1
|
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.
Collapse
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
| |
Collapse
|
2
|
Qiu S, Brandt MS, Horion S, Ding Z, Tong X, Hu T, Peng J, Fensholt R. Facing the challenge of NDVI dataset consistency for improved characterization of vegetation response to climate variability. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 944:173308. [PMID: 38795990 DOI: 10.1016/j.scitotenv.2024.173308] [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: 10/15/2023] [Revised: 05/14/2024] [Accepted: 05/15/2024] [Indexed: 05/28/2024]
Abstract
Non-linear trend detection in Earth observation time series has become a standard method to characterize changes in terrestrial ecosystems. However, results are largely dependent on the quality and consistency of the input data, and only few studies have addressed the impact of data artifacts on the interpretation of detected abrupt changes. Here we study non-linear dynamics and turning points (TPs) of temperate grasslands in East Eurasia using two independent state-of-the-art satellite NDVI datasets (CGLS v3 and MODIS C6) and explore the impact of water availability on observed vegetation changes during 2001-2019. By applying the Break For Additive Season and Trend (BFAST01) method, we conducted a classification typology based on vegetation dynamics which was spatially consistent between the datasets for 40.86 % (459,669 km2) of the study area. When considering also the timing of the TPs, 27.09 % of the pixels showed consistent results between datasets, suggesting that careful interpretation was needed for most of the areas of detected vegetation dynamics when applying BFAST to a single dataset. Notably, for these areas showing identical typology we found that interrupted decreases in vegetation productivity were dominant in the transition zone between desert and steppes. Here, a strong link with changes in water availability was found for >80 % of the area, indicating that increasing drought stress had regulated vegetation productivity in recent years. This study shows the necessity of a cautious interpretation of the results when conducting advanced characterization of vegetation response to climate variability, but at the same time also the opportunities of going beyond the use of single dataset in advanced time-series approaches to better understanding dryland vegetation dynamics for improved anthropogenic interventions to combat vegetation productivity decrease.
Collapse
Affiliation(s)
- Sijing Qiu
- Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Martin Stefan Brandt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen 1350, Denmark
| | - Stephanie Horion
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen 1350, Denmark
| | - Zihan Ding
- Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Xiaowei Tong
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen 1350, Denmark
| | - Tao Hu
- Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Jian Peng
- Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China.
| | - Rasmus Fensholt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen 1350, Denmark
| |
Collapse
|
3
|
Liu Q, Guo H, Zhang J, Li S, Li J, Yao F, Mahecha MD, Peng J. Global assessment of terrestrial productivity in response to water stress. Sci Bull (Beijing) 2024; 69:2352-2356. [PMID: 38918143 DOI: 10.1016/j.scib.2024.05.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 05/09/2024] [Accepted: 05/10/2024] [Indexed: 06/27/2024]
Affiliation(s)
- Qi Liu
- School of Computer Engineering, Jiangsu University of Technology, Changzhou 213001, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 101408, China; Department of Remote Sensing, Helmholtz Centre for Environmental Research-UFZ, Leipzig 04318, Germany; Remote Sensing Centre for Earth System Research, Leipzig University, Leipzig 04103, Germany
| | - Huadong Guo
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
| | - Jiahua Zhang
- Remote Sensing and Digital Earth Center, School of Computer Science and Technology, Qingdao University, Qingdao 266071, China; Key Laboratory of Earth Observation of Hainan Province, Hainan Aerospace Information Research Institute, Chinese Academy of Sciences, Sanya 572000, China; Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China.
| | - Shijie Li
- Department of Remote Sensing, Helmholtz Centre for Environmental Research-UFZ, Leipzig 04318, Germany; Remote Sensing Centre for Earth System Research, Leipzig University, Leipzig 04103, Germany; School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Ji Li
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Fengmei Yao
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 101408, China.
| | - Miguel D Mahecha
- Department of Remote Sensing, Helmholtz Centre for Environmental Research-UFZ, Leipzig 04318, Germany; Remote Sensing Centre for Earth System Research, Leipzig University, Leipzig 04103, Germany; German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig 04103, Germany
| | - Jian Peng
- Department of Remote Sensing, Helmholtz Centre for Environmental Research-UFZ, Leipzig 04318, Germany; Remote Sensing Centre for Earth System Research, Leipzig University, Leipzig 04103, Germany.
| |
Collapse
|
4
|
Varghese R, Behera S, Behera MD. Tropical ocean teleconnections with gross primary productivity of monsoon-Asia. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 938:173337. [PMID: 38797406 DOI: 10.1016/j.scitotenv.2024.173337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 05/07/2024] [Accepted: 05/16/2024] [Indexed: 05/29/2024]
Abstract
The intricate oceanic climate interactions with terrestrial primary production of Asian ecosystems exert crucial social-economical-environmental repercussions. Yet, a holistic understanding of tropical sea surface temperature (SST) anomalies associated with the gross primary productivity (GPP) variations of monsoon-Asia remains constrained. This study provides a statistical framework demonstrating how SST perturbations in the tropics influence GPP fluctuations in monsoon-Asia by modulating hydrothermal conditions of different climate system components. Observation evidence explicitly illustrated the characteristic anomalous SST signatures of positive and negative GPP anomalies in South and Southeast Asia during June-August. The SST anomalies of the central-eastern tropical Pacific showed a robust negative impact on the GPP variability of South-Asia. The GPP alterations in maritime-Southeast-Asia exhibited strong connections with SST anomalies of the western Pacific (positive) and eastern equatorial Pacific (negative). The oceanic signals in the GPP variability of South-Asia and maritime-Southeast-Asia mirrored canonical El Niño and La Niña patterns. The detected SST-GPP link is feasible through large-scale atmospheric circulation variability and the consequent regional modulation of heat and moisture fluxes. The anomalous strengthening (weakening) of Walker cell enhances (reduces) water availability to plants for photosynthesis during the La Niña (El Niño) phase of the ENSO cycle and thus elevates (lowers) GPP in South-Asia and Maritime-southeast-Asia. In contrast, the enhanced GPP anomaly in mainland-Southeast-Asia depicts signs of canonical La Niña and Indian Ocean subtropical dipole (IOSD) teleconnections. The positive impact of IOSD was through the modulation of the Mascarene High and the consequent impact on the monsoon. Meanwhile, decreased GPP bears the imprint of El Niño Modoki and warm tropical Indian Ocean SSTs. The atmospheric teleconnections demonstrated the delayed impact of El Niño Modoki on GPP variability through the Indian Ocean capacitor effect. Our findings could be instrumental in forecasting the probable effects on vegetation growth in monsoon-Asia associated with high-frequency tropical oceanic changes.
Collapse
Affiliation(s)
- Roma Varghese
- Centre for Ocean, River, Atmosphere and Land Sciences, Indian Institute of Technology Kharagpur, India.
| | - Swadhin Behera
- Applications Laboratory, Research Institute for Value Added Information Generation, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan.
| | - Mukunda Dev Behera
- Centre for Ocean, River, Atmosphere and Land Sciences, Indian Institute of Technology Kharagpur, India.
| |
Collapse
|
5
|
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.
Collapse
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
| |
Collapse
|
6
|
Kumar BSK, Sarma VVSS. Dissolved organic carbon (DOC) and labile organic compounds' spatial and temporal variations in coastal Indian groundwater: their bioavailability and transfer to neighboring coastal waters of India. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024:10.1007/s11356-024-34509-x. [PMID: 39102145 DOI: 10.1007/s11356-024-34509-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 07/23/2024] [Indexed: 08/06/2024]
Abstract
Submarine groundwater drainage (SGD) changes the elemental composition of the neighboring coastal ocean and impacts the biogeochemical cycles. To examine the seasonal and spatial variability in dissolved organic carbon (DOC) and labile organic compound biochemical compounds like dissolved carbohydrates (TDCHO), dissolved proteins (TDPRO), and dissolved free amino acid (TDFAA) concentrations during the dry and wet periods, groundwater samples were taken at 90 locations (180 samples) along the Indian coast. The mean DOC contents in Indian coastal groundwaters were more significant than the global mean values. DOC, TDCHO, TDPRO, and TDFAA concentrations are higher during wet than dry periods. The DOC and labile organic compound showed a substantial positive association with soil organic carbon, and respective labile compounds in soil, population, and land usage and poor relation with woodland territories, implying that soil organic compounds leaching is a source of DOC and other labile organic compounds into the groundwater. DOC and other labile compounds concentrations were linearly associated with population density, land usage, and sewage production, demonstrating that anthropogenic activities tightly regulate the formation of DOC in groundwater. During the wet and dry periods, total labile organic compounds (TDCHO, TDFAA, and TDPRO) constituted 21% and 10.5% of DOC, respectively. Compared to the wet time, more aromatic compounds accumulated during the dry season but were less bioavailable. SGD DOC flux contributed 2-7% of riverine DOC flux to the coastal ocean. The SGD flux from the Indian subcontinent to the nearby northern Indian Ocean accounts for approximately 2% of the worldwide SGD flux. The effect of DOC flux via SGD on coastal bacterial activity, the plankton food web, and the oxygen minimum zone must be studied.
Collapse
Affiliation(s)
- B S K Kumar
- CSIR-National Institute of Oceanography, 176 Lawsons Bay Colony, Visakhapatnam, India.
- Centre for Marine Living Resources and Ecology, Kochi, India.
| | - V V S S Sarma
- CSIR-National Institute of Oceanography, 176 Lawsons Bay Colony, Visakhapatnam, India
- Academy of Scientific and Innovative Research, Ghaziabad, India
| |
Collapse
|
7
|
Xu Z, Shen X, Ge S, Sun Q, Yang Y, Cao L. An advanced TSMK-FVC approach combined with Landsat 5/8 imagery for assessing the long-term effects of terrain and climate on vegetation growth. FRONTIERS IN PLANT SCIENCE 2024; 15:1363690. [PMID: 39091321 PMCID: PMC11291374 DOI: 10.3389/fpls.2024.1363690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Accepted: 06/17/2024] [Indexed: 08/04/2024]
Abstract
Introduction As an exceptional geographical entity, the vegetation of the Qinghai-Tibetan Plateau (QTP) exhibits high sensitivity to climate change. The Baima Snow Mountain National Nature Reserve (BNNR) is located in the south-eastern sector of the QTP, serving as a transition area from sub-tropical evergreen broadleaf forest to high-mountain vegetation. However, there has been limited exploration into predicting the temporal and spatial variability of vegetation cover using anti-interference methods to address outliers in long-term historical data. Additionally, the correlation between these variables and environmental factors in natural forests with complex terrain has rarely been analyzed. Methods This study has developed an advanced approach based on TS (Theil-Sen slope estimator) MK (Mann-Kendall test)-FVC (fractional vegetation cover) to accurately evaluate and predict the time and spatial shifts in FVC within the BNNR, utilizing the GEE (Google Earth Engine). The satellite data utilized in this paper consisted of Landsat images spanning from 1986 to2020. By integrating TS and MK methodologies to monitor and assess the FVC trend, the Hurst index was employed to forecast FVC. Furthermore, the association between FVC and topographic factors was evaluated, the partial correlation between FVC and climatic influences was analyzed at the pixel level (30×30m). Results and discussion Here are the results of this research: (1) Overall, the FVC of the BNNR exhibits a growth trend, with the mean FVC value increasing from 59.40% in 1986 to 68.67% in 2020. (2) The results based on the TS-MK algorithm showed that the percentage of the area of the study area with an increasing and decreasing trend was 59.03% (significant increase of 28.04%) and 22.13% (significant decrease of 6.42%), respectively. The coupling of the Hurst exponent with the Theil-Sen slope estimator suggests that the majority of regions within the BNNR are projected to sustain an upward trend in FVC in the future. (3) Overlaying the outcomes of TS-MK with the terrain factors revealed that the FVC changes were notably influenced by elevation. The partial correlation analysis between climate factors and vegetation changes indicated that temperature exerts a significant influence on vegetation cover, demonstrating a high spatial correlation.
Collapse
Affiliation(s)
- Zhenxian Xu
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, Jiangsu, China
| | - Xin Shen
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, Jiangsu, China
| | - Sang Ge
- Yunnan Baima Snow Mountain National Nature Reserve Management Bureau, Shangri-La, Yunnan, China
| | - Qinglei Sun
- Yunnan Baima Snow Mountain National Nature Reserve Management Bureau, Shangri-La, Yunnan, China
| | - Ying Yang
- Yunnan Baima Snow Mountain National Nature Reserve Management Bureau, Shangri-La, Yunnan, China
| | - Lin Cao
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, Jiangsu, China
| |
Collapse
|
8
|
Gizawu Garbaba F, Negasa Wolteji B. Application of geospatial technology on land suitability analysis for wheat and maize farming: In a case of Guder sub-watershed North West Oromia, Ethiopia. Heliyon 2024; 10:e33557. [PMID: 39040410 PMCID: PMC11261788 DOI: 10.1016/j.heliyon.2024.e33557] [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: 12/16/2023] [Revised: 06/21/2024] [Accepted: 06/24/2024] [Indexed: 07/24/2024] Open
Abstract
Cereal crops like wheat and maize are crucial to providing food security in rural areas of Ethiopia. However, due to population growth, agricultural practices for these cereal crops have been expanded to vulnerable areas, and increasing land degradation. Geospatial technologies are essential for decision-making to reduce land degradation and ensure sustainable agriculture activities. In the Guder sub-watershed, Oromia regional state of Ethiopia, where land degradation has been a persistent issue, agricultural suitability study is crucial. This study is focused on the Guder sub-watershed, which aimed to analyze the land suitability based on ten controlling parameters, including elevation, slope, soil texture, soil depth, soil PH, soil drainage, proximity to the road, temperature, rainfall and land use/land cover, for the two most significant cereal crops (wheat and maize). All of these factors were weighted in accordance with the relative importance of each component for the appropriateness of wheat and maize land suitability using MCDA and AHP method, based on the recommendations of numerous writers and expert opinions. The findings of the study showed that 6 %, 50.58 %, 23.26 %, and 20.26 % of the total study area were highly, moderately, marginally and not suitable for wheat cultivation, respectively, whereas 5.1 %, 57.3 %, 17.3 %, and 20.3 % of the study area were highly, moderately, marginally and not suitable for cultivating maize crop respectively. This result support decision makers to develop land use planning thereby improve productivity and minimize land degradation.
