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• The 57.00% of the Yangtze River Economic Belt area exhibited a significant increase in annual NPP. • The response of NPP on climate factors was nonlinear, with greater sensitivity to temperature. • The impact of topographic factors on NPP changes had a threshold effect. Net primary productivity (NPP) of terrestrial ecosystems serves as a crucial carbon sink, playing a significant role in mitigating climate change. This study, focusing on the Yangtze River Economic Belt (YREB), a key area for both economic development and ecological conservation in China, evaluates the temporal and spatial changes in regional NPP and its responses to climatic factors against the backdrop of global change. Utilizing long-term NPP and meteorological grid data from 1981 to 2017, we analyzed the annual change patterns of NPP and its linear and nonlinear responses to climatic factors using copula functions. Our findings indicate that 57.00 % of the YREB has experienced a significant increase in NPP, with the most substantial decreases observed in Shanghai and its surrounding areas (P < 0.05). Temperature emerged as the primary climatic driver, positively correlating with NPP changes in over half of the study area (P < 0.05). Moreover, the nonlinear response of NPP to temperature and precipitation underscores the complex interactions between these factors, revealing a sensitivity to temperature variations that surpasses that to precipitation. The study also highlights the influence of solar radiation and topographic factors, with a significant positive correlation between NPP and solar radiation observed in 15.85 % of the area (P < 0.05). The practical significance of these findings lies in their implications for regional ecological management and climate resilience strategies. The positive correlation between temperature and NPP underscores the potential for targeted temperature management to optimize carbon sequestration across the YREB. Furthermore, the identified nonlinear responses and the role of solar radiation and topography in influencing NPP offer valuable insights for the formulation of adaptive strategies that enhance ecosystem productivity and contribute to achieving carbon neutrality goals. By elucidating the dynamics of NPP in response to a range of environmental factors, this study provides a foundation for informed decision-making in ecological conservation and climate change mitigation efforts within the YREB and similar regions globally. [ABSTRACT FROM AUTHOR]

• The Carbon sink capacity of a typical ecotypic county was precisely estimated. • STARFM was employed to estimate interannual NEP at county scale. • The NEP dataset at a 30 m grid scale from 2000 to 2020 was generated. • Spatio-temporal dynamics of NEP in ecotype county were grasped. Net ecosystem productivity (NEP) serves as a pivotal metric for quantitatively elucidating the carbon sink function of terrestrial ecosystems. As a prototype county for the development of an ecological civilization in China, the quantitative estimation of the ecotypic county's ecosystem carbon sink capacity holds immense significance in comprehending the carbon cycle and facilitating the sustainable advancement of regional ecosystems. This study undertook the estimation of NEP in Wuning County from 2000 to 2020, employing a fusion of multi-source remote sensing data, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), the improved Carnegie-Ames-Stanford Approach model, and the soil respiration model. Furthermore, we delved into the differences in NEP across various types of land cover. In addition, we employed the Theil-Sen Median trend analysis and Mann-Kendall test to discern the spatio-temporal trends of NEP. The findings indicated the following: (1) The downscaled NDVI generated by STARFM exhibited a remarkable consistency with Landsat NDVI overall (R 2 > 0.95, P < 0.01, 0 < RMSE < 0.1). (2) The gross NEP from 2000 to 2020 in the study area ranged from 542.78 to 720 Gg C, with a multi-year average NEP of 183.84 g C m−2 yr−1. The simulated NEP demonstrated higher accuracy when compared to the measured data (R 2 = 0.79, P < 0.01). (3) The NEP exhibited a spatial pattern characterized by lower values in the central area and higher values in the north and south. Approximately 89.60 % of the total area demonstrated an increase in NEP, with woodland acting as the primary contributor, while 4.50 % of the total area displayed a decreasing trend, predominantly due to the expansion of built-up land. (4) Notable variations in NEP existed among different types of land cover. In terms of vegetation types, the annual average NEP ranked as follows: woodland > grassland > cropland. The application of STARFM has provided valuable insights into the methodology for precise delineation of spatio-temporal dynamics of NEP at the county scale. The outcomes of this study have furnished support for implementing climate change mitigation strategies in ecologically-oriented counties and the bottom-up promotion of China's carbon peaking and carbon neutrality goals. [ABSTRACT FROM AUTHOR]

