工业工程最新文献

{"title":"[Impact Analysis of Different Buffer Scale Landscape Patterns on Water Quality of the Fourth Drainage Ditch in Ningxia Yellow River Irrigation Area].","authors":"Ji-Long Ma, Kun Ma, Tie-Na Xie, Jian-Jun Ma, Hong Li, Xiang Yue, Lin-Pu Han, Yong-Jie Qi, Jia-Qi Gao, Biao Jia","doi":"10.13227/j.hjkx.202407049","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407049","url":null,"abstract":"<p><p>Landscape patterns at specific spatial scales can respond to the sources of non-point source pollutants in water bodies and the surface landscape's ability to absorb them. To investigate the influence of landscape patterns on the water quality of the drainage ditch at different circular buffer scales， the fourth drainage ditch of the Ningxia Yellow River Irrigation Area （YDIA） was taken as the research object， and based on the land-use data in 2022 and the dynamic water quality monitoring data of 26 sampling points from 2021 to 2022， five circular buffer scales， including 100， 200， 500， 1 000， and 2 000 m， were set up， and three methods. Landscape pattern analysis， Spearman rank correlation analysis， and redundancy analysis were used to filter the water quality of the drainage ditch. Landscape pattern analysis， Spearman rank correlation analysis， and redundancy analysis were used to screen out the optimal buffer scales and corresponding key landscape indicators to explain the changes in water quality and to analyze the response relationship between the water quality of the drainage ditch and landscape features. The results showed that： ① The fourth drainage ditch in Ningxia Huang Irrigation Area was mostly polluted by high nitrogen， and more than 70% of the TN indexes exceeded the standard limit for Class V water throughout the year， while the TP indexes did not exceed the standard limit for Class III water， which was less polluted. ② The landscape characteristics at the scale of the 200 m circular buffer zone had a close relationship with the water quality indexes of the two periods， and the explanation rates of the fallow period and the cultivation period at that scale were the highest， 45.76% and 44.14%， respectively， and the explanation rate was the highest， 47.63% and 45.83%， respectively， which was the best buffer scale for discriminating the water quality of the fourth drainage ditch. ③ Cultivated land was the main 'source' land use type within the optimal buffer zone， which was the main factor affecting the change of pollutants in the drainage ditch. Followed by the spreading index， aggregation index， scattering and juxtaposition index， and fragrance uniformity， which were the main landscape factors affecting the change of water quality. Therefore， when optimizing the landscape pattern method for monitoring and controlling water pollution in drainage ditches， it is recommended to strictly control the proportion of arable land and other 'source' land-use types within the 200 m circular buffer zone， and at the same time， improve the diversity， connectivity， and aggregation of the landscape. The results of this study can provide new ideas and solutions for monitoring and analyzing the water quality of drainage ditches in Ningxia's Yellow River Irrigation District.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 7","pages":"4251-4263"},"PeriodicalIF":0.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Optimization and Application of Soil Health Evaluation Method for Edible Beans].","authors":"Kai-Lu Zhang, Xue-Bin Xu, Hui-Lin Yan, Qiong Liu, Liang Wei, Ti-da Ge","doi":"10.13227/j.hjkx.202406046","DOIUrl":"https://doi.org/10.13227/j.hjkx.202406046","url":null,"abstract":"<p><p>Edible beans play a significant role in healthy dietary structures， human health， and soil improvement. Scientifically and reasonably assessing the health status of the soil where they are cultivated is crucial for achieving green， high-yield， and high-quality production. This study focused on soils from major edible bean-producing areas across the country， collecting soil samples from 0-20 cm depth and measuring 27 indicators reflecting soil physical， chemical， and biological characteristics. Principal component analysis （PCA） and network analysis （NWA） were used to obtain the minimum data set， combined with linear scoring （L） and nonlinear scoring （NL） standardization methods， as well as the integrated health index （IHI） and Nemerow quality index （NQI） integration methods， to construct eight soil health assessment methods and calculate the corresponding soil health index （SHI）. By comparing the SHI constructed from the full dataset through correlation and sensitivity analyses