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Li Y, He T, Ding F, Li X, Huang Y, He E, Cai H, Shi P, Liu J, Li Y, Qu R, Zheng W, Xie Y, Liu X, Zhao L, Liu M. The inventory of pollutants in brownfield sites: An innovative strategy for prevention and control of soil pollution in China. Sci Bull (Beijing) 2024; 69:566-569. [PMID: 38218633 DOI: 10.1016/j.scib.2023.12.055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2024]
Affiliation(s)
- Ye Li
- Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Tianhao He
- Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Fangfang Ding
- Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Xiaofei Li
- Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Ye Huang
- Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Erkai He
- Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Hongming Cai
- Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China
| | - Peili Shi
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China
| | - Jian Liu
- College of Environmental Natural Resource Sciences, Zhejiang University, Hangzhou 310058, China
| | - Yan Li
- Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Ruijuan Qu
- State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Wang Zheng
- Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China
| | - Yunfeng Xie
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China
| | - Xingmei Liu
- College of Environmental Natural Resource Sciences, Zhejiang University, Hangzhou 310058, China
| | - Ling Zhao
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Min Liu
- Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, China.
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Chen X, Hou G, Shi P, Zong N, Yu J. Functional Groups Dominate Aboveground Net Primary Production under Long-Term Nutrient Additions in a Tibetan Alpine Meadow. Plants (Basel) 2024; 13:344. [PMID: 38337876 PMCID: PMC10857096 DOI: 10.3390/plants13030344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 01/09/2024] [Accepted: 01/22/2024] [Indexed: 02/12/2024]
Abstract
Anthropogenic nutrient additions are influencing the structure and function of alpine grassland ecosystems. However, the underlying mechanisms of the direct and indirect effects of nutrient additions on aboveground net primary productivity (ANPP) are not well understood. In this study, we conducted an eight-year field experiment to explore the ecological consequences of nitrogen (N) and/or phosphorous (P) additions on the northern Tibetan Plateau. ANPP, species diversity, functional diversity, and functional groups were used to assess species' responses to increasing nutrients. Our results showed that nutrient additions significantly increased ANPP due to the release in nutrient limitations. Although N addition had a significant effect on species richness and functional richness, and P and N + P additions altered functional diversity, it was functional groups rather than biodiversity that drove changes in ANPP in the indirect pathways. We identified the important roles of N and P additions in begetting the dominance of grasses and forbs, respectively. The study highlights that the shift of functional groups should be taken into consideration to better predict the structure, function, and biodiversity-ANPP relationship in grasslands, particularly under future multifaceted global change.
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Affiliation(s)
- Xueying Chen
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (X.C.); (G.H.); (N.Z.); (J.Y.)
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Ge Hou
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (X.C.); (G.H.); (N.Z.); (J.Y.)
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (X.C.); (G.H.); (N.Z.); (J.Y.)
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Ning Zong
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (X.C.); (G.H.); (N.Z.); (J.Y.)
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Jialuo Yu
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (X.C.); (G.H.); (N.Z.); (J.Y.)
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
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Yu J, Hou G, Shi P, Zong N, Peng J. Nitrogen rather than phosphorous addition alters the asymmetric responses of primary productivity to precipitation variability across a precipitation gradient on the northern Tibetan Plateau. Sci Total Environ 2024; 907:167856. [PMID: 37866615 DOI: 10.1016/j.scitotenv.2023.167856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 09/25/2023] [Accepted: 10/13/2023] [Indexed: 10/24/2023]
Abstract
Understanding the response of alpine grassland productivity to precipitation fluctuations is essential for assessing the future changes of ecosystem services. However, the underlying mechanism by which grassland productivity responds to wet and dry years after nitrogen (N) or/and phosphorus (P) nutrient addition remains unclear. In this study, we investigated the dynamics of plant communities based on eight-year N or/and P addition gradient experiments in four grassland types across a precipitation gradient on the north Tibetan Plateau. The asymmetry index (AI) was used to evaluate the responses of aboveground net primary productivity (ANPP) to precipitation fluctuations where AI > 0 indicates a greater increase of ANPP in wet years compared to the decline in dry years, and AI < 0 indicates a greater decline of ANPP in dry years compared to the increase in wet years. Our results showed that the AI values at community level in four natural grasslands were non-significant trend across the precipitation gradient, and showed slightly negative asymmetry, suggesting that the increase of ANPP in wet years was less than the decrease in dry years. N addition resulted in a significant decrease in community-level AI values with increasing mean annual precipitation (MAP), indicating that improved nutrient availability may favor the recovery of productivity in drier grasslands in wet years. At the functional group level, nutrient addition resulted in a significant decrease in the AI values of grasses and legumes and an increase in the AI values of forbs as MAP increased. Furthermore, the coupling of nutrients with precipitation can influence the productivity responses to precipitation changes by affecting soil nutrient availability and species richness. This research provides new insights into better predicting vegetation activity on N deposition rates and precipitation changes exacerbated in the context of climate change.
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Affiliation(s)
- Jialuo Yu
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Ge Hou
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China.
| | - Ning Zong
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Jinlong Peng
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
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Wei J, Shi P, Cui G, Li X, Xu M, Xu D, Xie Y. Analysis of soil pollution characteristics and influencing factors based on ten electroplating enterprises. Environ Pollut 2023; 337:122562. [PMID: 37717896 DOI: 10.1016/j.envpol.2023.122562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 08/31/2023] [Accepted: 09/14/2023] [Indexed: 09/19/2023]
Abstract
The electroplating industry encompasses various processes and plating types that contribute to environmental pollution, which has led to growing public concern. To investigate related soil pollution in China, the study selected 10 sites with diverse industrial characteristics distributed across China and collected 1052 soil samples to determine the presence of industrial priority pollutants (PP) based on production process and pollutant toxicity. The factors influencing site pollution as well as proposed pollution prevention and control approaches were then evaluated. The results indicate the presence of significant pollution in the electroplating industry, with ten constituents surpassing the risk screening values (RSV). The identified PP consist of Cr(VI), zinc (Zn), nickel (Ni), total chromium (Cr), and petroleum hydrocarbons (C10-C40). PP contamination was primarily observed in production areas, liquid storage facilities, and solid zones. The vertical distribution of metal pollutants decreased with soil depth, whereas the reverse was true for petroleum hydrocarbons (C10-C40). Increase in site production time was strongly correlated with soil pollution, but strengthening anti-seepage measures in key areas can effectively reduce the soil exceedance standard ratio. This study serves as a foundation for conceptualizing site repair technology in the electroplating industry and offers a reference and methodology for pollution and source control in this and related sectors.
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Affiliation(s)
- Jinjin Wei
- School of Chemical and Environmental Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China; Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing, 100012, China
| | - Peili Shi
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing, 100012, China
| | - Guannan Cui
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing, 100012, China
| | - Xin Li
- Department of Environment, College of Environment and Resources, Xiangtan University, Xiangtan, Hunan, 411105, China
| | - Minke Xu
- School of Chemical and Environmental Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
| | - Dongyao Xu
- School of Chemical and Environmental Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
| | - Yunfeng Xie
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing, 100012, China.
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Zhu J, Zong N, Shi P, He Y, Yang X, Zhang Y, Jiang L. Resource co-limitation of community biomass but not structure of an alpine grassland. Ecology 2023; 104:e4167. [PMID: 37671849 DOI: 10.1002/ecy.4167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/09/2023] [Accepted: 07/29/2023] [Indexed: 09/07/2023]
Abstract
Anthropogenic environmental changes are influencing the structure and function of many ecological communities, but their underlying mechanisms are often poorly understood. We conducted a 7-year field experiment to explore the ecological consequences of nitrogen (N) and phosphorous (P) enrichment in a high-altitude Tibetan alpine grassland. We found that the enrichment of both N and P, but not either alone, increased plant above- and belowground biomass. In contrast, N, but not P, enrichment reduced species richness and altered plant phylogenetic diversity and structure. Whereas plant species loss and changes in phylogenetic structure were mainly driven by higher soil manganese levels under N addition, they were mainly driven by increased plant belowground biomass under the addition of both N and P. Our study highlights the resource co-limitation of community biomass but not the structure of the study grassland, while also identifying soil metal toxicity and belowground competition as important mechanisms driving community changes following nutrient amendment.
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Affiliation(s)
- Juntao Zhu
- Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Ning Zong
- Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Peili Shi
- Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Yunlong He
- Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Xian Yang
- State Key Laboratory of Biocontrol, School of Ecology, Sun Yat-sen University, Guangzhou, China
| | - Yangjian Zhang
- Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Lin Jiang
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
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Guo Q, Liu J, Dou X, Zhu K, Shi P, Zhang Y, Li S, Feng R, Yue J. Camrelizumab with Chemoradiotherapy for Locally Advanced Biliary Tract Cancer: Preliminary Results from A Phase II Study. Int J Radiat Oncol Biol Phys 2023; 117:e355. [PMID: 37785226 DOI: 10.1016/j.ijrobp.2023.06.2434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) For locally advanced biliary tract cancer (BTC), capecitabine-based chemoradiotherapy (CRT) is commonly used but has limited benefits. Immunotherapy is potentially effective for BTC and may be synergized with CRT. Followed by gemcitabine and cisplatin (GP) consolidation chemotherapy (CT), we evaluated the safety and efficacy of combined camrelizumab and capecitabine-based CRT for locally advanced BTC. MATERIALS/METHODS Patients had stage II-III (T4N0M0, T1-4N+M0) BTC (per the 7th [2010] edition of the American Joint Committee on Cancer staging system) were eligible for CRT (capecitabine plus [50-60 Gy] radiotherapy), to be followed by GP CT. Camrelizumab was given concurrently with CRT. Safety was defined as the incidence and severity of adverse events (AEs), while efficacy was defined as overall survival (OS), progression-free survival (PFS), objective response rate (ORR) and disease control rate (DCR). RESULTS Ten patients completed the planned treatment. None experienced grade ≥3 treatment-related AEs during CRT. Grade ≥3 immune-related AEs occurred in 2 of 10 patients (20%) only during GP CT. The mean OS time was 18.2 months (95% confidence interval [CI] 12.9m-23.5m) while the median OS time was 14.1 months (95% CI 10.1m-18.1m). OS rates were 100%, 59%, 44% at 6 months, 1 year and 2 years, respectively. The ORR was 30% while the DCR was 90%. Two patients (20%) obtained OS over 2 years with partial response (25.9m, 29.1m). Median PFS time was 14.1 months (95% CI 9.3m-18.9m). CONCLUSION Camrelizumab in combination with concurrent CRT was well tolerated and did not impair delivery of CRT in patients with locally advanced BTC.
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Affiliation(s)
- Q Guo
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - J Liu
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - X Dou
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - K Zhu
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - P Shi
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Y Zhang
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - S Li
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - R Feng
- Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - J Yue
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Shandong Cancer Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
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7
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Xie M, Ma X, Wang Y, Li C, Shi H, Yuan X, Hellwich O, Chen C, Zhang W, Zhang C, Ling Q, Gao R, Zhang Y, Ochege FU, Frankl A, De Maeyer P, Buchmann N, Feigenwinter I, Olesen JE, Juszczak R, Jacotot A, Korrensalo A, Pitacco A, Varlagin A, Shekhar A, Lohila A, Carrara A, Brut A, Kruijt B, Loubet B, Heinesch B, Chojnicki B, Helfter C, Vincke C, Shao C, Bernhofer C, Brümmer C, Wille C, Tuittila ES, Nemitz E, Meggio F, Dong G, Lanigan G, Niedrist G, Wohlfahrt G, Zhou G, Goded I, Gruenwald T, Olejnik J, Jansen J, Neirynck J, Tuovinen JP, Zhang J, Klumpp K, Pilegaard K, Šigut L, Klemedtsson L, Tezza L, Hörtnagl L, Urbaniak M, Roland M, Schmidt M, Sutton MA, Hehn M, Saunders M, Mauder M, Aurela M, Korkiakoski M, Du M, Vendrame N, Kowalska N, Leahy PG, Alekseychik P, Shi P, Weslien P, Chen S, Fares S, Friborg T, Tallec T, Kato T, Sachs T, Maximov T, di Cella UM, Moderow U, Li Y, He Y, Kosugi Y, Luo G. Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing. Sci Data 2023; 10:587. [PMID: 37679357 PMCID: PMC10485062 DOI: 10.1038/s41597-023-02473-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 08/14/2023] [Indexed: 09/09/2023] Open
Abstract
Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002-2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983-2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.
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Affiliation(s)
- Mingjuan Xie
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
- Department of Geography, Ghent University, Ghent, 9000, Belgium
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
- Sino-Belgian Joint Laboratory for Geo-Information, Urumqi, China
- Sino-Belgian Joint Laboratory for Geo-Information, Ghent, Belgium
| | - Xiaofei Ma
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
| | - Yuangang Wang
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Chaofan Li
- School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Haiyang Shi
- School of Earth Sciences and Engineering, Hohai University, Nanjing, 211100, China
| | - Xiuliang Yuan
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
| | - Olaf Hellwich
- Department of Computer Vision & Remote Sensing, Technische Universität Berlin, 10587, Berlin, Germany
| | - Chunbo Chen
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
| | - Wenqiang Zhang
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
- Department of Geography, Ghent University, Ghent, 9000, Belgium
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
- Sino-Belgian Joint Laboratory for Geo-Information, Urumqi, China
- Sino-Belgian Joint Laboratory for Geo-Information, Ghent, Belgium
| | - Chen Zhang
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Qing Ling
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Ruixiang Gao
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yu Zhang
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
- Department of Geography, Ghent University, Ghent, 9000, Belgium
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
- Sino-Belgian Joint Laboratory for Geo-Information, Urumqi, China
- Sino-Belgian Joint Laboratory for Geo-Information, Ghent, Belgium
| | - Friday Uchenna Ochege
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
- Department of Geography and Environmental Management, University of Port Harcourt, PMB 5323 Choba, East-West, Port Harcourt, Nigeria
| | - Amaury Frankl
- Department of Geography, Ghent University, Ghent, 9000, Belgium
| | - Philippe De Maeyer
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
- Department of Geography, Ghent University, Ghent, 9000, Belgium
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
- Sino-Belgian Joint Laboratory for Geo-Information, Urumqi, China
- Sino-Belgian Joint Laboratory for Geo-Information, Ghent, Belgium
| | - Nina Buchmann
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092, Zürich, Switzerland
| | - Iris Feigenwinter
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092, Zürich, Switzerland
| | - Jørgen E Olesen
- Department of Agroecology, Aarhus University, Tjele, Denmark
| | - Radoslaw Juszczak
- Laboratory of Bioclimatology, Department of Ecology and Environmental Protection, Faculty of Environmental and Mechanical Engineering, Poznan University of Life Sciences, Piatkowska 94, 60-649, Poznan, Poland
| | - Adrien Jacotot
- Sol, Agro et hydrosystèmes, Spatialisation (SAS), UMR 1069, INRAE, Institut Agro, 35000, Rennes, France
| | - Aino Korrensalo
- Department of Environmental and Biological Sciences, University of Eastern Finland, Joensuu campus, P.O Box 111, Joensuu, FI-80101, Finland
- Natural Resources Institute Finland, Joensuu, Yliopistokatu 6, FI-80130, Joensuu, Finland
| | - Andrea Pitacco
- University of Padova - DAFNAE, Viale dell'Università 16, I-35020, Padova, Legnaro (PD), Italy
| | - Andrej Varlagin
- A.N Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, 119071, Leninsky pr.33, Moscow, Russia
| | - Ankit Shekhar
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092, Zürich, Switzerland
| | - Annalea Lohila
- Climate System Research, Finnish Meteorological Institute, P.O Box 503, FI-00101, Helsinki, Finland
- University of Helsinki, Institute for Atmospheric and Earth System Research (INAR)/Physics, Faculty of Science, Helsinki, Finland
| | - Arnaud Carrara
- Fundación CEAM, Parque Tecnológico, C/Charles R. Darwin, 14, Paterna, 46980, Spain
| | - Aurore Brut
- CESBIO, Université de Toulouse, CNES/CNRS/INRAE/IRD/UPS, Toulouse, France
| | - Bart Kruijt
- Wageningen Univertsity, Water Systems and Global change group, PO bx 47, 7700AA, Wageningen, Netherlands
| | - Benjamin Loubet
- ECOSYS, INRAE, AgroParisTech, Université Paris-Saclay, 22 place de l'agronomie, 91120, Palaiseau, France
| | - Bernard Heinesch
- Terra Teaching and Research Center, University of Liège - Gembloux Agro-Bio Tech, 5030, Gembloux, Belgium
| | - Bogdan Chojnicki
- Laboratory of Bioclimatology, Department of Ecology and Environmental Protection, Faculty of Environmental and Mechanical Engineering, Poznan University of Life Sciences, Piatkowska 94, 60-649, Poznan, Poland
| | - Carole Helfter
- UK Centre for Ecology & Hydrology (UKCEH), Bush Estate, Penicuik, EH26 0QB, UK
| | - Caroline Vincke
- Earth and Life Institute, Université Catholique de Louvain, 1348, Louvain-la-Neuve, Belgium
| | - Changliang Shao
- National Hulunber Grassland Ecosystem Observation and Research Station & Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Christian Bernhofer
- Institute of Hydrology and Meteorology, TUD Dresden University of Technology, Pienner Str. 23, 01737, Tharandt, Germany
| | - Christian Brümmer
- Thünen Institute of Climate-Smart Agriculture, 38116, Braunschweig, Germany
| | - Christian Wille
- GFZ German Research Centre for Geosciences, Telegrafenberg, 14473, Potsdam, Germany
| | - Eeva-Stiina Tuittila
- School of Forest Sciences, University of Eastern Finland, P.O Box 111, FIN-80100, Joensuu, Finland
| | - Eiko Nemitz
- UK Centre for Ecology & Hydrology (UKCEH), Bush Estate, Penicuik, EH26 0QB, UK
| | - Franco Meggio
- University of Padova - DAFNAE, Viale dell'Università 16, I-35020, Padova, Legnaro (PD), Italy
| | - Gang Dong
- School of Life Science, Shanxi University, Taiyuan, 030006, China
| | | | - Georg Niedrist
- Eurac research, Institute for Alpine Environment, Viale Druso 1, 39100, Bolzano, Italy
| | - Georg Wohlfahrt
- Institut für Ökologie, Universität Innsbruck, Innrain 52, 6020, Innsbruck, Austria
| | - Guoyi Zhou
- Institute of Ecology and School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Ignacio Goded
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Thomas Gruenwald
- Institute of Hydrology and Meteorology, TUD Dresden University of Technology, Pienner Str. 23, 01737, Tharandt, Germany
| | - Janusz Olejnik
- Laboratory of Meteorology, Department of Construction and Geoengineering, Faculty of Environmental and Mechanical Engineering, Poznan University of Life Sciences, Piatkowska 94, 60-649, Poznan, Poland
| | - Joachim Jansen
- Department of Ecology and Genetics/Limnology, Uppsala University, Norbyvägen 18 D, 752 36, Uppsala, Sweden
| | - Johan Neirynck
- Research Institute for Nature and Forest, Geraardsbergen, 9500, Belgium
| | - Juha-Pekka Tuovinen
- Climate System Research, Finnish Meteorological Institute, P.O Box 503, FI-00101, Helsinki, Finland
| | - Junhui Zhang
- School of life sciences, Qufu Normal University, 57 Jingxuan West Road, Qufu, 273165, Shandong, China
| | - Katja Klumpp
- Grassland Ecosystem Research, INRAE, VetAgro-Sup, University of Clermont Auvergne, 5 Chemin de Beaulieu, 63000, Clermont Ferrand, France
| | - Kim Pilegaard
- Department of Environmental Engineering, Technical University of Denmark (DTU), Kgs, Lyngby, 2800, Denmark
| | - Ladislav Šigut
- Department of Matter and Energy Fluxes, Global Change Research Institute CAS, Bělidla 986/4a, CZ-603 00, Brno, Czech Republic
| | - Leif Klemedtsson
- Departement of Earth Sciences, Gothenburg University, Guldhedsgatan 5A, Po.Box 460, SE 405 30, Gothenburg, Sweden
| | - Luca Tezza
- University of Padova - DAFNAE, Viale dell'Università 16, I-35020, Padova, Legnaro (PD), Italy
| | - Lukas Hörtnagl
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092, Zürich, Switzerland
| | - Marek Urbaniak
- Laboratory of Meteorology, Department of Construction and Geoengineering, Faculty of Environmental and Mechanical Engineering, Poznan University of Life Sciences, Piatkowska 94, 60-649, Poznan, Poland
| | - Marilyn Roland
- Department of Biology, University of Antwerp, Wilrijk, 2610, Belgium
| | - Marius Schmidt
- Agrosphere Institute IBG-3, Forschungszentrum Jülich, Jülich, 52425, Germany
| | - Mark A Sutton
- UK Centre for Ecology & Hydrology (UKCEH), Bush Estate, Penicuik, EH26 0QB, UK
| | - Markus Hehn
- Institute of Hydrology and Meteorology, TUD Dresden University of Technology, Pienner Str. 23, 01737, Tharandt, Germany
| | - Matthew Saunders
- School of Natural Sciences, Botany Discipline, Trinity College Dublin, D2, Dublin, Ireland
| | - Matthias Mauder
- Institute of Hydrology and Meteorology, TUD Dresden University of Technology, Pienner Str. 23, 01737, Tharandt, Germany
| | - Mika Aurela
- Climate System Research, Finnish Meteorological Institute, P.O Box 503, FI-00101, Helsinki, Finland
| | - Mika Korkiakoski
- Climate System Research, Finnish Meteorological Institute, P.O Box 503, FI-00101, Helsinki, Finland
| | - Mingyuan Du
- National Agriculture and Food Research Organization, Tsukuba, Ibaraki, 305-8517, Japan
| | - Nadia Vendrame
- Center Agriculture Food Environment, University of Trento, Via Edmund Mach 1, I-38010, Trento, San Michele all'Adige (TN), Italy
| | - Natalia Kowalska
- Department of Matter and Energy Fluxes, Global Change Research Institute CAS, Bělidla 986/4a, CZ-603 00, Brno, Czech Republic
| | - Paul G Leahy
- School of Engineering & Architecture, University College Cork, College Road, Cork, T12 K8AF, Republic of Ireland
| | - Pavel Alekseychik
- Natural Resources Institute Finland, Bioeconomy and environment, 00790, Helsinki, Finland
| | - Peili Shi
- Lhasa Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Per Weslien
- Departement of Earth Sciences, Gothenburg University, Guldhedsgatan 5A, Po.Box 460, SE 405 30, Gothenburg, Sweden
| | - Shiping Chen
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Silvano Fares
- National Research Council of Italy, Institute for Agriculture and Forestry Systems in the Mediterranean, Portici, Naples, Italy
| | - Thomas Friborg
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Oester Voldgade 10, 1350, Copenhagen K, Denmark
| | - Tiphaine Tallec
- CESBIO, Université de Toulouse, CNES/CNRS/INRAE/IRD/UPS, Toulouse, France
| | - Tomomichi Kato
- Research Faculty of Agriculture, Hokkaido University, Sapporo, Hokkaido, 060-8589, Japan
| | - Torsten Sachs
- GFZ German Research Centre for Geosciences, Telegrafenberg, 14473, Potsdam, Germany
| | - Trofim Maximov
- Institute for Biological Problems of Cryolithozone, Siberian Branch of the Russian Academy of Sciences, Yakutsk, Russia
| | - Umberto Morra di Cella
- Climate Change Dept., Environmental Protection Agency of Aosta Valley, Saint-Christophe, I-11020, Italy
| | - Uta Moderow
- Institute of Hydrology and Meteorology, TUD Dresden University of Technology, Pienner Str. 23, 01737, Tharandt, Germany
| | - Yingnian Li
- Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Qinghai, Xining, 810008, China
| | - Yongtao He
- Lhasa Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yoshiko Kosugi
- Laboratory of Forest Hydrology, Graduate School of Agriculture, Kyoto University, 606-8502, Kyoto, Japan
| | - Geping Luo
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China.
