Pub Date : 2026-01-01DOI: 10.1016/j.ecolind.2025.114567
Yiqiong Guo , Tianyang Fu , Zhenhao Zhang , Yi Hu , Ruiyu Ai , Yunxiang Cheng
Grazing is a major land use in natural grasslands; however, spatial use differences among livestock types and the underlying mechanisms in mixed grazing systems remain unclear. In this study, we used global positioning system-accelerometer collars, unmanned aerial vehicle-based multispectral remote sensing, and ground vegetation quadrats to quantify the spatial foraging patterns of cattle and sheep and identify their driving factors in a typical family ranch in Xilingol, Inner Mongolia. We found that the foraging behavior of cattle was significantly influenced by the aboveground biomass. They clearly tended to choose areas with high normalized vegetation index (NDVI) values, which are characterized by high vegetation coverage and productivity. In contrast, sheep exhibited a more uniform foraging distribution, favoring plant species with higher nutrient contents, particularly total nitrogen. Structural equation modeling revealed that grassland resources influenced livestock foraging not only directly as suggested by indicators such as the NDVI, but also indirectly by regulating plant nitrogen and phosphorus concentrations. Overall, cattle had a quantity-oriented foraging strategy, whereas sheep showed a quality-oriented preference. Our findings suggest that the NDVI and plant total nitrogen can serve as complementary indicators for grassland monitoring and degradation assessment in mixed grazing systems, providing a scientific basis for spatially explicit livestock allocation, overgrazing mitigation, and grassland restoration management.
{"title":"Differential grassland use by livestock in Inner mongolian pastures: cattle seek biomass, sheep favor nutritional quality","authors":"Yiqiong Guo , Tianyang Fu , Zhenhao Zhang , Yi Hu , Ruiyu Ai , Yunxiang Cheng","doi":"10.1016/j.ecolind.2025.114567","DOIUrl":"10.1016/j.ecolind.2025.114567","url":null,"abstract":"<div><div>Grazing is a major land use in natural grasslands; however, spatial use differences among livestock types and the underlying mechanisms in mixed grazing systems remain unclear. In this study, we used global positioning system-accelerometer collars, unmanned aerial vehicle-based multispectral remote sensing, and ground vegetation quadrats to quantify the spatial foraging patterns of cattle and sheep and identify their driving factors in a typical family ranch in Xilingol, Inner Mongolia. We found that the foraging behavior of cattle was significantly influenced by the aboveground biomass. They clearly tended to choose areas with high normalized vegetation index (NDVI) values, which are characterized by high vegetation coverage and productivity. In contrast, sheep exhibited a more uniform foraging distribution, favoring plant species with higher nutrient contents, particularly total nitrogen. Structural equation modeling revealed that grassland resources influenced livestock foraging not only directly as suggested by indicators such as the NDVI, but also indirectly by regulating plant nitrogen and phosphorus concentrations. Overall, cattle had a quantity-oriented foraging strategy, whereas sheep showed a quality-oriented preference. Our findings suggest that the NDVI and plant total nitrogen can serve as complementary indicators for grassland monitoring and degradation assessment in mixed grazing systems, providing a scientific basis for spatially explicit livestock allocation, overgrazing mitigation, and grassland restoration management.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"182 ","pages":"Article 114567"},"PeriodicalIF":7.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145920689","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}
Pub Date : 2026-01-01DOI: 10.1016/j.ecolind.2025.114553
Guilherme Santana Lustosa , Adalberto José Santos , Antonio Domingos Brescovit , Bárbara Teixeira Faleiro , Gustavo Rodrigo Sanchez Ruiz , Pedro Henrique Martins , Leonardo Sousa Carvalho
Riparian zones in the Brazilian Cerrado are increasingly threatened by agricultural expansion, deforestation, and land-use change, with significant implications for biodiversity conservation. Spiders are ecologically important predators and bioindicators, yet little is known about how they respond to changes in vegetation structure in riparian habitats. This study aims to assess the influence of canopy cover and understory complexity on the diversity, abundance, and composition of understory spider assemblages in riparian zones. We sampled 3260 adult spiders across 30 first- to fourth-order streams in the Cerrado, using standardized beating tray methods, and measured habitat structure variables. Our results showed that canopy cover had a positive effect on spider abundance and species richness, while understory complexity was significantly related only to species richness. Vegetation structure had a limited effect on species composition. Using threshold indicator taxa analysis (TITAN), we identified ecological thresholds for canopy cover between 58 % and 77 %, and 16 spider taxa were classified as indicators of change along this gradient. The study demonstrates that canopy cover is a significant driver of spider diversity and that threshold-based metrics can help identify sensitive points of ecosystem change.
Implications for insect conservation: Riparian zones in the Cerrado biome should be prioritized for conservation and restoration, especially where canopy cover has been markedly diminished. Preserving canopy cover above 60 % is likely essential to maintain both the structural integrity and functional dynamics of understory spider assemblages. As reliable bioindicators at species and community levels, spiders can effectively reflect riparian habitat quality. Therefore, conservation strategies ought to encompass restricting deforestation along riparian margins, enforcing buffer-zone regulations and reestablishing native vegetation to enhance habitat complexity. These measures are crucial not only for protecting spider diversity but also for sustaining the ecosystem services they provide, such as natural pest control and trophic regulation at the aquatic–terrestrial interface.