Collapse
Affiliation(s)
- Fayera Gizawu Garbaba
- Department of Earth Sciences, College of Natural and Computational Sciences, Wollega University Nekemte Campus, Ethiopia
| | - Bayisa Negasa Wolteji
- Department of Earth Sciences, College of Natural and Computational Sciences, Wollega University Nekemte Campus, Ethiopia
| |
Collapse
|
9
|
Liu Q, Liang L, Sun T, Wang X, Yan D, Li C. Hydrological response of drought impacts across catchments worldwide. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 931:172912. [PMID: 38697524 DOI: 10.1016/j.scitotenv.2024.172912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 04/22/2024] [Accepted: 04/29/2024] [Indexed: 05/05/2024]
Abstract
Drought will inevitably affect linkages between different water components, which have previously been investigated across different spatiotemporal scales. Elucidating drought-induced precipitation (P) partition effects remain uncertain because they involve drought propagation, even inducing streamflow (Q) non-stationarity. This study collected data on 1069 catchments worldwide to investigate Q and evapotranspiration (ET) impacts from P deficit-derived reductions in drought propagation. Results show that P deficits trigger soil moisture drought, subsequently inducing negative Q and ET anomalies that vary under different climate regimes. Generally, drought-induced hydrological legacies indicate that breaks in hydrological linkages cause a relatively rapid Q response (i.e., negative Q anomaly), amplified by drought strength and duration. Compared with the Q response, the ET response to drought stress involves a more complex, associative vegetation response and an associative evaporative state controlled by water and energy, which lags behind the Q response and can also intensify with increasing drought severity and duration. This is confirmed by the ET response under different climate regimes. Namely, in drier climates, a positive ET anomaly can be detected in its early stages, this is unusual in wetter climate. Additionally, Q and ET sensitivity to drought strength can be mechanistically explained by the water and energy status. This implies that ET is mainly controlled by water and energy, resulting in higher and lower drought sensitivity within water- and energy-limited regions, respectively. Understanding the impacts of drought on Q and ET response is essential for identifying key linkages in drought propagation across different climate regimes. Our findings will also be useful for developing early warning and adaptation systems that support both human and ecosystem requirements.
Collapse
Affiliation(s)
- Qiang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Liqiao Liang
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Tao Sun
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Xuan Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Denghua Yan
- State Key Laboratory of Simulation and Regulation of the Water Cycle in River Basins, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
| | - Chunhui Li
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China
| |
Collapse
|
10
|
Zhou J, Yang Y, Liu Q, Liang L, Wang X, Sun T, Li S, Gan L. Revisiting the hydrological legacy of revegetation on China's Loess Plateau using Eagleson's ecohydrological perspective. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 929:172758. [PMID: 38670382 DOI: 10.1016/j.scitotenv.2024.172758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 04/23/2024] [Accepted: 04/23/2024] [Indexed: 04/28/2024]
Abstract
Revegetation has resulted in a trend of increasing vegetation greenness on the Chinese Loess Plateau. However, it remains unclear whether the regional vegetation coverage exceeds hydroclimatic limitations in the context of revegetation, and the hydrological effects of greening are controversial. Eagleson's optimality hypothesis can explain some of the hydrological effects on the Loess Plateau. Here, building on previous research, the geospatial vegetation states were estimated for pre- and post-revegetation periods on the Loess Plateau from 1982 to 2015 using Eagleson's ecological optimality theory. Additionally, a drought composite analysis approach was utilized to investigate the hydrological effects related to drought (including sensitivity and partitioning) under various vegetation states. It was found that revegetation increased the proportion of catchments in the equilibrium state and decreased the proportion in the disturbed state, owing to a wetter climate compared with the pre-revegetation period. Root-zone soil drought, driven by precipitation (P) deficit, asymmetrically triggered hydrological effects for both the pre- and post-revegetation periods, with reduced runoff (Q) for both periods and a decrease in evapotranspiration (ET) during the pre-revegetation period but an increase in ET during the post-revegetation period. Moreover, catchments in an equilibrium state exhibited lower sensitivity between ET and P, and more stable partitioning of ET with regards to P, compared with those in a disturbed state. These results underscore the theoretical framework that an equilibrium state is crucial for maintaining ecosystem ET. Our results highlight the necessity of considering the hydrologic regulation of vegetation states when assessing the hydrological effects of vegetation change.
Collapse
Affiliation(s)
- Jialiang Zhou
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yuting Yang
- State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
| | - Qiang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China.
| | - Liqiao Liang
- Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Xuan Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Tao Sun
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Shuzhen Li
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Luoyang Gan
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China
| |
Collapse
|
11
|
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
|
12
|
Mao R, Xing L, Wu Q, Song J, Li Q, Long Y, Shi Y, Huang P, Zhang Q. Evaluating net primary productivity dynamics and their response to land-use change in the loess plateau after the 'Grain for Green' program. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 360:121112. [PMID: 38733847 DOI: 10.1016/j.jenvman.2024.121112] [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: 02/15/2024] [Revised: 05/06/2024] [Accepted: 05/06/2024] [Indexed: 05/13/2024]
Abstract
Assessing net primary productivity (NPP) dynamics and the contribution of land-use change (LUC) to NPP can help guide scientific policy to better restore and control the ecological environment. Since 1999, the "Green for Grain" Program (GGP) has strongly affected the spatial and temporal pattern of NPP on the Loess Plateau (LP); however, the multifaceted impact of phased vegetation engineering measures on NPP dynamics remains unclear. In this study, the Carnegie-Ames-Stanford Approach (CASA) model was used to simulate NPP dynamics and quantify the relative contributions of LUC and climate change (CC) to NPP under two different scenarios. The results showed that the average NPP on the LP increased from 240.7 gC·m-2 to 422.5 gC·m-2 from 2001 to 2020, with 67.43% of the areas showing a significant increasing trend. LUC was the main contributor to NPP increases during the study period, and precipitation was the most important climatic factor affecting NPP dynamics. The cumulative amount of NPP change caused by LUC (ΔNPPLUC) showed a fluctuating growth trend (from 46.23 gC·m-2 to 127.25 gC·m-2), with a higher growth rate in period ΙΙ (2010-2020) than in period Ι (2001-2010), which may be related to the accumulation of vegetation biomass and the delayed effect of the GGP on NPP. The contribution rate of LUC to increased NPP in periods Ι and ΙΙ was 101.2% and 51.2%, respectively. Regarding the transformation mode, the transformation of grassland to forest had the greatest influence on ΔNPPLUC. Regarding land-use type, the increased efficiency of NPP was improved in cropland, grassland, and forest. This study provides a scientific basis for the scientific management and development of vegetation engineering measures and regional sustainable development.
Collapse
Affiliation(s)
- Ruichen Mao
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China
| | - Lutong Xing
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China
| | - Qiong Wu
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China
| | - Jinxi Song
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China; Institute of Qinling Mountains, Northwest University, Xi'an, 710127, China.
| | - Qi Li
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China
| | - Yongqing Long
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China
| | - Yuna Shi
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China
| | - Peng Huang
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China
| | - Qifang Zhang
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China
| |
Collapse
|
13
|
Montesano PM, Frost M, Li J, Carroll M, Neigh CSR, Macander MJ, Sexton JO, Frost GV. A shift in transitional forests of the North American boreal will persist through 2100. COMMUNICATIONS EARTH & ENVIRONMENT 2024; 5:290. [PMID: 38826489 PMCID: PMC11142915 DOI: 10.1038/s43247-024-01454-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 05/17/2024] [Indexed: 06/04/2024]
Abstract
High northern latitude changes with Arctic amplification across a latitudinal forest gradient suggest a shift towards an increased presence of trees and shrubs. The persistence of change may depend on the future scenarios of climate and on the current state, and site history, of forest structure. Here, we explore the persistence of a gradient-based shift in the boreal by connecting current forest patterns to recent tree cover trends and future modeled estimates of canopy height through 2100. Results show variation in the predicted potential height changes across the structural gradient from the boreal forest through the taiga-tundra ecotone. Positive potential changes in height are concentrated in transitional forests, where recent positive changes in cover prevail, while potential change in boreal forest is highly variable. Results are consistent across climate scenarios, revealing a persistent biome shift through 2100 in North America concentrated in transitional landscapes regardless of climate scenario.
Collapse
Affiliation(s)
- Paul M. Montesano
- NASA Goddard Space Flight Center, Greenbelt, MD USA
- ADNET Systems, Inc., Bethesda, MD USA
| | - Melanie Frost
- NASA Goddard Space Flight Center, Greenbelt, MD USA
- ASRC Federal InuTeq, Beltsville, MD USA
| | - Jian Li
- NASA Goddard Space Flight Center, Greenbelt, MD USA
- ASRC Federal InuTeq, Beltsville, MD USA
| | - Mark Carroll
- NASA Goddard Space Flight Center, Greenbelt, MD USA
| | | | | | | | | |
Collapse
|
14
|
Li Q, He G, Zhang D, Liu X. Quantitative analysis of the impact of climate variability and human activities on grassland productivity of the Qilian Mountain National Park, China. PLoS One 2024; 19:e0300577. [PMID: 38728344 PMCID: PMC11086858 DOI: 10.1371/journal.pone.0300577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 02/29/2024] [Indexed: 05/12/2024] Open
Abstract
To quantitatively analyze the impact of climate variability and human activities on grassland productivity of China's Qilian Mountain National Park, this study used Carnegic-Ames-Stanford Approach model (CASA) and Integrated Vegetation model improved by the Comprehensive and Sequential Classification System (CSCS) to assess the trends of grassland NPP from 2000 to 2015, the residual trend analysis method was used to quantify the impact of human activities and climate change on the grassland based on the NPP changes. The actual grassland NPP accumulation mainly occurred in June, July and August (autumn); the actual NPP showed a fluctuating upward trend with an average increase of 2.2 g C·m-2 a-1, while the potential NPP increase of 1.6 g C·m-2 a-1 and human-induced NPP decreased of 0.5 g C·m-2 a-1. The annual temperature showed a fluctuating upward trend with an average increase of 0.1°C 10a-1, but annual precipitation showed a fluctuating upward trend with an average annual increase of 1.3 mm a-1 from 2000 to 2015. The area and NPP of grassland degradation caused by climate variability was significantly greater than that caused by human activities and mainly distributed in the northwest and central regions, but area and NPP of grassland restored caused by human activities was significantly greater than that caused by climate variability and mainly distributed in the southeast regions. In conclusion, grassland in Qilian Mountain National Park showed a trend of degradation based on distribution area, but showed a trend of restoration based on actual NPP. Climate variability was the main cause of grassland degradation in the northwestern region of study area, and restoration of grassland in the eastern region was the result of the combined effects of human activities and climate variability. Under global climate change, the establishment of Qilian Mountain National Park was of great significance to the grassland's protection and the grasslands ecological restoration that have been affected by humans.
Collapse
Affiliation(s)
- Qiang Li
- State Key Laboratory of Plateau Ecology and Agriculture/College of Agriculture and Animal Husbandry, Qinghai University, Xining, 810016, China
| | - Guoxing He
- College of Grassland Science, Gansu Agricultural University, Lanzhou, P. R. China
| | - Degang Zhang
- College of Grassland Science, Gansu Agricultural University, Lanzhou, P. R. China
| | - Xiaoni Liu
- College of Grassland Science, Gansu Agricultural University, Lanzhou, P. R. China
| |
Collapse
|
15
|
Liu Y, Wu G, Ma B, Wu T, Wang X, Wu Q. Revealing climatic and groundwater impacts on the spatiotemporal variations in vegetation coverage in marine sedimentary basins of the North China Plain, China. Sci Rep 2024; 14:10085. [PMID: 38698166 PMCID: PMC11066038 DOI: 10.1038/s41598-024-60838-5] [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: 01/02/2024] [Accepted: 04/28/2024] [Indexed: 05/05/2024] Open
Abstract
The North China Plain (NCP) is one of the three great plains in China and also serves as a vital region for grain, cotton, and oil production. Under the influence of regional hydrothermal changes, groundwater overexploitation, and seawater intrusion, the vegetation coverage is undergoing continuous alterations. However, a comprehensive assessment of impacts of precipitation, temperature, and groundwater on vegetation in marine sedimentary regions of the NCP is lacking. Heilonggang Basin (HB) is located in the low-lying plain area in the east of NCP, which is part of the NCP. In this study, the HB was chosen as a typical area of interest. We collected a series of data, including the Normalized Difference Vegetation Index (NDVI), precipitation, temperature, groundwater depth, and Total Dissolved Solids (TDS) from 2001 to 2020. Then the spatiotemporal variation in vegetation was analyzed, and the underlying driving mechanisms of vegetation variation were explored in this paper. The results show that NDVI experiences a rapid increase from 2001 to 2004, followed by stable fluctuations from 2004 to 2020. The vegetation in the HB has achieved an overall improvement in the past two decades, with 76% showing improvement, mainly in the central and eastern areas, and 24% exhibiting deterioration in other areas. From 2001 to 2020, NDVI correlates positively with precipitation, whereas its relationship with temperature fluctuates between positive and negative, and is not statistically significant. There is a threshold for the synergistic change of NDVI and groundwater depth. When the groundwater depth is lower than 3.8 m, NDVI increases sharply with groundwater depth. However, beyond this threshold, NDVI tends to stabilize and fluctuate. In the eastern coastal areas, NDVI exhibits a strong positive correlation with groundwater depth, influenced by the surface soil TDS controlled by groundwater depth. In the central regions, a strong negative correlation is observed, where NDVI is primarily impacted by soil moisture under the control of groundwater. In the west and south, a strong positive correlation exists, with NDVI primarily influenced by the intensity of groundwater exploitation. Thus, precipitation and groundwater are the primary driving forces behind the spatiotemporal variability of vegetation in the HB, while in contrast, the influence of temperature is uncertain. This study has elucidated the mechanism of vegetation response, providing a theoretical basis for mitigating adverse factors affecting vegetation growth and formulating rational water usage regulations in the NCP.
