1
|
Zheng S, Peng D, Zhang B, Yu L, Pan Y, Wang Y, Feng X, Dou C. Temporal variation characteristics in the association between climate and vegetation in Northwest China. Sci Rep 2024; 14:17905. [PMID: 39095561 PMCID: PMC11297244 DOI: 10.1038/s41598-024-68066-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 07/19/2024] [Indexed: 08/04/2024] Open
Abstract
Northwest China has undergone notable alterations in climate and vegetation growth in recent decades. Nevertheless, uncertainties persist concerning the response of different vegetation types to climate change and the underlying mechanisms. This study utilized the Normalized Difference Vegetation Index (NDVI) and three sets of meteorological data to investigate the interannual variations in the association between vegetation and climate (specifically precipitation and temperature) from 1982 to 2015. Several conclusions were drawn. (1) RNDVI-GP (relationship between Growing Season NDVI and precipitation) decreased significantly across all vegetation, while RNDVI-GT (relationship between Growing Season NDVI and temperature) showed an insignificant increase. (2) Trends of RNDVI-GP and RNDVI-GT exhibited great variations across various types of vegetation, with forests displaying notable downward trends in both indices. The grassland exhibited a declining trend in RNDVI-GP but an insignificant increase in RNDVI-GT, while no significant temporal changes in RNDVI-GP or RNDVI-GT were observed in the barren land. (3) The fluctuations in RNDVI-GP and RNDVI-GT closely aligned with variations in drought conditions. Specifically, in regions characterized by VPD (vapor pressure deficit) trends less than 0.02 hpa/yr, which are predominantly grasslands, a rise in SWV (soil water volume) tended to cause a reduction in RNDVI-GP but an increase in RNDVI-GT. However, a more negative trend in SWV was associated with a more negative trend in both RNDVI-GP and RNDVI-GT when the VPD trend exceeded 0.02 hPa/yr, primarily in forests. Our results underscore the variability in the relationship between climate change and vegetation across different vegetation types, as well as the role of drought in modulating these associations.
Collapse
Affiliation(s)
- Shijun Zheng
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Dailiang Peng
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China.
- International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.
| | - Bing Zhang
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
- International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Le Yu
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China.
| | - Yuhao Pan
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
- International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China
| | - Yan Wang
- Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, 999077, China
| | - Xuxiang Feng
- China Remote Sensing Satellite Ground Station (RSGS), Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
| | - Changyong Dou
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
- International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China
| |
Collapse
|
2
|
Zhao W, Zhu Z, Cao S, Li M, Zha J, Pu J, Myneni RB. A global dataset of the fraction of absorbed photosynthetically active radiation for 1982-2022. Sci Data 2024; 11:707. [PMID: 38942755 PMCID: PMC11213951 DOI: 10.1038/s41597-024-03561-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Accepted: 06/20/2024] [Indexed: 06/30/2024] Open
Abstract
The fraction of absorbed photosynthetically active radiation (FPAR) is an essential biophysical parameter that characterizes the structure and function of terrestrial ecosystems. Despite the extensive utilization of several satellite-derived FPAR products, notable temporal inconsistencies within each product have been underscored. Here, the new generation of the GIMMS FPAR product, GIMMS FPAR4g, was developed using a combination of a machine learning algorithm and a pixel-wise multi-sensor records integration approach. PKU GIMMS NDVI, which eliminates the orbital drift and sensor degradation issues, was used as the data source. Comparisons with ground-based measurements indicate root mean square errors ranging from 0.10 to 0.14 with R-squared ranging from 0.73 to 0.87. More importantly, our product demonstrates remarkable spatiotemporal coherence and continuity, revealing a persistent terrestrial darkening over the past four decades (0.0004 yr-1, p < 0.001). The GIMMS FPAR4g, available for half-month intervals at a spatial resolution of 1/12° from 1982 to 2022, promises to be a valuable asset for in-depth analyses of vegetation structures and functions spanning the last 40 years.
Collapse
Affiliation(s)
- Weiqing Zhao
- School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China
- Institute of Carbon Neutrality, Peking University, Beijing, 100871, China
- Key Laboratory of Earth Surface System and Human-Earth Relations, Ministry of Natural Resources of China, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China
| | - Zaichun Zhu
- School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China.
- Institute of Carbon Neutrality, Peking University, Beijing, 100871, China.
- Key Laboratory of Earth Surface System and Human-Earth Relations, Ministry of Natural Resources of China, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China.
| | - Sen Cao
- School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China
- Institute of Carbon Neutrality, Peking University, Beijing, 100871, China
- Key Laboratory of Earth Surface System and Human-Earth Relations, Ministry of Natural Resources of China, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China
| | - Muyi Li
- School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China
- Institute of Carbon Neutrality, Peking University, Beijing, 100871, China
- Key Laboratory of Earth Surface System and Human-Earth Relations, Ministry of Natural Resources of China, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China
| | - Junjun Zha
- School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China
- Institute of Carbon Neutrality, Peking University, Beijing, 100871, China
- Key Laboratory of Earth Surface System and Human-Earth Relations, Ministry of Natural Resources of China, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China
| | - Jiabin Pu
- Department of Earth and Environment, Boston University, Boston, MA, 02215, USA
| | - Ranga B Myneni
- Department of Earth and Environment, Boston University, Boston, MA, 02215, USA
| |
Collapse
|
3
|
Shrestha B, Zhang L, Shrestha S, Khadka N, Maharjan L. Spatiotemporal patterns, sustainability, and primary drivers of NDVI-derived vegetation dynamics (2003-2022) in Nepal. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:607. [PMID: 38858316 DOI: 10.1007/s10661-024-12754-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 05/25/2024] [Indexed: 06/12/2024]
Abstract
Understanding the vegetation dynamics and their drivers in Nepal has significant scientific reference value for implementing sustainable ecological policies. This study provides a comprehensive analysis of the spatio-temporal variations in vegetation cover in Nepal from 2003 to 2022 using MODIS NDVI data and explores the effects of climatic factors and anthropogenic activities on vegetation. Mann-Kendall test was used to assess the significant trend in NDVI and was integrated with the Hurst exponent to predict future trends. The driving factors of NDVI dynamics were analyzed using Pearson's correlation, partial derivative, and residual analysis methods. The results indicate that over the last 20 years, Nepal has experienced an increasing trend in NDVI at 0.0013 year-1, with 80% of the surface area (vegetation cover) showing an increasing vegetation trend (~ 28% with a significant increase in vegetation). Temperature influenced vegetation dynamics in the higher elevation areas, while precipitation and human interventions influenced the lower elevation areas. The Hurst exponent analysis predicts an improvement in the vegetation cover (greening) for a larger area compared to vegetation degradation (browning). A significantly increased area of NDVI residuals indicates a positive anthropogenic influence on vegetation cover. Anthropogenic activities have a higher relative contribution to NDVI variation followed by temperature and then precipitation. The results of residual trend and Hurst analysis in different regions of Nepal help identify degraded areas, both in the present and future. This information can assist relevant authorities in implementing appropriate policies for a sustainable ecological environment.
Collapse
Affiliation(s)
- Bhaskar Shrestha
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, North, No. 20 A, Datun Road, Chaoyang District, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lifu Zhang
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, North, No. 20 A, Datun Road, Chaoyang District, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| | | | - Nitesh Khadka
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Linda Maharjan
- Progoo Research Institute, Tianjin Progoo Information Technology Co., Ltd., Tianjin, 300380, China
| |
Collapse
|
4
|
Li Y, Janssen TAJ, Chen R, He B, Veraverbeke S. Trends and drivers of Arctic-boreal fire intensity between 2003 and 2022. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 926:172020. [PMID: 38547987 DOI: 10.1016/j.scitotenv.2024.172020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 02/27/2024] [Accepted: 03/25/2024] [Indexed: 04/01/2024]
Abstract
Climate change has disproportional effects on Arctic-boreal ecosystems, as the increase of air temperatures in these northern regions is several times higher than the global average. Ongoing warming and drying have resulted in recent record-breaking fire years in Arctic-boreal ecosystems, resulting in substantial carbon emissions that might accelerate climate change. While recent trends in Arctic-boreal burned area have been well documented, it is still unclear how fire intensity has changed. Fire intensity relates to the energy release from combustion and to a large extent drives the impact of a fire on the vegetation and soils, the emission of various gasses and the combustion completeness of different fuels. Here, we used the active fire product from the Moderate Resolution Imaging Spectroradiometer (MODIS) to examine trends in fire radiative power (FRP) over the entire Arctic-boreal region. We found a significant increase in annual median fire intensity between 2003 and 2022 in Eurasian boreal forests, for both daytime (increase of 0.392 MW/km2 per year, R2 = 0.56, p < 0.001) and nighttime fires (increase of 0.175 MW/km2 per year, R2 = 0.47, p < 0.001), while no general trend in FRP was observed in boreal North America. This increase in FRP in Eurasian boreal forests was strongly associated with simultaneous increases in air temperature, vapour pressure deficit, fire weather and fuel availability. We estimated that for Eurasia with each degree increase in air temperature, annual median daytime FRP increases with 1.58 MW/km2 in the tundra and 0.94 MW/km2 in the taiga. Climate change has thus resulted in a widespread and clear increase in fire intensity in central and eastern Eurasia while we could not discern clear trends in Arctic-boreal North America. Arctic-boreal fire intensity may further increase with climate change, with potentially major consequences for fire regimes, carbon emissions and society.
Collapse
Affiliation(s)
- Yanxi Li
- School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan, China; Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Thomas A J Janssen
- Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Rui Chen
- School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Binbin He
- School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
| | - Sander Veraverbeke
- Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom
| |
Collapse
|
5
|
Liu Y, Zhang X, Du X, Du Z, Sun M. Alpine grassland greening on the Northern Tibetan Plateau driven by climate change and human activities considering extreme temperature and soil moisture. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 916:169995. [PMID: 38242484 DOI: 10.1016/j.scitotenv.2024.169995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 12/24/2023] [Accepted: 01/05/2024] [Indexed: 01/21/2024]
Abstract
Alpine grassland is among the world's most vulnerable ecosystems, characterized by a high sensitivity to climate change (CC) and human activities (HA). Quantifying the relative contributions of CC and HA to grassland change plays a crucial role in safeguarding grassland ecological security and devising sustainable grassland management strategies. Although there were adequate studies focusing on the separate impacts of CC and HA on alpine ecosystem, insufficient attention has been given to investigating the effects of extreme temperatures and soil moisture. In this study, the spatiotemporal variations of alpine grassland were analyzed based on MODIS NDVI during the growing season from 2000 to 2020 in Naqu, using partial least squares regression and residual analysis methods to analyze the importance of climate factors and the impacts of CC and HA on grassland change. The results show that the NDVI during the growing season in Naqu exhibited an increasing trend of 0.0046/10a. At the biome scale, the most significant and rapid increase was observed in alpine desert and alpine desert grassland. Extreme temperature and soil moisture (SM) exerted a more significant importance on alpine grassland at whole scale. SM always showed a significant importance at biome and grid scale. The contributions of CC and HA to the change during the growing season were calculated as 0.0032/10a and 0.0015/10a, respectively, accounting for 68.05 % and 31.05 %. CC dominated the increase in NDVI during the growing season; HA contributed positively to NDVI in most areas of Naqu. The results are expected to enhance our understanding of grassland variations under CC and HA and provide a scientific basis for future ecological conservation in alpine regions.
Collapse
Affiliation(s)
- Yuanguo Liu
- School of Public Administration, Hohai University, Nanjing, China
| | - Xiaoke Zhang
- School of Public Administration, Hohai University, Nanjing, China; Center for Environmental and Social Studies, Hohai University, Nanjing, China.
| | - Xindong Du
- School of Public Administration, Hohai University, Nanjing, China
| | - Ziyin Du
- School of Land and Resources, China West Normal University, Nanchong, China
| | - Mingze Sun
- School of Public Administration, Hohai University, Nanjing, China
| |
Collapse
|
6
|
Liu J, Wennberg PO. An emergent constraint on the thermal sensitivity of photosynthesis and greenness in the high latitude northern forests. Sci Rep 2024; 14:6189. [PMID: 38485968 PMCID: PMC11319809 DOI: 10.1038/s41598-024-56362-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 03/05/2024] [Indexed: 03/19/2024] Open
Abstract
Despite the general consensus that the warming over the high latitudes northern forests (HLNF) has led to enhanced photosynthetic activity and contributed to the greening trend, isolating the impact of temperature increase on photosynthesis and greenness has been difficult due to the concurring influence of the CO2 fertilization effect. Here, using an ensemble of simulations from biogeochemical models that have contributed to the Trends in Net Land Atmosphere Carbon Exchange project (TRENDY), we identify an emergent relationship between the simulation of the climate-driven temporal changes in both gross primary productivity (GPP) and greenness (Leaf Area Index, LAI) and the model's spatial sensitivity of these quantities to growing-season (GS) temperature. Combined with spatially-resolved observations of LAI and GPP, we estimate that GS-LAI and GS-GPP increase by 17.0 ± 2.4% and 24.0 ± 3.0% per degree of warming, respectively. The observationally-derived sensitivities of LAI and GPP to temperature are about 40% and 71% higher, respectively, than the mean of the ensemble of simulations from TRENDY, primarily due to the model underestimation of the sensitivity of light use efficiency to temperature. We estimate that the regional mean GS-GPP increased 28.2 ± 5.1% between 1983-1986 and 2013-2016, much larger than the 5.8 ± 1.4% increase from the CO2 fertilization effect implied by Wenzel et al. This suggests that warming, not CO2 fertilization, is primarily responsible for the observed dramatic changes in the HLNF biosphere over the last century.
Collapse
Affiliation(s)
- Junjie Liu
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA.