{"title":"Environmental thresholds in canopy cover shape spider assemblages in Cerrado riparian zones","authors":"Guilherme Santana Lustosa , Adalberto José Santos , Antonio Domingos Brescovit , Bárbara Teixeira Faleiro , Gustavo Rodrigo Sanchez Ruiz , Pedro Henrique Martins , Leonardo Sousa Carvalho","doi":"10.1016/j.ecolind.2025.114553","DOIUrl":"10.1016/j.ecolind.2025.114553","url":null,"abstract":"<div><div>Riparian zones in the Brazilian Cerrado are increasingly threatened by agricultural expansion, deforestation, and land-use change, with significant implications for biodiversity conservation. Spiders are ecologically important predators and bioindicators, yet little is known about how they respond to changes in vegetation structure in riparian habitats. This study aims to assess the influence of canopy cover and understory complexity on the diversity, abundance, and composition of understory spider assemblages in riparian zones. We sampled 3260 adult spiders across 30 first- to fourth-order streams in the Cerrado, using standardized beating tray methods, and measured habitat structure variables. Our results showed that canopy cover had a positive effect on spider abundance and species richness, while understory complexity was significantly related only to species richness. Vegetation structure had a limited effect on species composition. Using threshold indicator taxa analysis (TITAN), we identified ecological thresholds for canopy cover between 58 % and 77 %, and 16 spider taxa were classified as indicators of change along this gradient. The study demonstrates that canopy cover is a significant driver of spider diversity and that threshold-based metrics can help identify sensitive points of ecosystem change.</div><div><strong>Implications for insect conservation:</strong> Riparian zones in the Cerrado biome should be prioritized for conservation and restoration, especially where canopy cover has been markedly diminished. Preserving canopy cover above 60 % is likely essential to maintain both the structural integrity and functional dynamics of understory spider assemblages. As reliable bioindicators at species and community levels, spiders can effectively reflect riparian habitat quality. Therefore, conservation strategies ought to encompass restricting deforestation along riparian margins, enforcing buffer-zone regulations and reestablishing native vegetation to enhance habitat complexity. These measures are crucial not only for protecting spider diversity but also for sustaining the ecosystem services they provide, such as natural pest control and trophic regulation at the aquatic–terrestrial interface.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"182 ","pages":"Article 114553"},"PeriodicalIF":7.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145920943","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}
Pub Date : 2026-01-01DOI: 10.1016/j.ecolind.2025.114581
Yao Zhang , Yanan Jiang , Qihao Ma , Ya Yan , Jianzhe Hou , Xun Zhang , Jianqiang He , Xiaojun Wang , Qiang Li , Shikun Sun
The demand for agricultural products has been increasing in many developing countries all over the world due to improved living standards. It has generated significant rise in agricultural water consumption and ever-expanding irrigation area which are very sensitive to both climate change and farmers' irrigation and adaption strategies. In canal and well combined irrigation areas, because of ever increasing need for higher yield and intense variations in surface water supply and extreme weather conditions due to climate change, both groundwater over-exploitation in dry seasons and farmland inundation in wet seasons could happen. The ratios of canal irrigation (CI) to well irrigation (WI) in different regions with various cropping structures have to be carefully determined to avoid negative environmental impacts. To address these challenging and complex issues, this work developed a tightly coupled simulation-optimization framework based on FloPy and the many-objective genetic algorithm (NSGA-III) within the Pymoo framework. This approach enabled the evaluation of five key indicators: water productivity, total income, total water loss, equity (quantified by the Gini coefficient) and groundwater level fluctuation. The framework could provide actionable insights to support decision-making in ecological, environmental and economic contexts. The model was then tested and validated in Jinghuiqu irrigation area in Shaanxi Province (China) to obtain the Pareto Front for wet, normal and dry years. The key findings are as follows. (1) A reasonable canal-well combined irrigation water volume and proportion could be determined by the proposed simulation-optimization framework; (2) the average groundwater level fluctuations of recommend schemes are +0.82 m, +0.063 m, -0.26 m in wet, normal and dry years, respectively; (3) the ratios of canal-well of recommend schemes are 1:2.25, 1:1.19, and 1:1.74 in wet, normal and dry years; (4) different ratios of canal irrigation to well irrigation is crucial for sustainable groundwater development and managed aquifer recharge; (5) the results reveal distinct spatial-temporal variations across different administrative districts, thereby highlighting the considerable potential of the tightly coupled simulation-optimization model for integrated management of surface water and groundwater in climate sensitive canal-well combined irrigation area when dealing with many objectives.
