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Assessment of spongy moth infestation impacts on forest productivity and carbon loss using the Sentinel-2 satellite remote sensing and eddy covariance flux data

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Ecological Processes 2024年第2期13卷 231-245页

作者： Nur Hussain Alemu Gonsamo Shusen Wang M.Altaf Arain School of Earth Environment and Society and McMaster Centre for Climate Change Mc Master University Canada centre for Remote Sensing Natural Resources Canada

Background Deciduous forests in eastern North America experienced a widespread and intense spongy moth（Lymantria dispar） infestation in 2021. This study quantified the impact of this spongy moth infestation on carbon（C） cycle in forests across the Great Lakes region in Canada, utilizing high-resolution（10 × 10 m2） Sentinel-2 satellite remote sensing images and eddy covariance（EC） flux data. Study results showed a significant reduction in leaf area index（LAI） and gross primary productivity（GPP） values in deciduous and mixed forests in the region in *** Remote sensing derived, growing season mean LAI values of deciduous（mixed） forests were 3.66（3.18）, 2.74（2.64）, and 3.53（2.94） m2m-2in 2020, 2021 and 2022, respectively, indicating about 24（14）% reduction in LAI, as compared to pre-and post-infestation years. Similarly, growing season GPP values in deciduous（mixed） forests were 1338（1208）, 868（932）, and 1367（1175） g C m-2, respectively in 2020, 2021 and 2022, showing about 35（22）% reduction in GPP in 2021 as compared to pre-and post-infestation years. This infestation induced reduction in GPP of deciduous and mixed forests, when upscaled to whole study area（178,000 km2）, resulted in 21.1（21.4） Mt of C loss as compared to 2020（2022）, respectively. It shows the large scale of C losses caused by this infestation in Canadian Great Lakes *** The methods developed in this study offer valuable tools to assess and quantify natural disturbance impacts on the regional C balance of forest ecosystems by integrating field observations, high-resolution remote sensing data and models. Study results will also help in developing sustainable forest management practices to achieve net-zero C emission goals through nature-based climate change solutions.

关键词： Spongy moth Infestation Carbon Gross ecosystem productivity Leaf area index Temperate forest Remote sensing Sentinel-2 Eddy covariance

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Pollen analysis reveals the effects of uncovered interactions,pollen-carrying structures,and pollinator sex on the structure of wild bee-plant networks

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Insect Science 2024年第3期31卷 971-988页

作者： Clément Tourbez Carmelo Gómez-Martínez MiguelÁngel Gonzalez-Estévez Amparo Lazaro Mediterranean Institute for Advanced Studies(UIB-CSIC) Global Change Research GroupEsporlesBalearic IslandsSpain Department of Biology Ecology AreaUniversity of the Balearic/slandsPalmaSpain

Pollination networks are increasingly used to model the complexity of interactions between pollinators and flowering plants in *** methods exist to sample these interactions,with direct observations of plant-pollinator contacts in the field being by far the most *** the identification of pollen carried by pollinators allows uncovering interactions and increasing sample sizes,the methods used to build pollen-transport networks are variable and their effect on network structure remains *** understand how interaction sampling influences the structure of networks,we analyzed the pollen found on wild bees from eight communities across Mallorca Island and investigated the differences in pollen loads between bee body parts(scopa ***)and *** then assessed how these differences,as well as the uncovered interactions not detected in the field,influenced the structure of wild bee-plant *** identified a higher quantity and diversity of pollen in the scopa than in the rest of the female body,but these differences did not lead to differences in structure between plant-pollination(excluding scopa pollen)and bee-feeding interaction(including scopa pollen)***,networks built with pollen data were richer in plant species and interactions and showed lower modularity and specialization(H2'),and higher nestedness than visitation networks based on field *** interactions with plants were stronger compared to those of males,although not ***,females were more generalist(low d')and tended to be more central in interaction networks,indicating their more key role structuring pollination networks in comparison to *** study highlights the importance of palynological data to increase the resolution of networks,as well as to understand important ecological questions such as the differences between plant-pollination and bee-feeding interaction networks,and the role of sexes in pollination.

