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Huang F, Liu L, Gao J, Yin Z, Zhang Y, Jiang Y, Zuo L, Fang W. Effects of extreme drought events on vegetation activity from the perspectives of meteorological and soil droughts in southwestern China. Sci Total Environ 2023; 903:166562. [PMID: 37633390 DOI: 10.1016/j.scitotenv.2023.166562] [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: 05/08/2023] [Revised: 08/20/2023] [Accepted: 08/23/2023] [Indexed: 08/28/2023]
Abstract
Under climate warming, extreme drought events (EDEs) in southwestern China have become more frequent and severe and have had significant impacts on vegetation growth. Clarifying the influence of soil and meteorological droughts on the vegetation photosynthetic rate (PHR) and respiration rate (RER) can help policymakers to anticipate the impacts of drought on vegetation and take measures to reduce losses. In this study, the frequency and features of EDEs from 1990 to 2021 were analyzed using the standardized precipitation evapotranspiration index, and the longest-lasting and most severe EDE was chosen to assess the effects of drought on vegetation activity. Then, a land surface model was used to simulate the vegetation PHR and RER. Finally, the effects of the EDE on the vegetation PHR and RER were analyzed from the perspectives of soil and meteorological droughts. The results revealed that from 1990 to 2021, a total of 11 EDEs were observed in southwestern China, and the longest-lasting and most severe EDE occurred in 2009-2010 (EDE2009/2010). EDE2009/2010 significantly reduced the monthly mean PHR and RER by 9.82 g C m-2 month-1 and 0.80 g C m-2 month-1, respectively, causing a cumulative reduction of approximately 5.61 × 1013 g C. Soil and meteorological droughts had a driving force of 39 % on the PHR changes and an explanatory force of 42 % on the RER reduction. In particular, the soil drought had an average explanatory force of 25 % on the PHR and made a contribution of 24 % to the RER. The drought affected different types of vegetation differently, and crops were more susceptible than grassland and forests on the monthly time scale. The vegetation exhibited resilience to drought, returning to normal PHR and RER levels 2 months after the end of EDE2009/2010. This research contributes to understanding and predicting the impact of EDEs on vegetation growth in southwestern China.
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Affiliation(s)
- Fengxian Huang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lulu Liu
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Jiangbo Gao
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Academy of Plateau Science and Sustainability, People's Government of Qinghai Province & Beijing Normal University, Qinghai Normal University, Xining 810008, China.
| | - Ziying Yin
- China University of Geosciences (Beijing), Beijing 100083, China
| | - Yibo Zhang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuan Jiang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Liyuan Zuo
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wenguo Fang
- School of Geographic Science, Qinghai Normal University, Xining 810016, China
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Yang Z, Luo X, Shi Y, Zhou T, Luo K, Lai Y, Yu P, Liu L, Olchev A, Bond-Lamberty B, Hao D, Jian J, Fan S, Cai C, Tang X. Controls and variability of soil respiration temperature sensitivity across China. Sci Total Environ 2023; 871:161974. [PMID: 36740054 DOI: 10.1016/j.scitotenv.2023.161974] [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: 07/22/2022] [Revised: 01/03/2023] [Accepted: 01/29/2023] [Indexed: 06/18/2023]
Abstract
Understanding the temperature sensitivity (Q10) of soil respiration is critical for benchmarking the potential intensity of regional and global terrestrial soil carbon fluxes-climate feedbacks. Although field observations have demonstrated the strong spatial heterogeneity of Q10, a significant knowledge gap still exists regarding to the factors driving spatial and temporal variabilities of Q10 at regional scales. Therefore, we used a machine learning approach to predict Q10 from 1994 to 2016 with a spatial resolution of 1 km across China from 515 field observations at 5 cm soil depth using climate, soil and vegetation variables. Predicted Q10 varied from 1.54 to 4.17, with an area-weighted average of 2.52. There was no significant temporal trend for Q10 (p = 0.32), but annual vegetation production (indicated by normalized difference vegetation index, NDVI) was positively correlated to it (p < 0.01). Spatially, soil organic carbon (SOC) was the most important driving factor in 62 % of the land area across China, and varied greatly, demonstrating soil controls on the spatial pattern of Q10. These findings highlighted different environmental controls on the spatial and temporal pattern of soil respiration Q10, which should be considered to improve global biogeochemical models used to predict the spatial and temporal patterns of soil carbon fluxes to ongoing climate change.