- California Institute of Technology, Pasadena, USA.
| | | |
Collapse
|
7
|
Lu Q, Liu H, Wei L, Zhong Y, Zhou Z. Global prediction of gross primary productivity under future climate change. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169239. [PMID: 38072275 DOI: 10.1016/j.scitotenv.2023.169239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 12/06/2023] [Accepted: 12/07/2023] [Indexed: 12/17/2023]
Abstract
The ecosystem gross primary productivity (GPP) is crucial to land-atmosphere carbon exchanges, and changes in global GPP as well as its influencing factors have been well studied in recent years. However, identifying the spatio-temporal variations of global GPP under future climate changes is still a challenging issue. This study aims to develop data-driven approach for predicting the global GPP as well as its monthly and annual variations up to the year 2100 under changing climate. Specifically, Catboost was employed to examine the potential relationship between the GPP and environmental factors, with climate variables, CO2 concentration and terrain attributes being selected as environmental factors. The predicted monthly and annual GPP from Coupled Model Intercomparison Project phase 6 (CMIP6) under future SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 scenarios were analyzed. The results indicate that the global GPP is predicted to increase under the future climate change in the 21st century. The annual GPP is expected to be 115.122 Pg C, 116.537 Pg C, 117.626 Pg C, and 120.097 Pg C in 2100 under four future scenarios, and the predicted monthly GPP shows seasonal difference. Meanwhile, GPP tends to increase in the northern mid-high latitude regions and decrease in the equatorial regions. For the climate zones form Köppen-Geiger classification, the arid, cold, and polar zones present increased GPP, while GPP in the tropical zone will decrease in the future. Moreover, the high importance of climate variables in GPP prediction illustrates that the future climate change is the main driver of the global GPP dynamics. This study provides a basis for predicting how global GPP responds to future climate change in the coming decades, which contribute to understanding the interactions between vegetation and climate.
Collapse
Affiliation(s)
- Qikai Lu
- Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China; Hubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430062, China; Key Laboratory of Digital Mapping and Land Information Application, Ministry of Natural Resources, Wuhan University, Wuhan 430079, China; Key Laboratory of Natural Resources Monitoring and Supervision in Southern Hilly Region, Ministry of Natural Resources, Second Surveying and Mapping Institute of Hunan Province, Changsha 410118, China
| | - Hui Liu
- Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China
| | - Lifei Wei
- Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China; Hubei Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430062, China.
| | - Yanfei Zhong
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
| | - Zheng Zhou
- Changjiang Basin Ecology and Environment Monitoring and Scientific Research Center, Changjiang Basin Ecology and Environment Administration, Ministry of Ecology and Environment, Wuhan 430010, China
| |
Collapse
|
8
|
Short AW, Sebastian JSV, Huang J, Wang G, Dassanayake M, Finnegan PM, Parker JD, Cao KF, Wee AKS. Comparative transcriptomics of the chilling stress response in two Asian mangrove species, Bruguiera gymnorhiza and Rhizophora apiculata. TREE PHYSIOLOGY 2024; 44:tpae019. [PMID: 38366388 DOI: 10.1093/treephys/tpae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 11/30/2023] [Accepted: 02/03/2024] [Indexed: 02/18/2024]
Abstract
Low temperatures largely determine the geographic limits of plant species by reducing survival and growth. Inter-specific differences in the geographic distribution of mangrove species have been associated with cold tolerance, with exclusively tropical species being highly cold-sensitive and subtropical species being relatively cold-tolerant. To identify species-specific adaptations to low temperatures, we compared the chilling stress response of two widespread Indo-West Pacific mangrove species from Rhizophoraceae with differing latitudinal range limits-Bruguiera gymnorhiza (L.) Lam. ex Savigny (subtropical range limit) and Rhizophora apiculata Blume (tropical range limit). For both species, we measured the maximum photochemical efficiency of photosystem II (Fv/Fm) as a proxy for the physiological condition of the plants and examined gene expression profiles during chilling at 15 and 5 °C. At 15 °C, B. gymnorhiza maintained a significantly higher Fv/Fm than R. apiculata. However, at 5 °C, both species displayed equivalent Fv/Fm values. Thus, species-specific differences in chilling tolerance were only found at 15 °C, and both species were sensitive to chilling at 5 °C. At 15 °C, B. gymnorhiza downregulated genes related to the light reactions of photosynthesis and upregulated a gene involved in cyclic electron flow regulation, whereas R. apiculata downregulated more RuBisCo-related genes. At 5 °C, both species repressed genes related to CO2 assimilation. The downregulation of genes related to light absorption and upregulation of genes related to cyclic electron flow regulation are photoprotective mechanisms that likely contributed to the greater photosystem II photochemical efficiency of B. gymnorhiza at 15 °C. The results of this study provide evidence that the distributional range limits and potentially the expansion rates of plant species are associated with differences in the regulation of photosynthesis and photoprotective mechanisms under low temperatures.
Collapse
Affiliation(s)
- Aidan W Short
- Guangxi Key Laboratory of Forest Ecology and Conservation, College of Forestry, Guangxi University, Daxuedonglu 100, Nanning 530004, China
- Institute of Ecology and Evolution, Department of Biology, 5289 University of Oregon, Eugene, OR 97403, USA
| | - John Sunoj V Sebastian
- Guangxi Key Laboratory of Forest Ecology and Conservation, College of Forestry, Guangxi University, Daxuedonglu 100, Nanning 530004, China
- State Key Laboratory of Conservation and Utilization of Subtropical Agro-Bioresources, College of Forestry, Guangxi University, Daxuedonglu 100, Nanning, Guangxi 530004, China
| | - Jie Huang
- Guangxi Key Laboratory of Forest Ecology and Conservation, College of Forestry, Guangxi University, Daxuedonglu 100, Nanning 530004, China
| | - Guannan Wang
- Department of Biological Sciences, Louisiana State University (LSU), 202 Life Science Bldg, Baton Rouge, LA 70803, USA
| | - Maheshi Dassanayake
- Department of Biological Sciences, Louisiana State University (LSU), 202 Life Science Bldg, Baton Rouge, LA 70803, USA
| | - Patrick M Finnegan
- School of Biological Sciences, University of Western Australia, 35 Stirling Highway, Perth, WA 6009, Australia
| | - John D Parker
- Smithsonian Environmental Research Center, Smithsonian Institution, 647 Contees Wharf Road, Edgewater, MD 21037, USA
| | - Kun-Fang Cao
- Guangxi Key Laboratory of Forest Ecology and Conservation, College of Forestry, Guangxi University, Daxuedonglu 100, Nanning 530004, China
- State Key Laboratory of Conservation and Utilization of Subtropical Agro-Bioresources, College of Forestry, Guangxi University, Daxuedonglu 100, Nanning, Guangxi 530004, China
| | - Alison K S Wee
- Guangxi Key Laboratory of Forest Ecology and Conservation, College of Forestry, Guangxi University, Daxuedonglu 100, Nanning 530004, China
- State Key Laboratory of Conservation and Utilization of Subtropical Agro-Bioresources, College of Forestry, Guangxi University, Daxuedonglu 100, Nanning, Guangxi 530004, China
- School of Environmental and Geographical Sciences, University of Nottingham Malaysia, Jalan Broga, 43500 Semenyih, Malaysia
| |
Collapse
|
9
|
Lei J, Su Y, Jian S, Guo X, Yuan M, Bates CT, Shi ZJ, Li J, Su Y, Ning D, Wu L, Zhou J, Yang Y. Warming effects on grassland soil microbial communities are amplified in cool months. THE ISME JOURNAL 2024; 18:wrae088. [PMID: 38747385 PMCID: PMC11170927 DOI: 10.1093/ismejo/wrae088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 03/25/2024] [Accepted: 05/14/2024] [Indexed: 06/14/2024]
Abstract
Global warming modulates soil respiration (RS) via microbial decomposition, which is seasonally dependent. Yet, the magnitude and direction of this modulation remain unclear, partly owing to the lack of knowledge on how microorganisms respond to seasonal changes. Here, we investigated the temporal dynamics of soil microbial communities over 12 consecutive months under experimental warming in a tallgrass prairie ecosystem. The interplay between warming and time altered (P < 0.05) the taxonomic and functional compositions of microbial communities. During the cool months (January to February and October to December), warming induced a soil microbiome with a higher genomic potential for carbon decomposition, community-level ribosomal RNA operon (rrn) copy numbers, and microbial metabolic quotients, suggesting that warming stimulated fast-growing microorganisms that enhanced carbon decomposition. Modeling analyses further showed that warming reduced the temperature sensitivity of microbial carbon use efficiency (CUE) by 28.7% when monthly average temperature was low, resulting in lower microbial CUE and higher heterotrophic respiration (Rh) potentials. Structural equation modeling showed that warming modulated both Rh and RS directly by altering soil temperature and indirectly by influencing microbial community traits, soil moisture, nitrate content, soil pH, and gross primary productivity. The modulation of Rh by warming was more pronounced in cooler months compared to warmer ones. Together, our findings reveal distinct warming-induced effects on microbial functional traits in cool months, challenging the norm of soil sampling only in the peak growing season, and advancing our mechanistic understanding of the seasonal pattern of RS and Rh sensitivity to warming.
Collapse
Affiliation(s)
- Jiesi Lei
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Yuanlong Su
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Siyang Jian
- Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019, United States
| | - Xue Guo
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Mengting Yuan
- Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019, United States
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA 94704, United States
| | - Colin T Bates
- Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019, United States
| | - Zhou Jason Shi
- Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019, United States
| | - Jiabao Li
- Key Laboratory of Environmental and Applied Microbiology, Chinese Academy of Sciences and Environmental Microbiology & Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610213, China
| | - Yifan Su
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Daliang Ning
- Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019, United States
| | - Liyou Wu
- Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019, United States
| | - Jizhong Zhou
- Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019, United States
- School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK 73019, United States
- Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, United States
| | - Yunfeng Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| |
Collapse
|
10
|
Xie J, Yin G, Ma D, Chen R, Zhao W, Xie Q, Wang C, Lin S, Yuan W. Climatic limitations on grassland photosynthesis over the Tibetan Plateau shifted from temperature to water. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167663. [PMID: 37813264 DOI: 10.1016/j.scitotenv.2023.167663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 09/15/2023] [Accepted: 10/06/2023] [Indexed: 10/11/2023]
Abstract
Plant photosynthesis plays an essential role in regulating the global carbon cycle. Therefore, it is essential to understand the limitations imposed by climate on plant photosynthesis to comprehend the impacts of climate change on land carbon dynamics. In this study, taking gross primary productivity as a direct representation of photosynthesis, we employed a light use efficiency model (i.e., the revised EC-LUE) and factorial analysis method to quantify the spatiotemporal variation of temperature- and water-limitations on plant photosynthesis over the Tibetan Plateau (TP) grasslands during growing season (May to October) in 1983-2018. Results revealed a clear spatiotemporal pattern of the temperature- and water-limitations: temperature is the primary climatic limiting factor in the eastern TP, while water is the primary climatic limiting factor in the western TP; the water- and temperature-limitations prevail in summer and spring/autumn, respectively. The water- and temperature-limitations intensified and alleviated, respectively, during 1983 through 2018. There also was a widespread shift from temperature-limitation to water-limitation in the TP, particularly in midsummer (August). Our findings demonstrated the shifting relative importance of climatic limitations on plant photosynthesis under changing climate, which is crucial for predicting future terrestrial carbon cycle dynamics.
Collapse
Affiliation(s)
- Jiangliu Xie
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610031, China
| | - Gaofei Yin
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610031, China.
| | - Dujuan Ma
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610031, China
| | - Rui Chen
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610031, China
| | - Wei Zhao
- Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
| | - Qiaoyun Xie
- School of Engineering, The University of Western Australia, Perth, WA 6009, Australia
| | - Cong Wang
- Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province/School of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China
| | - Shangrong Lin
- School of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen University, Zhuhai 519000, China
| | - Wenping Yuan
- School of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen University, Zhuhai 519000, China
| |
Collapse
|
11
|
Zhang J, Yang T, Deng M, Huang H, Han Y, Xu H. Spatiotemporal variations and its driving factors of NDVI in Northwest China during 2000-2021. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:118782-118800. [PMID: 37919507 DOI: 10.1007/s11356-023-30250-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 09/29/2023] [Indexed: 11/04/2023]
Abstract
Northwest China (WTL) is an essential ecological barrier zone of China, an important node of the "Silk Road Economic Belt," and a crucial bearing area for China's execution of the "One Road and One Belt" and "Going Global" strategies. However, its ecology is exceedingly fragile and particularly vulnerable to climate change and human interference. This study explored the spatiotemporal evolution characteristics of vegetation in WTL using NDVI data and investigated its drive mechanisms by geodetector, partial correlation analysis, and residual trend analysis methods. As well as forecasting the trend for vegetation changes. The findings demonstrated that (1) the change in NDVI manifested an overall improvement trend and the distribution in space of NDVI rose from the center to the periphery. 57.07% of the area had a sparse cover of vegetation (NDVI between 0 and 0.2). In addition, about 49% of regions had deterioration tendencies, which were mainly aggregated in HX, QCXDB, QCXDN, and the eastern of QCXQN and QCXXB. (2) The NDVI's shifting trend was unsustainability, and the region of uncertain future accounted for 57.45% of the total, with apparent unsustainability features. (3) The key parameters influencing NDVI spatial distribution were Pre (precipitation), vegetation type, land use type, and soil type. The interaction between two factors enhanced the influence of any single element, which appeared as bivariate and nonlinear enhancements. (4) Both climate variations and human activities have been recognized as key variables affecting NDVI growth. NDVI variance in 73.02% of areas was influenced by the combined effects of climate variations and human activities. However, human activities were the most influential element in NDVI growth, with the relative contributions of 80.28% (19.72% of which was caused by climate variations). These results can be conducive to deepening insights into the local vegetation status, identifying the mechanisms driving vegetation change, and providing scientific recommendations for WTL's ecosystem restoration measures based on actual situations.