关键词： palynology pollen-transport networks pollination role of bee sexes sampling methodology visitation networks

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Effects of nitrogen and phosphorus additions on soil nematode community of soybean farmland

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Soil Ecology Letters 2024年第2期6卷 45-55页

作者： Huiying Zhang Mengyang Tian Meiguang Jiang Jingyuan Yang Qi Xu Ying Zhang Minglu Ji Yuteng Yao Cancan Zhao Yuan Miao International Joint research Laboratory for global change Ecology School of Life SciencesHenan UniversityKaifeng475004China Henan Dabieshan National Field Observation and research Station of Forest Ecosystem Xinyang Academy of Ecological ResearchXinyang464000China

The nitrogen(N)and phosphorus(P)addition promotes the abundance of soybean soil *** addition of nitrogen can alleviate the suppression of phosphorus on *** addition affects nematode abundance by ammonium nitrogen.

关键词： soil nematodes nitrogen addition phosphorus addition soil food web soybean

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Multiscale spatiotemporal meteorological drought prediction:A deep learning approach

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Advances in Climate change research 2024年第2期15卷 211-221页

作者： Jia-Li ZHANG Xiao-Meng HUANG Yu-Ze SUN Department of Earth System Science Ministry of Education Key Laboratory for Earth System ModellingInstitute for Global Change StudiesTsinghua UniversityBeijing 100084China

Reliable monitoring and thorough spatiotemporal prediction of meteorological drought are crucial for early warning and decision-making regarding drought-related *** utilisation of multiscale methods is effective for a comprehensive evaluation of drought occurrence and progression,given the complex nature of meteorological ***,the nonlinear spatiotemporal features of meteorological droughts,influenced by various climatological,physical and environmental factors,pose significant challenges to integrated prediction that considers multiple indicators and time *** address these constraints,we introduce an innovative deep learning framework based on the shifted window transformer,designed for executing spatiotemporal prediction of meteorological drought across multiple *** formulate four prediction indicators using the standardized precipitation index and the standard precipitation evaporation index as core methods for drought definition using the ERA5 reanalysis *** indicators span time scales of approximately 30 d and one ***-term indicators capture more anomalous variations,whereas long-term indicators attain comparatively higher accuracy in predicting future *** focus on the East Asian region,notable for its diverse climate conditions and intricate terrains,to validate the model's efficacy in addressing the complexities of nonlinear spatiotemporal *** model's performance is evaluated from diverse spatiotemporal viewpoints,and practical application values are analysed by representative drought *** results substantiate the effectiveness of our proposed model in providing accurate multiscale predictions and capturing the spatiotemporal evolution characteristics of *** of the four drought indicators accurately delineates specific facets of the meteorological drought ***,three representative drought events,namely flash drought,sustained drought and severe drought,

关键词： Meteorological drought Spatiotemporal prediction Multiscale Swim transformer Deep learning

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Co-influence of the start of thermal growing season and precipitation on vegetation spring green-up on the Tibetan Plateau

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Advances in Climate change research 2024年第2期15卷 327-337页

作者： Chen-Peng WANG Meng-Tian HUANG Pan-Mao ZHAI State Key Laboratory of Severe Weather and Institute of global change and Polar Meteorology Chinese Academy of Meteorological SciencesBeijing 100081China University of Chinese Academy of Sciences Beijing 100049China

The climate in the Tibetan Plateau(TP)has undergone significant change in recent decades,mainly in thermal and water conditions,which plays a crucial role in phenological changes in vegetation spring ***,how the start of the thermal growing season(SOS-T)and the start of the rainy season(SORS)as key climatic factors affect vegetation green-up remains *** that these factors characterize thermal and water conditions required for vegetation green-up,this study investigated changes in the SOS-T and SORS from 1961 to 2022,using observation-based datasets with long time *** found that the SOS-T and SORS have advanced across the TP in 1961-2022 and have shown a spatial pattern of advancement in the east and delay in the west in ***,the co-effect of temperature and precipitation change on the start of vegetation growing season(SOS-V)in 2000-2022 was *** across TP,the SOS-V had an early onset of 1.3 d per decade during 2000-2022,corresponding to advanced SOS-T and ***,the SOS-V generally occurred nearly at the same time as the SOS-T in the high-altitude meadow region.A substantial delay in the SOS-V relative to the SOS-T was observed in the desert,shrub,grassland and forest regions and generally kept pace with the ***,for 50%of the vegetated regions on the TP,inter-annual variation in the delay in the SOS-V relative to the SOS-T was dominated by precipitation change,which was profound in warm-climate *** study highlights the co-regulation of precipitation and temperature change in the SOS-V in different vegetation cover regions in the TP,offering a scientific foundation for comprehending the impact of climate change and prospects for vegetation phenology on the TP.

