Ecological Indicators最新文献

{"title":"Optimization of resource management in vulnerable areas within the interconnected framework of ecosystem services supply and demand","authors":"Yuan Liu ,&nbsp;Chengyuan Wang ,&nbsp;Bingxin Han ,&nbsp;Zian Liu ,&nbsp;Tongpeng Wang ,&nbsp;Zhenglin Tian ,&nbsp;Longxin Ding ,&nbsp;Xuegang Mao ,&nbsp;Viktor Karminovd ,&nbsp;Sergey Chumachenkod","doi":"10.1016/j.ecolind.2025.113235","DOIUrl":"10.1016/j.ecolind.2025.113235","url":null,"abstract":"<div><div>Ecological zoning is utilized to identify critical ecological areas that are essential for preserving ecosystem integrity and stability. However, the zoning of fragile areas does not adequately address issues related to uneven distribution of ecological resources and the lack of synergistic management. To overcome this limitation, a comprehensive ecological zoning framework is proposed in this study, integrating the multidimensional Comprehensive Ecosystem Services Supply and Demand Ratio (CESDR) and Ecological Risk Index (ERI) within the Yellow River Basin (YRB), a prototypical ecologically fragile zone in China. Results indicate that: (1) the supply capacity of ecological resources in the YRB has gradually increased between 2000 and 2020, exhibiting a surplus in the south, a deficit in the north, and a spatial mismatch between the supply and demand of water resources; (2) the YRB is predominantly characterized by areas of medium to high ecological risk, which decreased by 83,640 km2 (10.34 %) between 2000 and 2020; (3) the YRB is classified into Ecological Resource Supply Zones (ERSZs), Ecological Resource Development Zones (ERDZs), Ecological Resource Redline Zones (ERRZs), and Ecological Resource Conservation Zones (ERCZs); (4) notably, the ERRZs, which predominate in the YRB, decreased by 20.88 % between 2000 and 2020, primarily transitioning into ERCZs (16.18 % increase) and ERSZs (3.49 % increase). It is proposed that ERSZs and ERCZs leverage ecological resource allocation to mitigate the imbalance between supply and demand within the YRB, enhance the ecological compensation mechanism for ERRZs to facilitate value accounting. This study provides insights into the sustainable development of fragile ecosystems.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113235"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction and optimization of the watershed-scale ecological network based on network characteristic analysis: A case study of the Lancang River Basin","authors":"Yi Wang ,&nbsp;Xiaogang Zhou ,&nbsp;Chang Ding ,&nbsp;Wenxuan Li ,&nbsp;Linyun Huang ,&nbsp;Beichen Ge ,&nbsp;Yuhong Song","doi":"10.1016/j.ecolind.2025.113164","DOIUrl":"10.1016/j.ecolind.2025.113164","url":null,"abstract":"<div><div>The growth of socio-economic development and human activities markedly threatens the ecological security of river basins. Establishing a robust ecological network (EN) is a viable solution to this problem. Nonetheless, optimizing the structure and stability of ENs remains a complex issue. This study focused on the Lancang River Basin, identifying ecological corridors and critical ecological regions through circuit theory to develop the EN of the Lancang River Basin. Subsequently, complex network theory was utilized to compare the optimization effects of various strategies on the EN, proposing effective optimization methods for the study area. The findings revealed that (1) the EN of the Lancang River Basin comprised 26 ecological sources, 43 ecological corridors, and 106 key ecological regions. (2) The EN was enhanced by incorporating 12 corridors using the low-degree-first (LDF) strategy and the low-betweenness-first (LBF) strategy. Both strategies resulted in substantial improvements in average degree, network diameter, and average path length. (3) Under scenarios of random and deliberate attacks, the LDF strategy proved superior in augmenting overall network performance and bolstering network stability. The optimized network effectively addressed the ecological deficiencies in the Weiyuan River region. This research explored the utilization of complex network theory in EN optimization and provided a foundation for ecological spatial planning and protection policies in the Lancang River Basin.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113164"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143359481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of industrial structural transformation in the Yangtze River economic belt on the trade-offs and synergies between urbanization and carbon balance","authors":"Ran Wu ,&nbsp;Gang Yu ,&nbsp;Yimo Cao","doi":"10.1016/j.ecolind.2025.113165","DOIUrl":"10.1016/j.ecolind.2025.113165","url":null,"abstract":"<div><div>Promoting carbon balance in the Yangtze River Economic Belt is a crucial step in China’s pursuit of carbon neutrality, with industrial structural transformation serving as a vital pathway toward this goal. This paper employs the GeoShapley model and the spatial Durbin model to investigate the spatiotemporal evolution of the trade-offs and synergies between urbanization and carbon balance in 1028 county-level units of the Yangtze River Economic Belt from 2011 to 2021, as well as the impact of industrial structural transformation on these relationships. The results reveal the following: (1) the spatial distribution pattern of trade-off and synergy remained largely unchanged between 2011 and 2021, but there was an overall shift from synergy to trade-off. (2) In the overall regression results, the industrial greening index exhibits opposing effects on local regions and their surroundings, while the industrial upgrading index suppresses development in surrounding areas. (3) In the regional regression results, the industrial greening index shows contrasting effects on the downstream and upstream regions, with a suppressive effect on surrounding areas occurring only in the downstream region. The industrial upgrading index inhibits development in both the downstream and midstream regions, while the industrial rationalization index exerts a suppressive effect exclusively in the downstream region.