Inland river basins in Northw est China are highly sensitive to climate change and human activities, and increasing development under water scarcity has intensified ecological pressure. However, cross-regional spatial coupling between ecological quality and socioeconomic development remains insufficiently understood. Using the Heihe River Basin (HRB) as the study area, this study developed a pressure-state-coordination (PSC) framework based on the logic of the pressure-state-response (PSR) model. Within this framework, the pressure dimension is represented by the rasterised socioeconomic development index (RSED) as a measure of socioeconomic development intensity and a proxy for potential ecological pressure, the state dimension by an improved ecological quality index (GDBRSEI), and the coordination dimension by the local coupling coordination degree (CCD) and the local-cross-regional coupling coordination degree (LTCCD). The optimal parameters-based geographical detector (OPGD) identified the main explanatory factors. The results show that after the HRB entered the routine water allocation phase, ecological quality shifted from degradation to recovery, with the strongest improvement in the wetlands of Ejina Banner (EJNQ) in the downstream (Downs) region. Socioeconomic development differed spatially, with the midstream (Mids) as the main growth area, the upstream (Ups) remaining relatively stable, and the Downs lagging behind. CCD changed from imbalance to coordination, while LTCCD shifted from weak connection to weak synergy. The Mids showed stronger cross-regional coordination than the Ups and Downs. CCD mainly reflected local coupling shaped by natural conditions, economic development, and water demand, whereas LTCCD was more sensitive to water use, runoff conditions, and socioeconomic spatial links, especially irrigation water (IR), domestic water (DW), and downstream runoff (RU). These findings suggest that water-resource allocation and socioeconomic spatial links are key factors affecting ecological-socioeconomic coordination in arid river basins. This study provides a local-to-cross-regional perspective for understanding ecological-socioeconomic relationships and supports ecological management and sustainable development in arid river basins.
Ecological protection compensation has been widely recognized as an effective policy instrument for enhancing ecosystem services and alleviating poverty. This study systematically analyzes the horizontal ecological compensation mechanism of Inter-county Forest Ecological Credit Transactions (IFECT) and employs Double Machine Learning to empirically evaluate its impact on rural residents' income using a panel dataset of 1865 county-level units in China from 2012 to 2023. The IFECT operational mechanism analysis indicates that IFECT represents an institutional innovation within China's horizontal ecological protection compensation system. The benchmark regression shows that IFECT significantly increases rural residents' income. Mechanism analysis shows that IFECT is positively related to forestland transfer-out, the development of forestry ecological industries, and the intensity of forestry ecological subsidies. These findings provide supportive evidence that these factors may serve as potential channels through which IFECT affects rural residents' income. Heterogeneity analysis reveals that the positive effect is more pronounced in former state-level impoverished counties. Further analysis demonstrates that IFECT policy is positively related to rural residents' wage, operating, property, and transfer income. IFECT generates stronger income gains in credit-selling than in credit-buying counties, while actual transaction participation significantly increases rural residents' income in Chongqing. These findings provide empirical evidence and policy insights from China for countries simultaneously pursuing ecological conservation and rural income growth.
Existing studies seldom distinguish the lagged and cumulative responses of vegetation to meteorological drought (MD) and agricultural drought (AD), nor do they link drought propagation time (DPT) to vegetation response modes in climatic transition zones. Here we quantified the lagged and cumulative effects, DPT, and driving factors of vegetation responses to MD and AD across the sub-humid and semi-arid transitional zones of Northern China using correlation analysis and the XGBoost–SHAP framework. Regionally, vegetation exhibited a “short lag–short cumulative” pattern in response to MD, whereas AD induced a “long lag–short cumulative” pattern. Compared with the sub-humid region, semi-arid vegetation and forest sub-types showed “high sensitivity–high tolerance” to MD but “delayed response–low tolerance” to AD. For MD, shrublands were the most sensitive and grasslands the most tolerant, and needleleaf forests were more tolerant than broadleaf forests. For AD, forests exhibited the highest sensitivity and tolerance, and broadleaf forests responded faster than needleleaf forests. Soil hydrological buffering was prominent: 51.8% of all vegetation and 53.4% of forests had a DPT of 8–9 months. DPT increased in the order grassland < forest < cropland < shrubland across the study area and the semi-arid region, and broadleaf forests consistently had shorter DPT than needleleaf forests in all climatic zones. Potential evapotranspiration (PET), precipitation (PRE), and temperature (TMP) were the dominant drivers, with PET controlling lagged effects and PRE controlling cumulative effects for both drought types. These findings provide a basis for ecological protection and climate-change adaptation in transitional climatic zones.