and combining the linear fitting results of SHI with soil organic carbon （SOC） and yield， the most suitable soil health assessment method for the major edible bean-producing areas was selected， and the soil health status was evaluated. The results indicated： ① The four SHIs （L-IHI， NL-IHI， L-NQI， and NL-NQI） based on the minimum data set obtained by NWA showed a higher correlation （<i>r</i>&gt;0.8） with the SHI constructed from the full dataset than those based on PCA （0.6&lt;<i>r</i>&lt;0.8）， better reflecting overall soil health status. ② The variation degree of the four SHIs based on NWA （60%-70%） was much higher than that of the SHI constructed from the full dataset and PCA （20%-40%）， indicating higher sensitivity for evaluating soil health in major edible bean-producing areas nationwide. ③ Among the four SHIs based on NWA， L-IHI showed the best linear fitting results with yield and SOC， indicating that NWA-L-IHI is the optimal method for evaluating soil health in major edible bean-producing areas. ④ According to the NWA-L-IHI method for evaluating soil health in major edible bean-producing areas nationwide， the results showed that the soil health level in subtropical and warm temperate regions was generally higher than that in mid-temperate regions. The soil health level in major producing areas in Yunnan and Fujian provinces was relatively high （SHI&gt;0.2）， whereas the soil health status in major producing areas in Shaanxi， Shanxi， Hebei， and Inner Mongolia provinces （autonomous regions） was relatively poor （0.05&lt;SHI&lt;0.15）. The study results clarified the soil health status in different regions， providing a scientific basis for soil management. Appropriate nutrient management， such as fertilization and providing organic cover， can address the deficiency of nitrogen， phosphorus， and micronutrients， and each province can also improve soil health by exploring locally suitable edible bean planting patterns.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 7","pages":"4450-4460"},"PeriodicalIF":0.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Quantitative Analysis of Wetland Evolution Characteristics and Driving Factors in Ruoergai Plateau Based on Landsat Time Series Remote Sensing Images].","authors":"Man Yang, En-Qin Liu, Yang Yang, Bing Gao, Lei Guan","doi":"10.13227/j.hjkx.202406190","DOIUrl":"https://doi.org/10.13227/j.hjkx.202406190","url":null,"abstract":"<p><p>The Ruoergai Wetland， China's largest high-altitude marsh， plays a crucial role in the carbon cycle and climate management. However， the Ruoergai Wetland has experienced significant damage as a result of human activity and global warming. Based on the Google Earth Engine （GEE） cloud platform and time-series Landsat images， a random forest algorithm was applied to produce a detailed classification map of the Ruoergai wetlands from 1990 to 2020. Through the transfer matrix and landscape pattern index， the spatiotemporal change law and change trend of wetlands were analyzed. Then， the influencing factors of wetland distribution were quantitatively analyzed using geographic detector. The results showed that： ① The total wetland area averaged 3 910 km² from 1990 to 2020， dominated by marshy and wet meadows， accounting for 83.13% of the total wetland area. From 1990 to 2010， the wetland area of Ruoergai showed a decreasing trend， and from 2010 to 2020， the wetland area increased slightly. ② From 1990 to 2020， the decrease in wetland area was mainly reflected in the degradation of wet meadows into alpine grassland. There were also changes among different wetland types， which were mainly reflected in the conversion of marsh meadows and wet meadows. ③ From 1990 to 2010， the wetland landscape tended to be fragmented and complicated， and the aggregation degree decreased. From 2010 to 2020， wetland fragmentation decreased， and the wetland landscape became more concentrated. ④ Slope， temperature， and aspect were the main natural factors affecting wetland distribution. At the same time， population density has gradually become a significant social and economic factor affecting wetland distribution. The results can provide scientific support for the wetland protection planning of Ruoergai and serve for the ecological preservation and high-level development of the area.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 7","pages":"4461-4472"},"PeriodicalIF":0.