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China.
- Sino-Belgian Joint Laboratory for Geo-Information, Urumqi, China.
- The National Key Laboratory of Ecological Security and Sustainable Development in Arid Region (proposed), Chinese Academy of Sciences, Urumqi, China.
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8
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Cai HZ, Zhuge LD, Huang ZH, Shi P, Wang SX, Zhao BH, An CM, Niu LJ, Li ZJ. [Risk factors of occult lymph node metastasis of levels Ⅲ and Ⅳ in papillary thyroid carcinoma]. Zhonghua Zhong Liu Za Zhi 2023; 45:692-696. [PMID: 37580275 DOI: 10.3760/cma.j.cn112152-20221202-00804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/16/2023]
Abstract
Objective: To investigate the potential risk factors for occult lateral cervical lymph node metastasis (LNM) to levels Ⅲ and Ⅳ in patients with papillary thyroid carcinoma (PTC) and the necessity of super-selective lateral lymph node dissection for patients harboring these metastases. Methods: This prospective study included PTC patients who were operated by the same surgeon in the Department of Head and Neck Surgery of Cancer Hospital, Chinese Academy of Medical Sciences from October 2015 through October 2019. Preoperative ultrasound and enhanced Computer Tomography (CT) did not denote suspected enlarged lymph nodes in the lateral neck. All patients underwent lymph node dissection in levels Ⅲ and Ⅳ on the basis of original thyroid collar incision after LNM to level Ⅵ was confirmed by preoperative fine needlebiopsy or intraoperative frozen pathology. Results: Of all 143 patients, 74 (51.7%) had occult LNM in levels Ⅲ and Ⅳ confirmed by postoperative pathology. The average number of metastasized lymph nodes in levels Ⅲ and Ⅳ was 2.64±1.80, and that in level Ⅵ was 3.77±3.27. There was a significant linear positive correlation between the number of metastasized lymph nodes in level Ⅵ and that in levels Ⅲ and Ⅳ (r=0.341, P<0.001). That the metastasized lymph nodes in level Ⅵ equals three was the best predictor of occult lateral LNM to levels Ⅲ and Ⅳ. Univariate analysis showed that age <55 years, tumor size ≥2.0 cm, number of metastasized lymph nodes in level Ⅵ ≥3, and percentage of metastasized lymph nodes in the total number of dissected lymph nodes in level Ⅵ >50% were associated with occult LNM in levels Ⅲ and Ⅳ (P<0.05). Multivariate analysis showed that number of metastasized lymph nodes in level Ⅵ≥3 was an independent risk factor for occult LNM in levels Ⅲ and Ⅳ (P=0.006). Conclusions: Age, tumor size and LNM in level Ⅵ were associated with occult lateral LNM in PTC patients. Lymph node dissection in levels Ⅲ and Ⅳ could be considered for selective patients, since it will help to avoid secondary operation for residual tumor or recurrence resulted from insufficient treatment without increasing the incidence of complications or affecting patients' appearances.
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Affiliation(s)
- H Z Cai
- Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - L D Zhuge
- Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Z H Huang
- Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - P Shi
- Department of Ear-Nose-Throat, Hebei Medical University Forth Hospital, Shijiazhuang 050011, China
| | - S X Wang
- Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - B H Zhao
- Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Shenzhen Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - C M An
- Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - L J Niu
- Department of Ultrasound, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Z J Li
- Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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9
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Zheng XX, Shi P, Feng HL, Lyu R, Xu CJ, Chen ZW. [Current status and research advances on catheter-associated urinary tract infection in burn patients]. Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi 2023; 39:581-585. [PMID: 37805775 DOI: 10.3760/cma.j.cn501225-20220904-00378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 10/09/2023]
Abstract
Catheter-associated urinary tract infection (CAUTI) is one of the common nosocomial infections in burn patients. It not only extends the length of hospital stay of patients, increases the economic burden on family and society, but also seriously affects the prognosis and quality of life of patients, increases the risk of death of patients. In this paper, the epidemiological characteristics, influencing factors, and prevention measures of CAUTI in burn patients are reviewed to draw high attention of clinical medical staff and to provide some reference for clinical practice.
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Affiliation(s)
- X X Zheng
- School of Nursing, Huzhou University, Huzhou 313000, China
| | - P Shi
- School of Nursing, Huzhou University, Huzhou 313000, China
| | - H L Feng
- School of Nursing, Huzhou University, Huzhou 313000, China
| | - R Lyu
- School of Nursing, Huzhou University, Huzhou 313000, China
| | - C J Xu
- Nursing Department, the Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Z W Chen
- Department of Neurosurgery, the Fourth Affiliated Hospital of Zhejiang University School of Medicine, Yiwu 322000, China
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10
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Xue W, Ying D, Li Y, Sheng Y, He T, Shi P, Liu M, Zhao L. Method for establishing soil contaminant discharge inventory: An arsenic-contaminated site case study. Environ Res 2023; 227:115700. [PMID: 36931375 DOI: 10.1016/j.envres.2023.115700] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 03/06/2023] [Accepted: 03/14/2023] [Indexed: 05/08/2023]
Abstract
The existing method to survey site pollution is generally based on soil-groundwater sampling and instrumental analysis, which enables us to access the detailed soil pollution status while lacking quantitative association with industrial activities. It is urgent to understand contaminant discharge modes and establish a discharge inventory for achieving process-targeted pollution control. This study took a 40-year phosphate fertilizer-sulfuric acid site as an example and constructed a contaminant tracing method based on on-site investigations and detailed industrial data. These investigations and data were combined to determine the characteristic pollutant of this site, arsenic. And the calculation process of four-pathway pollution modes (atmospheric deposition, wastewater, solid waste leaching, and storage dripping) is derived from the existing acceptance criteria and risk assessment guidelines. They are set to calculate the arsenic's factory-to-soil discharge flux. The absent process contaminant release information and parameters, such as discharge coefficient, were obtained from soil-groundwater pollution control standards and discharge handbooks. It was found that the high concentration of arsenic (around 1930 mg g-1) was preponderantly caused by sulfur-iron slag and tailing leaching (96.19%), while the other pathways accounted for only 0.13% (atmospheric deposition), 3.59% (wastewater) and 0.09% (storage tank). Results were verified by the measured arsenic concentration, and the difference was +16.29%, which was acceptable. Finally, a contaminant discharge inventory was established with high-resolution spatial distribution and time-scale (historical discharge) evolution. The innovation of this study lies in the preliminary construction of a method for formulating soil discharge inventory. This study would contribute to the refined management of site pollution and reduction of source contaminants discharge. In addition, it will help infer the pollution condition of sites that are difficult to sample so as to help the government achieve precise source control.
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Affiliation(s)
- Weizhen Xue
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Diwen Ying
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Ye Li
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
| | - Yi Sheng
- College of Chemical Engineering, Zhejiang University of Technology, Zhejiang, 310014, China
| | - Tianhao He
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
| | - Peili Shi
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, China
| | - Min Liu
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
| | - Ling Zhao
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
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11
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Duan C, Yu C, Shi P, Huangqing D, Zhang X, Dai E. Assessing trade-offs among productive, economic, and environmental indicators of forage systems in southern Tibetan crop-livestock integration. Sci Total Environ 2023; 876:162641. [PMID: 36921851 DOI: 10.1016/j.scitotenv.2023.162641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 02/28/2023] [Accepted: 03/01/2023] [Indexed: 06/18/2023]
Abstract
Fostering crop-livestock integration via crop-forage rotation provides opportunities to cope with land degradation, feed deficit, and agropastoral sustainability. Farmers' preferences for forage options are influenced by economic benefit, environmental preference, and productive performance. However, there is little information available on evaluating multiple trade-offs of forage systems for the design of crop-forage rotations. Here, we performed a comprehensive evaluation to compare the economic, environmental, and productive indicators of five typical forage systems in terms of habitat conditions, soil ecosystem services, economic profit, and forage yield and nutritive value on the southern Tibetan Plateau. Alfalfa pasture and silage corn were mostly cultivated in lower altitudes, with more abundant precipitation, and higher growing degree days. Soil carbon and nitrogen accumulation were significantly higher in perennial alfalfa than in the other forage systems. The relative feed value of alfalfa pasture was also evidently greater than the other forage systems, whereas the yield of silage corn was among the highest. Alfalfa pasture presented superior economic benefits compared to the others. But the alfalfa pasture over six years showed a significant decrease in soil carbon and nitrogen storage, net present value, and yield. Forage systems generally have more soil carbon accumulation, but only forage legumes are more likely to positively affect soil nitrogen retention compared to cereal croplands. The trade-offs among economic, environmental, and productive indicators demonstrated that annual forage systems (silage corn, forage oat, and ryegrass) met productive target rather than environmental and economic objectives, while perennial alfalfa showed synergies among the three goals. These findings indicate that integrating crop-forage rotation, particularly introducing legume forages into farming systems is an adaptive option for crop-livestock integration on the southern Tibetan Plateau. Given the large topographic variation, suitable crop-forage systems should be designed for the heterogeneous Yarlung Zangbo River valleys. Among them, alfalfa-silage corn intercropping is recommended as a promising system to meet both productivity and profitability.
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Affiliation(s)
- Cheng Duan
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100190, China
| | - Chengqun Yu
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100190, China.
| | - Dongzhi Huangqing
- Xining Comprehensive Center of Natural Resources, China Geological Survey, Xining 810000, China
| | - Xianzhou Zhang
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100190, China
| | - Erfu Dai
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100190, China
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12
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Zhang YH, Li F, Zhou YY, Shi P, Cao LF, Wang JS, Shen J. [Characteristics of plasma Epstein-Barr virus DNA in children with primary infection]. Zhonghua Er Ke Za Zhi 2023; 61:245-249. [PMID: 36849352 DOI: 10.3760/cma.j.cn112140-20220825-00752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
Abstract
Objective: To explore the characteristics of plasma Epstein-Barr virus (EBV) DNA in primary infection in pediatric cases. Methods: The laboratory and clinical data of 571 children diagnosed with EBV primary infection in Children's Hospital of Fudan University during September 1st, 2017 to September 30th, 2018 were retrospectively analyzed. According to the results of plasma EBV DNA, they were divided into positive group and negative group. According to the EBV DNA, they were devided into high plasma virol load group and low plasma virol load group. The Chi-square test, Wilcoxon rank sum test were used to compare the differences between groups. Results: Among the 571 children with EBV primary infection, 334 were males and 237 were females. The age of first diagnosis was 3.8 (2.2, 5.7) years. There were 255 cases in positive group and 316 cases in negative group. The percentage of cases with fever,hepatomegaly and (or) splenomegaly, elevated transaminase in the positive group were higher than those in the negative group (235 cases (92.2%) vs. 255 cases (80.7%), χ2=15.22, P<0.001; 169 cases (66.3%) vs. 85 cases (26.9%), χ2=96.80, P<0.001; and 144 cases (56.5%) vs. 120 cases (38.0%), χ2=18.27, P<0.001; respectively).In the positive group, 70 cases were followed up for 46 (27, 106) days, 68 cases (97.1%) turned negative within 28 days, with the exception of 2 cases (2.9%) developed chronic active EBV infection by follow-up revision.There were 218 cases in high plasma viral DNA copies group and 37 cases in low copies group. More cases presented with elevated transaminases in the high plasma viral DNA copies group than those in the low group (75.7% (28/37) vs. 56.0%(116/207), χ2=5.00, P=0.025).Both the positive rate of EBV DNA in peripheral blood leukocytes (84.2% (266/316) vs. 44.7% (255/571), χ2=76.26, P<0.001) and the copies of EBV DNA (7.0×107 (1.3×107, 3.0×108) vs. 3.1×106 (1.6×106, 6.1×106) copies /L, Z=15.23, P<0.001) were higher than that of plasma. Conclusions: In immunocompetent pediatric cases diagnosed as EBV primary infection, cases with positive plasma EBV DNA were prone to have fever, hepatomegaly and (or) splenomegaly, and elevated transaminase than those with negative plasma viral DNA. The plasma EBV DNA usually turns negative within 28 days after initial diagnosis.Most cases with high viral load in plasma showed elevated aminotransferase.
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Affiliation(s)
- Y H Zhang
- Department of Infectious Disease, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - F Li
- Department of Infectious Disease, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - Y Y Zhou
- Department of Infectious Disease, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - P Shi
- Clinical Research Unit, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - L F Cao
- Department of Virology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - J S Wang
- Department of Infectious Disease, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
| | - J Shen
- Department of Infectious Disease, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China
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13
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Zhu DQ, Shi P, Shen J, Chen YW, Li F. [Clinical characteristics of anomalous aortic origin of a coronary artery in children]. Zhonghua Er Ke Za Zhi 2023; 61:240-244. [PMID: 36849351 DOI: 10.3760/cma.j.cn112140-20221031-00925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
Abstract
Objective: To analyze the clinical characteristics, diagnosis and treatment of anomalous aortic origin of a coronary artery (AAOCA) in children. Methods: There were 17 children diagnosed with AAOCA from January 2013 to January 2022 in Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine.Their clinical manifestations, laboratory and imaging data, treatment and prognosis were retrospectively analyzed. Results: These 17 children included 14 males and 3 females, with the age of (8.7±3.5) years. There were 4 anomalous left coronary artery (ALCA) and 13 anomalous right coronary artery (ARCA). Seven children presented with chest pain or chest pain after exercise, three patients presented with cardiac syncope, one complained chest tightness and weakness, and the other six patients had no specific symptoms. Cardiac syncope and chest tightness occurred in patients with ALCA. Fourteen children had the dangerous anatomical basis of myocardial ischemia caused by coronary artery compression or stenosis on imaging. Seven children had coronary artery repair, of whom two were ALCA and five were ARCA. One patient had received heart transplantation because of heart failure. The incidence of adverse cardiovascular events and poor prognosis in ALCA group was higher than that in ARCA group (4/4 vs. 0/13, P<0.05). They were followed up in the outpatient department regularly for 6 (6, 12) months; except for the one who lost visit, the rest of the patients had a good prognosis. Conclusions: Cardiogenic syncope or cardiac insufficiency usually occurs in ALCA, and adverse cardiovascular events and poor prognosis are more common in ALCA than in ARCA. Early surgical treatment should be considered for children with ALCA and ARCA accompanied by myocardial ischemia.
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Affiliation(s)
- D Q Zhu
- Department of Pediatric Cardiology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - P Shi
- Department of Pediatric Cardiology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - J Shen
- Department of Pediatric Cardiology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Y W Chen
- Department of Pediatric Cardiology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - F Li
- Department of Pediatric Cardiology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
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14
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Zong N, Hou G, Shi P, Song M. Winter warming alleviates the severely negative effects of nitrogen addition on ecosystem stability in a Tibetan alpine grassland. Sci Total Environ 2023; 855:158923. [PMID: 36165909 DOI: 10.1016/j.scitotenv.2022.158923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 09/02/2022] [Accepted: 09/18/2022] [Indexed: 06/16/2023]
Abstract
Many recent studies have explored how global warming and increased nitrogen (N) deposition affect the structure and function of natural ecosystems. However, how ecosystems respond to the combination of warming and N enrichment remains unexplored, especially under asymmetric seasonal warming scenarios. We conducted a decade-long field experiment in an alpine grassland to investigate the effects of warming (ambient condition (NW), winter-only (WW), and year-round (YW) warming) and N addition on the temporal stability of communities. Although N addition significantly reduced community temporal stability in NW, WW, and YW, WW relieved the severely negative effects of N addition compared to NW and YW (from 47.7 % in NW and 76.1 % in YW to 18.6 % in WW under 80 kg N hm-2 year-1). The most remarkable finding is that the main factors driving community stability shifted with warming patterns. The increase in community dominance under NW was a significant driver of the decreased temporal stability in the community. However, the decrease in community stability caused by N addition was ascribed to the decreased stability of both dominant and common species under WW. In contrast, N addition decreased community temporal stability mainly via a decrease in species asynchrony under YW. Our results suggested that warming patterns can modulate the effects of N enhancement on community stability. To predict the effects of climate change on alpine grasslands accurately, the idiosyncratic effects of asymmetric seasonal warming under future climate change scenarios should be considered.
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Affiliation(s)
- Ning Zong
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Ge Hou
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Minghua Song
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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Lu YW, Shi P, Sun JY, Zhang ZY. Changes in physical activity behavior in children and adolescents: a systematic review and meta-analysis based on a trans-theoretical model. Eur Rev Med Pharmacol Sci 2022; 26:8860-8872. [PMID: 36524505 DOI: 10.26355/eurrev_202212_30558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
OBJECTIVE This article presents a systematic review and meta-analysis of cross-sectional studies of physical activity (PA) behavioral changes in children and adolescents based on the trans-theoretical model (TTM). The main purpose is to test the rationality of TTM and the secondary purpose is to analyze whether PA can effectively identify the stages of change. MATERIALS AND METHODS The databases CNKI, Wan-Fang, VIP, WOS, PubMed, and EBSCO were searched by computer. Two researchers independently reviewed the literature, extracted data, and evaluated the quality of the literature. Stata 23.0 software was used for statistical analysis. RESULTS A total of 17 articles of medium and high quality were included in the meta-analysis. First, the behavior changes of PA of children and adolescents are related to the process of change (POC), self-efficacy (SEI), and decisional balance (DBL). The POC, SEI, and DBL have obvious stage characteristics. Second, with increasing intensity of PA, the degree of discrimination of stage of change (SOC) also improved, but PA could not still fully distinguish each stage. CONCLUSIONS It is suggested that follow-up studies should compare the stages of change of different criteria by comprehensive behavioral data, exercise willingness, and exercise habits. Furthermore, it is recommended that more studies use longitudinal surveys or experimental interventions to test the rationality of TTM. It is suggested that the follow-up study design more standardized measurement tools to explore the change in PA behavior of children and adolescents.
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Affiliation(s)
- Y-W Lu
- Medical College of Jiaying University, Meizhou, China.
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16
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Shi P, Cheng YP, Li ZY, Wang SP, Shi YZ, Ji YM, Fang L, Zhao JJ, Gao L, Xu C. [Identification and functional analysis of combined oxidative phosphorylation deficiency 28 gene mutation]. Zhonghua Nei Ke Za Zhi 2022; 61:1324-1329. [PMID: 36456512 DOI: 10.3760/cma.j.cn112138-20211208-00875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Objective: To report a case of combined oxidative phosphorylation deficiency 28 (COXPD28) in China, identified the pathogenic mutation and explored the pathogenic mechanism preliminarily. Methods: The clinical characteristics of a patient with COXPD28 were retrospectively analyzed and the pathogenic mutations were identified by mitochondrial gene sequencing and whole exome sequencing. The wild-type and mutant plasmids of pathogenic genes were constructed, and effect of mutation on protein expression by quantitative real-time PCR (qPCR) and Western blot were evaluated. Statistical methods mainly used one-way ANOVA and LSD test. Results: A 21 year old female patient presented with lactic acid poisoning due to repeated chest distress and wheezing since childhood. The sequencing of the whole exon group gene found that solute carrier family 25 member 26 (SLC25A26) gene had a compound heterozygous mutation (c.34G>C, p.A12P; c.197C>A, p.A66E), which was the first report in China. In vitro function test showed that the expression levels of SLC25A26 mRNA and S-adenosylmethionine carrier (SAMC) protein in cells transfected with SLC25A26 mutant plasmid were significantly lower than those transfected with wild type plasmid. The p.A66E mutant plasmid reduced the expression level of SLC25A26 mRNA and SAMC protein to 6% and 26% of wild type plasmids respectively (both P<0.001), while p.A12P mutant plasmid decreased to 62% and 82% of wild type plasmids respectively (P<0.001, P=0.044). When the double mutant (p.A66E+p.A12P) plasmids were co-transfected, the expression levels of SLC25A26 mRNA and SAMC protein decreased to 47% and 57% of the wild type plasmids, respectively (P<0.001, P=0.001). Conclusion: The pathogenic mutation gene of this patient with COXPD28 is SLC25A26 gene mutation (p.A66E, p.A12P), which causes the decrease of SLC25A26 expression level, mitochondrial oxidative phosphorylation dysfunction, and induces COXPD28.
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Affiliation(s)
- P Shi
- Shandong University, Jinan 250021, China Department of Endocrinology, Shandong Provincial Hospital, Shandong Key Laboratory of Endocrinology and Lipid Metabolism, Jinan 250021, China
| | - Y P Cheng
- Shandong University, Jinan 250021, China Department of Endocrinology, Shandong Provincial Hospital, Shandong Key Laboratory of Endocrinology and Lipid Metabolism, Jinan 250021, China
| | - Z Y Li
- Department of Endocrinology, Shandong Provincial Hospital, Shandong Key Laboratory of Endocrinology and Lipid Metabolism, Jinan 250021, China
| | - S P Wang
- Department of Endocrinology, the People's Hospital of Dongying City, Dongying 257091, China
| | - Y Z Shi
- Shandong University, Jinan 250021, China Department of Endocrinology, Shandong Provincial Hospital, Shandong Key Laboratory of Endocrinology and Lipid Metabolism, Jinan 250021, China
| | - Y M Ji
- Department of Endocrinology, Shandong Provincial Hospital, Shandong Key Laboratory of Endocrinology and Lipid Metabolism, Jinan 250021, China
| | - L Fang
- Department of Endocrinology, Shandong Provincial Hospital, Shandong Key Laboratory of Endocrinology and Lipid Metabolism, Jinan 250021, China
| | - J J Zhao
- Department of Endocrinology, Shandong Provincial Hospital, Shandong Key Laboratory of Endocrinology and Lipid Metabolism, Jinan 250021, China
| | - L Gao
- Department of Endocrinology, Shandong Provincial Hospital, Shandong Key Laboratory of Endocrinology and Lipid Metabolism, Jinan 250021, China
| | - C Xu
- Shandong University, Jinan 250021, China Department of Endocrinology, Shandong Provincial Hospital, Shandong Key Laboratory of Endocrinology and Lipid Metabolism, Jinan 250021, China
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17
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Rhodes TL, Michael CA, Shi P, Scannell R, Storment S, Pratt Q, Lantsov R, Fitzgerald I, Hall-Chen VH, Crocker NA, Peebles WA. Design elements and first data from a new Doppler backscattering system on the MAST-U spherical tokamak. Rev Sci Instrum 2022; 93:113549. [PMID: 36461471 DOI: 10.1063/5.0101848] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 09/25/2022] [Indexed: 06/17/2023]
Abstract
A new Doppler backscattering (DBS) system has been installed and tested on the MAST-U spherical tokamak. It utilizes eight simultaneous fixed frequency probe beams (32.5, 35, 37.5, 40, 42.5, 45, 47.5, and 50 GHz). These frequencies provide a range of radial positions from the edge plasma to the core depending on plasma conditions. The system utilizes a combination of novel features to provide remote control of the probed density wavenumber, the launched polarization (X vs O-mode), and the angle of the launched DBS to match the magnetic field pitch angle. The range of accessible density turbulence wavenumbers (kθ) is reasonably large with normalized wavenumbers kθρs ranging from ≤0.5 to 9 (ion sound gyroradius ρs = 1 cm). This wavenumber range is relevant to a variety of instabilities believed to be important in establishing plasma transport (e.g., ion temperature gradient, trapped electron, electron temperature gradient, micro-tearing, kinetic ballooning modes). The system is specifically designed to address the requirement of density fluctuation wavevector alignment which can significantly reduce the SNR if not accounted for.
