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Zhou S, Wu S, Gao J, Liu L, Li D, Yan R, Wang J. Increased stress from compound drought and heat events on vegetation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 949:175113. [PMID: 39084366 DOI: 10.1016/j.scitotenv.2024.175113] [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: 04/24/2024] [Revised: 06/25/2024] [Accepted: 07/27/2024] [Indexed: 08/02/2024]
Abstract
Compound drought and heat events (CDHEs), which are frequently occurring compound extreme climate events, have garnered considerable attention because of their detrimental effects on ecosystems. However, the intricacies of the spatial and temporal distributions of different durations of compound events, along with the variability in vegetation responses remain unclear. Here, we delineated the CDHEs based on meteorological observation data and investigated the spatial and temporal characteristics of CDHEs from 1993 to 2020 using the Theil-Sen trend test and Mann-Kendall nonparametric test. Furthermore, we utilized sliding correlation analysis to evaluate the impacts of CDHEs on vegetation among different climatic regions and ecosystems. Our findings indicate significant increasing trends in both the frequency and persistence of CDHEs from 1993 to 2020. The average trend of CDHEs frequency across different duration periods amounted to 13.80 %/decade. The fractional contribution of CDHEs lasting more than three days exhibited a significant increase, with an average trend of 2.00 %/decade. We also observed that vegetation is most significantly affected by compound events lasting 5-9 days. During the study period, the geographical extent of vegetation significantly impacted by CDHEs expanded by 0.89 %, correlation strength increased by 0.02, and lag time decreased by 0.25 months. These insights highlight the growing impact of CDHEs on vegetation under climate change, improving our understanding of vegetation responses to these compound events.
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Affiliation(s)
- Shuang Zhou
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shaohong Wu
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiangbo Gao
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Lulu Liu
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Delong Li
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Rui Yan
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jie Wang
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
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2
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MacDougall AS, Esch E, Chen Q, Carroll O, Bonner C, Ohlert T, Siewert M, Sulik J, Schweiger AK, Borer ET, Naidu D, Bagchi S, Hautier Y, Wilfahrt P, Larson K, Olofsson J, Cleland E, Muthukrishnan R, O'Halloran L, Alberti J, Anderson TM, Arnillas CA, Bakker JD, Barrio IC, Biederman L, Boughton EH, Brudvig LA, Bruschetti M, Buckley Y, Bugalho MN, Cadotte MW, Caldeira MC, Catford JA, D'Antonio C, Davies K, Daleo P, Dickman CR, Donohue I, DuPre ME, Elgersma K, Eisenhauer N, Eskelinen A, Estrada C, Fay PA, Feng Y, Gruner DS, Hagenah N, Haider S, Harpole WS, Hersch-Green E, Jentsch A, Kirkman K, Knops JMH, Laanisto L, Lannes LS, Laungani R, Lkhagva A, Macek P, Martina JP, McCulley RL, Melbourne B, Mitchell R, Moore JL, Morgan JW, Muraina TO, Niu Y, Pärtel M, Peri PL, Power SA, Price JN, Prober SM, Ren Z, Risch AC, Smith NG, Sonnier G, Standish RJ, Stevens CJ, Tedder M, Tognetti P, Veen GFC, Virtanen R, Wardle GM, Waring E, Wolf AA, Yahdjian L, Seabloom EW. Widening global variability in grassland biomass since the 1980s. Nat Ecol Evol 2024:10.1038/s41559-024-02500-x. [PMID: 39103674 DOI: 10.1038/s41559-024-02500-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 07/09/2024] [Indexed: 08/07/2024]
Abstract
Global change is associated with variable shifts in the annual production of aboveground plant biomass, suggesting localized sensitivities with unclear causal origins. Combining remotely sensed normalized difference vegetation index data since the 1980s with contemporary field data from 84 grasslands on 6 continents, we show a widening divergence in site-level biomass ranging from +51% to -34% globally. Biomass generally increased in warmer, wetter and species-rich sites with longer growing seasons and declined in species-poor arid areas. Phenological changes were widespread, revealing substantive transitions in grassland seasonal cycling. Grazing, nitrogen deposition and plant invasion were prevalent in some regions but did not predict overall trends. Grasslands are undergoing sizable changes in production, with implications for food security, biodiversity and carbon storage especially in arid regions where declines are accelerating.
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Affiliation(s)
- Andrew S MacDougall
- Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada.
- Department of Ecology and Environmental Sciences, Umeå University, Umeå, Sweden.