{"title":"A many-objective simulation-optimization framework for integrated water resources management in canal-well combined irrigation area based on FloPy and NSGA-III","authors":"Yao Zhang , Yanan Jiang , Qihao Ma , Ya Yan , Jianzhe Hou , Xun Zhang , Jianqiang He , Xiaojun Wang , Qiang Li , Shikun Sun","doi":"10.1016/j.ecolind.2025.114581","DOIUrl":"10.1016/j.ecolind.2025.114581","url":null,"abstract":"<div><div>The demand for agricultural products has been increasing in many developing countries all over the world due to improved living standards. It has generated significant rise in agricultural water consumption and ever-expanding irrigation area which are very sensitive to both climate change and farmers' irrigation and adaption strategies. In canal and well combined irrigation areas, because of ever increasing need for higher yield and intense variations in surface water supply and extreme weather conditions due to climate change, both groundwater over-exploitation in dry seasons and farmland inundation in wet seasons could happen. The ratios of canal irrigation (CI) to well irrigation (WI) in different regions with various cropping structures have to be carefully determined to avoid negative environmental impacts. To address these challenging and complex issues, this work developed a tightly coupled simulation-optimization framework based on FloPy and the many-objective genetic algorithm (NSGA-III) within the Pymoo framework. This approach enabled the evaluation of five key indicators: water productivity, total income, total water loss, equity (quantified by the Gini coefficient) and groundwater level fluctuation. The framework could provide actionable insights to support decision-making in ecological, environmental and economic contexts. The model was then tested and validated in Jinghuiqu irrigation area in Shaanxi Province (China) to obtain the Pareto Front for wet, normal and dry years. The key findings are as follows. (1) A reasonable canal-well combined irrigation water volume and proportion could be determined by the proposed simulation-optimization framework; (2) the average groundwater level fluctuations of recommend schemes are +0.82 m, +0.063 m, -0.26 m in wet, normal and dry years, respectively; (3) the ratios of canal-well of recommend schemes are 1:2.25, 1:1.19, and 1:1.74 in wet, normal and dry years; (4) different ratios of canal irrigation to well irrigation is crucial for sustainable groundwater development and managed aquifer recharge; (5) the results reveal distinct spatial-temporal variations across different administrative districts, thereby highlighting the considerable potential of the tightly coupled simulation-optimization model for integrated management of surface water and groundwater in climate sensitive canal-well combined irrigation area when dealing with many objectives.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"182 ","pages":"Article 114581"},"PeriodicalIF":7.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145920635","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}
Pub Date : 2026-01-01DOI: 10.1016/j.ecolind.2025.114531
Pingping Luo , Ziwen Wang , Manting Luo , Jiachao Chen , Yubin Zhang , Meimei Zhou , Jianxin Zhang , Binaya Kumar Mishra , Maochuan Hu , Ahmed Elbeltagi
Rapidly growing population and urbanization have led to serious urban water environment problems. Rainwater is increasingly recognized and utilized as a viable alternative water source in response to these issues. Rainfall pattern, tank size and water use scenarios significantly affect the efficiency of RainWater Harvesting (RWH) systems. To better compare and analyze the impacts of the above factors on the reliability and efficiency of RWH systems, this study conducted experiments in three Chinese cities within different climate zones across three representative years (wet year, average year and dry year). Robust analysis was performed based on careful data pre-processing, which excludes irrelevant rainfall data. A computational tool was developed to evaluate the performance and reliability of rainwater management for RWH systems. Performance analysis and optimization of the RWH system for multi-story residential buildings based on a water balance model were conducted in three Chinese cities. We combined the roof catchment area, water tank volume, and rainwater utilization scenarios to obtain the rainwater harvesting efficiency, overflow ratio, water saving efficiency, and reliability charts of RWH system. In cities with large rainfall (Wuhan), before the maximum rainwater collection size is reached, increasing the tank size can significantly enhance the efficiency of the RWH system. In cities with average or low rainfall (Xi'an and Xining), the maximum rainfall storage capacity of the tank is easily reached, so rainfall is the main factor affecting the efficiency of the RWH system. Meanwhile, the water use scenario is the main factor affecting the reliability of the RWH system in cities with average or low rainfall. Demand scenario critically determines reliability—irrigation (B) achieves high reliability (up to ∼78 %), whereas toilet flushing (A) or combined use (C) exhibit much lower reliability (as low as 2.74 %) due to demand exceeding supply. Results of the study provide decision support for urban water authorities to effectively mitigate urban water supply deficiencies and urban flooding risks.
{"title":"Spatiotemporal assessment of rainwater harvesting efficiency for multi-story residential buildings across different climate zones in China","authors":"Pingping Luo , Ziwen Wang , Manting Luo , Jiachao Chen , Yubin Zhang , Meimei Zhou , Jianxin Zhang , Binaya Kumar Mishra , Maochuan Hu , Ahmed Elbeltagi","doi":"10.1016/j.ecolind.2025.114531","DOIUrl":"10.1016/j.ecolind.2025.114531","url":null,"abstract":"<div><div>Rapidly growing population and urbanization have led to serious urban water environment problems. Rainwater is increasingly recognized and utilized as a viable alternative water source in response to these issues. Rainfall pattern, tank size and water use scenarios significantly affect the efficiency of RainWater Harvesting (RWH) systems. To better compare and analyze the impacts of the above factors on the reliability and efficiency of RWH systems, this study conducted experiments in three Chinese cities within different climate zones across three representative years (wet year, average year and dry year). Robust analysis was performed based on careful data pre-processing, which excludes irrelevant rainfall data. A computational tool was developed to evaluate the performance and reliability of rainwater management for RWH systems. Performance analysis and optimization of the RWH system for multi-story residential buildings based on a water balance model were conducted in three Chinese cities. We combined the roof catchment area, water tank volume, and rainwater utilization scenarios to obtain the rainwater harvesting efficiency, overflow ratio, water saving efficiency, and reliability charts of RWH system. In cities with large rainfall (Wuhan), before the maximum rainwater collection size is reached, increasing the tank size can significantly enhance the efficiency of the RWH system. In cities with average or low rainfall (Xi'an and Xining), the maximum rainfall storage capacity of the tank is easily reached, so rainfall is the main factor affecting the efficiency of the RWH system. Meanwhile, the water use scenario is the main factor affecting the reliability of the RWH system in cities with average or low rainfall. Demand scenario critically determines reliability—irrigation (B) achieves high reliability (up to ∼78 %), whereas toilet flushing (A) or combined use (C) exhibit much lower reliability (as low as 2.74 %) due to demand exceeding supply. Results of the study provide decision support for urban water authorities to effectively mitigate urban water supply deficiencies and urban flooding risks.