Collapse
Affiliation(s)
- Yang Liu
- Hebei Key Laboratory of Geological Resources and Environment Monitoring and Protection, Hebei Geo-Environment Monitoring Institute, Shijiazhuang, 050021, China
| | - Guangdong Wu
- Changjiang Water Resources Commission of the Ministry of Water Resources of China, Changjiang River Scientific Research Institute, Wuhan, 430010, China.
- Hubei Key Laboratory of Water Resources & Eco-Environmental Sciences, Wuhan, 430010, China.
| | - Baiheng Ma
- Hebei Key Laboratory of Geological Resources and Environment Monitoring and Protection, Hebei Geo-Environment Monitoring Institute, Shijiazhuang, 050021, China
| | - Tao Wu
- Hebei Key Laboratory of Geological Resources and Environment Monitoring and Protection, Hebei Geo-Environment Monitoring Institute, Shijiazhuang, 050021, China
- Hebei Center for Ecological and Environmental Geology Research, Hebei GEO University, Shijiazhuang, 050031, China
| | - Xinzhou Wang
- Hebei Key Laboratory of Geological Resources and Environment Monitoring and Protection, Hebei Geo-Environment Monitoring Institute, Shijiazhuang, 050021, China
| | - Qinghua Wu
- Changjiang Water Resources Commission of the Ministry of Water Resources of China, Changjiang River Scientific Research Institute, Wuhan, 430010, China
| |
Collapse
|
16
|
Pearson AR, Fox BRS, Hellstrom JC, Vandergoes MJ, Breitenbach SFM, Drysdale RN, Höpker SN, Wood CT, Schiller M, Hartland A. Warming drives dissolved organic carbon export from pristine alpine soils. Nat Commun 2024; 15:3522. [PMID: 38664386 PMCID: PMC11045798 DOI: 10.1038/s41467-024-47706-6] [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: 07/10/2023] [Accepted: 04/10/2024] [Indexed: 04/28/2024] Open
Abstract
Despite decades of research, the influence of climate on the export of dissolved organic carbon (DOC) from soil remains poorly constrained, adding uncertainty to global carbon models. The limited temporal range of contemporary monitoring data, ongoing climate reorganisation and confounding anthropogenic activities muddy the waters further. Here, we reconstruct DOC leaching over the last ~14,000 years using alpine environmental archives (two speleothems and one lake sediment core) across 4° of latitude from Te Waipounamu/South Island of Aotearoa New Zealand. We selected broadly comparable palaeoenvironmental archives in mountainous catchments, free of anthropogenically-induced landscape changes prior to ~1200 C.E. We show that warmer temperatures resulted in increased allochthonous DOC export through the Holocene, most notably during the Holocene Climatic Optimum (HCO), which was some 1.5-2.5 °C warmer than the late pre-industrial period-then decreased during the cooler mid-Holocene. We propose that temperature exerted the key control on the observed doubling to tripling of soil DOC export during the HCO, presumably via temperature-mediated changes in vegetative soil C inputs and microbial degradation rates. Future warming may accelerate DOC export from mountainous catchments, with implications for the global carbon cycle and water quality.
Collapse
Affiliation(s)
- Andrew R Pearson
- Environmental Research Institute, School of Science, Faculty of Science and Engineering, University of Waikato, Kirikiriroa Hamilton, Waikato, Aotearoa, New Zealand.
- Institute of Environmental Science and Research (ESR), Ōtautahi Christchurch, Aotearoa, New Zealand.
| | - Bethany R S Fox
- Department of Biological and Geographical Sciences, University of Huddersfield, Huddersfield, UK
| | - John C Hellstrom
- School of Geography, Earth and Atmospheric Sciences, University of Melbourne, Melbourne, VIC, Australia
| | | | | | - Russell N Drysdale
- School of Geography, Earth and Atmospheric Sciences, University of Melbourne, Melbourne, VIC, Australia
| | - Sebastian N Höpker
- Environmental Research Institute, School of Science, Faculty of Science and Engineering, University of Waikato, Kirikiriroa Hamilton, Waikato, Aotearoa, New Zealand
| | - Christopher T Wood
- Environmental Research Institute, School of Science, Faculty of Science and Engineering, University of Waikato, Kirikiriroa Hamilton, Waikato, Aotearoa, New Zealand
- GNS Science, Te Awa Kairangi ki Tai Lower Hutt, Aotearoa, New Zealand
| | - Martin Schiller
- Centre for Star and Planet Formation, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Adam Hartland
- Environmental Research Institute, School of Science, Faculty of Science and Engineering, University of Waikato, Kirikiriroa Hamilton, Waikato, Aotearoa, New Zealand.
- Lincoln Agritech Ltd, Ruakura, Kirikiriroa Hamilton, Waikato, Aotearoa, New Zealand.
| |
Collapse
|
17
|
Kearsley E, Verbeeck H, Stoffelen P, Janssens SB, Yakusu EK, Kosmala M, De Mil T, Bauters M, Kitima ER, Ndiapo JM, Chuda AL, Richardson AD, Wingate L, Ilondea BA, Beeckman H, van den Bulcke J, Boeckx P, Hufkens K. Historical tree phenology data reveal the seasonal rhythms of the Congo Basin rainforest. PLANT-ENVIRONMENT INTERACTIONS (HOBOKEN, N.J.) 2024; 5:e10136. [PMID: 38476212 PMCID: PMC10926959 DOI: 10.1002/pei3.10136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 01/05/2024] [Accepted: 01/23/2024] [Indexed: 03/14/2024]
Abstract
Tropical forest phenology directly affects regional carbon cycles, but the relation between species-specific and whole-canopy phenology remains largely uncharacterized. We present a unique analysis of historical tropical tree phenology collected in the central Congo Basin, before large-scale impacts of human-induced climate change. Ground-based long-term (1937-1956) phenological observations of 140 tropical tree species are recovered, species-specific phenological patterns analyzed and related to historical meteorological records, and scaled to characterize stand-level canopy dynamics. High phenological variability within and across species and in climate-phenology relationships is observed. The onset of leaf phenophases in deciduous species was triggered by drought and light availability for a subset of species and showed a species-specific decoupling in time along a bi-modal seasonality. The majority of the species remain evergreen, although central African forests experience relatively low rainfall. Annually a maximum of 1.5% of the canopy is in leaf senescence or leaf turnover, with overall phenological variability dominated by a few deciduous species, while substantial variability is attributed to asynchronous events of large and/or abundant trees. Our results underscore the importance of accounting for constituent signals in canopy-wide scaling and the interpretation of remotely sensed phenology signals.
Collapse
Affiliation(s)
- Elizabeth Kearsley
- Computational and Applied Vegetation Ecology Lab, Department of Environment, Faculty of Bioscience EngineeringGhent UniversityGentBelgium
- BlueGreen LabsMelseleBelgium
| | - Hans Verbeeck
- Computational and Applied Vegetation Ecology Lab, Department of Environment, Faculty of Bioscience EngineeringGhent UniversityGentBelgium
| | | | - Steven B. Janssens
- Meise Botanic GardenMeiseBelgium
- Department of Biology, Leuven Plant InstituteKULeuvenLeuvenBelgium
| | - Emmanuel Kasongo Yakusu
- UGent‐Woodlab (Laboratory of Wood Technology), Department of Environment, Faculty of Bioscience EngineeringGhent UniversityGentBelgium
- Service of Wood BiologyRoyal Museum for Central AfricaTervurenBelgium
- Faculté de gestion des ressources naturelles renouvelablesUniversité de KisanganiKisanganiDemocratic Republic of Congo
| | - Margaret Kosmala
- Department of Organismic and Evolutionary BiologyHarvard UniversityCambridgeMassachusettsUSA
- CIBO TechnologiesCambridgeMassachusettsUSA
| | - Tom De Mil
- Forest is Life, TERRA Teaching and Research Centre, Gembloux Agro Bio‐TechUniversity of LiègeGemblouxBelgium
| | - Marijn Bauters
- Isotope Bioscience Laboratory ‐ ISOFYS, Department of Green Chemistry and TechnologyGhent UniversityGentBelgium
- Research Group of Plants and Ecosystems (PLECO), Department of BiologyUniversity of AntwerpWilrijkBelgium
| | - Elasi Ramanzani Kitima
- Institut National pour l'Etude et la Recherche Agronomiques‐INERAYangambiDemocratic Republic of Congo
| | - José Mbifo Ndiapo
- Institut National pour l'Etude et la Recherche Agronomiques‐INERAYangambiDemocratic Republic of Congo
| | - Adelard Lonema Chuda
- Institut National pour l'Etude et la Recherche Agronomiques‐INERAYangambiDemocratic Republic of Congo
| | - Andrew D. Richardson
- Center for Ecosystem Science and SocietyNorthern Arizona UniversityFlagstaffArizonaUSA
- School of Informatics, Computing and Cyber SystemsNorthern Arizona UniversityFlagstaffArizonaUSA
| | | | - Bhély Angoboy Ilondea
- UGent‐Woodlab (Laboratory of Wood Technology), Department of Environment, Faculty of Bioscience EngineeringGhent UniversityGentBelgium
- Service of Wood BiologyRoyal Museum for Central AfricaTervurenBelgium
- Institut National pour l'Étude et la Recherche AgronomiquesKinshasaDemocratic Republic of Congo
| | - Hans Beeckman
- Service of Wood BiologyRoyal Museum for Central AfricaTervurenBelgium
| | - Jan van den Bulcke
- UGent‐Woodlab (Laboratory of Wood Technology), Department of Environment, Faculty of Bioscience EngineeringGhent UniversityGentBelgium
| | - Pascal Boeckx
- Isotope Bioscience Laboratory ‐ ISOFYS, Department of Green Chemistry and TechnologyGhent UniversityGentBelgium
| | - Koen Hufkens
- Computational and Applied Vegetation Ecology Lab, Department of Environment, Faculty of Bioscience EngineeringGhent UniversityGentBelgium
- BlueGreen LabsMelseleBelgium
- INRAE, UMR ISPAVillenave d'OrnonFrance
| |
Collapse
|
18
|
Wang RY, Mo X, Ji H, Zhu Z, Wang YS, Bao Z, Li T. Comparison of the CASA and InVEST models' effects for estimating spatiotemporal differences in carbon storage of green spaces in megacities. Sci Rep 2024; 14:5456. [PMID: 38443413 PMCID: PMC10914835 DOI: 10.1038/s41598-024-55858-0] [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: 11/04/2023] [Accepted: 02/28/2024] [Indexed: 03/07/2024] Open
Abstract
Urban green space is a direct way to improve the carbon sink capacity of urban ecosystems. The carbon storage assessment of megacity green spaces is of great significance to the service function of urban ecosystems and the management of urban carbon zoning in the future. Based on multi-period remote sensing image data, this paper used the CASA model and the InVEST model to analyze the spatio-temporal variation and driving mechanism of carbon storage in Shenzhen green space and discussed the applicability of the two models to the estimation of carbon storage in urban green space. The research results showed that, from 2008 to 2022, in addition to the rapid expansion of construction land, the area of green space and other land types in Shenzhen showed a significant decrease trend. The estimation results of the carbon storage model showed that the carbon storage of green space shows a significant trend of reduction from 2008 to 2022, and the reduction amounts are 0.8 × 106 t (CASA model) and 0.64 × 106 t (InVEST model), respectively. The evaluation results of the model show that, in megacities, the spatial applicability of InVEST model is lower than that of CASA model, and the CASA model is more accurate in estimating the carbon storage of urban green space. The research results can provide a scientific basis for the assessment of the carbon sink capacity of megacity ecosystems with the goal of "dual carbon".
Collapse
Affiliation(s)
- Ruei-Yuan Wang
- Department of Geographical Science, Guangdong University of Petrochemical Technology (GDUPT), Maoming, 525000, Guangdong Province, China
| | - Xueying Mo
- Department of Geographical Science, Guangdong University of Petrochemical Technology (GDUPT), Maoming, 525000, Guangdong Province, China
| | - Hong Ji
- Department of Geographical Science, Guangdong University of Petrochemical Technology (GDUPT), Maoming, 525000, Guangdong Province, China
| | - Zhe Zhu
- Department of Geographical Science, Guangdong University of Petrochemical Technology (GDUPT), Maoming, 525000, Guangdong Province, China
| | - Yun-Shang Wang
- Graduate Institute, Fu Jen Catholic University, New Taipei City, 24205, Taiwan, China
| | - Zhilin Bao
- Water Conservancy and Civil Engineering College, Xinjiang Agricultural University, Urumqi, 830052, Xinjiang, China
| | - Taohui Li
- Key Laboratory of Plateau Geographic Processes and Environment Change of Yunnan Province, Faculty of Geography, Yunnan Normal University, Kunming, 650500, China.
| |
Collapse
|
19
|
Vermeulen LM, Verbist B, Van Meerbeek K, Slingsby J, Bernardino PN, Somers B. Wetness severity increases abrupt shifts in ecosystem functioning in arid savannas. GLOBAL CHANGE BIOLOGY 2024; 30:e17235. [PMID: 38497525 DOI: 10.1111/gcb.17235] [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: 07/10/2023] [Revised: 02/08/2024] [Accepted: 02/22/2024] [Indexed: 03/19/2024]
Abstract
The accelerating pace of climate change has led to unprecedented shifts in surface temperature and precipitation patterns worldwide, with African savannas being among the most vulnerable regions. Understanding the impacts of these extreme changes on ecosystem health, functioning and stability is crucial. This paper focuses on the detection of breakpoints, indicative of shifts in ecosystem functioning, while also determining relevant ecosystem characteristics and climatic drivers that increase susceptibility to these shifts within the semi-arid to arid savanna biome. Utilising a remote sensing change detection approach and rain use efficiency (RaUE) as a proxy for ecosystem functioning, spatial and temporal patterns of breakpoints in the savanna biome were identified. We then employed a novel combination of survival analysis and remote sensing time series analysis to compare ecosystem characteristics and climatic drivers in areas experiencing breakpoints versus areas with stable ecosystem functioning. Key ecosystem factors increasing savanna breakpoint susceptibility were identified, namely higher soil sand content, flatter terrain and a cooler long-term mean temperature during the wet summer season. Moreover, the primary driver of changes in ecosystem functioning in arid savannas, as opposed to wetter tropical savannas, was found to be the increased frequency and severity of rainfall events, rather than drought pressures. This research highlights the importance of incorporating wetness severity metrics alongside drought metrics to comprehensively understand climate-ecosystem interactions leading to abrupt shifts in ecosystem functioning in arid biomes. The findings also emphasise the need to consider the underlying ecosystem characteristics, including soil, topography and vegetation composition, in assessing ecosystem responses to climate change. While this research primarily concentrated on the southern African savanna as a case study, the methodological robustness of this approach enables its application to diverse arid and semi-arid biomes for the assessment of climate-ecosystem interactions that contribute to abrupt shifts.