Collapse
Affiliation(s)
- Jiaxin Zhang
- State Key Laboratory of Hydrology Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, China
- The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, 210098, Jiangsu, China
| | - Tao Yang
- State Key Laboratory of Hydrology Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, China
- The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, 210098, Jiangsu, China
| | - Mingjiang Deng
- State Key Laboratory of Hydrology Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, China
- Xinjiang Ertix River Basin Development and Construction Management Bureau, Urumqi, 830000, China
| | - Huiping Huang
- College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China
| | - Yuping Han
- College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
| | - Huanhuan Xu
- College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China
| |
Collapse
|
12
|
Luo Y, Gessler A, D'Odorico P, Hufkens K, Stocker BD. Quantifying effects of cold acclimation and delayed springtime photosynthesis resumption in northern ecosystems. THE NEW PHYTOLOGIST 2023; 240:984-1002. [PMID: 37583086 DOI: 10.1111/nph.19208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Accepted: 07/24/2023] [Indexed: 08/17/2023]
Abstract
Land carbon dynamics in temperate and boreal ecosystems are sensitive to environmental change. Accurately simulating gross primary productivity (GPP) and its seasonality is key for reliable carbon cycle projections. However, significant biases have been found in early spring GPP simulations of northern forests, where observations often suggest a later resumption of photosynthetic activity than predicted by models. Here, we used eddy covariance-based GPP estimates from 39 forest sites that differ by their climate and dominant plant functional types. We used a mechanistic and an empirical light use efficiency (LUE) model to investigate the magnitude and environmental controls of delayed springtime photosynthesis resumption (DSPR) across sites. We found DSPR reduced ecosystem LUE by 30-70% at many, but not all site-years during spring. A significant depression of LUE was found not only in coniferous but also at deciduous forests and was related to combined high radiation and low minimum temperatures. By embedding cold-acclimation effects on LUE that considers the delayed effects of minimum temperatures, initial model bias in simulated springtime GPP was effectively resolved. This provides an approach to improve GPP estimates by considering physiological acclimation and enables more reliable simulations of photosynthesis in northern forests and projections in a warming climate.
Collapse
Affiliation(s)
- Yunpeng Luo
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903, Birmensdorf, Switzerland
- Department of Environmental System Science, Institute of Agricultural Sciences, ETH Zurich, 8902, Zurich, Switzerland
| | - Arthur Gessler
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903, Birmensdorf, Switzerland
| | - Petra D'Odorico
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903, Birmensdorf, Switzerland
| | - Koen Hufkens
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903, Birmensdorf, Switzerland
- Department of Environmental System Science, Institute of Agricultural Sciences, ETH Zurich, 8902, Zurich, Switzerland
| | - Benjamin D Stocker
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903, Birmensdorf, Switzerland
- Department of Environmental System Science, Institute of Agricultural Sciences, ETH Zurich, 8902, Zurich, Switzerland
- Institute of Geography, University of Bern, Hallerstrasse 12, 3012, Bern, Switzerland
- Oeschger Centre for Climate Change Research, University of Bern, Falkenplatz 16, 3012, Bern, Switzerland
| |
Collapse
|
13
|
Le T. Increased impact of the El Niño-Southern Oscillation on global vegetation under future warming environment. Sci Rep 2023; 13:14459. [PMID: 37660230 PMCID: PMC10475042 DOI: 10.1038/s41598-023-41590-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 08/29/2023] [Indexed: 09/04/2023] Open
Abstract
There are broad effects of vegetation changes on regional climate, carbon budget, the water cycle, and ecosystems' productivity. Therefore, further knowledge of the drivers of future vegetation changes is critical to mitigate the influences of global warming. The El Niño-Southern Oscillation (ENSO) is a major mode of interannual climate variability and is likely to affect vegetation on the global scale. Nonetheless, little is known about the causal impacts of ENSO on future vegetation cover with changes in land use and a warming environment. Here, we examined the connections between ENSO and vegetation using leaf area index (LAI) data over the period 2015-2100 from Coupled Modeling Intercomparison Project Phase 6. Our findings indicate that, compared with the historical period 1915-2000, the vegetated areas influenced by ENSO are projected to rise by approximately 55.2% and 20.7% during the twenty-first century of the scenarios SSP2-4.5 and SSP5-8.5, respectively. Though uncertainty for the causal link between ENSO and vegetation changes remains in several regions (i.e., parts of North America, southern Australia, and western Asia), ENSO signature on LAI variations is robust over northern Australia, Amazonia, and parts of Southeast Asia. These results indicate that the influences of ENSO on global vegetation may strengthen in the future.
Collapse
Affiliation(s)
- Thanh Le
- Department of Civil and Environmental Engineering, Sejong University, Seoul, 05006, Republic of Korea.
- School of Atmospheric Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
| |
Collapse
|
14
|
He Y, Liu Y, Lei L, Terrer C, Huntingford C, Peñuelas J, Xu H, Piao S. CO 2 fertilization contributed more than half of the observed forest biomass increase in northern extra-tropical land. GLOBAL CHANGE BIOLOGY 2023; 29:4313-4326. [PMID: 37277951 DOI: 10.1111/gcb.16806] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 04/23/2023] [Accepted: 05/11/2023] [Indexed: 06/07/2023]
Abstract
The existence of a large-biomass carbon (C) sink in Northern Hemisphere extra-tropical ecosystems (NHee) is well-established, but the relative contribution of different potential drivers remains highly uncertain. Here we isolated the historical role of carbon dioxide (CO2 ) fertilization by integrating estimates from 24 CO2 -enrichment experiments, an ensemble of 10 dynamic global vegetation models (DGVMs) and two observation-based biomass datasets. Application of the emergent constraint technique revealed that DGVMs underestimated the historical response of plant biomass to increasing [CO2 ] in forests (β Forest Mod ) but overestimated the response in grasslands (β Grass Mod ) since the 1850s. Combining the constrainedβ Forest Mod (0.86 ± 0.28 kg C m-2 [100 ppm]-1 ) with observed forest biomass changes derived from inventories and satellites, we identified that CO2 fertilization alone accounted for more than half (54 ± 18% and 64 ± 21%, respectively) of the increase in biomass C storage since the 1990s. Our results indicate that CO2 fertilization dominated the forest biomass C sink over the past decades, and provide an essential step toward better understanding the key role of forests in land-based policies for mitigating climate change.
Collapse
Affiliation(s)
- Yue He
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Yongwen Liu
- State Key Laboratory of Earth System and Environmental Resources of the Tibetan Plateau (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
| | - Lingjie Lei
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - César Terrer
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | | | - Josep Peñuelas
- CREAF, Cerdanyola del Valles, Barcelona, Spain
- CSIC, Global Ecology Unit CREAF-CSIC-UAB, Barcelona, Spain
| | - Hao Xu
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Shilong Piao
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
- State Key Laboratory of Earth System and Environmental Resources of the Tibetan Plateau (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
| |
Collapse
|
15
|
Li Z, Qu H, Li L, Zheng J, Wei D, Wang F. Effects of climate change on vegetation dynamics of the Qinghai-Tibet Plateau, a causality analysis using empirical dynamic modeling. Heliyon 2023; 9:e16001. [PMID: 37206005 PMCID: PMC10189261 DOI: 10.1016/j.heliyon.2023.e16001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 04/27/2023] [Accepted: 04/28/2023] [Indexed: 05/21/2023] Open
Abstract
Given the vital role of the Qinghai-Tibet Plateau (QTP) as water tower in Asia and regulator for regional and even global climate, the relationship between climate change and vegetation dynamics on it has received considerable focused attention. Climate change may influence the vegetation growth on the plateau, but clear empirical evidence of such causal linkages is sparse. Herein, using datasets CRU-TS v4.04 and AVHHR NDVI from 1981 to 2019, we quantify causal effects of climate factors on vegetation dynamics with an empirical dynamical model (EDM) -- a nonlinear dynamical systems analysis approach based on state-space reconstruction rather than correlation. Results showed the following: (1) climate change promotes the growth of vegetation on the QTP, and specifically, this favorable influence of temperature is stronger than precipitation's; (2) the direction and strength of climate effects on vegetation varied over time, and the effects are seasonally different; (3) a significant increase in temperature and a slight increase in precipitation are beneficial to vegetation growth, specifically, NDVI will increase within 2% in the next 40 years with the climate trend of warming and humidity. Besides the above results, another interesting finding is that the two seasons in which precipitation strongly influence vegetation in the Three-River Source region (part of the QTP) are spring and winter. This study provides insights into the mechanisms by which climate change affects vegetation growth on the QTP, aiding in the modeling of vegetation dynamics in future scenarios.
Collapse
Affiliation(s)
- Zhaoni Li
- College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
- College of Computer, Qinghai Normal University, Xining, 810008, China
- Institute of Ecological Safety Forewarning and Control, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
| | - Hongchun Qu
- College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
- College of Automation, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
- Institute of Ecological Safety Forewarning and Control, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
- Corresponding author. College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China.
| | - Lin Li
- College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
| | - Jian Zheng
- College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
| | - Dianwen Wei
- Institute of Natural Resources and Ecology, Heilongjiang Academy of Sciences, Harbin, 150040, China
| | - Fude Wang
- Institute of Forestry Science of Heilongjiang Province, Harbin, 150081, China
| |
Collapse
|
16
|
Li G, Wu C, Chen Y, Huang C, Zhao Y, Wang Y, Ma M, Ding Z, Yu P, Tang X. Increasing temperature regulates the advance of peak photosynthesis timing in the boreal ecosystem. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 882:163587. [PMID: 37087004 DOI: 10.1016/j.scitotenv.2023.163587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 04/14/2023] [Accepted: 04/15/2023] [Indexed: 05/03/2023]
Abstract
The shift in vegetation phenology is an essential indicator of global climate change. Numerous researches based on reflectance-based vegetation index data have explored the changes in the start (SOS) and end (EOS) of vegetation life events at long time scales, while a huge discrepancy existed between the phenological metrics of vegetation structure and function. The peak photosynthesis timing (PPT), which is crucial in regulating terrestrial ecosystem carbon balance, has not received much attention. Using two global reconstructed solar-induced chlorophyll fluorescence data (CSIF and GOSIF) directly associated with vegetation photosynthesis, the spatio-temporal dynamics in PPT as well as the key environmental controls across the boreal ecosystem during 2001-2019 were systematically explored. Multi-year mean pattern showed that PPT mainly appeared in the first half of July. Compared to the northern Eurasia, later PPT appeared in the northern North America continent for about 4-5 days. Meanwhile, spatial trend in PPT exhibited an advanced trend during the last two decades. Especially, shrubland and grassland were obvious among all biomes. Spatial partial correlation analysis revealed that preseason temperature was the dominant environmental driver of PPT trends, occupying 81.32% and 78.04% of the total pixels of PPTCSIF and PPTGOSIF, respectively. Attribution analysis by ridge regression again emphasized the largest contribution of temperature to PPT dynamics in the boreal ecosystem by 52.22% (PPTCSIF) and 46.59% (PPTGOSIF), followed by radiation (PPTCSIF: 24.44%; PPTGOSIF: 28.66%) and precipitation (PPTCSIF: 23.34%; PPTGOSIF: 24.75%). These results have significant implications for deepening our understanding between vegetation photosynthetic phenology and carbon cycling with respect to future climate change in the boreal ecosystem.
Collapse
Affiliation(s)
- Guo Li
- Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China; Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
| | - Chaoyang Wu
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yanan Chen
- Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China; Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
| | - Changping Huang
- National Engineering Laboratory for Satellite Remote Sensing Applications, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Yan Zhao
- Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China; Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
| | - Yanan Wang
- Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China; Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
| | - Mingguo Ma
- Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China; Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
| | - Zhi Ding
- Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China; Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
| | - Pujia Yu
- Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China; Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
| | - Xuguang Tang
- Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China; Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China.
| |
Collapse
|
17
|
Leng R, Harrison S, Anderson K. Himalayan alpine ecohydrology: An urgent scientific concern in a changing climate. AMBIO 2023; 52:390-410. [PMID: 36324019 PMCID: PMC9755440 DOI: 10.1007/s13280-022-01792-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 06/22/2022] [Accepted: 08/31/2022] [Indexed: 06/16/2023]
Abstract
Climate change is projected to have important impacts on snow and vegetation distribution in global mountains. Despite this, the coupling of ecological shifts and hydrological processes within alpine zones has not attracted significant scientific attention. As the largest and one of the most climatically sensitive mountain systems, we argue that Himalayan alpine ecohydrological processes require urgent scientific attention because up to 1.6 billion people rely on water supplies from the mountains. We review studies from global mountain systems to highlight the importance of considering ecohydrological impacts within Himalayan alpine zones (4100-6000 m.a.s.l), explaining mechanisms for interactions between snow and dwarf plants. Our findings highlight the paucity of monitoring stations within Himalayan alpine systems. We suggest that it is likely that alpine ecological shifts will impact hydrological processes, but we found that specific mechanisms and functional relationships are missing for Himalayan systems, so the strength and direction of ecohydrological relationships is currently unknown. We advocate for more purposeful and widespread monitoring efforts below glaciers and above the treeline, calling for new experiments to query the role of small plants within the Himalayan alpine hydrological system. We outline the need for community engagement with alpine ecohydrological experiments, and we explain how new snow and vegetation products derived from remote sensing observations have the potential to improve scientific understanding of the interacting effects of warming and ecohydrological factors in this sensitive region.