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Affiliation(s)
- Zhihan Yang
- State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China; College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, Sichuan, China
| | - Xinrui Luo
- College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, Sichuan, China
| | - Yuehong Shi
- College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, Sichuan, China
| | - Tao Zhou
- College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, Sichuan, China
| | - Ke Luo
- College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, Sichuan, China
| | - Yunsen Lai
- College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, Sichuan, China
| | - Peng Yu
- College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, Sichuan, China
| | - Liang Liu
- College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, Sichuan, China
| | - Alexander Olchev
- Department of Meteorology and Climatology, Faculty of Geography, Lomonosov Moscow State University, GSP-1, Leninskie Gory, 119991 Moscow, Russia
| | - Ben Bond-Lamberty
- Pacific Northwest National Laboratory, Joint Global Change Research Institute at the University of Maryland-College Park, 5825 University Research Court, Suite 3500, College Park, MD 20740, USA
| | - Dalei Hao
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Jinshi Jian
- State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China
| | - Shaohui Fan
- Key Laboratory of Bamboo and Rattan, International Centre for Bamboo and Rattan, Beijing 100102, China
| | - Chunju Cai
- Key Laboratory of Bamboo and Rattan, International Centre for Bamboo and Rattan, Beijing 100102, China
| | - Xiaolu Tang
- State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China; College of Ecology and Environment, Chengdu University of Technology, Chengdu 610059, Sichuan, China.
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3
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Zhu G, Wang X, Xiao J, Zhang K, Wang Y, He H, Li W, Chen H. Daytime and nighttime warming has no opposite effects on vegetation phenology and productivity in the northern hemisphere. Sci Total Environ 2022; 822:153386. [PMID: 35093352 DOI: 10.1016/j.scitotenv.2022.153386] [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] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 01/19/2022] [Accepted: 01/20/2022] [Indexed: 06/14/2023]
Abstract
Over the past 50 years, global land surface air temperature has been rising at a much higher rate at night than during the day. Understanding plant responses to the asymmetric daytime and nighttime warming in the context of climate change has been a hot topic in global change biology and global ecology. It has been debatable whether the asymmetric warming has opposite effects on vegetation activity (e.g., phenology, productivity). Here we settle the debate by scrutinizing the underpinnings of different statistical methods and revealing how the misuse or improper use of these methods could mischaracterize the effects of asymmetric warming with in situ and satellite observations. The use of the ordinary least square (OLS) methods including both daytime (Tmax) and nighttime (Tmin) temperature in the multiple regression models could overlook the multicollinearity problem and yield the misinterpretations that Tmax and Tmin had opposite effects on spring phenology, autumn phenology, gross primary production (GPP), and normalized difference vegetation index (NDVI). However, when the OLS methods were applied with Tmax and Tmin included in separate models or alternatively the ridge regression (RR) method with properly selected ridge parameter was used, the effects of Tmax and Tmin on vegetation activity were generally in the same direction. The use of the RR method with improperly selected ridge parameter could also mischaracterize the effects of asymmetric warming. Our findings show that daytime and nighttime warming has no opposite effects on vegetation phenology and productivity in the northern hemisphere, and properly dealing with the multicollinearity problem is critical for understanding the effects of asymmetric warming on vegetation activity.
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Affiliation(s)
- Gaofeng Zhu
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), Lanzhou University, 730000 Lanzhou, China.
| | - Xufeng Wang
- Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, 730000 Lanzhou, China.