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"182 ","pages":"Article 114531"},"PeriodicalIF":7.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921062","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}
Promoting ecological farms is a critical initiative for greening agriculture and advancing eco-agricultural theory into practice. Although China integrated ecological farm construction into national plans post-2020, its development remains nascent, necessitating objective and quantitative methods to classify farm models and evaluate their performance. This study addresses this gap by applying unsupervised machine learning—specifically Partitioning Around Medoids (PAM) clustering—to 2022 declaration data from 678 national ecological farms. Our analysis identified three distinct typologies: National Varieties Fine Management Type (NVFMT, 40.27 %), characterized by small-scale, specialty-crop operations with minimal synthetic inputs; Diversified Business Type (DBT, 33.78 %), integrating vegetable production, agritourism, and high adoption of eco-measures; and Large-scale Traditional Type (LTT, 25.96 %), focused on grain cultivation with extensive land use and flood irrigation. Performance evaluation using life cycle assessment, total factor productivity (TFP), and revenue analysis revealed no significant economic differences across types. However, NVFMT and DBT exhibited 48–52 % lower greenhouse gas (GHG) emission intensity than LTT, attributable to reduced fertilizer use and diversified practices. DBT also achieved significantly higher TFP (1.18) compared to NVFMT (0.68) and LTT (0.72), linked to operational diversity and technological integration. As the first national-scale application of machine learning to ecological farm typology in China, this research provides an evidence-based framework to guide targeted policies for sustainable agricultural transformation.
{"title":"Ecological farm typology and comparison in China: An unsupervised machine learning approach","authors":"Xiangbo Xu , Shuang Liu , Ziyi Zhou , Yue Xu , Yinghao Xue , Zhiyu Xu , Xiaofang Hu , Xiaohua Yu , Linxiu Zhang","doi":"10.1016/j.ecolind.2025.114560","DOIUrl":"10.1016/j.ecolind.2025.114560","url":null,"abstract":"<div><div>Promoting ecological farms is a critical initiative for greening agriculture and advancing eco-agricultural theory into practice. Although China integrated ecological farm construction into national plans post-2020, its development remains nascent, necessitating objective and quantitative methods to classify farm models and evaluate their performance. This study addresses this gap by applying unsupervised machine learning—specifically Partitioning Around Medoids (PAM) clustering—to 2022 declaration data from 678 national ecological farms. Our analysis identified three distinct typologies: National Varieties Fine Management Type (NVFMT, 40.27 %), characterized by small-scale, specialty-crop operations with minimal synthetic inputs; Diversified Business Type (DBT, 33.78 %), integrating vegetable production, agritourism, and high adoption of eco-measures; and Large-scale Traditional Type (LTT, 25.96 %), focused on grain cultivation with extensive land use and flood irrigation. Performance evaluation using life cycle assessment, total factor productivity (TFP), and revenue analysis revealed no significant economic differences across types. However, NVFMT and DBT exhibited 48–52 % lower greenhouse gas (GHG) emission intensity than LTT, attributable to reduced fertilizer use and diversified practices. DBT also achieved significantly higher TFP (1.18) compared to NVFMT (0.68) and LTT (0.72), linked to operational diversity and technological integration. As the first national-scale application of machine learning to ecological farm typology in China, this research provides an evidence-based framework to guide targeted policies for sustainable agricultural transformation.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"182 ","pages":"Article 114560"},"PeriodicalIF":7.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921066","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}
Pub Date : 2026-01-01DOI: 10.1016/j.ecolind.2025.114589
Haonan Hou , Qinghai Guo , Jinxin Guo , Gang Lian , Dou Zhang , Yulong Zhang
Changes in urban landscape patterns significantly influence the functioning of water-related ecosystem services (WESs). However, existing research often focuses on the spatial correlation mechanisms between landscape patterns and WES, resulting in a limited understanding of their dynamic mechanisms across the temporal dimension. This study systematically analyzed landscape pattern changes in Suzhou, China, from 2004 to 2022, quantifying multiple water-related ecosystem services, including water yield, habitat quality, soil conservation, nitrogen and phosphorus export. The Geographically and Temporally Weighted Regression (GTWR) model was employed to investigate the temporal effects of landscape pattern changes on WESs throughout the study period. Our findings revealed that: (1) WESs exhibited distinct temporal variation patterns, with habitat quality showing linear decline, nitrogen and phosphorus exports following V-shaped trajectories, and water yield and soil retention displaying M-shaped fluctuations. All landscape pattern changes slowed in magnitude after 2013. (2) Among multiple landscape indicators with significant effects (p < 0.05), landscape connectivity emerged as the key driver for various WESs. (3) The impact intensity of landscape aggregation and fragmentation on all WESs declined sharply after 2019. Notably, the abrupt decrease in fragmentation's influence led to a shift in the dominant factor for nitrogen and phosphorus exports—from fragmentation to diversity—post-2019. (4) Landscape patterns simultaneously enhance one service while suppressing another; however, this relationship is not static and may evolve into synergistic promotion of multiple services over time. This study analyzes the temporal dynamics of landscape patterns' influence on WESs, highlighting the importance of incorporating temporal dimensions into ecosystem services research.
