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Drivers of spatial structure in thinned forests

forest Ecosystems 2024年第2期11卷 202-213页

作者： Zichun Wang Yaoxiang Li Guangyu Wang Zheyu Zhang Ya Chen Xiaoli Liu Rundong Peng College of Mechanical and Electrical engineering Northeast Forestry UniversityHarbin150040China department of forest Resources management University of British ColumbiaVancouverCanada

Background:As is widely known,an increasing number of forest areas were managed to preserve and enhance the health of forest ecosystems.However,previous research on forest management has often overlooked the importance of structure-based.Aims:Our objectives were to define the direction of structure-based forest management.Subsequently,we investigated the relationships between forest structure and the regeneration,growth,and mortality of trees under different thinning treatments.Ultimately,the drivers of forest structural change were explored.Methods:On the basis of 92 sites selected from northeastern China,with different recovery time (from 1 to 15years) and different thinning intensities (0–59.9%) since the last thinning.Principal component analysis (PCA)identified relationships among factors determining forest spatial structure.The structural equation model (SEM)was used to analyze the driving factors behind the changes in forest spatial structure after thinning.Results:Light thinning (0–20%trees removed) promoted forest regeneration,and heavy thinning (over 35% of trees removed) facilitated forest growth.However,only moderate thinning (20%–35%trees removed) created a reasonable spatial structure.While dead trees were clustered,and they were hardly affected by thinning intensity.Additionally,thinning intensity,recovery time,and altitude indirectly improve the spatial structure of the forest by influencing diameter at breast height (DBH) and canopy area.Conclusion:Creating larger DBH and canopy area through thinning will promote the formation of complex forest structures,which cultivates healthy and stable forests.

关键词： Thinning Natural secondary forest Spatial structure Dynamic changes Growth factors Structural equation modeling

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Automated, economical, and environmentally-friendly asphalt mix design based on machine learning and multi-objective grey wolf optimization

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Journal of Traffic and Transportation engineering(English Edition) 2024年第3期11卷 381-405页

作者： Jian Liu Fangyu Liu Linbing Wang department of Civil and environmental engineering Virginia Polytechnic Institute and State University School of environmental CivilAgricultural and Mechanical EngineeringUniversity of Georgia Illinois Center for Transportation Department of Civil and Environmental EngineeringUniversity of Illinois Urbana-Champaign

The increasing impact of the greenhouse effect on ecosystems is prompting transportation agencies to seek methods for reducing CO2emissions during pavement construction and maintenance.Additionally,the laboratory mix design process,which involves selecting aggregate gradation and binder content,is time-consuming and labor-intensive.To accelerate the traditional mix design procedure,this study presented a mix design procedure that can automatically determine gradation and binder content based on machine learning （ML） and a meta-heuristic algorithm.Specifically,ML approaches were employed to model the relationship between volumetric properties (mixture bulk specific gravity（Gmb） and air void （VV）) and both mixture component properties and mixture proportion,based on a dataset collected from literature with 660 mixture designs.Integrated with the prediction of ML models and the modified multi-objective grey wolf optimization （MOGWO）algorithm,an automatic asphalt mix design was proposed to pursue three goals,including VV,cost,and CO2emission.The results indicated that least squares support vector regression （LSSVR） and e Xtreme gradient boosting （XGBoost） achieved the highest prediction accuracies （correlation coefficient:0.92 for VV and 0.96 for Gmb）.The MOGWO algorithm successfully found the 26 optimal mix designs for the case of VV vs.cost vs.CO2emission.Compared to the traditional laboratory design,the optimal mixture with VV of4%achieves a cost saving of 2.46%and a reduction of 4.03%in carbon emission.The volumetric properties of the mixtures output by the approach also align closely with values measured in a laboratory.