Collapse
Affiliation(s)
- L M Vermeulen
- Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium
- African Climate and Development Initiative, University of Cape Town, Cape Town, South Africa
| | - B Verbist
- Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium
| | - K Van Meerbeek
- Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium
- KU Leuven Plant Institute, KU Leuven, Leuven, Belgium
| | - J Slingsby
- Department of Biological Sciences and Centre for Statistics in Ecology, Environment and Conservation, University of Cape Town, Cape Town, South Africa
- Fynbos Node, South African Environmental Observation Network, Centre for Biodiversity Conservation, Cape Town, South Africa
| | - P N Bernardino
- Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium
- Department of Plant Biology, University of Campinas, Campinas, SP, Brazil
| | - B Somers
- Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium
- KU Leuven Plant Institute, KU Leuven, Leuven, Belgium
| |
Collapse
|
20
|
Arrogante-Funes P, Osuna D, Arrogante-Funes F, Álvarez-Ripado A, G Bruzón A. Uncovering NDVI time trends in Spanish high mountain biosphere reserves: A detailed study. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 355:120527. [PMID: 38457893 DOI: 10.1016/j.jenvman.2024.120527] [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: 06/09/2023] [Revised: 01/11/2024] [Accepted: 02/29/2024] [Indexed: 03/10/2024]
Abstract
Global warming is increasing the vulnerability of ecosystems, especially in peninsular Spain. Biosphere Reserves are internationally protected areas that seek to protect biodiversity and, at the same time, promote sustainable development. Evaluating these protected areas is essential to verify environmental changes and establish priorities in their management. In this work, we have studied the time trends of NDVI in the high mountain Biosphere Reserves of Spain from 2001 to 2016 to check if the trend patterns are associated with some environmental variables. Significant differences were found between NDVI trends and high mountain Biosphere Reserves. Firstly, significant positive trends in NDVI were observed when analysing both reserves together. However, significant differences were found between the two reserves. The Ordesa-Viñamala Reserve shows higher positive NDVI trends and lower negative trends, while this pattern is reversed in Sierra Nevada. We observed how the fluctuations in temperature and drought due to climate change have already negatively affected the Mediterranean reserve (Sierra Nevada). In contrast, the alpine reserve (Ordesa-Viñamala) maintains positive NDVI trends. This study helps to close the gap in information related to Biosphere Reserves, which gives value to the work that is being carried out by the local communities that make up them, generating statistically significant results that Biosphere Reserves are protected areas that help us understand how to manage and govern socioecological systems sustainably.
Collapse
Affiliation(s)
- Patricia Arrogante-Funes
- Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, C/Tulipán s/n, Móstoles, 28933, Madrid, Spain; Research Group on Technologies for Landscape Analysis and Diagnosis (TADAT), Rey Juan Carlos University, C/Tulipán s/n, Móstoles, 28933, Madrid, Spain
| | - Dina Osuna
- Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, C/Tulipán s/n, Móstoles, 28933, Madrid, Spain
| | - Fátima Arrogante-Funes
- Universidad de Alcalá, Environmental Remote Sensing Research Group, Department of Geology, Geography and the Environment, Calle Colegios 2, 28801, Alcalá de Henares, Spain.
| | - Ariadna Álvarez-Ripado
- Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, C/Tulipán s/n, Móstoles, 28933, Madrid, Spain
| | - Adrián G Bruzón
- Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, C/Tulipán s/n, Móstoles, 28933, Madrid, Spain; Research Group on Technologies for Landscape Analysis and Diagnosis (TADAT), Rey Juan Carlos University, C/Tulipán s/n, Móstoles, 28933, Madrid, Spain
| |
Collapse
|
21
|
Zhang L, Zhang Y, Wang J, Liang X, Wei Y. Spatiotemporal evolution characteristics and driving forces of vegetation cover variations in the Chengdu-Chongqing region of China under the background of rapid urbanization. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:22976-22993. [PMID: 38418788 DOI: 10.1007/s11356-024-32645-y] [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: 11/06/2023] [Accepted: 02/21/2024] [Indexed: 03/02/2024]
Abstract
The research on the spatiotemporal changes and driving factors of ecosystems in rapidly urbanizing regions has always been a topic of widespread concern. As the fourth pole of China's economic development, the research on the Chengdu-Chongqing region has reference significance for the urbanization process of developing countries such as India, Brazil, and South Africa.The normalized difference vegetation index (NDVI) has been widely applied in studies of plant and ecosystem changes. Based on MODIS NDVI data from 2001 to 2020 and meteorological data of the same period, this study reveals the evolution of NDVI in the Chengdu-Chongqing region from three aspects: the spatiotemporal variation characteristics of NDVI, the prediction of future trends in vegetation coverage, and the response of vegetation to climate change and human activities. During the period of plant growth, the mean NDVI achieved a value of 0.78, and the vegetation coverage rate is increasing year by year. According to the Hurst index, the future NDVI in Chengdu-Chongqing region will tend to decrease, and its trend is opposite to that of the past period of time. The Chengdu-Chongqing region vegetation positively affected by human activities is greater than those negatively affected, and in terms of vegetation degradation, the impact of human activities is greater than climate change.
Collapse
Affiliation(s)
- Luoqi Zhang
- College of Resource, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yan Zhang
- College of Resource, Sichuan Agricultural University, Chengdu, 611130, China
| | - Junyi Wang
- College of Resource, Sichuan Agricultural University, Chengdu, 611130, China
| | - Xinyu Liang
- College of Resource, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yali Wei
- College of Resource, Sichuan Agricultural University, Chengdu, 611130, China.
| |
Collapse
|
22
|
He L, Guo J, Yang W, Jiang Q, Li X, Chen S, Zhang M, Li D. Changes in vegetation in China's drylands are closely related to afforestation compared with climate change. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169121. [PMID: 38070552 DOI: 10.1016/j.scitotenv.2023.169121] [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: 07/23/2023] [Revised: 10/02/2023] [Accepted: 12/03/2023] [Indexed: 01/18/2024]
Abstract
The response of vegetation to climate change and human activities has attracted considerable attention. However, quantitative studies on the effects of climate change and human activities on dryland vegetation in different seasons remain unclear. This study investigated the impacts of precipitation, temperature, soil water storage (SWS) (top [0-7 cm], shallow [7-28 cm], and middle [28-100 cm] layers), vapor pressure deficit (VPD), and afforestation on vegetation as well as their relative contribution rates during the rainy season ([RS], June to September), dry season ([DS], November to April), transition season ([TS], May and October), and all year period (AY) in China's drylands from 2001 to 2020 using the first-difference method. Areas with precipitation and SWS showing significant positive correlation with dryland vegetation (p < 0.05) were found to be larger in RS than in DS and TS, and the positive effect of SWS increased with soil depth in the 0-28 cm interval. Increasing VPD induced a significant negative effect on vgetation during RS but it was not predominant in DS and TS. Afforestation showed an extremely significant positive correlated with dryland vegetation across >60 % of China's dryland areas (p < 0.01), but this improvement was found to be limited to regions with the highest afforestation area. Moreover, dryland vegetation dynamics were driven by afforestation in all seasons, with contribution rates of 64.23 %-71.46 %. The effects of SWS and VPD on vegetation driven by precipitation and temperature exceeded the direct effects of precipitation and temperature. Among climatic factors, VPD showed a major regulating effect on dryland vegetation at the top and shallow soil layers in almost all seasons, whereas the relative contribution rate of SWS increased with soil layer. The findings can provide a scientific reference for the sustainable development and protection of drylands under global warming.
Collapse
Affiliation(s)
- Liang He
- Key Laboratory of State Forestry Administration on Soil and Water Conservation, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
| | - Jianbin Guo
- Key Laboratory of State Forestry Administration on Soil and Water Conservation, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China.
| | - Wenbin Yang
- Institute of Desertification Studies, Chinese Academy of Forestry, Beijing 100091, China
| | - Qunou Jiang
- Key Laboratory of State Forestry Administration on Soil and Water Conservation, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
| | - Xuebin Li
- Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwest China, College of Ecology and Environmental Science, Ningxia University, Yinchuan, Ningxia 750021, China
| | - Shenggang Chen
- Key Laboratory of State Forestry Administration on Soil and Water Conservation, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
| | - Mingliang Zhang
- Bureau of Aohan Banner Forestry and Grassland, Aohan 024300, China
| | - Donghui Li
- Xinhui forest farm of Aohan Banner, Aohan 024300, China
| |
Collapse
|
23
|
Chen Z, Wang W, Forzieri G, Cescatti A. Transition from positive to negative indirect CO 2 effects on the vegetation carbon uptake. Nat Commun 2024; 15:1500. [PMID: 38374331 PMCID: PMC10876672 DOI: 10.1038/s41467-024-45957-x] [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: 07/22/2023] [Accepted: 02/08/2024] [Indexed: 02/21/2024] Open
Abstract
Although elevated atmospheric CO2 concentration (eCO2) has substantial indirect effects on vegetation carbon uptake via associated climate change, their dynamics remain unclear. Here we investigate how the impacts of eCO2-driven climate change on growing-season gross primary production have changed globally during 1982-2014, using satellite observations and Earth system models, and evaluate their evolution until the year 2100. We show that the initial positive effect of eCO2-induced climate change on vegetation carbon uptake has declined recently, shifting to negative in the early 21st century. Such emerging pattern appears prominent in high latitudes and occurs in combination with a decrease of direct CO2 physiological effect, ultimately resulting in a sharp reduction of the current growth benefits induced by climate warming and CO2 fertilization. Such weakening of the indirect CO2 effect can be partially attributed to the widespread land drying, and it is expected to be further exacerbated under global warming.
Collapse
Affiliation(s)
- Zefeng Chen
- National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, China
- Yangtze Institute for Conservation and Development, Hohai University, Nanjing, China
- College of Hydrology and Water Resources, Hohai University, Nanjing, China
| | - Weiguang Wang
- National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, China.
- Yangtze Institute for Conservation and Development, Hohai University, Nanjing, China.
- College of Hydrology and Water Resources, Hohai University, Nanjing, China.
| | - Giovanni Forzieri
- Department of Civil and Environmental Engineering, University of Florence, Florence, Italy
| | | |
Collapse
|
24
|
Su J, Fan L, Yuan Z, Wang Z, Wang Z. Quantifying the drought sensitivity of grassland under different climate zones in Northwest China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 910:168688. [PMID: 37992825 DOI: 10.1016/j.scitotenv.2023.168688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 11/14/2023] [Accepted: 11/16/2023] [Indexed: 11/24/2023]
Abstract
Grassland is essential for maintaining the stability and functionality of terrestrial ecosystems. Although previous research has explored how grassland responds to drought, the drought sensitivity of grassland (DSG) across climate zones and aridity gradients remains uncertain. In this study, we conducted a comprehensive investigation spanning 1982 to 2015 in Northwest China. To assess the time-cumulative effect (TCE) and the time-lag effect (TLE) of drought on grassland, we employed Spearman rank correlation analysis, utilizing long-term datasets of the normalized difference vegetation index (NDVI) and the standardized precipitation evapotranspiration index (SPEI). This analysis allowed us to quantify the DSG in the region and further examine its variations across climate zones and aridity gradient. Our results revealed that 81.2 % and 99.7 % of the grassland in Northwest China was influenced by the TCE and TLE of drought, respectively, with 38.2 % and 60.9 % of these effects being statistically significant (p < 0.05). The mean accumulated and lagged timescales of drought on grassland were 7.89 and 9.41 months, respectively. Remarkably, the highest DSG was observed in the semi-arid zone (0.58), followed by the arid (0.54), sub-humid (0.51), and humid (0.44) zones. Furthermore, we identified significant nonlinear variation patterns of DSG along the aridity gradient, characterized by several discernible trend breaks. These findings contribute to our understanding of the impacts of drought on vegetation, particularly in ecologically fragile regions.