| | - Ellen Esch
- Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada
| | - Qingqing Chen
- Institute of Ecology, College of Urban and Environmental Science, Peking University, Beijing, China
| | - Oliver Carroll
- Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada
| | - Colin Bonner
- Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada
| | - Timothy Ohlert
- Department of Biology, University of New Mexico, Albuquerque, NM, USA
| | - Matthias Siewert
- Department of Ecology and Environmental Sciences, Umeå University, Umeå, Sweden
| | - John Sulik
- Department of Plant Agriculture, University of Guelph, Guelph, Ontario, Canada
| | - Anna K Schweiger
- Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, MT, USA
| | - Elizabeth T Borer
- Department of Ecology, Evolution, and Behavior, University of Minnesota, Saint Paul, MN, USA
| | - Dilip Naidu
- Centre for Ecological Sciences, Indian Institute of Science, Bangalore, India
| | - Sumanta Bagchi
- Centre for Ecological Sciences, Indian Institute of Science, Bangalore, India
| | - Yann Hautier
- Ecology and Biodiversity Group, Department of Biology, Utrecht University, Utrecht, The Netherlands
| | - Peter Wilfahrt
- Department of Ecology, Evolution, and Behavior, University of Minnesota, Saint Paul, MN, USA
| | - Keith Larson
- Department of Ecology and Environmental Sciences, Umeå University, Umeå, Sweden
| | - Johan Olofsson
- Department of Ecology and Environmental Sciences, Umeå University, Umeå, Sweden
| | - Elsa Cleland
- Division of Biological Sciences, University of California, San Diego, San Diego, CA, USA
| | | | - Lydia O'Halloran
- Baruch Institute of Coastal Ecology and Forest Science, Clemson University, Clemson, SC, USA
| | - Juan Alberti
- Instituto de Investigaciones Marinas y Costeras (IIMyC) FCEyN, UNMdP-CONICET, Mar del Plata, Argentina
| | | | - Carlos A Arnillas
- Department of Physical and Environmental Sciences, University of Toronto-Scarborough, Toronto, Ontario, Canada
| | - Jonathan D Bakker
- School of Environmental and Forest Sciences, University of Washington, Seattle, WA, USA
| | - Isabel C Barrio
- Faculty of Environmental and Forest Sciences, Agricultural University of Iceland, Reykjavik, Iceland
| | - Lori Biederman
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, USA
| | | | - Lars A Brudvig
- Department of Plant Biology and Program in Ecology, Evolution, and Behavior, Michigan State University, East Lansing, MI, USA
| | - Martin Bruschetti
- Instituto de Investigaciones Marinas y Costeras (IIMyC) FCEyN, UNMdP-CONICET, Mar del Plata, Argentina
| | - Yvonne Buckley
- Department of Zoology, School of Natural Sciences, Trinity College Dublin, Dublin, Ireland
| | - Miguel N Bugalho
- Centre for Applied Ecology, School of Agriculture, University of Lisbon, Lisbon, Portugal
| | - Marc W Cadotte
- Department of Biological Sciences, University of Toronto-Scarborough, Toronto, Ontario, Canada
| | - Maria C Caldeira
- Forest Research Centre, School of Agriculture, University of Lisbon, Lisbon, Portugal
| | - Jane A Catford
- Department of Geography, King's College London, London, UK
| | - Carla D'Antonio
- Department of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Kendi Davies
- Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO, USA
| | - Pedro Daleo
- Instituto de Investigaciones Marinas y Costeras (IIMyC) FCEyN, UNMdP-CONICET, Mar del Plata, Argentina
| | - Christopher R Dickman
- School of Life and Environmental Sciences, University of Sydney, Camperdown, New South Wales, Australia
| | - Ian Donohue
- Department of Zoology, School of Natural Sciences, Trinity College Dublin, Dublin, Ireland
| | | | | | - Nico Eisenhauer
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Institute of Biology, Leipzig University, Leipzig, Germany
| | - Anu Eskelinen
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Department of Physiological Diversity, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany
- Department of Ecology and Genetics, University of Oulu, Oulu, Finland
| | | | - Philip A Fay
- USDA-ARS Grassland Soil, and Water Research Laboratory, Temple, TX, USA
| | - Yanhao Feng
- College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, China
| | - Daniel S Gruner
- Department of Entomology, University of Maryland, College Park, MD, USA
| | - Nicole Hagenah
- Department of Zoology & Entomology, University of Pretoria, Pretoria, South Africa
| | - Sylvia Haider
- Institute of Ecology, Leuphana University of Lüneburg, Lüneburg, Germany
| | - W Stanley Harpole
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Department of Physiological Diversity, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany
- Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Erika Hersch-Green
- Department of Biological Sciences, Michigan Technological University, Houghton, MI, USA
| | - Anke Jentsch
- Department of Disturbance Ecology, Bayreuth Center of Ecology and Environmental Research, University of Bayreuth, Bayreuth, Germany
| | - Kevin Kirkman
- School of Life Sciences, College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Durban, South Africa
| | - Johannes M H Knops
- Department of Health and Environmental Sciences, Jiatong-Liverpool University, Suzhou, China
| | - Lauri Laanisto
- Chair of Biodiversity and Nature Tourism, Estonian University of Life Sciences, Tartu, Estonia
| | - Lucíola S Lannes
- Department of Biology and Animal Sciences, Sao Paulo State University UNESP, Ilha Solteira, Brazil
| | - Ramesh Laungani
- Department of Environmental Science and Policy, Marist College, Poughkeepsie, NY, USA
| | | | - Petr Macek
- Institute of Hydrobiology, Biology Centre of Czech Academy of Sciences, Ceske Budejovice, Czech Republic
| | - Jason P Martina
- Department of Biology, Texas State University, San Marcos, TX, USA
| | - Rebecca L McCulley
- Department of Plant and Soil Sciences, University of Kentucky, Lexington, KY, USA
| | - Brett Melbourne
- Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO, USA
| | - Rachel Mitchell
- School of Earth and Sustainability, Northern Arizona University, Flagstaff, AZ, USA
| | - Joslin L Moore
- Arthur Rylah Institute for Environment Research, Department of Energy Environment and Climate Action, Melbourne, Victoria, Australia
- School of Biological Sciences, Monash University, Clayton, Victoria, Australia
- School of Agriculture, Food and Ecosystem Sciences, The University of Melbourne, Melbourne, Victoria, Australia
| | - John W Morgan
- Department of Environment and Genetics, La Trobe University, Bundoora, Victoria, Australia
| | - Taofeek O Muraina
- Department of Animal Health and Production, Oyo State College of Agriculture and Technology, Igbo-Ora, Nigeria
- Department of Biology, Texas State University, San Marcos, TX, USA
| | - Yujie Niu
- Department of Biological Sciences, Michigan Technological University, Houghton, MI, USA
- College of Grassland Science, Key Laboratory of Grassland Ecosystem of the Ministry of Education, Gansu Agricultural University, Lanzhou, China
| | - Meelis Pärtel
- Institute of Ecology and Earth Sciences, University of Tartu, Tartu, Estonia
| | - Pablo L Peri
- INTA-UNPA-CONICET, Universidad Nacional de la Patagonia, Rìo Gallegos, Argentina
| | - Sally A Power
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, New South Wales, Australia
| | - Jodi N Price
- Gulbali Institute, Charles Sturt University, Albury, New South Wales, Australia
