Ecological Indicators最新文献

{"title":"Responses of soil carbon, nitrogen, and phosphorus stoichiometry to afforestation of severely desertified land in northern China","authors":"Yuqiang Li ,&nbsp;Wenjie Cao ,&nbsp;Yun Chen ,&nbsp;Libing Han","doi":"10.1016/j.ecolind.2025.113520","DOIUrl":"10.1016/j.ecolind.2025.113520","url":null,"abstract":"<div><div>Large-scale afforestation is being implemented globally to promote carbon sequestration in ecosystems, address climate change, and restore degraded ecosystems. However, the impacts of trees and shrubs on soil stoichiometry in severely desertified land remain unclear. We investigated the topsoil (0 − 20 cm) carbon, nitrogen, and phosphorus (C:N:P) stoichiometry of <em>Pinus sylvestris</em> var. <em>mongolica</em> and <em>Caragana microphylla</em> plantations established on mobile sand dunes in northern China. Soil organic carbon (SOC, 2.6 to 11.3 g kg⁻¹) and total nitrogen (TN, 0.3 to 1.2 g kg⁻¹) concentrations increased by 3.2 to 6.5 times the values in mobile dunes, on average, after 40 years of afforestation. Total phosphorus (TP, 0.1 to 0.2 g kg⁻¹) in the 40-year-old <em>P. sylvestris</em> and <em>C</em>. <em>microphylla</em> plantations increased by 15.1 and 24.3 %, respectively. Well-constrained C:N ratios (7.7 to 10.1 on average) indicated strong coupling relationship between SOC and TN. The average C:P (7.2 to 43.8) and average N:P (0.8 to 4.4) ratios increased with increasing afforestation age due to disproportionate changes in the three elements, but the rate of increase under <em>C. microphylla</em> decreased. N:P ratios under <em>P. sylvestris</em> increased with increasing afforestation age, indicating that long-term <em>P. sylvestris</em> afforestation may become P-limited. Environmental factors explained 75 % of the total variation of soil C:N:P stoichiometry. The improved plant diversity, productivity, and soil physical properties after afforestation improved the soil C:N:P stoichiometry. Climate and terrain had negative impacts on this stoichiometry. We suggest combining multiple species for afforestation to improve species diversity and providing supplemental P in later stages of afforestation to counteract the future P limitation. Our findings provide new knowledge on the relationships between afforestation and soil stoichiometry in severely desertified areas, and provide a reference for optimizing afforestation.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113520"},"PeriodicalIF":7.0,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869610","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":"Evaluation mechanism of urban green competitiveness via a gray fuzzy comprehensive evaluation model","authors":"Cheng Wang ,&nbsp;Xiyin Qiu ,&nbsp;Hui Shen ,&nbsp;Congjun Rao","doi":"10.1016/j.ecolind.2025.113510","DOIUrl":"10.1016/j.ecolind.2025.113510","url":null,"abstract":"<div><div>Green development is a mode of economic growth and social development aimed at efficiency, harmony and sustainability. Green competitiveness has gradually become a key factor in measuring the comprehensive competitiveness of a country or region. However, existing studies lack a unified evaluation index system and comprehensive methodology for assessing urban green competitiveness. This study fills this gap by integrating gray correlation analysis and fuzzy comprehensive evaluation to provide a more accurate and systematic assessment. First, 40 green competitiveness indicators were selected from four aspects of economic level, environmental pressure, resource consumption and social policy, and a green competitiveness evaluation index system was constructed. Second, the weight of each evaluation index was subsequently determined via the entropy weight method. Third, the gray correlation analysis and the fuzzy comprehensive evaluation method are combined to establish a gray fuzzy comprehensive evaluation model for evaluating urban green competitiveness. Finally, 11 provinces and cities along the Yangtze River Economic Zone in China were used as research objects, and the established evaluation mechanism was applied for empirical analysis. According to the comprehensive scores and ranking results of provinces and cities, some corresponding countermeasures and suggestions are provided to promote the competitiveness of the Yangtze River Economic Zone in terms of the economy, environment, resources, society and so on.