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Author Correction: Human and environmental safety of carbon nanotubes across their life cycle

Nature Reviews Materials 2024年 374页

作者： Mijin Kim Dana Goerzen Prakrit V. Jena Emma Zeng Daniel A. Heller Matteo Pasquali Rachel A. Meidl Molecular Pharmacology Program Memorial Sloan Kettering Cancer Center New York NY USA School of Chemistry and Biochemistry Georgia Institute of Technology Atlanta GA USA Department of Physiology Biophysics and Systems Biology Weill Cornell Medicine Cornell University New York NY USA Department of Pharmacology Weill Cornell Medicine Cornell University New York NY USA Department of Chemical and Biomolecular Engineering Rice University Houston TX USA Carbon Hub Rice University Houston TX USA Department of Chemistry Rice University Houston TX USA Department of Materials Science and NanoEngineering Rice University Houston TX USA Smalley-Curl Institute Rice University Houston TX USA Baker Institute for Public Policy Rice University Houston TX USA

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Left ventricular hypertrophy detection using electrocardiographic signal

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Scientific reports 2023年第1期13卷 2556页

作者： Cheng-Wei Liu Fu-Hsing Wu Yu-Lun Hu Ren-Hao Pan Chuen-Horng Lin Yung-Fu Chen Guo-Shiang Tseng Yung-Kuan Chan Ching-Lin Wang Division of Cardiology Department of Internal Medicine Tri-Service General Hospital Songshan Branch National Defense Medical Center Taipei Taiwan. Bachelor Degree Program of Artificial Intelligence National Taichung University of Science and Technology Taichung Taiwan. Department of Management Information Systems National Chung-Hsing University Taichung Taiwan. La Vida Tec. Co. Ltd. Taichung Taiwan. Preventive Medicine Center National Yang Ming Chiao Tung University Taipei Taiwan. Department of Information Management Tunghai University Taichung Taiwan. Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung Taiwan. Department of Dental Technology and Materials Science Central Taiwan University of Science and Technology Taichung Taiwan. Division of Cardiology Department of Internal Medicine Taoyuan Armed Force General Hospital Hsinchu Branch Hsinchu Taiwan. Department of Management Information Systems National Chung-Hsing University Taichung Taiwan. ykchan@nchu.edu.tw. Department of Information Management National Chin-Yi University of Technology Taichung Taiwan. clwang@ncut.edu.tw.

Left ventricular hypertrophy (LVH) indicates subclinical organ damage, associating with the incidence of cardiovascular diseases. From the medical perspective, electrocardiogram (ECG) is a low-cost, non-invasive, and easily reproducible tool that is often used as a preliminary diagnosis for the detection of heart disease. Nowadays, there are many criteria for assessing LVH by ECG. These criteria usually include that voltage combination of RS peaks in multi-lead ECG must be greater than one or more thresholds for diagnosis. We developed a system for detecting LVH using ECG signals by two steps: firstly, the R-peak and S-valley amplitudes of the 12-lead ECG were extracted to automatically obtain a total of 24 features and ECG beats of each case (LVH or non-LVH) were segmented; secondly, a back propagation neural network (BPN) was trained using a dataset with these features. Echocardiography (ECHO) was used as the gold standard for diagnosing LVH. The number of LVH cases (of a Taiwanese population) identified was 173. As each ECG sequence generally included 8 to 13 cycles (heartbeats) due to differences in heart rate, etc., we identified 1466 ECG cycles of LVH patients after beat segmentation. Results showed that our BPN model for detecting LVH reached the testing accuracy, precision, sensitivity, and specificity of 0.961, 0.958, 0.966 and 0.956, respectively. Detection performances of our BPN model, on the whole, outperform 7 methods using ECG criteria and many ECG-based artificial intelligence (AI) models reported previously for detecting LVH.

