Land

This study is situated at the critical stage of comprehensive implementation of China’s territorial spatial planning system, addressing the strategic need for planning evaluation and optimization. We innovatively construct a Computable General Equilibrium Model for China’s Territorial Spatial Planning (CTSPM-CHN) that integrates dual factors of construction land costs and energy consumption costs. Through designing two policy scenarios of rigid constraints and structural optimization, we systematically simulate and evaluate the dynamic impacts of different territorial spatial governance strategies on macroeconomic indicators, residents’ welfare, and carbon emissions, revealing the multidimensional effects and operational mechanisms of territorial spatial planning policies. The findings demonstrate the following: First, strict implementation of land use scale control from the National Territorial Planning Outline (2016–2030) could reduce carbon emission growth rate by 12.3% but would decrease annual GDP growth rate by 0.8%, reflecting the trade-off between environmental benefits and economic growth. Second, industrial land structure optimization generates significant synergistic effects, with simulation results showing that by 2035, total GDP under this scenario would increase by 4.8% compared to the rigid constraint scenario, while carbon emission intensity per unit GDP would decrease by 18.6%, confirming the crucial role of structural optimization in promoting high-quality development. Third, manufacturing land adjustment exhibits policy thresholds: moderate reduction could lower carbon emission peak by 9.5% without affecting economic stability, but excessive cuts would lead to a 2.3 percentage point decline in industrial added value. Based on systematic multi-scenario analysis, this study proposes optimized pathways for territorial spatial governance: the planning system should transition from scale control to a structural optimization paradigm, establishing a flexible governance mechanism incorporating anticipatory constraint indicators; simultaneously advance efficiency improvement in key sector land allocation and energy structure decarbonization, constructing a coordinated “space–energy” governance framework. These findings provide quantitative decision-making support for improving territorial spatial governance systems and advancing ecological civilization construction.

Diurnally asymmetric warming under global climate change is reshaping terrestrial ecosystems, with important implications for vegetation productivity, biodiversity, and carbon sequestration. However, the mechanisms underlying the delayed and differentiated vegetation responses to daytime and nighttime warming, particularly under interacting precipitation regimes, remain insufficiently understood, limiting accurate assessments of ecosystem resilience under future climate scenarios. Clarifying how vegetation responds dynamically to asymmetric temperature changes and precipitation, including their lagged effects, is therefore essential. Here, we analyzed the spatiotemporal evolution of growing-season Normalized Difference Vegetation Index (NDVI) across the Yellow River Basin from 2001 to 2022 using Theil–Sen median trend estimation and the Mann–Kendall test. We further quantified the lagged responses of NDVI to daytime maximum temperature (Tmax), nighttime minimum temperature (Tmin), and precipitation, and identified their dominant controls using partial correlation analysis and an XGBoost–SHAP framework. Results show that (1) growing-season climate in the YRB experienced pronounced diurnal warming asymmetry: Tmax, Tmin, and precipitation all increased, but Tmin rose substantially faster than Tmax. (2) NDVI exhibited an overall increasing trend, with declines confined to only 2.72% of the basin, mainly in Inner Mongolia, Ningxia, and Qinghai. (3) NDVI responded to Tmax, Tmin, and precipitation with distinct lag times, averaging 43, 16, and 42 days, respectively. (4) Lag times were strongly modulated by topography, soil properties, and hydro-climatic background. Specifically, Tmax lag time shortened with increasing elevation, soil silt content, and slope, while showing a decrease-then-increase pattern with potential evapotranspiration. Tmin lag time lengthened with elevation, soil sand content, and soil pH, but shortened with higher potential evapotranspiration. Precipitation lag time increased with soil silt content and net primary productivity, decreased with soil pH, and varied nonlinearly with elevation (decrease then increase). By explicitly linking diurnal warming asymmetry to vegetation response lags and their environmental controls, this study advances process-based understanding of climate–vegetation interactions in arid and semi-arid regions. The findings provide a transferable framework for improving ecosystem vulnerability assessments and informing adaptive vegetation management and conservation strategies under ongoing asymmetric warming.

The Yellow River Basin (YRB), a typical river system facing the challenge of balancing ecological conservation and economic development, offers valuable insights for global sustainable watershed governance through its forestry green transformation. Based on panel data from nine provinces in the basin from 2005 to 2022, this study constructs an efficiency evaluation indicator system for forestry green development. This system incorporates four inputs (labor, land, capital, and energy), two desirable outputs (economic and ecological benefits), and three undesirable outputs (wastewater, waste gas, and solid waste). By systematically integrating the undesirable outputs-based super-SBM model and the global Malmquist–Luenberger (GML) index, this study provides an assessment from both static and dynamic perspectives. The findings are as follows. (1) Forestry green development efficiency showed fluctuations over the study period, with the basin-wide average remaining below the production frontier. Spatially, it exhibits a pattern of “downstream > upstream > midstream”. (2) The average GML index is 0.984 during the study period, representing an average annual decline in forestry green total factor productivity of 1.6%. The growth dynamics transitioned from a stage dominated solely by technological progress to a dual-driver model involving both technological progress and technical efficiency. (3) The drivers of forestry green total factor productivity growth in the basin show profound regional heterogeneity. The downstream region demonstrates a synergistic dual-driver model of technical efficiency and technological progress, the midstream region is trapped in “dual stagnation” of both technical efficiency and technological progress, and the upstream region differentiates into four distinct pathways: technology-driven yet foundationally weak, efficiency-improving yet technology-lagged, endowment-advantaged yet transformation-constrained, and condition-constrained with efficiency limitations. The assessment framework and empirical findings established in this study can provide empirical evidence and policy insights for basins worldwide to resolve the ecological-development dilemma and promote forestry green transformation.