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Spatial Heterogeneity of Carbon Emissions from Construction Projects Based on XGBoost-SHAP].","authors":"Yuan-Qing Wang, Jia-Yue Li, Bei Liu, Fang Wang","doi":"10.13227/j.hjkx.202406040","DOIUrl":"https://doi.org/10.13227/j.hjkx.202406040","url":null,"abstract":"<p><p>To make the carbon emission reduction of highway construction more effective， this study focuses on the spatial heterogeneity of carbon emission in the process of highway construction. Based on the seven key indicators of carbon emission impacts of the type of structure， bridge-to-tunnel ratio， design gradient， route length， fill volume， excavation volume， and cement consumption screened out from the 40 segment samples of highway project A in Guangdong Province， we trained and validated the XGBoost carbon emission prediction model and constructed the SHAP algorithm to explain the impacts， total feature contributions， and feature interaction effects of the features of these 40 road segments. The SHAP algorithm was constructed to explain the spatial heterogeneity of carbon emissions of these 40 road sections， and the influence of road section features on carbon emissions， total feature contribution， and feature interaction effect were investigated. The results showed that the increase in cement consumption contributed the most to the nonlinear increase of carbon emission， and the route length， excavation volume， and bridge-to-tunnel ratio also contributed significantly to the carbon emission. The analysis of hot and cold spots revealed that the carbon emission tended to be higher in the road sections with a gradient higher than 2.5% and with complex topography， and there exists an agglomeration effect. The XGBoost-SHAP model explained the spatial distribution of carbon emission more clearly than the geographically weighted regression model （GWR）； the model captured the characteristics and their influencing factors and also the spatial distribution and effects on carbon emission. The XGBoost-SHAP model could explain the spatial distribution of carbon emissions and its influencing factors more clearly than GWR and performed better in capturing the key carbon sources and understanding the spatial distribution of carbon emissions. Based on the above findings， this study proposes a comprehensive strategy for carbon emission reduction in highway construction and maintenance to promote the sustainable development of highway construction.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 7","pages":"4090-4100"},"PeriodicalIF":0.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Spatio-temporal Dynamic Characteristics and Driving Factors of Vegetation NPP in Hetao Irrigation District of Inner Mongolia].","authors":"Jian-Xun Ji, Xin Tong, Li-Min Duan, Xiao-Yan Liu, Yu Gong, Ting-Xi Liu","doi":"10.13227/j.hjkx.202405296","DOIUrl":"https://doi.org/10.13227/j.hjkx.202405296","url":null,"abstract":"<p><p>Vegetation net primary productivity （NPP） is a key indicator for the evaluation of ecological environment quality. Identifying and analyzing the dynamic characteristics and driving forces of vegetation NPP is a prerequisite for achieving regional environmentally sustainable development. Trend analysis， Hurst index， and stability analysis were used to elucidate the changing pattern of vegetation NPP in the basin of Hetao Irrigation District in Inner Mongolia. Furthermore， the dominant driving factors of spatial heterogeneity of vegetation NPP in different regions were quantitatively identified by geographical detector. The results showed that the annual mean （C） of vegetation NPP in the whole basin from 2001 to 2020 was 139.14 g·（m²·a）^-1， showing a fluctuating increasing trend， and the interannual increase rate （C） was 2.06 g·（m²·a）^-1 （<i>P</i>&lt; 0.05）. The NPP of vegetation inside and outside the irrigation area also improved. Spatially， the NPP of vegetation was generally high in the irrigation area and low outside the irrigation area. Among them， 63.51 % of the regional vegetation NPP increased significantly， mostly concentrated in the western and peripheral regions of the irrigation area. The average coefficient of variation of vegetation NPP was 0.17， which primarily showed low fluctuation， and the future anti-continuous change trend was significantly stronger than the continuous change trend. Land use type was the first dominant factor affecting the spatial distribution of vegetation NPP in the whole basin and inside and outside the irrigation area. Temperature and precipitation had relatively strong explanatory power for the change of vegetation NPP in the irrigation area， and the influence of each driving factor was obvious inside and outside the irrigation area. Under the influence of different natural geographical units， ecosystem types， meteorological and hydrological conditions， and human activities， the spatial and temporal differentiation characteristics of vegetation NPP and its driving mechanism in the Hetao Irrigation District of Inner Mongolia showed obvious spatial heterogeneity. In the future， ecological construction projects should be carried out according to local conditions， and the comprehensive management and system protection of the ecological environment of the basin should be strengthened to continuously promote the ecological protection and high-quality development of the Yellow River Basin.