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113510"},"PeriodicalIF":7.0,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143874073","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":"Spatiotemporal patterns of abrupt vegetation changes and reversal trends in the Yellow River Basin: Climate and human drivers","authors":"Xiaohui He,&nbsp;Tingwei Fan,&nbsp;Mengjia Qiao","doi":"10.1016/j.ecolind.2025.113502","DOIUrl":"10.1016/j.ecolind.2025.113502","url":null,"abstract":"<div><div>Vegetation changes involve both gradual trends and abrupt changes, with the latter serving as critical indicators for detecting vegetation state transitions and identifying potential environmental stresses. In recent decades, the structure and function of vegetation ecosystems in the Yellow River Basin have undergone significant alterations. However, there remains limited understanding of whether abrupt changes occurred during these alterations and their driving mechanisms. So here, this study utilized the Normalized Difference Vegetation Index (NDVI) as a proxy for vegetation changes, characterized the spatiotemporal distribution of abrupt vegetation changes characteristics based on the Breaks for Additive Seasonal and Trend (BFAST) algorithm, and employed a Random Forest model to elucidate the driving factors behind these changes. The results showed that 73.1% of the vegetation in the basin experienced at least one abrupt change, with 2011 marking the peak year (9.8% affected area). Notably, 21.35% of pixels exhibited trend reversals, a phenomenon masked in previous linear trend studies. Regarding driving factors, positive abrupt changes were primarily driven by moderate warming and extreme precipitation anomalies, while the concentrated positive abrupt changes in 2011 were significantly influenced by the transition between dry and wet years and ecological restoration projects. In contrast, negative abrupt changes predominantly resulted from extreme temperatures and intensified human activities. These findings reveal the causes and response mechanisms of abrupt vegetation changes in the Yellow River Basin, providing new insights and perspectives for exploring the patterns of vegetation changes in this region.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113502"},"PeriodicalIF":7.0,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869611","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":"Probabilistic risk assessment and source identification of heavy metals in soil-rice systems in northern area of Fujian Province, China","authors":"Anni Wei ,&nbsp;Jin Jia ,&nbsp;Pengyan Chang ,&nbsp;Songliang Wang","doi":"10.1016/j.ecolind.2025.113504","DOIUrl":"10.1016/j.ecolind.2025.113504","url":null,"abstract":"<div><div>In this study, the ecological-human health risks and sources of heavy metals in paddy soils in the northern area of Fujian Province were investigated. The innovative ecological and health indicators that were evaluated in a probabilistic form were utilized rather than the traditional quotient form to make the results more accurate. By considering the bioaccessibility (BA) of heavy metals when calculating the hazard index (HI) for non-carcinogenic risks and total carcinogenic risk (TCR) for carcinogenic risk, the health risks caused by the ingestion of rice grains were significant. The HI and TCR values for both children and adults exceeded the standard values. In the meantime, the health risks of heavy metals in soils were not as high as expected. The geochemical baseline value (GBV) of Cd (0.087 mg/kg) was higher than the background concentration value (BCV) (0.054 mg/kg). The species sensitivity distribution (SSD) curves were built to determine the threshold values (hazardous concentration, HC_p) of soil heavy metals that can protect 5 %, 50 %, and 95 % of local rice varieties. The results showed that the allocation of rice production areas in the study site appeared to be largely in accordance with the needs of rice production. The outcomes of the APCA-MLR model indicated that the main sources included mining and associated industrial activities, natural sources, and agricultural activities, with a total contribution rate of 37.4 %, 30 %, and 32.6 % to the accumulation of heavy metals, respectively. The findings of this study contribute to the deeper understanding of the impact of heavy metal pollution in paddy soils on the health of local people and agroecosystems.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"174 ","pages":"Article 113504"},"PeriodicalIF":7.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143863788","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":"Reservoir impoundment alters surrounding plant physiological activities revealed by stable isotopes in tree rings","authors":"Lian Sun ,&nbsp;Yanpeng Cai ,&nbsp;Yesi Zhao ,&nbsp;Zixun Qi ,&nbsp;Xinsheng Liu ,&nbsp;Hongkai Gao ,&nbsp;Lu Wang ,&nbsp;Suyan Dai ,&nbsp;Siyuan Lu ,&nbsp;Jiejun Wang ,&nbsp;Xijie Yin","doi":"10.1016/j.ecolind.2025.113519","DOIUrl":"10.1016/j.ecolind.2025.113519","url":null,"abstract":"<div><div>Reservoir impoundment influences the growth of surrounding plants by altering the microclimate. However, the physiological mechanism of responses remains unclear. Due to the long tree-ring sequences and the distinct physiological mechanisms of stable isotopes in tree rings, we employed the technique of tree-ring carbon and oxygen isotopes to assess the physiological response to reservoir impoundment. We collected the tree rings of <em>Pinus yunnanensis</em> Franch. surrounding the Ertan Reservoir in southwestern China, and calculated the annual discrimination capabilities of ¹³C and ¹⁸O (i.e., Δ¹³C and Δ¹⁸O) in cellulose–α. Using moving window correlation analysis and a carbon–oxygen dual-isotope model, we identified shifts in the response patterns. The results indicate no significant difference in Δ¹⁸O across the impoundment timeline. Compared with before impoundment period (1980–1997), Δ¹³C increases during initial impoundment period (1998–2004), followed by a rapid decline and stabilization during stable impoundment period (2005–2020). The ¹⁸O enrichment in<!