Topographic position indices (TPIs) measure essential impacts on ecosystem service supply capacity. The identification of changes in ecosystem services and value metrics under varying TPIs has become a topical subject of global change research. Multidimensional changes in spatiotemporal and geographical aspects of ecosystem service values (ESVs) are assessed in this article using land cover/use data from 2000–2015. Effects of land-use/cover changes and topographic indices on ESVs are explored using the Chinese terrestrial unit area ecosystem service value equivalence table combined with topographic factors. A sensitivity index is introduced to quantify the robustness of total ESV to land-use/cover and topographic indices. The results show that: (1) The total ESV in the Qihe watershed declined with a change in land-use/cover during the period 2000–2015. The maximum ESV was CNY 1.984 billion in 2005 and the minimum was CNY 1.940 billion in 2010; (2) The response of ESV to land/use cover varied greatly across TPIs, with the most significant change in ESV occurring in the 0.6–0.8 TPI range and the greatest change in a single ecosystem service occurred in water areas; (3) The sensitivity indices of ESVs are all less than 1. The sensitivity indices of unused land and water tended to zero. Woodland sensitivity indices were the highest at 0.53, followed by those of arable land and grassland, owing to the large proportion of arable land and grassland areas in the overall area of land-use categories.

Rapid urbanization and economic development have resulted in a mismatch between the supply and demand of ecosystem services. The theoretical value of ecosystem services (ESTV) is not suitable for determining ecosystem service compensation, posing challenges for integrated regional ecological development. A scarcity value model was used to analyze the influence of changes in supply and demand on the scarcity value of ecosystem services (ESSV) in the context of land-use change. The spatio-temporal distribution characteristics and trends of the ESSV from 2010 to 2020 were assessed in the Yangtze River Delta (YRD) urban agglomeration in China, and the driving factors were analyzed to provide theoretical guidance for horizontal ecological compensation across regions. The results show the following: (1) In the scenario that did not consider the impact of supply and demand changes on the scarcity value, the total ESTV decreased by 8.67% from 2010 to 2020, and high-value areas shifted to the west and south, whereas low-value areas shifted to the central and northern region and the Jiangsu, Zhejiang, and Shanghai Ringbelt. The ESTV was low in Shanghai and Jiangsu and high in Zhejiang. (2) In the scenario that considered changes in the supply and demand of ecosystem services, the ESSV increased from RMB 213 million in 2010 to RMB 1.323 billion in 2020; an increase of 521.13%. The scarcity value showed high variability within the provinces, with a larger difference between Zhejiang and Jiangsu and a smaller difference between Anhui and Shanghai. The ESSV was higher in counties with increased urbanization and high population density and lower in counties with slower economic growth and fewer people. (3) Regional ecological integration planning and management should be strengthened, and the ESSV might be considered as the reference standard for ecological compensation. The ESSV showed that spatio-temporal heterogeneity might guide the conversion from ecological resources to ecological capital and promote the regulatory role of market mechanisms to achieve horizontal payments for ecosystem services across regions.

Introduction: The interplay between the green transformation of cultivated land use (GTCLU) Q7and agricultural carbon emissions (ACE) plays a critical role in promoting sustain-able land management and advancing high-quality agricultural development. This study examines the Yangtze River Delta Urban Agglomeration (YRDUA) and con-structs a GTCLU evaluation framework based on spatial, functional, and modal dimensions. Methods: We assess the level of GTCLU and the agricultural carbon emissions intensity (ACEI), and apply a coupling coordination degree model to quantify their interaction. Using Geographical Detector and Geographically Weighted Regression (GWR), we further analyze how natural, economic, and social fac-tors infuence their coupling coordination degree (CCD). Results: Results indicate that between 2002 and 2022, GTCLU from 0.25 to 0.22, indicating a declining trend, with a persistent north–south gradient of higher levels in the north. ACEI initially increased before declining, spatially concentrated in central regions. The mean CCD increased from 0.31 to 0.32, with a net rise of 0.01. Spatially, low values in the central region and high values in the peripheral area. Temperature emerged as the strongest driver of CCD ( q = 0.41 in 2022), followed by population density ( q = 0.35 in 2002). Factor interactions were predominantly bifactor-enhanced or nonlinear-enhanced, with temperature combined with rural income or popula-tion density explaining up to 76% of CCD variation. GWR results show spatially heterogeneous efects: temperature, rural income, and population density gen-erally exerted positive infuences, while other factors tended to have negative impacts. Discussion: These fndings underscore the need for coordinated strategies that enhance GTCLU–ACEI synergy and support region-specifc, low-carbon agri-cultural pathways in the YRDUA.