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 7","pages":"4392-4402"},"PeriodicalIF":0.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Effects of Long-term Corn Stover Return on Fungal Communities and Enzyme Activities in Brown Soil].","authors":"Hao-Kai Yin, Yu-Hang Zhao, Wen-Yan Xie, Zhi-Ping Liu, Huai-Ping Zhou, Zhen-Xing Yang","doi":"10.13227/j.hjkx.202406205","DOIUrl":"https://doi.org/10.13227/j.hjkx.202406205","url":null,"abstract":"<p><p>Based on a 31-year consecutive long-term positioning trial of stover return to field， including four different corn stover return methods： stover not returned to field （CK）， stover overgrown （CM）， stover crushed and directly returned to field （SC）， and stover mulched （SM）； the soil nutrient content， extracellular enzyme activity， fungal community structure， and mycorrhizal functional activity were comprehensively analyzed using high-throughput sequencing technology， FUNGuild functional prediction， and ecological network approach. We investigated the effects of different straw return modes on the nutrient content of brown soil farmland， analyzed the characteristics of soil extracellular enzymes and functional activities of fungal communities， and provided a theoretical basis for efficiently improving the soil fertility of brown soil farmland. The results showed that： ① Long-term different straw return treatments （SM， SC， and CM） significantly increased soil fertility， maize yield， and extracellular enzyme activities， and soil organic carbon （SOC）； total nitrogen （TN）； total phosphorus （TP）； total potassium （TK）； alkaline dissolved nitrogen （AN）； effective phosphorus （AP）； quick-acting potassium （AK）； cumulative yield of maize； and the contents of soil glucosidase （<i>β</i>-GC）， cellobiose hydrolase （CBH）， and dehydrogenase （DHA） contents were elevated from 17.0%-42.9%， 3.0%-50.0%， 2.3%-27.9%， 4.4%-11.5%， 11.2%-71.0%， 14.1%-320.8%， 17.1%-153.6%， 6.4%-23.0%， 35.6%-190.7%， 41.9%-58.6%， and 28.8%-773.8%； among them， the CM treatment had the most significant enhancement effect. ② Long-term different straw return treatments changed the structural composition of the soil fungal community， and the relative abundance of fungi in the phylum Periphyton decreased by 29.05%-31.12%， and the phylum Stachybotrys was enhanced by 24.76%-481.10%. The soil pH was an important influencing factor affecting the composition of the fungal community. ③ The results of network analysis showed that the indicator species of different straw return treatments in the long term belonged to different modules， which were significantly correlated with soil nutrient content and enzyme activity， among which <i>Phaeoacremonium</i> and <i>Conocybe</i> enriched in the CM treatment formed specific functional microbial clusters through a strong symbiotic relationship. ④ Functional prediction based on FUNGuild found that long-term different straw return treatments both increased the relative abundance of pathogenic and saprophytic trophic fungi and decreased the relative abundance of saprophytic-symbiotic trophic fungi. Long-term straw return can improve soil fertility and extracellular enzyme activity， increase the abundance of beneficial flora， significantly change the structure and composition of fungal communities， and favor carbon and nitrogen cycling， thus promoting the formation of a suitable environment for crop and fungal growth in brown soils.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 7","pages":"4699-4709"},"PeriodicalIF":0.