Ecological Indicators最新文献

{"title":"Earlywood and latewood density in pines from northern subtropical China exhibit distinct and robust climate signals","authors":"Huiming Song ,&nbsp;Xueli Zeng ,&nbsp;Yu Liu ,&nbsp;Jesper Björklund ,&nbsp;Changfeng Sun ,&nbsp;Yifan Ma ,&nbsp;Quan Zhang ,&nbsp;Pei Li ,&nbsp;Xuan Wu ,&nbsp;Qiang Li","doi":"10.1016/j.ecolind.2025.113575","DOIUrl":"10.1016/j.ecolind.2025.113575","url":null,"abstract":"<div><div>Tree-ring densitometric parameters are essential tools in ecological and climate change studies. Among these, maximum latewood density (MXD) is the most widely used for summer temperature reconstructions, particularly in high-latitude and high-elevation regions where tree growth is primarily limited by temperature. In drought-prone sites, minimum earlywood density (MND) has been shown to reflect moisture variability. However, the application of these parameters in tropical or subtropical regions has been less well-explored. In this study, we conducted tree-ring densitometric studies in a northern subtropical forest of China to investigate the potential of tree-ring density parameters for climate reconstructions. MND exhibited significant positive correlations with maximum temperature and negative correlations with the Standardized Precipitation Evapotranspiration Index (SPEI) during May-June. MXD showed analogous response patterns to the same climate factors during August–September. Based on these robust correlations, we reconstructed the maximum temperatures during May-June and August-September separately. However, no synchronization was observed between these two temperature reconstructions on annual scale. Our study represents one of the first comprehensive densitometric investigations capturing extensive and strong climatic signals, highlighting the great potential of tree-ring densitometric parameters for climate reconstruction within subtropical regions.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113575"},"PeriodicalIF":7.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of bivariate relationships between spatial patterns: Revisiting the global and local L bivariate indices for wildlife management and conservation","authors":"Sonia Illanas ,&nbsp;Virgilio Gómez-Rubio ,&nbsp;Joaquín Vicente ,&nbsp;Pelayo Acevedo","doi":"10.1016/j.ecolind.2025.113551","DOIUrl":"10.1016/j.ecolind.2025.113551","url":null,"abstract":"<div><div>In wildlife management and conservation, the spatial relationship between two species (<em>e.g.</em> abundance patterns) is often studied through overlapping local information or implementing clustering analysis. However, conventional approaches overlook processes operating at larger spatial scales than the observation unit. Analyses that consider not only a location but also its neighbors, such as the Global L bivariate index (GL) and its Local (LL) measure, can be more appropriate for addressing spatial relationships between two species. The current formulation considers a unique connectivity matrix to define neighbors’ structure, assuming both species exhibit the same spatial dependence even when they may differ. We revisited the Global (GL′) and Local (LL′) indices to incorporate specific connectivity matrices to enhance wildlife applicability. We studied the behavior of the revisited indices through a simulation and a case study of four wildlife species with contrasting movement capabilities. The simulation study revealed the indices’ intrinsic characteristics, including smaller GL′ values and smoother LL′ patterns as the number of neighbors increases. The case study suggested imbalanced coexistence and divergence areas for the species studied, providing meaningful scenarios for wildlife management. The application of species-specific connectivity matrices facilitates the consideration of spatial use characteristics, offering a more reliable understanding of ecological relationships, particularly when the observation unit is smaller than the species’ home range. These findings are crucial for determining accurate and ecologically meaningful connectivity matrices. Overall, the revisited indices offer high flexibility and a comprehensive description of the spatial relationships between ecological indicators.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113551"},"PeriodicalIF":7.