Collapse
Affiliation(s)
- Ruolin Leng
- Department of Geography, University of Exeter, Cornwall Campus, Penryn, TR10 9FE Cornwall UK
- Environment and Sustainability Institute, University of Exeter, Cornwall Campus, Penryn,, TR10 9FE Cornwall UK
| | - Stephan Harrison
- Department of Geography, University of Exeter, Cornwall Campus, Penryn, TR10 9FE Cornwall UK
- Environment and Sustainability Institute, University of Exeter, Cornwall Campus, Penryn,, TR10 9FE Cornwall UK
| | - Karen Anderson
- Department of Geography, University of Exeter, Cornwall Campus, Penryn, TR10 9FE Cornwall UK
- Environment and Sustainability Institute, University of Exeter, Cornwall Campus, Penryn,, TR10 9FE Cornwall UK
| |
Collapse
|
18
|
Zhu Z, Wang H, Harrison SP, Prentice IC, Qiao S, Tan S. Optimality principles explaining divergent responses of alpine vegetation to environmental change. GLOBAL CHANGE BIOLOGY 2023; 29:126-142. [PMID: 36176241 PMCID: PMC10092415 DOI: 10.1111/gcb.16459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 09/02/2022] [Indexed: 06/16/2023]
Abstract
Recent increases in vegetation greenness over much of the world reflect increasing CO2 globally and warming in cold areas. However, the strength of the response to both CO2 and warming in those areas appears to be declining for unclear reasons, contributing to large uncertainties in predicting how vegetation will respond to future global changes. Here, we investigated the changes of satellite-observed peak season absorbed photosynthetically active radiation (Fmax ) on the Tibetan Plateau between 1982 and 2016. Although climate trends are similar across the Plateau, we identified robust divergent responses (a greening of 0.31 ± 0.14% year-1 in drier regions and a browning of 0.12 ± 0.08% year-1 in wetter regions). Using an eco-evolutionary optimality (EEO) concept of plant acclimation/adaptation, we propose a parsimonious modelling framework that quantitatively explains these changes in terms of water and energy limitations. Our model captured the variations in Fmax with a correlation coefficient (r) of .76 and a root mean squared error of .12 and predicted the divergent trends of greening (0.32 ± 0.19% year-1 ) and browning (0.07 ± 0.06% year-1 ). We also predicted the observed reduced sensitivities of Fmax to precipitation and temperature. The model allows us to explain these changes: Enhanced growing season cumulative radiation has opposite effects on water use and energy uptake. Increased precipitation has an overwhelmingly positive effect in drier regions, whereas warming reduces Fmax in wetter regions by increasing the cost of building and maintaining leaf area. Rising CO2 stimulates vegetation growth by enhancing water-use efficiency, but its effect on photosynthesis saturates. The large decrease in the sensitivity of vegetation to climate reflects a shift from water to energy limitation. Our study demonstrates the potential of EEO approaches to reveal the mechanisms underlying recent trends in vegetation greenness and provides further insight into the response of alpine ecosystems to ongoing climate change.
Collapse
Affiliation(s)
- Ziqi Zhu
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change StudiesTsinghua UniversityBeijingChina
| | - Han Wang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change StudiesTsinghua UniversityBeijingChina
| | - Sandy P. Harrison
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change StudiesTsinghua UniversityBeijingChina
- School of Archaeology, Geography and Environmental Sciences (SAGES)University of ReadingReadingUK
| | - Iain Colin Prentice
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change StudiesTsinghua UniversityBeijingChina
- Georgina Mace Centre for the Living Planet, Department of Life SciencesImperial College LondonAscotUK
- Department of Biological SciencesMacquarie UniversityNorth RydeNew South WalesAustralia
| | - Shengchao Qiao
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change StudiesTsinghua UniversityBeijingChina
| | - Shen Tan
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change StudiesTsinghua UniversityBeijingChina
| |
Collapse
|
19
|
Shen F, Yang L, Zhang L, Guo M, Huang H, Zhou C. Quantifying the direct effects of long-term dynamic land use intensity on vegetation change and its interacted effects with economic development and climate change in jiangsu, China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 325:116562. [PMID: 36308967 DOI: 10.1016/j.jenvman.2022.116562] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 10/13/2022] [Accepted: 10/16/2022] [Indexed: 06/16/2023]
Abstract
Vegetation change reflects sensitive responses of ecosystem environment to global climate change as well as land use. It is well known that land use type and its transformation affect vegetation change. However, how the changes in land use intensity (LUI) within different land use types impact vegetation and the interactions with other drivers remain poorly understood. We measured the LUI of Jiangsu Province, China, within the main land use types in 1995, 2000, 2005, 2010, 2015 and 2018 by combining remote sensing-based land use data with representative county scale economic and social indicators. Structural equation models (SEMs) were built to quantify the influences of long term LUI on vegetation change interacting with economic development, climate change and topographical conditions in transformed land, cropland, rural settlements and urbanized land, respectively. Seventy percent of significant vegetation change existed in non-transformed land use types. Although the area with a vegetation greening trend is larger than that with a vegetation browning trend, the vegetation browning areas is prominent in urbanized lands and some croplands in south basins. The constructed SEMs suggested the dominant negative effect of fast economic development regardless of land use types, while LUI played important and different direct and indirect effects on affecting vegetation change significantly interacting with economic development and climate change in different land use types. The LUI increasing led a vegetation greening in cropland, and stronger than climate warming with both positive direct and indirect effects for influencing climate change. The LUI change took negative effects on vegetation change in rural and urban areas, while a positive indirect effect of LUI increasing in urbanized land signaled the positive results of human managements. We then provided some land use-specific suggestions on basin scale for land management in Jiangsu. Our results highlight the necessity of long-term LUI quantification and promote the understanding of its effects on vegetation change interacted with other drivers within different land use types. This can be very helpful for sustainable land use and managements in regions with fast economic development.
Collapse
Affiliation(s)
- Feixue Shen
- School of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China.
| | - Lin Yang
- School of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China; State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Lei Zhang
- School of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China.
| | - Mao Guo
- School of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China.
| | - Haili Huang
- School of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China.
| | - Chenghu Zhou
- School of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China; State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
| |
Collapse
|
20
|
Ma B, Jing J, Liu B, Wang Y, He H. Assessing the contribution of human activities and climate change to the dynamics of NPP in ecologically fragile regions. Glob Ecol Conserv 2023. [DOI: 10.1016/j.gecco.2023.e02393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
|
21
|
Yang S, Zhou B, Lou H, Wu Z, Wang S, Zhang Y, Pan Z, Li C. Remote sensing hydrological indication: Responses of hydrological processes to vegetation cover change in mid-latitude mountainous regions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 851:158170. [PMID: 35988605 DOI: 10.1016/j.scitotenv.2022.158170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 08/15/2022] [Accepted: 08/16/2022] [Indexed: 06/15/2023]
Abstract
Hydrological processes in mid-latitude mountainous regions are greatly affected by changes in vegetation cover that induced by the climate change. However, studies on hydrological processes in mountainous regions are limited, because of difficulties in building and maintaining basin-wide representative hydrological stations. In this study, a new method, remote sensing technology for monitoring river discharge by combining satellite remote sensing, unmanned aerial vehicles and hydrological surveying, was used for evaluating the runoff processes in the Changbai Mountains, one of the mid-latitude mountainous regions in the eastern part of Northeast China. Based on this method, the impact of vegetation cover change on hydrological processes was revealed by combining the data of hydrological processes, meteorology, and vegetation cover. The results showed a decreasing trend in the monitored river discharge from 2000 to 2021, with an average rate of -5.13 × 105 m3 yr-1. At the monitoring section mainly influenced by precipitation, the precipitation-induced proportion of changes in river discharge to annual average river discharge and its change significance was only 6.5 % and 0.23, respectively, showing the precipitation change was not the cause for the decrease in river discharge. A negative impact of evapotranspiration on river discharge was found, and the decrease in river discharge was proven to be caused by the increasing evapotranspiration, which was induced by the drastically increased vegetation cover under a warming climate. Our findings suggested that increases in vegetation cover due to climate change could reshape hydrological processes in mid-latitude mountainous regions, leading to an increase in evapotranspiration and a subsequent decrease in river discharge.
Collapse
Affiliation(s)
- Shengtian Yang
- College of Water Sciences, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China
| | - Baichi Zhou
- College of Water Sciences, Beijing Normal University, Beijing 100875, China
| | - Hezhen Lou
- College of Water Sciences, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China.
| | - Zhengfang Wu
- School of Geographical Sciences, Northeast Normal University, Changchun 130024, China
| | - Shusheng Wang
- School of Geographical Sciences, Northeast Normal University, Changchun 130024, China
| | - Yujia Zhang
- College of Water Sciences, Beijing Normal University, Beijing 100875, China
| | - Zihao Pan
- College of Water Sciences, Beijing Normal University, Beijing 100875, China
| | - Chaojun Li
- College of Water Sciences, Beijing Normal University, Beijing 100875, China
| |
Collapse
|
22
|
Zheng Z. Climate Controls on the Spatial Variability of Vegetation Greenup Rate across Ecosystems in Northern Hemisphere. PLANTS (BASEL, SWITZERLAND) 2022; 11:2971. [PMID: 36365427 PMCID: PMC9653628 DOI: 10.3390/plants11212971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 10/29/2022] [Accepted: 10/31/2022] [Indexed: 06/16/2023]
Abstract
Variations in individual phenological events in response to global change have received considerable attentions. However, the development of phenological stages is relatively neglected, especially based on in situ observation data. In this study, the rate of vegetation greenup (Vgreenup) across the Northern Hemisphere was examined for different plant functional types (PFTs) by using eddy covariance flux data from 40 sites (417 site-years). Then, the controls of climatic variables on the spatial distribution of Vgreenup across PFTs were further investigated. The mean Vgreenup was 0.22 ± 0.11 g C m-2 day-2 across all sites, with the largest and lowest values observed in cropland and evergreen needle-leaf forest, respectively. A strong latitude dependence by Vgreenup was observed in both Europe and North America. The spatial variations of Vgreenup were jointly regulated by the duration of greenup (Dgreenup) and the amplitude of greenup (Agreenup). However, the predominant factor was Dgreenup in Europe, which changed to Agreenup in North America. Spring climatic factors exerted significant influences on the spatial distribution of Vgreenup across PFTs. Specifically, increasing temperature tended to shorten Dgreenup and promote Agreenup simultaneously, resulting in an acceleration of Vgreenup. Dryness had a depression effect on Vgreenup for the whole study area, as exhibited by a lower Vgreenup with increasing vapor pressure deficit or decreasing soil moisture. However, Vgreenup in North America was only significantly and positively correlated with temperature. Without the limitation of other climatic factors, the temperature sensitivity of Vgreenup was higher in North America (0.021 g C m-2 day-2 °C-1) than in Europe (0.015 g C m-2 day-2 °C-1). This study provides new cognitions for Vgreenup dynamics from in situ observations in complement to satellite observations, which can improve our understanding of terrestrial carbon cycles.
Collapse
Affiliation(s)
- Zhoutao Zheng
- 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 100101, China
| |
Collapse
|
23
|
Wang H, Zhan J, Wang C, Liu W, Yang Z, Liu H, Bai C. Greening or browning? The macro variation and drivers of different vegetation types on the Qinghai-Tibetan Plateau from 2000 to 2021. FRONTIERS IN PLANT SCIENCE 2022; 13:1045290. [PMID: 36388493 PMCID: PMC9643839 DOI: 10.3389/fpls.2022.1045290] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 10/11/2022] [Indexed: 06/16/2023]
Abstract
Vegetation greenness is one of the main indicators to characterize changes in terrestrial ecosystems. China has implemented a few large-scale ecological restoration programs on the Qinghai-Tibetan Plateau (QTP) to reverse the trend of ecosystem degradation. Although the effectiveness of these programs is beginning to show, the mechanisms of vegetation degradation under climate change and human activities are still controversial. Existing studies have mostly focused on changes in overall vegetation change, with less attention on the drivers of change in different vegetation types. In this study, earth satellite observation records were used to robustly map changes in vegetation greenness on the QTP from 2000 to 2021. The random forest (RF) algorithm was further used to detect the drivers of greenness browning on the QTP as a whole and in seven different vegetation types. The results show that an overall trend of greening in all seven vegetation types on the QTP over a 21-year period. The area of greening was 46.54×104 km2, and browning was 5.32×104 km2, representing a quarter and 2.86% of the natural vegetation area, respectively. The results of the browning driver analysis show that areas with high altitude, reduced annual precipitation, high intensity of human activity, average annual maximum and average annual minimum precipitation of approximately 500 mm are most susceptible to browning on the QTP. For the seven different vegetation types, their top 6 most important browning drivers and the ranking of drivers differed. DEM and precipitation changes are important drivers of browning for seven vegetation types. These results reflect the latest spatial and temporal dynamics of vegetation on the QTP and highlight the common and characteristic browning drivers of vegetation ecosystems. They provide support for understanding the response of different vegetation to natural and human impacts and for further implementation of site-specific restoration measures.