关键词： Tibetan Plateau Start of growing season Temperature Precipitation Climate change

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Reply to “Beyond microbial carbon use efficiency”

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National Science Review 2024年第4期11卷 35-37页

作者： Feng Tao Johannes Lehmann Ying-Ping Wang Lifen Jiang Bernhard Ahrens Kostiantyn Viatkin Stefano Manzoni Benjamin Z.Houlton Yuanyuan Huang Xiaomeng Huang Yiqi Luo Department of Ecology and Evolutionary Biology Cornell University Soil and Crop Sciences Section School of Integrative Plant ScienceCornell University CSIRO Environment Max Planck Institute for Biogeochemistry Department of Physical Geography and Bolin centre for Climate research Stockholm University Department of global Development Cornell University Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Department of Earth System Science Ministry of Education Key Laboratory for Earth System Modelling Institute for Global Change Studies Tsinghua University

In their commentary, Xiao et al.[1]cautioned that the conclusions on the critical role of microbial carbon use efficiency (CUE) in global soil organic carbon (SOC) storage in the paper by Tao et al.[2] might be too *** claimed that Tao et al.’s study lacked mechanistic consideration of SOC formation and excluded important data *** et al. brought up important points,which can be largely reconciled with our findings by understanding the differences in expressing processes in empirical studies and in models.

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Projecting Spring Consecutive Rainfall Events in the Three Gorges Reservoir Based on Triple-Nested Dynamical Downscaling

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Advances in Atmospheric Sciences 2024年第8期41卷 1539-1558页

作者： Yanxin ZHENG Shuanglin LI Noel KEENLYSIDE Shengping HE Lingling SUO Department of Atmospheric Science CMA-CUG Joint Centre for Severe Weather and Climate and Hydro-geological HazardsChina University of GeosciencesWuhan 430074China Institute of Atmospheric Physics and Climate change research Center Chinese Academy of SciencesBeijing 100029China Three Gorges National Climatological Observatory Yichang 443099China Geophysical Institute University of Bergen and Bjerknes Centre for Climate ResearchBergen 5007Norway Nansen Environmental and Remote Sensing Center and Bjerknes centre for Climate research Bergen 5007Norway Nansen-Zhu International research centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China

Spring consecutive rainfall events(CREs) are key triggers of geological hazards in the Three Gorges Reservoir area(TGR), China. However, previous projections of CREs based on the direct outputs of global climate models(GCMs) are subject to considerable uncertainties, largely caused by their coarse resolution. This study applies a triple-nested WRF(Weather research and Forecasting) model dynamical downscaling, driven by a GCM, MIROC6(Model for Interdisciplinary research on Climate, version 6), to improve the historical simulation and reduce the uncertainties in the future projection of CREs in the TGR. Results indicate that WRF has better performances in reproducing the observed rainfall in terms of the daily probability distribution, monthly evolution and duration of rainfall events, demonstrating the ability of WRF in simulating CREs. Thus, the triple-nested WRF is applied to project the future changes of CREs under the middle-of-the-road and fossil-fueled development scenarios. It is indicated that light and moderate rainfall and the duration of continuous rainfall spells will decrease in the TGR, leading to a decrease in the frequency of CREs. Meanwhile, the duration, rainfall amount, and intensity of CREs is projected to regional increase in the central-west TGR. These results are inconsistent with the raw projection of MIROC6. Observational diagnosis implies that CREs are mainly contributed by the vertical moisture advection. Such a synoptic contribution is captured well by WRF, which is not the case in MIROC6,indicating larger uncertainties in the CREs projected by MIROC6.

关键词： triple-nested downscaling Three Gorges Reservoir area consecutive rainfall events geological hazards projection

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Mobility of rhenium and selenium during chemical weathering and their implication for petrogenic organic carbon oxidation

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Science China Earth Sciences 2024年第3期67卷 740-750页

作者： Yuhong ZHANG Jin WANG Yuanxin QU Chao ZHU Zhangdong JIN State Key Laboratory of Loess and Quaternary Geology Institute of Earth EnvironmentChinese Academy of SciencesXi'an 710061China University of Chinese Academy of Sciences Beijing 100049China Xi'an Institute for Innovative Earth Environment research Xi'an 710061China Institute of global Environmental change Xi'an Jiaotong UniversityXi'an 710049China

