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The quality attribute of watershed ecosystem is more important than the landscape attribute in controlling erosion of red soil in southern China

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International Soil and Water Conservation Research 2022年第3期10卷 507-517页

作者： Qing Zhu Xi Guo Jiaxin Guo Jun Wu Yingcong Ye Wenbo Cai Shiyu Liu School of Design Shanghai Jiao Tong UniversityShanghai200240China Key Laboratory of Poyang Lake Watershed Agricultural Resources and Ecology of Jiangxi Province Jiangxi Agricultural UniversityNanchangJiangxi330045China College of Land Resource and Environment Jiangxi Agricultural UniversityNanchangJiangxi330045China State Key Laboratory of Urban and Regional Ecology Research Center for Eco-environment SciencesChinese Academy of SciencesBeijing100085China

Landscape and quality attributes are major ecosystem characteristics closely associated with soil conservation service(SCS).However,the intrinsic mechanisms by which these two attributes influence SCS are still ***,this study quantitatively analyzed the landscape pattern,ecological quality,and SCS in the Lianshui River watershed(a typical soil and water loss area of red soil in southern China)and its sub-watersheds in *** boosted regression tree model was used to explore the influence of 15 factors(i.e.,landscape and quality attributes)on SCS at the sub-watershed *** to the results,compared with the landscape attribute,the quality attribute of the watershed ecosystem could better explain the spatial heterogeneity of SCS across 66 *** overall degree of influence of five quality factors on SCS reached 57.81%,with the highest being the normalized differential build-up and bare soil index(NDBSI),at 25.11%.Among 10 landscape factors,aggregation had the greatest influence on SCS,at 28.64%.The relationships between key influencing factors and SCS were nonmonotonic and non-linear,with threshold *** example,NDBSI values of 0.18e0.41 had a positive influence on SCS,while NDBSI values of 0.41e0.65 had a negative influence on *** findings broaden our understanding of the response of SCS to changes in landscape and quality attributes at the sub-watershed scale,and could offer comprehensive support for soil erosion management in the watershed ecosystem.

关键词： Landscape pattern Ecological quality Soil conservation service boosted regression tree Red soil region in southern China

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Sustainable Intensification and Large-scale Operation of Cultivated Land Use at the Farmers’ Scale:A Case Study of Shandong Province,China

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Chinese Geographical Science 2024年第1期34卷 149-167页

作者： LI Li LYU Xiao ZHANG Anlu NIU Shandong PENG Wenlong School of Public Administration Huazhong Agricultural UniversityWuhan430070China Department of Geography University of ZurichZurich8057Switzerland School of Humanities and Law Northeastern UniversityShenyang110169China School of Geography and Tourism Qufu Normal UniversityRizhao276800China

Sustainable intensification of cultivated land use(SICLU) and large-scale operations(LSO) are widely acknowledged strategies for enhancing agricultural ***,the existing literature has faced challenges in precisely defining SICLU and constructing comprehensive indicators,which has hindered the exploration of factors influencing LSO within the SICLU *** address this gap,we integrated self-efficacy theory into the design of an index framework for evaluating *** subsequently employed econometric models to analyze the significant factors that impact *** findings reveal that SICLU can be divided into four key dimensions:intensive management,efficient output,resource conservation,and ecological environment ***,it is crucial to incorporate belief-based cognitive factors into the index system,as farmers’ understanding of fertilizer and pesticide application significantly influences their willingness to engage in ***,we identify grain market turnover as the most influential factor in promoting LSO,with single-factor contribution rates reaching 70.9% for cultivated land transfer willingness and 62.5% for the total planting ***,unlike irrigation and agricultural machinery inputs,increased labor inputs correspond to larger planting areas for *** trend may be attributed to reduced labor availability because of rural labor migration,whereas the reduction in irrigation and agricultural input is contingent on innovations in production practices and the transfer of cultivated land management ***,SICLU dynamically influences LSO,with each index related to SICLU having an optimal range that fosters *** insights offer valuable guidance for policymakers,emphasizing farmers as their central focus,with the adjustment of input and output factors as a means to achieve LSO as the ultimate *** conclusion,we propose research avenues for further enriching the SICLU framework to ensur