{"title":"The temporal effect of urban landscape pattern on the spatiotemporal heterogeneity of water-related ecosystem services: evidence from Suzhou, China (2004–2022)","authors":"Haonan Hou , Qinghai Guo , Jinxin Guo , Gang Lian , Dou Zhang , Yulong Zhang","doi":"10.1016/j.ecolind.2025.114589","DOIUrl":"10.1016/j.ecolind.2025.114589","url":null,"abstract":"<div><div>Changes in urban landscape patterns significantly influence the functioning of water-related ecosystem services (WESs). However, existing research often focuses on the spatial correlation mechanisms between landscape patterns and WES, resulting in a limited understanding of their dynamic mechanisms across the temporal dimension. This study systematically analyzed landscape pattern changes in Suzhou, China, from 2004 to 2022, quantifying multiple water-related ecosystem services, including water yield, habitat quality, soil conservation, nitrogen and phosphorus export. The Geographically and Temporally Weighted Regression (GTWR) model was employed to investigate the temporal effects of landscape pattern changes on WESs throughout the study period. Our findings revealed that: (1) WESs exhibited distinct temporal variation patterns, with habitat quality showing linear decline, nitrogen and phosphorus exports following V-shaped trajectories, and water yield and soil retention displaying M-shaped fluctuations. All landscape pattern changes slowed in magnitude after 2013. (2) Among multiple landscape indicators with significant effects (<em>p</em> < 0.05), landscape connectivity emerged as the key driver for various WESs. (3) The impact intensity of landscape aggregation and fragmentation on all WESs declined sharply after 2019. Notably, the abrupt decrease in fragmentation's influence led to a shift in the dominant factor for nitrogen and phosphorus exports—from fragmentation to diversity—post-2019. (4) Landscape patterns simultaneously enhance one service while suppressing another; however, this relationship is not static and may evolve into synergistic promotion of multiple services over time. This study analyzes the temporal dynamics of landscape patterns' influence on WESs, highlighting the importance of incorporating temporal dimensions into ecosystem services research.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"182 ","pages":"Article 114589"},"PeriodicalIF":7.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921231","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}
Pub Date : 2026-01-01DOI: 10.1016/j.ecolind.2025.114603
Jinlei Kai , Junbo Wang , Jianting Ju , Liping Zhu
Alpine rivers rapidly transport large-stored dissolved carbon (DC) from glaciers and alpine permafrost to downstream aquatic ecosystems. The Tibetan Plateau (TP) is an extraordinarily high-altitude region with ubiquitous alpine rivers undergoing intensified changes due to climate changes. However, the potential impacts on the magnitude and properties of DC in alpine rivers still remain poorly understood. Here, we examined the spatio-temporal variability of DC concentrations and properties across 14 alpine rivers in the central TP. Based on monthly investigations conducted during the open water season, the average concentration of dissolved organic carbon (DOC) and inorganic carbon (DIC) in TP alpine rivers was 1.03 ± 0.73 and 14.73 ± 13.05 mg L−1, respectively. The aromatic degree of dissolved organic matter (DOM) was relatively high with mean SUVA254 of 4.18 ± 1.52 L mg C−1 m−1. Moreover, DOC export rate was found more intensive in glacier fed streams (0.017 ± 0.015 g C km−2 s−1) was found than nonglacier fed rivers (0.009 ± 0.011 g C km−2 s−1). Multiple regression models indicate that riverine DC concentrations were overwhelmingly elevated by vegetation coverage within the subbasins. In the glacier recharging catchments, inputs of summer glacier meltwater significantly enhanced terrigenous humic-like DOM (with higher SUVA254) flushing, which caused nearly constant riverine DOM over seasons. In contrast, nonglacier fed rivers were characterized by a sharp decline in DOM during the post monsoon season. These findings suggest a future scenario of heightened terrestrial leaching and riverine export of DC, driven by the expansion of vegetations and increased glacier derived DOM subsidy under ongoing climate warming and wetting on the TP.