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Affiliation(s)
- T L Rhodes
- Physics and Astronomy Department, University of California, Los Angeles, California 90098, USA
| | - C A Michael
- Physics and Astronomy Department, University of California, Los Angeles, California 90098, USA
| | - P Shi
- UKAEA/CCFE, Culham Science Centre, Abingdon, Oxfordshire, OX14 3DB, UK
| | - R Scannell
- UKAEA/CCFE, Culham Science Centre, Abingdon, Oxfordshire, OX14 3DB, UK
| | - S Storment
- Physics and Astronomy Department, University of California, Los Angeles, California 90098, USA
| | - Q Pratt
- Physics and Astronomy Department, University of California, Los Angeles, California 90098, USA
| | - R Lantsov
- Physics and Astronomy Department, University of California, Los Angeles, California 90098, USA
| | - I Fitzgerald
- UKAEA/CCFE, Culham Science Centre, Abingdon, Oxfordshire, OX14 3DB, UK
| | - V H Hall-Chen
- Institute of High Performance Computing, Singapore 138632, Singapore
| | - N A Crocker
- Physics and Astronomy Department, University of California, Los Angeles, California 90098, USA
| | - W A Peebles
- Physics and Astronomy Department, University of California, Los Angeles, California 90098, USA
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18
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Li J, Liu S, Zhang Y, Dong J, Kong W, Shi P. Impact of impurities on drift wave instabilities in reversed-field pinch plasmas. Phys Rev E 2022; 106:045203. [PMID: 36397586 DOI: 10.1103/physreve.106.045203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 09/22/2022] [Indexed: 06/16/2023]
Abstract
The drift wave in the presence of impurity ions was investigated numerically in reversed-field pinch plasmas, using the gyrokinetic integral eigenmode equation. By comparing the results of regular and hollow plasma density profiles, it was found that the ion temperature gradient mode for the hollow density profile case is much harder to excite. For the impurity effects, when the impurity density gradient is opposite to the electrons, namely when L_{ez} (L_{ez}=L_{ne}/L_{nz} with 1/L_{n} being the density gradient scale length, and the subscript "e" and "z" indicates electrons and impurity ions, respectively) is negative, the impurities can enhance the instability. On the contrary, when L_{ez} is positive, the instability is stabilized. Regarding the trapped electron mode (TEM), the growth rate for plasmas with a hollow density profile remains smaller than that of the standard density gradient. There exists a threshold in L_{ez}. When L_{ez} is less than this value, the impurities destabilize the TEMs, while when L_{ez} is greater than this value, the impurities stabilize the TEMs. In addition, the influence of the collisionality on the TEMs was also studied.
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Affiliation(s)
- Jingchun Li
- Department of Earth and Space Sciences, Southern University of Science and Technology, 518055 Shenzhen, Guangdong, People's Republic of China
| | - Songfen Liu
- School of Physics, Nankai University, Tianjin 300071, People's Republic of China
| | - Yilong Zhang
- School of Physics, Nankai University, Tianjin 300071, People's Republic of China
| | - Jiaqi Dong
- ENN Science and Technology Development Co., Ltd., Langfang 065001, China
| | - Wei Kong
- College of Science, Civial Aviation University of China, Tianjin 300300, People's Republic of China
| | - P Shi
- United Kingdom Atomic Energy Authority, Culham Centre for Fusion Energy, Culham Science Centre, Abingdon, Oxon OX14 3DB, United Kingdom
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19
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Hou G, Zhou T, Sun J, Zong N, Shi P, Yu J, Song M, Zhu J, Zhang Y. Functional identity of leaf dry matter content regulates community stability in the northern Tibetan grasslands. Sci Total Environ 2022; 838:156150. [PMID: 35613643 DOI: 10.1016/j.scitotenv.2022.156150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 05/06/2022] [Accepted: 05/18/2022] [Indexed: 06/15/2023]
Abstract
Biodiversity-stability mechanisms have been the focus of many long-term community stability studies. Community functional composition (i.e., functional diversity and functional identity of community plant functional traits) is critical for community stability; however, this topic has received less attention in large-scale studies. Here, we combined a field survey of biodiversity and plant functional traits in 22 alpine grassland sites throughout the northern Tibetan Plateau with 20 years of satellite-sensed proxy data (enhanced vegetation index) of community productivity to identify the factors influencing community stability. Our results showed that functional composition influenced community stability the most, explaining 61.71% of the variation in community stability (of which functional diversity explained 18.56% and functional identity explained 43.15%), which was a higher contribution than that of biodiversity (Berger-Parker index and species evenness; 35.04%). Structural equation modeling suggested that functional identity strongly affected community stability, whereas biodiversity had a minor impact. Furthermore, functional identity of leaf dry matter content regulated community stability by enhancing species dominance (Berger-Parker index). Our findings demonstrate that functional composition, specifically functional identity, plays a key role in community stability, highlighting the importance of functional identity in understanding and revealing the stabilizing mechanisms in these fragile alpine ecosystems which are subjected to increasing environmental fluctuations.
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Affiliation(s)
- Ge Hou
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Tiancai Zhou
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Jian Sun
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Ning Zong
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China.
| | - Jialuo Yu
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Minghua Song
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Juntao Zhu
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yangjian Zhang
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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20
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Yu J, Hou G, Zhou T, Shi P, Zong N, Sun J. Variation of plant CSR strategies across a precipitation gradient in the alpine grasslands on the northern Tibet Plateau. Sci Total Environ 2022; 838:156512. [PMID: 35679928 DOI: 10.1016/j.scitotenv.2022.156512] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 05/24/2022] [Accepted: 06/02/2022] [Indexed: 06/15/2023]
Abstract
Identifying ecological strategies based on functional traits can help us better understand plants' adaptations and changes in ecological processes, and thus predict the impact of climate change on ecosystems, especially in the vulnerable alpine grasslands. Herein, we investigated the plant CSR strategies of four grassland types (alpine meadows, AM; alpine meadow steppes, AMS; alpine steppes, AS; and alpine desert steppes, ADS) and its functional groups (grasses, sedges, legumes, and forbs) along the east-to-west gradient of decreasing precipitation on the northern Tibetan grasslands by using Grime's CSR (C: competitor, S: stress tolerator, and R: ruderal) analysis. Although alpine grasslands were dominated by S-strategy, our results also indicated that AM with higher water, nitrogen (N) and phosphorus (P) availability had significantly lower S-strategy values and relatively higher C- and R-strategy values (C: S: R = 6: 63: 31 %) than those in AMS (C: S: R = 3: 94: 3 %,), AS (C: S: R = 3: 87: 10 %), and ADS (C: S: R = 1: 94: 5 %). The CSR strategy values of forbs and legumes showed greater variability compared with grasses and sedges in the environmental gradient. Furthermore, water variability on the precipitation gradient eventually affected plant traits and CSR strategies through soil N and P availability and pH. Our findings highlighted that plant CSR strategies were regulated by the availability of soil resources, and plants adopted more flexible adaptation strategies in relatively resource-rich environments. This study sheds light on the mechanisms of plant adaptation to the changing environment in the alpine grasslands.
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Affiliation(s)
- Jialuo Yu
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Ge Hou
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Tiancai Zhou
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China.
| | - Ning Zong
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Jian Sun
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
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21
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Ma T, Hao L, Shi P, Qiu M, Liang M, Sun YF, Shi YF. [Clinical outcomes of transoral endoscopic thyroidectomy vestibular approach assisted with submental mini-incision for early thyroid papillary carcinoma]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2022; 57:986-990. [PMID: 36058667 DOI: 10.3760/cma.j.cn115330-20210901-00590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To investigate the efficacy of transoral endoscopic thyroidectomy vestibular approach (TOETVA) assisted with submental mini-incision in early thyroid papillary carcinoma. Methods: A total of 63 patients with early papillary thyroid carcinoma (cT1N0M0) were included who underwent TOETVA from December 2019 to May 2021 in Department of Thyroid Surgery of the Affiliated Hospital of Jining Medical University. There were 4 males and 59 females, aged from 17 to 46 years old. Of those 36 patients received traditional TOETVA as control and 27 patients accepted modified TOETVA assisted with submental mini-incision. The clinical outcomes of patients in two groups were compared. Chi-square test and t test were used in statistical analyses. Results: Compared to control group, modified TOETVA group had the less mean operation time [(146.63±38.62) minutes vs. (167.78±36.71) minutes, t=-2.21, P=0.031], the shorter time required for returning to normal diet after operation [(2.11±0.89) days vs. (2.72±1.16) days, t=-2.28, P=0.026], and the lower probability of mandibular numbness (0 vs. 16.67%, χ2=4.97, P=0.026). There was no significant difference between two groups in intraoperative blood loss, postoperative drainage volume, number of central lymph nodes dissection, and postoperative complications such as gas embolism, postoperative bleeding, postoperative infection, skin burns, subcutaneous effusion and so on(all P>0.05). After 6 months of operation, the thyroid ultrasound of the patients in two groups showed no recurrence, and the patients were satisfied with their surgical incision appearances. Conclusion: Both the modified and traditional TOETVA show similar efficacies for treatments of early thyroid papillary carcinoma, but the modified TOETVA can reduce the operation time and improve the quality of life.
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Affiliation(s)
- T Ma
- Department of Thyroid Surgery, the Affiliated Hospital of Jining Medical University, Jining 272000, China
| | - L Hao
- Department of Thyroid Surgery, the Affiliated Hospital of Jining Medical University, Jining 272000, China
| | - P Shi
- Department of Thyroid Surgery, the Affiliated Hospital of Jining Medical University, Jining 272000, China
| | - M Qiu
- Department of Thyroid Surgery, the Affiliated Hospital of Jining Medical University, Jining 272000, China
| | - M Liang
- Department of Thyroid Surgery, the Affiliated Hospital of Jining Medical University, Jining 272000, China
| | - Y F Sun
- Department of Thyroid Surgery, the Affiliated Hospital of Jining Medical University, Jining 272000, China
| | - Y F Shi
- Department of Thyroid Surgery, the Affiliated Hospital of Jining Medical University, Jining 272000, China
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22
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Tian Q, Lu P, Zhai X, Zhang R, Zheng Y, Wang H, Nie B, Bai W, Niu S, Shi P, Yang Y, Li K, Yang D, Stevens C, Lambers H, Zhang WH. An integrated belowground trait-based understanding of nitrogen-driven plant diversity loss. Glob Chang Biol 2022; 28:3651-3664. [PMID: 35231142 DOI: 10.1111/gcb.16147] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 02/15/2022] [Indexed: 06/14/2023]
Abstract
Belowground plant traits play important roles in plant diversity loss driven by atmospheric nitrogen (N) deposition. However, the way N enrichment shapes plant microhabitats by patterning belowground traits and finally determines aboveground responses is poorly understood. Here, we investigated the rhizosheath trait of 74 plant species in seven N-addition simulation experiments across multiple grassland ecosystems in China. We found that rhizosheath formation differed among plant functional groups and contributed to changes in plant community composition induced by N enrichment. Compared with forb species, grass and sedge species exhibited distinct rhizosheaths; moreover, grasses and sedges expanded their rhizosheaths with increasing N-addition rate which allowed them to colonize belowground habitats. Grasses also shaped a different microenvironment around their roots compared with forbs by affecting the physicochemical, biological, and stress-avoiding properties of their rhizosphere soil. Rhizosheaths act as a "biofilm-like shield" by the accumulation of protective compounds, carboxylic anions and polysaccharides, determined by both plants and microorganisms. This enhanced the tolerance of grasses and sedges to stresses induced by N enrichment. Conversely, forbs lacked the protective rhizosheaths which renders their roots sensitive to stresses induced by N enrichment, thus contributing to their disappearance under N-enriched conditions. This study uncovers the processes by which belowground facilitation and trait matching affect aboveground responses under conditions of N enrichment, which advances our mechanistic understanding of the contribution of competitive exclusion and environmental tolerance to plant diversity loss caused by N deposition.
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Affiliation(s)
- Qiuying Tian
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Peng Lu
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Xiufeng Zhai
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Ruifang Zhang
- Mountain Area Research Institute, Agricultural University of Hebei, Baoding, China
| | - Yao Zheng
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Hong Wang
- Mountain Area Research Institute, Agricultural University of Hebei, Baoding, China
| | - Bao Nie
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Wenming Bai
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Shuli Niu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Yuanhe Yang
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Kaihui Li
- Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China
| | - Dianlin Yang
- Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, Tianjin, China
| | - Carly Stevens
- Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | - Hans Lambers
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, Western Australia, Australia
- National Academy for Green Agriculture, China Agricultural University, Beijing, China
| | - Wen-Hao Zhang
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
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23
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Feng XS, Shi P. Can the parental socio-economic status promote the children to participate in physical exercise? An empirical study based on the survey data of CGSS 2017. Eur Rev Med Pharmacol Sci 2022; 26:4188-4296. [PMID: 35776014 DOI: 10.26355/eurrev_202206_29055] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
OBJECTIVE This paper discusses the promotion effect and mechanism of the parental socio-economic status (SES) on their offspring's participation in physical exercise and provides direction and guidance for the formulation of sports public policies. MATERIALS AND METHODS 7,965 data were obtained from the 2017 Chinese General Social Survey (CGSS) dataset. To investigate the effect and mechanism of parental SES in encouraging offspring to engage in physical activity, this paper used a binary logistic regression model and an ordinal logistic regression model. The moderating effects of urban-rural variables and birth cohorts were explored through hierarchical regression analysis and regression coefficient difference test. Robustness tests were performed by sample screening and model replacement. RESULTS After controlling for related variables, the parental SES can improve the possibility of children's participation in physical exercise (OR = 1.134, p < 0.01). Part of this promotion effect is realized by improving their children's education level (19.87%) and social communication (2.56%), and the promotion effect increases gradually with the passage of time and social changes. The robustness test results show that the empirical research results are reliable. CONCLUSIONS The parental SES can promote their children to participate in physical exercise.
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Affiliation(s)
- X S Feng
- Physical Education College, Liaoning Normal University, Dalian, P.R. China.
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Shi P, Li CY, Sun JY. Effects of air pollutant exposure on lung function in exercisers: a systematic review and meta-analysis. Eur Rev Med Pharmacol Sci 2022; 26:462-470. [PMID: 35113422 DOI: 10.26355/eurrev_202201_27871] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
OBJECTIVE The aim of this study is to systematically evaluate the effect of air pollutant exposure on lung function in exercisers. MATERIALS AND METHODS Computer search Web of Science, PubMed, EBSCO and Cochrane Library, MINORS scale for literature quality evaluation, and Stata 12.0 software for statistical analysis. RESULTS According to the literature inclusion and exclusion criteria, a total of 14 pieces of literature were screened and included in the Meta-analysis, and the literature quality was relatively high. Meta-analysis shows that air pollutant exposure has no significant effect on FVC, FEV1 and PEF of exercisers (p>0.05); but it can significantly increase the FeNO level of exercisers [Z=2.26, p = 0.024, SMD=-0.228, 95% CI= (-0.426, -0.031)]. Egger linear regression analysis shows that FVC [β=-4.64, p = 0.004, 95% CI= (-7.32,-1.95)] has the possibility of publication bias; FEV1, PEF and FeNO p>0.05 and 95% CI contains 0, there is no publication bias in the included literature. There is no sensitivity problem in the included literature, and the combined result is robust and reliable. CONCLUSIONS Exposure to air pollutants may cause allergic airway inflammation by increasing FeNO levels in exercised populations, and adversely affecting human health.
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Affiliation(s)
- P Shi
- School of Physical Education and Sports Training, Shanghai University of Sport, Shanghai, China.
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Zhou T, Hou G, Sun J, Zong N, Shi P. Degradation shifts plant communities from S- to R-strategy in an alpine meadow, Tibetan Plateau. Sci Total Environ 2021; 800:149572. [PMID: 34392221 DOI: 10.1016/j.scitotenv.2021.149572] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 08/01/2021] [Accepted: 08/06/2021] [Indexed: 05/25/2023]
Abstract
The replacement of dominant sedges/grasses with secondary forbs is common in alpine rangelands, but the underlying plant ecological strategies and their relevance to leaf traits and their variabilities of different plant functional groups remain largely unknown. Here, we measured key leaf traits and analyzed the competitor, stress-tolerator and ruderal (CSR) strategies of major species with different functional groups (sedges, grasses and forbs) in an alpine meadow along a degradation gradient on the Tibetan Plateau. Our results indicated that S-selected species were dominant in both non-degraded (C:S:R = 1:95:4%) and severely degraded (C:S:R = 2:87:11%) meadows. However, there was a shift from S- to R-strategy in the communities after rangeland degradation. More specifically, sedges and grasses with a "conservative" strategy maintained stronger S-strategy to tolerate degraded and stressful conditions. In contrast, forbs with an "opportunistic" strategy (increase 9.5% in R-score) tended to adapt to degraded stages. Moreover, 51.1% and 23.9% of the increased R-scores in forbs were accounted by leaf mass per area and specific leaf area, respectively. Generally, higher leaf water and nitrogen contents coupled with larger variations in leaf traits and flexible SR strategies in forbs enabled them to capitalize on lower soil water and nutrient availability. Our findings highlighted that the contrasting strategies of plant species in response to the decrease in available resources might lead to niche expansion of secondary forbs and loss of diversity in the degraded alpine meadow. The emerging alternative stable states in the degraded rangelands might bring about a predicament for rangeland restoration.
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Affiliation(s)
- Tiancai Zhou
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China.
| | - Ge Hou
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Jian Sun
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Ning Zong
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China.
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China.
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Li H, Wang C, Zhang F, He Y, Shi P, Guo X, Wang J, Zhang L, Li Y, Cao G, Zhou H. Atmospheric water vapor and soil moisture jointly determine the spatiotemporal variations of CO 2 fluxes and evapotranspiration across the Qinghai-Tibetan Plateau grasslands. Sci Total Environ 2021; 791:148379. [PMID: 34412395 DOI: 10.1016/j.scitotenv.2021.148379] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 06/07/2021] [Accepted: 06/07/2021] [Indexed: 06/13/2023]
Abstract
Alpine grasslands play important functions in mitigating climate change and regulating water resources. However, the spatiotemporal variability of their carbon and water budgets remains unquantified. Here, 47 site-year observations of CO2 and water vapor fluxes (ET) are analyzed at sites situated along a hydrothermal gradient across the Qinghai-Tibetan Plateau, including an alpine wetland (wettest), an alpine shrub (coldest), an alpine meadow, an alpine meadow-steppe, and an alpine steppe (driest and warmest). The results show that the benchmarks for annual net ecosystem exchange (NEE) are -79.3, -77.8, -66.7, 20.2, and 100.9 g C m-2 year-1 at the meadow, shrub, meadow-steppe, steppe, and wetland, respectively. The peak daily NEE normalized by peak leaf area index converges to 0.93 g C m-2 d-1 at the 5 sites. Except in the wetland (722.8 mm), the benchmarks of annual ET fluctuate from 511.0 mm in the steppe to 589.2 mm in the meadow. Boosted regression trees-based analysis suggests that the enhanced vegetation index (EVI) and net radiation (Rn) determine the variations of growing season monthly CO2 fluxes and ET, respectively, although the effect is to some extent site-specific. Inter-annual variability in NEE, ecosystem respiration (RES), and ET are tightly (R2 > 0.60) related to the inter-growing season NEE, RES, and ET, respectively. Both annual RES and annual NEE are significantly constrained by annual gross primary productivity (GPP), with 85% of the per-unit GPP contributing to RES (R2 = 0.84) and 15% to NEE (R2 = 0.12). Annual GPP significantly correlates with annual ET alone at the drier sites of the meadow-steppe and the steppe, suggesting the coupling of carbon and water is moisture-dependent in alpine grasslands. Over half of the inter-annual spatial variability in GPP, RES, NEE, and ET is explained by EVI, atmospheric water vapor, topsoil water content, and bulk surface resistance (rs), respectively. Because the spatial variations of EVI and rs are strongly regulated by atmospheric water vapor (R2 = 0.48) and topsoil water content (R2 = 0.54), respectively, we conclude that atmospheric water vapor and topsoil water content, rather than the expected air/soil temperatures, drive the spatiotemporal variations in CO2 fluxes and ET across temperature-limited grasslands. These findings are critical for improving predictions of the carbon sequestration and water holding capacity of alpine grasslands.
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Affiliation(s)
- Hongqin Li
- College of Life Sciences, Luoyang Normal University, Luoyang, Henan 471934, China; Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai 810001, China
| | - Chunyu Wang
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai 810001, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fawei Zhang
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai 810001, China; Qinghai Provincial Key Laboratory of Restoration Ecology in Cold Region, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai 810001, China; Institute of Sanjiangyuan National Park, Chinese Academy of Sciences, Xining, Qinghai 810001, China.
| | - Yongtao He
- Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Peili Shi
- Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaowei Guo
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai 810001, China
| | - Junbang Wang
- Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Leiming Zhang
- Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yingnian Li
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai 810001, China; Institute of Sanjiangyuan National Park, Chinese Academy of Sciences, Xining, Qinghai 810001, China.
| | - Guangmin Cao
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai 810001, China
| | - Huakun Zhou
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai 810001, China; Qinghai Provincial Key Laboratory of Restoration Ecology in Cold Region, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai 810001, China
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Zhou T, Sun J, Zong N, Hou G, Shi P. Community species diversity mediates the trade-off between aboveground and belowground biomass for grasses and forbs in degraded alpine meadow, Tibetan Plateau. Ecol Evol 2021; 11:13259-13267. [PMID: 34646467 PMCID: PMC8495812 DOI: 10.1002/ece3.8048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 08/03/2021] [Accepted: 08/06/2021] [Indexed: 11/11/2022] Open
Abstract
Although many empirical experiments have shown that increasing degradation results in lower aboveground biomass (AGB), our knowledge of the magnitude of belowground biomass (BGB) for individual plants is a prerequisite for accurately revealing the biomass trade-off in degraded grasslands. Here, by linking the AGB and BGB of individual plants, species in the community, and soil properties, we explored the biomass partitioning patterns in different plant functional groups (grasses of Stipa capillacea and forbs of Anaphalis xylorhiza). Our results indicated that 81% and 60% of the biomass trade-off variations could be explained by environmental factors affecting grasses and forbs, respectively. The change in community species diversity dominated the biomass trade-off via either direct or indirect effects on soil properties and biomass. However, the community species diversity imparted divergent effects on the biomass trade-off for grasses (scored at -0.72) and forbs (scored at 0.59). Our findings suggest that plant communities have evolved two contrasting strategies of biomass allocation patterns in degraded grasslands. These are the "conservative" strategy in grasses, in which plants with larger BGB trade-off depends on gigantic roots for soil resources, and the "opportunistic" strategy in forbs, in which plants can adapt to degraded lands using high variation and optimal biomass allocation.