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Author Correction: Feasibility of peak temperature targets in light of institutional constraints

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Nature Climate Change 2025年 119页

作者： Christoph Bertram Ryna Cui Nate Hultman Gokul Iyer Gunnar Luderer Elmar Kriegler Rahel Mandaroux Elina Brutschin Bas van Ruijven Oliver Fricko Shinichiro Fujimori Volker Krey Joeri Rogelj Keywan Riahi Laurent Drouet Lara Aleluia Reis Luiz Bernardo Baptista Roberto Schaeffer Harmen-Sytze de Boer Vassilis Daioglou Isabela Tagomori Detlef van Vuuren Florian Fosse Kimon Keramidas Dimitris Fragkiadakis Zoi Vrontisi Diego Silva Robin D. Lamboll Pedro Rochedo Center for Global Sustainability (CGS) School of Public Policy University of Maryland College Park MD USA Potsdam Institute for Climate Impact Research (PIK) Member of the Leibniz Association Potsdam Germany Joint Global Change Research Institute Pacific Northwest National Laboratory and University of Maryland College Park MD USA Global Energy Systems Analysis Technische Universität Berlin Berlin Germany Faculty of Economics and Social Sciences University of Potsdam Potsdam Germany International Institute for Applied System Analysis (IIASA) Laxenburg Austria Department of Environmental Engineering Kyoto University Kyoto Japan Social Systems Division National Institute for Environmental Studies (NIES) Tsukuba Japan Centre for Environmental Policy and Grantham Institute–Climate Change and Environment Imperial College London London UK Graz University of Technology Graz Austria CMCC Foundation–Euro-Mediterraneaen Center on Climate Change Milan Italy RFF-CMCC European Institute of Economics and the Environment Milan Italy Centre for Energy and Environmental Economics (Cenergia) Energy Planning Program (PPE) COPPE Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil Netherland’s Environmental Agency (PBL) The Hague The Netherlands Copernicus Institute for Sustainable Development Utrecht University Utrecht The Netherlands European Commission Joint Research Centre (JRC) Seville Spain Grenoble Applied Economics Lab Université Grenoble Alpes Grenoble France E3Modelling Athens Greece Research and Innovation Center on CO2 and Hydrogen (RICH Center) and Management Science and Engineering Department Khalifa University Abu Dhabi United Arab Emirates

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Computationally designed proteins mimic antibody immune evasion in viral evolution

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Immunity 2025年

作者： Youssef, Noor Gurev, Sarah Ghantous, Fadi Brock, Kelly P. Jaimes, Javier A. Thadani, Nicole N. Dauphin, Ann Sherman, Amy C. Yurkovetskiy, Leonid Soto, Daria Estanboulieh, Ralph Kotzen, Ben Notin, Pascal Kollasch, Aaron W. Cohen, Alexander A. Dross, Sandra E. Erasmus, Jesse Fuller, Deborah H. Bjorkman, Pamela J. Lemieux, Jacob E. Luban, Jeremy Seaman, Michael S. Marks, Debora S. Department of Systems Biology Harvard Medical School Boston 02115 MA United States Broad Institute of Harvard and MIT Cambridge 02139 MA United States Department of Electrical Engineering and Computer Science MIT Cambridge 02139 MA United States Center for Virology and Vaccine Research Beth Israel Deaconess Medical Center Boston 02215 MA United States Program in Molecular Medicine University of Massachusetts Chan Medical School Worcester 01655 MA United States Division of Infectious Diseases Department of Medicine Brigham and Women's Hospital Boston 02115 MA United States Massachusetts General Hospital Boston 02114 MA United States Division of Biology and Biological Engineering California Institute of Technology Pasadena 91125 CA United States Department of Microbiology University of Washington Seattle 98195 WA United States National Primate Research Center Seattle 98109 WA United States HDT Bio Seattle 98109 WA United States Massachusetts Consortium on Pathogen Readiness Boston 02115 MA United States Ragon Institute of MGH MIT and Harvard Cambridge 02139 MA United States