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143916636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Direct and indirect effects of climatic factors on ecosystem carbon and water fluxes and water use efficiency across different climatic zones in China","authors":"Weiru Zhao ,&nbsp;Junliang Jin ,&nbsp;Zhenxin Bao ,&nbsp;Jiarui Wu ,&nbsp;Qixiao Zhang ,&nbsp;Chang Yu ,&nbsp;Guoqing Wang","doi":"10.1016/j.ecolind.2025.113565","DOIUrl":"10.1016/j.ecolind.2025.113565","url":null,"abstract":"<div><div>Understanding how climatic factors affect ecosystem carbon and water processes is essential for preserving ecosystem health and managing water resources effectively. In addition to their direct impacts, climatic factors also indirectly regulate these fluxes by modifying leaf area index (LAI) and root-zone soil moisture (SMroot). Therefore, this study employed structural equation modeling to evaluate the total (STE), direct (SDE), and indirect (SIE) effects of climatic factors on ecological indicators (EIs). The EIs included gross primary productivity (GPP), evapotranspiration (ET), and ecosystem water use efficiency (eWUE). The findings indicate that temperature is the key climatic driver of GPP, with its STEs ranging from 0.34 to 0.89. The LAI-mediated indirect effect (SIE_LAI) accounts for over 58.6% of the STE, suggesting that warming-induced increases in GPP are primarily due to enhanced LAI. Climatic factors affect ET mainly through direct impacts. In arid regions, STEs of precipitation on ET range from 0.28 to 0.56, whereas in humid regions, STEs range from 0.03 to 0.28, suggesting that precipitation has a more pronounced effect on ET under water-limited conditions. In contrast, under sufficient water availability in humid regions, temperature plays a crucial role in driving ET, with STEs exceeding 0.78. Notably, the indirect effect of precipitation on ET via replenishing SMroot (SIE_SMroot) accounts for more than 50.6% of the SIE in arid and semi-arid regions, indicating that SMroot is a critical mediator of precipitation’s impact on ET. Although wind speed and CO₂ have minimal effects on GPP and ET, they significantly reduce eWUE by lowering GPP and raising ET. As a result, they become key climatic drivers in most regions, particularly in agricultural lands, where STEs fall below −0.36. Warming can enhance eWUE in most regions. However, the effect of precipitation depends on local water availability. It tends to lower eWUE in arid and semi-arid regions and slightly increase it in humid and semi-humid regions.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113565"},"PeriodicalIF":7.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards sustainable agriculture: A blueprint for European KPI-based farm-level assessment","authors":"B.T. Barış ,&nbsp;S.M. Marselis ,&nbsp;G.H. Ros ,&nbsp;A. van Doorn ,&nbsp;J.W. Erisman","doi":"10.1016/j.ecolind.2025.113560","DOIUrl":"10.1016/j.ecolind.2025.113560","url":null,"abstract":"<div><div>Key Performance Indicator (KPI) methodologies have emerged as potent tools for estimating sustainability performance in agriculture. With the proliferation of data availability, there is a growing opportunity to conduct sustainability assessments at the farm level and transition from traditional practice-based policies to performance-based policies. In this paper, we propose a blueprint for a Europe-wide KPI-based farm level sustainability performance assessment and monitoring system. By drawing insights from literature on farm-level sustainability assessment systems and tools, we synthesized eight guiding principles and a 5-step process framework for developing and operationalizing a European Agricultural KPI system built around the potential advantages of performance-based policies. The guiding principles include defining sustainability, involving stakeholders, ensuring applicability across sectors and countries, using normative benchmarking, and implementing decision support approaches. The proposed process framework can guide public and private stakeholders in Europe through the establishment of sustainability goals, modeling linkages between objectives and available data, KPI development, online user interface creation, and adaptive management. By leveraging advanced analytics and the integration of diverse agricultural data sources, our system aims to provide policymakers with the opportunity to instrumentalize performance-based financial support mechanisms to incentivize the adoption of sustainable agricultural practices among farmers. The essential components of a policy structure supporting the effective and ethical implementation of the proposed KPI system are discussed.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113560"},"PeriodicalIF":7.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143916634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ecological monitoring of invasive species through deep learning-based object detection","authors":"Xinwu Ji ,&nbsp;Yang Zhang ,&nbsp;Jiaquan Wan ,&nbsp;Tao Yang ,&nbsp;Qiong Yang ,&nbsp;Jiaqing Liao","doi":"10.1016/j.ecolind.2025.113572","DOIUrl":"10.1016/j.ecolind.2025.113572","url":null,"abstract":"<div><div>Water hyacinth (Eichhornia crassipes) is a highly invasive aquatic species that poses significant threats to aquatic ecosystem health and water resource sustainability. Monitoring its spatial distribution offers a valuable ecological indicator for assessing environmental degradation and guiding ecological interventions. However, traditional monitoring