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Affiliation(s)
- Tiancai Zhou
- Key Laboratory of Ecosystem Network Observation and Modelling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China
- College of Resources and Environment University of Chinese Academy of Sciences Beijing China
| | - Jian Sun
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE) Institute of Tibetan Plateau Research Chinese Academy of Sciences Beijing China
| | - Ning Zong
- Key Laboratory of Ecosystem Network Observation and Modelling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China
| | - Ge Hou
- Key Laboratory of Ecosystem Network Observation and Modelling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China
- College of Resources and Environment University of Chinese Academy of Sciences Beijing China
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and Modelling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China
- College of Resources and Environment University of Chinese Academy of Sciences Beijing China
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Wen J, Shi ZB, Zhong WL, Yang ZC, Yang ZJ, Wang B, Jiang M, Shi PW, Hillesheim JC, Freethy SJ, Shi P, Liang AS, Tong RH, Fang KR, Deng WC, Liu Y, Yang QW, Ding XT, Xu M. A remote gain controlled and polarization angle tunable Doppler backward scattering reflectometer. Rev Sci Instrum 2021; 92:063513. [PMID: 34243534 DOI: 10.1063/5.0043676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 05/15/2021] [Indexed: 06/13/2023]
Abstract
Remote control of the diagnostic systems is the basic requirement for the high performance plasma operation in a fusion device. This work presents the development of the remote control system for the multichannel Doppler backward scattering (DBS) reflectometers. It includes a remote controlled quasi-optical system and a remote intermediate frequency (IF) amplifier gain control system. The quasi-optical system contains a rotational polarizer, its polarization angle is tunable through a remote controlled motor, and it could combine the microwave beams with a wide frequency range into one focused beam. The remote IF gain control system utilizes the digital microcontroller (MCU) technique to regulate the signal amplitude for each signal channel. The gain parameters of amplifiers are adjustable, and the feedback of working status in the IF system will be sent to MCU in real time for safe operation. The gain parameters could be controlled either by the Ethernet remote way or directly through the local control interface on the system. Preliminary experimental results show the effectiveness of the remote controlled multichannel DBS system.
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Affiliation(s)
- J Wen
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
| | - Z B Shi
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
| | - W L Zhong
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
| | - Z C Yang
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
| | - Z J Yang
- Huazhong University of Science and Technology, Wuhan 430074, China
| | - B Wang
- University of Electronic Science and Technology of China, Chengdu 610054, China
| | - M Jiang
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
| | - P W Shi
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
| | - J C Hillesheim
- Culham Centre for Fusion Energy, Abingdon, Oxon OX14 3DB, United Kingdom
| | - S J Freethy
- Culham Centre for Fusion Energy, Abingdon, Oxon OX14 3DB, United Kingdom
| | - P Shi
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
| | - A S Liang
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
| | - R H Tong
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
| | - K R Fang
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
| | - W C Deng
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
| | - Y Liu
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
| | - Q W Yang
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
| | - X T Ding
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
| | - M Xu
- Southwestern Institute of Physics, P.O. Box 432, Chengdu 610041, China
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30
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Niu B, Zhang X, Piao S, Janssens IA, Fu G, He Y, Zhang Y, Shi P, Dai E, Yu C, Zhang J, Yu G, Xu M, Wu J, Zhu L, Desai AR, Chen J, Bohrer G, Gough CM, Mammarella I, Varlagin A, Fares S, Zhao X, Li Y, Wang H, Ouyang Z. Warming homogenizes apparent temperature sensitivity of ecosystem respiration. Sci Adv 2021; 7:7/15/eabc7358. [PMID: 33837072 PMCID: PMC8034862 DOI: 10.1126/sciadv.abc7358] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 02/24/2021] [Indexed: 06/02/2023]
Abstract
Warming-induced carbon loss through terrestrial ecosystem respiration (Re) is likely getting stronger in high latitudes and cold regions because of the more rapid warming and higher temperature sensitivity of Re (Q 10). However, it is not known whether the spatial relationship between Q 10 and temperature also holds temporally under a future warmer climate. Here, we analyzed apparent Q 10 values derived from multiyear observations at 74 FLUXNET sites spanning diverse climates and biomes. We found warming-induced decline in Q 10 is stronger at colder regions than other locations, which is consistent with a meta-analysis of 54 field warming experiments across the globe. We predict future warming will shrink the global variability of Q 10 values to an average of 1.44 across the globe under a high emission trajectory (RCP 8.5) by the end of the century. Therefore, warming-induced carbon loss may be less than previously assumed because of Q 10 homogenization in a warming world.
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Affiliation(s)
- Ben Niu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xianzhou Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Shilong Piao
- College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
- Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100085, China
| | - Ivan A Janssens
- Department of Biology, University of Antwerpen, Universiteitsplein 1, Wilrijk B-2610, Belgium
| | - Gang Fu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yongtao He
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Yangjian Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Erfu Dai
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Chengqun Yu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Jing Zhang
- College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
| | - Guirui Yu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Ming Xu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Jianshuang Wu
- Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, 100081 Beijing, China
| | - Liping Zhu
- Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100085, China
| | - Ankur R Desai
- Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Jiquan Chen
- Department of Geography, Michigan State University, East Lansing, MI 48823, USA
| | - Gil Bohrer
- Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH 43210, USA
| | - Christopher M Gough
- Department of Biology, Virginia Commonwealth University, Richmond, VA 23284-2012, USA
| | - Ivan Mammarella
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, P.O. Box 68, Helsinki FI-00014, Finland
| | - Andrej Varlagin
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow 119071, Russia
| | - Silvano Fares
- National Research Council of Italy, Institute of BioEconomy, Via dei Taurini 19, 00100 Rome, Italy
| | - Xinquan Zhao
- Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China
| | - Yingnian Li
- Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China
| | - Huiming Wang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhu Ouyang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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Zhou J, Cheng T, Li X, Pineda J, Wang X, Si H, Shi P, Shen R, Zhou N, Bai C. P46.01 Intronic Noncoding RNA Expression of DCN is Related to Cancer-Associated Fibroblasts and NSCLC Patients’ Prognosis. J Thorac Oncol 2021. [DOI: 10.1016/j.jtho.2021.01.850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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32
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Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah YW, Poindexter C, Chen J, Elbashandy A, Humphrey M, Isaac P, Polidori D, Reichstein M, Ribeca A, van Ingen C, Vuichard N, Zhang L, Amiro B, Ammann C, Arain MA, Ardö J, Arkebauer T, Arndt SK, Arriga N, Aubinet M, Aurela M, Baldocchi D, Barr A, Beamesderfer E, Marchesini LB, Bergeron O, Beringer J, Bernhofer C, Berveiller D, Billesbach D, Black TA, Blanken PD, Bohrer G, Boike J, Bolstad PV, Bonal D, Bonnefond JM, Bowling DR, Bracho R, Brodeur J, Brümmer C, Buchmann N, Burban B, Burns SP, Buysse P, Cale P, Cavagna M, Cellier P, Chen S, Chini I, Christensen TR, Cleverly J, Collalti A, Consalvo C, Cook BD, Cook D, Coursolle C, Cremonese E, Curtis PS, D'Andrea E, da Rocha H, Dai X, Davis KJ, De Cinti B, de Grandcourt A, De Ligne A, De Oliveira RC, Delpierre N, Desai AR, Di Bella CM, di Tommasi P, Dolman H, Domingo F, Dong G, Dore S, Duce P, Dufrêne E, Dunn A, Dušek J, Eamus D, Eichelmann U, ElKhidir HAM, Eugster W, Ewenz CM, Ewers B, Famulari D, Fares S, Feigenwinter I, Feitz A, Fensholt R, Filippa G, Fischer M, Frank J, Galvagno M, Gharun M, Gianelle D, Gielen B, Gioli B, Gitelson A, Goded I, Goeckede M, Goldstein AH, Gough CM, Goulden ML, Graf A, Griebel A, Gruening C, Grünwald T, Hammerle A, Han S, Han X, Hansen BU, Hanson C, Hatakka J, He Y, Hehn M, Heinesch B, Hinko-Najera N, Hörtnagl L, Hutley L, Ibrom A, Ikawa H, Jackowicz-Korczynski M, Janouš D, Jans W, Jassal R, Jiang S, Kato T, Khomik M, Klatt J, Knohl A, Knox S, Kobayashi H, Koerber G, Kolle O, Kosugi Y, Kotani A, Kowalski A, Kruijt B, Kurbatova J, Kutsch WL, Kwon H, Launiainen S, Laurila T, Law B, Leuning R, Li Y, Liddell M, Limousin JM, Lion M, Liska AJ, Lohila A, López-Ballesteros A, López-Blanco E, Loubet B, Loustau D, Lucas-Moffat A, Lüers J, Ma S, Macfarlane C, Magliulo V, Maier R, Mammarella I, Manca G, Marcolla B, Margolis HA, Marras S, Massman W, Mastepanov M, Matamala R, Matthes JH, Mazzenga F, McCaughey H, McHugh I, McMillan AMS, Merbold L, Meyer W, Meyers T, Miller SD, Minerbi S, Moderow U, Monson RK, Montagnani L, Moore CE, Moors E, Moreaux V, Moureaux C, Munger JW, Nakai T, Neirynck J, Nesic Z, Nicolini G, Noormets A, Northwood M, Nosetto M, Nouvellon Y, Novick K, Oechel W, Olesen JE, Ourcival JM, Papuga SA, Parmentier FJ, Paul-Limoges E, Pavelka M, Peichl M, Pendall E, Phillips RP, Pilegaard K, Pirk N, Posse G, Powell T, Prasse H, Prober SM, Rambal S, Rannik Ü, Raz-Yaseef N, Rebmann C, Reed D, de Dios VR, Restrepo-Coupe N, Reverter BR, Roland M, Sabbatini S, Sachs T, Saleska SR, Sánchez-Cañete EP, Sanchez-Mejia ZM, Schmid HP, Schmidt M, Schneider K, Schrader F, Schroder I, Scott RL, Sedlák P, Serrano-Ortíz P, Shao C, Shi P, Shironya I, Siebicke L, Šigut L, Silberstein R, Sirca C, Spano D, Steinbrecher R, Stevens RM, Sturtevant C, Suyker A, Tagesson T, Takanashi S, Tang Y, Tapper N, Thom J, Tomassucci M, Tuovinen JP, Urbanski S, Valentini R, van der Molen M, van Gorsel E, van Huissteden K, Varlagin A, Verfaillie J, Vesala T, Vincke C, Vitale D, Vygodskaya N, Walker JP, Walter-Shea E, Wang H, Weber R, Westermann S, Wille C, Wofsy S, Wohlfahrt G, Wolf S, Woodgate W, Li Y, Zampedri R, Zhang J, Zhou G, Zona D, Agarwal D, Biraud S, Torn M, Papale D. Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Sci Data 2021; 8:72. [PMID: 33633116 PMCID: PMC7907353 DOI: 10.1038/s41597-021-00851-9] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Affiliation(s)
- Gilberto Pastorello
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
| | - Carlo Trotta
- DIBAF, University of Tuscia, Viterbo, 01100, Italy
| | - Eleonora Canfora
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy
| | - Housen Chu
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Danielle Christianson
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - You-Wei Cheah
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Cristina Poindexter
- Department of Civil Engineering, California State University, Sacramento, CA, 95819, USA
| | - Jiquan Chen
- Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI, 48823, USA
| | - Abdelrahman Elbashandy
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Marty Humphrey
- Department of Computer Science, University of Virginia, Charlottesville, VA, 22904, USA
| | - Peter Isaac
- TERN Ecosystem Processes, Menzies Creek, VIC3159, Australia
| | - Diego Polidori
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy
| | | | - Alessio Ribeca
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy
| | - Catharine van Ingen
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Nicolas Vuichard
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA CNRS, UVSQ UPSACLAY, Gif sur Yvette, 91190, France
| | - Leiming Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Brian Amiro
- Department of Soil Science, University of Manitoba, Winnipeg, MB, R3T2N2, Canada
| | - Christof Ammann
- Department of Agroecology and Environment, Agroscope Research Institute, Zürich, 8046, Switzerland
| | - M Altaf Arain
- School of Geography and Earth Sciences, McMaster University, L8S4K1, Hamilton, ON, Canada
| | - Jonas Ardö
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, 22362, Sweden
| | - Timothy Arkebauer
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA
| | - Stefan K Arndt
- School of Ecosystem and Forest Sciences, The University of Melbourne, Richmond, VIC3121, Australia
| | - Nicola Arriga
- Department of Biology, Research Group PLECO, University of Antwerp, Antwerp, 2610, Belgium.,Joint Research Centre, European Commission, Ispra, 21027, Italy
| | - Marc Aubinet
- TERRA Teaching and Research Center, University of Liege, Gembloux, B-5030, Belgium
| | - Mika Aurela
- Finnish Meteorological Institute, Helsinki, 00560, Finland
| | - Dennis Baldocchi
- ESPM, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Alan Barr
- Global Institute for Water Security, University of Saskatchewan, Saskatoon, SK, S7N3H5, Canada.,Climate Research Division, Environment and Climate Change Canada, Saskatoon, SK, S7N3H5, Canada
| | - Eric Beamesderfer
- School of Geography and Earth Sciences, McMaster University, L8S4K1, Hamilton, ON, Canada
| | - Luca Belelli Marchesini
- Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige, 38010, Italy.,Department of Landscape Design and Sustainable Ecosystems, Agrarian-Technological Institute, RUDN University, Moscow, 117198, Russia
| | - Onil Bergeron
- Direction du marché du carbone, Ministère du Développement durable de l'Environnement et de la Lutte contre les changements climatiques, Québec, QC, G1R5V7, Canada
| | - Jason Beringer
- School of Agriculture and Environment, University of Western Australia, Crawley, 6009, Australia
| | - Christian Bernhofer
- Institute of Hydrology and Meteorology, Technische Universität Dresden, Tharandt, 01737, Germany
| | - Daniel Berveiller
- Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Systématique et Evolution, Orsay, 91405, France
| | - Dave Billesbach
- Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA
| | - Thomas Andrew Black
- Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, V6T1Z4, Canada
| | - Peter D Blanken
- Department of Geography, University of Colorado, Boulder, CO, 80309, USA
| | - Gil Bohrer
- Department of Civil, Environmental & Geodetic Engineering, Ohio State University, Columbus, OH, 43210, USA
| | - Julia Boike
- Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, 14482, Germany.,Geography Department, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Paul V Bolstad
- Forest Resources, University of Minnesota, St Paul, MN, 55108, USA
| | - Damien Bonal
- Université de Lorraine, AgroParisTech, INRAE, UMR Silva, Nancy, 54000, France
| | | | - David R Bowling
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - Rosvel Bracho
- School of Forest Resources and Conservation, University of Florida, Gainesville, FL, 32611, USA
| | - Jason Brodeur
- McMaster University Library, McMaster University, Hamilton, ON, L8S4L6, Canada
| | - Christian Brümmer
- Thünen Institute of Climate-Smart Agriculture, Federal Research Institute of Rural Areas, Forestry and Fisheries, Braunschweig, 38116, Germany
| | - Nina Buchmann
- Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
| | | | - Sean P Burns
- Department of Geography, University of Colorado, Boulder, CO, 80309, USA.,Mesoscale and Microscale Meteorology Laboratory, National Center for Atmospheric Research, Boulder, CO, 80301, USA
| | - Pauline Buysse
- Université Paris-Saclay, INRAE, AgroParisTech, UMR ECOSYS, Thiverval-Grignon, 78850, France
| | - Peter Cale
- Australian Landscape Trust, Renmark, SA5341, Australia
| | - Mauro Cavagna
- Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige, 38010, Italy
| | - Pierre Cellier
- Université Paris-Saclay, INRAE, AgroParisTech, UMR ECOSYS, Thiverval-Grignon, 78850, France
| | - Shiping Chen
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Isaac Chini
- Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige, 38010, Italy
| | - Torben R Christensen
- Department of Bioscience, Arctic Research Center, Aarhus University, Roskilde, 4000, Denmark
| | - James Cleverly
- School of Life Sciences, University of Technology Sydney, Sydney, 2007, Australia.,Terrestrial Ecosystem Research Network TERN, University of Technology, Sydney, 2007, Australia
| | - Alessio Collalti
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Institute for Agricultural and Forestry Systems in the Mediterranean, National Research Council of Italy, Ercolano, 80056, Italy
| | - Claudia Consalvo
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Research Institute on Terrestrial Ecosystems, National Research Council of Italy, Porano, 05010, Italy
| | - Bruce D Cook
- Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, 20771, USA
| | - David Cook
- Environmental Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA
| | - Carole Coursolle
- Canadian Forest Service, Natural Resources Canada, Québec, QC, G1V4C7, Canada.,Centre d'étude de la forêt, Faculté de foresterie, de géographie et de géomatique, Université Laval, Québec, QC, G1V0A6, Canada
| | - Edoardo Cremonese
- Climate Change Unit, Environmental Protection Agency of Aosta Valley, Saint Christophe, 11020, Italy
| | - Peter S Curtis
- Department of Evolution, Ecology, and Organismal Biology, Ohio State University, Columbus, OH, 43210, USA
| | - Ettore D'Andrea
- Institute for Agricultural and Forestry Systems in the Mediterranean, National Research Council of Italy, Ercolano, 80056, Italy
| | - Humberto da Rocha
- Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, SP, 01000-000, Brazil
| | - Xiaoqin Dai
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Kenneth J Davis
- Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Bruno De Cinti
- Institute of Research on Terrestrial Ecosystems, National Research Council of Italy, Montelibretti, 00010, Italy
| | | | - Anne De Ligne
- TERRA Teaching and Research Center, University of Liege, Gembloux, B-5030, Belgium
| | | | - Nicolas Delpierre
- Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Systématique et Evolution, Orsay, 91405, France
| | - Ankur R Desai
- Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Carlos Marcelo Di Bella
- Departamento de Métodos Cuantitativos y Sistemas de Información, Facultad de Agronomía, UBA, Buenos Aires, 1417, Argentina
| | - Paul di Tommasi
- Institute for Agricultural and Forestry Systems in the Mediterranean, National Research Council of Italy, Ercolano, 80056, Italy
| | - Han Dolman
- Department of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
| | - Francisco Domingo
- Desertification and Geoecology Department, Experimental Station of Arid Zones, CSIC, Almería, 04120, Spain
| | - Gang Dong
- School of Life Science, Shanxi University, Taiyuan, 030006, China
| | | | - Pierpaolo Duce
- Institute of BioEconomy, National Research Council of Italy, Sassari, 07100, Italy
| | - Eric Dufrêne
- Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Systématique et Evolution, Orsay, 91405, France
| | - Allison Dunn
- Department of Earth, Environment, and Physics, Worcester State University, Worcester, MA, 01602, USA
| | - Jiří Dušek
- Department of Matter and Energy Fluxes, Global Change Research Institute of the Czech Academy of Sciences, Brno, 60300, Czech Republic
| | - Derek Eamus
- School of Life Sciences, University of Technology Sydney, Sydney, 2007, Australia
| | - Uwe Eichelmann
- Institute of Hydrology and Meteorology, Technische Universität Dresden, Tharandt, 01737, Germany
| | | | - Werner Eugster
- Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
| | - Cacilia M Ewenz
- Airborne Research Australia, TERN Ecosystem Processes Central Node, Parafield, 5106, Australia
| | - Brent Ewers
- Department of Botany, Program in Ecology, University of Wyoming, 1000 E. Univ. Ave, Laramie, WY, 82071, USA
| | - Daniela Famulari
- Institute for Agricultural and Forestry Systems in the Mediterranean, National Research Council of Italy, Ercolano, 80056, Italy
| | - Silvano Fares
- Institute of BioEconomy, National Research Council of Italy, Rome, 00100, Italy.,Research Centre for Forestry and Wood, Council for Agricultural Research and Economics, Rome, 00166, Italy
| | - Iris Feigenwinter
- Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
| | | | - Rasmus Fensholt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, 1350, Denmark
| | - Gianluca Filippa
- Climate Change Unit, Environmental Protection Agency of Aosta Valley, Saint Christophe, 11020, Italy
| | - Marc Fischer
- Energy Analysis & Environmental Impacts Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - John Frank
- USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO, 80526, USA
| | - Marta Galvagno
- Climate Change Unit, Environmental Protection Agency of Aosta Valley, Saint Christophe, 11020, Italy
| | - Mana Gharun
- Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
| | - Damiano Gianelle
- Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige, 38010, Italy
| | - Bert Gielen
- Department of Biology, Research Group PLECO, University of Antwerp, Antwerp, 2610, Belgium
| | - Beniamino Gioli
- Institute of BioEconomy, National Research Council of Italy, Firenze, 50145, Italy
| | - Anatoly Gitelson
- School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA
| | - Ignacio Goded
- Joint Research Centre, European Commission, Ispra, 21027, Italy
| | | | | | - Christopher M Gough
- Department of Biology, Virginia Commonwealth University, Richmond, VA, 23284, USA
| | - Michael L Goulden
- Department of Earth System Science, University of California, Irvine, CA, 92697, USA
| | - Alexander Graf
- Agrosphere (IBG3), Forschungszentrum Jülich, Jülich, 52428, Germany
| | - Anne Griebel
- School of Ecosystem and Forest Sciences, The University of Melbourne, Richmond, VIC3121, Australia
| | | | - Thomas Grünwald