Recurrent waves of viral infection necessitate vaccines and therapeutics that remain effective against emerging viruses. Our ability to evaluate interventions is currently limited to assessments against past or circulating variants, which likely differ in their immune escape potential compared with future variants. To address this, we developed EVE-Vax, a computational method for designing antigens that foreshadow immune escape observed in future viral variants. We designed 83 SARS-CoV-2 spike proteins that transduced ACE2-positive cells and displayed neutralization resistance comparable to variants that emerged up to 12 months later in the COVID-19 pandemic. Designed spikes foretold antibody escape from B.1-BA.4/5 bivalent booster sera seen in later variants. The designed constructs also highlighted the increased neutralization breadth elicited by nanoparticle-based, compared with mRNA-based, boosters in non-human primates. Our approach offers targeted panels of synthetic proteins that map the immune landscape for early vaccine and therapeutic evaluation against future viral strains. © 2025 The Authors

关键词： antibody escape generative protein models immune landscape machine learning protein design vaccine evaluation viral evolution

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Spatiotemporal dynamics of coastal dead zones in the Gulf of Mexico over 20 years using remote sensing

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Science of the Total Environment 2025年 979卷

作者： Li, Yingjie Xia, Zilong Nguyen, Lan Wan, Ho Yi Wan, Luwen Wang, Mengqiu Jia, Nan Matli, Venkata Rohith Reddy Li, Yi Seeley, Megan Moran, Emilio F. Liu, Jianguo Center for Systems Integration and Sustainability Department of Fisheries and Wildlife Michigan State University East LansingMI48823 United States Environmental Science and Policy Program Michigan State University East LansingMI48823 United States Natural Capital Project Woods Institute for the Environment Doerr School of Sustainability Stanford University StanfordCA94305 United States Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu Nanjing210023 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Jiangsu Nanjing210023 China Department of Biological Sciences University of Calgary CalgaryABT2N 1N4 Canada Department of Wildlife California State Polytechnic University Humboldt ArcataCA95521 United States Department of Wildlife Ecology and Conservation University of Florida GainesvilleFL32611 United States Department of Earth System Science Stanford University StanfordCA94305 United States Earth and Environmental Sciences Michigan State University East LansingMI48824 United States School of Remote Sensing and Information Engineering Wuhan University Wuhan430072 China Department of Earth Sciences The University of Hong Kong Hong Kong 999077 China Center for Geospatial Analytics North Carolina State University RaleighNC27607 United States College of the Environment and Ecology Xiamen University Xiamen361102 China School of Geographical Sciences and Urban Planning Arizona State University TempeAZ85281 United States Center for Global Discovery and Conservation Science Arizona State University TempeAZ85281 United States Center for Global Change and Earth Observations Michigan State University East LansingMI48824 United States Department of Geography Environment and Spatial Science

Spreading marine dead zones (or hypoxia) are threatening coastal ecosystems and affecting billions of people's livelihoods globally. However, the lack of field observations makes it challenging to estimate dead zones with spatial precision and across large scales. While satellites offer great potential for detecting environmental changes through large-scale and temporal consistent data, they have yet to be fully integrated into the spatio-temporal dynamic mapping of hypoxia. To address this limitation, we integrated satellite imagery with field observations in random forest models on the Google Earth Engine platform to characterize dead zone dynamics from 2000 to 2019. We applied the workflow to the Gulf of Mexico, which has the largest dead zones in North America. Our model explained 64 % (± 5 %) of the variance in predicting dead zones using satellite data. The analysis revealed that dead zones in the Gulf peaked in 2009 (17,699 ± 679 km2) and contracted afterward in terms of both size and persistence (% days with hypoxia). Despite this contraction, the average size between 2010 and 2019 was twice that of the coastal reduction goal (2) set by the Gulf of Mexico Hypoxia Task Force. Furthermore, dead zones occurred more frequently in the western Gulf, and nearly half of the western region experienced dead zones annually. In addition to inter-annual changes, our analysis highlighted the intra-annual dynamics of this phenomenon. Notably, dead zones expanded in June, peaking in size from mid-August to early September. The high temporal and spatial resolution of this dataset allows policymakers to develop targeted management plans and environmental policies. Our approach, which incorporates remote sensing for long-term monitoring of coastal dead zones, can be applied to worldwide monitoring initiatives when paired with local field observations. © 2025 Elsevier B.V.