Collapse
Affiliation(s)
- Huihui Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China
| | - Jinyan Zhan
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China
| | - Chao Wang
- School of Labor Economics, Capital University of Economics and Business, Beijing, China
| | - Wei Liu
- College of Geography and Environment, Shandong Normal University, Jinan, China
| | - Zheng Yang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China
| | - Huizi Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China
| | - Chunyue Bai
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China
| |
Collapse
|
24
|
Liu Y, Liu H, Chen Y, Gang C, Shen Y. Quantifying the contributions of climate change and human activities to vegetation dynamic in China based on multiple indices. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 838:156553. [PMID: 35690202 DOI: 10.1016/j.scitotenv.2022.156553] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 06/03/2022] [Accepted: 06/04/2022] [Indexed: 06/15/2023]
Abstract
Distinguishing the respective roles of climate change and anthropogenic activities can provide crucial information for sustainable management of the environment. Here, using the residual trend method (RESTREND), which measures the residue of the actual and potential trends of vegetation, we quantified the relative contributions of human activities (e.g., ecological restoration, overgrazing, and urbanization) and climate change (the warmer and wetter trend) to vegetation dynamics in China during 1988-2018 based on multiple vegetation indices, including the vegetation optical depth (Ku-VOD, C-VOD), normalized difference vegetation index (NDVI), and gross primary productivity (GPP). The results showed that the VOD, NDVI, and GPP exhibited overall increasing trends during 1988-2018. Human activities contributed >70% to the increases in NDVI and GPP in China, whereas a counterbalanced contribution of human activities and climate change was identified for the VOD dynamics (51% vs. 49%). Regions with high contributions from human activities to NDVI, GPP, and VOD were located in northeastern, southern, central, and northwestern China. In northern China, the positive impacts of human activities on NDVI (78%) and BEPS-GPP (83%) were greater than those of climate change. In contrast, human activities contributed 96% to the decrease in Ku-VOD over the same period. Before 2000, climate change promoted increases in GPP and NDVI in most regions of southern China. The increasing rates of GPP and NDVI accelerated after 2000 due to afforestation. However, human activities like overgrazing and urbanization have led to decreases in Ku-VOD in northern and southwestern China, and in C-VOD in northeastern, eastern, central, southwestern, and southern China. In all, the relative roles of climate and human factors varied in different regions when NDVI, GPP, or VOD were individually considered. Our results highlighted that the regional-scale vegetation conditions should be taken into full account to achieve sustainable management of ecosystems.
Collapse
Affiliation(s)
- Yue Liu
- College of Grassland Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Huanhuan Liu
- College of Grassland Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yin Chen
- College of Grassland Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Chengcheng Gang
- Institute of Soil and Water Conservation, Northwest A&F University, Yangling, Shaanxi 712100, China; Institute of Soil and Water Conservation, Chinese Academy of Science and Ministry of Water Resources, Yangling, Shaanxi 712100, China.
| | - Yifan Shen
- College of Grassland Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
| |
Collapse
|
25
|
Wang X, Wang R, Gao J. Precipitation and soil nutrients determine the spatial variability of grassland productivity at large scales in China. FRONTIERS IN PLANT SCIENCE 2022; 13:996313. [PMID: 36160972 PMCID: PMC9505511 DOI: 10.3389/fpls.2022.996313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Accepted: 08/17/2022] [Indexed: 06/16/2023]
Abstract
Changes in net primary productivity (NPP) to global change have been studied, yet the relative impacts of global change on grassland productivity at large scales remain poorly understood. Using 182 grassland samples established in 17 alpine meadows (AM) and 21 desert steppes (DS) in China, we show that NPP of AM was significantly higher than that of DS. NPP increased significantly with increasing leaf nitrogen content (LN) and leaf phosphorus content (LP) but decreased significantly with increasing leaf dry matter content (LDMC). Among all abiotic factors, soil nutrient factor was the dominant factor affecting the variation of NPP of AM, while the NPP of DS was mainly influenced by the changing of precipitation. All abiotic factors accounted for 62.4% of the spatial variation in the NPP of AM, which was higher than the ability to explain the spatial variation in the NPP of DS (43.5%). Leaf traits together with soil nutrients and climatic factors determined the changes of the grassland productivity, but the relative contributions varied somewhat among different grassland types. We quantified the effects of biotic and abiotic factors on grassland NPP, and provided theoretical guidance for predicting the impacts of global change on the NPP of grasslands.
Collapse
Affiliation(s)
- Xianxian Wang
- College of Life Sciences, Xinjiang Normal University, Urumqi, China
| | - Ru Wang
- College of Life Sciences, Xinjiang Normal University, Urumqi, China
| | - Jie Gao
- College of Life Sciences, Xinjiang Normal University, Urumqi, China
- Institute of Ecology and Key Laboratory of Earth Surface Processes of Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, China
| |
Collapse
|
26
|
Kuai L, Parazoo NC, Shi M, Miller CE, Baker I, Bloom AA, Bowman K, Lee M, Zeng Z, Commane R, Montzka SA, Berry J, Sweeney C, Miller JB, Yung YL. Quantifying Northern High Latitude Gross Primary Productivity (GPP) Using Carbonyl Sulfide (OCS). GLOBAL BIOGEOCHEMICAL CYCLES 2022; 36:e2021GB007216. [PMID: 36590828 PMCID: PMC9787914 DOI: 10.1029/2021gb007216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 07/21/2022] [Accepted: 08/08/2022] [Indexed: 06/17/2023]
Abstract
The northern high latitude (NHL, 40°N to 90°N) is where the second peak region of gross primary productivity (GPP) other than the tropics. The summer NHL GPP is about 80% of the tropical peak, but both regions are still highly uncertain (Norton et al. 2019, https://doi.org/10.5194/bg-16-3069-2019). Carbonyl sulfide (OCS) provides an important proxy for photosynthetic carbon uptake. Here we optimize the OCS plant uptake fluxes across the NHL by fitting atmospheric concentration simulation with the GEOS-CHEM global transport model to the aircraft profiles acquired over Alaska during NASA's Carbon in Arctic Reservoirs Vulnerability Experiment (2012-2015). We use the empirical biome-specific linear relationship between OCS plant uptake flux and GPP to derive the six plant uptake OCS fluxes from different GPP data. Such GPP-based fluxes are used to drive the concentration simulations. We evaluate the simulations against the independent observations at two ground sites of Alaska. The optimized OCS fluxes suggest the NHL plant uptake OCS flux of -247 Gg S year-1, about 25% stronger than the ensemble mean of the six GPP-based OCS fluxes. GPP-based OCS fluxes systematically underestimate the peak growing season across the NHL, while a subset of models predict early start of season in Alaska, consistent with previous studies of net ecosystem exchange. The OCS optimized GPP of 34 PgC yr-1 for NHL is also about 25% more than the ensembles mean from six GPP data. Further work is needed to fully understand the environmental and biotic drivers and quantify their rate of photosynthetic carbon uptake in Arctic ecosystems.
Collapse
Affiliation(s)
- Le Kuai
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | | | - Mingjie Shi
- Pacific Northwest National LaboratoryRichlandWAUSA
| | - Charles E. Miller
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Ian Baker
- Colorado State UniversityFort CollinsCOUSA
| | - Anthony A. Bloom
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Kevin Bowman
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Meemong Lee
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Zhao‐Cheng Zeng
- University of California Los AngelesJIFRESSELos AngelesCAUSA
| | - Roisin Commane
- Lamont‐Doherty Earth Observatory at Columbia UniversityPalisadesNYUSA
| | | | | | | | | | - Yuk L. Yung
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
- California Institute of TechnologyPasadenaCAUSA
| |
Collapse
|
27
|
Assessment of climate change effects on vegetation and river hydrology in a semi-arid river basin. PLoS One 2022; 17:e0271991. [PMID: 36037176 PMCID: PMC9423654 DOI: 10.1371/journal.pone.0271991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 07/12/2022] [Indexed: 11/19/2022] Open
Abstract
Climate change plays a key role in changing vegetation productivity dynamics, which ultimately affect the hydrological cycle of a watershed through evapotranspiration (ET). Trends and correlation analysis were conducted to investigate vegetation responses across the whole Upper Jhelum River Basin (UJRB) in the northeast of Pakistan using the normalized difference vegetation index (NDVI), climate variables, and river flow data at inter-annual/monthly scales between 1982 and 2015. The spatial variability in trends calculated with the Mann-Kendall (MK) trend test on NDVI and climate data was assessed considering five dominant land use/cover types. The inter-annual NDVI in four out of five vegetation types showed a consistent increase over the 34-year study period; the exception was for herbaceous vegetation (HV), which increased until the end of the 1990s and then decreased slightly in subsequent years. In spring, significant (p<0.05) increasing trends were found in the NDVI of all vegetation types. Minimum temperature (Tmin) showed a significant increase during spring, while maximum temperature (Tmax) decreased significantly during summer. Average annual increase in Tmin (1.54°C) was much higher than Tmax (0.37°C) over 34 years in the UJRB. Hence, Tmin appears to have an enhancing effect on vegetation productivity over the UJRB. A significant increase in NDVI, Tmin and Tmax during spring may have contributed to reductions in spring river flow by enhancing evapotranspiration observed in the watershed of UJRB. These findings provide valuable information to improve our knowledge and understanding about the interlinkages between vegetation, climate and river flow at a watershed scale.
Collapse
|
28
|
Revealing four decades of snow cover dynamics in the Hindu Kush Himalaya. Sci Rep 2022; 12:13443. [PMID: 35927463 PMCID: PMC9352756 DOI: 10.1038/s41598-022-17575-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 07/27/2022] [Indexed: 11/09/2022] Open
Abstract
Knowledge about the distribution and dynamics of seasonal snow cover (SSC) is of high importance for climate studies, hydrology or hazards assessment. SSC varies considerably across the Hindu Kush Himalaya both in space and time. Previous studies focused on regional investigations or the influence of snow melt on the local hydrological system. Here, we present a systematic assessment of metrics to evaluate SSC dynamics for the entire HKH at regional and basin scale based on AVHRR GAC data at a 0.05° spatial and daily temporal resolution. Our findings are based on a unique four-decade satellite-based time series of snow cover information. We reveal strong variability of SSC at all time scales. We find significantly decreasing SSC trends in individual summer and winter months and a declining tendency from mid-spring to mid-fall, indicating a shift in seasonality. Thanks to this uniquely spatio-temporally resolved long-term data basis, we can particularly highlight the unique temporally variable character of seasonal snow cover and its cross-disciplinary importance for mountain ecosystems and downstream regions.
Collapse
|
29
|
Zhang L, Yang L, Zohner CM, Crowther TW, Li M, Shen F, Guo M, Qin J, Yao L, Zhou C. Direct and indirect impacts of urbanization on vegetation growth across the world's cities. SCIENCE ADVANCES 2022; 8:eabo0095. [PMID: 35857465 PMCID: PMC9269895 DOI: 10.1126/sciadv.abo0095] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Urban environments, regarded as "harbingers" of future global change, may exert positive or negative impacts on urban vegetation growth. Because of limited ground-based experiments, the responses of vegetation to urbanization and its associated controlling factors at the global scale remain poorly understood. Here, we use satellite observations from 2001 to 2018 to quantify direct and indirect impacts of urbanization on vegetation growth in 672 worldwide cities. After controlling for the negative direct impact of urbanization on vegetation growth, we find a widespread positive indirect effect that has been increasing over time. These indirect effects depend on urban development intensity, population density, and background climate, with more pronounced positive effects in cities with cold and arid environments. We further show that vegetation responses to urbanization are modulated by a cities' developmental status. Our findings have important implications for understanding urbanization-induced impacts on vegetation and future sustainable urban development.
Collapse
Affiliation(s)
- Lei Zhang
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
| | - Lin Yang
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
- Corresponding author. (L.Y.); (C.Z.)
| | - Constantin M. Zohner
- Institute of Integrative Biology, ETH Zurich (Swiss Federal Institute of Technology), Zurich Switzerland
| | - Thomas W. Crowther
- Institute of Integrative Biology, ETH Zurich (Swiss Federal Institute of Technology), Zurich Switzerland
| | - Manchun Li
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
| | - Feixue Shen
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
| | - Mao Guo
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
| | - Jun Qin
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Ling Yao
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Chenghu Zhou
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
- Center for Ocean Remote Sensing of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China
- Corresponding author. (L.Y.); (C.Z.)
| |
Collapse
|
30
|
Ecological Dynamics and Regeneration Expansion of Treeline Ecotones in Response to Climate Change in Northern Bhutan Himalayas. FORESTS 2022. [DOI: 10.3390/f13071062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The alpine treeline ecotones are an early indicator of vegetation’s response to changes in climate, and the advancement of diffuse treeline ecotones has been associated with mean annual warming temperatures. However, the knowledge of how tree demographic size, age and population distribution, and regeneration decrease with increasing elevation and mean annual temperature remain fragmentary in Bhutan. There was no explanation of how treelines migrate in response to the climate. Therefore, the objectives of this study were to investigate tree demographic size and age and population distribution, as well as the regeneration expansion of treeline ecotones of Abies densa trees in response to climate change. Demographic data from thirty transect bands from treeline ecotones and reconstructed mean annual temperatures from tree-rings were used. Regression analysis was used to establish a relationship between elevation/temperature and demographic tree size and age, as well as to determine recruitment frequency distributions and whether these could be driven by climate change. The tree demography indicated that the treeline ecotone in our sampling site is temperature limited. Hence, cooler temperatures at higher elevations should drive decreases in basal diameter, age and recruitment frequencies. From the dendroecological analysis, the diffuse treeline ecotones appear to be climbing on average 1.00 m per year in Northern Bhutan. We also found that the recruitment frequency has increased over recent years (1850–2017), as temperatures continue to rise. The thermal treeline ecotones will be likely to serve as a line of bioclimatic reference against which other zones of bioclimate can be defined. With documented responses of treeline ecotones toward mean annual temperatures, the expectation is that additional warming will continue to influence regeneration expansion in the future. This dynamic response of treeline ecotones towards the climate acts as an indicator of climate change. Information about climbing treelines and altered ecotones should be a vital part of the material for decision makers to consider, to assess impacts and threats to Himalayan alpine biota.
Collapse
|
31
|
Liu Y, Riley WJ, Keenan TF, Mekonnen ZA, Holm JA, Zhu Q, Torn MS. Dispersal and fire limit Arctic shrub expansion. Nat Commun 2022; 13:3843. [PMID: 35788612 PMCID: PMC9253140 DOI: 10.1038/s41467-022-31597-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 06/24/2022] [Indexed: 11/08/2022] Open
Abstract
Arctic shrub expansion alters carbon budgets, albedo, and warming rates in high latitudes but remains challenging to predict due to unclear underlying controls. Observational studies and models typically use relationships between observed shrub presence and current environmental suitability (bioclimate and topography) to predict shrub expansion, while omitting shrub demographic processes and non-stationary response to changing climate. Here, we use high-resolution satellite imagery across Alaska and western Canada to show that observed shrub expansion has not been controlled by environmental suitability during 1984-2014, but can only be explained by considering seed dispersal and fire. These findings provide the impetus for better observations of recruitment and for incorporating currently underrepresented processes of seed dispersal and fire in land models to project shrub expansion and climate feedbacks. Integrating these dynamic processes with projected fire extent and climate, we estimate shrubs will expand into 25% of the non-shrub tundra by 2100, in contrast to 39% predicted based on increasing environmental suitability alone. Thus, using environmental suitability alone likely overestimates and misrepresents shrub expansion pattern and its associated carbon sink.
