Ecological Indicators最新文献

{"title":"Spatial and temporal variation of water stress in China and its driving factors: A multi-scale analysis","authors":"Jianmin Qiao ,&nbsp;Qin Zhang ,&nbsp;Jing Shao ,&nbsp;Qian Cao ,&nbsp;Haimeng Liu ,&nbsp;Furong Lv","doi":"10.1016/j.ecolind.2024.112820","DOIUrl":"10.1016/j.ecolind.2024.112820","url":null,"abstract":"<div><div>Water resources are fundamental for sustaining natural ecosystems and human activities, playing a critical role in the sustainable development of the regional environment. Under the dual pressures of human activities and climate change, however, the stress on water resources has become increasingly evident, emerging as one of the greatest global risks for the next decade. In this study, by applying the water stress index, Lorenz curve, and Theil index, we explored the spatiotemporal patterns and inequality distribution characteristics of water resource stress across two scales: catchment and basin. Additionally, we used partial least squares regression to identify the key factors influencing water resource stress. The results indicated significant regional variations in water stress across China during 2002 to 2020. At the catchment scale, areas with a water stress index greater than 0.4 were distributed in the eastern, northeastern and northwestern regions. While at the basin scale, a north–south pattern emerged with lower stress in the south and higher stress in the north. The Haihe and Huaihe river basins exhibited the highest water stress. The Lorenz curve deviated significantly from the line of absolute equality, indicating a high degree of inequality in regional water resource stress. The Theil index increased from 1.26 to 1.50, showing a slight upward trend in inequality. Analysis of the driving factors revealed that the Yellow River Basin was primarily influenced by GDP and population, the Songhua River Basin was affected by population and urban land use, and the Southwest River Basin is driven mainly by vegetation cover. Overall, precipitation was the most critical driver affecting water stress, predominantly exerting a negative influence. This study provides a theoretical basis for alleviating regional water stress and offers valuable insights for the scientific planning and management of water resources.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112820"},"PeriodicalIF":7.0,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662292","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":"Invasion of Pine Wilt Disease: A threat to forest carbon storage in China","authors":"Bohai Hu ,&nbsp;Wenjiang Huang ,&nbsp;Zhuoqing Hao ,&nbsp;Jing Guo ,&nbsp;Yanru Huang ,&nbsp;Xiangzhe Cheng ,&nbsp;Jing Zhao ,&nbsp;Quanjun Jiao ,&nbsp;Biyao Zhang","doi":"10.1016/j.ecolind.2024.112819","DOIUrl":"10.1016/j.ecolind.2024.112819","url":null,"abstract":"<div><div>China’s forests, which balance atmospheric carbon (C) levels through photosynthesis, play a crucial role in combating global climate change. The emergence of Pine wilt disease (PWD), caused by the pine wood nematode (PWN, <em>Bursaphelenchus xylophilus</em>), has challenged the stability of these forests, leading to significant tree mortality and disrupting the original ecological balance. However, the impact of PWD on carbon storage and recovery in Chinese forests remains unclear. In this study, we integrated multiple data sources, including forest surveys, remote sensing, and meteorological observations, and applied a method of finely partitioning the resistance of host pine trees across China. Using the MaxEnt model, a live carbon risk model, and a C recovery REGIME model that incorporates disturbance mechanisms, we predicted the forest C risk loss caused by the comprehensive invasion of PWD and assessed the C recovery time for affected forests. We estimate that the total risk of C loss due to PWD invasion under current climate conditions in Chinese forests is 483.23 Tg C, with an average C recovery time of 13.95 years. The main risk areas for PWD are concentrated in the southern coastal regions of China and adjacent provinces, presenting a risk spillover pattern that radiates from focal areas outward. The six provinces with the highest forest risk degree (risk C/total regional C) are, in order, Fujian (13.69%), Zhejiang (9.42%), Hunan (7.49%), Guangxi (7.40%), Jiangxi (7.35%), and Guangdong (7.05%). Our findings indicate that the severe consequences of PWD invasion have transformed affected forests from C sinks to sources. This underscores the urgency of implementing effective measures to block its introduction and spread, thereby promoting the recovery and sustainable development of forest ecosystems.