关键词： Asphalt mix design Machine learning MOGWO CO 2 emission Volumetric properties

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Why ecosystem characteristics predicted from remotely sensed data are unbiased and biased at the same time-and how this affects applications

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forest Ecosystems 2024年第1期11卷 24-31页

作者： Goran Ståhl Terje Gobakken Svetlana Saarela Henrik J.Persson Magnus Ekstrom Sean P.Healey Zhiqiang Yang Johan Holmgren Eva Lindberg Kenneth Nystrom Emanuele Papucci Patrik Ulvdal Hans OleØrka Erik Næsset Zhengyang Hou Håkan Olsson Ronald E.McRoberts department of forest Resource management Swedish University of Agricultural Sciences90183UmeåSweden Faculty of environmental Sciences and Natural Resource management Norwegian University of Life SciencesÅsNorway USDA forest Service Rocky Mountain Research StationOgdenUTUSA The Key Laboratory for Silviculture and Conservation of Ministry of Education Beijing Forestry UniversityBeijing100083China department of forest Resources University of MinnesotaSt.PaulMNUSA

Remotely sensed data are frequently used for predicting and mapping ecosystem characteristics,and spatially explicit wall-to-wall information is sometimes proposed as the best possible source of information for decisionmaking.However,wall-to-wall information typically relies on model-based prediction,and several features of model-based prediction should be understood before extensively relying on this type of information.One such feature is that model-based predictors can be considered both unbiased and biased at the same time,which has important implications in several areas of application.In this discussion paper,we first describe the conventional model-unbiasedness paradigm that underpins most prediction techniques using remotely sensed(or other)auxiliary data.From this point of view,model-based predictors are typically unbiased.Secondly,we show that for specific domains,identified based on their true values,the same model-based predictors can be considered biased,and sometimes severely so.We suggest distinguishing between conventional model-bias,defined in the statistical literature as the difference between the expected value of a predictor and the expected value of the quantity being predicted,and design-bias of model-based estimators,defined as the difference between the expected value of a model-based estimator and the true value of the quantity being predicted.We show that model-based estimators(or predictors)are typically design-biased,and that there is a trend in the design-bias from overestimating small true values to underestimating large true values.Further,we give examples of applications where this is important to acknowledge and to potentially make adjustments to correct for the design-bias trend.We argue that relying entirely on conventional model-unbiasedness may lead to mistakes in several areas of application that use predictions from remotely sensed data.

关键词： Bias Model-based inference Design-based inference

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A state-of-the-art review of the development of self-healing concrete for resilient infrastructure

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Frontiers of Structural and Civil engineering 2024年第2期18卷 151-169页

作者： Dong LU Xi JIANG Yao ZHANG Shaowei ZHANG Guoyang LU Zhen LENG department of Civil and environmental engineering The Hong Kong Polytechnic UniversityHong Kong 999077China Laboratory of Fire Safety School of Safety Engineering and Emergency ManagementShijiazhuang Tiedao UniversityShijiazhuang 050043China department of Architecture and Civil engineering City University of Hong KongHong Kong 999077China

The brittleness of cement composites makes cracks almost inevitable,producing a serious limitation on the lifespan,resilience,and safety of concrete infrastructure.To address this brittleness,self-healing concrete has been developed for regaining its mechanical and durability properties after becoming cracked,thereby promising sustainable development of concrete infrastructure.This paper provides a comprehensive review of the latest developments in self-healing concrete.It begins by summarizing the methods used to evaluate the self-healing efficiency of concrete.Next,it compares strategies for achieving healing concrete.It then discusses the typical approaches for developing self-healing concrete.Finally,critical insights are proposed to guide future studies on the development of novel self-healing concrete.This review will be useful for researchers and practitioners interested in the field of self-healing concrete and its potential to improve the durability,resilience,and safety of concrete infrastructure.