Collapse
Affiliation(s)
- Yanlan Liu
- School of Earth Sciences, The Ohio State University, Columbus, OH, USA.
- School of Environment and Natural Resources, The Ohio State University, Columbus, OH, USA.
| | - William J Riley
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Trevor F Keenan
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Department of Environmental Science Policy and Management, University of California, Berkeley, CA, USA
| | - Zelalem A Mekonnen
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Jennifer A Holm
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Qing Zhu
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Margaret S Torn
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| |
Collapse
|
32
|
Berner LT, Goetz SJ. Satellite observations document trends consistent with a boreal forest biome shift. GLOBAL CHANGE BIOLOGY 2022; 28:3275-3292. [PMID: 35199413 PMCID: PMC9303657 DOI: 10.1111/gcb.16121] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 01/13/2022] [Indexed: 05/03/2023]
Abstract
The boreal forest biome is a major component of Earth's biosphere and climate system that is projected to shift northward due to continued climate change over the coming century. Indicators of a biome shift will likely first be evident along the climatic margins of the boreal forest and include changes in vegetation productivity, mortality, and recruitment, as well as overall vegetation greenness. However, the extent to which a biome shift is already underway remains unclear because of the local nature of most field studies, sparsity of systematic ground-based ecological monitoring, and reliance on coarse resolution satellite observations. Here, we evaluated early indicators of a boreal forest biome shift using four decades of moderate resolution (30 m) satellite observations and biogeoclimatic spatial datasets. Specifically, we quantified interannual trends in annual maximum vegetation greenness using an ensemble of vegetation indices derived from Landsat observations at 100,000 sample sites in areas without signs of recent disturbance. We found vegetation greenness increased (greened) at 38 [29, 42] % and 22 [15, 26] % of sample sites from 1985 to 2019 and 2000 to 2019, whereas vegetation greenness decreased (browned) at 13 [9, 15] % and 15 [13, 19] % of sample sites during these respective periods [95% Monte Carlo confidence intervals]. Greening was thus 3.0 [2.6, 3.5] and 1.5 [0.8, 2.0] times more common than browning and primarily occurred in cold sparsely treed areas with high soil nitrogen and moderate summer warming. Conversely, browning primarily occurred in the climatically warmest margins of both the boreal forest biome and major forest types (e.g., evergreen conifer forests), especially in densely treed areas where summers became warmer and drier. These macroecological trends reflect underlying shifts in vegetation productivity, mortality, and recruitment that are consistent with early stages of a boreal biome shift.
Collapse
Affiliation(s)
- Logan T. Berner
- School of Informatics, Computing, and Cyber SystemsNorthern Arizona UniversityFlagstaffArizonaUSA
| | - Scott J. Goetz
- School of Informatics, Computing, and Cyber SystemsNorthern Arizona UniversityFlagstaffArizonaUSA
| |
Collapse
|
33
|
Yuan Y, Bao A, Jiapaer G, Jiang L, De Maeyer P. Phenology-based seasonal terrestrial vegetation growth response to climate variability with consideration of cumulative effect and biological carryover. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 817:152805. [PMID: 34982988 DOI: 10.1016/j.scitotenv.2021.152805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 12/06/2021] [Accepted: 12/27/2021] [Indexed: 06/14/2023]
Abstract
Vegetation growth is influenced not only by climate variability but also by its past states. However, the differences in the degree of the climate variability and past states affecting vegetation growth over seasons are still poorly understood, particularly given the cumulative climate effects. Relying on the Normalized Difference Vegetation Index (NDVI) data from 1982 to 2014, the vegetation growing season was decomposed into three periods (sub-seasons) - green-up (GSgp), maturity (GSmp), and senescence (GSsp) - following a phenology-based definition. A distributed lag model was then utilized to analyze the time-lag effect of vegetation growth response to climatic factors including precipitation, temperature, and solar radiation during each sub-season. On this basis, the relative importance of climatic factors and vegetation growth carryover (VGC) effect on vegetation growth was quantified at the phenology-based seasonal scale. Results showed that the longest peak lag of precipitation, temperature, and solar radiation occurred in the GSmp, GSsp, and GSgp, with 1.27 (1.13 SD), 0.89 (1.02 SD), and 0.80 (1.04 SD) months, respectively. The influence of climate variability was strongest in the GSgp, and diminished over the season, while the opposite for the VGC effect. The relative influence of each climatic factor also varied between sub-seasons. Vegetation in more than 58% of areas was more affected by temperature in the GSgp, and the proportion decreased to 34.00% and 31.78% in the GSmp and GSsp, respectively. Precipitation and solar radiation acted as the dominant climatic factors in only 28.80% and 20.88% of vegetation areas in the GSgp, but they increased to 35.21%, 32.61% in the GSmp, and 38.20%, 30.02% in the GSsp, respectively. The increased regions influenced by precipitation were mainly in dry areas especially for the boreal and cool temperate climate zones, while increased regions influenced by solar radiation were primarily located in moist areas of mid-high latitudes of the Northern Hemisphere. By introducing the cumulative climate effect, our findings highlight seasonal patterns of vegetation growth affected by climate variability and the VGC effect. The results provide a more comprehensive perspective on climate-vegetation interactions, which may help us to accurately forecast future vegetation growth under accelerating global warming.
Collapse
Affiliation(s)
- Ye Yuan
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing 100049, China; Department of Geography, Ghent University, Ghent 9000, Belgium
| | - Anming Bao
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; China-Pakistan Joint Research Center on Earth Sciences, CAS-HEC, Islamabad 45320, Pakistan; Sino-Belgian Laboratory for Geo-Information, Urumqi 83011, China.
| | - Guli Jiapaer
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
| | - Liangliang Jiang
- School of Geography and Tourism, Chongqing Normal University, Chongqing 401331, China
| | - Philippe De Maeyer
- Department of Geography, Ghent University, Ghent 9000, Belgium; Sino-Belgian Laboratory for Geo-Information, Ghent 9000, Belgium
| |
Collapse
|
34
|
Gao S, Liang E, Liu R, Babst F, Camarero JJ, Fu YH, Piao S, Rossi S, Shen M, Wang T, Peñuelas J. An earlier start of the thermal growing season enhances tree growth in cold humid areas but not in dry areas. Nat Ecol Evol 2022; 6:397-404. [PMID: 35228669 DOI: 10.1038/s41559-022-01668-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 01/13/2022] [Indexed: 11/09/2022]
Abstract
Climatic warming alters the onset, duration and cessation of the vegetative season. While previous studies have shown a tight link between thermal conditions and leaf phenology, less is known about the impacts of phenological changes on tree growth. Here, we assessed the relationships between the start of the thermal growing season and tree growth across the extratropical Northern Hemisphere using 3,451 tree-ring chronologies and daily climatic data for 1948-2014. An earlier start of the thermal growing season promoted growth in regions with high ratios of precipitation to temperature but limited growth in cold-dry regions. Path analyses indicated that an earlier start of the thermal growing season enhanced growth primarily by alleviating thermal limitations on wood formation in boreal forests and by lengthening the period of growth in temperate and Mediterranean forests. Semi-arid and dry subalpine forests, however, did not benefit from an earlier onset of growth and a longer growing season, presumably due to associated water loss and/or more frequent early spring frosts. These emergent patterns of how climatic impacts on wood phenology affect tree growth at regional to hemispheric scales hint at how future phenological changes may affect the carbon sequestration capacity of extratropical forest ecosystems.
Collapse
Affiliation(s)
- Shan Gao
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
| | - Eryuan Liang
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China.
| | - Ruishun Liu
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
| | - Flurin Babst
- School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA.,Laboratory of Tree-Ring Research, University of Arizona, Tucson, AZ, USA
| | | | - Yongshuo H Fu
- College of Water Sciences, Beijing Normal University, Beijing, China
| | - Shilong Piao
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China.,Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Sergio Rossi
- Département des Sciences Fondamentales, Université du Québec à Chicoutimi, Chicoutimi, Quebec, Canada.,Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
| | - Miaogen Shen
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, China
| | - Tao Wang
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
| | - Josep Peñuelas
- CREAF, Cerdanyola del Valles, Barcelona, Spain.,CSIC, Global Ecology Unit CREAF-CSIC-UAB, Barcelona, Spain
| |
Collapse
|
35
|
Wang Z, Wang H, Wang T, Wang L, Liu X, Zheng K, Huang X. Large discrepancies of global greening: Indication of multi-source remote sensing data. Glob Ecol Conserv 2022. [DOI: 10.1016/j.gecco.2022.e02016] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
|
36
|
Euskirchen ES, Serbin SP, Carman TB, Fraterrigo JM, Genet H, Iversen CM, Salmon V, McGuire AD. Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2022; 32:e2499. [PMID: 34787932 PMCID: PMC9285828 DOI: 10.1002/eap.2499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 06/22/2021] [Accepted: 07/20/2021] [Indexed: 06/13/2023]
Abstract
As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near Utqiaġvik to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive to parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change.
Collapse
Affiliation(s)
| | - Shawn P. Serbin
- Terrestrial Ecosystem Science & Technology GroupEnvironmental Sciences DepartmentBrookhaven National LaboratoryUptonNew York11973USA
| | - Tobey B. Carman
- Institute of Arctic BiologyUniversity of Alaska FairbanksFairbanksAlaska99775USA
| | - Jennifer M. Fraterrigo
- Department of Natural Resources and Environmental SciencesUniversity of Illinois at Urbana‐ChampaignUrbanaIllinois61801USA
| | - Hélène Genet
- Institute of Arctic BiologyUniversity of Alaska FairbanksFairbanksAlaska99775USA
| | - Colleen M. Iversen
- Environmental Sciences Division and Climate Change Science InstituteOak Ridge National LaboratoryOak RidgeTennessee37831USA
| | - Verity Salmon
- Environmental Sciences Division and Climate Change Science InstituteOak Ridge National LaboratoryOak RidgeTennessee37831USA
| | - A. David McGuire
- Institute of Arctic BiologyUniversity of Alaska FairbanksFairbanksAlaska99775USA
| |
Collapse
|
37
|
Dror I, Yaron B, Berkowitz B. The Human Impact on All Soil-Forming Factors during the Anthropocene. ACS ENVIRONMENTAL AU 2022; 2:11-19. [PMID: 37101758 PMCID: PMC10114744 DOI: 10.1021/acsenvironau.1c00010] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
Soil-the thin outer skin of the Earth's land-is a critical and fragile natural resource. Soil is the basis for almost all global agriculture and the medium in which most terrestrial biological activity occurs. Here, we reconsider the five forming factors of soil originally suggested more than a century ago (parent material, time, climate, topography, and organisms) and updated over the years to add human activity as the sixth forming factor. We demonstrate how present anthropogenic activity has become the leading component influencing each one of the original forming factors. We thus propose that, starting from the Anthropocene, human activity should no longer be considered as a separate forming factor but rather a main driving force of each of the five original ones. We suggest that the importance of soil and the strong direct and indirect effects of anthropogenic factors on soil-forming factors should be considered together to ensure sustainability of this critical resource.
Collapse
|
38
|
A Pixel-Based Vegetation Greenness Trend Analysis over the Russian Tundra with All Available Landsat Data from 1984 to 2018. REMOTE SENSING 2021. [DOI: 10.3390/rs13234933] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
As Arctic warming continues, its impact on vegetation greenness is complex, variable and inherently scale-dependent. Studies with multiple spatial resolution satellite observations, with 30 m resolution included, on tundra greenness have been implemented all over the North American tundra. However, finer resolution studies on the greenness trends in the Russian tundra have only been carried out at a limited local or regional scale and the spatial heterogeneity of the trend remains unclear. Here, we analyzed the fine spatial resolution dataset Landsat archive from 1984 to 2018 over the entire Russian tundra and produced pixel-by-pixel greenness trend maps with the support of Google Earth Engine (GEE). The entire Russian tundra was divided into six geographical regions based on World Wildlife Fund (WWF) ecoregions. A Theil–Sen regression (TSR) was used for the trend identification and the changed pixels with a significance level p < 0.05 were retained in the final results for a subsequent greening/browning trend analysis. Our results indicated that: (1) the number of valid Landsat observations was spatially varied. The Western and Eastern European Tundras (WET and EET) had denser observations than other regions, which enabled a trend analysis during the whole study period from 1984 to 2018; (2) the most significant greening occurred in the Yamal-Gydan tundra (WET), Bering tundra and Chukchi Peninsula tundra (CT) during 1984–2018. The EET had a greening trend of 2.3% and 6.6% and the WET of 3.4% and 18% during 1984–1999 and 2000–2018, respectively. The area of browning trend was relatively low when we first masked the surface water bodies out before the trend analysis; and (3) the Landsat-based greenness trend was broadly similar to the AVHRR-based trend over the entire region but AVHRR retrieved more browning areas due to spectral mixing adjacent effects. Higher resolution images and field measurement studies are strongly needed to understand the vegetation trend over the Russian tundra ecosystem.