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA.
| | - Kun Zhang
- National Tibetan Plateau Data Center, Key Laboratory of Tibetan Environmental Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yunquan Wang
- School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
| | - Honglin He
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences, Beijing 100101, China
| | - Weide Li
- School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000, Gansu, China
| | - Huiling Chen
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), Lanzhou University, 730000 Lanzhou, China
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Vicente-Serrano SM, Peña-Angulo D, Murphy C, López-Moreno JI, Tomas-Burguera M, Domínguez-Castro F, Tian F, Eklundh L, Cai Z, Alvarez-Farizo B, Noguera I, Camarero JJ, Sánchez-Salguero R, Gazol A, Grainger S, Conradt T, Boincean B, El Kenawy A. The complex multi-sectoral impacts of drought: Evidence from a mountainous basin in the Central Spanish Pyrenees. Sci Total Environ 2021; 769:144702. [PMID: 33736257 DOI: 10.1016/j.scitotenv.2020.144702] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 11/18/2020] [Accepted: 12/22/2020] [Indexed: 06/12/2023]
Abstract
We analyzed the impacts of drought severity on a variety of sectors in a topographically complex basin (the upper Aragón basin 2181 km2) in the Central Spanish Pyrenees. Using diverse data sources including meteorological and hydrological observations, remote sensing and tree rings, we analyze the possible hydrological implications of drought occurrence and severity on water availability in various sectors, including downstream impacts on irrigation water supply for crop production. Results suggest varying responses in forest activity, secondary growth, plant phenology, and crop yield to drought impacts. Specifically, meteorological droughts have distinct impacts downstream, mainly due to water partitioning between streamflow and irrigation channels that transport water to crop producing areas. This implies that drought severity can extend beyond the physical boundaries of the basin, with impacts on crop productivity. This complex response to drought impacts makes it difficult to develop objective basin-scale operational definitions for monitoring drought severity. Moreover, given the high spatial variability in responses to drought across sectors, it is difficult to establish reliable drought thresholds from indices that are relevant across all socio-economic sectors. The anthropogenic impacts (e.g. water regulation projects, ecosystem services, land cover and land use changes) pose further challenges to assessing the response of different systems to drought severity. This study stresses the need to consider the seasonality of drought impacts and appropriate drought time scales to adequately assess and understand their complexity.
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Affiliation(s)
- S M Vicente-Serrano
- Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain.
| | - D Peña-Angulo
- Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain
| | - C Murphy
- Irish Climate Analysis and Research UnitS (ICARUS), Department of Geography, Maynooth University, Maynooth, Ireland
| | - J I López-Moreno
- Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain
| | - M Tomas-Burguera
- Estación Experimental de Aula Dei, Consejo Superior de Investigaciones Científicas (EEAD-CSIC), Zaragoza, Spain
| | - F Domínguez-Castro
- Aragonese Agency for Research and Development Researcher (ARAID), Spain; Department of Geography, University of Zaragoza, Zaragoza, Spain
| | - F Tian
- Department of Geography, Lund University, Lund, Sweden
| | - L Eklundh
- Department of Geography, Lund University, Lund, Sweden
| | - Z Cai
- Department of Geography, Lund University, Lund, Sweden
| | - B Alvarez-Farizo
- Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain
| | - I Noguera
- Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain
| | - J J Camarero
- Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain
| | - R Sánchez-Salguero
- Departamento Sistemas Físicos, Químicos y Naturales, Universidad Pablo de Olavide, 41013 Sevilla, Spain
| | - A Gazol
- Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain
| | - S Grainger
- Irish Climate Analysis and Research UnitS (ICARUS), Department of Geography, Maynooth University, Maynooth, Ireland
| | - T Conradt
- Potsdam Institute for Climate Impact Research, Potsdam, Germany
| | - B Boincean
- Selectia Research Institute Of Field Crops, Balti, Republic of Moldova
| | - A El Kenawy
- Department of Geography, Mansoura University, Mansoura, Egypt; Department of Geography, Sultan Qaboos University, Al Khoud, Muscat, Oman
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Ding Y, Xu J, Wang X, Peng X, Cai H. Spatial and temporal effects of drought on Chinese vegetation under different coverage levels. Sci Total Environ 2020; 716:137166. [PMID: 32069697 DOI: 10.1016/j.scitotenv.2020.137166] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [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: 11/14/2019] [Revised: 02/01/2020] [Accepted: 02/05/2020] [Indexed: 06/10/2023]
Abstract