--> <em>P. yunnanensis</em> <!-->is mainly driven by the uptake of surface soil water in late-growing season (notably Sept.). Reservoir impoundment attenuates Sept. humidity declines, stabilizing surface soil moisture and stomatal conductance. In contrast, ¹³C discrimination correlates closely with environmental conditions in early growing season (especially Jun.). During the initial impoundment period, high humidity limits the stomatal conductance, while lower air temperature reduces photosynthetic activity. At the onset of the stable impoundment period, the regional climate changes reversely with reservoir microclimate unable to counteract the regional shifts. Under the interactive effects of temperature and humidity, the photosynthetic capacity increases markedly, leading to a decline in Δ¹³C. As environmental conditions stabilize in the stable impoundment period, Δ¹³C also remains unchanged. These findings will promote our ability to predict future impacts of large-scale engineering on terrestrial ecosystems under global climate change.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113519"},"PeriodicalIF":7.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864849","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 risk assessment and source identification of heavy metals in the sediments of the Danjiang River Basin: A quantitative method combining multivariate analysis and the APCS-MLR model","authors":"Zhiming Cao ,&nbsp;Hui Qian ,&nbsp;Yanyan Gao ,&nbsp;Kang Li ,&nbsp;Yixin Liu ,&nbsp;Xiaoxin Shi ,&nbsp;Siqi Li ,&nbsp;Weijie Zhao ,&nbsp;Shuhan Yang ,&nbsp;Panpan Tian ,&nbsp;Puxia Wu ,&nbsp;Yandong Ma","doi":"10.1016/j.ecolind.2025.113518","DOIUrl":"10.1016/j.ecolind.2025.113518","url":null,"abstract":"<div><div>The heavy metal content in river sediment is a sensitive indicator of pollution in aquatic ecosystems and plays a key role in understanding the risks, characteristics, and sources of heavy metal pollution in a region. This study combined traditional assessment methods with the Nemerow integrated risk index (NIRI), which is improved based on the potential ecological risk index (RI) and the Nemerow integrated pollution index (NIPI), to evaluate the pollution level of sediment in the Danjiang River. Based on principal component analysis (PCA), the absolute principal component score-multiple linear regression (APCS-MLR) model was employed to analyze the contribution of pollution sources. The study results showed that the average concentrations of most heavy metals exceeded their corresponding background values, and the distribution of heavy metal content was significantly influenced by human activities. The degree of pollution varied among the sampling sites, and the results of NIRI on the spatial distribution and severity of contamination are generally consistent with other assessment indicators, providing a more detailed and comprehensive delineation. The results of the multivariate statistical analysis indicate that Cu, Zn, Pb, and As mainly originated from natural sources, Cd and Ni primarily came from mixed sources such as agriculture and mining, while Cr was mainly associated with industrial activities. The APCS-MLR model results further confirm with high confidence that the sources of heavy metals in the sediments of the study area are complex, predominantly influenced by natural processes such as weathering and erosion. As the water source for the Middle Route of the South-to-North Water Diversion Project, the safety of the Danjiang River’s aquatic ecosystem is crucial for the health of nearly 100 million people in China. These findings provide an important foundation for Danjiang River water resource protection and offer a reference for ecological security and pollution prevention in other rivers.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113518"},"PeriodicalIF":7.