关键词： Eutrophication

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Residential factors associated with mental health in United States Veterans, Air Force military, and Air Force employees

Indoor Environments

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Indoor Environments 2025年第2期2卷

作者： Andrew J. Hoisington Christopher A. Stamper Molly E. Penzenik Meredith Reitter Elizabeth J. Kovacs Nazanin H. Bahraini Lisa A. Brenner Department of Physical Medicine & Rehabilitation University of Colorado Anschutz Medical Campus Aurora CO USA Department of Systems Engineering & Management Air Force Institute of Technology Wright-Patterson AFB OH USA Rocky Mountain Mental Illness Research Education and Clinical Center (MIRECC) Rocky Mountain Regional VA Medical Center (RMRVAMC) Aurora CO USA Department of Surgery Division of GI Trauma and Endocrine Surgery University of Colorado Anschutz Medical Campus Aurora CO USA Alcohol Research Program University of Colorado Anschutz Medical Campus Aurora CO USA Department of Psychiatry University of Colorado Anschutz Medical Campus Aurora CO USA Veterans Health Administration Eastern Colorado Health Care System Rocky Mountain Regional Veterans Affairs Medical Center (RMRVAMC) Aurora CO USA Center for Neuroscience University of Colorado Anschutz Medical Campus Aurora CO USA

Individuals in Westernized countries spend most of their time indoors. However, exploration of residential building factors that may influence occupants’ mental health is limited in scientific literature. The purpose of this study was to explore investigator’s perceived areas of importance in residences to mental health via survey methods. To that end, we administered the Housing, Occupancy, Materials, and Environment (HOME) survey to assess factors that may influence mental health to those working in the United States (US) Air Force (n = 230) or past military members, US Veterans (n = 180). Self-reported mental health surveys were also administered to the Air Force (RAND 36-Item Short-Form) and Veterans (36-Item Short-Form survey version 2, Patient Health Questionnaire-9). The residential question that correlated to the most mental health measures for both groups was an ability to adjust indoor climate, with positive correlations. Other correlations between residential questions and health scores across the two groups were dissimilar, indicating the residential factors of importance to mental health may be variable across an individual’s life. For example, multiple positive correlations between mental health measures and nature in the older Veteran group support robust and support previous results on the importance of nature to older adults. Overall, this study provides a basis for future research and targeted clinical interventions that can quantify and positively impact the home environment and improve mental health outcomes.

关键词： AF Air Force BASE Building Assessment Survey and Evaluation HOME Housing Occupancy Materials and Environment CBE Center for the Built Environment MCS Mental Component Score PCS Physical Component Score MIRECC Rocky Mountain Mental Illness Research Education and Clinical Center US United States US-VMP United States-Veteran Microbiome Project Residences Mental Health Survey Military Indoor Environment Building Quality

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The Ni isotopic composition of Ryugu reveals a common accretion region for carbonaceous chondrites