Collapse
|
39
|
Choler P, Bayle A, Carlson BZ, Randin C, Filippa G, Cremonese E. The tempo of greening in the European Alps: Spatial variations on a common theme. GLOBAL CHANGE BIOLOGY 2021; 27:5614-5628. [PMID: 34478202 DOI: 10.1111/gcb.15820] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 07/13/2021] [Indexed: 06/13/2023]
Abstract
The long-term increase in satellite-based proxies of vegetation cover is a well-documented response of seasonally snow-covered ecosystems to climate warming. However, observed greening trends are far from uniform, and substantial uncertainty remains concerning the underlying causes of this spatial variability. Here, we processed surface reflectance of the moderate resolution imaging spectroradiometer (MODIS) to investigate trends and drivers of changes in the annual peak values of the Normalized Difference Vegetation Index (NDVI). Our study focuses on above-treeline ecosystems in the European Alps. NDVI changes in these ecosystems are highly sensitive to land cover and biomass changes and are marginally affected by anthropogenic disturbances. We observed widespread greening for the 2000-2020 period, a pattern that is consistent with the overall increase in summer temperature. At the local scale, the spatial variability of greening was mainly due to the preferential response of north-facing slopes between 1900 and 2400 m. Using high-resolution imagery, we noticed that the presence of screes and outcrops locally magnified this response. At the regional scale, we identified hotspots of greening where vegetation cover is sparser than expected given the elevation and exposure. Most of these hotspots experienced delayed snow melt and green-up dates in recent years. We conclude that the ongoing greening in the Alps primarily reflects the high responsiveness of sparsely vegetated ecosystems that are able to benefit the most from temperature and water-related habitat amelioration above treeline.
Collapse
Affiliation(s)
- Philippe Choler
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Arthur Bayle
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Bradley Z Carlson
- Centre de Recherches sur les Écosystèmes d'Altitude (CREA), Chamonix, France
| | - Christophe Randin
- Department of Ecology & Evolution/Interdisciplinary Centre for Mountain Research (CIRM), Université de Lausanne, Lausanne, Switzerland
| | - Gianluca Filippa
- Climate Change Unit, Environmental Protection Agency of Aosta Valley, Saint-Christophe, Italy
| | - Edoardo Cremonese
- Climate Change Unit, Environmental Protection Agency of Aosta Valley, Saint-Christophe, Italy
| |
Collapse
|
40
|
Diao C, Liu Y, Zhao L, Zhuo G, Zhang Y. Regional-scale vegetation-climate interactions on the Qinghai-Tibet Plateau. ECOL INFORM 2021. [DOI: 10.1016/j.ecoinf.2021.101413] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
|
41
|
Sigdel SR, Pandey J, Liang E, Muhammad S, Babst F, Leavitt SW, Shen M, Zhu H, Salerno F, Piao S, Camarero JJ, Peñuelas J. No benefits from warming even for subnival vegetation in the central Himalayas. Sci Bull (Beijing) 2021; 66:1825-1829. [PMID: 36654391 DOI: 10.1016/j.scib.2021.06.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Revised: 05/10/2021] [Accepted: 05/11/2021] [Indexed: 02/03/2023]
Affiliation(s)
- Shalik Ram Sigdel
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Jayram Pandey
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Eryuan Liang
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Sher Muhammad
- International Centre for Integrated Mountain Development (ICIMOD), Kathmandu, Nepal; Institute of International Rivers and Eco-security, Yunnan University, Kunming 650500, China
| | - Flurin Babst
- School of Natural Resources and the Environment, University of Arizona, Tucson, AZ 85721, USA; Laboratory of Tree-Ring Research, University of Arizona, Tucson, AZ 85721, USA
| | - Steven W Leavitt
- Laboratory of Tree-Ring Research, University of Arizona, Tucson, AZ 85721, USA
| | - Miaogen Shen
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Haifeng Zhu
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Franco Salerno
- Water Research Institute-National Research Council (IRSA-CNR), Brugherio 20861, Italy
| | - Shilong Piao
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - J Julio Camarero
- Instituto Pirenaico de Ecología (IPE-CSIC), Zaragoza 50080, Spain
| | - Josep Peñuelas
- CSIC, Global Ecology Unit CREAF-CSIC-UAB, Cerdanyola del Vallès, Catalonia 08913, Spain; CREAF, Cerdanyola del Vallès, Catalonia 08913, Spain.
| |
Collapse
|
42
|
Sang Y, Huang L, Wang X, Keenan TF, Wang C, He Y. Comment on "Recent global decline of CO 2 fertilization effects on vegetation photosynthesis". Science 2021; 373:eabg4420. [PMID: 34554773 DOI: 10.1126/science.abg4420] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
[Figure: see text].
Collapse
Affiliation(s)
- Yuxing Sang
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Ling Huang
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Xuhui Wang
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Trevor F Keenan
- Department of Environmental Science, Policy and Management, University of California, Berkeley, CA 94720, USA.,Earth and Environmental Science Area, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Chenzhi Wang
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Yue He
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| |
Collapse
|
43
|
Inconsistency of Global Vegetation Dynamics Driven by Climate Change: Evidences from Spatial Regression. REMOTE SENSING 2021. [DOI: 10.3390/rs13173442] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Global greening over the past 30 years since 1980s has been confirmed by numerous studies. However, a single-dimensional indicator and non-spatial modelling approaches might exacerbate uncertainties in our understanding of global change. Thus, comprehensive monitoring for vegetation’s various properties and spatially explicit models are required. In this study, we used the newest enhanced vegetation index (EVI) products of Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 to detect the inconsistency trend of annual peak and average global vegetation growth using the Mann–Kendall test method. We explored the climatic factors that affect vegetation growth change from 2001 to 2018 using the spatial lag model (SLM), spatial error model (SEM) and geographically weighted regression model (GWR). The results showed that EVImax and EVImean in global vegetated areas consistently showed linear increasing trends during 2001–2018, with the global averaged trend of 0.0022 yr−1 (p < 0.05) and 0.0030 yr−1 (p < 0.05). Greening mainly occurred in the croplands and forests of China, India, North America and Europe, while browning was almost in the grasslands of Brazil and Africa (18.16% vs. 3.08% and 40.73% vs. 2.45%). In addition, 32.47% of the global vegetated area experienced inconsistent trends in EVImax and EVImean. Overall, precipitation and mean temperature had positive impacts on vegetation variation, while potential evapotranspiration and vapour pressure had negative impacts. The GWR revealed that the responses of EVI to climate change were inconsistent in an arid or humid area, in cropland or grassland. Climate change could affect vegetation characteristics by changing plant phenology, consequently rendering the inconsistency between peak and mean greening. In addition, anthropogenic activities, including land cover change and land use management, also could lead to the differences between annual peak and mean vegetation variations.
Collapse
|
44
|
BVOC Emissions From a Subarctic Ecosystem, as Controlled by Insect Herbivore Pressure and Temperature. Ecosystems 2021. [DOI: 10.1007/s10021-021-00690-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Abstract
The biogenic volatile organic compounds, BVOCs have a central role in ecosystem–atmosphere interactions. High-latitude ecosystems are facing increasing temperatures and insect herbivore pressure, which may affect their BVOC emission rates, but evidence and predictions of changes remain scattered. We studied the long-term effects of + 3 °C warming and reduced insect herbivory (achieved through insecticide sprayings) on mid- and late summer BVOC emissions from field layer vegetation, supplemented with birch saplings, and the underlying soil in Subarctic mountain birch forest in Finland in 2017–2018. Reduced insect herbivory decreased leaf damage by 58–67% and total ecosystem BVOC emissions by 44–72%. Of the BVOC groups, total sesquiterpenes had 70–80% lower emissions with reduced herbivory, and in 2017 the decrease was greater in warmed plots (89% decrease) than in ambient plots (34% decrease). While non-standardized total BVOC, monoterpene, sesquiterpene and GLV emissions showed instant positive responses to increasing chamber air temperature in midsummer samplings, the long-term warming treatment effects on standardized emissions mainly appeared as changes in the compound structure of BVOC blends and varied with compounds and sampling times. Our results suggest that the effects of climate warming on the total quantity of BVOC emissions will in Subarctic ecosystems be, over and above the instant temperature effects, mediated through changes in insect herbivore pressure rather than plant growth. If insect herbivore numbers will increase as predicted under climate warming, our results forecast herbivory-induced increases in the quantity of Subarctic BVOC emissions.
Graphic Abstract
Collapse
|
45
|
Gao X, Huang X, Lo K, Dang Q, Wen R. Vegetation responses to climate change in the Qilian Mountain Nature Reserve, Northwest China. Glob Ecol Conserv 2021. [DOI: 10.1016/j.gecco.2021.e01698] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
|
46
|
Chen Z, Liu H, Xu C, Wu X, Liang B, Cao J, Chen D. Modeling vegetation greenness and its climate sensitivity with deep-learning technology. Ecol Evol 2021; 11:7335-7345. [PMID: 34188816 PMCID: PMC8216928 DOI: 10.1002/ece3.7564] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 03/29/2021] [Indexed: 12/30/2022] Open
Abstract
Climate sensitivity of vegetation has long been explored using statistical or process-based models. However, great uncertainties still remain due to the methodologies' deficiency in capturing the complex interactions between climate and vegetation. Here, we developed global gridded climate-vegetation models based on long short-term memory (LSTM) network, which is a powerful deep-learning algorithm for long-time series modeling, to achieve accurate vegetation monitoring and investigate the complex relationship between climate and vegetation. We selected the normalized difference vegetation index (NDVI) that represents vegetation greenness as model outputs. The climate data (monthly temperature and precipitation) were used as inputs. We trained the networks with data from 1982 to 2003, and the data from 2004 to 2015 were used to validate the models. Error analysis and sensitivity analysis were performed to assess the model errors and investigate the sensitivity of global vegetation to climate change. Results show that models based on deep learning are very effective in simulating and predicting the vegetation greenness dynamics. For models training, the root mean square error (RMSE) is <0.01. Model validation also assure the accuracy of our models. Furthermore, sensitivity analysis of models revealed a spatial pattern of global vegetation to climate, which provides us a new way to investigate the climate sensitivity of vegetation. Our study suggests that it is a good way to integrate deep-learning method to monitor the vegetation change under global change. In the future, we can explore more complex climatic and ecological systems with deep learning and coupling with certain physical process to better understand the nature.
Collapse
Affiliation(s)
- Zhiting Chen
- College of Urban and Environmental Sciences and MOE Laboratory for Earth Surface ProcessesPeking UniversityBeijingChina
| | - Hongyan Liu
- College of Urban and Environmental Sciences and MOE Laboratory for Earth Surface ProcessesPeking UniversityBeijingChina
| | - Chongyang Xu
- College of Urban and Environmental Sciences and MOE Laboratory for Earth Surface ProcessesPeking UniversityBeijingChina
| | - Xiuchen Wu
- Faculty of Geographical SciencesBeijing Normal UniversityBeijingChina
| | - Boyi Liang
- College of Urban and Environmental Sciences and MOE Laboratory for Earth Surface ProcessesPeking UniversityBeijingChina
| | - Jing Cao
- College of Urban and Environmental Sciences and MOE Laboratory for Earth Surface ProcessesPeking UniversityBeijingChina
| | - Deliang Chen
- August Röhss ChairDepartment of Earth SciencesUniversity of GothenburgGothenburgSweden
| |
Collapse
|
47
|
Zhao W, Yu X, Jiao C, Xu C, Liu Y, Wu G. Increased association between climate change and vegetation index variation promotes the coupling of dominant factors and vegetation growth. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 767:144669. [PMID: 33429281 DOI: 10.1016/j.scitotenv.2020.144669] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Revised: 12/15/2020] [Accepted: 12/15/2020] [Indexed: 06/12/2023]
Abstract
Vegetation productivity dynamics are closely related to climate change, and water availability determines vegetation growth in water-limited ecosystems. Nevertheless, how changes in the interactions between climatic factors and vegetation activity variation regulate the relationship between their trends remains unclear. The Normalized Difference Vegetation Index (NDVI) is an effective proxy of vegetation growth. First, we investigated the NDVI trends, and the results revealed a vegetation activity with weaker greening and greater spatial heterogeneity after an obvious land-cover breakpoint in 1999 compared with that before 1999 in northwest China. Notably, the Loess Plateau greatly led the greenness trends, but the Tibet Plateau showed mean browning after 1999, which implied that the coupling of climate change and vegetation trends varied with spatio-temporal changes. Subsequently, using the Geographical Detector Method (GDM), we quantified and compared the association between climate change and the interannual variability of NDVI in the two stages. Vegetation productivity variation is more closely related to changes in climatic factors after 1999 compared with that before 1999. Precipitation (PPT) and vapor pressure deficit (VPD) are the primary constraints to vegetation growth in both stages. Patterns in NDVI trend increases are consistent with those of increased PPT and decreased VPD and vice versa after 1999. However, the same patterns were not observed before 1999 because of the weak association between climate change and NDVI variation. This implicated a great significance of the association between climate change and changes in vegetation activity for the prediction of potential carbon sequestration due to the shift of dominant factors and their trends under future climate change.