- Institute of Hydrology and Meteorology, Technische Universität Dresden, Tharandt, 01737, Germany
| | - Albin Hammerle
- Department of Ecology, University of Innsbruck, Innsbruck, 6020, Austria
| | - Shijie Han
- International Joint Research Laboratory for Global Change Ecology, School of Life Sciences, Henan University, Kaifeng, 450000, China.,Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China
| | - Xingguo Han
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Birger Ulf Hansen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, 1350, Denmark
| | - Chad Hanson
- Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, 97333, USA
| | - Juha Hatakka
- Finnish Meteorological Institute, Helsinki, 00560, Finland
| | - Yongtao He
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100190, China
| | - Markus Hehn
- Institute of Hydrology and Meteorology, Technische Universität Dresden, Tharandt, 01737, Germany
| | - Bernard Heinesch
- TERRA Teaching and Research Center, University of Liege, Gembloux, B-5030, Belgium
| | - Nina Hinko-Najera
- School of Ecosystem and Forest Sciences, The University of Melbourne, Creswick, VIC3363, Australia
| | - Lukas Hörtnagl
- Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
| | - Lindsay Hutley
- Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, 0909, Australia
| | - Andreas Ibrom
- Department of Environmental Engineering, Technical University of Denmark (DTU), Kongens Lyngby, 2800, Denmark
| | - Hiroki Ikawa
- Institute for Agro-Environmental Sciences, National Agriculture and Food Research Organization, Tsukuba, 305-8604, Japan
| | - Marcin Jackowicz-Korczynski
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, 22362, Sweden.,Department of Bioscience, Arctic Research Center, Aarhus University, Roskilde, 4000, Denmark
| | - Dalibor Janouš
- Department of Matter and Energy Fluxes, Global Change Research Institute of the Czech Academy of Sciences, Brno, 60300, Czech Republic
| | - Wilma Jans
- Wageningen Environmental Research, Wageningen University and Research, Wageningen, 6708PB, The Netherlands
| | - Rachhpal Jassal
- Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, V6T1Z4, Canada
| | - Shicheng Jiang
- Key Laboratory of Vegetation Ecology, Ministry of Education, Northeast Normal University, Changchun, 130024, China
| | - Tomomichi Kato
- Research Faculty of Agriculture, Hokkaido University, Sapporo, 060-8589, Japan.,GI-Core, Hokkaido University, Sapporo, 060-0808, Japan
| | - Myroslava Khomik
- School of Geography and Earth Sciences, McMaster University, L8S4K1, Hamilton, ON, Canada.,Geography and Environmental Management, Waterloo, ON, N2L3G1, Canada
| | - Janina Klatt
- Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, 82467, Germany
| | - Alexander Knohl
- Bioclimatology, University of Goettingen, Goettingen, 37077, Germany.,Centre of Biodiversity and Sustainable Land Use (CBL), University of Goettingen, Goettingen, 37077, Germany
| | - Sara Knox
- Department of Geography, The University of British Columbia, Vancouver, BC, V6T1Z2, Canada
| | - Hideki Kobayashi
- Research Institute for Global Change, Institute of Arctic Climate and Environment Research, Japan Agency for Marine-Earth Science and Technology, Yokoama, 236-0001, Japan
| | - Georgia Koerber
- Biological Sciences, University of Adelaide, Adelaide, SA5064, Australia
| | - Olaf Kolle
- Max Planck Institute for Biogeochemistry, Jena, 03641, Germany
| | - Yoshiko Kosugi
- Graduate School of Agriculture, Kyoto University, Kyoto, 606-8502, Japan
| | - Ayumi Kotani
- Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, 4648601, Japan
| | - Andrew Kowalski
- Department of Applied Physics, University of Granada, Granada, 18071, Spain
| | - Bart Kruijt
- Water systems and Global Change group, Wageningen University, Wageningen, 6500, The Netherlands
| | - Julia Kurbatova
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow, 119071, Russia
| | - Werner L Kutsch
- Head Office, Integrated Carbon Observation System (ICOS ERIC), Helsinki, 00560, Finland
| | - Hyojung Kwon
- Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, 97333, USA
| | | | - Tuomas Laurila
- Finnish Meteorological Institute, Helsinki, 00560, Finland
| | - Bev Law
- Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, 97333, USA
| | | | - Yingnian Li
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810008, China
| | - Michael Liddell
- Centre for Tropical Environmental Sustainability Studies, James Cook University, Cairns, 4878, Australia
| | | | - Marryanna Lion
- Forestry and Environment Division, Forest Research Institute Malaysia (FRIM), Kepong, 52109, Malaysia
| | - Adam J Liska
- Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA
| | - Annalea Lohila
- Finnish Meteorological Institute, Helsinki, 00560, Finland.,Institute for Atmosphere and Earth System Research/Physics, University of Helsinki, Helsinki, 00560, Finland
| | - Ana López-Ballesteros
- Department of Botany, School of Natural Sciences, Trinity College Dublin, Dublin, D02PN40, Ireland
| | - Efrén López-Blanco
- Department of Bioscience, Arctic Research Center, Aarhus University, Roskilde, 4000, Denmark
| | - Benjamin Loubet
- Université Paris-Saclay, INRAE, AgroParisTech, UMR ECOSYS, Thiverval-Grignon, 78850, France
| | - Denis Loustau
- ISPA, Bordeaux Sciences Agro, INRAE, Villenave d'Ornon, 33140, France
| | - Antje Lucas-Moffat
- Thünen Institute of Climate-Smart Agriculture, Federal Research Institute of Rural Areas, Forestry and Fisheries, Braunschweig, 38116, Germany.,German Meteorological Service (DWD), Centre for Agrometeorological Research, Braunschweig, 38116, Germany
| | - Johannes Lüers
- Micrometeorology, University of Bayreuth, Bayreuth, 95440, Germany.,Bayreuth Center of Ecology and Environmental Research, 95448, Bayreuth, Germany
| | - Siyan Ma
- ESPM, University of California Berkeley, Berkeley, CA, 94720, USA
| | | | - Vincenzo Magliulo
- Institute for Agricultural and Forestry Systems in the Mediterranean, National Research Council of Italy, Ercolano, 80056, Italy
| | - Regine Maier
- Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
| | - Ivan Mammarella
- Institute for Atmosphere and Earth System Research/Physics, University of Helsinki, Helsinki, 00560, Finland
| | - Giovanni Manca
- Joint Research Centre, European Commission, Ispra, 21027, Italy
| | - Barbara Marcolla
- Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige, 38010, Italy
| | - Hank A Margolis
- Centre d'étude de la forêt, Faculté de foresterie, de géographie et de géomatique, Université Laval, Québec, QC, G1V0A6, Canada
| | - Serena Marras
- Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy.,Department of Agriculture, University of Sassari, Sassari, 07100, Italy
| | - William Massman
- USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO, 80526, USA
| | - Mikhail Mastepanov
- Department of Bioscience, Arctic Research Center, Aarhus University, Roskilde, 4000, Denmark.,Oulanka research station, University of Oulu, Kuusamo, 93900, Finland
| | - Roser Matamala
- Environmental Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA
| | | | - Francesco Mazzenga
- Research Institute on Terrestrial Ecosystems, National Research Council of Italy, Monterotondo Scalo, 00015, Italy
| | - Harry McCaughey
- Department of Geography and Planning, Queen's University, Kingston, ON, K7L3N6, Canada
| | - Ian McHugh
- School of Ecosystem and Forest Sciences, The University of Melbourne, Richmond, VIC3121, Australia
| | - Andrew M S McMillan
- Environmental Analytics NZ, Ltd. Raumati South, Paraparaumu, 5032, New Zealand
| | - Lutz Merbold
- Mazingira Centre, International Livestock Research Institute (ILRI), Nairobi, 00100, Kenya
| | - Wayne Meyer
- Biological Sciences, University of Adelaide, Adelaide, SA5064, Australia
| | - Tilden Meyers
- NOAA/OAR/Air Resources Laboratory, 325 Broadway, Boulder, CO, 80303, USA
| | - Scott D Miller
- Atmospheric Sciences Research Center, State University of New York at Albany, Albany, NY, 12203, USA
| | | | - Uta Moderow
- Institute of Hydrology and Meteorology, Technische Universität Dresden, Tharandt, 01737, Germany
| | - Russell K Monson
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA
| | - Leonardo Montagnani
- Forest Department of South Tyrol, Bolzano, 39100, Italy.,Faculty of Science and Technology, Free University of Bolzano, Bolzano, 39100, Italy
| | - Caitlin E Moore
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Eddy Moors
- IHE Delft, Delft, 2611, The Netherlands.,Faculty of Science, VU Amsterdam, Amsterdam, 1081, The Netherlands
| | - Virginie Moreaux
- ISPA, Bordeaux Sciences Agro, INRAE, Villenave d'Ornon, 33140, France.,University Grenoble Alpes, IRD, CNRS, IGE, Grenoble, 38000, France
| | - Christine Moureaux
- TERRA Teaching and Research Center, University of Liege, Gembloux, B-5030, Belgium
| | - J William Munger
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA.,Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, 02138, USA
| | - Taro Nakai
- School of Forestry and Resource Conservation, National Taiwan University, Taipei, 0617, Taiwan.,International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK, 99775, USA
| | - Johan Neirynck
- Environment and Climate, Research Institute for Nature and Forest, Geraardsbergen, 9500, Belgium
| | - Zoran Nesic
- Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, V6T1Z4, Canada
| | - Giacomo Nicolini
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy
| | - Asko Noormets
- Department of Ecosystem Science and Management, Texas A&M University, College Station, TX, 77843, USA
| | - Matthew Northwood
- Research Institute for the Environment and Livelihoods, Charles Darwin University, Casuarina, 0810, Australia
| | - Marcelo Nosetto
- Grupo de Estudios Ambientales, Instituto de Matemática Aplicada San Luis (UNSL & CONICET), San Luis, D5700HHW, Argentina.,Facultad de Ciencias Agropecuarias (UNER), Oro Verde, 3100, Argentina
| | - Yann Nouvellon
- UMR Eco&Sols, CIRAD, Montpellier, 34060, France.,Eco&Sols, Univ Montpellier-CIRAD-INRA-IRD-Montpellier SupAgro, Montpellier, 34060, France
| | - Kimberly Novick
- O'Neill School of Public and Environmental Affairs, Indiana University Bloomington, Bloomington, IN, 47405, USA
| | - Walter Oechel
- Global Change Research Group, Dept. Biology, San Diego State University, San Diego, CA, 92182, USA.,Department of Geography, College of Life and Environmental Sciences, University of Exeter, Exeter, EX44RJ, United Kingdom
| | - Jørgen Eivind Olesen
- Department of Agroecology, Aarhus University, Tjele, 8830, Denmark.,iCLIMATE, Aarhus University, Tjele, 8830, Denmark
| | | | - Shirley A Papuga
- Department of Geology, Wayne State University, Detroit, MI, 48202, USA
| | - Frans-Jan Parmentier
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, 22362, Sweden.,Department of Geosciences, University of Oslo, Oslo, 0315, Norway
| | | | - Marian Pavelka
- Department of Matter and Energy Fluxes, Global Change Research Institute of the Czech Academy of Sciences, Brno, 60300, Czech Republic
| | - Matthias Peichl
- Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Umeå, 90183, Sweden
| | - Elise Pendall
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, 2751, Australia
| | - Richard P Phillips
- Department of Biology, Indiana University Bloomington, Bloomington, IN, 47401, USA
| | - Kim Pilegaard
- Department of Environmental Engineering, Technical University of Denmark (DTU), Kongens Lyngby, 2800, Denmark
| | - Norbert Pirk
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, 22362, Sweden.,CSIRO Land and Water, Wembley, 6913, Australia
| | - Gabriela Posse
- Instituto de Clima y Agua, Instituto Nacional de Tecnologia Agropecuaria (INTA), Buenos Aires, 1686, Argentina
| | - Thomas Powell
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Heiko Prasse
- Institute of Hydrology and Meteorology, Technische Universität Dresden, Tharandt, 01737, Germany
| | | | - Serge Rambal
- CEFE, CNRS, Univ Montpellier, Montpellier, 34293, France
| | - Üllar Rannik
- Institute for Atmosphere and Earth System Research/Physics, University of Helsinki, Helsinki, 00560, Finland
| | - Naama Raz-Yaseef
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Corinna Rebmann
- Department Computational Hydrosystems, Helmholtz Centre for Environmental Research UFZ, Leipzig, 04318, Germany
| | - David Reed
- Center for Global Change & Earth Observations, Michigan State University, East Lansing, MI, 48823, USA
| | - Victor Resco de Dios
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, 2751, Australia.,School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang, 621010, China
| | - Natalia Restrepo-Coupe
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA
| | - Borja R Reverter
- Departamento de Química e Física, Universidade Federal da Paraiba, Areia, PB, 58397-000, Brazil
| | - Marilyn Roland
- Department of Biology, Research Group PLECO, University of Antwerp, Antwerp, 2610, Belgium
| | | | - Torsten Sachs
- Remote Sensing and Geoinformatics, GFZ German Research Centre for Geosciences, Potsdam, 14473, Germany
| | - Scott R Saleska
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA
| | - Enrique P Sánchez-Cañete
- Department of Applied Physics, University of Granada, Granada, 18071, Spain.,Andalusian Institute for Earth System Research (CEAMA-IISTA), Granada, 18006, Spain
| | - Zulia M Sanchez-Mejia
- Ciencias del Agua y Medioambiente, Instituto Tecnológico de Sonora, Ciudad Obregón, 85000, Mexico
| | - Hans Peter Schmid
- Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, 82467, Germany
| | - Marius Schmidt
- Agrosphere (IBG3), Forschungszentrum Jülich, Jülich, 52428, Germany
| | - Karl Schneider
- Geographical Institute, University of Cologne, Cologne, 50923, Germany
| | - Frederik Schrader
- Thünen Institute of Climate-Smart Agriculture, Federal Research Institute of Rural Areas, Forestry and Fisheries, Braunschweig, 38116, Germany
| | - Ivan Schroder
- Department of Industry, Innovation and Science, Geoscience Australia, Canberra, 2609, Australia
| | - Russell L Scott
- Southwest Watershed Research Center, USDA-ARS, Tucson, AZ, 85719, USA
| | - Pavel Sedlák
- Department of Matter and Energy Fluxes, Global Change Research Institute of the Czech Academy of Sciences, Brno, 60300, Czech Republic.,Institute of Atmospheric Physics of the Czech Academy of Sciences, Prague, 14100, Czech Republic
| | - Penélope Serrano-Ortíz
- Andalusian Institute for Earth System Research (CEAMA-IISTA), Granada, 18006, Spain.,Department of Ecology, University of Granada, Granada, 18071, Spain
| | - Changliang Shao
- National Hulunber Grassland Ecosystem Observation and Research Station & Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Ivan Shironya
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow, 119071, Russia
| | - Lukas Siebicke
- Bioclimatology, University of Goettingen, Goettingen, 37077, Germany
| | - Ladislav Šigut
- Department of Matter and Energy Fluxes, Global Change Research Institute of the Czech Academy of Sciences, Brno, 60300, Czech Republic
| | - Richard Silberstein
- School of Agriculture and Environment, University of Western Australia, Crawley, 6009, Australia.,School of Science, Edith Cowan University, Joondalup, 6027, Australia
| | - Costantino Sirca
- Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy.,Department of Agriculture, University of Sassari, Sassari, 07100, Italy
| | - Donatella Spano
- Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy.,Department of Agriculture, University of Sassari, Sassari, 07100, Italy
| | - Rainer Steinbrecher
- Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, 82467, Germany
| | | | - Cove Sturtevant
- National Ecological Observatory Network Program, Boulder, CO, 80301, USA
| | - Andy Suyker
- School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA
| | - Torbern Tagesson
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, 22362, Sweden.,Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, 1350, Denmark
| | - Satoru Takanashi
- Kansai Research Center, Forestry and Forest Products Research Institute, Kyoto, 612-0855, Japan
| | - Yanhong Tang
- College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Nigel Tapper
- School of Earth, Atmosphere and Environment, Monash University, Clayton, 3800, Australia
| | - Jonathan Thom
- Space Science and Engineering Center, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Michele Tomassucci
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Terrasystem srl, Viterbo, 01100, Italy
| | | | - Shawn Urbanski
- USDA Forest Service, Rocky Mountain Research Station, Missoula, MT, 59808, USA
| | - Riccardo Valentini
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy
| | - Michiel van der Molen
- Meteorology and Air Quality group, Wageningen University, 6500, Wageningen, The Netherlands
| | - Eva van Gorsel
- Fenner School of Environment and Society, Australian National University Canberra, Canberra, ACT, 2600, Australia
| | - Ko van Huissteden
- Department of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
| | - Andrej Varlagin
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow, 119071, Russia
| | | | - Timo Vesala
- Institute for Atmosphere and Earth System Research/Physics, University of Helsinki, Helsinki, 00560, Finland
| | - Caroline Vincke
- Earth and Life Institute, Université Catholique de Louvain, Louvain-la-Neuve, 1348, Belgium
| | - Domenico Vitale
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy
| | - Natalia Vygodskaya
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow, 119071, Russia
| | - Jeffrey P Walker
- Department of Civil Engineering, Monash University, Clayton, 3800, Australia
| | - Elizabeth Walter-Shea
- School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA
| | - Huimin Wang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Robin Weber
- ESPM, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Sebastian Westermann
- Instituto de Clima y Agua, Instituto Nacional de Tecnologia Agropecuaria (INTA), Buenos Aires, 1686, Argentina
| | - Christian Wille
- Remote Sensing and Geoinformatics, GFZ German Research Centre for Geosciences, Potsdam, 14473, Germany
| | - Steven Wofsy
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA.,Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, 02138, USA
| | - Georg Wohlfahrt
- Department of Ecology, University of Innsbruck, Innsbruck, 6020, Austria
| | - Sebastian Wolf
- Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
| | - William Woodgate
- CSIRO Land and Water, Canberra, 2601, Australia.,School of Earth and Environmental Sciences, The University of Queensland, St Lucia, 4072, Australia
| | - Yuelin Li
- South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China
| | - Roberto Zampedri
- Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige, 38010, Italy
| | - Junhui Zhang
- Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China
| | - Guoyi Zhou
- College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Donatella Zona
- Global Change Research Group, Dept. Biology, San Diego State University, San Diego, CA, 92182, USA.,Department of Animal and Plant Sciences, University of Sheffield, Sheffield, S102TN, United Kingdom
| | - Deb Agarwal
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Sebastien Biraud
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Margaret Torn
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Dario Papale
- DIBAF, University of Tuscia, Viterbo, 01100, Italy. .,Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy.
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Hao W, Liu HZ, Zhou LG, Sun YJ, Su H, Ni JQ, He T, Shi P, Wang X. MiR-122-3p regulates the osteogenic differentiation of mouse adipose-derived stem cells via Wnt/β catenin signaling pathway. Eur Rev Med Pharmacol Sci 2020; 23:3892-3898. [PMID: 31115017 DOI: 10.26355/eurrev_201905_17817] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE To explore the regulatory mechanism of micro-ribonucleic acid (miR)-122-3p in the osteogenic differentiation of mouse adipose-derived stem cells (mADSCs). MATERIALS AND METHODS The regulatory mechanism of miR-122-3p in the osteogenic differentiation of mesenchymal stem cells was investigated through its overexpression and knockdown. RESULTS The overexpression of miR-122-3p inhibited the osteogenic differentiation of mADSCs. On the contrary, its knockdown promoted the osteogenic differentiation of mADSCs. The further study on the molecular mechanism of miR-122-3p regulating mADSCs' osteogenic differentiation showed that the overexpression of miR-122-3p could activate the Wingless and int-1 (WNT)/β-catenin signaling pathway, but the knockdown of miR-122-3p could repress this signaling pathway. CONCLUSIONS MiR-122-3p influences the osteogenic differentiation of mADSCs by modulating the WNT/β-catenin signaling pathway.
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Affiliation(s)
- W Hao
- Department of Orthopaedics and Traumatology, Yantai Yuhuangding Hospital, Yantai, China.
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34
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Ge M, Chen J, Zhu Z, Shi P, Yin L, Xia L. Wrist ROM measurements using smartphone photography: Reliability and validity. Hand Surgery and Rehabilitation 2020; 39:261-264. [DOI: 10.1016/j.hansur.2020.02.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 11/19/2019] [Accepted: 02/25/2020] [Indexed: 10/24/2022]
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35
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Sun J, Liu M, Fu B, Kemp D, Zhao W, Liu G, Han G, Wilkes A, Lu X, Chen Y, Cheng G, Zhou T, Hou G, Zhan T, Peng F, Shang H, Xu M, Shi P, He Y, Li M, Wang J, Tsunekawa A, Zhou H, Liu Y, Li Y, Liu S. Reconsidering the efficiency of grazing exclusion using fences on the Tibetan Plateau. Sci Bull (Beijing) 2020; 65:1405-1414. [PMID: 36659220 DOI: 10.1016/j.scib.2020.04.035] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 04/12/2020] [Accepted: 04/13/2020] [Indexed: 01/21/2023]
Abstract
Grazing exclusion using fences is a key policy being applied by the Chinese government to rehabilitate degraded grasslands on the Tibetan Plateau (TP) and elsewhere. However, there is a limited understanding of the effects of grazing exclusion on alpine ecosystem functions and services and its impacts on herders' livelihoods. Our meta-analyses and questionnaire-based surveys revealed that grazing exclusion with fences was effective in promoting aboveground vegetation growth for up to four years in degraded alpine meadows and for up to eight years in the alpine steppes of the TP. Longer-term fencing did not bring any ecological and economic benefits. We also found that fencing hindered wildlife movement, increased grazing pressure in unfenced areas, lowered the satisfaction of herders, and rendered substantial financial costs to both regional and national governments. We recommend that traditional free grazing should be encouraged if applicable, short-term fencing (for 4-8 years) should be adopted in severely degraded grasslands, and fencing should be avoided in key wildlife habitat areas, especially the protected large mammal species.