arXiv

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arXiv 2024年

作者： Spitzer, Fridolin Kleine, Thorsten Burkhardt, Christoph Hopp, Timo Yokoyama, Tetsuya Abe, Yoshinari Aléon, Jérôme OD. Alexander, Conel M. Amari, Sachiko Amelin, Yuri Bajo, Ken-Ichi Bizzarro, Martin Bouvier, Audrey Carlson, Richard W. Chaussidon, Marc Choi, Byeon-Gak Dauphas, Nicolas Davis, Andrew M. Rocco, Tommaso Di Fujiya, Wataru Fukai, Ryota Gautam, Ikshu Haba, Makiko K. Hibiya, Yuki Hidaka, Hiroshi Homma, Hisashi Hoppe, Peter Huss, Gary R. Ichida, Kiyohiro Iizuka, Tsuyoshi Ireland, Trevor R. Ishikawa, Akira Itoh, Shoichi Kawasaki, Noriyuki Kita, Noriko T. Kitajima, Kouki Komatani, Shintaro Krot, Alexander N. Liu, Ming-Chang Masuda, Yuki Morita, Mayu Moynier, Fréderic Motomura, Kazuko Nakai, Izumi Nagashima, Kazuhide Nguyen, Ann Nittler, Larry Onose, Morihiko Pack, Andreas Park, Changkun Piani, Laurette Qin, Liping Russell, Sara S. Sakamoto, Naoya Schönbächler, Maria Tafla, Lauren Tang, Haolan Terada, Kentaro Terada, Yasuko Usui, Tomohiro Wada, Sohei Wadhwa, Meenakshi Walker, Richard J. Yamashita, Katsuyuki Yin, Qing-Zhu Yoneda, Shigekazu Young, Edward D. Yui, Hiroharu Zhang, Ai-Cheng Nakamura, Tomoki Naraoka, Hiroshi Noguchi, Takaaki Okazaki, Ryuji Sakamoto, Kanako Yabuta, Hikaru Abe, Masanao Miyazaki, Akiko Nakato, Aiko Nishimura, Masahiro Okada, Tatsuaki Yada, Toru Yogata, Kasumi Nakazawa, Satoru Saiki, Takanao Tanaka, Satoshi Terui, Fuyuto Tsuda, Yuichi Watanabe, Sei-Ichiro Yoshikawa, Makoto Tachibana, Shogo Yurimoto, Hisayoshi Max Planck Institute for Solar System Research Justus-von-Liebig-Weg 3 Göttingen37077 Germany Department of Earth and Planetary Sciences Tokyo Institute of Technology Tokyo152-8551 Japan Graduate School of Engineering Materials Science and Engineering Tokyo Denki University Tokyo120-8551 Japan Institut de Minéralogie de Physique des Matériaux et de Cosmochimie Sorbonne Université Museum National d'Histoire Naturelle CNRS UMR 7590 IRD Paris75005 France Earth and Planets Laboratory Carnegie Institution for Science WashingtonDC20015 United States McDonnell Center for the Space Sciences and Physics Department Washington University 35 St. LouisMO63130 United States Geochemical Research Center The University of Tokyo Tokyo113-0033 Japan Guangzhou Institute of Geochemistry Chinese Academy of Sciences GD Guangzhou510640 China Departement of Natural History Sciences Hokkaido University Sapporo001-0021 Japan Centre for Star and Planet Formation Globe Institute University of Copenhagen Copenhagen1350 Denmark Bayerisches Geoinstitut Universität Bayreuth Bayreuth95447 Germany Université Paris Cité Institut de Physique du Globe de Paris CNRS Paris75005 France Department of Earth Science Education Seoul National University Seoul08826 Korea Republic of Department of the Geophysical Sciences Enrico Fermi Institute The University of Chicago 5734 South Ellis Avenue Chicago60637 United States Faculty of Geosciences and Geography University of Göttingen GöttingenD-37077 Germany Faculty of Science Ibaraki University Mito310-8512 Japan ISAS/JSEC JAXA Sagamihara252-5210 Japan Research Center for Advanced Science and Technology The University of Tokyo Tokyo153-8904 Japan Research Institute for Marine Resources Utilization Japan Agency for Marine-Earth Science and Technology Kanagawa237-0061 Japan Departement of Earth and Planetary Sciences Nagoya University Nagoya464-8601 Japan Osaka Application Laboratory SBUWDX Rigaku Corporation Osaka569-1

The isotopic compositions of samples returned from Cb-type asteroid Ryugu and Ivuna-type (CI) chondrites are distinct from other carbonaceous chondrites, which has led to the suggestion that Ryugu/CI chondrites formed in a different region of the accretion disk, possibly around the orbits of Uranus and Neptune. We show that, like for Fe, Ryugu and CI chondrites also have indistinguishable Ni isotope anomalies, which differ from those of other carbonaceous chondrites. We propose that this unique Fe and Ni isotopic composition reflects different accretion efficiencies of small FeNi metal grains among the carbonaceous chondrite parent bodies. The CI chondrites incorporated these grains more efficiently, possibly because they formed at the end of the disk’s lifetime, when planetesimal formation was also triggered by photoevaporation of the disk. Isotopic variations among carbonaceous chondrites may thus reflect fractionation of distinct dust components from a common reservoir, implying CI chondrites/Ryugu may have formed in the same region of the accretion disk as other carbonaceous chondrites. © 2024, CC BY.