| | - Suzanne M Prober
- CSIRO Environment, Canberra, Australian Capital Territory, Australia
| | - Zhengwei Ren
- College of Ecology, Lanzhou University, Lanzhou, China
| | - Anita C Risch
- Swiss Federal Institute for Forest Snow and Landscape Research WSL, Birmensdorf, Switzerland
| | - Nicholas G Smith
- Department of Biological Sciences, Texas Tech University, Lubbock, TX, USA
| | | | | | - Carly J Stevens
- Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | - Michelle Tedder
- School of Life Sciences, College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Durban, South Africa
| | - Pedro Tognetti
- IFEVA Facultad de Agronomía, Universidad de Buenos Aires-CONICET, Buenos Aires, Argentina
| | - G F Ciska Veen
- Department of Terrestrial Ecology, Netherlands Institute of Ecology, Wageningen, The Netherlands
| | - Risto Virtanen
- Department of Ecology and Genetics, University of Oulu, Oulu, Finland
| | - Glenda M Wardle
- School of Life and Environmental Sciences, University of Sydney, Camperdown, New South Wales, Australia
| | - Elizabeth Waring
- Department of Natural Sciences, Northeastern State University, Tahlequah, OK, USA
| | - Amelia A Wolf
- Department of Integrative Biology, University of Texas at Austin, Austin, TX, USA
| | - Laura Yahdjian
- IFEVA Facultad de Agronomía, Universidad de Buenos Aires-CONICET, Buenos Aires, Argentina
| | - Eric W Seabloom
- Department of Ecology, Evolution, and Behavior, University of Minnesota, Saint Paul, MN, USA
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3
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Zhao Y, Wang L, Jiang Q, Wang Z. Sensitivity of gross primary production to precipitation and the driving factors in China's agricultural ecosystems. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 948:174938. [PMID: 39047829 DOI: 10.1016/j.scitotenv.2024.174938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Revised: 07/18/2024] [Accepted: 07/19/2024] [Indexed: 07/27/2024]
Abstract
Recent climate warming has significantly affected the sensitivity of Gross Primary Productivity (GPP) to precipitation within China's agricultural ecosystems. Nonetheless, the spatial and temporal nonlinear evolution patterns of GPP-precipitation sensitivity under climate change, as well as the underlying drivers and long-term trends of this sensitivity, are not well understood. This study employs correlation analysis to quantify the sensitivity between GPP and precipitation in China's agricultural ecosystems, and utilizes nonlinear detection algorithms to examine the long-term changes in this sensitivity. Advanced machine learning techniques and frameworks are subsequently applied to analyze the driving factors of GPP-precipitation sensitivity in China's agricultural ecosystems. The findings reveal that approximately 49.00 % of the analyzed pixels exhibit a significant positive correlation between GPP and precipitation. Nonlinear change analysis indicates spatial heterogeneity in GPP-precipitation sensitivity across China's agricultural ecosystems, with patterns showing initial increases followed by decreases accounting for 25.12 %, and patterns of initial decreases followed by increases at 13.27 %. Machine learning analysis identifies temperature, soil moisture, and crop water footprint as the primary factors influencing GPP-precipitation sensitivity in agricultural ecosystems. This study is the first to introduce crop water footprint as a significant factor in the analysis of GPP-precipitation sensitivity. It not only offers new insights into the temporal nonlinear changes and driving factors of GPP-precipitation sensitivity but also underscores the importance of enhancing agricultural water efficiency to maintain agricultural ecosystem health and ensure food security under climate change.
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Affiliation(s)
- Youzhu Zhao
- School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150030, China
| | - Luchen Wang
- School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150030, China
| | - Qiuxiang Jiang
- School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150030, China.
| | - Zilong Wang
- School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150030, China
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4
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Li C, Zhang S. Disentangling the impact of climate change, human activities, vegetation dynamics and atmospheric CO 2 concentration on soil water use efficiency in global karst landscapes. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 932:172865. [PMID: 38692319 DOI: 10.1016/j.scitotenv.2024.172865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 04/09/2024] [Accepted: 04/27/2024] [Indexed: 05/03/2024]
Abstract
Soil Water Use Efficiency (SWUE), which quantifies the carbon gain against each unit of soil moisture depletion, represents an essential ecological parameter that delineates the carbon-water coupling within terrestrial ecosystems. However, the spatiotemporal dynamics of SWUE, its sensitivity to environmental variables, and the underlying driving mechanisms across various temporal scales in the global karst region are largely uncharted. This study utilized the sensitivity algorithm of partial least squares regression, partial differential equations, and elasticity coefficients to investigate the characteristics of SWUE variations across different climatic zones in the global karst region and their responsiveness to environmental variables. Moreover, the study quantified the individual contributions of climate variability, atmospheric carbon dioxide concentration, human activities, and vegetation changes to SWUE variations. The results indicated that SWUE across different climatic zones in the global karst region demonstrated an increasing trend from 2000 to 2018, with the most notable improvement observed in the humid zone. SWUE presented regular distribution and variation characteristics across different latitudinal zones at a monthly scale. The sensitivity of SWUE to precipitation was significantly higher compared to its responsiveness to other environmental factors. Additionally, the trend in SWUE's sensitivity to precipitation demonstrated the most significant change. The sensitivity of SWUE to various environmental factors and the trend of this sensitivity in the arid zone revealed significant variation compared to other climatic zones. Gross primary productivity and soil moisture were identified as the intrinsic factors influencing SWUE changes, contributing 16 % and - 84 %, respectively. Climate variability and human activities were identified as the primary exogenous factors contributing to the increase in SWUE, accounting for 76 % and 16 %, respectively. This study advances the understanding of carbon-water coupling in karst regions, providing significant insights into the ecological management of global karst environments amidst climate variations.
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Affiliation(s)
- Chao Li
- College of Urban and Environmental Science, Northwest University, Xi'an 710127, PR China; Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, PR China
| | - Shiqiang Zhang
- College of Urban and Environmental Science, Northwest University, Xi'an 710127, PR China; Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, PR China.