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113165"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143359482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Smart Cities, Smarter land Use? Unveiling the efficiency gains from China’s digital urban transformation","authors":"Zhenyu Zhuo ,&nbsp;Jiashuo Ye ,&nbsp;Yu Wang ,&nbsp;Hao Chen ,&nbsp;Bin Liang","doi":"10.1016/j.ecolind.2025.113151","DOIUrl":"10.1016/j.ecolind.2025.113151","url":null,"abstract":"<div><div>Urban smart transformation serves as a key driver of high-quality economic development in the digital economy era, playing a crucial role in advancing sustainable urban growth. This paper analyzes panel data from 282 prefecture-level cities in China over 12 years, employing the SBM-Undesirable model to measure urban land use efficiency (ULUE). By treating the smart city construction policy as a quasi-natural experiment, this study uses a time-varying DID approach to assess the impact of urban smart transformation on ULUE and employs moderating and spatial effect models to explore underlying mechanisms. The findings reveal that: (1) Smart city construction significantly enhances ULUE, with increases of 16 %, 11.4 %, and 11.1 % of the three pilot batches; (2) Urban smart transformation improves ULUE through three mechanisms: fostering innovation investment, expanding internet user bases, and optimizing industrial land use efficiency; (3) Urban smart transformation has a more pronounced effect on ULUE in eastern and western cities, while the impact in central cities is not significant; (4) The long-term effects of smart city policy surpass short-term impacts and exhibit synergistic interactions with innovation policies; (5) Urban smart transformation has a spatial spillover effect, benefiting neighboring cities within an 80 km radius by significantly boosting ULUE. This paper employs rigorous empirical methods to analyze the causal relationship between urban smart transformation and ULUE, while also delving into the underlying mechanisms, time lag effects, and spatial spillovers. Furthermore, the study offers actionable policy recommendations. These insights provide valuable guidance for sustainable urban development strategies in developing countries.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113151"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143359172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of the Giant Panda National Park corridor and restoration of edible bamboo: A case study of from the Chengdu area region","authors":"Xing Wang ,&nbsp;Yu-Ting Yang ,&nbsp;Yan Wu ,&nbsp;Yu Xie ,&nbsp;Pei Tu ,&nbsp;Mei-Ling Liu ,&nbsp;Mei-Jiao Zhang ,&nbsp;Tao Lu","doi":"10.1016/j.ecolind.2025.113143","DOIUrl":"10.1016/j.ecolind.2025.113143","url":null,"abstract":"<div><div>Giant pandas (<em>Ailuropoda melanoleuca</em>) serve as flagship species for global biodiversity conservation. Establishing wildlife corridors and introducing edible bamboo species into their understory can enhance giant panda migration and mitigate their vulnerability to human activities and climate change. This study employs the MaxEnt model to analyze habitat suitability for giant pandas and edible bamboo, using the principle of least-cost paths to construct potential ecological corridors while also identifying suitable bamboo species for planting. Results revealed that (1) the habitat suitability index was high in the study region’s central area but low at the periphery, with fragmentation observed, particularly in the northeastern mountains; (2) eight giant panda habitat patches (C1–C8) and nine potential ecological corridors were identified, where C1–C6 patches were small and corridors exhibited low connectivity; and (3) four bamboo species were suitable for planting in the corridors, identified by overlaying corridor layers with bamboo suitability maps. Among the bamboo species<em>, Fargesia spathacea</em> is considered most adaptable, capable of occupying over 40% of the corridor area, followed by <em>Fargesia robusta</em>, recommended for widespread planting in corridor habitats. These findings underscore the importance of strategic habitat management and bamboo restoration in promoting the long-term survival of giant pandas.