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Affiliation(s)
- Jian Sun
- Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Miao Liu
- Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Bojie Fu
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - David Kemp
- Agricultural Systems Charles Sturt University, Orange, NSW 2800, Australia
| | - Wenwu Zhao
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Guohua Liu
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
| | - Guodong Han
- Key Laboratory of Grassland Resources of the Ministry of Education, Key Laboratory of Forage Cultivation, Processing and High Efficient Utilization of the Ministry of Agriculture and Rural Affairs, Inner Mongolia Key Laboratory of Grassland Management and Utilization, College of Grassland, Resources and Environment, Inner Mongolia Agricultural University, Hohhot 010011, China
| | - Andreas Wilkes
- Values for Development Ltd, Bury St Edmunds, IP33 3EQ, UK
| | - Xuyang Lu
- Institute of Mountain Hazard and Environment, Chinese Academy of Sciences, Chengdu 610041, China
| | - Youchao Chen
- Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, China
| | - Genwei Cheng
- Institute of Mountain Hazard and Environment, Chinese Academy of Sciences, Chengdu 610041, China
| | - Tiancai Zhou
- Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Ge Hou
- Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Tianyu Zhan
- Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Fei Peng
- Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
| | - Hua Shang
- Department of Ecology, Evolution, and Natural Resources, School Environmental and Biological Sciences, Rutgers University, New Brunswick, NJ 08901, USA
| | - Ming Xu
- Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Department of Ecology, Evolution, and Natural Resources, School Environmental and Biological Sciences, Rutgers University, New Brunswick, NJ 08901, USA; The College of Environment and Planning of Henan University, Kaifeng 475004, China
| | - Peili Shi
- Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yongtao He
- Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Meng Li
- Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Jinniu Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, China
| | - Atsushi Tsunekawa
- Arid Land Research Center, Tottori University, Tottori, 6800001, Japan
| | - Huakun Zhou
- Key Laboratory of Restoration Ecology for Cold Regions in Qinghai, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810008, China
| | - Yu Liu
- Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yurui Li
- Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Shiliang Liu
- School of Environment, Beijing Normal University, Beijing 100875, China
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36
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Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah YW, Poindexter C, Chen J, Elbashandy A, Humphrey M, Isaac P, Polidori D, Reichstein M, Ribeca A, van Ingen C, Vuichard N, Zhang L, Amiro B, Ammann C, Arain MA, Ardö J, Arkebauer T, Arndt SK, Arriga N, Aubinet M, Aurela M, Baldocchi D, Barr A, Beamesderfer E, Marchesini LB, Bergeron O, Beringer J, Bernhofer C, Berveiller D, Billesbach D, Black TA, Blanken PD, Bohrer G, Boike J, Bolstad PV, Bonal D, Bonnefond JM, Bowling DR, Bracho R, Brodeur J, Brümmer C, Buchmann N, Burban B, Burns SP, Buysse P, Cale P, Cavagna M, Cellier P, Chen S, Chini I, Christensen TR, Cleverly J, Collalti A, Consalvo C, Cook BD, Cook D, Coursolle C, Cremonese E, Curtis PS, D'Andrea E, da Rocha H, Dai X, Davis KJ, Cinti BD, Grandcourt AD, Ligne AD, De Oliveira RC, Delpierre N, Desai AR, Di Bella CM, Tommasi PD, Dolman H, Domingo F, Dong G, Dore S, Duce P, Dufrêne E, Dunn A, Dušek J, Eamus D, Eichelmann U, ElKhidir HAM, Eugster W, Ewenz CM, Ewers B, Famulari D, Fares S, Feigenwinter I, Feitz A, Fensholt R, Filippa G, Fischer M, Frank J, Galvagno M, Gharun M, Gianelle D, Gielen B, Gioli B, Gitelson A, Goded I, Goeckede M, Goldstein AH, Gough CM, Goulden ML, Graf A, Griebel A, Gruening C, Grünwald T, Hammerle A, Han S, Han X, Hansen BU, Hanson C, Hatakka J, He Y, Hehn M, Heinesch B, Hinko-Najera N, Hörtnagl L, Hutley L, Ibrom A, Ikawa H, Jackowicz-Korczynski M, Janouš D, Jans W, Jassal R, Jiang S, Kato T, Khomik M, Klatt J, Knohl A, Knox S, Kobayashi H, Koerber G, Kolle O, Kosugi Y, Kotani A, Kowalski A, Kruijt B, Kurbatova J, Kutsch WL, Kwon H, Launiainen S, Laurila T, Law B, Leuning R, Li Y, Liddell M, Limousin JM, Lion M, Liska AJ, Lohila A, López-Ballesteros A, López-Blanco E, Loubet B, Loustau D, Lucas-Moffat A, Lüers J, Ma S, Macfarlane C, Magliulo V, Maier R, Mammarella I, Manca G, Marcolla B, Margolis HA, Marras S, Massman W, Mastepanov M, Matamala R, Matthes JH, Mazzenga F, McCaughey H, McHugh I, McMillan AMS, Merbold L, Meyer W, Meyers T, Miller SD, Minerbi S, Moderow U, Monson RK, Montagnani L, Moore CE, Moors E, Moreaux V, Moureaux C, Munger JW, Nakai T, Neirynck J, Nesic Z, Nicolini G, Noormets A, Northwood M, Nosetto M, Nouvellon Y, Novick K, Oechel W, Olesen JE, Ourcival JM, Papuga SA, Parmentier FJ, Paul-Limoges E, Pavelka M, Peichl M, Pendall E, Phillips RP, Pilegaard K, Pirk N, Posse G, Powell T, Prasse H, Prober SM, Rambal S, Rannik Ü, Raz-Yaseef N, Rebmann C, Reed D, Dios VRD, Restrepo-Coupe N, Reverter BR, Roland M, Sabbatini S, Sachs T, Saleska SR, Sánchez-Cañete EP, Sanchez-Mejia ZM, Schmid HP, Schmidt M, Schneider K, Schrader F, Schroder I, Scott RL, Sedlák P, Serrano-Ortíz P, Shao C, Shi P, Shironya I, Siebicke L, Šigut L, Silberstein R, Sirca C, Spano D, Steinbrecher R, Stevens RM, Sturtevant C, Suyker A, Tagesson T, Takanashi S, Tang Y, Tapper N, Thom J, Tomassucci M, Tuovinen JP, Urbanski S, Valentini R, van der Molen M, van Gorsel E, van Huissteden K, Varlagin A, Verfaillie J, Vesala T, Vincke C, Vitale D, Vygodskaya N, Walker JP, Walter-Shea E, Wang H, Weber R, Westermann S, Wille C, Wofsy S, Wohlfahrt G, Wolf S, Woodgate W, Li Y, Zampedri R, Zhang J, Zhou G, Zona D, Agarwal D, Biraud S, Torn M, Papale D. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Sci Data 2020; 7:225. [PMID: 32647314 PMCID: PMC7347557 DOI: 10.1038/s41597-020-0534-3] [Citation(s) in RCA: 173] [Impact Index Per Article: 43.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 05/20/2020] [Indexed: 12/02/2022] Open
Abstract
The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible. Measurement(s) | net ecosystem exchange • carbon dioxide • water • energy | Technology Type(s) | eddy covariance • measurement device | Sample Characteristic - Environment | terrestrial biome • atmosphere | Sample Characteristic - Location | Earth (planet) |
Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12295910
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Affiliation(s)
- Gilberto Pastorello
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
| | - Carlo Trotta
- DIBAF, University of Tuscia, Viterbo, 01100, Italy
| | - Eleonora Canfora
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy
| | - Housen Chu
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Danielle Christianson
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - You-Wei Cheah
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Cristina Poindexter
- Department of Civil Engineering, California State University, Sacramento, CA, 95819, USA
| | - Jiquan Chen
- Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI, 48823, USA
| | - Abdelrahman Elbashandy
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Marty Humphrey
- Department of Computer Science, University of Virginia, Charlottesville, VA, 22904, USA
| | - Peter Isaac
- TERN Ecosystem Processes, Menzies Creek, VIC3159, Australia
| | - Diego Polidori
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy
| | | | - Alessio Ribeca
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy
| | - Catharine van Ingen
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Nicolas Vuichard
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA CNRS, UVSQ UPSACLAY, Gif sur Yvette, 91190, France
| | - Leiming Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Brian Amiro
- Department of Soil Science, University of Manitoba, Winnipeg, MB, R3T2N2, Canada
| | - Christof Ammann
- Department of Agroecology and Environment, Agroscope Research Institute, Zürich, 8046, Switzerland
| | - M Altaf Arain
- School of Geography and Earth Sciences, McMaster University, L8S4K1, Hamilton, ON, Canada
| | - Jonas Ardö
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, 22362, Sweden
| | - Timothy Arkebauer
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA
| | - Stefan K Arndt
- School of Ecosystem and Forest Sciences, The University of Melbourne, Richmond, VIC3121, Australia
| | - Nicola Arriga
- Department of Biology, Research Group PLECO, University of Antwerp, Antwerp, 2610, Belgium.,Joint Research Centre, European Commission, Ispra, 21027, Italy
| | - Marc Aubinet
- TERRA Teaching and Research Center, University of Liege, Gembloux, B-5030, Belgium
| | - Mika Aurela
- Finnish Meteorological Institute, Helsinki, 00560, Finland
| | - Dennis Baldocchi
- ESPM, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Alan Barr
- Global Institute for Water Security, University of Saskatchewan, Saskatoon, SK, S7N3H5, Canada.,Climate Research Division, Environment and Climate Change Canada, Saskatoon, SK, S7N3H5, Canada
| | - Eric Beamesderfer
- School of Geography and Earth Sciences, McMaster University, L8S4K1, Hamilton, ON, Canada
| | - Luca Belelli Marchesini
- Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige, 38010, Italy.,Department of Landscape Design and Sustainable Ecosystems, Agrarian-Technological Institute, RUDN University, Moscow, 117198, Russia
| | - Onil Bergeron
- Direction du marché du carbone, Ministère du Développement durable de l'Environnement et de la Lutte contre les changements climatiques, Québec, QC, G1R5V7, Canada
| | - Jason Beringer
- School of Agriculture and Environment, University of Western Australia, Crawley, 6009, Australia
| | - Christian Bernhofer
- Institute of Hydrology and Meteorology, Technische Universität Dresden, Tharandt, 01737, Germany
| | - Daniel Berveiller
- Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Systématique et Evolution, Orsay, 91405, France
| | - Dave Billesbach
- Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA
| | - Thomas Andrew Black
- Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, V6T1Z4, Canada
| | - Peter D Blanken
- Department of Geography, University of Colorado, Boulder, CO, 80309, USA
| | - Gil Bohrer
- Department of Civil, Environmental & Geodetic Engineering, Ohio State University, Columbus, OH, 43210, USA
| | - Julia Boike
- Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, 14482, Germany.,Geography Department, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Paul V Bolstad
- Forest Resources, University of Minnesota, St Paul, MN, 55108, USA
| | - Damien Bonal
- Université de Lorraine, AgroParisTech, INRAE, UMR Silva, Nancy, 54000, France
| | | | - David R Bowling
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - Rosvel Bracho
- School of Forest Resources and Conservation, University of Florida, Gainesville, FL, 32611, USA
| | - Jason Brodeur
- McMaster University Library, McMaster University, Hamilton, ON, L8S4L6, Canada
| | - Christian Brümmer
- Thünen Institute of Climate-Smart Agriculture, Federal Research Institute of Rural Areas, Forestry and Fisheries, Braunschweig, 38116, Germany
| | - Nina Buchmann
- Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
| | | | - Sean P Burns
- Department of Geography, University of Colorado, Boulder, CO, 80309, USA.,Mesoscale and Microscale Meteorology Laboratory, National Center for Atmospheric Research, Boulder, CO, 80301, USA
| | - Pauline Buysse
- Université Paris-Saclay, INRAE, AgroParisTech, UMR ECOSYS, Thiverval-Grignon, 78850, France
| | - Peter Cale
- Australian Landscape Trust, Renmark, SA5341, Australia
| | - Mauro Cavagna
- Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige, 38010, Italy
| | - Pierre Cellier
- Université Paris-Saclay, INRAE, AgroParisTech, UMR ECOSYS, Thiverval-Grignon, 78850, France
| | - Shiping Chen
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Isaac Chini
- Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige, 38010, Italy
| | - Torben R Christensen
- Department of Bioscience, Arctic Research Center, Aarhus University, Roskilde, 4000, Denmark
| | - James Cleverly
- School of Life Sciences, University of Technology Sydney, Sydney, 2007, Australia.,Terrestrial Ecosystem Research Network TERN, University of Technology, Sydney, 2007, Australia
| | - Alessio Collalti
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Institute for Agricultural and Forestry Systems in the Mediterranean, National Research Council of Italy, Ercolano, 80056, Italy
| | - Claudia Consalvo
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Research Institute on Terrestrial Ecosystems, National Research Council of Italy, Porano, 05010, Italy
| | - Bruce D Cook
- Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, 20771, USA
| | - David Cook
- Environmental Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA
| | - Carole Coursolle
- Canadian Forest Service, Natural Resources Canada, Québec, QC, G1V4C7, Canada.,Centre d'étude de la forêt, Faculté de foresterie, de géographie et de géomatique, Université Laval, Québec, QC, G1V0A6, Canada
| | - Edoardo Cremonese
- Climate Change Unit, Environmental Protection Agency of Aosta Valley, Saint Christophe, 11020, Italy
| | - Peter S Curtis
- Department of Evolution, Ecology, and Organismal Biology, Ohio State University, Columbus, OH, 43210, USA
| | - Ettore D'Andrea
- Institute for Agricultural and Forestry Systems in the Mediterranean, National Research Council of Italy, Ercolano, 80056, Italy
| | - Humberto da Rocha
- Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, SP, 01000-000, Brazil
| | - Xiaoqin Dai
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Kenneth J Davis
- Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Bruno De Cinti
- Institute of Research on Terrestrial Ecosystems, National Research Council of Italy, Montelibretti, 00010, Italy
| | | | - Anne De Ligne
- TERRA Teaching and Research Center, University of Liege, Gembloux, B-5030, Belgium
| | | | - Nicolas Delpierre
- Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Systématique et Evolution, Orsay, 91405, France
| | - Ankur R Desai
- Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Carlos Marcelo Di Bella
- Departamento de Métodos Cuantitativos y Sistemas de Información, Facultad de Agronomía, UBA, Buenos Aires, 1417, Argentina
| | - Paul di Tommasi
- Institute for Agricultural and Forestry Systems in the Mediterranean, National Research Council of Italy, Ercolano, 80056, Italy
| | - Han Dolman
- Department of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
| | - Francisco Domingo
- Desertification and Geoecology Department, Experimental Station of Arid Zones, CSIC, Almería, 04120, Spain
| | - Gang Dong
- School of Life Science, Shanxi University, Taiyuan, 030006, China
| | | | - Pierpaolo Duce
- Institute of BioEconomy, National Research Council of Italy, Sassari, 07100, Italy
| | - Eric Dufrêne
- Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Systématique et Evolution, Orsay, 91405, France
| | - Allison Dunn
- Department of Earth, Environment, and Physics, Worcester State University, Worcester, MA, 01602, USA
| | - Jiří Dušek
- Department of Matter and Energy Fluxes, Global Change Research Institute of the Czech Academy of Sciences, Brno, 60300, Czech Republic
| | - Derek Eamus
- School of Life Sciences, University of Technology Sydney, Sydney, 2007, Australia
| | - Uwe Eichelmann
- Institute of Hydrology and Meteorology, Technische Universität Dresden, Tharandt, 01737, Germany
| | | | - Werner Eugster
- Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
| | - Cacilia M Ewenz
- Airborne Research Australia, TERN Ecosystem Processes Central Node, Parafield, 5106, Australia
| | - Brent Ewers
- Department of Botany, Program in Ecology, University of Wyoming, 1000 E. Univ. Ave, Laramie, WY, 82071, USA
| | - Daniela Famulari
- Institute for Agricultural and Forestry Systems in the Mediterranean, National Research Council of Italy, Ercolano, 80056, Italy
| | - Silvano Fares
- Institute of BioEconomy, National Research Council of Italy, Rome, 00100, Italy.,Research Centre for Forestry and Wood, Council for Agricultural Research and Economics, Rome, 00166, Italy
| | - Iris Feigenwinter
- Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
| | | | - Rasmus Fensholt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, 1350, Denmark
| | - Gianluca Filippa
- Climate Change Unit, Environmental Protection Agency of Aosta Valley, Saint Christophe, 11020, Italy
| | - Marc Fischer
- Energy Analysis & Environmental Impacts Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - John Frank
- USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO, 80526, USA
| | - Marta Galvagno
- Climate Change Unit, Environmental Protection Agency of Aosta Valley, Saint Christophe, 11020, Italy
| | - Mana Gharun
- Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
| | - Damiano Gianelle
- Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige, 38010, Italy
| | - Bert Gielen
- Department of Biology, Research Group PLECO, University of Antwerp, Antwerp, 2610, Belgium
| | - Beniamino Gioli
- Institute of BioEconomy, National Research Council of Italy, Firenze, 50145, Italy
| | - Anatoly Gitelson
- School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA
| | - Ignacio Goded
- Joint Research Centre, European Commission, Ispra, 21027, Italy
| | | | | | - Christopher M Gough
- Department of Biology, Virginia Commonwealth University, Richmond, VA, 23284, USA
| | - Michael L Goulden
- Department of Earth System Science, University of California, Irvine, CA, 92697, USA
| | - Alexander Graf
- Agrosphere (IBG3), Forschungszentrum Jülich, Jülich, 52428, Germany
| | - Anne Griebel
- School of Ecosystem and Forest Sciences, The University of Melbourne, Richmond, VIC3121, Australia
| | | | - Thomas Grünwald
- Institute of Hydrology and Meteorology, Technische Universität Dresden, Tharandt, 01737, Germany
| | - Albin Hammerle
- Department of Ecology, University of Innsbruck, Innsbruck, 6020, Austria
| | - Shijie Han
- International Joint Research Laboratory for Global Change Ecology, School of Life Sciences, Henan University, Kaifeng, 450000, China.,Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China
| | - Xingguo Han
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Birger Ulf Hansen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, 1350, Denmark
| | - Chad Hanson
- Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, 97333, USA
| | - Juha Hatakka
- Finnish Meteorological Institute, Helsinki, 00560, Finland
| | - Yongtao He
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100190, China
| | - Markus Hehn
- Institute of Hydrology and Meteorology, Technische Universität Dresden, Tharandt, 01737, Germany
| | - Bernard Heinesch
- TERRA Teaching and Research Center, University of Liege, Gembloux, B-5030, Belgium
| | - Nina Hinko-Najera
- School of Ecosystem and Forest Sciences, The University of Melbourne, Creswick, VIC3363, Australia
| | - Lukas Hörtnagl
- Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
| | - Lindsay Hutley
- Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, 0909, Australia
| | - Andreas Ibrom
- Department of Environmental Engineering, Technical University of Denmark (DTU), Kongens Lyngby, 2800, Denmark
| | - Hiroki Ikawa
- Institute for Agro-Environmental Sciences, National Agriculture and Food Research Organization, Tsukuba, 305-8604, Japan
| | - Marcin Jackowicz-Korczynski
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, 22362, Sweden.,Department of Bioscience, Arctic Research Center, Aarhus University, Roskilde, 4000, Denmark
| | - Dalibor Janouš
- Department of Matter and Energy Fluxes, Global Change Research Institute of the Czech Academy of Sciences, Brno, 60300, Czech Republic
| | - Wilma Jans
- Wageningen Environmental Research, Wageningen University and Research, Wageningen, 6708PB, The Netherlands
| | - Rachhpal Jassal
- Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, V6T1Z4, Canada
| | - Shicheng Jiang
- Key Laboratory of Vegetation Ecology, Ministry of Education, Northeast Normal University, Changchun, 130024, China
| | - Tomomichi Kato
- Research Faculty of Agriculture, Hokkaido University, Sapporo, 060-8589, Japan.,GI-Core, Hokkaido University, Sapporo, 060-0808, Japan
| | - Myroslava Khomik
- School of Geography and Earth Sciences, McMaster University, L8S4K1, Hamilton, ON, Canada.,Geography and Environmental Management, Waterloo, ON, N2L3G1, Canada
| | - Janina Klatt
- Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, 82467, Germany
| | - Alexander Knohl
- Bioclimatology, University of Goettingen, Goettingen, 37077, Germany.,Centre of Biodiversity and Sustainable Land Use (CBL), University of Goettingen, Goettingen, 37077, Germany
| | - Sara Knox
- Department of Geography, The University of British Columbia, Vancouver, BC, V6T1Z2, Canada
| | - Hideki Kobayashi
- Research Institute for Global Change, Institute of Arctic Climate and Environment Research, Japan Agency for Marine-Earth Science and Technology, Yokoama, 236-0001, Japan
| | - Georgia Koerber
- Biological Sciences, University of Adelaide, Adelaide, SA5064, Australia
| | - Olaf Kolle
- Max Planck Institute for Biogeochemistry, Jena, 03641, Germany
| | - Yoshiko Kosugi
- Graduate School of Agriculture, Kyoto University, Kyoto, 606-8502, Japan
| | - Ayumi Kotani
- Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, 4648601, Japan
| | - Andrew Kowalski
- Department of Applied Physics, University of Granada, Granada, 18071, Spain
| | - Bart Kruijt
- Water systems and Global Change group, Wageningen University, Wageningen, 6500, The Netherlands
| | - Julia Kurbatova
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow, 119071, Russia
| | - Werner L Kutsch
- Head Office, Integrated Carbon Observation System (ICOS ERIC), Helsinki, 00560, Finland
| | - Hyojung Kwon
- Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, 97333, USA
| | | | - Tuomas Laurila
- Finnish Meteorological Institute, Helsinki, 00560, Finland
| | - Bev Law
- Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, 97333, USA
| | | | - Yingnian Li
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810008, China
| | - Michael Liddell
- Centre for Tropical Environmental Sustainability Studies, James Cook University, Cairns, 4878, Australia
| | | | - Marryanna Lion
- Forestry and Environment Division, Forest Research Institute Malaysia (FRIM), Kepong, 52109, Malaysia
| | - Adam J Liska
- Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA
| | - Annalea Lohila
- Finnish Meteorological Institute, Helsinki, 00560, Finland.,Institute for Atmosphere and Earth System Research/Physics, University of Helsinki, Helsinki, 00560, Finland
| | - Ana López-Ballesteros
- Department of Botany, School of Natural Sciences, Trinity College Dublin, Dublin, D02PN40, Ireland
| | - Efrén López-Blanco
- Department of Bioscience, Arctic Research Center, Aarhus University, Roskilde, 4000, Denmark
| | - Benjamin Loubet
- Université Paris-Saclay, INRAE, AgroParisTech, UMR ECOSYS, Thiverval-Grignon, 78850, France
| | - Denis Loustau
- ISPA, Bordeaux Sciences Agro, INRAE, Villenave d'Ornon, 33140, France
| | - Antje Lucas-Moffat
- Thünen Institute of Climate-Smart Agriculture, Federal Research Institute of Rural Areas, Forestry and Fisheries, Braunschweig, 38116, Germany.,German Meteorological Service (DWD), Centre for Agrometeorological Research, Braunschweig, 38116, Germany
| | - Johannes Lüers
- Micrometeorology, University of Bayreuth, Bayreuth, 95440, Germany.,Bayreuth Center of Ecology and Environmental Research, 95448, Bayreuth, Germany
| | - Siyan Ma
- ESPM, University of California Berkeley, Berkeley, CA, 94720, USA
| | | | - Vincenzo Magliulo
- Institute for Agricultural and Forestry Systems in the Mediterranean, National Research Council of Italy, Ercolano, 80056, Italy
| | - Regine Maier
- Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
| | - Ivan Mammarella
- Institute for Atmosphere and Earth System Research/Physics, University of Helsinki, Helsinki, 00560, Finland
| | - Giovanni Manca
- Joint Research Centre, European Commission, Ispra, 21027, Italy
| | - Barbara Marcolla
- Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige, 38010, Italy
| | - Hank A Margolis
- Centre d'étude de la forêt, Faculté de foresterie, de géographie et de géomatique, Université Laval, Québec, QC, G1V0A6, Canada
| | - Serena Marras
- Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy.,Department of Agriculture, University of Sassari, Sassari, 07100, Italy
| | - William Massman
- USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO, 80526, USA
| | - Mikhail Mastepanov
- Department of Bioscience, Arctic Research Center, Aarhus University, Roskilde, 4000, Denmark.,Oulanka research station, University of Oulu, Kuusamo, 93900, Finland
| | - Roser Matamala
- Environmental Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA
| | | | - Francesco Mazzenga
- Research Institute on Terrestrial Ecosystems, National Research Council of Italy, Monterotondo Scalo, 00015, Italy
