showed a stronger soil association and a negative leaf N–P relationship. These findings suggest that Q. variabilis may adjust its leaf stoichiometry in a zone-dependent manner in response to contrasting climate and soil conditions. This study provides a theoretical basis for understanding nutrient-use strategies and environmental adaptation of widely distributed tree species under heterogeneous climate and soil conditions.