关键词： Nickel

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Benchmarking Emergency Department Triage Prediction Models with Machine Learning and Large Public Electronic Health Records

arXiv

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arXiv 2021年

作者： Xie, Feng Zhou, Jun Lee, Jin Wee Tan, Mingrui Li, Siqi Rajnthern, Logasan S.O. Chee, Marcel Lucas Chakraborty, Bibhas Wong, An-Kwok Ian Dagan, Alon Ong, Marcus Eng Hock Gao, Fei Liu, Nan Centre for Quantitative Medicine and Programme in Health Services and Systems Research Duke-NUS Medical School Singapore Singapore Singapore Singapore School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Faculty of Medicine Nursing and Health Sciences Monash University VIC Australia Department of Statistics and Data Science National University of Singapore Singapore Singapore Department of Biostatistics and Bioinformatics Duke University DurhamNC United States Division of Pulmonary Allergy and Critical Care Medicine Duke University DurhamNC United States Department of Emergency Medicine Beth Israel Deaconess Medical Center Harvard Medical School BostonMA United States MIT Critical Data Laboratory for Computational Physiology Institute for Medical Engineering and Science Massachusetts Institute of Technology CambridgeMA United States Department of Emergency Medicine Singapore General Hospital Singapore Singapore SingHealth AI Health Program Singapore Health Services Singapore Singapore Institute of Data Science National University of Singapore Singapore Singapore

The demand for emergency department (ED) services is increasing across the globe, particularly during the current COVID-19 pandemic. Clinical triage and risk assessment have become increasingly challenging due to the shortage of medical resources and the strain on hospital infrastructure caused by the pandemic. As a result of the widespread use of electronic health records (EHRs), we now have access to a vast amount of clinical data, which allows us to develop predictive models and decision support systems to address these challenges. To date, however, there are no widely accepted benchmark ED triage prediction models based on large-scale public EHR data. An open-source benchmarking platform would streamline research workflows by eliminating cumbersome data preprocessing, and facilitate comparisons among different studies and methodologies. In this paper, based on the Medical Information Mart for Intensive Care IV Emergency Department (MIMIC-IV-ED) database, we developed a publicly available benchmark suite for ED triage predictive models and created a benchmark dataset that contains over 400,000 ED visits from 2011 to 2019. We introduced three ED-based outcomes (hospitalization, critical outcomes, and 72-hour ED reattendance) and implemented a variety of popular methodologies, ranging from machine learning methods to clinical scoring systems. We evaluated and compared the performance of these methods against benchmark tasks. Our codes are open-source, allowing anyone with MIMIC-IV-ED data access to perform the same steps in data processing, benchmark model building, and experiments. This study provides future researchers with insights, suggestions, and protocols for managing raw data and developing risk triaging tools for emergency care. © 2021, CC BY.

关键词： Learning systems

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Current and future uses of UAS for improved forecasts/warnings and scientific studies

Current and future uses of UAS for improved forecasts/warnin...

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作者： McFarquhar, Greg M. Smith, Elizabeth Pillar-Little, Elizabeth A. Brewster, Keith Chilson, Phillip B. Lee, Temple R. Waugh, Sean Yussouf, Nusrat Wang, Xuguang Xue, Ming de Boer, Gijs Gibbs, Jeremy A. Fiebrich, Chris Baker, Bruce Brotzge, Jerry Carr, Frederick Christophersen, Hui Fengler, Martin Hall, Philip Hock, Terry Houston, Adam Huck, Robert Jacob, Jamey Palmer, Robert Quinn, Patricia K. Wagner, Melissa Zhang, Yan Hawk, Darren Cooperative Institute for Mesoscale Meteorological Studies School of Meteorology University of Oklahoma NormanOK United States Cooperative Institute for Mesoscale Meteorological Studies University of Oklahoma NOAA National Severe Storms Laboratory NormanOK United States School of Meteorology Center for Autonomous Sensing and Sampling University of Oklahoma NormanOK United States Center for Analysis and Prediction of Storms University of Oklahoma NormanOK United States Cooperative Institute for Mesoscale Meteorological Studies University of Oklahoma NormanOK United States NOAA Air Resources Laboratory/Atmospheric Turbulence and Diffusion Division Oak RidgeTN United States NOAA National Severe Storms Laboratory NormanOK United States Cooperative Institute for Mesoscale Meteorological Studies University of Oklahoma NormanOK United States School of Meteorology University of Oklahoma NormanOK United States School of Meteorology Center for Analysis and Prediction of Storms University of Oklahoma NormanOK United States Cooperative Institute for Research on Environmental Studies University of Colorado Boulder NOAA Physical Sciences Division BoulderCO United States Oklahoma Climatological Survey University of Oklahoma NormanOK United States NOAA Air Resources Laboratory Atmospheric Turbulence and Diffusion Division Oak RidgeTN United States University at Albany State University of New York AlbanyNY United States Cooperative Institute of Marine and Atmospheric Studies University of Miami NOAA Atlantic Oceanographic and Meteorological Laboratory Hurricane Research Division MiamiFL United States Meteomatics AG Saint Gall Switzerland NOAA Unmanned Aircraft Systems Program Office Silver SpringMD United States National Center for Atmospheric Research BoulderCO United States University of Nebraska Lincoln Nebraska United States Advanced Technology Initiatives Choctaw Nation of Oklahoma DuranOK United States Oklahoma State University Stillwate