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112819"},"PeriodicalIF":7.0,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662230","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":"Developing cyanobacterial bloom indicators from spatiotemporal differences in productivity and water quality across a lake-stream network","authors":"Jordyn Brown ,&nbsp;Aaron Krivchenia ,&nbsp;Matt J. Pierce ,&nbsp;Courtney E. Richmond ,&nbsp;Nathan Ruhl","doi":"10.1016/j.ecolind.2024.112838","DOIUrl":"10.1016/j.ecolind.2024.112838","url":null,"abstract":"<div><div>Cyanobacterial Harmful Algal Blooms (cHABs) are an increasingly common occurrence in inland waters and carry ecological, economic, and public health consequences. It is difficult to predict when a cHAB will occur and there is a need to develop methods (indicators) to accurately predict the development of cHABs Here, we studied planktonic primary production (chlorophyll and phycocyanin) in a lake-stream network that is prone to cHABs in southern New Jersey, during bloom and non-bloom years. Primary productivity was lake-dependent, with productivity patterns interacting across sampling locations and years (p &lt; 0.001 for both chlorophyll and phycocyanin). The lake with recurrent cHABs had higher productivity readings in both years, but the sampling location within this lake had a large influence on the observed primary productivity patterns. Productivity differences among lakes were greater in the bloom year compared to the non-bloom year. The bloom year was characterized by a strong correlation between conductivity and nitrate readings, suggesting that cHABs in our study system are associated with nutrient-laden runoff. The linear progression of primary productivity readings was a better indicator for the onset of cHAB conditions than temporal autocorrelation using weekly samples.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112838"},"PeriodicalIF":7.0,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142661878","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":"Evaluating the trade-offs between nutrient and cadmium levels in soils in northeastern China: Accounting for variations in soil factors","authors":"Guohao Xie ,&nbsp;Yang Yang ,&nbsp;Ying Hou ,&nbsp;Bo Wang ,&nbsp;Weiping Chen","doi":"10.1016/j.ecolind.2024.112795","DOIUrl":"10.1016/j.ecolind.2024.112795","url":null,"abstract":"<div><div>Agricultural soils have relied on the application of fertilizers to enhance soil fertility and yields in response to increasing food demands. However, the potentially hazardous trace elements that accumulate in soils have been largely overlooked. In this study, we set out to determine the soil factor indicators in croplands using Exploratory Factor Analysis to illuminate the trade-off between surplus soil nutrients and cadmium (Cd) accumulation as a result of fertilizer application. The research in northeastern China highlights the fact that studies tend to ignore the accumulation and distribution of hazardous heavy metals in production fields in favor of an over-emphasis on soil fertility indicators; an ultimately unsustainable approach. The model showed that soil nutrient could be identified based on three soil factors: soil organic matter, soil available nutrients, and soil nutrient buffer structures. Fertilization enhanced the level of available nutrients and significantly increased both soil organic matter and available phosphorus by 0.71 % and 11 mg kg⁻¹, respectively. However, the long-term application of phosphorus (P) leads to a P-surplus and leaves soils more susceptible to Cd accumulation. The 90th percentile estimate of soil Cd concentration was 1.4 times higher than the P-optimal level. Scenario analyses of long-term fertilizer management indicated that, over a 50-year simulation period, the impact of Cd accumulation in soils in traditional agriculture was insignificant. However, prolonged application of excess P-fertilizer would lead to a continuous increase in the concentration of accumulated Cd from 0.17 mg kg⁻¹ to 0.40 mg kg⁻¹. Trade-off and scenario analyses guide agricultural fertilization practices to preserve soil quality while sustaining productivity.