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5
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Wang Y, Liu Y, Chen P, Song J, Fu B. Interannual precipitation variability dominates the growth of alpine grassland above-ground biomass at high elevations on the Tibetan Plateau. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 931:172745. [PMID: 38677425 DOI: 10.1016/j.scitotenv.2024.172745] [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: 09/20/2023] [Revised: 03/18/2024] [Accepted: 04/23/2024] [Indexed: 04/29/2024]
Abstract
The impact of global climate change on mountainous regions with significant elevational gaps is complex and often unpredictable. In particular, alpine grassland ecosystems, are experiencing changes in their spatial patterns along elevational gradients, which increases their vulnerability to degradation. Therefore, a more detailed understanding of spatiotemporal changes in alpine grassland productivity along elevational gradients and an elevation-dependent characterization of the effects of climatic variables on grassland productivity dynamics are essential. Thus, we conducted a study in the Tibetan Plateau, where we collected 2251 above-ground biomass (AGB) observations collected from 1986 to 2020. Mean annual temperature (TMP), annual precipitation (PRE), interannual precipitation variability (CVP), and snowmelt (SNMM) were chosen as influential variables. Using the Random Forest algorithm, we generated an AGB raster dataset covering the period 1989-2020 based on earth observation data at 30 m resolution to examine the dynamics of alpine grasslands and their response to climate change with respect to elevation. The results showed that the AGB of alpine grassland on the Tibetan Plateau was 49.17 g/m2. We observed an increasing trend in grassland AGB at high elevations, with a growth rate of about 0.28 g/m2 per year within the interval of 3100-4800 m. However, above the elevation of approximately 4400-4600 m, we observed a decoupling trend between grassland AGB and TMP. Moreover, at most elevations, the proportion of maximum partial correlation coefficients for CVP, PRE, and SNMM surpassed that of TMP. We found the dominant role of precipitation variability on grassland AGB dynamics, with 22.80 % and 18.86 % for CVP+ and CVP-, respectively. The proportion of CVP+ did not vary much at different elevations, whereas the proportion of CVP- increased with elevation, varying between 12.85 and 30.25 %. In the future, precipitation on the Tibetan plateau is expected to increase, potentially reversing its original positive impact.
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Affiliation(s)
- Yijia Wang
- Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Yanxu Liu
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
| | - Peng Chen
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Jiaxi Song
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Bojie Fu
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
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6
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Leifsson C, Buras A, Klesse S, Baittinger C, Bat-Enerel B, Battipaglia G, Biondi F, Stajić B, Budeanu M, Čada V, Cavin L, Claessens H, Čufar K, de Luis M, Dorado-Liñán I, Dulamsuren C, Garamszegi B, Grabner M, Hacket-Pain A, Hansen JK, Hartl C, Huang W, Janda P, Jump AS, Kazimirović M, Knutzen F, Kreyling J, Land A, Latte N, Lebourgeois F, Leuschner C, Longares LA, Martinez Del Castillo E, Menzel A, Motta R, Muffler-Weigel L, Nola P, Panayatov M, Petritan AM, Petritan IC, Popa I, Roibu CC, Rubio-Cuadrado Á, Rydval M, Scharnweber T, Camarero JJ, Svoboda M, Toromani E, Trotsiuk V, van der Maaten-Theunissen M, van der Maaten E, Weigel R, Wilmking M, Zlatanov T, Rammig A, Zang CS. Identifying drivers of non-stationary climate-growth relationships of European beech. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 937:173321. [PMID: 38782287 DOI: 10.1016/j.scitotenv.2024.173321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 05/15/2024] [Accepted: 05/15/2024] [Indexed: 05/25/2024]
Abstract
The future performance of the widely abundant European beech (Fagus sylvatica L.) across its ecological amplitude is uncertain. Although beech is considered drought-sensitive and thus negatively affected by drought events, scientific evidence indicating increasing drought vulnerability under climate change on a cross-regional scale remains elusive. While evaluating changes in climate sensitivity of secondary growth offers a promising avenue, studies from productive, closed-canopy forests suffer from knowledge gaps, especially regarding the natural variability of climate sensitivity and how it relates to radial growth as an indicator of tree vitality. Since beech is sensitive to drought, we in this study use a drought index as a climate variable to account for the combined effects of temperature and water availability and explore how the drought sensitivity of secondary growth varies temporally in dependence on growth variability, growth trends, and climatic water availability across the species' ecological amplitude. Our results show that drought sensitivity is highly variable and non-stationary, though consistently higher at dry sites compared to moist sites. Increasing drought sensitivity can largely be explained by increasing climatic aridity, especially as it is exacerbated by climate change and trees' rank progression within forest communities, as (co-)dominant trees are more sensitive to extra-canopy climatic conditions than trees embedded in understories. However, during the driest periods of the 20th century, growth showed clear signs of being decoupled from climate. This may indicate fundamental changes in system behavior and be early-warning signals of decreasing drought tolerance. The multiple significant interaction terms in our model elucidate the complexity of European beech's drought sensitivity, which needs to be taken into consideration when assessing this species' response to climate change.
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Affiliation(s)
- Christopher Leifsson
- Technical University of Munich, TUM School of Life Sciences, Land Surface-Atmosphere Interactions, Hans-Carl-v.-Carlowitz-Platz 2, 85354 Freising, Germany.