methods, such as manual inspection and remote sensing, often struggle with limited scalability, accuracy, and adaptability in complex natural environments. This study explores a novel ecological monitoring approach that uses the spatial distribution of water hyacinth as an indicator of aquatic ecosystem health, leveraging real-time object detection techniques. To implement this, we propose an enhanced YOLO-based model: HydroSpot-YOLO, which integrates an Attentional Scale Sequence Fusion (ASF) mechanism and a P2 detection layer to improve the detection of small and densely clustered targets under challenging conditions such as water reflections, cluttered backgrounds, and variable illumination. A specialized dataset, curated from real-world surveillance footage, was used for model training and validation. To support experimental validation, a specialized dataset was constructed from real-world aquatic surveillance footage, encompassing diverse and visually complex environments. Experimental results demonstrate that the improved model consistently outperforms existing baselines in terms of precision, recall, and mean Average Precision (mAP). These findings confirm the feasibility and effectiveness of applying deep learning-based object detection as an ecological indicator monitoring approach, offering a scalable and automated solution for invasive species management and aquatic ecosystem assessment.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113572"},"PeriodicalIF":7.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing water use efficiency: Insights from hydrological variability encounter of multiple water sources and implications for terminal Lake management in arid regions","authors":"Kun Liu ,&nbsp;Yunfei Chen ,&nbsp;Bin Wu ,&nbsp;Hailiang Xu ,&nbsp;Abdul Waheed ,&nbsp;Fan Gao ,&nbsp;Bing He ,&nbsp;Long Zhou ,&nbsp;Jie Wu ,&nbsp;Qin Zhang ,&nbsp;Jinhao Ju","doi":"10.1016/j.ecolind.2025.113564","DOIUrl":"10.1016/j.ecolind.2025.113564","url":null,"abstract":"<div><div>The escalating conflict between agricultural and ecological water demands, intensified by global climate change, poses significant challenges for water resource allocation in arid inland river basins. This study investigates the potential for integrated management of multiple water sources within the context of the Tarim River, Cherchen River, and Taitema Lake area. For the first time, we developed a joint distribution model of runoff for the Tarim and Cherchen Rivers, informed by the dynamics of Taitema Lake, to assess collaborative allocation strategies for terminal lake management in arid environments. Utilizing measured runoff data from 1960 to 2021, we employed a Bayesian vector autoregression model (BVAR) to analyze hydraulic connections between the rivers and the lake. Multivariate empirical mode decomposition (MEMD) was applied to identify periodic characteristics of runoff, while wavelet coherence transform assessed the consistency of runoff patterns. A Copula function was then utilized to construct a joint distribution model, quantifying variability patterns and their cascading effects on ecological water use in Taitema Lake. Findings reveal that the Cherchen River contributes more significantly to Taitema Lake than the Tarim River, exhibiting stable flows compared to the latter’s fluctuations. Significant lead-lag differences in flows were identified, with primary cycles of 2.9 years for the Tarim River and 5.7 years for the Cherchen River. The Copula model demonstrated a 44.52 % probability of synchronous wet-dry year occurrences, compared to 55.48 % for asynchronous occurrences. The complementarity between the Tarim River and the Cherchen River during wet and dry runoff encounter scenarios provides a foundation for establishing an efficient joint scheduling system and enhancing regional water use efficiency. This study underscores the critical role of strengthening multi-source water coordination and deepening understanding the dynamics of wet-dry runoff transitions to enhance water security and optimize resource management in arid regions.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113564"},"PeriodicalIF":7.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143916635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Linking patterns to processes: Using hunting bag data to classify raccoon (Procyon lotor) invasion stages in Germany since the 2000s","authors":"Sarah Cunze ,&nbsp;Gaby Schneider ,&nbsp;Norbert Peter ,&nbsp;Sven Klimpel","doi":"10.1016/j.ecolind.2025.113568","DOIUrl":"10.1016/j.ecolind.2025.113568","url":null,"abstract":"<div><div>Effective and successful management of invasive alien species requires a deep understanding of population dynamics in the invasion process. Following general concepts in invasion ecology we adapted the theoretical background to the stages of raccoon invasion in Germany. Hunting bag data provides time series over 21 years for each