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Estimation of Soil Organic Carbon Content in the Bosten Lake Basin Based on Synthetic Images and Multi-variables].","authors":"Dun Li, Xue-Mei Wang, Kun-Yu Li, Yan-Ping Guo","doi":"10.13227/j.hjkx.202406088","DOIUrl":"https://doi.org/10.13227/j.hjkx.202406088","url":null,"abstract":"<p><p>The selection of appropriate multi-temporal remote sensing image synthesis methods and modeling variables plays an important role in the estimation of soil organic carbon content and its spatial distribution inversion. Taking the soil organic carbon content in Xinjiang Bosten lake basin as the research object， spectral variables were generated according to the minimum， median， and mean Sentinel-2 multi-temporal satellite image synthesis method， and environmental variables such as climate and topography were added as modeling variables. The effects of different image compositing methods and variable sets on the estimation of soil organic carbon content in tillage were analyzed using the Boruta variable screening algorithm and random forest （RF） model. The results showed that： ① The combination of environmental and spectral variables significantly improved SOC content estimation， with climate variables among the environmental factors playing a crucial role in the Bosten lake basin. ② Models using variables selected by the Boruta algorithm outperformed those using the full variable set， demonstrating that the Boruta algorithm effectively enhanced model accuracy. ③ Among all models， the one using mean-synthesized spectral variables combined with environmental variables yielded the best results， with the optimal model achieving an estimation accuracy in which <i>R</i>² was 0.970， RMSE was 2.919 g·kg^-1， and RPD was 5.319. The integration of multi-temporal mean-synthesized spectral variables， environmental variables， Boruta algorithm， and random forest modeling provides a reliable approach for estimating the spatial distribution of topsoil SOC content in the Bosten Lake Basin， offering a technical reference for accurately assessing soil organic carbon storage in arid regions.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 7","pages":"4428-4440"},"PeriodicalIF":0.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Evaluation of Water Ecological Security and Analysis of Barriers in the Shaanxi Province Based on DPSIR-entropy Weight].","authors":"Yi-Yong Wang, Chao-Fan Zhou, Rong Huang, Zhao-Na Xue, Si-Ting Tian","doi":"10.13227/j.hjkx.202406023","DOIUrl":"https://doi.org/10.13227/j.hjkx.202406023","url":null,"abstract":"<p><p>This study utilizes the water ecological security data of 10 prefecture-level cities in Shaanxi Province from 2012 to 2021， constructs the evaluation index system based on the DPSIR evaluation model， and carries out the evaluation of water ecological security in the Shaanxi Province based on the entropy weighting method. Three methods were comprehensively used， namely， the comprehensive index method， the TOPSIS method， and the VIKOR method， and the obstacle degree analysis of the indexes was conducted. The results showed that： ① From 2012 to 2021， the water ecological security of all 10 prefectural-level cities in the Shaanxi Province improved， and as of 2021， the evaluation value of water ecological security of each prefectural-level city ranged from 0.546 23 to 0.78， and the evaluation value was between 0.546 23 and 0.780 00. The evaluation order was： Baoji &lt; Tongchuan &lt; Ankang &lt; Xianyang &lt; Shangluo &lt; Hanzhong &lt; Yan'an &lt; Yulin &lt; Weinan &lt; Xi'an. ② The barrier degree of the extreme indicators was distributed around 2016， and most of them were located in the pressure layer. The hierarchical barrier degree improved year by year in addition to the driving layer， and the barrier degree of the rest of the hierarchical levels declined in varying degrees. ③ Among the barrier factors of each prefectural-level city， the \"chemical oxygen demand\" （COD） emission and ammonia nitrogen （AN） emission were the main obstacle factors， and the improvement of water quality and the pursuit of high-quality economic development are the main ways to improve water ecological security in Shaanxi Province.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 7","pages":"4335-4348"},"PeriodicalIF":0.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Impact of Tillage Practices on the Organic Carbon Pool and Enzyme Stoichiometry Characteristics in Black Soil Farmland].","authors":"Peng-Xiang Sui, Yang Luo, Hao Wang, Ying Ren, Ye Yuan, Si-Qi Zhou, Sheng-Tao Tian, Wu-Ren Liu, Jin-Yu Zheng","doi":"10.13227/j.hjkx.202405289","DOIUrl":"https://doi.org/10.13227/j.hjkx.202405289","url":null,"abstract":"<p><p>To investigate the impact of different tillage practices on the organic carbon pool and the stoichiometry characteristics of extracellular enzymes in black soil farmland， a continuous 6-year field experiment was conducted. This study evaluated the effects of conventional tillage （CT）， no-till with straw mulching （NTS）， subsoiling tillage with straw strip mulching （STS）， and moldboard plowing with straw returning （MPS） on active organic carbon components， organic carbon pool， enzyme activity， and enzyme stoichiometric