关键词： sustainable intensification of cultivated land use(SICLU) self-efficacy status quo bias input and output boosted regression tree willingness to transfer cultivated land cultivated land planting areas Shandong,China

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Optimization of environmental variables in habitat suitability modeling for mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent waters

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Acta Oceanologica Sinica 2020年第6期39卷 36-47页

作者： Yunlei Zhang Huaming Yu Haiqing Yu Binduo Xu Chongliang Zhang Yiping Ren Ying Xue Lili Xu College of Fisheries Ocean University of ChinaQingdao 266003China Laboratory for Marine Fisheries Science and Food Production Processes Pilot National Laboratory for Marine Science and Technology(Qingdao)Qingdao 266237China College of Oceanic and Atmospheric Sciences Ocean University of ChinaQingdao 266100China Institute of Oceanology Chinese Academy of SciencesQingdao 266071China

Habitat suitability index(HSI)models have been widely used to analyze the relationship between species abundance and environmental factors,and ultimately inform management of marine *** response of species abundance to each environmental variable is different and habitat requirements may change over life history stages and ***,it is necessary to determine the optimal combination of environmental variables in HSI *** this study,generalized additive models(GAMs)were used to determine which environmental variables to be included in the HSI *** variables were retained and weighted in the HSI model according to their relative contribution(%)to the total deviation explained by the boosted regression tree(BRT).The HSI models were applied to evaluate the habitat suitability of mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent areas in 2011 and 2013–*** and seasonal variations in HSI models of mantis shrimp were also *** the four models(non-optimized model,BRT informed HSI model,GAM informed HSI model,and both BRT and GAM informed HSI model),both BRT and GAM informed HSI model showed the best *** environmental variables(bottom temperature,depth,distance offshore and sediment type)were selected in the HSI models for four groups(spring-juvenile,spring-adult,falljuvenile and fall-adult)of mantis *** distribution of habitat suitability showed similar patterns between juveniles and adults,but obvious seasonal variations were *** study suggests that the process of optimizing environmental variables in HSI models improves the performance of HSI models,and this optimization strategy could be extended to other marine organisms to enhance the understanding of the habitat suitability of target species.

关键词： habitat suitability index mantis shrimp generalized additive model boosted regression tree Haizhou Bay

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Priming effect and its regulating factors for fast and slow soil organic carbon pools: A meta-analysis

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Pedosphere 2022年第1期32卷 140-148页

作者： Changfu HUO Junyi LIANG Weidong ZHANG Peng WANG Weixin CHENG Key Laboratory of Forest Ecology and Management Institute of Applied EcologyChinese Academy of SciencesShenyang 110016China Department of Grassland Resources and Ecology College of Grassland Science and TechnologyChina Agricultural UniversityBeijing 100083China Environmental Studies Department University of CaliforniaSanta Cruz CA 95064USA

The priming effect (PE) plays a critical role in the control of soil carbon (C) cycling and influences the alteration of soil organic C (SOC) decomposition by fresh C ***,drivers of PE for the fast and slow SOC pools remain unclear because of the varying results from individual *** meta-analysis in combination with boosted regression tree (BRT) analysis,we evaluated the relative contribution of multiple drivers of PE with substrate and their patterns across each driver *** results showed that the variability of PE was larger for the fast SOC pool than for the slow SOC *** on the BRT analysis,67%and 34%of the variation in PE were explained for the fast and slow SOC pools,*** were seven determinants of PE for the fast SOC pool,with soil total nitrogen (N) content being the most important,followed by,in a descending order,substrate C:N ratio,soil moisture,soil clay content,soil pH,substrate addition rate,and SOC *** directions of PE were negative when soil total N content and substrate C:N ratio were below 2 g kg~(-1)and 20,respectively,but the directions changed from negative to positive with increasing levels of this two *** with optimal water content (50%–70%of the water-holding capacity) or moderately low pH (5–6) were prone to producing a greater *** the slow SOC pool,soil p H and soil total N content substantially explained the variation in *** magnitude of PE was likely to decrease with increasing soil pH for the slow SOC *** addition,the magnitude of PE slightly fluctuated with soil N content for the slow SOC ***,this meta-analysis provided new insights into the distinctive PEs for different SOC pools and indicated knowledge gaps between PE and its regulating factors for the slow SOC pool.