| | - Allan Buras
- Technical University of Munich, TUM School of Life Sciences, Land Surface-Atmosphere Interactions, Hans-Carl-v.-Carlowitz-Platz 2, 85354 Freising, Germany
| | - Stefan Klesse
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903 Birmensdorf, Switzerland
| | - Claudia Baittinger
- The National Museum of Denmark, Environmental Archaeology and Materials Science, I.C. Modewegs Vej 11, DK - 2800 Kgs. Lyngby, Denmark
| | - Banzragch Bat-Enerel
- Plant Ecology, University of Goettingen, 37073 Goettingen, Germany; Applied Vegetation Ecology, Faculty of Environment and Natural Resources, University of Freiburg, 79106 Freiburg, Germany
| | | | - Franco Biondi
- DendroLab, Dept. of Natural Resources and Environmental Science, University of Nevada, Reno, NV 89557, USA
| | - Branko Stajić
- University of Belgrade, Faculty of Forestry, Belgrade, Serbia
| | - Marius Budeanu
- National Institute for Research and Development in Forestry Marin Dracea, 13 Closca street, Brasov, Romania
| | - Vojtěch Čada
- Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Kamycka 129, Praha 6, Suchdol 16521, Czech Republic
| | - Liam Cavin
- Biological and Environmental Sciences, University of Stirling, Stirling FK9 4LA, Scotland, UK
| | - Hugues Claessens
- Forest is Life, ULiège, Passage des Déportés 2, B-5030 Gembloux, Belgium
| | - Katarina Čufar
- University of Ljubljana, Biotechnical Faculty, Department of Wood Science and Technology, Jamnikarjeva 101, 1000 Ljubljana, Slovenia
| | - Martin de Luis
- Dpto. de Geografía y Ordenación del Territorio, IUCA, Universidad de Zaragoza, C/ Pedro Cerbuna s/n, 50009 Zaragoza. Spain
| | - Isabel Dorado-Liñán
- Departamento de Sistemas y Recursos Naturales, Universidad Politécnica de Madrid, 28040 Madrid, Spain
| | - Choimaa Dulamsuren
- Applied Vegetation Ecology, Faculty of Environment and Natural Resources, University of Freiburg, 79106 Freiburg, Germany
| | - Balázs Garamszegi
- Institute of Forest Ecology, University of Natural Resources and Life Sciences, Vienna, Austria
| | - Michael Grabner
- University of Natural Resources and Life Sciences, Vienna, Austria
| | - Andrew Hacket-Pain
- Department of Geography and Planning, School of Environmental Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Jon Kehlet Hansen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Claudia Hartl
- Nature Rings - Environmental Research & Education, 55118 Mainz, Germany
| | - Weiwei Huang
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark; Collaborative Innovation Center of Sustainable Forestry in Southern China of Jiangsu Province, Nanjing Forestry University, Nanjing 210037, China
| | - Pavel Janda
- Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Kamycka 129, Praha 6, Suchdol 16521, Czech Republic
| | - Alistair S Jump
- Biological and Environmental Sciences, University of Stirling, Stirling FK9 4LA, Scotland, UK
| | | | - Florian Knutzen
- Climate Service Center Germany (GERICS), Helmholtz-Zentrum Hereon, Fischertwiete 1, 20095 Hamburg, Germany
| | - Jürgen Kreyling
- University of Greifswald, Experimental Plant Ecology, Soldmannstraße 15, 17498 Greifswald, Germany
| | - Alexander Land
- University of Hohenheim, Institute of Biology (190a), Garbenstraße 30, 70599 Stuttgart, Germany
| | - Nicolas Latte
- Forest is Life, ULiège, Passage des Déportés 2, B-5030 Gembloux, Belgium
| | | | | | - Luis A Longares
- Dpto. de Geografía y Ordenación del Territorio, IUCA, Universidad de Zaragoza, C/ Pedro Cerbuna s/n, 50009 Zaragoza. Spain
| | | | - Annette Menzel
- Technical University of Munich, TUM School of Life Sciences, Ecoclimatology, Hans-Carl-v.-Carlowitz-Platz 2, 85354 Freising, Germany
| | - Renzo Motta
- Department of Agricoltural Forest and Food Sciences, University of Turin, Largo Paolo Braccini 2, 10095 Grugliasco, TO, Italy
| | - Lena Muffler-Weigel
- Ecological-Botanical Garden, University of Bayreuth, 95447 Bayreuth, Germany
| | - Paola Nola
- Department of Earth and Environmental Sciences, University of Pavia, Via S. Epifanio 14, I-27100 Pavia, Italy
| | - Momchil Panayatov
- University of Forestry, Dendrology Department, Forest Faculty, Sofia, Bulgaria
| | - Any Mary Petritan
- National Institute for Research and Development in Forestry Marin Dracea, 13 Closca street, Brasov, Romania
| | - Ion Catalin Petritan
- Faculty of Silviculture and Forest Engineering, Department of Forest Engineering, Forest Management Planning and Terrestrial Measurements, Transilvania University of Braşov, Braşov, Romania
| | - Ionel Popa
- National Institute for Research and Development in Forestry Marin Dracea, 13 Closca street, Brasov, Romania; Center for Mountain Economy (CE-MONT), Vatra Dornei, Romania
| | - Cǎtǎlin-Constantin Roibu
- Forest Biometrics Laboratory, Faculty of Forestry, "Stefan cel Mare" University of Suceava, Universitatii street, no. 13, Suceava RO720229, Romania
| | - Álvaro Rubio-Cuadrado
- Departamento de Sistemas y Recursos Naturales, Escuela Técnica Superior de Ingeniería de Montes, Forestal y del Medio Natural, Universidad Politécnica de Madrid. Ciudad Universitaria s/n, 28040 Madrid, Spain
| | - Miloš Rydval
- Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Kamycka 129, Praha 6, Suchdol 16521, Czech Republic
| | - Tobias Scharnweber
- Institute for Botany and Landscape Ecology, University Greifswald, 17487 Greifswald, Germany
| | - J Julio Camarero
- Instituto Pirenaico de Ecología (IPE), CSIC, Avda. Montañana 1005, 50080 Zaragoza, Spain
| | - Miroslav Svoboda
- Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Kamycka 129, Praha 6, Suchdol 16521, Czech Republic
| | - Elvin Toromani
- Department of Forestry, Agricultural University Tirana, Tirana, Albania
| | - Volodymyr Trotsiuk
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903 Birmensdorf, Switzerland
| | | | - Ernst van der Maaten
- Chair of Forest Growth and Woody Biomass Production, TU Dresden, Dresden, Germany
| | - Robert Weigel
- Ecological-Botanical Garden, University of Bayreuth, 95447 Bayreuth, Germany
| | - Martin Wilmking
- Institute for Botany and Landscape Ecology, University Greifswald, 17487 Greifswald, Germany
| | - Tzvetan Zlatanov
- Institute of Biodiversity and Ecosystem Research, Bulgarian Academy of Sciences, 2 Gagarin Street, 1113 Sofia, Bulgaria
| | - Anja Rammig
- Technical University of Munich, TUM School of Life Sciences, Land Surface-Atmosphere Interactions, Hans-Carl-v.-Carlowitz-Platz 2, 85354 Freising, Germany
| | - Christian S Zang
- Weihenstephan-Triesdorf University of Applied Sciences, Department of Forestry, Hans-Carl-v.-Carlowitz-Platz 3, 85354 Freising, Germany
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7
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Zhang Z, Ma X, Maeda EE, Lu L, Wang Y, Xie Z, Li X, Pan Y, Huang L, Zhao Y, Huete A. Satellite observed dryland greening in Asian endorheic basins: Drivers and implications to sustainable development. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 922:171216. [PMID: 38412878 DOI: 10.1016/j.scitotenv.2024.171216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 02/06/2024] [Accepted: 02/21/2024] [Indexed: 02/29/2024]
Abstract
A large portion of Central-Western Asia is made up of contiguous closed basins, collectively termed as the Asian Endorheic Basins (AEBs). As these retention basins are only being replenished by the intermittent and scarce rainfall, global warming coupled with ever-rising human demand for water is exerting unprecedented pressures on local water and ecological security. Recent studies revealed a persistent and widespread water storage decline across the AEBs, yet the response of dryland vegetation to this recent hydroclimatic trend and a spatially explicit partitioning of the impact into the hydroclimatic factors and human activities remain largely unknown. To fill in this knowledge gap, we conducted trend and partial correlation analysis of vegetation and hydroclimatic change from 2001 to 2021 using multi-satellite observations, including vegetation greenness, total water storage anomalies (TWSA) and meteorological data. Here we show that much of the AEB (65.53 %), encompassing Mongolia Plateau, Northwest China, Qinghai Tibet Plateau, and Western Asia (except the Arabian Peninsula), exhibited a significant greening trend over the past two decades. In arid AEB, precipitation dominated the vegetation productivity trend. Such a rainfall dominance gave way to TWSA dominance in the hyper-arid AEB. We further showed that the decoupling of rainfall and hyper-arid vegetation greening was largely due to a significant expansion (17.3 %) in irrigated cropland across the hyper-arid AEB. Given the extremely harsh environment in the AEB, our results therefore raised a significant concern on the ecological and societal sustainability in this region, where a mild increase in precipitation cannot catch up the rising evaporative demand and water consumption resulted from global warming and agriculture intensification.