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112795"},"PeriodicalIF":7.0,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662290","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":"Modelling and spatial prediction of earthworms ecological-categories distribution reveal their habitat and environmental preferences","authors":"Gabriel Salako ,&nbsp;Andrey Zaitsev ,&nbsp;Bibiana Betancur-Corredor ,&nbsp;David J. Russell","doi":"10.1016/j.ecolind.2024.112832","DOIUrl":"10.1016/j.ecolind.2024.112832","url":null,"abstract":"<div><div>Earthworms are one of the important soil animals and have been generally described as soil engineers. Knowledge on environmental conditions driving the distribution and population of this soil animal and the habitat which support these conditions especially at the ecological level is required to understand their responses to these environmental conditions at different habitats so as to guide its usage as bio indicator of soil quality and health. In this study we use RandomForest (RF), a machine learning algorithm to model species distribution, density/abundance based (SDM/SAM) and predict the biodiversity distribution (richness and density, ind.m⁻²) of three basic earthworms ecological categories: epigeic, endogeic and anecic (including the epi-anecic subcategory) across soil and climate variables at multiple habitat type/land uses in Germany. Our study shows there are spatial/ geographic variation in the distribution of the species richness and density among the three earthworms’ ecological categories. Also their environmental and habitat preferences are equally different, while epigeic species are predicted to be climate driven mostly in forests, endogeics are predicted to be the most diverse (in richness and density), but are mostly driven by soil textural contents (clay and silt) and found primarily in arable and grassland. Vineyard and crop flood plain are predicted to be suitable and the preferred habitat for anecics/epi-anecics. This study also identify optimum environmental gradient at which the species density is at the peak in each of the earthworm’s ecological category which would not only provide guide on soil biodiversity monitoring but also the soil health status.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112832"},"PeriodicalIF":7.0,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662162","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":"Spatio-temporal variation in arthropod-plant interactions: A direct comparison of eDNA metabarcoding of tree crop flowers and digital video recordings","authors":"Joshua H. Kestel ,&nbsp;Philip W. Bateman ,&nbsp;David L. Field ,&nbsp;Nicole E. White ,&nbsp;Ben L. Phillips ,&nbsp;Paul Nevill","doi":"10.1016/j.ecolind.2024.112827","DOIUrl":"10.1016/j.ecolind.2024.112827","url":null,"abstract":"<div><div>Collating data about natural capital and the ecosystem services that underpin agricultural productivity, such as the activity of beneficial (e.g., pollinators) and antagonistic (e.g., plant pests) native and introduced arthropod taxa, is critical for timely management strategies. To date, these monitoring efforts have largely relied upon conventional survey and monitoring methods (e.g., sweep netting and morphological identifications), which are difficult to implement at the large scale of agriculture. Environmental DNA (eDNA) metabarcoding is a molecular method that amplifies trace amounts of DNA deposited by organisms from diverse substrates including soil, plant tissue and even air. In this study, we used eDNA metabarcoding of tree flowers, complemented with digital video recording (DVR) devices, to detect temporal, fine- and large-scale arthropod community changes across two <em>Persea americana</em> (‘Hass’ avocado) orchards. In total, we detected 42 arthropod families with eDNA metabarcoding. This molecular method detected five times the number of unique taxa (<em>N</em> = 50) compared to the DVRs (<em>N</em> = 10), nearly all of which are unmanaged native species. The number of arthropod eDNA detections increased by 14 % during peak flowering and included species from different functional groups including known arthropod pollinators, pests, parasites and predators. At fine-spatial scales, inflorescence samples collected in the upper and lower canopy show that Hymenoptera taxa were 13 % more likely to be detected in the upper canopy. While at large-spatial scales, eDNA metabarcoding showed that the arthropod communities in both orchards shared less than 50 % similarity at low flowering and became more similar towards peak flowering. With occupancy modelling, we determined that arthropod length did not correlate with eDNA detection probability. Our findings highlight the value of eDNA-based monitoring and illustrate that agroecosystem management requires a growing awareness that the production boundary has expanded, and that the goods and services that unmanaged arthropod species provide need to be included on the balance sheet.