关键词： resilient infrastructure sustainable concrete self-healing cracks

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Using satellite-derived land surface temperatures to clarify the spatiotemporal warming trends of the Alborz Mountains in northern Iran

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Journal of Mountain Science 2024年第2期21卷 449-469页

作者： ROSHAN Gholamreza SARLI Reza GHANGHERMEH Abdolazim TAHERIZADEH Mehrnoosh NIKNAM Arman department of Geography Golestan UniversityGorgan 49138-15759Iran department of forest Resources management Faculty of ForestryUniversity of Agriculture in KrakowAL.29 Listopada 4631-425 KrakówPoland department of Geoinformatics Physical and Environmental GeographyUniversity of SzegedSzeged 6722Hungary

The Alborz Mountains are some of the highest in Iran,and they play an important role in controlling the climate of the country’s northern regions.The land surface temperature(LST)is an important variable that affects the ecosystem of this area.This study investigated the spatiotemporal changes and trends of the nighttime LST in the western region of the Central Alborz Mountains at elevations of 1500-4000 m above sea level.MODIS data were extracted for the period of 2000-2021,and the Mann-Kendall nonparametric test was applied to evaluating the changes in the LST.The results indicated a significant increasing trend for the monthly average LST in May-August along the southern aspect.Both the northern and southern aspects showed decreasing trends for the monthly average LST in October,November,and March and an increasing trend in other months.At all elevations,the average decadal change in the monthly average LST was more severe along the southern aspect(0.60°C)than along the northern aspect(0.37°C).The LST difference between the northern and southern aspects decreased in the cold months but increased in the hot months.At the same elevation,the difference in the lapse rate between the northern and southern aspects was greater in the hot months than in the cold months.With increasing elevation,the lapse rate between the northern and southern aspects disappeared.Climate change was concluded to greatly decrease the difference in LST at different elevations for April-July.

关键词： Global warming Mountainous areas Lapse rate Surface air temperatures Alborz

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High-resolution multi-scale air pollution system:Evaluation of modelling performance and emission control strategies

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Journal of environmental Sciences 2024年第3期137卷 65-81页

作者： Diogo Lopes Joana Ferreira Sandra Rafael Ka In Hoi Xin Li Yuan Liu Ka-Veng Yuen Kai Meng Mok Ana Isabel Miranda department of Environment and Planning&CESAM University of AveiroAveiroPortugal department of Civil&environmental engineering Faculty of Science and TechnologyUniversity of MacaoMacao SARChina

A high percentage of the world's population lives in areas where air pollutant concentrations exceed the World Health Organization guidelines.This work aims to develop and test,a high-resolution multi-scale air pollution modelling system by integrating a set of adequate tools.This system is able to provide detailed air pollutant concentrations in urban areas and support air quality management strategies through a better identification of different atmospheric processes.It also allows furthering the design and assessment of air pollution control measures for a specific area.To evaluate its performance and suitability,the system was applied to the Macao Special Administrative Region(SAR),China,one of the most densely populated areas on earth,during a winter period when this area is affected by high levels of Particulate Matter(PM).Although the developed system tends to underestimate the PM concentrations,it revealed a good performance in reproducing the temporal and spatial air pollution patterns.Several exceedances of the Chinese air quality standards were calculated and high population exposure to PM pollution was estimated.The tested urban atmospheric emission reduction scenarios have shown air quality improvements,indicating that emission reduction measures at urban level should focus on the domestic sector.However,it is crucial to implement joint pollution prevention strategies with neighbouring regions to improve the air quality in Macao SAR.The approach developed in this work can support policymakers in defining new strategies to reduce atmospheric pollution in urban areas.

关键词： Urban areas High-resolution emission inventory Particulate matter Population exposure

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Autohydrolysis treatment of bamboo and potassium oxalate(K_(2)C_(2)O_(4))activation of bamboo product for CO_(2) capture utilization

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Frontiers of Chemical Science and engineering 2024年第4期18卷 63-72页

作者： Dang Duc Viet Doan Thi Thao Khuong Duy Anh Toshiki Tsubota department of Materials Science Faculty of EngineeringKyushu Institute of TechnologyFukuoka 804-8550Japan Vietnamese Academy of forest Sciences Hanoi 10000Vietnam Collaborative Research Centre for Green Materials on environmental Technology Kyushu Institute of TechnologyFukuoka 808-0196Japan