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Affiliation(s)
- Zhengyang Zhang
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, Gansu 730000, China; State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Xuanlong Ma
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, Gansu 730000, China.
| | - Eduardo Eiji Maeda
- Department of Geosciences and Geography, University of Helsinki, 68, FI-00014, Finland; Finnish Meteorological Institute, FMI, Helsinki, Finland
| | - Lei Lu
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, Gansu 730000, China
| | - Yuanyuan Wang
- Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China; Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China
| | - Zunyi Xie
- College of Geography and Environmental Science, Henan University, Kaifeng 475004, Henan, China
| | - Xiaoying Li
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, Gansu 730000, China
| | - Yaozhong Pan
- State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Lei Huang
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Yuhe Zhao
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, Gansu 730000, China
| | - Alfredo Huete
- School of Life Sciences, University of Technology Sydney, Sydney, NSW 2007, Australia
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8
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Liu S, Li T, Liu B, Xu C, Zhu Y, Xiao L. Grassland vegetation decline is exacerbated by drought and can be mitigated by soil improvement in Inner Mongolia, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 908:168464. [PMID: 37956850 DOI: 10.1016/j.scitotenv.2023.168464] [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: 08/29/2023] [Revised: 10/27/2023] [Accepted: 11/08/2023] [Indexed: 11/15/2023]
Abstract
Grassland activity is highly susceptible to drought while drivers from climate and soil attributes can largely affect drought propagation. However, understanding how these drives regulate the risk of vegetation decline under drought conditions remains limited, potentially impeding the adoption of appropriate adaptation strategies. To address this knowledge gap, we conducted a case study focusing on grassland activity in Inner Mongolia, China. In this study, we applied copula theorem to estimate the conditional probabilities of vegetation decline under drought conditions. Additionally, we utilized a structural equation model and a machine learning approach to identify the relative contributions of external drivers to the risk of vegetation decline. Our findings demonstrated a positive correlation between anomalies in vegetation activity and the status of water balance, and grassland vegetation in drier regions exhibited a more rapid response to water deficit. Increasing water deficit continuously reduced vegetation activity with risks of 77.27 %, 83.83 %, and 88.35 % under moderate, severe, and extreme drought conditions, respectively. Furthermore, the risks of vegetation decline under drought conditions were primarily governed by climate attributes, followed by soil properties and topography. Soil with high soil organic carbon stock content contributed significantly to mitigating the adverse effects of drought on grassland vegetation. In addition, we detected nonlinear patterns among environmental drivers and vegetation decline risks caused by drought. These findings highlight the importance of climate, soil properties, topography, and their intricate interconnections in regulating vegetation decline. This knowledge provides valuable insights into drought risk management for vegetation in advance and offers potential solutions to enhance vegetation resistance in the face of extreme drought events.
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Affiliation(s)
- Shengli Liu
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, Henan 450001, China
| | - Tong Li
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, Henan 450001, China
| | - Bing Liu
- National Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
| | - Chenyang Xu
- School of Agriculture, Sun Yat-sen University, Guangzhou, Guangdong 510275, China
| | - Yan Zhu
- National Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
| | - Liujun Xiao
- National Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China.
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9
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Li D, An L, Zhong S, Shen L, Wu S. Declining coupling between vegetation and drought over the past three decades. GLOBAL CHANGE BIOLOGY 2024; 30:e17141. [PMID: 38273520 DOI: 10.1111/gcb.17141] [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: 11/09/2023] [Revised: 12/10/2023] [Accepted: 12/19/2023] [Indexed: 01/27/2024]
Abstract
Droughts have been implicated as the main driver behind recent vegetation die-off and are projected to drive greater mortality under future climate change. Understanding the coupling relationship between vegetation and drought has been of great global interest. Currently, the coupling relationship between vegetation and drought is mainly evaluated by correlation coefficients or regression slopes. However, the optimal drought timescale of vegetation response to drought, as a key indicator reflecting vegetation sensitivity to drought, has largely been ignored. Here, we apply the optimal drought timescale identification method to examine the change in coupling between vegetation and drought over the past three decades (1982-2015) with long-term satellite-derived Normalized Difference Vegetation Index and Standardized Precipitation-Evapotranspiration Index data. We find substantial increasing response of vegetation to drought timescales globally, and the correlation coefficient between vegetation and drought under optimal drought timescale overall declines between 1982 and 2015. This decrease in vegetation-drought coupling is mainly observed in regions with water deficit, although its initial correlation is relatively high. However, vegetation in water-surplus regions, with low coupling in earlier stages, is prone to show an increasing trend. The observed changes may be driven by the increasing trend of atmospheric CO2 . Our findings highlight more pressing drought risk in water-surplus regions than in water-deficit regions, which advances our understanding of the long-term vegetation-drought relationship and provides essential insights for mapping future vegetation sensitivity to drought under changing climate conditions.