高山河流迅速将冰川和高山永久冻土中大量储存的溶解碳（DC）输送到下游水生生态系统。青藏高原是一个异常高海拔地区，高寒河流普遍存在，气候变化加剧。然而，对高寒河流中DC的大小和性质的潜在影响仍然知之甚少。本文对青藏高原中部14条高寒河流的DC浓度及其特征进行了时空变化分析。在开放水域季节进行的月度调查显示，TP高寒河流溶解有机碳（DOC）和无机碳（DIC）的平均浓度分别为1.03±0.73和14.73±13.05 mg L−1。溶解有机质（DOM）芳香度较高，平均SUVA254为4.18±1.52 L mg C−1 m−1。此外，冰川河流的DOC输出速率（0.017±0.015 g C km−2 s−1）高于非冰川河流（0.009±0.011 g C km−2 s−1）。多元回归模型表明，流域内植被覆盖显著提高了河流DC浓度。在冰川补给集水区，夏季冰川融水的输入显著增强了陆源腐殖质样DOM（具有较高的SUVA254）冲刷，导致河流DOM在季节上几乎不变。相比之下，非冰川河流的特征是在季风季节后DOM急剧下降。这些发现表明，在持续的气候变暖和青藏高原变湿的情况下，受植被扩张和冰川衍生的DOM补贴增加的驱动，未来陆地淋滤和河流输出的DC会增加。
{"title":"Dissolved carbon variability in alpine river catchments of the central Tibetan Plateau","authors":"Jinlei Kai , Junbo Wang , Jianting Ju , Liping Zhu","doi":"10.1016/j.ecolind.2025.114603","DOIUrl":"10.1016/j.ecolind.2025.114603","url":null,"abstract":"<div><div>Alpine rivers rapidly transport large-stored dissolved carbon (DC) from glaciers and alpine permafrost to downstream aquatic ecosystems. The Tibetan Plateau (TP) is an extraordinarily high-altitude region with ubiquitous alpine rivers undergoing intensified changes due to climate changes. However, the potential impacts on the magnitude and properties of DC in alpine rivers still remain poorly understood. Here, we examined the spatio-temporal variability of DC concentrations and properties across 14 alpine rivers in the central TP. Based on monthly investigations conducted during the open water season, the average concentration of dissolved organic carbon (DOC) and inorganic carbon (DIC) in TP alpine rivers was 1.03 ± 0.73 and 14.73 ± 13.05 mg L<sup>−1</sup>, respectively. The aromatic degree of dissolved organic matter (DOM) was relatively high with mean SUVA<sub>254</sub> of 4.18 ± 1.52 L mg C<sup>−1</sup> m<sup>−1</sup>. Moreover, DOC export rate was found more intensive in glacier fed streams (0.017 ± 0.015 g C km<sup>−2</sup> s<sup>−1</sup>) was found than nonglacier fed rivers (0.009 ± 0.011 g C km<sup>−2</sup> s<sup>−1</sup>). Multiple regression models indicate that riverine DC concentrations were overwhelmingly elevated by vegetation coverage within the subbasins. In the glacier recharging catchments, inputs of summer glacier meltwater significantly enhanced terrigenous humic-like DOM (with higher SUVA<sub>254</sub>) flushing, which caused nearly constant riverine DOM over seasons. In contrast, nonglacier fed rivers were characterized by a sharp decline in DOM during the post monsoon season. These findings suggest a future scenario of heightened terrestrial leaching and riverine export of DC, driven by the expansion of vegetations and increased glacier derived DOM subsidy under ongoing climate warming and wetting on the TP.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"182 ","pages":"Article 114603"},"PeriodicalIF":7.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145920633","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}
Pub Date : 2026-01-01DOI: 10.1016/j.ecolind.2025.114593
Adrija Roy , Lukas Thielemann , Masahiro Ryo , Juan Camilo Rivera-Palacio , Konlavach Mengsuwan , Kathrin Grahmann
Soil fauna plays a critical role in ecosystem functions such as nutrient cycling, organic matter decomposition, and soil structure maintenance. Accurately assessing their activity is therefore essential for monitoring soil health. Traditional methods like the bait lamina test, while widely used, rely on manual visual scoring, which can be subjective, time-consuming, and difficult to scale. In this study, we present an automated computer vision approach to quantify soil fauna activity by assessing bait consumption on bait lamina sticks, using high-resolution imagery processed with a Python-based pipeline. We implemented this approach on 159 bait sticks gathered from field plots in Brandenburg, Germany, and compared the automated findings with assessments from five independent human operators. The automated method displayed a strong agreement with manual evaluations, yielding Pearson's r between 0.80 and 0.92, depending on the operator, and Cohen's kappa of 0.48 in categorical concordance. The Bland-Altman analysis revealed that over 90 % of the automated scores were within +/− 0.2 of the manual measurements. This automated technique reduced the time required for analysis in comparison to manual scoring, along with removing operator subjectivity and bias. Although there was an underestimation in identifying fully consumed bait holes, the average difference between the automated and manual scores was only 0.02 (p = 0.0049), suggesting a negligible effect size. The automated approach is straight-forward, reproducible, and flexible, which facilitates the efficient and impartial evaluation of soil fauna activity for large-scale soil health monitoring. Possible improvements could involve enhancing the image-analysis workflow, such as improving hole-detection robustness, reducing sensitivity to coating or lighting variation, and exploring more advanced classification models.