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113143"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143359477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vegetation runoff and sediment reduction benefits and influential factor in the Loess Plateau of China: A meta-analysis","authors":"Mengrou Jia ,&nbsp;Cong Han ,&nbsp;Jianzhi Niu ,&nbsp;Miao Wang ,&nbsp;Linus Zhang ,&nbsp;Ronny Berndtsson","doi":"10.1016/j.ecolind.2025.113221","DOIUrl":"10.1016/j.ecolind.2025.113221","url":null,"abstract":"<div><div>The Loess Plateau is one of the most severely affected regions in China by soil erosion, where vegetation restoration is the principal strategy for soil and water conservation. Runoff and sediment reduction benefits (<em>RRB</em> and <em>SRB</em>) are key indicators used to evaluate the effectiveness of vegetation measures. While numerous observational and experimental studies have explored the effects of different vegetation types and climatic factors on <em>RRB</em> and <em>SRB</em>, the spatial variability and environmental controls of these benefits in the Loess Plateau remain insufficiently understood. This <em>meta</em>-analysis synthesizes data from 74 published studies, compiling a total of 1,518 data points derived from three vegetation types: forest, shrubland, and grassland. It analyzes the spatial variability of <em>RRB</em> and <em>SRB</em>, along with their relationships with vegetation, climatic, and geographic factors. The results indicate that <em>RRB</em> and <em>SRB</em> are highest in shrubland and lowest in grassland, with <em>SRB</em> generally exceeding <em>RRB</em> across all vegetation types. Both <em>RRB</em> and <em>SRB</em> are influenced by various environmental factors, with mean annual precipitation and vegetation cover exerting the greatest impact. Identified thresholds indicate that especially <em>RRB</em> (or <em>SRB</em>) is maximized at a stand age of 15–20 years, on slopes of 25–30° (20–25° for <em>SRB</em>), or with vegetation cover of 65–70 % (55–60 % for <em>SRB</em>). Vegetation measures significantly enhance soil and water conservation in the Loess Plateau. However, vegetation restoration should account for regional environment and require species suited to local conditions. Additionally, maintaining plantations regularly throughout the vegetation lifecycle is essential to achieve long-term sustainable results.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113221"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of factors that affect post-fire recovery of photosynthetic activity at global scale","authors":"Yicheng Shen ,&nbsp;I. Colin Prentice ,&nbsp;Sandy P. Harrison","doi":"10.1016/j.ecolind.2025.113206","DOIUrl":"10.1016/j.ecolind.2025.113206","url":null,"abstract":"<div><div>The time taken for ecosystems to recover after wildfire affects the rate of carbon sequestration, and this in turn impacts land–atmosphere exchanges and hydrological processes. Factors affecting post-fire recovery time have been investigated at site or regional scale, but there is comparatively little information about this at a global scale. In this study, we use solar-induced chlorophyll fluorescence (SIF) to estimate the recovery of photosynthetic activity after fire for more than 10,000 fires representing the range of ecosystems across the globe. We then examined the factors that influence post-fire recovery time, initially using the relaxed lasso technique to identify the most important factors and then using a linear regression model incorporating these factors. We show that vegetation characteristics, the characteristics of the fire, and post-fire climate all influence recovery time. Gross primary production (GPP) is the most important factor, with faster recovery in ecosystems with higher GPP. Fire properties which indicate substantial vegetation damage, such as fire intensity and duration, result in longer recovery times. Post-fire climate also affects recovery time: anomalous temperature and temperature seasonality, and higher than normal dry days increase recovery time while higher-than-average precipitation decreases recovery time. There is an additional impact of vegetation type (biome), which may reflect differences in plant adaptations to fire between biomes. We show that there is a clear relationship between the proportion of plants that resprout after fire in a biome and recovery time, with ecosystems characterised by higher abundance recovering faster.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113206"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnosis of land degradation and analysis of its spatiotemporal evolution in the Jinghe River Basin, Xinjiang","authors":"Ya Peng ,&nbsp;Zhaopeng Wu ,&nbsp;Xinpeng Shi ,&nbsp;Yuting Tian ,&nbsp;Ruirui Zhang","doi":"10.1016/j.ecolind.2025.113210","DOIUrl":"10.1016/j.ecolind.2025.113210","url":null,"abstract":"<div><div>Land degradation is one of the serious environmental problems faced globally, with profound impacts on human society, ecosystems, and economic development. The situation and trend of land degradation in the Jinghe River Basin are not clear. This study constructs a comprehensive Land Degradation Index (LDI) through multiple indicators to analyze the trend of land degradation in the Jinghe River Basin. The results show that from 2000 to 2020, the area of land degradation in Jinghe County is gradually decreasing, with severe land degradation decreasing annually and mild land degradation increasing annually. During the study period, moderate and above land degradation in Jinghe County was concentrated in the central part, and its center of gravity moved spatially from the northwest to the southeast, and then to the southwest, generally showing a “V” shape; the overall state of land degradation is relatively stable. Single land degradation process types account for 19.24 % of the total land degradation area and compound land degradation accounts for 80.76 %. In general, the type of land degradation in Jinghe County over the 20 years is still mainly compound land degradation. Land degradation in Jinghe County is formed by the combined action of nature and human social activities. Human activities are the leading factor in the increase of LDI, but natural factors have a significant correlation with local LDI changes; temperature, Normalized Difference Vegetation Index (NDVI), and population have a higher impact on the LDI changes in Jinghe County, and local LDI changes respond more strongly to precipitation, evapotranspiration, and Gross Domestic Product (GDP). The research results are of great significance for the management of land use and the promotion of ecological protection in Jinghe County.