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869609","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":"Multivariate geostatistical methods for analysing the contribution of urban lakes and neighbouring greenery to mitigating PM2.5 under stressor indicators","authors":"Han Liu ,&nbsp;Wenyu An ,&nbsp;Arkadiusz Przybysz ,&nbsp;Dingyi Hao ,&nbsp;Yimei Sun ,&nbsp;Junze Song ,&nbsp;Jiayi Sui ,&nbsp;Jiahan Sun ,&nbsp;Chunyang Zhu","doi":"10.1016/j.ecolind.2025.113489","DOIUrl":"10.1016/j.ecolind.2025.113489","url":null,"abstract":"<div><div>Maintaining the ecological integrity and functionality of ecosystems is one of the major challenges faced in the sustainable management of natural capital. Urban areas play a key role in this setting, providing multiple ecosystem services for a rapidly growing urban population worldwide while under constant pressure from several interacting natural and anthropogenic stressors. This paper targets the critical knowledge gap concerning how different stressor indicators – traffic (TD), building density (BD), building height (BH), percentage of impervious surface (PLAND_I) and land surface temperature (LST) – and their interactions affect the removal of particulate matter (PM_2.5) by urban blue-green infrastructure at multiple spatial scales. With spatial ranges varying with the area of blue-green infrastructure, the results showed that within the small-scale spatial range (90–450 m) the stressors LST, TD, PLAND_I and their interactions had a significant impact on PM_2.5; in the mesoscale spatial range (240–600 m), the stressors LST, TD, BH, PLAND_I, BD and their interactions had a strong impact on PM_2.5; while in the large-scale spatial range (390–1200 m), stressors of TD, PLAND_I, LST, BH and their interactions had a significant impact on PM_2.5. Additionally, several spatial structures of PM_2.5-stressor interactions were found, especially with larger lakes (exceeding 67.6 ha), which were dominated by negative correlations, which is singularity attributed to their greater capacity for PM_2.5 accumulation and microclimatic regulation and may mitigate the influence of stress factors. Importantly, this study confirmed that interactive stressors contributed more to the GAM model. Thus, overlooking interactive stressors may lead to an overestimation of PM removal by urban blue-green infrastructure. Regarding the spatial interactions of stressors-PM at multiple scales, spatial range conditions can change the properties of the blue-green infrastructure that determine the effective PM accumulation and identify the crucial stressor indices. A framework was developed to address the stressors’ mode of action and the extent to which the combined stressors affect PM mitigation. It allows the scientific community and relevant stakeholders to evaluate which stressors and their interactions in relation to PM removal share a common spatial pattern, and to assess independently the spatial covariation between stressors and PM removal at different spatial scales. It also demonstrates the possibility of using these stressor indicators as potential predictors of the impacts of land-use intensity on PM mitigation.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"174 ","pages":"Article 113489"},"PeriodicalIF":7.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143863718","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":"Climate controls the global distribution of soil organic and inorganic carbon","authors":"Yiheng Huang,&nbsp;Fangli Wei","doi":"10.1016/j.ecolind.2025.113514","DOIUrl":"10.1016/j.ecolind.2025.113514","url":null,"abstract":"<div><div>Soil organic carbon (SOC) and inorganic carbon (SIC) are key components of soil carbon, each playing a distinct role in soil health, carbon cycling, and climate regulation. However, their relative distributions across the global lands remains understudied. Here through analysing two data-driven global estimates of SOC and SIC, we found distinct distributions of SIC and SOC along vertical soil depths, among different land covers, soil orders and climate zones. While the density of SOC is higher in top soils, there are more SIC in deep soils. Vegetation shifts the relative distribution of SIC vs. SOC, with the ratio between SIC and SOC (<span><math><mrow><msub><mi>log</mi><mn>10</mn></msub><mfrac><mrow><mi>SIC</mi></mrow><mrow><mi>SOC</mi></mrow></mfrac></mrow></math></span>) decreasing progressively from bare soils, cropland, grassland to forest. Climate plays a major role in shaping <span><math><mrow><msub><mi>log</mi><mn>10</mn></msub><mfrac><mrow><mi>SIC</mi></mrow><mrow><mi>SOC</mi></mrow></mfrac></mrow></math></span>, accounting for 66 % of variations in top soil (0–0.3 m), 65 % in mid soil (0.3–1 m), and 74 % in deep soil (1–2 m). Higher temperature favours the preservation of SIC compared to SOC, as revealed by the positive relationship between <span><math><mrow><msub><mi>log</mi><mn>10</mn></msub><mfrac><mrow><mi>SIC</mi></mrow><mrow><mi>SOC</mi></mrow></mfrac></mrow></math></span> and MAT. The close link between key climate variables and the distribution of SIC vs. SOC indicates that future climate change is highly likely to alter the composition of soil carbon. Our finding provides support for differentiated soil carbon preservation strategies under different environment.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113514"},"PeriodicalIF":7.