| | - Harry McCaughey
- Department of Geography and Planning, Queen's University, Kingston, ON, K7L3N6, Canada
| | - Ian McHugh
- School of Ecosystem and Forest Sciences, The University of Melbourne, Richmond, VIC3121, Australia
| | - Andrew M S McMillan
- Environmental Analytics NZ, Ltd. Raumati South, Paraparaumu, 5032, New Zealand
| | - Lutz Merbold
- Mazingira Centre, International Livestock Research Institute (ILRI), Nairobi, 00100, Kenya
| | - Wayne Meyer
- Biological Sciences, University of Adelaide, Adelaide, SA5064, Australia
| | - Tilden Meyers
- NOAA/OAR/Air Resources Laboratory, 325 Broadway, Boulder, CO, 80303, USA
| | - Scott D Miller
- Atmospheric Sciences Research Center, State University of New York at Albany, Albany, NY, 12203, USA
| | | | - Uta Moderow
- Institute of Hydrology and Meteorology, Technische Universität Dresden, Tharandt, 01737, Germany
| | - Russell K Monson
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA
| | - Leonardo Montagnani
- Forest Department of South Tyrol, Bolzano, 39100, Italy.,Faculty of Science and Technology, Free University of Bolzano, Bolzano, 39100, Italy
| | - Caitlin E Moore
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Eddy Moors
- IHE Delft, Delft, 2611, The Netherlands.,Faculty of Science, VU Amsterdam, Amsterdam, 1081, The Netherlands
| | - Virginie Moreaux
- ISPA, Bordeaux Sciences Agro, INRAE, Villenave d'Ornon, 33140, France.,University Grenoble Alpes, IRD, CNRS, IGE, Grenoble, 38000, France
| | - Christine Moureaux
- TERRA Teaching and Research Center, University of Liege, Gembloux, B-5030, Belgium
| | - J William Munger
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA.,Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, 02138, USA
| | - Taro Nakai
- School of Forestry and Resource Conservation, National Taiwan University, Taipei, 0617, Taiwan.,International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK, 99775, USA
| | - Johan Neirynck
- Environment and Climate, Research Institute for Nature and Forest, Geraardsbergen, 9500, Belgium
| | - Zoran Nesic
- Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, V6T1Z4, Canada
| | - Giacomo Nicolini
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy
| | - Asko Noormets
- Department of Ecosystem Science and Management, Texas A&M University, College Station, TX, 77843, USA
| | - Matthew Northwood
- Research Institute for the Environment and Livelihoods, Charles Darwin University, Casuarina, 0810, Australia
| | - Marcelo Nosetto
- Grupo de Estudios Ambientales, Instituto de Matemática Aplicada San Luis (UNSL & CONICET), San Luis, D5700HHW, Argentina.,Facultad de Ciencias Agropecuarias (UNER), Oro Verde, 3100, Argentina
| | - Yann Nouvellon
- UMR Eco&Sols, CIRAD, Montpellier, 34060, France.,Eco&Sols, Univ Montpellier-CIRAD-INRA-IRD-Montpellier SupAgro, Montpellier, 34060, France
| | - Kimberly Novick
- O'Neill School of Public and Environmental Affairs, Indiana University Bloomington, Bloomington, IN, 47405, USA
| | - Walter Oechel
- Global Change Research Group, Dept. Biology, San Diego State University, San Diego, CA, 92182, USA.,Department of Geography, College of Life and Environmental Sciences, University of Exeter, Exeter, EX44RJ, United Kingdom
| | - Jørgen Eivind Olesen
- Department of Agroecology, Aarhus University, Tjele, 8830, Denmark.,iCLIMATE, Aarhus University, Tjele, 8830, Denmark
| | | | - Shirley A Papuga
- Department of Geology, Wayne State University, Detroit, MI, 48202, USA
| | - Frans-Jan Parmentier
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, 22362, Sweden.,Department of Geosciences, University of Oslo, Oslo, 0315, Norway
| | | | - Marian Pavelka
- Department of Matter and Energy Fluxes, Global Change Research Institute of the Czech Academy of Sciences, Brno, 60300, Czech Republic
| | - Matthias Peichl
- Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Umeå, 90183, Sweden
| | - Elise Pendall
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, 2751, Australia
| | - Richard P Phillips
- Department of Biology, Indiana University Bloomington, Bloomington, IN, 47401, USA
| | - Kim Pilegaard
- Department of Environmental Engineering, Technical University of Denmark (DTU), Kongens Lyngby, 2800, Denmark
| | - Norbert Pirk
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, 22362, Sweden.,CSIRO Land and Water, Wembley, 6913, Australia
| | - Gabriela Posse
- Instituto de Clima y Agua, Instituto Nacional de Tecnologia Agropecuaria (INTA), Buenos Aires, 1686, Argentina
| | - Thomas Powell
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Heiko Prasse
- Institute of Hydrology and Meteorology, Technische Universität Dresden, Tharandt, 01737, Germany
| | | | - Serge Rambal
- CEFE, CNRS, Univ Montpellier, Montpellier, 34293, France
| | - Üllar Rannik
- Institute for Atmosphere and Earth System Research/Physics, University of Helsinki, Helsinki, 00560, Finland
| | - Naama Raz-Yaseef
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Corinna Rebmann
- Department Computational Hydrosystems, Helmholtz Centre for Environmental Research UFZ, Leipzig, 04318, Germany
| | - David Reed
- Center for Global Change & Earth Observations, Michigan State University, East Lansing, MI, 48823, USA
| | - Victor Resco de Dios
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, 2751, Australia.,School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang, 621010, China
| | - Natalia Restrepo-Coupe
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA
| | - Borja R Reverter
- Departamento de Química e Física, Universidade Federal da Paraiba, Areia, PB, 58397-000, Brazil
| | - Marilyn Roland
- Department of Biology, Research Group PLECO, University of Antwerp, Antwerp, 2610, Belgium
| | | | - Torsten Sachs
- Remote Sensing and Geoinformatics, GFZ German Research Centre for Geosciences, Potsdam, 14473, Germany
| | - Scott R Saleska
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA
| | - Enrique P Sánchez-Cañete
- Department of Applied Physics, University of Granada, Granada, 18071, Spain.,Andalusian Institute for Earth System Research (CEAMA-IISTA), Granada, 18006, Spain
| | - Zulia M Sanchez-Mejia
- Ciencias del Agua y Medioambiente, Instituto Tecnológico de Sonora, Ciudad Obregón, 85000, Mexico
| | - Hans Peter Schmid
- Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, 82467, Germany
| | - Marius Schmidt
- Agrosphere (IBG3), Forschungszentrum Jülich, Jülich, 52428, Germany
| | - Karl Schneider
- Geographical Institute, University of Cologne, Cologne, 50923, Germany
| | - Frederik Schrader
- Thünen Institute of Climate-Smart Agriculture, Federal Research Institute of Rural Areas, Forestry and Fisheries, Braunschweig, 38116, Germany
| | - Ivan Schroder
- Department of Industry, Innovation and Science, Geoscience Australia, Canberra, 2609, Australia
| | - Russell L Scott
- Southwest Watershed Research Center, USDA-ARS, Tucson, AZ, 85719, USA
| | - Pavel Sedlák
- Department of Matter and Energy Fluxes, Global Change Research Institute of the Czech Academy of Sciences, Brno, 60300, Czech Republic.,Institute of Atmospheric Physics of the Czech Academy of Sciences, Prague, 14100, Czech Republic
| | - Penélope Serrano-Ortíz
- Andalusian Institute for Earth System Research (CEAMA-IISTA), Granada, 18006, Spain.,Department of Ecology, University of Granada, Granada, 18071, Spain
| | - Changliang Shao
- National Hulunber Grassland Ecosystem Observation and Research Station & Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Ivan Shironya
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow, 119071, Russia
| | - Lukas Siebicke
- Bioclimatology, University of Goettingen, Goettingen, 37077, Germany
| | - Ladislav Šigut
- Department of Matter and Energy Fluxes, Global Change Research Institute of the Czech Academy of Sciences, Brno, 60300, Czech Republic
| | - Richard Silberstein
- School of Agriculture and Environment, University of Western Australia, Crawley, 6009, Australia.,School of Science, Edith Cowan University, Joondalup, 6027, Australia
| | - Costantino Sirca
- Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy.,Department of Agriculture, University of Sassari, Sassari, 07100, Italy
| | - Donatella Spano
- Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy.,Department of Agriculture, University of Sassari, Sassari, 07100, Italy
| | - Rainer Steinbrecher
- Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, 82467, Germany
| | | | - Cove Sturtevant
- National Ecological Observatory Network Program, Boulder, CO, 80301, USA
| | - Andy Suyker
- School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA
| | - Torbern Tagesson
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, 22362, Sweden.,Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, 1350, Denmark
| | - Satoru Takanashi
- Kansai Research Center, Forestry and Forest Products Research Institute, Kyoto, 612-0855, Japan
| | - Yanhong Tang
- College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Nigel Tapper
- School of Earth, Atmosphere and Environment, Monash University, Clayton, 3800, Australia
| | - Jonathan Thom
- Space Science and Engineering Center, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Michele Tomassucci
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Terrasystem srl, Viterbo, 01100, Italy
| | | | - Shawn Urbanski
- USDA Forest Service, Rocky Mountain Research Station, Missoula, MT, 59808, USA
| | - Riccardo Valentini
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy
| | - Michiel van der Molen
- Meteorology and Air Quality group, Wageningen University, 6500, Wageningen, The Netherlands
| | - Eva van Gorsel
- Fenner School of Environment and Society, Australian National University Canberra, Canberra, ACT, 2600, Australia
| | - Ko van Huissteden
- Department of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
| | - Andrej Varlagin
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow, 119071, Russia
| | | | - Timo Vesala
- Institute for Atmosphere and Earth System Research/Physics, University of Helsinki, Helsinki, 00560, Finland
| | - Caroline Vincke
- Earth and Life Institute, Université Catholique de Louvain, Louvain, 1348, Belgium
| | - Domenico Vitale
- DIBAF, University of Tuscia, Viterbo, 01100, Italy.,Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy
| | - Natalia Vygodskaya
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow, 119071, Russia
| | - Jeffrey P Walker
- Department of Civil Engineering, Monash University, Clayton, 3800, Australia
| | - Elizabeth Walter-Shea
- School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA
| | - Huimin Wang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Robin Weber
- ESPM, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Sebastian Westermann
- Instituto de Clima y Agua, Instituto Nacional de Tecnologia Agropecuaria (INTA), Buenos Aires, 1686, Argentina
| | - Christian Wille
- Remote Sensing and Geoinformatics, GFZ German Research Centre for Geosciences, Potsdam, 14473, Germany
| | - Steven Wofsy
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA.,Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, 02138, USA
| | - Georg Wohlfahrt
- Department of Ecology, University of Innsbruck, Innsbruck, 6020, Austria
| | - Sebastian Wolf
- Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland
| | - William Woodgate
- CSIRO Land and Water, Canberra, 2601, Australia.,School of Earth and Environmental Sciences, The University of Queensland, St Lucia, 4072, Australia
| | - Yuelin Li
- South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China
| | - Roberto Zampedri
- Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige, 38010, Italy
| | - Junhui Zhang
- Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China
| | - Guoyi Zhou
- College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Donatella Zona
- Global Change Research Group, Dept. Biology, San Diego State University, San Diego, CA, 92182, USA.,Department of Animal and Plant Sciences, University of Sheffield, Sheffield, S102TN, United Kingdom
| | - Deb Agarwal
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Sebastien Biraud
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Margaret Torn
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Dario Papale
- DIBAF, University of Tuscia, Viterbo, 01100, Italy. .,Euro-Mediterranean Centre on Climate Change Foundation (CMCC), Lecce, 73100, Italy.
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Li CC, Shi P, Du LP, Yuan XC. Mapping the near-field spin angular momenta in the structured surface plasmon polariton field. Nanoscale 2020; 12:13674-13679. [PMID: 32573606 DOI: 10.1039/d0nr00618a] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Optical spin angular momenta in a confined electromagnetic field exhibit a remarkable difference with their free space counterparts; in particular, the optical transverse spin that is locked with the energy propagating direction lays the foundation for many intriguing physical effects such as unidirectional transportation, quantum spin Hall effects, photonic Skyrmions, etc. In order to investigate the underlying physics behind the spin-orbit interactions as well as to develop the optical spin-based applications, it is crucial to uncover the spin texture in a confined field, yet it faces challenges due to their chiral and near-field vectorial features. Here, we propose a scanning imaging technique which can map the near-field distributions of the optical spin angular momenta with an achiral dielectric nanosphere. The spin angular momentum component normal to the interface can be uncovered experimentally by employing the proposed scanning imaging technique and the three-dimensional spin vector can be reconstructed theoretically with the experimental results. The experiment is demonstrated on the example of surface plasmon polaritons excited with various vector vortex beams under a tight-focusing configuration, where the spin-orbit interaction emerges clearly. The proposed method, which can be utilized to reconstruct the photonic Skyrmion and other photonic topological structures, is straightforward and of high precision, and hence it is expected to be valuable for the study of near-field spin optics and topological photonics.
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Affiliation(s)
- C C Li
- Nanophotonics Research Center, Shenzhen Key Laboratory of Micro-Scale Optical Information Technology & Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, China.
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Abstract
MicroRNAs (miRNAs) have been demonstrated to have promoting or inhibiting effects on the tumorigenesis of multiple cancers, including ovarian cancer (OC), by regulating its downstream target genes. In the presented experiment, our aim was to explore the role of miR-543 in OC cell proliferation and invasion. Results of quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot revealed that miR-543 have lower expression levels, while Twist homolog 1 (TWIST1) was expressed with higher levels in OC tissues and cells. Furthermore, the effects of abnormal miR-543 expression in OC cell proliferation and invasion were detected by CCK-8 and Transwell assay. According to luciferase reporter assay results, TWIST1 was identified as a downstream target of miR-543 in OC, and a negative correlation was observed between TWIST1 and miR-543 expression by Spearman's correlation analysis in OC tissues. In addition, TWIST1 may reverse the miR-543 suppression effect on OC cell proliferation and invasion. To sum up, miR-543 may promote OC cell proliferation and invasion by targeting TWIST1.
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Affiliation(s)
- Q Yu
- Women Health Care Department, Zhangqiu Maternity and Child Care Hospital, Jinan China
| | - Z Zhang
- Emergency Department, Jinan Zhangqiu District Hospital of TCM, Jinan, China
| | - B He
- Jinan Li Cheng District Maternal and Child Health and Family Planning Service Centre, Jinan, China
| | - H Wang
- Infectious Disease Department, the People's Hospital of Zhangqiu Area, Jinan, China
| | - P Shi
- No 1 Department of Cardiology, the People's Hospital of Zhangqiu Area, Jinan, China
| | - Y Li
- Interventional Vascular Department, the People's Hospital of Zhangqiu Area, Jinan, China
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Zong N, Song M, Zhao G, Shi P. Nitrogen economy of alpine plants on the north Tibetan Plateau: Nitrogen conservation by resorption rather than open sources through biological symbiotic fixation. Ecol Evol 2020; 10:2051-2061. [PMID: 32128137 PMCID: PMC7042762 DOI: 10.1002/ece3.6038] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Revised: 12/21/2019] [Accepted: 12/31/2019] [Indexed: 11/29/2022] Open
Abstract
Nitrogen (N) is one of the most important factors limiting plant productivity, and N fixation by legume species is an important source of N input into ecosystems. Meanwhile, N resorption from senescent plant tissues conserves nutrients taken up in the current season, which may alleviate ecosystem N limitation. N fixation was assessed by the 15N dilution technique in four types of alpine grasslands along the precipitation and soil nutrient gradients. The N resorption efficiency (NRE) was also measured in these alpine grasslands. The aboveground biomass in the alpine meadow was 4-6 times higher than in the alpine meadow steppe, alpine steppe, and alpine desert steppe. However, the proportion of legume species to community biomass in the alpine steppe and the alpine desert steppe was significantly higher than the proportion in the alpine meadow. N fixation by the legume plants in the alpine meadow was 0.236 g N/m2, which was significantly higher than N fixation in other alpine grasslands (0.041 to 0.089 g N/m2). The NRE in the alpine meadows was lower than in the other three alpine grasslands. Both the aboveground biomass and N fixation of the legume plants showed decreasing trends with the decline of precipitation and soil N gradients from east to west, while the NRE of alpine plants showed increasing trends along the gradients, which indicates that alpine plants enhance the NRE to adapt to the increasing droughts and nutrient-poor environments. The opposite trends of N fixation and NRE along the precipitation and soil nutrient gradients indicate that alpine plants adapt to precipitation and soil nutrient limitation by promoting NRE (conservative nutrient use by alpine plants) rather than biological N fixation (open sources by legume plants) on the north Tibetan Plateau.
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Affiliation(s)
- Ning Zong
- Key Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
| | - Minghua Song
- Key Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
| | - Guangshuai Zhao
- China National Forestry-Grassland Economics and Development Research CenterNational Forestry and Grassland AdministrationBeijingChina
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijingChina
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Zhang ZL, Huang QB, Zhang Y, Shi P, Sang XG. [Clinical efficacy of damage control orthopaedics in treatment of patients with severe traumatic brain injury combined with limb fracture]. Zhonghua Yi Xue Za Zhi 2020; 99:3797-3802. [PMID: 31874517 DOI: 10.3760/cma.j.issn.0376-2491.2019.48.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To explore the clinical efficacy of damage control orthopaedics in treatment of patients with severe traumatic brain injury combined with limb fracture. Methods: Total 149 patients with sTBI combined with limb fracture treated in Emergency Surgery Department of Shandong University Qilu Hospital from January, 2011 to December, 2018 were collected. Patients that were treated with immediate definitive fixation before March 31st, 2013 were included into the routine treatment group (group A, 47 cases), and that were treated with damage control orthopaedics (DCO) after April 1st, 2013 were included into the DCO group (group B, 102 cases). The clinical data during hospitalization and prognosis 3 months after injury was analyzed retrospectively. Then according to the risk of postoperative ICP increase, the two groups were divided into low risk subgroup and high risk subgroup. The postoperative ICP, length of stay and GOS score were statistically analyzed. Results: There were no statistically significant differences in sex, age, preoperative GCS score, imaging type of lesion and initial intraoperative ICP between the two groups. The postoperative ICP and incidence of coagulation dysfunction were significantly higher in group A [(17.1±4.6) mmHg, 29.8%] than that in group B[(15.0±4.3) mmHg, 13.7%] separately(P<0.05), and there was no significant difference of length of stay and GOS score between the two groups (P=0.475 and 0.097, respectively). As for the subgroup with low risk of postoperative ICP increase, there was no significant difference in postoperative ICP and GOS score between group A and B, and the length of stay of group B was significantly longer than that of group A (P<0.05). As for the subgroup with high risk of postoperative ICP increase, there was no significant difference in the length of stay between group A and B (P=0.667), and for group A the postoperative ICP was higher and GOS score was lower than that of group B (P<0.05). Conclusions: For patients with sTBI combined with limb fracture, the application of DCO should be based on the severity of traumatic brain injury. For patients with high risk of postoperative ICP increase, DCO can significantly improve the prognosis of patients.
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Affiliation(s)
- Z L Zhang
- Department of Emergency Neurosurgery, Qilu Hospital of Shandong University, Jinan 250012,China
| | - Q B Huang
- Department of Emergency Neurosurgery, Qilu Hospital of Shandong University, Jinan 250012,China
| | - Y Zhang
- Department of Emergency Neurosurgery, Qilu Hospital of Shandong University, Jinan 250012,China
| | - P Shi
- Department of Emergency Neurosurgery, Qilu Hospital of Shandong University, Jinan 250012,China
| | - X G Sang
- Department of Emergency Neurosurgery, Qilu Hospital of Shandong University, Jinan 250012,China
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Niu B, Zeng C, Zhang X, He Y, Shi P, Tian Y, Feng Y, Li M, Wang Z, Wang X, Cao Y. High Below-Ground Productivity Allocation of Alpine Grasslands on the Northern Tibet. Plants (Basel) 2019; 8:plants8120535. [PMID: 31766615 PMCID: PMC6963938 DOI: 10.3390/plants8120535] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 11/15/2019] [Accepted: 11/16/2019] [Indexed: 11/16/2022]
Abstract
The allocation of net primary production (NPP) between above- and belowground components is a key step of ecosystem material cycling and energy flows, which determines many critical parameters, e.g., the fraction of below ground NPP (BNPP) to NPP (fBNPP) and root turnover rates (RTR), in vegetation models. However, direct NPP estimation and partition are scarcely based on field measurements of biomass dynamics in the alpine grasslands on the Northern Tibetan Plateau (NTP). Consequently, these parameters are unverifiable and controversial. Here, we measured above- and belowground biomass dynamics (monthly from May to September each year from 2013 to 2015) to estimate NPP dynamics and allocations in four typical alpine grassland ecosystems, i.e., an alpine meadow, alpine meadow steppe, alpine steppe and alpine desert steppe. We found that NPP and its components, above and below ground NPP (ANPP and BNPP), increased significantly from west to east on the NTP, and ANPP was mainly affected by temperature while BNPP and NPP were mainly affected by precipitation. The bulk of BNPP was generally concentrated in the top 10 cm soil layers in all four alpine grasslands (76.1% ± 9.1%, mean ± SD). Our results showed that fBNPP was significantly different among these four alpine grasslands, with its means in alpine meadow (0.93), alpine desert steppe (0.92) being larger than that in the alpine meadow steppe (0.76) and alpine steppe (0.77). Both temperature and precipitation had significant and positive effects on the fBNPP, while their interaction effects were significantly opposite. RTR decreased with increasing precipitation, but increased with increasing temperature across this ecoregion. Our study illustrated that alpine grasslands on the NTP, especially in the alpine meadow and alpine desert steppe, partitioned an unexpected and greater NPP to below ground than most historical reports across global grasslands, indicating a more critical role of the root carbon pool in carbon cycling in alpine grasslands on the NTP.
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Affiliation(s)
- Ben Niu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (B.N.); (C.Z.); (Y.H.); (P.S.); (Y.T.); (M.L.); (Z.W.); (X.W.); (Y.C.)
| | - Chaoxu Zeng
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (B.N.); (C.Z.); (Y.H.); (P.S.); (Y.T.); (M.L.); (Z.W.); (X.W.); (Y.C.)
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xianzhou Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (B.N.); (C.Z.); (Y.H.); (P.S.); (Y.T.); (M.L.); (Z.W.); (X.W.); (Y.C.)
- Correspondence: ; Tel.: +86-10-6488-6990; Fax: +86-10-6485-4230
| | - Yongtao He
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (B.N.); (C.Z.); (Y.H.); (P.S.); (Y.T.); (M.L.); (Z.W.); (X.W.); (Y.C.)