Carbon emission reduction in China matters to global climate change mitigation. China has been experiencing extensive land changes, which profoundly influence terrestrial ecosystem carbon storage (TECS) and carbon emissions. Scholars have predicted influences of land changes on TECS in China with scenarios obtained from global integrated assessment models (IAMs), which lack national details. Moreover, universally existing variations in land-use intensity have not been considered when estimating influences on TECS. This study simulated changes of land-use intensity of China from 2000 to 2050 using CLUMondo under China-specified policies for sustainable development modeled by a national IAM named Threshold21-China. We proposed a more precise TECS estimation method by distinguishing land-vegetation and land-soil types. Results demonstrated that under scenario with preceding policies, the total TECS can increase by 865.5 Tg C from 2000 to 2050. Through implementing preceding policies, TECS loss by conversions from cultivated land to artificial surfaces can decline by 82 Tg C, and new TECS accumulated by increased and densified forests can increase by 73 Tg C. Mountainous and rapidly urbanizing regions are sensitively influenced and need more restrict land change management policies. This study demonstrates the significance of sustainable development policies for TECS conservation and indicates specific critical regions. • Introducing national IAM into land change simulation. • Considering land-use intensities in land change simulation. • Proposing an improved TECS estimation method. • Estimating influences of land changes on China's TECS. • TECS accumulation could be improved under sustainable policies. [ABSTRACT FROM AUTHOR]

Highlights • Spatiotemporal changes of central heating CO 2 emissions at city level are shown. • A high-resolution gridded inventory of heating-related CO 2 emissions is built. • The satellite nighttime light data is used to downscale the city level emissions. • Differences in CO 2 emissions between urban and non-urban areas are discussed. Abstract Energy consumption from central heating has rapidly increased in the cities of the North China Plain (NCP). The increasing use of natural gas in the central heating supply system may have altered the spatial and temporal patterns of CO 2 emissions from central heating, yet the quantitative impacts are poorly understood. Here we detect the spatio-temporal dynamics of CO 2 emissions of central heating from 2012 to 2016 at the prefectural-city level in the NCP region, by using the satellite NPP-VIIRS nighttime light data and a panel regression model to estimate CO 2 emissions on a 5 × 5 km2 grid. We find that despite a slight decrease (2%) in 2014 under the "Natural Gas Utilization Policy", CO 2 emissions continued to grow. Between 2012 and 2016, CO 2 emissions from central heating in the NCP increased from 106 to 121 Tg, although CO 2 emissions declined by 12% in Beijing due to the increasing contribution of natural gas boilers. The gridded CO 2 emissions map shows that over 2012–2016 coal burning is the main driving force of CO 2 emissions in both urban and non-urban regions, despite the increasing fraction of gas-based heating. Our results contribute to city-level policymaking on carbon reduction and climate change mitigation. The high-resolution gridded CO 2 emissions can also be applied in physical models to facilitate carbon cycle studies. [ABSTRACT FROM AUTHOR]

• Species diversity enhanced soil organic carbon storage in subtropical forests. • Soil organic carbon storage decreased with MAT and MAP in subtropical forests. • Soil organic carbon storage was closely related to leaf litter C/N and root biomass. Tropical and subtropical forest ecosystems play an important role in the global carbon regulation. Although positive relationships between biodiversity and soil organic carbon (SOC) storage have been found in experimental grasslands, biodiversity effects on SOC storage in natural forests remain debated. Based on a large dataset from 523 forest inventory plots across subtropical forests in China, we tested the relationship between biodiversity and SOC storage and examined whether environmental conditions (temperature, precipitation, soil properties) and litter quantity (leaf litter and root biomass) and quality (leaf litter carbon to nitrogen ratio [leaf litter C/N]) had effects on SOC storage. Furthermore, we used linear mixed-effects models to test the relative effects of biodiversity, environmental conditions, and litter quantity and quality on SOC storage. We used structural equation models to test how these variables directly or indirectly affected SOC storage. We found that species diversity, together with climatic factors (mean annual temperature and mean annual precipitation), leaf litter C/N and root biomass determined SOC storage in subtropical forests at a large spatial scale. SOC storage was most strongly affected by climatic factors, followed by leaf litter C/N. Species diversity had both direct and indirect (through root biomass and leaf litter C/N) effects on SOC storage after accounting for environmental conditions. We also found that the positive diversity–SOC storage relationships were stronger in low and medium mean annual precipitation. Our findings highlight that higher species diversity can lead to higher SOC storage and therefore the conservation of biodiversity could play an important role in climate change mitigation. [ABSTRACT FROM AUTHOR]