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112827"},"PeriodicalIF":7.0,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662291","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 multidimensional urbanization on sustainable development goals (SDGs): A long-term analysis of the 31 provinces in China","authors":"Xiaoxuan Li ,&nbsp;Wen Song ,&nbsp;Shisong Cao ,&nbsp;You Mo ,&nbsp;Mingyi Du ,&nbsp;Ziyue He","doi":"10.1016/j.ecolind.2024.112822","DOIUrl":"10.1016/j.ecolind.2024.112822","url":null,"abstract":"<div><div>Sustainable development, intimately linked to the survival of the global human population, has garnered immense attention. The rapid pace of urbanization has exerted a profound influence on the achievement and progress towards the United Nations’ Sustainable Development Goals (SDGs). Nevertheless, a knowledge gap persists regarding the comprehensive impact of urbanization on these goals. The present study delved into the multifaceted impacts of urbanization on SDGs through a comprehensive analysis of four distinct urbanization dimensions: land urbanization (LURB), economic urbanization (EURB), population urbanization (PURB), and social urbanization (SURB). We analyzed the spatiotemporal characteristics of the four-dimensional urbanizations in 31 provinces of China from 1995 to 2015 using impervious surface and statistical data. We employed the Spearman coefficient to investigate the interaction between urbanizations and 17 SDGs. Furthermore, we delved into how economic zone settings influenced these interactions. The results reveal that land expansion, GDP per capita, and the degree of social consumption exhibited stronger synergies with SDGs, whereas the share of the secondary sector and the urban population rate demonstrated more trade-off effects. This underscores the importance of considering the multifaceted nature of urbanization when striving to achieve the SDGs. Additionally, the diverse impact of urbanization patterns on SDG implementation across various economic zones emphasizes the need for tailored and region-specific strategies to maximize the positive outcomes of urbanization and promote sustainable development.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112822"},"PeriodicalIF":7.0,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662153","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":"Phosphorus transport process and driving mechanism in the sediment of farm ponds in small watersheds of three Gorges Reservoir area","authors":"Yifan Zhao,&nbsp;Wei Zhang,&nbsp;Weihua Zhang","doi":"10.1016/j.ecolind.2024.112787","DOIUrl":"10.1016/j.ecolind.2024.112787","url":null,"abstract":"<div><div>The water quality health of the farm ponds in the small watersheds of the Three Gorges Reservoir Area is critical to maintaining agricultural productivity. The main challenge in managing the water quality is predicting and controlling the release of total phosphorus (TP) from endogenous pollution in the substrate. Numerous studies have shown that endogenous pollution release from large water bodies like lakes is influenced by factors such as temperature and pH. However, knowledge about the response mechanisms in smaller water bodies, such as farm ponds, is still lacking. This study focuses on TP, using indoor simulation tests and orthogonal tests to investigate the transport and transformation of TP in four representative farm ponds located in Ruxi Town, at the heart of the Three Gorges Reservoir Area. Results showed that seasonal variations led to temperature changes thereby significantly affect TP release, with the highest release rates occurring in summer when the temperature was highest. The farm ponds demonstrated a significant annual cycle in phosphorus source-sink dynamics. Furthermore, factors including pH and water depth influenced the release rates; acidic conditions promoted phosphorus release from the substrate more effectively than alkaline conditions. Additionally, disturbances at lower intensities were observed to inhibit TP release. Building on these findings, this study further explored the advantages and limitations of using multiple regression analysis and BP Neural Network models for modeling phosphorus release and predicting annual TP release. Ultimately, the study proposes measures to reduce and control endogenous pollution, laying a foundation for managing eutrophication and protecting aquatic health in farm ponds.