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Spatiotemporal dynamics of ecosystem fires and biomass burning-induced carbon emissions in China over the past two decades

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Geography and Sustainability 2020年第1期1卷 47-58页

作者： Anping Chen Rongyun Tang Jiafu Mao Chao Yue Xiran Li Mengdi Gao Xiaoying Shi Mingzhou Jin Daniel Ricciuto Sam Rabin Phillippe Ciais Shilong Piao Department of Biology Colorado State UniversityFort CollinsCO 80523USA Graduate Degree Program in Ecology Colorado State UniversityFort CollinsCO 80523USA Department of Industrial and Systems Engineering University of TennesseeKnoxvilleTN 37996USA Environmental Sciences Division and Climate Change Science Institute Oak Ridge National LaboratoryOak RidgeTN 37831USA State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau Northwest Agriculture&Forestry UniversityYanglingShanxi 712100China College of Urban and Environmental Sciences Central China Normal UniversityWuhanHubei 430079China Sino-French Institute for Earth System Science College of Urban and Environmental SciencesPeking UniversityBeijing 100871China Atmospheric Environmental Research(IMK-IFU) Institute of Meteorology and Climate ResearchKarlsruhe Institute of Technology(KIT)Kreuzeckbahnstraße 19Garmisch-Partenkirchen 82467Germany LSCE UMR CEA-CNRSBat.709CEL’Orme des MerisiersGif-sur-Yvette 91191France

Fire is a major type of disturbance that has important influences on ecosystem dynamics and carbon *** our understanding of ecosystem fires and their carbon cycle consequences is still limited,largely due to the difficulty of large-scale fire monitoring and the complex interactions between fire,vegetation,climate,and anthropogenic ***,using data from satellite-derived fire observations and ecosystem model simulations,we performed a comprehensive investigation of the spatial and temporal dynamics of China’s ecosystem fire disturbances and their carbon emissions over the past two decades(1997–2016).Satellite-derived results showed that on average about 3.47-4.53×10^(4) km^(2) of the land was burned annually during the past two decades,among which annual burned forest area was about 0.81-1.25×10^(4) km^(2),accounting for 0.33-0.51%of the forest area in *** burning emitted about 23.02 TgC per *** to satellite products,simulations from the Energy Exascale Earth System Land Model(ELM)strongly overestimated China’s burned area and fire-induced carbon *** burned area and fire-induced carbon emissions were high for boreal forest in Northeast China’s Daxing’anling region and subtropical dry forest in South Yunnan,as revealed by both the satellite product and the model *** results suggest that climate and anthropogenic factors play critical roles in controlling the spatial and seasonal distribution of China’s ecosystem fire *** findings highlight the importance of multiple complementary approaches in assessing ecosystem fire disturbance and its carbon *** studies are required to improve the methods of observing and modelling China’s ecosystem fire disturbances,which will provide valuable information for fire management and ecosystem sustainability in an era when both human activities and the natural environment are rapidly changing.

关键词： Fire emission Burned area Fire models China

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