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113210"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ecological security driving mechanisms and optimization of zoning in Chinese urban agglomerations: A case study of the central plains urban agglomeration","authors":"Jinyuan Zhang ,&nbsp;Xuning Qiao ,&nbsp;Yongju Yang ,&nbsp;Liang Liu ,&nbsp;Yalong Li ,&nbsp;Shengnan Zhao","doi":"10.1016/j.ecolind.2025.113190","DOIUrl":"10.1016/j.ecolind.2025.113190","url":null,"abstract":"<div><div>The global ecological security framework is facing unprecedented challenges and transformations, with ecological security issues transcending national and regional boundaries and evolving into a global concern. The Central Plains Urban Agglomeration (CPUA) serves as a critical urban growth pole in China. In light of mounting ecological security challenges, including disparities in ecological efficiency and growing constraints from resource and environmental limitations, the CPUA urgently requires achieving a balance and mutually beneficial relationship between economic growth and ecological protection. This study examines 271 counties within the CPUA, utilizing both objective and subjective weighting methods to assess ecological security from a three-dimensional perspective, encompassing ecosystem health, landscape ecological risk, and ecosystem services over the period from 2000 to 2020. The analysis identifies dominant driving factors and spatial heterogeneity through the application of the Optimal Parameter Geodetic Detector (OPGD) and Multi-scale Geographically Weighted Regression (MGWR) models. Additionally, it combines the ’Three-dimensional Rubik’s Cube model with primary functional zoning to enhance the optimization of ecological security delineation. The results indicate that: (1) The ecological security situation in the CPUA remained stable from 2000 to 2020. The number of counties experiencing an upgrade in ecological security levels was greater than those experiencing a downgrade, with transitions primarily occurring between adjacent levels. Spatial disparities in ecological security were relatively small, and counties with lower ecological security levels tended to show greater clustering; (2) The explanatory power of the driving factors is ranked as follows: human factors &gt; natural factors &gt; landscape factors. Interaction detection factors exhibit varying degrees of dual-factor or nonlinear enhancement, with the combined strength of positive effects being greater than that of negative effects; (3) The spatial distribution characteristics of ecological security zones in the CPUA align with those of ecological security conditions. The CPUA is divided into “three zones, two belts, and one area,” with personalized ecological security model recommendations based on the primary functional zoning. This research furnishes a theoretical foundation for crafting scientifically informed ecological security policies for the CPUA and provides meaningful insights applicable to comparable urban agglomerations worldwide.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113190"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143333442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation of water resources in ungauged region- case study in Nam Ou River Basin, Laos","authors":"Wenmei Cai ,&nbsp;Li Ren ,&nbsp;Li Zhang ,&nbsp;Yutong Liu ,&nbsp;Wenjiao Yang","doi":"10.1016/j.ecolind.2025.113173","DOIUrl":"10.1016/j.ecolind.2025.113173","url":null,"abstract":"<div><div>Hydrological studies in ungauged regions have garnered significant interest in recent research. This paper presents the development of a VIC model utilizing topographic, vegetation, soil, and climate data. The model parameters were calibrated and validated with measured flow data from the watershed. Through parameter transplantation, the calibrated parameters were applied to simulate the spatial distribution and annual allocation process of water resources in the Nam Ou River Basin. The analysis revealed that the spatial distribution of water resources and runoff coefficients closely aligns with the spatial distribution of precipitation, indicating a strong correlation between water resources and precipitation in the basin. From 1980 to 2010, the average water resources for the basin were estimated at 16.4 billion m3, with a rainy period from May to September. August recorded the highest water resources, while the dry period from December to February saw the lowest water resources in February. Upon evaluating the results’ robustness, it was concluded that the VIC model’s simulation accuracy is high, making it a valuable tool for future research in areas with insufficient or absent data.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113173"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143334041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}