Collapse
Affiliation(s)
- Jingxuan Su
- School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, Henan 454003, China
| | - Liangxin Fan
- School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, Henan 454003, China.
| | - Zhanliang Yuan
- School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, Henan 454003, China
| | - Zhen Wang
- School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, Henan 454003, China
| | - Zhijun Wang
- School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, Henan 454003, China
| |
Collapse
|
25
|
Li Z, Bai X, Tan Q, Zhao C, Li Y, Luo G, Chen F, Li C, Ran C, Zhang S, Xiong L, Song F, Du C, Xiao B, Xue Y, Long M. Dryness stress weakens the sustainability of global vegetation cooling. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 909:168474. [PMID: 37951263 DOI: 10.1016/j.scitotenv.2023.168474] [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: 09/05/2023] [Revised: 10/27/2023] [Accepted: 11/08/2023] [Indexed: 11/13/2023]
Abstract
Dryness stress can limit vegetation growth, and the cooling potential of vegetation will also be strongly influenced. However, it is still unclear how dryness stress feedback weakens the sustainability of vegetation-based cooling. Based on the long-time series of multi-source remote sensing product data for the period 2001-2020, the relative contribution rate, and the method of decoupling and boxing, we determined that greening will likely mitigate global warming by 0.065 ± 0.009 °C/a, but nearly 47 % of the area is unsustainable. This phenomenon is strongly related to dryness stress. The restricted area of soil moisture (SM: 68.35 %) to vegetation is larger than that of the atmospheric vapor pressure deficit (VPD: 34.19 %). With the decrease in SM, vegetation will decrease by an average of 14.9 %, and with the increase in VPD, vegetation will decrease by 3.8 %. With the continuous increase in the dryness stress area, the sustainability of the vegetation cooling effect will be threatened in an area of about 21.03 million km2, which is equivalent to the area of North America. Specifically, we found that with the decrease in SM and the increase in VPD, the contribution of vegetation to the cooling effect has been weakened by 10.8 %. This conclusion confirms that dryness stress will threaten the sustainability of vegetation-based climate cooling and provides further insight into the effect of dryness stress on vegetation cooling.
Collapse
Affiliation(s)
- Zilin Li
- School of Geography and Environmental Sciences, Guizhou Normal University, Guiyang 550001, Guizhou Province, China; State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China
| | - Xiaoyong Bai
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an 710061, Shanxi Province, China; College of resources and environmental engineering, Guizhou University, Guiyang 550025, China; College of Environment and Ecology, Chongqing University, Chongqing 404100, China.
| | - Qiu Tan
- School of Geography and Environmental Sciences, Guizhou Normal University, Guiyang 550001, Guizhou Province, China
| | - Cuiwei Zhao
- School of Geography and Environmental Sciences, Guizhou Normal University, Guiyang 550001, Guizhou Province, China
| | - Yangbing Li
- School of Geography and Environmental Sciences, Guizhou Normal University, Guiyang 550001, Guizhou Province, China
| | - Guangjie Luo
- Guizhou Provincial Key Laboratory of Geographic State Monitoring of Watershed, Guizhou Education University, Guiyang 550018, China
| | - Fei Chen
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China; College of resources and environmental engineering, Guizhou University, Guiyang 550025, China
| | - Chaojun Li
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China
| | - Chen Ran
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China
| | - Sirui Zhang
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China
| | - Lian Xiong
- School of Geography and Environmental Sciences, Guizhou Normal University, Guiyang 550001, Guizhou Province, China; State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China
| | - Fengjiao Song
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China
| | - Chaochao Du
- School of Geography and Environmental Sciences, Guizhou Normal University, Guiyang 550001, Guizhou Province, China; State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China
| | - Biqin Xiao
- School of Geography and Environmental Sciences, Guizhou Normal University, Guiyang 550001, Guizhou Province, China; State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China
| | - Yingying Xue
- School of Geography and Environmental Sciences, Guizhou Normal University, Guiyang 550001, Guizhou Province, China; State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China
| | - Minkang Long
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China
| |
Collapse
|
26
|
Shi L, Liu H, Wang L, Peng R, He H, Liang B, Cao J. Transitional responses of tree growth to climate warming at the southernmost margin of high latitudinal permafrost distribution. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 908:168503. [PMID: 37952654 DOI: 10.1016/j.scitotenv.2023.168503] [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: 09/05/2023] [Revised: 11/04/2023] [Accepted: 11/09/2023] [Indexed: 11/14/2023]
Abstract
The marked increase in temperature warming and permafrost degradation has raised apprehensions about the fate of forests of boreal forests in permafrost regions. However, the impact of climate on tree growth is not limited to direct effects but also involves complex interactions with permafrost. The degradation of permafrost poses a threat to forest growth that has received insufficient attention thus far, after analyzing the impact of permafrost degradation and climate on Dahurican larch (Larix gmelinii) growth from six forest sites with two maximum active layer thickness (ALT) classifications (more and less than tree root length) across the southern margin of the permafrost region. We found that accompanying the continued degradation of permafrost, tree growth was inhibited (slope = -0.67, p < 0.05) by the degradation of permafrost and the growth-climate relationship was shifted from positive to negative at maximum ALT less than tree root length sites. However, the growth rate of trees significantly accelerated (slope = 5.46, p < 0.05) at maximum ALT more than tree root length sites. Path analysis indicated that tree growth did not benefit from temperature warming and more stress could be caused by waterlogging due to permafrost degradation at maximum ALT less than tree root length sites, however, enhanced tree growth primarily by reducing the physical spatial constraints and root layer additional water source with permafrost degradation at maximum ALT more than tree root length sites. It also implies that the matchiness between tree root and maximum active layer depth is critical to the effect of permafrost degradation on tree growth. The transitional response to climate warming and the opposite trend of tree growth at two ALT classification sites suggest that future tree growth responds to the different stages of permafrost degradation differently. Our study provides a new insight on permafrost degradation impact on tree growth.
Collapse
Affiliation(s)
- Liang Shi
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; College of Urban and Environmental Sciences, Institute of Carbon Neutrality, Peking University, Beijing, China
| | - Hongyan Liu
- College of Urban and Environmental Sciences, Institute of Carbon Neutrality, Peking University, Beijing, China.
| | - Lu Wang
- Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China
| | - Ruonan Peng
- College of Urban and Environmental Sciences, Institute of Carbon Neutrality, Peking University, Beijing, China
| | - Honglin He
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Boyi Liang
- College of Forestry, Precision Forestry Key Laboratory of Beijing, Beijing Forestry University, Beijing, China
| | - Jing Cao
- State Key Laboratory of Environmental Criteria and Risk Assessment, State Environmental Protection Key Laboratory of Regional Eco-process and Function Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| |
Collapse
|
27
|
Dai T, Dai X, Lu H, He T, Li W, Li C, Huang S, Huang Y, Tong C, Qu G, Shan Y, Liang S, Liu D. The impact of climate change and human activities on the change in the net primary productivity of vegetation-taking Sichuan Province as an example. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:7514-7532. [PMID: 38159188 DOI: 10.1007/s11356-023-31520-6] [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: 08/23/2023] [Accepted: 12/09/2023] [Indexed: 01/03/2024]
Abstract
Vegetation is an essential component of terrestrial ecosystems, influenced by climate change and human activities. Quantifying the relative contributions of climate change and human activities to vegetation dynamics is crucial for addressing global climate change. Sichuan Province is one of the essential ecological functional areas in the upper reaches of the Yangtze River, and its vegetation change is of great significance to the environmental function and ecological security of the Yangtze River Basin and southwest China. In this paper, the modified Carnegie-Ames-Stanford Approach(CASA) model was used to estimate the monthly NPP (Net Primary Productivity) of vegetation in Sichuan Province from 2000 to 2018, and the univariate linear regression analysis was used to analyze the temporal and spatial variation of vegetation NPP in Sichuan Province from 2000 to 2018. In addition, taking vegetation NPP as an index, Pearson correlation analysis, partial correlation analysis, and second-order partial correlation analysis were carried out to quantitatively analyze the contribution of climate change and human activities to vegetation NPP. Finally, the Hurst index and nonparametric Man-Kendall significance test were used to predict the future change trend of vegetation NPP in Sichuan Province. The results show that (1) from 2000 to 2018, the NPP of vegetation in Sichuan Province has a significant increasing trend (Slope = 6.09gC·m-2·a-1), with a multi-year average of 438.72 gC·m-2·a-1, showing a trend of low in the east and high in the middle. The response of vegetation NPP to altitude is different at different elevations; (2) the contribution rates of climate change and human activities to vegetation NPP change are 4.12gC·m-2·a-1 and 1.97gC·m-2·a-1, respectively. In contrast, the impact of human activities on NPP is more significant than climate change. Human activities are the main factors affecting vegetation restoration and degradation in Sichuan Province. However, the positive contribution to NPP change is less than climate change; (3) the future vegetation NPP change trend in Sichuan Province is mainly rising, and the same direction change trend is much larger than the reverse change trend. The areas with an increasing trend in the future account for 89.187% of the total area. This research helps understand the impact of climate change and human activities on vegetation change in Sichuan Province. It offers scientific bases for vegetation restoration and ecosystem management in Sichuan and the surrounding areas.
Collapse
Affiliation(s)
- Tangrui Dai
- College of Earth Sciences, Chengdu University of Technology, Chengdu, 610059, China
| | - Xiaoai Dai
- College of Earth Sciences, Chengdu University of Technology, Chengdu, 610059, China.
| | - Heng Lu
- State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, 610065, China
| | - Tao He
- College of Earth Sciences, Chengdu University of Technology, Chengdu, 610059, China
| | - Weile Li
- State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China
| | - Cheng Li
- College of Earth Sciences, Chengdu University of Technology, Chengdu, 610059, China
| | - Shengqi Huang
- College of Earth Sciences, Chengdu University of Technology, Chengdu, 610059, China
| | - Yiyang Huang
- College of Earth Sciences, Chengdu University of Technology, Chengdu, 610059, China
| | - Chenbo Tong
- College of Earth Sciences, Chengdu University of Technology, Chengdu, 610059, China
| | - Ge Qu
- College of Earth Sciences, Chengdu University of Technology, Chengdu, 610059, China
| | - Yunfeng Shan
- College of Earth Sciences, Chengdu University of Technology, Chengdu, 610059, China
| | - Shuneng Liang
- Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing, 100048, China
| | - Dongsheng Liu
- PIESAT Information Technology Co., Ltd., Beijing, 100195, China
| |
Collapse
|
28
|
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.
Collapse
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
| |
Collapse
|
29
|
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
|
30
|
Zheng C, Wang S, Chen J, Xiang N, Sun L, Chen B, Fu Z, Zhu K, He X. Divergent impacts of VPD and SWC on ecosystem carbon-water coupling under different dryness conditions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 905:167007. [PMID: 37739082 DOI: 10.1016/j.scitotenv.2023.167007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 09/08/2023] [Accepted: 09/09/2023] [Indexed: 09/24/2023]
Abstract
Ecosystem water use efficiency (WUE) is an indicator of carbon-water interactions and is defined as the ratio of gross primary productivity (GPP) to evapotranspiration (ET). However, it is currently unclear how WUE responds to atmospheric and soil drought events in terrestrial ecosystems with different dryness conditions. Additionally, the contributions of GPP and ET to the WUE response remain poorly understood. Based on measurements from 26 flux tower sites distributed worldwide, the binning method and random forest model were employed to separate the sensitivities of daily ecosystem WUE, GPP, and ET to vapor pressure deficit (VPD) and soil water content (SWC) under different dryness conditions (dryness index = potential evapotranspiration/precipitation, DI). Results showed that the sensitivity of WUE to VPD was negative at humid sites (DI < 1), while the sensitivity of WUE to SWC was positive at arid sites (DI > 2). Furthermore, the contribution of GPP to VPD-induced WUE variability was 63 % at humid sites, and the contribution of ET to SWC-induced WUE variability was 68 % when SWC was less than the 60th percentile at arid sites. Consequently, one increasing VPD-induced decrease in GPP was generally linked to a decrease in WUE at humid sites, and one drying soil moisture-caused decrease in ET was linked to a WUE increase under low SWC conditions at arid sites. Finally, VPD had a stronger effect on WUE than SWC when VPD was less than the 90th percentile or SWC was greater than the 50th percentile. Our findings underscore the importance of considering ecosystem dryness when investigating the impacts of VPD and SWC on ecosystem carbon-water coupling.
Collapse
Affiliation(s)
- Chen Zheng
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shaoqiang Wang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Regional Ecological Process and Environment Evolution, School of Geography and Information Engineering, Chinese University of Geosciences, Wuhan 430074, China.
| | - Jinghua Chen
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ning Xiang
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Leigang Sun
- Institute of Geographical Sciences, Hebei Academy of Sciences, Shijiazhuang 050011, China; Hebei Technology Innovation Center for Geographic Information Application, Shijiazhuang 050011, China.
| | - Bin Chen
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zheng Fu
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Kai Zhu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xinlei He
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| |
Collapse
|
31
|
Liu Q, Liang L, Sun T, Wang X, Li C, Yan S. Assessment of the shift in the precipitation-streamflow relationship influenced by multiyear drought, Yellow River basin, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 903:166203. [PMID: 37582440 DOI: 10.1016/j.scitotenv.2023.166203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 08/08/2023] [Accepted: 08/08/2023] [Indexed: 08/17/2023]
Abstract
Climate change intensification (e.g., long-term drought) dramatically triggers catchment property changes, which introduces larger uncertainties for describing catchment hydrological behavior. In this study, hydrological behavior responses to multiyear drought were explored, and then causes were explained. The hydrological response to multiyear drought was explored using a magnitude of shift (M) in describing the relationship between precipitation (P) and streamflow (Q) in different catchment states, and a novel method, the trigonometric function decomposition method within the Budyko framework (the TFD method), was applied to assess the causes of Q changes. Several conclusions can be drawn: (i) multiyear drought mainly caused insignificant and significant upward (p < 0.05) changes in the P-Q relationship among 95.45 % of the studied catchments (p < 0.05); (ii) more server drying, lower leaf area index (LAI) and slope can induce a higher M via multiyear drought. In particular, catchment water storage, indicated by the deep soil layer in the Loess Plateau, can effectively mitigate the Q reduction and resulted in a 77.27 % (17/22) upward shift compared with the expected Q reduction; (iii) an asymmetric effect was caused by a multiyear P deficit, that is, (P-Q)/P increase and catchment property parameter (n) decrease were induced by the increases in ratio between potential evapotranspiration and P (Ep/P), suggesting that the catchment properties can mitigate the Q reduction; and (iv) catchment properties had negative effects on the Q reduction (7.76 mm a-1), and partially offset Q reduction (-21.32 mm a-1) resulted from climate change during the multiyear drought period. All of these results indicated that multiyear drought triggered Q reduction, while catchment behavior in the changeable induction mechanism induced a nonlinear Q response to P reduction, which is important for accurate Q projections and appropriate adaptation strategies for droughts.