关键词： boosted regression tree fresh C input recalcitrant carbon soil carbon cycling soil carbon mineralization soil moisture soil nitrogen content soil organic carbon

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Machine learning prediction of methane,ethane,and propane solubility in pure water and electrolyte solutions:Implications for stray gas migration modeling

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Acta Geochimica 2024年第5期43卷 971-984页

作者： Ghazal Kooti Reza Taherdangkoo Chaofan Chen Nikita Sergeev Faramarz Doulati Ardejani Tao Meng Christoph Butscher Institute of Geotechnics TU Bergakademie FreibergGustav-Zeuner-Str.109599 FreibergGermany Department of Petroleum Engineering Amirkabir University of TechnologyTehranIran Freiberg Center for Water Research ZeWaF TU Bergakademie Freiberg09599 FreibergGermany School of Mining College of EngineeringUniversity of TehranTehranIran Taiyuan University of Science and Technology Taiyuan 030024China

Hydraulic fracturing is an effective technology for hydrocarbon extraction from unconventional shale and tight gas reservoirs.A potential risk of hydraulic fracturing is the upward migration of stray gas from the deep subsurface to shallow *** stray gas can dissolve in groundwater leading to chemical and biological reactions,which could negatively affect groundwater quality and contribute to atmospheric *** knowledge oflight hydrocarbon solubility in the aqueous environment is essential for the numerical modelling offlow and transport in the ***,we compiled a database containing 2129experimental data of methane,ethane,and propane solubility in pure water and various electrolyte solutions over wide ranges of operating temperature and *** machine learning algorithms,namely regression tree(RT)and boosted regression tree(BRT)tuned with a Bayesian optimization algorithm(BO)were employed to determine the solubility of *** predictions were compared with the experimental data as well as four well-established thermodynamic *** analysis shows that the BRT-BO is sufficiently accurate,and the predicted values agree well with those obtained from the thermodynamic *** coefficient of determination(R2)between experimental and predicted values is 0.99 and the mean squared error(MSE)is 9.97×10^(-8).The leverage statistical approach further confirmed the validity of the model developed.

关键词： Gas solubility Hydraulic fracturing Thermodynamic models regression tree boosted regression tree Groundwater contamination

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Change of impervious surface area and its impacts on urban landscape:an example of Shenyang between 2010 and 2017

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Ecosystem Health and Sustainability 2020年第1期6卷 69-81,68页

作者： Wen Wu Chunlin Li Miao Liu Yuanman Hu Chunliang Xiu Jangho Architecture College Liaoning Provincial Key Laboratory of Urban and Architectural Digital TechnologyNortheastern UniversityShenyangChina Key Laboratory of Forest Ecology and Management Institute of Applied EcologyChinese Academy of SciencesShenyangChina

Introduction:One of the most striking features of urbanization is the replacement of the original natural land cover type by artificial impervious surface area(ISA).However,the extent of the contribution of various environmental factors,especially the growth of 3D space to ISA expansion,and the scope and mechanism of their influences in dramatically expanding cities,are yet to be *** boosted regression tree(BRT)model was adopted to analyze the main influencing factors and driving mechanisms of ISA change in Shenyang,China between 2010 and ***:The nearly complete-coverage ISA(≥0.7)increased from 42%in 2010 to 47%in *** percentage of landscape with a high ISA fraction increased,while the landscape evenness and diversity of ISA *** BRT analysis revealed that elevation,regional population density,and landscape class had the largest influences on the change of urban ISA,contributing 22.55%,18.16%,and 11.18%to the model,***:Overall,topographic and socioeconomic factors had the greatest influence on urban ISA change in Shenyang,followed by land use type and building pattern *** trend of high aggregation was strong in large commercial and residential *** 3D expansion of the city had an influence on its areal expansion.

关键词： Urban impervious surface landscape pattern boosted regression tree linear spectral mixture model driver analysis

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