Land surface vegetation dynamics are strongly affected by drought. Thus, understanding the responses of vegetation to drought can inform measures to increase biome stability. In this study, the normalized difference vegetation index (NDVI) and the Palmer drought severity index (PDSI) were utilized to investigate the relationship between vegetation activity and drought across different drought regions and ecological community types from 1982 to 2015. Our results showed that the highest correlation between monthly NDVI and PDSI at different timescales (1-36 months) indicated the degree of drought impact on vegetation. There were diverse responses of vegetation to drought according to the drought features and climatic environment. The northern grassland, cropland, and desert ecosystems were strongly impacted by drought. These vegetation ecosystems had a low sensitivity to drought in southern China. Drought had the strongest impact on grassland in summer, which is the high frequency drought season. The most susceptible ecosystem types to drought were those with homogenous vegetation, especially under long-term drought conditions (such as the Inner Mongolia Plateau dominated by grassland). Under global warming, drought with high-temperature characteristics is expected to become more frequent and severe. Such drought could threaten the survival of plateau grassland, arid plain grassland, and rain-fed cropland, as high temperatures accelerate evaporation, leading to water deficit. However, moist forests showed little threat under normal drought. We suggest that future research should focus on vegetation activity in northern and southwestern China, where the vegetation shows the greatest sensitivity to drought.
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Affiliation(s)
- Yibo Ding
- Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China; Institute of Water-saving Agriculture in Arid Areas of China, Northwest A&F University, Yangling 712100, China; College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China
| | - Jiatun Xu
- Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China; Institute of Water-saving Agriculture in Arid Areas of China, Northwest A&F University, Yangling 712100, China; College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China.
| | - Xiaowen Wang
- Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China; Institute of Water-saving Agriculture in Arid Areas of China, Northwest A&F University, Yangling 712100, China; College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China
| | - Xiongbiao Peng
- Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China; Institute of Water-saving Agriculture in Arid Areas of China, Northwest A&F University, Yangling 712100, China; College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China
| | - Huanjie Cai
- Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China; Institute of Water-saving Agriculture in Arid Areas of China, Northwest A&F University, Yangling 712100, China; College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China.
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Du Z, Zhao J, Pan H, Wu Z, Zhang H. Responses of vegetation activity to the daytime and nighttime warming in Northwest China. Environ Monit Assess 2019; 191:721. [PMID: 31691862 DOI: 10.1007/s10661-019-7855-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [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: 02/03/2019] [Accepted: 09/29/2019] [Indexed: 06/10/2023]
Abstract
Though temperature over the past three decades has shown an asynchronous warming trend between daytime and nighttime, the response of vegetation activity to such non-uniform warming is still not very clear. In this study, the least squares linear trend analysis and geographic information system spatial analysis were conducted to analyze the spatiotemporal patterns of the daytime and nighttime warming based on the daily temperature data from 1982 to 2015 in Northwest China. The normalized difference vegetation index (NDVI) from Global Inventory Monitoring and Modeling System and vegetation type data were used to investigate the responses of vegetation activity to the daytime and nighttime warming using the partial correlation analysis. Our results suggested that (1) there was a very significant increasing trend in both daytime and nighttime temperatures in Northwest China from 1982 to 2015; night temperatures increased about 1.2 times faster than daytime temperatures, showing diurnal asymmetric warming; (2) the responses of vegetation activity to daytime and nighttime warming in Northwest China showed a distinct spatial pattern; the change in night temperatures had a more significant (positive in most regions) effect on vegetation; (3) various types of vegetation responded differently to asymmetric daytime and nighttime warming. Grassland NDVI, broad-leaved, and coniferous forest NDVI significantly responded to daytime warming. Shrub NDVI and desert NDVI significantly responded to night warming. These findings can deepen the understanding of the effects of the daytime and nighttime warming on vegetation activities in arid regions in the context of the current asymmetric warming.