Collapse
Affiliation(s)
- Qiang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China.
| | - Liqiao Liang
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Tao Sun
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Xuan Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Chunhui Li
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Sirui Yan
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China
| |
Collapse
|
32
|
Xu B, Li J, Pei X, Yang H. Decoupling the response of vegetation dynamics to asymmetric warming over the Qinghai-Tibet plateau from 2001 to 2020. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 347:119131. [PMID: 37783082 DOI: 10.1016/j.jenvman.2023.119131] [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: 01/31/2023] [Revised: 06/28/2023] [Accepted: 08/30/2023] [Indexed: 10/04/2023]
Abstract
Global land surface air temperature data show that in the past 50 years, the rate of nighttime warming has been much faster than that of daytime, with the minimum daily temperature (Tmin) increasing about 40% faster than the maximum daily temperature (Tmax), resulting in a decreased diurnal temperature difference. The Qinghai-Tibet Plateau (QTP) is known as the "roof of the world", where temperatures have risen twice as fast as the global average warming rate in the last few decades. The factors affecting vegetation growth on the QTP are complex and still not fully understood to some extent. Previous studies paid less attention to the explanations of the complicated interactions and pathways between elements that influence vegetation growth, such as climate (especially asymmetric warming) and topography. In this study, we characterized the spatial and temporal trends of vegetation coverage and investigated the response of vegetation dynamics to asymmetric warming and topography in the QTP during 2001-2020 using trend analysis, partial correlation analysis, and partial least squares structural equation model (PLS-SEM) analysis. We found that from 2001 to 2020, the entire QTP demonstrated a greening trend in the growing season (April to October) at a rate of 0.0006/a (p < 0.05). The spatial distribution pattern of partial correlation between NDVI and Tmax differed from that of NDVI and Tmin. PLS-SEM results indicated that asymmetric warming (both Tmax and Tmin) had a consistent effect on vegetation development by directly promoting greening in the QTP, with NDVI values being more sensitive to Tmin, while topographic factors, especially elevation, mainly played an indirect role in influencing vegetation growth by affecting climate change. This study offers new insights into how vegetation responds to asymmetric warming and references for local ecological preservation.
Collapse
Affiliation(s)
- Binni Xu
- State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China
| | - Jingji Li
- State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China; College of Ecology and Environment, Chengdu University of Technology, Chengdu, 610059, China.
| | - Xiangjun Pei
- State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China; College of Ecology and Environment, Chengdu University of Technology, Chengdu, 610059, China.
| | - Hailong Yang
- State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China
| |
Collapse
|
33
|
Miller DL, Wolf S, Fisher JB, Zaitchik BF, Xiao J, Keenan TF. Increased photosynthesis during spring drought in energy-limited ecosystems. Nat Commun 2023; 14:7828. [PMID: 38030605 PMCID: PMC10687245 DOI: 10.1038/s41467-023-43430-9] [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: 02/10/2023] [Accepted: 11/09/2023] [Indexed: 12/01/2023] Open
Abstract
Drought is often thought to reduce ecosystem photosynthesis. However, theory suggests there is potential for increased photosynthesis during meteorological drought, especially in energy-limited ecosystems. Here, we examine the response of photosynthesis (gross primary productivity, GPP) to meteorological drought across the water-energy limitation spectrum. We find a consistent increase in eddy covariance GPP during spring drought in energy-limited ecosystems (83% of the energy-limited sites). Half of spring GPP sensitivity to precipitation was predicted solely from the wetness index (R2 = 0.47, p < 0.001), with weaker relationships in summer and fall. Our results suggest GPP increases during spring drought for 55% of vegetated Northern Hemisphere lands ( >30° N). We then compare these results to terrestrial biosphere model outputs and remote sensing products. In contrast to trends detected in eddy covariance data, model mean GPP always declined under spring precipitation deficits after controlling for air temperature and light availability. While remote sensing products captured the observed negative spring GPP sensitivity in energy-limited ecosystems, terrestrial biosphere models proved insufficiently sensitive to spring precipitation deficits.
Collapse
Affiliation(s)
- David L Miller
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, 94720, USA.
| | - Sebastian Wolf
- Department of Environmental Systems Science, ETH Zurich, 8092, Zurich, Switzerland.
| | - Joshua B Fisher
- Schmid College of Science and Technology, Chapman University, Orange, CA, 92866, USA
| | - Benjamin F Zaitchik
- Department of Earth and Planetary Sciences, The Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, 03824, USA
| | - Trevor F Keenan
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, 94720, USA.
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
| |
Collapse
|
34
|
Park T, Gumma MK, Wang W, Panjala P, Dubey SK, Nemani RR. Greening of human-dominated ecosystems in India. COMMUNICATIONS EARTH & ENVIRONMENT 2023; 4:419. [PMID: 38665186 PMCID: PMC11041707 DOI: 10.1038/s43247-023-01078-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 10/31/2023] [Indexed: 04/28/2024]
Abstract
Satellite data show the Earth has been greening and identify croplands in India as one of the most prominent greening hotspots. Though India's agriculture has been dependent on irrigation enhancement to reduce crop water stress and increase production, the spatiotemporal dynamics of how irrigation influenced the satellite observed greenness remains unclear. Here, we use satellite-derived leaf area data and survey-based agricultural statistics together with results from state-of-the-art Land Surface Models (LSM) to investigate the role of irrigation in the greening of India's croplands. We find that satellite observations provide multiple lines of evidence showing strong contributions of irrigation to significant greening during dry season and in drier environments. The national statistics support irrigation-driven yield enhancement and increased dry season cropping intensity. These suggest a continuous shift in India's agriculture toward an irrigation-driven dry season cropping system and confirm the importance of land management in the greening phenomenon. However, the LSMs identify CO2 fertilization as a primary driver of greening whereas land use and management have marginal impacts on the simulated leaf area changes. This finding urges a closer collaboration of the modeling, Earth observation, and land system science communities to improve representation of land management in the Earth system modeling.
Collapse
Affiliation(s)
- Taejin Park
- NASA Ames Research Center, Moffett Field, California USA
- Bay Area Environmental Research Institute, Moffett Field, California USA
| | - Murali K. Gumma
- International Crop Research Institute for Semi-Arid Tropics, Patancheru, Telangana India
| | - Weile Wang
- NASA Ames Research Center, Moffett Field, California USA
| | - Pranay Panjala
- International Crop Research Institute for Semi-Arid Tropics, Patancheru, Telangana India
| | | | - Ramakrishna R. Nemani
- NASA Ames Research Center, Moffett Field, California USA
- Bay Area Environmental Research Institute, Moffett Field, California USA
| |
Collapse
|
35
|
Li Q, Tietema A, Reinsch S, Schmidt IK, de Dato G, Guidolotti G, Lellei-Kovács E, Kopittke G, Larsen KS. Higher sensitivity of gross primary productivity than ecosystem respiration to experimental drought and warming across six European shrubland ecosystems. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 900:165627. [PMID: 37495128 DOI: 10.1016/j.scitotenv.2023.165627] [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: 03/24/2023] [Revised: 07/13/2023] [Accepted: 07/16/2023] [Indexed: 07/28/2023]
Abstract
Shrubland ecosystems across Europe face a range of threats including the potential impacts of climate change. Within the INCREASE project, six shrubland ecosystems along a European climatic gradient were exposed to ecosystem-level year-round experimental nighttime warming and long-term, repeated growing season droughts. We quantified the ecosystem level CO2 fluxes, i.e. gross primary productivity (GPP), ecosystem respiration (Reco) and net ecosystem exchange (NEE), in control and treatment plots and compared the treatment effects along the Gaussen aridity index. In general, GPP exhibited higher sensitivity to drought and warming than Reco and was found to be the dominant contributor to changes in overall NEE. Across the climate gradient, northern sites were more likely to have neutral to positive responses of NEE, i.e. increased CO2 uptake, to drought and warming partly due to seasonal rewetting. While an earlier investigation across the same sites showed a good cross-site relationship between soil respiration responses to climate over the Gaussen aridity index, the responses of GPP, Reco and NEE showed a more complex response pattern suggesting that site-specific ecosystem traits, such as different growing season periods and plant species composition, affected the overall response pattern of the ecosystem-level CO2 fluxes. We found that the observed response patterns of GPP and Reco rates at the six sites could be explained well by the hypothesized position of each site on site-specific soil moisture response curves of GPP/Reco fluxes. Such relatively simple, site-specific analyses could help improve our ability to explain observed CO2 flux patterns in larger meta-analyses as well as in larger-scale model upscaling exercises and thereby help improve our ability to project changes in ecosystem CO2 fluxes in response to future climate change.
Collapse
Affiliation(s)
- Qiaoyan Li
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Denmark.
| | - Albert Tietema
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, the Netherlands
| | - Sabine Reinsch
- UK Centre for Ecology & Hydrology, Environment Centre Wales, Bangor, United Kingdom
| | - Inger Kappel Schmidt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Denmark
| | - Giovanbattista de Dato
- CREA Council for Agricultural Research and Economics, Research Centre for Forestry and Wood, Arezzo, Italy
| | - Gabriele Guidolotti
- Research Institute on Terrestrial Ecosystems (IRET), National Research Council (CNR), Porano, TR, Italy
| | | | - Gillian Kopittke
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, the Netherlands
| | - Klaus Steenberg Larsen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Denmark
| |
Collapse
|
36
|
Wen Y, Yang J, Liao W, Xiao J, Yan S. Refined assessment of space-time changes, influencing factors and socio-economic impacts of the terrestrial ecosystem quality: A case study of the GBA. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 345:118869. [PMID: 37690249 DOI: 10.1016/j.jenvman.2023.118869] [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: 05/31/2023] [Revised: 08/09/2023] [Accepted: 08/26/2023] [Indexed: 09/12/2023]
Abstract
The terrestrial ecosystem is the cradle of energy and material basis for human survival and development. However, there are large research deficits in accurately and finely depicting the quality of the terrestrial ecosystem (QTE) and assessing its changing triggers' contribution. Here, we summarized three major principles for selecting image sources in remote sensing data fusion. A continuous 30-m net vegetation productivity (NPP) dataset during 2000-2019 for the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was derived by using the Carnegie-Ames-Stanford approach model and pre-fused normalized difference vegetation index. The factors' contributions to the QTE changes were quantitatively assessed. The role of the QTE in affecting the socio-economic and its behind mechanisms was quantitatively investigated. The results showed that: (1) High-quality images sources are the preference for spatio-temporal fusion of remote sensing data. Images with close month, the same season and year, and sensors should be then selected. Images of different sensors with similar spectral bandwidth, the ones from adjacent years and seasons, can be alternately considered. (2) Fine-resolution NPP has higher accuracy than coarse-resolution NPP and has marked advantages in finely characterizing the QTE. In the past 20 years, the QTE in the GBA has shown a fluctuating increasing trend (0.20 Tg C/yr). (3) Human activities contributed 54.19% of the QTE changes in the GBA, and dominates the QTE changes in the central rapidly urbanizing areas. Residual factors accounted for an overall contribution ratio of 35.71%. Climate change dominants the peripheral forest variations in the GBA. (4) In the GBA, the improvement of QTE has a significant positive socio-economic impact, it contributes to the GDP increment firstly then the GDP aggregate indirectly. Our results highlight that it is of great urgent to estimate long-term continuous NPP with high spatio-temporal resolution globally. Controlling strategies should be implemented to reduce factitious impacts on QTE. High level of ecological and environmental protection promotes the sustainable development.
Collapse
Affiliation(s)
- Youyue Wen
- South China Institute of Environmental Science, Ministry of Ecology and Environment, Guangzhou, 510535, PR China; National Key Laboratory of Urban Ecological Environment Simulation and Protection, Guangzhou, 510535, PR China
| | - Jian Yang
- South China Institute of Environmental Science, Ministry of Ecology and Environment, Guangzhou, 510535, PR China; National Key Laboratory of Urban Ecological Environment Simulation and Protection, Guangzhou, 510535, PR China.
| | - Weilin Liao
- School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, PR China
| | - Jianneng Xiao
- Guangdong Institute of Land Resources Surveying and Mapping, Guangzhou, 510535, PR China
| | - Shouhong Yan
- School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, PR China
| |
Collapse
|
37
|
Mirabel A, Girardin MP, Metsaranta J, Way D, Reich PB. Increasing atmospheric dryness reduces boreal forest tree growth. Nat Commun 2023; 14:6901. [PMID: 37903759 PMCID: PMC10616230 DOI: 10.1038/s41467-023-42466-1] [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: 07/19/2023] [Accepted: 10/11/2023] [Indexed: 11/01/2023] Open
Abstract
Rising atmospheric vapour pressure deficit (VPD) associated with climate change affects boreal forest growth via stomatal closure and soil dryness. However, the relationship between VPD and forest growth depends on the climatic context. Here we assess Canadian boreal forest responses to VPD changes from 1951-2018 using a well-replicated tree-growth increment network with approximately 5,000 species-site combinations. Of the 3,559 successful growth models, we observed a relationship between growth and concurrent summer VPD in one-third of the species-site combinations, and between growth and prior summer VPD in almost half of those combinations. The relationship between previous year VPD and current year growth was almost exclusively negative, while current year VPD also tended to reduce growth. Tree species, age, annual temperature, and soil moisture primarily determined tree VPD responses. Younger trees and species like white spruce and Douglas fir exhibited higher VPD sensitivity, as did areas with high annual temperature and low soil moisture. Since 1951, summer VPD increases in Canada have paralleled tree growth decreases, particularly in spruce species. Accelerating atmospheric dryness in the decades ahead will impair carbon storage and societal-economic services.