The oxidative weathering of petrogenic organic carbon(OC_(petro)) is an important source of carbon dioxide(CO_(2)) into the atmosphere on geological timescales and significantly influences the carbon cycle and global climate change. However, at present, a robust proxy to assess OC_(petro)oxidation is lacking. Riverine rhenium(Re) has emerged as a potential proxy to trace OC_(petro)oxidation, but little is known about Re sources and its relationship with OC_(petro)oxidation. To better understand the robustness of this proxy, we analyzed a shale weathering profile from the early Cambrian Shuijingtuo Formation in Chengkou County, Chongqing City, to address the mobility of Re and selenium(Se) and their relationship with the oxidation of OC_(petro)by analyses of the elemental variation and sequential extraction. The results showed that the chemical index of alteration(CIA)increases from the fresh bedrock to the weathered sections, indicating enhanced weathering intensity. Based on the sequential extraction and mass transfer coefficients(τ), Re and Se mainly exist in the organic phase of shale and are paired lost with OC_(petro) during weathering, with no obvious correlation with sulfide minerals. Furthermore, the different proportions of Re and Se loss with OC_(petro) loss can be attributed to their different geochemical behaviors during weathering. Our study supports Re as a robust proxy to trace OC_(petro) oxidation, whereas Se is the potential one. In the future, combined studies on various sedimentary rock profiles with catchment basins are needed to determine the sources of riverine Re and Se and their relationships with OC_(petro) oxidation.

关键词： Rhenium and selenium Shale Mobility OC_(petro) Chemical weathering

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Analysis of Hot Topics Regarding global Smart Elderly Care research—1997-2021

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China CDC weekly 2024年第9期6卷 157-161页

作者： Hongman Wang Hong Chen Yuqi Wang School of Health Humanities Peking UniversityBeijingChina Center for global Public Health Chinese Center for Disease Control and PreventionBeijingChina

Summary What is already known about this topic?With the assistance of the internet,big data,cloud computing,and other technologies,the concept of smart elderly care has *** is added by this report?This study presents information on the countries or regions that have conducted research on smart elderly care,as well as identifies global hotspots and development trends in this field.

关键词： Smart internet smart

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Fine classification of rice paddy using multitemporal compact polarimetric SAR C band data based on machine learning methods

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Frontiers of Earth Science 2024年第1期18卷 30-43页

作者： Xianyu GUO Junjun YIN Kun LI Jian YANG Huimin ZOU Fukun YANG School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Aerospace Information research Institute Chinese Academy of SciencesBeijing 100094China Department of Electronic Engineering Tsinghua UniversityBeijing 100084China College of global change and Earth System Science Beijing Normal UniversityBeijing 100875China

Rice is an important food crop for human *** distinguishing different varieties and sowing methods of rice on a large scale can provide more accurate information for rice growth monitoring,yield estimation,and phenological monitoring,which has significance for the development of modern *** polarimetric(CP)synthetic aperture radar(SAR)provides multichannel information and shows great potential for rice monitoring and ***,the use of machine learning methods to build classification models is a controversial *** this paper,the advantages of CP SAR data,the powerful learning ability of machine learning,and the important factors of the rice growth cycle were taken into account to achieve high-precision and fine classification of rice ***,CP SAR data were simulated by using the seven temporal RADARSAT-2 C-band data ***,20-two CP SAR parameters were extracted from each of the seven temporal CP SAR data *** addition,we fully considered the change degree of CP SAR parameters on a time scale(ΔCP_(DoY)).Six machine learning methods were employed to carry out the fine classification of rice *** results show that the classification methods of machine learning based on multitemporal CP SAR data can obtain better results in the fine classification of rice paddies by considering the parameters ofΔCP_(DoY).The overall accuracy is greater than 95.05%,and the Kappa coefficient is greater than *** them,the random forest(RF)and support vector machine(SVM)achieve the best results,with an overall accuracy reaching 97.32%and 97.37%,respectively,and Kappa coefficient values reaching 0.965 and 0.966,*** the two types of rice paddies,the average accuracy of the transplant hybrid(T-H)rice paddy is greater than 90.64%,and the highest accuracy is 95.95%.The average accuracy of direct-sown japonica(D-J)rice paddy is greater than 92.57%,and the highest accuracy is 96.13%.

关键词： compact polarimetric(CP)SAR rice paddy machine learning fine classification multitemporal

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