Collapse
Affiliation(s)
- Wei Zhao
- 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
| | - Xiubo Yu
- 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; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China.
| | - Cuicui Jiao
- College of Economics, Sichuan University of Science & Engineering, Yibin 644000, China
| | - Chengdong Xu
- 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; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Yu Liu
- 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; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Genan Wu
- 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; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China; Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| |
Collapse
|
48
|
Walker AP, De Kauwe MG, Bastos A, Belmecheri S, Georgiou K, Keeling RF, McMahon SM, Medlyn BE, Moore DJP, Norby RJ, Zaehle S, Anderson-Teixeira KJ, Battipaglia G, Brienen RJW, Cabugao KG, Cailleret M, Campbell E, Canadell JG, Ciais P, Craig ME, Ellsworth DS, Farquhar GD, Fatichi S, Fisher JB, Frank DC, Graven H, Gu L, Haverd V, Heilman K, Heimann M, Hungate BA, Iversen CM, Joos F, Jiang M, Keenan TF, Knauer J, Körner C, Leshyk VO, Leuzinger S, Liu Y, MacBean N, Malhi Y, McVicar TR, Penuelas J, Pongratz J, Powell AS, Riutta T, Sabot MEB, Schleucher J, Sitch S, Smith WK, Sulman B, Taylor B, Terrer C, Torn MS, Treseder KK, Trugman AT, Trumbore SE, van Mantgem PJ, Voelker SL, Whelan ME, Zuidema PA. Integrating the evidence for a terrestrial carbon sink caused by increasing atmospheric CO 2. THE NEW PHYTOLOGIST 2021; 229:2413-2445. [PMID: 32789857 DOI: 10.1111/nph.16866] [Citation(s) in RCA: 130] [Impact Index Per Article: 43.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 07/06/2020] [Indexed: 05/22/2023]
Abstract
Atmospheric carbon dioxide concentration ([CO2 ]) is increasing, which increases leaf-scale photosynthesis and intrinsic water-use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO2 ] increase and thus climate change. However, ecosystem CO2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO2 ]-driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO2 ] (iCO2 ) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre-industrial times. Established theory, supported by experiments, indicates that iCO2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO2 responses are high in comparison to experiments and predictions from theory. Plant mortality and soil carbon iCO2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO2 , albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.
Collapse
Affiliation(s)
- Anthony P Walker
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Martin G De Kauwe
- ARC Centre of Excellence for Climate Extremes, University of New South Wales, Sydney, NSW, 2052, Australia
- Climate Change Research Centre, University of New South Wales, Sydney, NSW, 2052, Australia
- Evolution and Ecology Research Centre, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Ana Bastos
- Ludwig Maximilians University of Munich, Luisenstr. 37, Munich, 80333, Germany
| | - Soumaya Belmecheri
- Laboratory of Tree Ring Research, University of Arizona, 1215 E Lowell St, Tucson, AZ, 85721, USA
| | - Katerina Georgiou
- Department of Earth System Science, Stanford University, Stanford, CA, 94305, USA
| | - Ralph F Keeling
- Scripps Institution of Oceanography, UC San Diego, La Jolla, CA, 92093, USA
| | - Sean M McMahon
- Smithsonian Environmental Research Center, Edgewater, MD, 21037, USA
| | - Belinda E Medlyn
- Hawkesbury Institute for the Environment, Western Sydney University, Locked Bag 1797, Penrith, NSW, 2751, Australia
| | - David J P Moore
- School of Natural Resources and the Environment, 1064 East Lowell Street, Tucson, AZ, 85721, USA
| | - Richard J Norby
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Sönke Zaehle
- Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, Jena, 07745, Germany
| | - Kristina J Anderson-Teixeira
- Conservation Ecology Center, Smithsonian Conservation Biology Institute, MRC 5535, Front Royal, VA, 22630, USA
- Center for Tropical Forest Science-Forest Global Earth Observatory, Smithsonian Tropical Research Institute, Panama City, Panama
| | - Giovanna Battipaglia
- Department of Environmental, Biological and Pharmaceutical Sciences and Technologies, Università della Campania, Caserta, 81100, Italy
| | | | - Kristine G Cabugao
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Maxime Cailleret
- INRAE, UMR RECOVER, Aix-Marseille Université, 3275 route de Cézanne, Aix-en-Provence Cedex 5, 13182, France
- Swiss Federal Institute for Forest Snow and Landscape Research (WSL), Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
| | - Elliott Campbell
- Department of Geography, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Josep G Canadell
- CSIRO Oceans and Atmosphere, GPO Box 1700, Canberra, ACT, 2601, Australia
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, F-91191, France
| | - Matthew E Craig
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - David S Ellsworth
- Hawkesbury Institute for the Environment, Western Sydney University, Locked Bag 1797, Penrith, NSW, 2751, Australia
| | - Graham D Farquhar
- Plant Sciences, Research School of Biology, The Australian National University, Canberra, ACT, 2601, Australia
| | - Simone Fatichi
- Department of Civil and Environmental Engineering, National University of Singapore, 1 Engineering Drive 2, Singapore, 117576, Singapore
- Institute of Environmental Engineering, ETH Zurich, Stefano-Franscini Platz 5, Zurich, 8093, Switzerland
| | - Joshua B Fisher
- Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA, 91109, USA
| | - David C Frank
- Laboratory of Tree Ring Research, University of Arizona, 1215 E Lowell St, Tucson, AZ, 85721, USA
| | - Heather Graven
- Department of Physics, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK
| | - Lianhong Gu
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Vanessa Haverd
- CSIRO Oceans and Atmosphere, GPO Box 1700, Canberra, ACT, 2601, Australia
| | - Kelly Heilman
- Laboratory of Tree Ring Research, University of Arizona, 1215 E Lowell St, Tucson, AZ, 85721, USA
| | - Martin Heimann
- Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, Jena, 07745, Germany
| | - Bruce A Hungate
- Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, 86011, USA
| | - Colleen M Iversen
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Fortunat Joos
- Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Sidlerstr. 5, Bern, CH-3012, Switzerland
| | - Mingkai Jiang
- Hawkesbury Institute for the Environment, Western Sydney University, Locked Bag 1797, Penrith, NSW, 2751, Australia
| | - Trevor F Keenan
- Department of Environmental Science, Policy and Management, UC Berkeley, Berkeley, CA, 94720, USA
- Earth and Environmental Sciences Area, Lawrence Berkeley National Lab., Berkeley, CA, 94720, USA
| | - Jürgen Knauer
- CSIRO Oceans and Atmosphere, GPO Box 1700, Canberra, ACT, 2601, Australia
| | - Christian Körner
- Department of Environmental Sciences, Botany, University of Basel, Basel, 4056, Switzerland
| | - Victor O Leshyk
- Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, 86011, USA
| | - Sebastian Leuzinger
- School of Science, Auckland University of Technology, Auckland, 1142, New Zealand
| | - Yao Liu
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Natasha MacBean
- Department of Geography, Indiana University, Bloomington, IN, 47405, USA
| | - Yadvinder Malhi
- School of Geography and the Environment, University of Oxford, Oxford, OX1 3QY, UK
| | - Tim R McVicar
- CSIRO Land and Water, GPO Box 1700, Canberra, ACT, 2601, Australia
- Australian Research Council Centre of Excellence for Climate Extremes, 142 Mills Rd, Australian National University, Canberra, ACT, 2601, Australia
| | - Josep Penuelas
- CSIC, Global Ecology CREAF-CSIC-UAB, Bellaterra, Barcelona, Catalonia, 08193, Spain
- CREAF, Cerdanyola del Vallès, Barcelona, Catalonia, 08193, Spain
| | - Julia Pongratz
- Ludwig Maximilians University of Munich, Luisenstr. 37, Munich, 80333, Germany
- Max Planck Institute for Meteorology, Bundesstr. 53, 20146 Hamburg, Germany
| | - A Shafer Powell
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Terhi Riutta
- School of Geography and the Environment, University of Oxford, Oxford, OX1 3QY, UK
| | - Manon E B Sabot
- ARC Centre of Excellence for Climate Extremes, University of New South Wales, Sydney, NSW, 2052, Australia
- Climate Change Research Centre, University of New South Wales, Sydney, NSW, 2052, Australia
- Evolution and Ecology Research Centre, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Juergen Schleucher
- Department of Medical Biochemistry & Biophysics, Umeå University, Umea, 901 87, Sweden
| | - Stephen Sitch
- College of Life and Environmental Sciences, University of Exeter, Exeter, Laver Building, EX4 4QF, UK
| | - William K Smith
- School of Natural Resources and the Environment, 1064 East Lowell Street, Tucson, AZ, 85721, USA
| | - Benjamin Sulman
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Benton Taylor
- Smithsonian Environmental Research Center, Edgewater, MD, 21037, USA
| | - César Terrer
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, 94550, USA
| | - Margaret S Torn
- Earth and Environmental Sciences Area, Lawrence Berkeley National Lab., Berkeley, CA, 94720, USA
| | - Kathleen K Treseder
- Department of Ecology and Evolutionary Biology, University of California Irvine, Irvine, CA, 92697, USA
| | - Anna T Trugman
- Department of Geography, 1832 Ellison Hall, Santa Barbara, CA, 93016, USA
| | - Susan E Trumbore
- Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, Jena, 07745, Germany
| | | | - Steve L Voelker
- Department of Environmental and Forest Biology, State University of New York College of Environmental Science and Forestry, Syracuse, NY, 13210, USA
| | - Mary E Whelan
- Department of Environmental Sciences, Rutgers University, 14 College Farm Road, New Brunswick, NJ, 08901, USA
| | - Pieter A Zuidema
- Forest Ecology and Forest Management group, Wageningen University, PO Box 47, Wageningen, 6700 AA, the Netherlands
| |
Collapse
|
49
|
Lian X, Piao S, Chen A, Wang K, Li X, Buermann W, Huntingford C, Peñuelas J, Xu H, Myneni RB. Seasonal biological carryover dominates northern vegetation growth. Nat Commun 2021; 12:983. [PMID: 33579949 PMCID: PMC7881040 DOI: 10.1038/s41467-021-21223-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Accepted: 01/19/2021] [Indexed: 11/17/2022] Open
Abstract
The state of ecosystems is influenced strongly by their past, and describing this carryover effect is important to accurately forecast their future behaviors. However, the strength and persistence of this carryover effect on ecosystem dynamics in comparison to that of simultaneous environmental drivers are still poorly understood. Here, we show that vegetation growth carryover (VGC), defined as the effect of present states of vegetation on subsequent growth, exerts strong positive impacts on seasonal vegetation growth over the Northern Hemisphere. In particular, this VGC of early growing-season vegetation growth is even stronger than past and co-occurring climate on determining peak-to-late season vegetation growth, and is the primary contributor to the recently observed annual greening trend. The effect of seasonal VGC persists into the subsequent year but not further. Current process-based ecosystem models greatly underestimate the VGC effect, and may therefore underestimate the CO2 sequestration potential of northern vegetation under future warming.
Collapse
Affiliation(s)
- Xu Lian
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Shilong Piao
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China.
- Key Laboratory of Alpine Ecology, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China.
- Center for Excellence in Tibetan Earth Science, Chinese Academy of Sciences, Beijing, China.
| | - Anping Chen
- Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, USA
| | - Kai Wang
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Xiangyi Li
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Wolfgang Buermann
- Institute of Geography, Augsburg University, Augsburg, Germany
- Institute of the Environment and Sustainability, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Josep Peñuelas
- CREAF, Cerdanyola del Valles, Barcelona, Catalonia, Spain
- CSIC, Global Ecology Unit CREAF-CSIC-UAB, Bellaterra, Barcelona, Catalonia, Spain
| | - Hao Xu
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Ranga B Myneni
- Department of Earth and Environment, Boston University, Boston, MA, USA
| |
Collapse
|
50
|
McDowell NG, Allen CD, Anderson-Teixeira K, Aukema BH, Bond-Lamberty B, Chini L, Clark JS, Dietze M, Grossiord C, Hanbury-Brown A, Hurtt GC, Jackson RB, Johnson DJ, Kueppers L, Lichstein JW, Ogle K, Poulter B, Pugh TAM, Seidl R, Turner MG, Uriarte M, Walker AP, Xu C. Pervasive shifts in forest dynamics in a changing world. Science 2020; 368:368/6494/eaaz9463. [DOI: 10.1126/science.aaz9463] [Citation(s) in RCA: 301] [Impact Index Per Article: 75.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
| | - Craig D. Allen
- U.S. Geological Survey, Fort Collins Science Center, New Mexico Landscapes Field Station, Los Alamos, NM 87544, USA
| | - Kristina Anderson-Teixeira
- Conservation Ecology Center, Smithsonian Conservation Biology Institute, Front Royal, VA 22630, USA
- Forest Global Earth Observatory, Smithsonian Tropical Research Institute, Republic of Panama
| | - Brian H. Aukema
- Department of Entomology, University of Minnesota, St. Paul, MN 55108, USA
| | - Ben Bond-Lamberty
- Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD 20740, USA
| | - Louise Chini
- Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
| | - James S. Clark
- Nicholas School of the Environment, Duke University, Durham, NC 27708, USA
| | - Michael Dietze
- Department of Earth and Environment, Boston University, Boston, MA 02215, USA
| | - Charlotte Grossiord
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903 Birmensdorf, Switzerland
| | - Adam Hanbury-Brown
- Energy and Resources Group, University of California, Berkeley, Berkeley, CA 94720, USA
| | - George C. Hurtt
- Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
| | - Robert B. Jackson
- Department of Earth System Science, Woods Institute for the Environment, and Precourt Institute for Energy, Stanford University, Stanford, CA 94305, USA
| | - Daniel J. Johnson
- School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA
| | - Lara Kueppers
- Energy and Resources Group, University of California, Berkeley, Berkeley, CA 94720, USA
- Division of Climate and Ecosystem Sciences, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | | | - Kiona Ogle
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ 86001, USA
| | - Benjamin Poulter
- Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
| | - Thomas A. M. Pugh
- School of Geography, Earth and Environmental Sciences, University of Birmingham, B15 2TT Birmingham, UK
- Birmingham Institute of Forest Research, University of Birmingham, B15 2TT Birmingham, UK
| | - Rupert Seidl
- Department of Forest and Soil Sciences, University of Natural Resources and Life Sciences Vienna, 1180 Vienna, Austria
- School of Life Sciences, Technical University of Munich, 85354 Freising, Germany
| | - Monica G. Turner
- Department of Integrative Biology, University of Wisconsin–Madison, Madison, WI 53706, USA
| | - Maria Uriarte
- Department of Ecology, Evolution and Environmental Biology, Columbia University, New York, NY 10027, USA
| | - Anthony P. Walker
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Chonggang Xu
- Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
| |
Collapse
|