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Affiliation(s)
- Ziqiang Du
- Institute of Loess Plateau, Shanxi University, Taiyuan, 030006, Shanxi, China.
| | - Jie Zhao
- College of Natural Resources & Environment, Northwest A & F University, Yangling, 712100, Shaanxi, China
| | - Huanhuan Pan
- Institute of Loess Plateau, Shanxi University, Taiyuan, 030006, Shanxi, China
| | - Zhitao Wu
- Institute of Loess Plateau, Shanxi University, Taiyuan, 030006, Shanxi, China
| | - Hong Zhang
- College of Environmental & Resource Sciences, Shanxi University, Taiyuan, 030006, Shanxi, China
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Cong N, Shen M, Yang W, Yang Z, Zhang G, Piao S. Varying responses of vegetation activity to climate changes on the Tibetan Plateau grassland. Int J Biometeorol 2017; 61:1433-1444. [PMID: 28247125 DOI: 10.1007/s00484-017-1321-5] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [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: 01/17/2016] [Revised: 02/03/2017] [Accepted: 02/06/2017] [Indexed: 06/06/2023]
Abstract
Vegetation activity on the Tibetan Plateau grassland has been substantially enhanced as a result of climate change, as revealed by satellite observations of vegetation greenness (i.e., the normalized difference vegetation index, NDVI). However, little is known about the temporal variations in the relationships between NDVI and temperature and precipitation, and understanding this is essential for predicting how future climate change would affect vegetation activity. Using NDVI data and meteorological records from 1982 to 2011, we found that the inter-annual partial correlation coefficient between growing season (May-September) NDVI and temperature (RNDVI-T) in a 15-year moving window for alpine meadow showed little change, likely caused by the increasing RNDVI-T in spring (May-June) and autumn (September) and decreasing RNDVI-T in summer (July-August). Growing season RNDVI-T for alpine steppe increased slightly, mainly due to increasing RNDVI-T in spring and autumn. The partial correlation coefficient between growing season NDVI and precipitation (RNDVI-P) for alpine meadow increased slightly, mainly in spring and summer, and RNDVI-P for alpine steppe increased, mainly in spring. Moreover, RNDVI-T for the growing season was significantly higher in those 15-year windows with more precipitation for alpine steppe. RNDVI-P for the growing season was significantly higher in those 15-year windows with higher temperature, and this tendency was stronger for alpine meadow than for alpine steppe. These results indicate that the impact of warming on vegetation activity of Tibetan Plateau grassland is more positive (or less negative) during periods with more precipitation and that the impact of increasing precipitation is more positive (or less negative) during periods with higher temperature. Such positive effects of the interactions between temperature and precipitation indicate that the projected warmer and wetter future climate will enhance vegetation activity of Tibetan Plateau grassland.
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Affiliation(s)
- Nan Cong
- Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China
| | - Miaogen Shen
- Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China.
- CAS Center for Excellence in Tibetan Plateau Earth Sciences, 16 Lincui Road, Beijing, 100101, China.
| | - Wei Yang
- Center for Environmental Remote Sensing, Chiba University, Chiba, 263-8522, Japan
| | - Zhiyong Yang
- Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China
| | - Gengxin Zhang
- Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China
| | - Shilong Piao
- Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China
- CAS Center for Excellence in Tibetan Plateau Earth Sciences, 16 Lincui Road, Beijing, 100101, China
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