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (B.N.); (C.Z.); (Y.H.); (P.S.); (Y.T.); (M.L.); (Z.W.); (X.W.); (Y.C.)
| | - Yuan Tian
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (B.N.); (C.Z.); (Y.H.); (P.S.); (Y.T.); (M.L.); (Z.W.); (X.W.); (Y.C.)
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yunfei Feng
- Department of Resource Management, Tangshan Normal University, Tangshan 063000, China;
| | - Meng Li
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (B.N.); (C.Z.); (Y.H.); (P.S.); (Y.T.); (M.L.); (Z.W.); (X.W.); (Y.C.)
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhipeng Wang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (B.N.); (C.Z.); (Y.H.); (P.S.); (Y.T.); (M.L.); (Z.W.); (X.W.); (Y.C.)
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiangtao Wang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (B.N.); (C.Z.); (Y.H.); (P.S.); (Y.T.); (M.L.); (Z.W.); (X.W.); (Y.C.)
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yanan Cao
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; (B.N.); (C.Z.); (Y.H.); (P.S.); (Y.T.); (M.L.); (Z.W.); (X.W.); (Y.C.)
- University of Chinese Academy of Sciences, Beijing 100049, China
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Zong N, Zhao G, Shi P. Different sensitivity and threshold in response to nitrogen addition in four alpine grasslands along a precipitation transect on the Northern Tibetan Plateau. Ecol Evol 2019; 9:9782-9793. [PMID: 31534693 PMCID: PMC6745826 DOI: 10.1002/ece3.5514] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 07/10/2019] [Accepted: 07/10/2019] [Indexed: 11/29/2022] Open
Abstract
The increase in atmospheric nitrogen (N) deposition has resulted in some terrestrial ecological changes. In order to identify the response of sensitive indicators to N input and estimate the sensitivity and saturation thresholds in alpine grasslands, we set up a series of multilevel N addition experiments in four types of alpine grasslands (alpine meadow [AM], alpine meadow-steppe [AMS], alpine steppe [AS], and alpine desert-steppe [ADS]) along with a decreasing precipitation gradient from east to west on the Northern Tibetan Plateau. N addition only had significant effects on species diversity in AMS, while had no effects on the other three alpine grasslands. Aboveground biomass of grasses and overall community in ADS were enhanced with increasing N addition, but such effects did not occur in AS. Legume biomass in ADS and AS showed similar unimodal patterns and exhibited a decreasing tend in AM. Regression fitting showed that the most sensitive functional groups were grasses, and the N saturation thresholds were 103, 115, 136, and 156 kg N hm-2 year-1 in AM, AMS, AS, and ADS, respectively. This suggests that alpine grasslands become more and more insensitive to N input with precipitation decrease. N saturation thresholds also negatively correlated with soil N availability. N sensitivity differences caused by precipitation and nutrient availability suggest that alpine grasslands along the precipitation gradient will respond differently to atmospheric N deposition in the future global change scenario. This different sensitivity should also be taken into consideration when using N fertilization to restore degraded grasslands.
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Affiliation(s)
- Ning Zong
- Lhasa National Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
| | - Guangshuai Zhao
- Lhasa National Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- China National Forestry Economics and Development Research CenterBeijingChina
| | - Peili Shi
- Lhasa National Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
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Zhou LG, Shi P, Sun YJ, Liu HZ, Ni JQ, Wang X. MiR-214-3p delays fracture healing in rats with osteoporotic fracture through inhibiting BMP/Smad signaling pathway. Eur Rev Med Pharmacol Sci 2019; 23:449-455. [PMID: 30720150 DOI: 10.26355/eurrev_201901_16854] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE The purpose of this study was to explore the mechanism of micro-ribonucleic acid (miR)-214-3p in regulating fracture healing in rats with osteoporosis. MATERIALS AND METHODS A total of 30 female Sprague-Dawley rats were selected and randomly divided into 3 groups, including group A [phosphate-buffered saline (PBS), n=10], group B (AntagomiR-NC, n=10), and group C (AntagomiR-214-3p, n=10). All rats underwent ovariectomy, and the osteoporosis rat model was verified by dual-energy X-ray absorptiometry 8 weeks after the operation. Then the osteoporotic fracture was established in rats via a second operation. From the successful modeling until the 6th week, 50 μL PBS (2 nmoL) was intraperitoneally injected in group A, an equal amount of AntagomiR-NC was injected in group B, and an equal amount of AntagomiR-214-3p was injected in group C once a week. At the 6th week, fracture healing of osteoporosis rats was evaluated. At the same time, the expression of miR-214-3p in the three groups was detected via reverse Transcription-Polymerase Chain Reaction (RT-PCR). Furthermore, the protein expressions of bone morphogenetic protein 2 (BMP2) and Smad4 in the three groups were detected via Western blotting (WB). RESULTS After ovariectomy, the bone mineral density in each group was significantly lower than that before ovariectomy, and the differences were statistically significant (p<0.05). Imaging evaluation demonstrated that compared with group A and B, there were significantly more callus tissues in group C. Meanwhile, the fracture line healing was better and blurred, and the internal fixation had no displacement and loosening. RT-PCR results indicated that the expression level of miR-214-3p in group C was significantly lower than that of the other two groups (p<0.05). WB results showed that the protein expression levels of BMP2 and Smad4 in group C were significantly higher than those of group A and group B (p<0.05). CONCLUSIONS MiR-214-3p delays fracture healing in rats with osteoporotic fracture by inhibiting the BMP/Smad signaling pathway.
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Affiliation(s)
- L-G Zhou
- Department of Orthopaedics Traumatology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China.
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Shen Z, Hou D, Zhang P, Wang Y, Zhang Y, Shi P, O'Connor D. Lead-based paint in children's toys sold on China's major online shopping platforms. Environ Pollut 2018; 241:311-318. [PMID: 29843013 DOI: 10.1016/j.envpol.2018.05.078] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2018] [Revised: 05/17/2018] [Accepted: 05/22/2018] [Indexed: 06/08/2023]
Abstract
Lead in paint is a major public health concern and has drawn much attention from international organizations such as the World Health Organization (WHO) and the United Nations Environmental Programme (UNEP). However, there is limited research on lead-based paint, especially its use in toys, which poses an explicit health risk to vulnerable children. The present study sampled 100 different toys purchased from the three largest online shopping platforms in China: JD, Taobao (TB) and Tmall (TM). These selected toys have been sold nearly 3 million times in total, suggesting that they may have reached the dwellings of millions of children. It was found that the toys sold by JD and TM, which are considered organized sellers, had average lead concentrations of 25 mg/kg and 32 mg/kg, respectively, much lower than that of toys sold by unorganized sellers on the TB platform, at 219 mg/kg. Approximately 12% of the toys purchased from TB contained paint with total lead concentrations exceeding China's regulatory standard for paints in toy manufacturing, and nearly 36% of the toys purchased from TB exceeded the equivalent US regulatory standard and EU standard. These results suggest that further action is needed to verify the health and safety standards of toys sold by such unorganized sellers. Moreover, this study found that China's regulatory standard (90 mg/kg) based on soluble lead may underestimate the risk posed by lead in paints, and it is suggested that future regulatory thresholds for lead levels in paints for toy manufacture be based on total rather than soluble lead concentrations. The present study also explored various influencing factors on lead concentration, and found that lead concentrations were related to toy price, age group, color, and sales volume.
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Affiliation(s)
- Zhengtao Shen
- School of Environment, Tsinghua University, Beijing, 100084, China; Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, T6G 2E3, Canada
| | - Deyi Hou
- School of Environment, Tsinghua University, Beijing, 100084, China.
| | - Ping Zhang
- School of Environment, Tsinghua University, Beijing, 100084, China
| | - Yinan Wang
- School of Environment, Tsinghua University, Beijing, 100084, China
| | - Yunhui Zhang
- Department of Engineering, University of Cambridge, Cambridge, CB2 1PZ, United Kingdom
| | - Peili Shi
- School of Environment, Tsinghua University, Beijing, 100084, China
| | - David O'Connor
- School of Environment, Tsinghua University, Beijing, 100084, China
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Zong N, Geng S, Duan C, Shi P, Chai X, Zhang X. The effects of warming and nitrogen addition on ecosystem respiration in a Tibetan alpine meadow: The significance of winter warming. Ecol Evol 2018; 8:10113-10125. [PMID: 30397451 PMCID: PMC6206223 DOI: 10.1002/ece3.4484] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2017] [Revised: 04/02/2018] [Accepted: 07/27/2018] [Indexed: 11/10/2022] Open
Abstract
In recent decades, global warming has become an indisputable fact on the Tibetan Plateau. Alpine ecosystems are very sensitive to global warming, and the impact may depend on the degree of atmospheric nitrogen (N) deposition. The previous studies have paid more attention to year-round warming, but the effect of winter warming has been unstudied. In this study, a manipulative experiment was conducted, consisting of warming and N addition. It was carried out since 2010 in an alpine meadow, and three types of warming treatments were set up: no warming (NW), year-round (YW), and winter warming (WW). Warming significantly increased air and soil temperature, but decreased soil moisture. Under no N addition, YW showed significantly decreased ecosystem respiration (Reco) in 2012, and WW decreased Reco in 2014. Under N addition, neither YW nor WW had significant effects on Reco, indicating that N addition compensated the negative effect of warming on Reco. Annually, YW and WW decreased ecosystem carbon (C) emissions, and the extent of the reduction was even larger under WW. Under no N addition, both YW and WW significantly decreased aboveground biomass. Moreover, especially under no N, YW and WW significantly decreased soil inorganic N. WW also had negative effects on soil microbial biomass C. Structure equation modeling showed that soil moisture was the most important factors controlling Reco, and soil inorganic N content and microbial biomass C could explain 46.6% and 16.8% of the variation of Reco. The findings indicate that soil property changes under warming had substantial effects on ecosystem C efflux. The inhibitory effects of winter warming on ecosystem C efflux were mainly attributed to the decline of soil N and microbial biomass. Thus, the effects of winter warming on ecosystem C emissions in this semiarid alpine meadow are not as serious as expected and largely depend on N deposition.
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Affiliation(s)
- Ning Zong
- Lhasa National Ecological Research StationKey Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
| | - Shoubao Geng
- Lhasa National Ecological Research StationKey Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Cheng Duan
- Lhasa National Ecological Research StationKey Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Peili Shi
- Lhasa National Ecological Research StationKey Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Xi Chai
- Lhasa National Ecological Research StationKey Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Xianzhou Zhang
- Lhasa National Ecological Research StationKey Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
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Shi P, Qiu QS, Zhuang G, Gao L, Zhou YN, Zhou CX. Measurement of density fluctuation propagation direction via the far-forward collective scattering diagnostic based on polarimeter-interferometer. Rev Sci Instrum 2018; 89:10C110. [PMID: 30399876 DOI: 10.1063/1.5038845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2018] [Accepted: 08/06/2018] [Indexed: 06/08/2023]
Abstract
Previously, the 17-channel three-wave polarimeter-interferometer system (POLARIS) on the J-TEXT tokamak has been implemented to measure far-forward collective scattering (FFCS) from electron density fluctuations. Recently, this system has been exploited to measure the propagation direction of density fluctuation. After considering the refraction of the laser probe beam passing through plasma, the ray tracing result shows that the detector of POLARIS may receive asymmetric far-forward scattering beams. Thus, the heterodyne detection of FFCS is available to identify the propagation direction of density fluctuation by resolving the asymmetric scattering spectrum. Experimentally, the transform of the heterodyne scattering spectrum from symmetry to asymmetry has been observed, while the refraction effect becomes strong demonstrating the capacity of measuring the propagation direction of fluctuation. Furthermore, by changing the plasma potential through the use of an applied positive electrode biasing, the reverse of frequency shift for the heterodyne scattering spectrum is identified, confirming the validity of direction discrimination of density fluctuation.
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Affiliation(s)
- P Shi
- International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics, State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Q S Qiu
- International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics, State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - G Zhuang
- International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics, State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - L Gao
- International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics, State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Y N Zhou
- International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics, State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - C X Zhou
- International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics, State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
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Liu Q, Zhao LC, Shi P, Ren FX, Wu YF, Xie GQ. [Correlation of baseline serum interleukin-6, 10 and its ratio with 7-year all-cause mortality in 11 communities of Beijing]. Zhonghua Yi Xue Za Zhi 2018; 98:460-466. [PMID: 29429261 DOI: 10.3760/cma.j.issn.0376-2491.2018.06.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To evaluate whether baseline interleukin-6 (IL-6), interleukin-10 (IL-10) as well as their ratio was associated with overall mortality risk over 7 years of follow-up in 11 communities of Beijing. Methods: Data from a prospective cohort study conducted between 2005 and 2012 in 11 communities of Beijing was analyzed to examine the above associations. Serum IL-6 and IL-10 were analyzed using enzyme-linked immunosorbent assay (ELISA) kits. Follow-up surveys were conducted in 2007, 2010 and 2012 to collect data about participant's survival. Cox regression model was used to estimate the impact of IL-6, IL-10 and their ratio on overall mortality risk. Results: Among 1 539 eligible participants (10 263 total person-years), 77 deaths occurred in 7 years of follow-up. The rates of all-cause death were 4.86, 7.24, and 10.56 per 1 000 person-years (P=0.009) in the first, second, and third tertile of IL-6, respectively. The corresponding age-sex-adjusted hazard ratios (HR) were 1.00, 1.18 (95% CI: 0.64-2.19), and 1.80 (95% CI: 1.01-3.23) and full-adjusted HR were 1.00, 1.17 (95% CI: 0.63-2.19) and 1.87 (95% CI: 1.04-3.36). The corresponding rates of all-cause deaths were not significantly different among three tertiles of IL-10. The age-sex and full-adjusted HR were not significantly different in Cox model. The rates of all-cause death were 4.63, 8.99, and 8.93 per 1 000 person-years (P=0.043) in the first, second, and third tertile of IL-6/IL-10 ratio, respectively. The corresponding age-sex-adjusted HR were 1.00, 1.67 (95% CI: 0.91-3.06), and 1.98 (95% CI: 1.08-3.64) and full-adjusted HR were 1.00, 1.66 (95% CI: 0.90-3.06), and 2.09 (95% CI: 1.13-3.87). Conclusion: High IL-6 and IL-6/IL-10 ratio may be new risk factors to all-cause death. However, IL-10 is not significantly associated with death.
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Affiliation(s)
- Q Liu
- Peking University Clinical Research Institute, Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Beijing 100191, China
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Fu JG, Shi C, Sha D, Shi P, Bao CJ, Ai J. [Genetic characterization of norovirus isolated in an outbreak of gastroenteritis in Jiangsu province]. Zhonghua Liu Xing Bing Xue Za Zhi 2018; 39:72-74. [PMID: 29374900 DOI: 10.3760/cma.j.issn.0254-6450.2018.01.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To analyze the genetic characterization of norovirus isolated in an outbreak of gastroenteritis in Jiangsu province. Methods: Extracted viral RNA from the swab samples of cases of acute gastroenteritis outbreak in Jiangsu province on December 16-27, 2016 was reversely transcribed to cDNA, and partial RNA-dependent RNA polymerase sequence and complete capsid sequence (VP1) were amplified by RT-PCR. Amplification products were sequenced for the analysis of genetic characteristics. Results: Based on sequence alignment, the variant shared a high level of identity with the strain GⅡ.g isolated in Spain and Finland (98.7%) in the RNA-dependent RNA polymerase region, and with the strain GⅡ.1 isolated in American (99.4%) in the VP1. The recombination was determined by using software Simplot, and the breakpoint of recombination was located in the ORF1/2 overlap region at position 5 106 of VP1. The result of amino acids alignment in capsid region showed that there were no mutations in the amino acids of the predicted epitopes and receptor binding site Ⅰ-Ⅲ, but a unique amino acid change was detected at position 132 (N-S). Conclusion: The norovirus isolated in the outbreak of gastroenteritis in Jiangsu province was a rare recombinant norovirus variant GⅡ.g-GⅡ.1.
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Affiliation(s)
- J G Fu
- Key Laboratory of Enteric Pathogenic Microbiology, Ministry of Health, Jiangsu Provincial Center of Disease Control and Prevention, Nanjing 210009, China
| | - C Shi
- Wuxi Prefecture Center for Disease Control and Prevention, Wuxi 214002, China
| | - D Sha
- Wuxi Prefecture Center for Disease Control and Prevention, Wuxi 214002, China
| | - P Shi
- Wuxi Prefecture Center for Disease Control and Prevention, Wuxi 214002, China
| | - C J Bao
- Key Laboratory of Enteric Pathogenic Microbiology, Ministry of Health, Jiangsu Provincial Center of Disease Control and Prevention, Nanjing 210009, China
| | - J Ai
- Key Laboratory of Enteric Pathogenic Microbiology, Ministry of Health, Jiangsu Provincial Center of Disease Control and Prevention, Nanjing 210009, China
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Tu Q, Hao J, Zhou X, Yan L, Dai H, Sun B, Yang D, An S, Lv L, Jiao B, Chen C, Lai R, Shi P, Zhao X. CDKN2B deletion is essential for pancreatic cancer development instead of unmeaningful co-deletion due to juxtaposition to CDKN2A. Oncogene 2017; 37:128-138. [PMID: 28892048 PMCID: PMC5759028 DOI: 10.1038/onc.2017.316] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Revised: 06/07/2017] [Accepted: 07/31/2017] [Indexed: 12/28/2022]
Abstract
Pancreatic cancer is among the deadliest malignancies; however, the genetic events that lead to pancreatic carcinogenesis in adults remain unclear. In vivo models in which these genetic alterations occur in adult animals may more accurately reflect the features of human cancer. In this study, we demonstrate that inactivation of Cdkn2b (p15ink4b) is necessary for induction of pancreatic cancer by oncogenic KRASG12D expression and inactivation of Tp53 and Cdkn2a in adult mouse pancreatic ductal cells (P60 or older). KRASG12D overexpression in these cells activated transforming growth factor-β signaling and expression of CDKN2B, which, along with CDKN2A, led to cellular senescence and protected cells from KRAS-mediated transformation via inhibition of retinoblastoma phosphorylation. These results show a critical role of CDKN2B inactivation in pancreatic carcinogenesis, and provide a useful adult animal model by genetic engineering via lentiviral delivery.
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Affiliation(s)
- Q Tu
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences/Key Laboratory of Bioactive Peptides of Yunnan Province, Kunming Institute of Zoology, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - J Hao
- State Key Laboratory of Genetic Resources and Evolution, Laboratory of Evolutionary and Functional Genomics, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - X Zhou
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences/Key Laboratory of Bioactive Peptides of Yunnan Province, Kunming Institute of Zoology, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - L Yan
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences/Key Laboratory of Bioactive Peptides of Yunnan Province, Kunming Institute of Zoology, Kunming, China.,Kunming Primate Research Center, Chinese Academy of Sciences, Kunming, China
| | - H Dai
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences/Key Laboratory of Bioactive Peptides of Yunnan Province, Kunming Institute of Zoology, Kunming, China
| | - B Sun
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences/Key Laboratory of Bioactive Peptides of Yunnan Province, Kunming Institute of Zoology, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - D Yang
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences/Key Laboratory of Bioactive Peptides of Yunnan Province, Kunming Institute of Zoology, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - S An
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences/Key Laboratory of Bioactive Peptides of Yunnan Province, Kunming Institute of Zoology, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - L Lv
- Kunming Primate Research Center, Chinese Academy of Sciences, Kunming, China
| | - B Jiao
- State Key Laboratory of Genetic Resources and Evolution, Laboratory of Evolutionary and Functional Genomics, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - C Chen
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences/Key Laboratory of Bioactive Peptides of Yunnan Province, Kunming Institute of Zoology, Kunming, China
| | - R Lai
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences/Key Laboratory of Bioactive Peptides of Yunnan Province, Kunming Institute of Zoology, Kunming, China
| | - P Shi
- State Key Laboratory of Genetic Resources and Evolution, Laboratory of Evolutionary and Functional Genomics, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - X Zhao
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences/Key Laboratory of Bioactive Peptides of Yunnan Province, Kunming Institute of Zoology, Kunming, China.,Kunming Primate Research Center, Chinese Academy of Sciences, Kunming, China.,KIZ-SU Joint Laboratory of Animal Model and Drug Development, College of Pharmaceutical Sciences, Soochow University, Suzhou, China
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Zhao G, Shi P, Wu J, Xiong D, Zong N, Zhang X. Foliar nutrient resorption patterns of four functional plants along a precipitation gradient on the Tibetan Changtang Plateau. Ecol Evol 2017; 7:7201-7212. [PMID: 28944011 PMCID: PMC5606856 DOI: 10.1002/ece3.3283] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2016] [Revised: 03/30/2017] [Accepted: 07/03/2017] [Indexed: 12/05/2022] Open
Abstract
Nutrient resorption from senesced leaves as a nutrient conservation strategy is important for plants to adapt to nutrient deficiency, particularly in alpine and arid environment. However, the leaf nutrient resorption patterns of different functional plants across environmental gradient remain unclear. In this study, we conducted a transect survey of 12 communities to address foliar nitrogen (N) and phosphorus (P) resorption strategies of four functional groups along an eastward increasing precipitation gradient in northern Tibetan Changtang Plateau. Soil nutrient availability, leaf nutrient concentration, and N:P ratio in green leaves ([N:P]g) were linearly correlated with precipitation. Nitrogen resorption efficiency decreased, whereas phosphorus resorption efficiency except for sedge increased with increasing precipitation, indicating a greater nutrient conservation in nutrient-poor environment. The surveyed alpine plants except for legume had obviously higher N and P resorption efficiencies than the world mean levels. Legumes had higher N concentrations in green and senesced leaves, but lowest resorption efficiency than nonlegumes. Sedge species had much lower P concentration in senesced leaves but highest P resorption efficiency, suggesting highly competitive P conservation. Leaf nutrient resorption efficiencies of N and P were largely controlled by soil and plant nutrient, and indirectly regulated by precipitation. Nutrient resorption efficiencies were more determined by soil nutrient availability, while resorption proficiencies were more controlled by leaf nutrient and N:P of green leaves. Overall, our results suggest strong internal nutrient cycling through foliar nutrient resorption in the alpine nutrient-poor ecosystems on the Plateau. The patterns of soil nutrient availability and resorption also imply a transit from more N limitation in the west to a more P limitation in the east Changtang. Our findings offer insights into understanding nutrient conservation strategy in the precipitation and its derived soil nutrient availability gradient.
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Affiliation(s)
- Guangshuai Zhao
- Key Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- China National Forestry Economics and Development Research CenterBeijingChina
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- College of Resource and EnvironmentUniversity of Chinese Academy of SciencesBeijingChina
| | - Jianshuang Wu
- Key Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- Functional BiodiversityDahlem Center of Plant ScienceFree University of BerlinBerlinGermany
| | - Dingpeng Xiong
- Key Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
| | - Ning Zong
- Key Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
| | - Xianzhou Zhang
- Key Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
- College of Resource and EnvironmentUniversity of Chinese Academy of SciencesBeijingChina
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