Collapse
Affiliation(s)
- Ariane Mirabel
- Department of Biology, University of Western Ontario, London, Ontario, Canada.
- Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec City, QC, Canada.
- UMR DECOD (Ecosystem Dynamics and Sustainability), Institut Agro, IFREMER, INRAE, Rennes, France.
| | - Martin P Girardin
- Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec City, QC, Canada.
| | - Juha Metsaranta
- Natural Resources Canada, Canadian Forest Service, Northern Forestry Centre, Edmonton, AB, Canada
| | - Danielle Way
- Department of Biology, University of Western Ontario, London, Ontario, Canada
- Research School of Biology, The Australian National University, Acton, ACT, 2601, Australia
- Environmental & Climate Sciences Department, Brookhaven National Laboratory, Upton, New York, USA
- Nicholas School of the Environment, Duke University, Durham, NC, USA
| | - Peter B Reich
- Department of Forest Resources, University of Minnesota, St. Paul, MN, 55108, USA
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, 2753, Australia
- Institute for Global Change Biology, and School for the Environment and Sustainability, University of Michigan, Ann Arbor, MI, 48109, USA
| |
Collapse
|
38
|
Araujo HFP, Canassa NF, Machado CCC, Tabarelli M. Human disturbance is the major driver of vegetation changes in the Caatinga dry forest region. Sci Rep 2023; 13:18440. [PMID: 37891196 PMCID: PMC10611708 DOI: 10.1038/s41598-023-45571-9] [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: 01/17/2023] [Accepted: 10/21/2023] [Indexed: 10/29/2023] Open
Abstract
Drastic changes in vegetation structure caused by exceeding ecological thresholds have fueled the interest in tropical forest responses to climate and land-use changes. Here, we examine the potential successional trajectories experienced by the largest dry tropical forest region in South America, driven by climate conditions and human disturbance. We built potential distribution models for vertebrate taxa associated with forest or shrub habitats to estimate natural vegetation cover. Distribution patterns were compared to current vegetation across the entire region to identify distinct forest degradation levels. Our results indicate the region has climatic and soil conditions suitable for more forest cover than is currently found, even in some areas with limited precipitation. However, 11.04% of natural cover persists across such an immense region, with only 4.34% consisting of forest cover. Forest degradation is characterized by the dramatic expansion of shrubland (390%), farming, and non-vegetation cover due to changes in land-use, rather than climatic conditions. Although different climate conditions have been the principal drivers for natural forest distribution in the region, the forest seems unable to resist the consequences of land-use changes, particularly in lower precipitation areas. Therefore, land-use change has exceeded the ecological thresholds for the persistence of forests, while climate change may exacerbate vegetation-type transitions.
Collapse
Affiliation(s)
- Helder F P Araujo
- Department of Biosciences, Federal University of Paraíba, Areia, Paraíba, 58397-000, Brazil.
- Postgraduate Program of Biological Sciences-Zoology, Federal University of Paraíba, João Pessoa, Paraíba, Brazil.
- Department of Biosciences, Federal University of Paraíba, Areia, PB, CEP: 58397-000, Brazil.
| | - Nathália F Canassa
- Department of Biosciences, Federal University of Paraíba, Areia, Paraíba, 58397-000, Brazil
- Postgraduate Program of Biological Sciences-Zoology, Federal University of Paraíba, João Pessoa, Paraíba, Brazil
| | - Célia C C Machado
- Center of Applied Biological and Social Sciences, State University of Paraíba, João Pessoa, Paraíba, Brazil
| | - Marcelo Tabarelli
- Department of Botany, Federal University of Pernambuco, Recife, Pernambuco, Brazil
| |
Collapse
|
39
|
Jackson JA, Bajer A, Behnke-Borowczyk J, Gilbert FS, Grzybek M, Alsarraf M, Behnke JM. Remotely sensed localised primary production anomalies predict the burden and community structure of infection in long-term rodent datasets. GLOBAL CHANGE BIOLOGY 2023; 29:5568-5581. [PMID: 37548403 DOI: 10.1111/gcb.16898] [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: 04/12/2023] [Revised: 06/08/2023] [Accepted: 07/06/2023] [Indexed: 08/08/2023]
Abstract
The increasing frequency and cost of zoonotic disease emergence due to global change have led to calls for the primary surveillance of wildlife. This should be facilitated by the ready availability of remotely sensed environmental data, given the importance of the environment in determining infectious disease dynamics. However, there has been little evaluation of the temporal predictiveness of remotely sensed environmental data for infection reservoirs in vertebrate hosts due to a deficit of corresponding high-quality long-term infection datasets. Here we employ two unique decade-spanning datasets for assemblages of infectious agents, including zoonotic agents, in rodents in stable habitats. Such stable habitats are important, as they provide the baseline sets of pathogens for the interactions within degrading habitats that have been identified as hotspots for zoonotic emergence. We focus on the enhanced vegetation index (EVI), a measure of vegetation greening that equates to primary productivity, reasoning that this would modulate infectious agent populations via trophic cascades determining host population density or immunocompetence. We found that EVI, in analyses with data standardised by site, inversely predicted more than one-third of the variation in an index of infectious agent total abundance. Moreover, in bipartite host occupancy networks, weighted network statistics (connectance and modularity) were linked to total abundance and were also predicted by EVI. Infectious agent abundance and, perhaps, community structure are likely to influence infection risk and, in turn, the probability of transboundary emergence. Thus, the present results, which were consistent in disparate forest and desert systems, provide proof-of-principle that within-site fluctuations in satellite-derived greenness indices can furnish useful forecasting that could focus primary surveillance. In relation to the well-documented global greening trend of recent decades, the present results predict declining infection burden in wild vertebrates in stable habitats; but if greening trends were to be reversed, this might magnify the already upwards trend in zoonotic emergence.
Collapse
Affiliation(s)
- Joseph A Jackson
- School of Science, Engineering and Environment, University of Salford, Manchester, UK
| | - Anna Bajer
- Department of Eco-Epidemiology of Parasitic Diseases, Institute of Developmental Biology and Biomedical Sciences, Faculty of Biology, University of Warsaw, Warsaw, Poland
| | - Jolanta Behnke-Borowczyk
- Department of Forest Pathology, Faculty of Forestry, Poznań University of Life Sciences, Poznań, Poland
| | - Francis S Gilbert
- School of Life Sciences, University of Nottingham, University Park, Nottingham, UK
| | - Maciej Grzybek
- Department of Tropical Parasitology, Institute of Maritime and Tropical Medicine, Medical University of Gdansk, Gdynia, Poland
| | - Mohammed Alsarraf
- Department of Eco-Epidemiology of Parasitic Diseases, Institute of Developmental Biology and Biomedical Sciences, Faculty of Biology, University of Warsaw, Warsaw, Poland
| | - Jerzy M Behnke
- School of Life Sciences, University of Nottingham, University Park, Nottingham, UK
| |
Collapse
|
40
|
Kittipornkul P, Thiravetyan P, Hoshika Y, Sorrentino B, Popa I, Leca S, Sicard P, Paoletti E, De Marco A. Surface ozone risk to human health and vegetation in tropical region: The case of Thailand. ENVIRONMENTAL RESEARCH 2023; 234:116566. [PMID: 37423361 DOI: 10.1016/j.envres.2023.116566] [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: 06/12/2023] [Revised: 07/03/2023] [Accepted: 07/04/2023] [Indexed: 07/11/2023]
Abstract
Tropospheric ozone (O3) is a threat to vegetation and human health over the world, in particular in Asia. Knowledge on O3 impacts on tropical ecosystems is still very limited. An O3 risk assessment to crops, forests, and people from 25 monitoring stations across the tropical and subtropical Thailand during 2005-2018 showed that 44% of sites exceeded the critical levels (CLs) of SOMO35 (i.e., the annual Sum Of daily maximum 8-h Means Over 35 ppb) for human health protection. The concentration-based AOT40 CL (i.e., sum of the hourly exceedances above 40 ppb for daylight hours during the assumed growing season) was exceeded at 52% and 48% of the sites where the main crops rice and maize are present, respectively, and at 88% and 12% of the sites where evergreen or deciduous forests are present, respectively. The flux-based metric PODY (i.e., Phytotoxic Ozone Dose above a threshold Y of uptake) was calculated and was found to exceed the CLs at 1.0%, 1.5%, 20.0%, 1.5%, 0% and 68.0% of the sites where early rice, late rice, early maize, late maize, evergreen forests, and deciduous forests can grow, respectively. Trend analysis indicated that AOT40 increased over the study period (+5.9% year-1), while POD1 decreased (- 5.3% year-1), suggesting that the role of climate change in affecting the environmental factors that control stomatal uptake cannot be neglected. These results contribute novel knowledge on O3 threat to human health, forest productivity, and food security in tropical and subtropical areas.
Collapse
Affiliation(s)
- Piyatida Kittipornkul
- Pilot Plant Development and Training Institute, King Mongkut's University of Technology Thonburi (Bangkuntien), 49 Soi Tientalay 25, Bangkuntien, Bangkok, 10150, Thailand
| | - Paitip Thiravetyan
- School of Bioresources and Technology, King Mongkut's University of Technology Thonburi, Bangkok, 10150, Thailand
| | - Yasutomo Hoshika
- Institute of Research on Terrestrial Ecosystems (IRET), National Research Council (CNR), Via Madonna del Piano 10, Sesto Fiorentino, Florence, Italy
| | | | - Ionel Popa
- INCDS, 128 Eroilor Bvd., Voluntari, 077030, Romania
| | - S Leca
- INCDS, 128 Eroilor Bvd., Voluntari, 077030, Romania
| | - Pierre Sicard
- ARGANS, 260 Route du Pin Montard, 06410, Biot, France
| | - Elena Paoletti
- Institute of Research on Terrestrial Ecosystems (IRET), National Research Council (CNR), Via Madonna del Piano 10, Sesto Fiorentino, Florence, Italy
| | | |
Collapse
|
41
|
Mainali KP, Singh PB, Evans M, Adhikari A, Hu Y, Hu H. A brighter shade of future climate on Himalayan musk deer Moschus leucogaster. Sci Rep 2023; 13:12771. [PMID: 37550330 PMCID: PMC10406878 DOI: 10.1038/s41598-023-39481-z] [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: 01/30/2023] [Accepted: 07/26/2023] [Indexed: 08/09/2023] Open
Abstract
Himalayan musk deer (Moschus leucogaster) is classified as an endangered species by IUCN with a historically misunderstood distribution due to misidentification with other species of musk deer, Moschus spp. Taking advantage of recent genetic analyses confirming the species of various populations in Nepal and China, we produced an accurate estimate of the species' current and future distribution under multiple climate change scenarios. We collected high-quality occurrence data using systematic surveys of various protected areas of Nepal to train species distribution models. The most influential determinants of the distribution of Himalayan musk deer were precipitation of the driest quarter, temperature seasonality, and annual mean temperature. These variables, and precipitation in particular, determine the vegetation type and structure in the Himalaya, which is strongly correlated with the distribution of Himalayan musk deer. We predicted suitable habitats between the Annapurna and Kanchenjunga region of Nepal Himalaya as well as the adjacent Himalaya in China. Under multiple climate change scenarios, the vast majority (85-89%) of current suitable sites are likely to remain suitable and many new areas of suitable habitat may emerge to the west and north of the current species range in Nepal and China. Two-thirds of current and one-third of future suitable habitats are protected by the extensive network of protected areas in Nepal. The projected large gains in suitable sites may lead to population expansion and conservation gains, only when the threat of overexploitation and population decline is under control.
Collapse
Affiliation(s)
- Kumar P Mainali
- National Socio-Environmental Synthesis Center, Annapolis, Maryland, USA
- Conservation Innovation Center, Chesapeake Conservancy, Annapolis, Maryland, USA
| | - Paras Bikram Singh
- Guangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Institute of Zoology, Guangdong Academy of Sciences, Guangzhou, China.
- Biodiversity Conservation Society Nepal, Bagdol, Lalitpur, Nepal.
| | - Michael Evans
- National Socio-Environmental Synthesis Center, Annapolis, Maryland, USA
- Environmental Science and Policy Dept., George Mason University, Fairfax, VA, USA
| | - Arjun Adhikari
- Department of Natural Resource Ecology and Management, Oklahoma State University, Stillwater, OK, USA
| | - Yiming Hu
- Guangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Institute of Zoology, Guangdong Academy of Sciences, Guangzhou, China
| | - Huijian Hu
- Guangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Institute of Zoology, Guangdong Academy of Sciences, Guangzhou, China.
| |
Collapse
|
42
|
Chang X, Yu L, Li G, Li X, Bao L. Wetland vegetation cover changes and its response to climate changes across Heilongjiang-Amur River Basin. FRONTIERS IN PLANT SCIENCE 2023; 14:1169898. [PMID: 37600201 PMCID: PMC10437219 DOI: 10.3389/fpls.2023.1169898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 04/17/2023] [Indexed: 08/22/2023]
Abstract
The Heilongjiang-Amur River Basin is one of the largest and most complex aquatic systems in Asia, comprising diverse wetland resources. The wetland vegetation in mid-high latitude areas has high natural value and is sensitive to climate changes. In this study, we investigated the wetland vegetation cover changes and associated responses to climate change in the Heilongjiang-Amur River Basin from 2000 to 2018 based on the growing season (May to September) climate and LAI data. Our results indicated that the wetland LAI increased at 0.014 m2·m-2/yr across Heilongjiang-Amur River Basin with the regional climate showed wetting and warming trends. On a regional scale, wetland vegetation in China and Russia had positive partial correlation with solar radiation and minimum air temperature, with precipitation showing a slight lag effect. In contrast, wetland vegetation in Mongolia had positive partial correlation with precipitation. These correlations were further investigated at different climate intervals. We found the precipitation is positively correlated with LAI in the warm regions while is negatively correlated with LAI in the wet regions, indicating an increase in precipitation is beneficial for the growth of wetland vegetation in heat sufficient areas, and when precipitation exceeds a certain threshold, it will hinder the growth of wetland vegetation. In the cold regions, we found solar radiation and minimum air temperature are positively correlated with LAI, suggesting SR and minimum air temperature instead of mean air temperature and maximum air temperature play more important roles in affecting the wetland vegetation growth in the heat limited areas. The LAI was found to be negatively correlated with maximum air temperature in the arid areas, indicating excessive temperature would inhibit the wetland vegetation growth when the water is limited. Our investigation can provide a scientific foundation for the trilateral region in wetland ecosystem protection and is beneficial for a more comprehensive understanding of the responses of wetlands in the middle and high latitudes to climate change.