Typically,the hydroxide agents,such as sodium hydroxide and potassium hydroxide,which have corrosive properties,are used in the carbon activation process.In this study,potassium oxalate(K_(2)C_(2)O_(4)),a less toxic and non-corrosive activating reagent,was used to synthesize activated carbon from the solid residue after autohydrolysis treatment.The effect of the autohydrolysis treatment and the ratio of the K_(2)C_(2)O_(4)/solid residue are presented in this study.Moreover,the comparison between the activated carbon from bamboo and biochar from the solid residue are also reported.The resulting activated carbon from the solid residue exhibited a high surface area of up to 1432 m^(2)·g^(-1) and a total pore volume of up to 0.88 cm^(3)·g^(-1).The autohydrolysis treatment enhanced the microporosity properties compared to those without pretreatment of the activated carbon.The microporosity of the activated carbon from the solid residue was dominated by the pore width at 0.7 nm,which is excellent for CO_(2) storage.At 25℃ and 1.013×10^(5) Pa,the CO_(2) captured reached up to 4.1 mmol·g^(-1).On the other hand,the ratio between K_(2)C_(2)O_(4) and the solid residue has not played a critical role in determining the porosity properties.The ratio of the K_(2)C_(2)O_(4)/solid residue of 2 could help the carbon material reach a highly microporous textural property that produces a high carbon capture capacity.Our finding proved the benefit of using the solid residue from the autohydrolysis treatment as a precursor material and offering a more friendly and sustainable activation carbon process.

关键词： activated carbon bamboo biochar CO_(2)capture potassium oxalate

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Parkland trees on smallholder farms ameliorate soil physical-chemical properties in the semi-arid area of Tigray,Ethiopia

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Journal of Arid Land 2024年第1期16卷 1-13页

作者： Selam LJALEM Emiru BIRHANE Kassa TEKA Daniel H BERHE department of Land Resources management and environmental Protection College of Dryland Agriculture and Natural ResourcesMekelle UniversityMekelle 231Ethiopia Institute of Climate and Society Mekelle UniversityMekelle 231Ethiopia Faculty of environmental Sciences and Natural Resource management Norwegian University of Life Sciences(NMBU)Ås 1432Norway department of Natural Resources management Adigrat UniversityAdigrat 50Ethiopia

Proposed agroforestry options should begin with the species that farmers are most familiar with,which would be the native multipurpose trees that have evolved under smallholder farms and socioeconomic conditions.The African birch(Anogeissus leiocarpa(DC.)Guill.&Perr.)and pink jacaranda(Stereospermum kunthianum Cham.)trees are the dominant species in the agroforestry parkland system in the drylands of Tigray,Ethiopia.Smallholder farmers highly value these trees for their multifunctional uses including timber,firewood,charcoal,medicine,etc.These trees also could improve soil fertility.However,the amount of soil physical and chemical properties enhanced by the two species must be determined to maintain the sustainable conservation of the species in the parklands and to scale up to similar agroecological systems.Hence,we selected twelve isolated trees,six from each species that had similar dendrometric characteristics and were growing in similar environmental conditions.We divided the canopy cover of each tree into three radial distances:mid-canopy,canopy edge,and canopy gap(control).At each distance,we took soil samples from three different depths.We collected 216 soil samples(half disturbed and the other half undisturbed)from each canopy position and soil depth.Bulk density(BD),soil moisture content(SMC),soil organic carbon(SOC),total nitrogen(TN),available phosphorus(AP),available potassium(AK),p H,electrical conductivity(EC),and cation exchange capacity(CEC)were analysed.Results revealed that soil physical and chemical properties significantly improved except for soil texture and EC under both species,CEC under A.leiocarpus,and soil p H under S.kunthianum,all the studied soils were improved under both species canopy as compared with canopy gap.SMC,TN,AP,and AK under canopy of these trees were respectively 24.1%,11.1%,55.0%,and 9.3% higher than those soils under control.The two parkland agroforestry species significantly enhanced soil fertility near the canopy of topsoil through improving soil physical and chemica