Blue carbon ecosystems (BCEs) function as ecological shock absorbers with respect to extreme climatic changes, but this normative functionality changes in response to ecosystem-specific stressors such as pollution or fragmentation at local scales. As a result, variable magnitudes of co-benefits such as eco-restorative capabilities and climatic resilience are reported, which either underestimate or overestimate the major roles of BCEs in ecosystem services (ES) delivery and natural carbon sequestration (C-seq). Hence, a comprehensive understanding on the operationalization of climate resilience in BCE is essential to understand how ecosystems cross-subsidise to sustain co-benefits with C-seq and ES delivery. The present study investigated available scientific evidence for mapping functional connectivity in BCEs, which can be connected via one or more of the following pathways: geographic connectivity, adjacency, habitat and ecological connectivity, as well as cross-subsidies. Systematic evidence synthesis of 451 non-duplicated publications on BCEs in the past 26 years (i.e., 2000–2026) provided critical insights on the nature of functional connectivity established among different BCEs. Further, bibliometric indicators illustrated that the functions of BCEs evolved well when concurrent with habitat changes in ‘connected’ states. Thematic and trend analyses, co-occurrence network analyses and evidence gap map synthesis provided insights on the roles of such connectivity on critical ecosystem factors. Low Risk of Bias in the present systematic evidence synthesis greater than or equal to 75% implied greater confidence in the interpretation of the natural processes operating in BCEs. The present study highlighted the need for models to assess the magnitude of functional connectivity that facilitates ES delivery and higher C-Seq rendering the systems amenable to better eco-restoration and higher resilience.
As large-scale reservoir construction continues globally, eutrophication and frequent algal blooms have emerged as critical threats to water security and hydraulic infrastructure. While precise monitoring is essential, the temporal resolution of current mid-to-high resolution optical sensors often fails to capture the rapid ecological succession of blooms due to cloud interference and revisit cycle limitations. We propose a modified red-edge floating algae index (reFAI) for bloom detection in the Danjiangkou Reservoir using Sentinel-2 MSI data. The reFAI algorithm significantly outperforms traditional indices (NDVI, ABDI) by minimizing atmospheric and CDOM interference, achieving an overall accuracy of 0.89. Applying this algorithm to a 121-scene dataset from 2016 to 2024 reveals distinct spatiotemporal heterogeneity in algal bloom dynamics. Statistical analysis reveals a decadal intensification of bloom frequency in urban-impacted tributaries, specifically the Shending and Sihe rivers, which had the highest annual growth rates (5.12% and 4.67%, respectively). Pixel-based Mann-Kendall analysis further identifies that algal proliferation is predominantly concentrated in upstream reservoir embayments where stagnant hydrodynamic conditions facilitate localized nutrient trapping and reduced vertical mixing. These findings highlight that given sufficient background nutrients, localized flow stagnation acts as the key trigger for concentrated algal bloom outbreaks. Interpretable machine learning indicated that thermal factors set the growth baseline, hydrodynamics dominated accumulation, and nutrients provided the material basis. This study provides a monitoring framework for early warning systems and informs management strategies for reservoir and inter-basin water transfer projects.