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Affiliation(s)
- Delong Li
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Li An
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Shuai Zhong
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Lei Shen
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- China-Pakistan Joint Research Center on Earth Sciences, CAS-HEC, Islamabad, Pakistan
- Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Natural Resources of the People's Republic of China, Beijing, China
| | - Shuyao Wu
- Center for Yellow River Ecosystem Products, Shandong University, Qingdao, Shandong, China
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10
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Liang C, Zhang M, Wang Z, Xiang X, Gong H, Wang K, Liu H. The strengthened impact of water availability at interannual and decadal time scales on vegetation GPP. GLOBAL CHANGE BIOLOGY 2024; 30:e17138. [PMID: 38273499 DOI: 10.1111/gcb.17138] [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: 09/07/2023] [Revised: 12/08/2023] [Accepted: 12/08/2023] [Indexed: 01/27/2024]
Abstract
Water availability (WA) is a key factor influencing the carbon cycle of terrestrial ecosystems under climate warming, but its effects on gross primary production (EWA-GPP ) at multiple time scales are poorly understood. We used ensemble empirical mode decomposition (EEMD) and partial correlation analysis to assess the WA-GPP relationship (RWA-GPP ) at different time scales, and geographically weighted regression (GWR) to analyze their temporal dynamics from 1982 to 2018 with multiple GPP datasets, including near-infrared radiance of vegetation GPP, FLUXCOM GPP, and eddy covariance-light-use efficiency GPP. We found that the 3- and 7-year time scales dominated global WA variability (61.18% and 11.95%), followed by the 17- and 40-year time scales (7.28% and 8.23%). The long-term trend also influenced 10.83% of the regions, mainly in humid areas. We found consistent spatiotemporal patterns of the EWA-GPP and RWA-GPP with different source products: In high-latitude regions, RWA-GPP changed from negative to positive as the time scale increased, while the opposite occurred in mid-low latitudes. Forests had weak RWA-GPP at all time scales, shrublands showed negative RWA-GPP at long time scales, and grassland (GL) showed a positive RWA-GPP at short time scales. Globally, the EWA-GPP , whether positive or negative, enhanced significantly at 3-, 7-, and 17-year time scales. For arid and humid zones, the semi-arid and sub-humid zones experienced a faster increase in the positive EWA-GPP , whereas the humid zones experienced a faster increase in the negative EWA-GPP . At the ecosystem types, the positive EWA-GPP at a 3-year time scale increased faster in GL, deciduous broadleaf forest, and savanna (SA), whereas the negative EWA-GPP at other time scales increased faster in evergreen needleleaf forest, woody savannas, and SA. Our study reveals the complex and dynamic EWA-GPP at multiple time scales, which provides a new perspective for understanding the responses of terrestrial ecosystems to climate change.
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Affiliation(s)
- Chuanzhuang Liang
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing, China
- College of Geography Science, Nanjing Normal University, Nanjing, China
| | - Mingyang Zhang
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China
- Institutional Center for Shared Technologies and Facilities of Institute of Subtropical Agriculture, CAS, Changsha, China
- Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Sciences, Huanjiang, China
| | - Zheng Wang
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing, China
- College of Geography Science, Nanjing Normal University, Nanjing, China
- Jiangsu Key Laboratory of Ocean-Land Environmental Change and Ecological Construction, Nanjing Normal University, Nanjing, China
- State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing Normal University, Nanjing, China
- Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, China
| | - Xueqiao Xiang
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing, China
- College of Geography Science, Nanjing Normal University, Nanjing, China
- Jiangsu Key Laboratory of Ocean-Land Environmental Change and Ecological Construction, Nanjing Normal University, Nanjing, China
- State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing Normal University, Nanjing, China
- Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, China
| | - Haibo Gong
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing, China
- College of Geography Science, Nanjing Normal University, Nanjing, China
- Jiangsu Key Laboratory of Ocean-Land Environmental Change and Ecological Construction, Nanjing Normal University, Nanjing, China
- State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing Normal University, Nanjing, China
- Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, China
| | - Kelin Wang
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China
- Institutional Center for Shared Technologies and Facilities of Institute of Subtropical Agriculture, CAS, Changsha, China
| | - Huiyu Liu
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing, China
- College of Geography Science, Nanjing Normal University, Nanjing, China
- Jiangsu Key Laboratory of Ocean-Land Environmental Change and Ecological Construction, Nanjing Normal University, Nanjing, China
- State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing Normal University, Nanjing, China
- Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, China
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11
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Dong G, Chen S, Liu K, Wang W, Hou H, Gao L, Zhang F, Su H. Spatiotemporal variation in sensitivity of urban vegetation growth and greenness to vegetation water content: Evidence from Chinese megacities. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 905:167090. [PMID: 37716675 DOI: 10.1016/j.scitotenv.2023.167090] [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: 06/11/2023] [Revised: 08/28/2023] [Accepted: 09/13/2023] [Indexed: 09/18/2023]
Abstract
Understanding the sensitivity of vegetation growth and greenness to vegetation water content change is crucial for elucidating the mechanism of terrestrial ecosystems response to water availability change caused by climate change. Nevertheless, we still have limited knowledge of such aspects in urban in different climatic contexts under the influence of human activities. In this study, we employed Google Earth Engine (GEE), remote sensing satellite imagery, meteorological data, and Vegetation Photosynthesis Model (VPM) to explore the spatiotemporal pattern of vegetation growth and greenness sensitivity to vegetation water content in three megacities (Beijing, Shanghai, and Guangzhou) located in eastern China from 2001 to 2020. We found a significant increase (slope > 0, p < 0.05) in the sensitivity of urban vegetation growth and greenness to vegetation water content (SLSWI). This indicates the increasing dependence of urban vegetation ecosystems on vegetation water resources. Moreover, evident spatial heterogeneity was observed in both SLSWI and the trends of SLSWI, and spatial heterogeneity in SLSWI and the trends of SLSWI was also present among identical vegetation types within the same city. Additionally, both SLSWI of vegetation growth and greenness and the trend of SLSWI showed obvious spatial distribution differences (e.g., standard deviations of trends in SLSWI of open evergreen needle-leaved forest of GPP is 14.36 × 10-2 and standard deviations of trends in SLSWI of open evergreen needle-leaved forest of EVI is 10.16 × 10-2), closely associated with factors such as vegetation type, climatic conditions, and anthropogenic influences.