关键词： agroforestry bulk density carbon stock dispersed tree soil texture tree canopy

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Monitoring and evaluation of the water quality of the Lower Neches River, Texas, USA

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Water Science and engineering 2024年第1期17卷 21-32页

作者： Qin Qian Mengjie He Frank Sun Xinyu Liu department of Civil and environmental engineering Lamar UniversityBeaumontTX 77710USA department of Industry engineering Lamar UniversityBeaumontTX 77710USA department of Computer Science Lamar UniversityBeaumontTX 77710USA

Increasing bacteria levels in the Lower Neches River caused by Hurricane Harvey has been of a serious concern.This study is to analyze the historical water sampling measurements and real-time water quality data collected with wireless sensors to monitor and evaluate water quality under different hydrological and hydraulic conditions.The statistical and Pearson correlation analysis on historical water samples determines that alkalinity,chloride,hardness,conductivity,and pH are highly correlated,and they decrease with increasing flow rate due to dilution.The flow rate has positive correlations with Escherichia coli,total suspended solids,and turbidity,which demonstrates that runoff is one of the causes of the elevated bacteria and sediment loadings in the river.The correlation between E.coli and turbidity indicates that turbidity greater than 45 nephelometric turbidity units in the Neches River can serve as a proxy for E.coli to indicate the bacterial outbreak.A series of statistical tools and an innovative two-layer data smoothing filter are developed to detect outliers,fill missing values,and filter spikes of the sensor measurements.The correlation analysis on the sensor data illustrates that the elevated sediment/bacteria/algae in the river is either caused by the first flush rain and heavy rain events in December to March or practices of land use and land cover.Therefore,utilizing sensor measurements along with rainfall and discharge data is recommended to monitor and evaluate water quality,then in turn to provide early alerts on water resources management decisions.

关键词： Water quality Pearson correlation analysis Lower Neches River YSI wireless sensors Non-point pollution

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Causal relationship between circulating vitamin C and 25-hydroxyvitamin D concentrations and common mental disorders-a Mendelian randomization study

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Food Science and Human Wellness 2024年第4期13卷 1877-1885页

作者： Yuanyuan Wang Lirong Dong Meng Zhao Shiyu Yin Pan Da Dengfeng Xu Yifei Lu Jiayue Xia Niannian Wang Shaokang Wang Guiju Sun Key Laboratory of environmental Medicine and engineering of Ministry of Education and Department of Nutrition and Food HygieneSchool of Public HealthSoutheast UniversityNanjing 210009China department of Integrated Service and management Jiangsu Provincial Center for Disease Control and PreventionNanjing 210009China

Mental disorders seriously affect people’s health and social stability.This Mendelian randomization(MR)study was designed to investigate the causal relationship between circulating vitamin C(VC)or 25-hydroxyvitamin D(25(OH)D)levels and mental disorders.The data used for the MR analysis were derived from the summary genome-wide association studies(GWAS)database for VC and 25(OH)D and from the Finn Gen consortium for fourteen mental disorders.Based on the inverse variance weighted(IVW)method,we found a potential causal association between circulating VC and anxiety disorders(IVW:OR=1.139,95%CI:1.023-1.269,P=0.018).However,no causal association was found between VC or 25(OH)D and other mental disorders(P>0.05).In the reverse MR analysis,individuals with Alzheimer’s disease was causally associated with higher concentrations of circulating VC(P=0.012),while individuals with anxiety disorders had a negative association between the concentrations of 25(OH)D(P=0.012).However,the current evidence does not support a causal relationship between VC or 25(OH)D and other mental disorders.In addition,there was no causal association between circulating VC and 25(OH)D(P>0.05).Future studies are needed to confirm these findings and to elucidate the mechanisms of potential causality.

关键词： Circulating vitamin C 25-Hydroxyvitamin D Mental disorder Mendelian randomization

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