characteristics in the 0-40 cm soil layer. The results showed that compared with those in the CT treatment， the NTS， STS， and MPS treatments significantly increased the contents of easily oxidizable organic carbon （EOC）， particulate organic carbon （POC）， soil organic carbon （SOC）， carbon pool index （CPI）， and carbon pool management index （CPMI） in the 0-40 cm soil layer， with increases of 7.55%-19.81%， 31.75%-59.05%， 6.19%-21.42%， 7.00%-20.00%， and 6.45%-19.67%， respectively. The largest increase was observed in the NTS treatment. Furthermore， the MPS treatment significantly enhanced the activities of <i>β</i>-1，4-glucosidase （BG） and leucine aminopeptidase （LAP） by 37.66%-47.38% and 9.57%-23.93%， respectively， compared to those in the other treatments. Additionally， the activities of acid phosphatase （ACP） in the STS and MPS treatments were 9.51%-15.18% higher than those in the CT and NTS treatments. The STS and MPS treatments significantly increased the vector angle （VA） in the 0-10 cm soil layer and the vector length （VL） in the 0-20 cm soil layer， while reducing VL and VA in the 20-40 cm soil layer. Redundancy analysis indicated that active organic carbon components and the organic carbon pool were the primary factors influencing enzyme stoichiometric characteristics. These findings are crucial for assessing the long-term effects of conservation tillage on soil organic carbon turnover and microbial nutrient utilization.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 7","pages":"4441-4449"},"PeriodicalIF":0.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Spatio-temporal Differentiation Characteristics of Ecological Sensitivity in the Middle Reaches of the Yellow River].","authors":"Yi Qu, Liang-Yi Rao","doi":"10.13227/j.hjkx.202406086","DOIUrl":"10.13227/j.hjkx.202406086","url":null,"abstract":"<p><p>The fragile habitat in the middle reaches of the Yellow River is one of the most prominent ecological problems in the Yellow river basin. The study of ecological sensitivity in the middle reaches of the Yellow River can provide a reference for the restoration and protection of the regional ecosystem. Three ecological sensitivity indexes were selected based on the actual situation of the region： soil and water loss， land desertification， and biodiversity. The spatial distance index method was used to construct a comprehensive ecological sensitivity index. The spatio-temporal differentiation characteristics and driving factors of ecological sensitivity within the middle reaches of the Yellow River from 2005 to 2020 were explored through spatial autocorrelation analysis， grid coding analysis， and geographic detector. The results showed that：① The comprehensive ecological sensitivity of the middle reaches of the Yellow River from 2005 to 2020 had obvious spatial differentiation， showing a distribution pattern of \"high in the northwest and low in the southeast.\" In terms of time， the average comprehensive ecological sensitivity index of the middle reaches of the Yellow River continued to decrease from 6.854 in 2005 to 6.350 in 2020， and the regional ecological sensitivity decreased. ② From 2005 to 2020， the comprehensive ecological sensitivity of the middle reaches of the Yellow River had a significant spatial positive correlation and strong spatial aggregation. However， over time， the spatial aggregation gradually weakened. ③ From 2005 to 2020， the overall change of comprehensive ecological sensitivity in the middle reaches of the Yellow River was small， and the regional area with 0 and 1 changes accounted for 70.79% of the total area. The areas with increased ecological sensitivity were mainly located in the Guanzhong Plain and the northwest of Henan Province. The areas that had maintained a high-value sensitivity for a long period were moxtly located in the northern part of the Jinghe river basin， Wuding river basin， and the northeast of the Ordos Plateau. These areas require special attention in the future. ④ Fractional vegetation coverage was the main driving factor for the spatial differentiation of comprehensive ecological sensitivity in the middle reaches of the Yellow River， and the biological richness index was the secondary factor. Altogther， the comprehensive ecological sensitivity in the middle reaches of the Yellow River gradually decreased， and the ecological environment improved. This study can provide a reference for ecosystem protection and high-quality development in the middle reaches of the Yellow River.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 7","pages":"4568-4579"},"PeriodicalIF":0.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}