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Affiliation(s)
- Guannan Dong
- Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shaohui Chen
- Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Kai Liu
- Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Weimin Wang
- Shenzhen Ecological and Environmental Monitoring Center of Guangdong Province, Shenzhen 518049, China; Guangdong Greater Bay Area, Change and Comprehensive Treatment of Regional Ecology and Environment, National Observation and Research Station, Shenzhen 518049, China; State Environmental Protection Scientific Observation and Research Station for Ecology and Environment of Rapid Urbanization Region, Shenzhen 518049, China
| | - Haoran Hou
- Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Long Gao
- Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Furong Zhang
- Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hongbo Su
- Department of Civil, Environmental & Geomatics Engineering, College of Engineering & Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA.
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12
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Zhao C, Liu J, Mou W, Zhao W, Zhou Z, Ta F, Lei L, Li C. Topography shapes the carbon allocation patterns of alpine forests. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 898:165542. [PMID: 37454841 DOI: 10.1016/j.scitotenv.2023.165542] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 07/10/2023] [Accepted: 07/12/2023] [Indexed: 07/18/2023]
Abstract
Topography plays a crucial role in determining the structure of alpine forests, as it restricts the availability of nutrients and water necessary for plant growth. Nevertheless, our information on how variations in forest carbon allocation patterns driven by fine-scale topography are influenced by broader-scale environmental contexts is limited. In the northern Tibetan Plateau, we combined field data from 89 forest plots with a high-resolution (1 m2) digital elevation model (DEM) and utilized a linear mixed-effects model to investigate how microtopography (characterized by slope, aspect, and topographic wetness index (TWI)) and broader-scale environmental context (characterized by elevation) and their interactions affect the carbon allocation patterns of alpine forest. Our results revealed that at low and high elevations with pronounced subsurface resource limitations, plants tend to allocate a higher proportion of carbon to the root system and have lower aboveground carbon stocks (ACS). Microtopographic heterogeneity significantly influenced the carbon allocation patterns of forest, with the intensity and direction of these effects varying across the environmental gradient. At low elevations, topographically wetter and northerly microhabitats had higher ACS and lower ratios of below- and aboveground carbon stocks (RBA); however, at high elevations, topographically drier and southerly microhabitats had higher ACS and lower RBA. TWI and aspect had the weakest effect on ACS and RBA in the mid-elevations. The relationship between slope and ACS and RBA was significantly positive but not evidently related to the broader-scale environmental gradient.
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Affiliation(s)
- Changxing Zhao
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China
| | - Jinrong Liu
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China.
| | - Wenbo Mou
- State Key Laboratory of Grassland Agro-ecosystems, School of Life Science, Lanzhou University, Lanzhou 730000, China
| | - Weijun Zhao
- Academy of Water Resources Conservation Forests in Qilian Mountains of Gansu Province, Zhangye 734000, China
| | - Ziqiang Zhou
- Institute of Geological Natural Disaster Prevention and Control, Gansu Academy of Sciences, Lanzhou 730030, China
| | - Feng Ta
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China
| | - Longju Lei
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China
| | - Chaonan Li
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China
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13
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Liu C, Shi S, Wang T, Gong W, Xu L, Shi Z, Du J, Qu F. Analysis of Net Primary Productivity Variation and Quantitative Assessment of Driving Forces-A Case Study of the Yangtze River Basin. PLANTS (BASEL, SWITZERLAND) 2023; 12:3412. [PMID: 37836151 PMCID: PMC10574783 DOI: 10.3390/plants12193412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 09/22/2023] [Accepted: 09/24/2023] [Indexed: 10/15/2023]
Abstract
Net primary productivity (NPP) can indirectly reflect vegetation's capacity for CO2 fixation, but its spatiotemporal dynamics are subject to alterations to some extent due to the influences of climate change and human activities. In this study, NPP is used as an indicator to investigate vegetarian carbon ability changes in the vital ecosystems of the Yangtze River Basin (YRB) in China. We also explored the NPP responses to climate change and human activities. We conducted a comprehensive analysis of the temporal dynamics and spatial variations in NPP within the YRB ecosystems from 2003 to 2020. Furthermore, we employed residual analysis to quantitatively assess the contributions of climate factors and human activities to NPP changes. The research findings are as follows: (1) Over the 18-year period, the average NPP within the basin amounted to 543.95 gC/m2, displaying a noticeable fluctuating upward trend with a growth rate of approximately 3.1 gC/m2; (2) The areas exhibiting an increasing trend in NPP account for 82.55% of the total study area. Regions with relatively high stability in the basin covered 62.36% of the total area, while areas with low stability accounted for 2.22%, mainly situated in the Hengduan Mountains of the western Sichuan Plateau; (3) NPP improvement was jointly driven by human activities and climate change, with human activities contributing more significantly to NPP growth. Specifically, the contributions were 65.39% in total, with human activities contributing 59.28% and climate change contributing 40.01%. This study provides an objective assessment of the contributions of human activities and climate change to vegetation productivity, offering crucial insights for future ecosystem development and environmental planning.
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Affiliation(s)
- Chenxi Liu
- Electronic Information School, Wuhan University, Wuhan 430072, China; (C.L.)
| | - Shuo Shi
- Electronic Information School, Wuhan University, Wuhan 430072, China; (C.L.)
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan 430079, China
- Perception and Effectiveness Assessment for Carbon-Neutrality Efforts, Engineering Research Center of Ministry of Education, Wuhan 430079, China
| | - Tong Wang
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan 430079, China
| | - Wei Gong
- Electronic Information School, Wuhan University, Wuhan 430072, China; (C.L.)
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan 430079, China
- Perception and Effectiveness Assessment for Carbon-Neutrality Efforts, Engineering Research Center of Ministry of Education, Wuhan 430079, China
- Wuhan Institute of Quantum Technology, Wuhan 430206, China
| | - Lu Xu
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan 430079, China
| | - Zixi Shi
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan 430079, China
| | - Jie Du
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan 430079, China
| | - Fangfang Qu
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan 430079, China
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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.
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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.
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