{"title":"Scalable computer vision-based assessment of bait lamina sticks to quantify soil fauna activity","authors":"Adrija Roy , Lukas Thielemann , Masahiro Ryo , Juan Camilo Rivera-Palacio , Konlavach Mengsuwan , Kathrin Grahmann","doi":"10.1016/j.ecolind.2025.114593","DOIUrl":"10.1016/j.ecolind.2025.114593","url":null,"abstract":"<div><div>Soil fauna plays a critical role in ecosystem functions such as nutrient cycling, organic matter decomposition, and soil structure maintenance. Accurately assessing their activity is therefore essential for monitoring soil health. Traditional methods like the bait lamina test, while widely used, rely on manual visual scoring, which can be subjective, time-consuming, and difficult to scale. In this study, we present an automated computer vision approach to quantify soil fauna activity by assessing bait consumption on bait lamina sticks, using high-resolution imagery processed with a Python-based pipeline. We implemented this approach on 159 bait sticks gathered from field plots in Brandenburg, Germany, and compared the automated findings with assessments from five independent human operators. The automated method displayed a strong agreement with manual evaluations, yielding Pearson's r between 0.80 and 0.92, depending on the operator, and Cohen's kappa of 0.48 in categorical concordance. The Bland-Altman analysis revealed that over 90 % of the automated scores were within +/− 0.2 of the manual measurements. This automated technique reduced the time required for analysis in comparison to manual scoring, along with removing operator subjectivity and bias. Although there was an underestimation in identifying fully consumed bait holes, the average difference between the automated and manual scores was only 0.02 (<em>p</em> = 0.0049), suggesting a negligible effect size. The automated approach is straight-forward, reproducible, and flexible, which facilitates the efficient and impartial evaluation of soil fauna activity for large-scale soil health monitoring. Possible improvements could involve enhancing the image-analysis workflow, such as improving hole-detection robustness, reducing sensitivity to coating or lighting variation, and exploring more advanced classification models.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"182 ","pages":"Article 114593"},"PeriodicalIF":7.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145920641","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}
The agro-pastoral ecotone of northern China (APENC) is a critical ecological security barrier that has long faced imbalances, spatial mismatches, and functional degradation in ecosystem service (ES). Using multi-source remote sensing products and statistical data from 2000 to 2020, this study assessed five ESs in the APENC, including grain production, soil conservation, water yield, carbon storage, and windbreak and sand fixation. The spatiotemporal dynamics of ES supply and demand were quantified, dominant drivers were identified, and a zoning-based optimization framework was developed. From 2000 to 2020, the supply of all ESs increased significantly except for windbreak and sand fixation. In contrast, demand exhibited divergent trajectories, with declining demand for grain production and windbreak and sand fixation, increasing demand for carbon storage and soil conservation, and relatively stable demand for water yield. Although the overall supply-demand ratio improved, windbreak and sand fixation showed persistent deficits. Supply-demand coupling coordination was generally low and was mainly characterized by slightly and nearly uncoordinated states, while coordinated areas occurred only sporadically. The dominant matching pattern was low supply and low demand, whereas areas characterized by low supply and high demand expanded over time. The driving mechanisms shifted from predominantly environmental controls to a coupled regime integrating biophysical conditions and socioeconomic pressures, with vegetation conditions and population-economic intensity emerging as key interactive drivers. The proposed zoning scheme supports differentiated strategies for supply enhancement, demand regulation, and resilience strengthening, and provides guidance for ecological function improvement and spatial governance in the APENC.
{"title":"Unraveling ecosystem service supply-demand relationships and zoning optimization in the agro-pastoral ecotone of northern China","authors":"Yu Bai, Yuxin Wang, Linru Li, Jianmei Fu, Xuefeng Yuan","doi":"10.1016/j.ecolind.2025.114590","DOIUrl":"10.1016/j.ecolind.2025.114590","url":null,"abstract":"<div><div>The agro-pastoral ecotone of northern China (APENC) is a critical ecological security barrier that has long faced imbalances, spatial mismatches, and functional degradation in ecosystem service (ES). Using multi-source remote sensing products and statistical data from 2000 to 2020, this study assessed five ESs in the APENC, including grain production, soil conservation, water yield, carbon storage, and windbreak and sand fixation. The spatiotemporal dynamics of ES supply and demand were quantified, dominant drivers were identified, and a zoning-based optimization framework was developed. From 2000 to 2020, the supply of all ESs increased significantly except for windbreak and sand fixation. In contrast, demand exhibited divergent trajectories, with declining demand for grain production and windbreak and sand fixation, increasing demand for carbon storage and soil conservation, and relatively stable demand for water yield. Although the overall supply-demand ratio improved, windbreak and sand fixation showed persistent deficits. Supply-demand coupling coordination was generally low and was mainly characterized by slightly and nearly uncoordinated states, while coordinated areas occurred only sporadically. The dominant matching pattern was low supply and low demand, whereas areas characterized by low supply and high demand expanded over time. The driving mechanisms shifted from predominantly environmental controls to a coupled regime integrating biophysical conditions and socioeconomic pressures, with vegetation conditions and population-economic intensity emerging as key interactive drivers. The proposed zoning scheme supports differentiated strategies for supply enhancement, demand regulation, and resilience strengthening, and provides guidance for ecological function improvement and spatial governance in the APENC.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"182 ","pages":"Article 114590"},"PeriodicalIF":7.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145920755","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}
Pub Date : 2026-01-01DOI: 10.1016/j.ecolind.2025.114564