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870534","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":"Synergistic security relationships and risk measurement of water resources-social economy-ecological environment in Beijing-Tianjin-Hebei region","authors":"Yue Xu ,&nbsp;Li Yang ,&nbsp;Keyu Sun ,&nbsp;Junqi Zhu","doi":"10.1016/j.ecolind.2025.113512","DOIUrl":"10.1016/j.ecolind.2025.113512","url":null,"abstract":"<div><div>China’s productivity progress has promoted good socio-economic functioning, but has brought serious negative impacts on natural resources and eco-environment. Promoting synergistic security of water resources (W), social economy (S) and ecological environment (E) provides technical support for promoting regional economic growth, social progress and ecological harmony. This study constructed an index system based on stability (S), coordination (C) and resilience (R). Then the entropy weight-CRITIC method, coupled coordination degree model, and obstacle degree model were used to comprehensively evaluate the level of synergistic security of WSE-SCR in the Beijing-Tianjin-Hebei (BTH) region. Finally, the two-dimensional and three-dimensional joint risk probability distributions of different provincial regions were explored by combining the Copula function. The results showed that the level of synergistic security in the BTH region increased from 2006 to 2022, and the multi-year average value was within the security range, specifically Beijing (0.69) &gt; Hebei (0.66) &gt; Tianjin (0.65). The key factors affecting the WSE-SCR are per capita water resources (S1), per capita water consumption (S3), proportion of secondary industry (S5), ecological water use ratio (C4), and investment in infrastructure construction (R8). In terms of two-dimensional joint risk probability, the C-R of Beijing and the S-R of Tianjin and Hebei had the highest probability of security risk, which were 0.5598, 0.5308 and 0.5488, respectively. The three-dimensional joint risk probability of the S-C-R of Beijing, Tianjin and Hebei (S ≤ 0.6, C ≤ 0.6, and R ≤ 0.6) were greater than 30 %, which were 0.389, 0.341 and 0.352, and increased with the increase of single dimension risk. This study can provide scientific information for advancing the synergistic security and sustainable improvement of WSE in arid zones.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113512"},"PeriodicalIF":7.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869608","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":"Analysis of the spatio-temporal characteristics and driving forces of greenness in mega urban agglomerations in China","authors":"Shaoyu Wang ,&nbsp;Dongmei Yan ,&nbsp;Yayang Lu ,&nbsp;Wanrong Wu ,&nbsp;Ying Sun ,&nbsp;Zhe Zhang","doi":"10.1016/j.ecolind.2025.113472","DOIUrl":"10.1016/j.ecolind.2025.113472","url":null,"abstract":"<div><div>Timely monitoring of greenness dynamics in urban agglomerations and analyzing their driving factors are important for sustainable development. However, current research on vegetation greenness at the scale of urban agglomerations remains limited. This study examines the greenness dynamics and its driving factors in China’s four major urban agglomerations Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), Pearl River Delta (PRD), Chengdu–Chongqing (CC) at a 30-meter spatial resolution over a long period (2000–2023). The use of an innovative integrated approach, combining the Gap Filling and Savitzky–Golay filtering (GF-SG) method, pixel dichotomy model, spatiotemporal dynamic analysis and geographical detector, provides a more comprehensive understanding of greenness dynamics in urban agglomerations. The results indicate several key points: 1.The proportion of areas where vegetation greenness increased (27.69 %, 14.10 %, 31.56 %, 23.09 %) is consistently larger than the proportion of areas where greenness decreased (4.3 %, 6.78 %, 5.11 %, 1.62 %) within BTH, YRD, PRD, CC. Greenness is dramatically increasing in all urban centers, but significantly decreasing at the edges of urban expansion; 2. Land cover conversions emerged as the dominant driver of greenness changes (the highest Q-value is 0.5743), which indicates that land cover conversions play a greater role than natural factors. 3. The expansion of urban land and ecological land restoration explain the main reasons for the decrease and increase in greenness. Meanwhile, there are differences in the primary land cover conversions corresponding to the greenness changes among the four urban agglomerations. These findings not only contribute to understanding urban greenness dynamics but also offer a new perspective on the role of land cover conversions in shaping vegetation patterns.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"174 ","pages":"Article 113472"},"PeriodicalIF":7.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143858821","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}