of 398 districts in Germany. In some cases the invasion processes might develop for longer time period than what could be studied. However it was possible to interpret individual time series as a part of the overall process: in particular absence (stage I), a lag phase – low level and strongly driven by chance (stage II), the spread phase subdivided according to the shape (linear – IIIa; exponential – IIIb and saturated – IIIc) and the stabilisation phase (stage IV) with random fluctuation at a high level. We applied a piecewise regression algorithm to differentiate between stages in the spread phase. The spatial patterns of this classification indicated two hotspots of late stages that coincide with the two assumed founding areas where raccoons (<em>Procyon lotor</em>) were first introduced, intentionally and accidentally, in the 1930s and 1940s. These results support the assumption that invasion proceeds in these phases. Densely populated areas in late phases may act as sources of immigration. Individuals may migrate to neighboring areas where they initiate or support the invasion process. Of course, this does not mean that all immigrating raccoons originate from hotspot regions in late stages of invasion. Germany hosts one of the largest non-native raccoon populations and thus represents a potential source of immigration to neighbouring countries. This study develops a spatial classification framework that can serve as an indicator for invasion dynamics in other species/ecosystems. Similar to the immigration from the two hotspots in central and north-eastern Germany into neighbouring areas, the raccoon can spread from Germany, the largest non-native population, into neighbouring countries where successive stages of invasion can be established.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113568"},"PeriodicalIF":7.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Full-chain comprehensive assessment and multi-scenario simulation of geological disaster vulnerability based on the VSD framework: a case study of Yunnan province in China","authors":"Li Xu ,&nbsp;Shucheng Tan ,&nbsp;Runyang Li","doi":"10.1016/j.ecolind.2025.113573","DOIUrl":"10.1016/j.ecolind.2025.113573","url":null,"abstract":"<div><div>With increasing global climate change and human-induced disturbances to geological environments, the frequency and destructiveness of geological disasters are intensifying. Thus, scientifically assessing and predicting geological disasters and formulating disaster prevention and mitigation policies are of critical importance for promoting regional sustainable development. However, current evaluations of geological disasters often overlook the adaptive capacity of the disaster-bearing body and focus primarily on cross-sectional comparisons across different regions at specific time points, with insufficient attention to spatiotemporal dynamics. This study selects Yunnan Province, one of the most severely affected regions by geological disasters in China, as a case study. Based on the Vulnerability Scoping Diagram (VSD) framework, a full-chain dynamic analysis framework was developed to assess past and present geological disaster vulnerability (GDV) and simulate future scenarios. This framework integrates exposure, sensitivity, and adaptive capacity to establish an indicator system that reflects the unique economic and ecological characteristics of the region. Using various mathematical models, the spatial differentiation and evolutionary trends of GDV in Yunnan Province from 2000 to 2020 were quantitatively analyzed. Furthermore, the Ordered Weighted Averaging (OWA) algorithm and the Partical Swarm Optimization-Support Vector Machine (PSO-SVM) model were combined to simulate future GDV scenarios for 2030–2050 under three development preferences: environment oriented, status quo, and economically oriented. The results show that from 2030 to 2050, GDV in Yunnan Province is generally at a medium–high level, with a spatial distribution pattern of “centered on Kunming, with a radial increase extending outward.” Temporally, GDV exhibits an initial increase followed by a decline, with regions clustering primarily as high-high and low-low GDV areas. Additionally, the predicted GDV outcomes vary across different development preferences. In the economically oriented scenario, GDV predominantly stabilizes at moderate levels, while in the environment oriented scenario, GDV improves the fastest but subsequently shows a slight rebound. These findings suggest that single-focus decisions prioritizing either economic development or environmental protection result in unsustainable GDV improvements. Therefore, decision-makers should consider GDV fluctuations under various scenarios when setting strategic development goals for different regions and phases, ensuring localized and adaptive adjustments. This study aims to provide insights from the Yunnan case for balancing disaster governance and regional economic development in global regions prone to geological disasters.