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112787"},"PeriodicalIF":7.0,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662152","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":"How can the natural background and ecological & environment promote the green and sustainable development of Chinese tourist attractions?","authors":"Ning Yan ,&nbsp;Jing Zhang ,&nbsp;Bing Xia ,&nbsp;Shihua Li ,&nbsp;Wen Yang","doi":"10.1016/j.ecolind.2024.112813","DOIUrl":"10.1016/j.ecolind.2024.112813","url":null,"abstract":"<div><div>In the context of the global carbon peak and carbon neutrality initiatives and post-pandemic, studying the green and sustainable development of tourist attractions is of great significance for the sustainable utilization of tourism resources. This study focuses on tourist attractions in 30 provinces in China from 2001 to 2019, establishes an input–output indicator system for economic efficiency and eco-efficiency, and uses the Super-SBM model in Data Envelopment Analysis to calculate the economic efficiency and eco-efficiency of tourist attractions in China. To analyze the natural background and environmental driving factors that affect eco-efficiency, as well as the interaction between these factors, using a geographic detector model, and propose a green and sustainable development path for tourist attractions. The research results indicate that the eco-efficiency of Chinese tourist attractions was higher than the economic efficiency, and both showed a downward trend. The proportion of altitude and nature reserve area to the area under the jurisdiction, as well as the total investment in environmental pollution control, have a significant impact on eco-efficiency; The interaction between temperature, precipitation, and normalized difference vegetation index (NDVI), and the proportion of nature reserves in the jurisdiction and the total investment in environmental pollution control, is significantly enhanced, indirectly affecting the eco-efficiency of Chinese tourist attractions. Among the natural factors, temperature, precipitation, and NDVI all could interact with altitude to significantly the impacts on the eco-efficiency of Chinese tourist attractions. The research aims to provide a Chinese solution for developing tourist attractions in developing countries similar to China.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112813"},"PeriodicalIF":7.0,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662161","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":"Study on spatiotemporal changes of wetlands based on PLS-SEM and PLUS model: The case of the Sanjiang Plain","authors":"Jinhao Shi ,&nbsp;Peng Zhang ,&nbsp;Yang Liu ,&nbsp;Le Tian ,&nbsp;Yazhuo Cao ,&nbsp;Yue Guo ,&nbsp;Ji Li ,&nbsp;Yunhan Wang ,&nbsp;Junhan Huang ,&nbsp;Ri Jin ,&nbsp;Weihong Zhu","doi":"10.1016/j.ecolind.2024.112812","DOIUrl":"10.1016/j.ecolind.2024.112812","url":null,"abstract":"<div><div>Wetlands are among the most productive ecosystems and play crucial roles in relation to biodiversity conservation and various ecosystem services. However, rapid urbanization and environmental changes have led to the loss of a significant number of wetlands, making it imperative to understand the driving forces behind wetland changes. This study employed Partial Least Squares Structural Equation Modeling (PLS-SEM) and the Patch-generating Land Use Simulation (PLUS) model to investigate the influences of natural factors and urbanization on wetland distribution. Based on the driving factors, simulations were conducted for three scenarios—Natural Increase Scenario (NIS), Economic Development Scenario (EDS), and Wetland Protection Scenario (WPS)—projecting the wetland distribution in the Sanjiang Plain until 2050. Results indicate that from 1990 to 2020, the wetland area increased by 9,548.58 km², with paddy fields increasing by 12,995.73 km² and marsh wetlands decreasing by 1,031.9 km². The factors driving wetland distribution varied across different periods. Between 1990 and 2000, topography and urbanization significantly influenced wetland distribution, whereas climate factors became gradually more significant between 2010 and 2020. Furthermore, in addition to exerting direct impacts on wetland distribution, urbanization and climate factors can indirectly affect wetland distribution by influencing topography and soil. Future development scenarios indicate an inevitable increase in paddy field areas and decrease in wetland areas. This framework provides an effective approach for exploring regional wetland changes and supporting regional wetland conservation and future sustainable development.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112812"},"PeriodicalIF":7.0,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662163","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}