Ziyan Ling , Qiuling Li , Weiguo Jiang , Ze Zhang , Peng Hou , Shihui Huang , Zhe Yang , Zhijie Xiao , Xiaogan Yin
<div><div>The implementation of International Wetland City certification and associated conservation measures coincided with changes in the potential distribution of waterbirds in China's coastal wetlands. However, it remains unclear how the certification affects the overall distribution patterns of multi-species waterbird habitats and the specific mechanisms by which different species respond to environmental factors. Moreover, identifying key habitats for these guilds is essential for targeted species conservation and habitat restoration. Therefore, based on the Data-Information-Knowledge-Wisdom (DIKW) framework, this study classified 166 waterbird species into four ecological guilds: shorebirds, wading birds, open-water birds, and waterfowl. Using a coupled MaxEnt and hotspot analysis approach, we evaluated habitat suitability for these four waterbird guilds before and after the designation of Panjin, Dongying, and Yancheng as International Wetland Cities (2018–2024) and identified their distribution hotspots.The results indicated that: (1) After 10 iterations of training, the MaxEnt models for all four waterbird guilds achieved a mean AUC above 0.8 and a mean TSS above 0.60, demonstrating good predictive accuracy in simulating waterbird habitats. From 2018 to 2024, the total area of suitable waterbird habitat increased significantly in Panjin, Dongying, and Yancheng, with net expansions of 346.26 km<sup>2</sup>, 602.48 km<sup>2</sup>, and 40.51 km<sup>2</sup>, respectively; (2) Pronounced regional heterogeneity was evident in waterbird distribution patterns across the wetland cities. In Panjin, waterbirds showed a stronger preference for natural habitats such as herbaceous marshes and tidal flats, whereas in Dongying and Yancheng, they demonstrated greater adaptability, with a marked increase in occurrence probability in human-modified landscapes such as cropland; (3) Suitable waterbird habitats in all three wetland cities demonstrated a spatial pattern of “overall improvement despite localized contraction.” Although some coastal areas experienced partial habitat loss, these habitats continued to expand inland, with shorebirds facing the more significant pressure from habitat contraction, particularly in coastal zones; (4) Land use/land cover (LULC) and distance to farmland (DFC) were the dominant factors influencing waterbird distribution in Panjin. In Dongying, distribution was significantly affected by LULC, distance to roads (DFR), NDVI, mean diurnal range (BIO2), and precipitation seasonality (BIO15). In Yancheng, habitat selection was primarily influenced by climatic factors such as BIO2 and isothermality (BIO3), as well as DFC and distance to constructed surfaces (DFS); (5) Hotspots of suitable waterbird habitat continued to expand, forming a trend centered on nature reserves and gradually extending outward.This study reveals the spatiotemporal evolution patterns and driving mechanisms of habitat suitability for multiple waterbird guil
{"title":"Multi-guild waterbird habitat suitability change and hotspots (2018–2024) in China's international wetland cities: MaxEnt + Gi* within a DIKW framework","authors":"Ziyan Ling , Qiuling Li , Weiguo Jiang , Ze Zhang , Peng Hou , Shihui Huang , Zhe Yang , Zhijie Xiao , Xiaogan Yin","doi":"10.1016/j.ecolind.2025.114564","DOIUrl":"10.1016/j.ecolind.2025.114564","url":null,"abstract":"<div><div>The implementation of International Wetland City certification and associated conservation measures coincided with changes in the potential distribution of waterbirds in China's coastal wetlands. However, it remains unclear how the certification affects the overall distribution patterns of multi-species waterbird habitats and the specific mechanisms by which different species respond to environmental factors. Moreover, identifying key habitats for these guilds is essential for targeted species conservation and habitat restoration. Therefore, based on the Data-Information-Knowledge-Wisdom (DIKW) framework, this study classified 166 waterbird species into four ecological guilds: shorebirds, wading birds, open-water birds, and waterfowl. Using a coupled MaxEnt and hotspot analysis approach, we evaluated habitat suitability for these four waterbird guilds before and after the designation of Panjin, Dongying, and Yancheng as International Wetland Cities (2018–2024) and identified their distribution hotspots.The results indicated that: (1) After 10 iterations of training, the MaxEnt models for all four waterbird guilds achieved a mean AUC above 0.8 and a mean TSS above 0.60, demonstrating good predictive accuracy in simulating waterbird habitats. From 2018 to 2024, the total area of suitable waterbird habitat increased significantly in Panjin, Dongying, and Yancheng, with net expansions of 346.26 km<sup>2</sup>, 602.48 km<sup>2</sup>, and 40.51 km<sup>2</sup>, respectively; (2) Pronounced regional heterogeneity was evident in waterbird distribution patterns across the wetland cities. In Panjin, waterbirds showed a stronger preference for natural habitats such as herbaceous marshes and tidal flats, whereas in Dongying and Yancheng, they demonstrated greater adaptability, with a marked increase in occurrence probability in human-modified landscapes such as cropland; (3) Suitable waterbird habitats in all three wetland cities demonstrated a spatial pattern of “overall improvement despite localized contraction.” Although some coastal areas experienced partial habitat loss, these habitats continued to expand inland, with shorebirds facing the more significant pressure from habitat contraction, particularly in coastal zones; (4) Land use/land cover (LULC) and distance to farmland (DFC) were the dominant factors influencing waterbird distribution in Panjin. In Dongying, distribution was significantly affected by LULC, distance to roads (DFR), NDVI, mean diurnal range (BIO2), and precipitation seasonality (BIO15). In Yancheng, habitat selection was primarily influenced by climatic factors such as BIO2 and isothermality (BIO3), as well as DFC and distance to constructed surfaces (DFS); (5) Hotspots of suitable waterbird habitat continued to expand, forming a trend centered on nature reserves and gradually extending outward.This study reveals the spatiotemporal evolution patterns and driving mechanisms of habitat suitability for multiple waterbird guil","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"182 ","pages":"Article 114564"},"PeriodicalIF":7.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921151","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}
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