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113573"},"PeriodicalIF":7.0,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143912828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nitrate dynamics in deep soils of the Loess Plateau: Impact of different land use types","authors":"Peiyuan Chen ,&nbsp;Jinzhu Ma ,&nbsp;Xiaobo Yue ,&nbsp;Haitao Zeng ,&nbsp;Chengyi Wang ,&nbsp;Qingmei Huang ,&nbsp;Ying Zhou ,&nbsp;Li Zhang","doi":"10.1016/j.ecolind.2025.113578","DOIUrl":"10.1016/j.ecolind.2025.113578","url":null,"abstract":"<div><div>The nitrogen cycling characteristics of soil in the Loess Plateau are critical for regional agriculture and environmental protection. This study investigates deep soil water nitrate distribution and dynamics under different land use types using δ¹⁵N-NO₃^–, δ¹⁸O-NO₃^–, δ¹⁸O-H₂O, δ²H-H₂O, and hydrochemical ions (F^–, Cl^–, NO₃^–, and SO₄^2–). The results indicate that agricultural lands, such as cornfields and apple orchards, exhibit higher nitrate concentrations in shallow soils (cornfields: median ∼ 50 mg/L, extremes &gt; 80 mg/L) due to fertilization and irrigation. However, deeper soil layers did not show significant nitrate enrichment despite prolonged cultivation. In contrast, grasslands and woodlands maintain lower and stable nitrate levels (grasslands: 10–15 mg/L, woodlands: ∼5 mg/L) due to natural nitrogen fixation. Nitrate sources differ by land use. Apple orchards and shrublands are influenced by NH₄⁺-fertilizers and soil nitrogen, while cornfields utilize both NH₄⁺- and NO₃^–-fertilizers. Land-use changes from agriculture to woodland increased deep soil nitrate (woodlands by 22.7 % and shrublands by 83 %), suggesting heightened leaching and groundwater pollution risks. Soil moisture also impacts nitrate accumulation. Shrublands exhibit the highest nitrate accumulation (27.24 kg N·ha⁻¹·cm⁻¹), followed by cornfields (0.74 ± 0.2 kg N·ha⁻¹·cm⁻¹), while grasslands show the lowest accumulation (0.43 ± 0.03 kg N·ha⁻¹·cm⁻¹). To mitigate groundwater nitrate pollution, rational fertilization, conservation tillage, and efficient irrigation are recommended for agricultural lands. For natural lands, maintaining vegetation and soil management practices is essential. Tailored strategies are crucial to optimize soil health and water quality.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113578"},"PeriodicalIF":7.0,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143912827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A dual-method approach integrating dynamic QCA and LightGBM-SHAP algorithms to uncover the configuration paths and key drivers of water resource green efficiency in China","authors":"Naiming He,&nbsp;Rijia Ding","doi":"10.1016/j.ecolind.2025.113540","DOIUrl":"10.1016/j.ecolind.2025.113540","url":null,"abstract":"<div><div>Water resource utilization is crucial for sustainable development, and enhancing water resource green efficiency (WRGE) is essential for addressing water scarcity. This study presents three key innovations: (1) It applies the super-efficiency epsilon-based measurement and global Malmquist–Luenberger index (Super-EBM-GML) model from the perspective of high-quality economic development to analyze the spatiotemporal characteristics of WRGE across 30 Chinese provinces from 2014 to 2022. (2) It uses the Technology-Organization-Environment (TOE) framework and dynamic qualitative comparative analysis (QCA) model to identify the key drivers of WRGE and regional variations. (3) It integrates machine learning (light gradient-boosting machine with Shapley additive explanations; LightGBM-SHAP) with QCA to quantify the impact of variables, combining qualitative and quantitative analysis. Key findings include the following: (1) WRGE showed an upward trend, with higher efficiency in the eastern and economically developed regions. Growth in the GML index was mainly driven by green technological progress (GTC). (2) Although no single necessary condition was found to drive WRGE, three model types and four configuration paths were identified: technology–environment-driven, environment-driven, and organization–environment-driven. (3) The most influential factors were digital economy development, followed by industrial structure rationalization and environmental regulation. This study provides key policy recommendations, including the promotion of green technology, the strengthening of regulations, the enhancement of policy resilience, the implementation of region-specific strategies, and the integration of the digital economy with water resource management, thus offering valuable insights for regions facing water scarcity.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113540"},"PeriodicalIF":7.0,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143912829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}