Collapse
Affiliation(s)
- Xinyue Chang
- Remote Sensing and Geographic Information Research Centre, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Lingxue Yu
- Remote Sensing and Geographic Information Research Centre, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
| | - Guangshuai Li
- Remote Sensing and Geographic Information Research Centre, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
- College of Geography Science, Changchun Normal University, Changchun, China
| | - Xuan Li
- Remote Sensing and Geographic Information Research Centre, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
- School of Geomatics and Prospecting Engineering, Jilin Jianzhu University, Changchun, China
| | - Lun Bao
- Remote Sensing and Geographic Information Research Centre, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
| |
Collapse
|
43
|
Das S, Sarkar SK. Spatio-temporal variability of vegetation and its relation to different hydroclimatic factors in Bangladesh. Heliyon 2023; 9:e18412. [PMID: 37533977 PMCID: PMC10391951 DOI: 10.1016/j.heliyon.2023.e18412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 07/16/2023] [Accepted: 07/17/2023] [Indexed: 08/04/2023] Open
Abstract
Bangladesh, known for its remarkable ecological diversity, is faced with the pressing challenges of contemporary climate change. It is crucial to understand how vegetation dynamics respond to different climatic factors. Hence, this study aimed to investigate the spatio-temporal variations of vegetation and their interconnectedness with a range of hydroclimatic factors. The majority of the dataset used in this study relies on MODIS satellite imagery. The Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), precipitation (PPT), evapotranspiration (ET), and land surface temperature (LST) data from the years 2001 to 2020 have been obtained from Google Earth Engine (GEE). In this study, the temporal variations of the NDVI, EVI, PPT, ET, and LST have been investigated. The findings of the Mann-Kendall trend test indicate noticeable trends in both the NDVI and the EVI. Sen's slope value for NDVI and EVI is 0.00424/year and 0.00256/year, respectively. Compared to NDVI, EVI has shown a stronger connection with hydroclimatic factors. In particular, EVI exhibits a better relationship with ET, as indicated by a r2 value of 0.37 and a P-value of 6.81 × 10-26, whereas NDVI exhibits a r2 value of 0.17 and a P-value of 2.96 × 10-11. Furthermore, ET can explain 17% of the fluctuation in NDVI, and no correlation between NDVI and PPT has been found. The results clarify the significant relationship between the EVI and hydroclimatic factors and highlight the efficiency of the EVI for detecting vegetation changes.
Collapse
|
44
|
Cao D, Zhang J, Zhang T, Yao F, Ji R, Zi S, Li H, Cheng Q. Spatiotemporal variations and driving factors of global terrestrial vegetation productivity gap under the changing of climate, CO 2, landcover and N deposition. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 880:162753. [PMID: 37019238 DOI: 10.1016/j.scitotenv.2023.162753] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 02/14/2023] [Accepted: 03/05/2023] [Indexed: 05/27/2023]
Abstract
Understanding the gap between potential productivity and the actual productivity of vegetation (vegetation productivity gap, VPG) is the basis to explore the potential productivity improvement and identify its constraints. In this study, we used the classification and regression tree model to simulate the potential net primary productivity (PNPP) based on the flux-observational maximum net primary productivity (NPP) across different vegetation types, that is, potential productivity. The actual NPP (ANPP) is obtained from the grid NPP averaged over five terrestrial biosphere models, and the VPG is subsequently calculated. On this basis, we used the variance decomposition method to separate the effects of climate change, land-use change, CO2, and nitrogen deposition on the trend and the interannual variability (IAV) of VPG from 1981 to 2010. Meanwhile, the spatiotemporal variation characteristics and influencing factors of VPG under future climate scenarios are analyzed. The results showed an increasing trend in PNPP and ANPP, while there was a decreasing trend of VPG in most parts of the world and this trend is more significant under representative concentration pathways (RCPs). The turning points (TP) of VPG variation are found under RCPs and the reduction trend of VPG before TP is more than that after TP. The VPG reduction in most regions was caused by the combined effects of PNPP and ANPP (41.68 %) from 1981 to 2010. However, the dominant factors of global VPG reduction are changing under RCPs, and the increment of NPP (39.71 % - 49.3 %) has become the dominating factor of VPG variation. CO2 plays a decisive role in the multi-year trend of VPG, while climate change is the main factor determining the IAV of VPG. Under changing climate, temperature and precipitation are negatively correlated with VPG in most parts of the world, and the relationship between radiation and VPG from weak negative to positive correlation.
Collapse
Affiliation(s)
- Dan Cao
- Key Labotatory of UAV Emergency Rescue Technology, China Fire and Rescue Institute, Beijing 102202, China
| | - Jiahua Zhang
- Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen, 518034, China.; Space Information and Big Earth Data Research Center, College of Computer Science and Technology, Qingdao University, Qingdao 266071, China.; The Key Laboratory of Earth Observation of Hainan Province, Hainan Aerospace Information Research Institute, Sanya, 572000, China.; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Tian Zhang
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; Aerospace Hongtu Information Technology Co.,Ltd, Beijing 100089, China..
| | - Fengmei Yao
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Renxin Ji
- Key Labotatory of UAV Emergency Rescue Technology, China Fire and Rescue Institute, Beijing 102202, China
| | - Shuanjin Zi
- Key Labotatory of UAV Emergency Rescue Technology, China Fire and Rescue Institute, Beijing 102202, China
| | - Hong Li
- Key Labotatory of UAV Emergency Rescue Technology, China Fire and Rescue Institute, Beijing 102202, China
| | - QuanYing Cheng
- Key Labotatory of UAV Emergency Rescue Technology, China Fire and Rescue Institute, Beijing 102202, China
| |
Collapse
|
45
|
Zhang J, Fu Z, Nie Y, Lian J, Luo Z, Wang F, Chen H. Microclimate stability on the critical zone of a karst hillslope in southwest China: Insights from continuous temperature observations at the air-soil-epikarst interface. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 336:117656. [PMID: 36898236 DOI: 10.1016/j.jenvman.2023.117656] [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: 12/29/2022] [Revised: 02/20/2023] [Accepted: 03/01/2023] [Indexed: 06/18/2023]
Abstract
Temperature is an important near-surface microclimate parameter that plays a key role in hydrological, ecological, and biogeochemical functions. However, the spatio-temporal distribution of temperature on the invisible and inaccessible soil-weathered bedrock continuum, wherein hydrothermal processes are most active, remains poorly understood. Temperature dynamics were monitored at 5 min intervals in the air-soil-epikarst (∼3 m) system at different topographical positions of the karst peak-cluster depression in southwest China. The weathering intensity was characterized based on the physicochemical properties of samples collected through drilling. No significant difference was observed in air temperature across slope positions, which was related to the limited distance and elevation resulting in roughly consistent energy input. The control effect of air temperature on the soil-epikarst was weakened with the decrease in elevation (±0.36 to ±0.25 °C). It is attributed to the enhanced temperature regulation capacity of vegetation cover from the up slope (shrub dominant) to down slope (tree dominant) in a relatively uniform energy environment. Temperature stability is clearly distinguished in two adjacent hillslopes that were differentiated by weathering intensity. For every 1 °C change in the ambient temperature, the amplitude of soil-epikasrt temperature variation on the strongly and weakly weathered hillslopes were ±0.28 and ± 0.32 °C, respectively. The response of soil-epikarst temperature to ambient temperature was more sensitive in the wet season (±0.40 °C) than in the dry season (±0.20 °C), which was related to the cooling effect caused by abundant rainfall. The cooling effect was particularly prominent in the preferential flow development area composed of pipeline cracks, which appear in the hillslope with relatively weak weathering intensity. These demonstrate that soil-epikarst temperature responds more gently to the variability of rainfall and ambient temperature on a relatively strong weathered hillslope. Accordingly, this study highlights that the sensitivity of soil-epikarst temperature to climate change is regulated by vegetation and weathering intensity on karst hillslopes in southwest China.
Collapse
Affiliation(s)
- Jun Zhang
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, 410125, China; Guangxi Key Laboratory of Karst Ecological Processes and Services, Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Science, Huanjiang, 547100, China; University of Chinese Academy of Science, Beijing, 100049, China
| | - Zhiyong Fu
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, 410125, China; Guangxi Key Laboratory of Karst Ecological Processes and Services, Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Science, Huanjiang, 547100, China.
| | - Yunpeng Nie
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, 410125, China; Guangxi Key Laboratory of Karst Ecological Processes and Services, Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Science, Huanjiang, 547100, China
| | - Jinjiao Lian
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, 410125, China; Guangxi Key Laboratory of Karst Ecological Processes and Services, Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Science, Huanjiang, 547100, China
| | - Zidong Luo
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, 410125, China; Guangxi Key Laboratory of Karst Ecological Processes and Services, Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Science, Huanjiang, 547100, China
| | - Fa Wang
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, 410125, China; Guangxi Key Laboratory of Karst Ecological Processes and Services, Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Science, Huanjiang, 547100, China
| | - Hongsong Chen
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, 410125, China; Guangxi Key Laboratory of Karst Ecological Processes and Services, Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Science, Huanjiang, 547100, China
| |
Collapse
|
46
|
Kashyap R, Kuttippurath J, Kumar P. Browning of vegetation in efficient carbon sink regions of India during the past two decades is driven by climate change and anthropogenic intrusions. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 336:117655. [PMID: 36898237 DOI: 10.1016/j.jenvman.2023.117655] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 02/25/2023] [Accepted: 03/01/2023] [Indexed: 06/18/2023]
Abstract
Accurate estimation of carbon cycle is a challenging task owing to the complexity and heterogeneity of ecosystems. Carbon Use Efficiency (CUE) is a metric to define the ability of vegetation to sequester carbon from the atmosphere. It is key to understand the carbon sink and source pathways of ecosystems. Here, we quantify CUE using remote sensing measurements to examine its variability, drivers and underlying mechanisms in India for the period 2000-2019, by applying the principal component analyses (PCA), multiple linear regression (MLR) and causal discovery. Our analysis shows that the forests in the hilly regions (HR) and northeast (NE), and croplands in the western areas of South India (SI) exhibit high (>0.6) CUE. The northwest (NW), Indo-Gangetic plain (IGP) and some areas in Central India (CI) show low (<0.3) CUE. In general, the water availability as soil moisture (SM) and precipitation (P) promote higher CUE, but higher temperature (T) and air organic carbon content (AOCC) reduce CUE. It is found that SM has the strongest relative influence (33%) on CUE, followed by P. Also, SM has a direct causal link with all drivers and CUE; reiterating its importance in driving vegetation carbon dynamics (VCD) for the cropland dominated India. The long-term analysis reveals that the low CUE regions in NW (moisture induced greening) and IGP (irrigation induced agricultural boom) have an increasing trend in productivity (greening). However, the high CUE regions in NE (deforestation and extreme events) and SI (warming induced moisture stress) exhibit a decreasing trend in productivity (browning), which is a great concern. Our study, therefore, provides new insights on the rate of carbon allocation and the need of proper planning for maintaining balance in the terrestrial carbon cycle. This is particularly important in the context of drafting policy decisions for the mitigation of climate change, food security and sustainability.
Collapse
Affiliation(s)
- Rahul Kashyap
- CORAL, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
| | | | - Pankaj Kumar
- CORAL, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
| |
Collapse
|
47
|
Lee B, Kwon H, Zhao P, Tenhunen J. Improved gross primary production estimation in rice fields through integrated multi-scale methodologies. PLANT-ENVIRONMENT INTERACTIONS (HOBOKEN, N.J.) 2023; 4:163-174. [PMID: 37362422 PMCID: PMC10290427 DOI: 10.1002/pei3.10109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 04/15/2023] [Accepted: 05/01/2023] [Indexed: 06/28/2023]
Abstract
Understanding productivity in agricultural ecosystems is important, as it plays a significant role in modifying regional carbon balances and capturing carbon in the form of agricultural yield. This study in particular combines information from flux determinations using the eddy covariance (EC) methodology, process-based modeling of carbon gain, remotely (satellite) sensed vegetation indices (VIs), and field surveys to assess the gross primary production (GPP) of rice, which is a primary food crop worldwide. This study relates two major variables determining GPP. The first is leaf area index (LAI) and carboxylation capacity of the rice canopy (Vcuptake), and the second being MODIS remotely sensed vegetation indices (VIs). Success in applying such derived relationships has allowed GPP to be remotely determined over the seasonal course of rice development. The relationship to VIs of both LAI and Vcuptake was analyzed first by using the regression approaches commonly applied in remote sensing studies. However, the resultant GPP estimations derived from these generic models were not consistently accurate and led to a large proportion of underestimations. The new, alternative approach developed to estimate LAI and Vcuptake uses consistent development curves for rice (i.e., relies on consistent biological regulations of plant development). The modeled GPP based on this consistent development curve for both LAI and Vcuptake agreed with R 2 from 0.76 to 0.92 (within the 95% confidence interval). The results of this study demonstrate that improved linkages between ground-based survey data, eddy flux measurements, process-based models, and remote sensing data can be constructed to estimate GPP in rice paddies. This study suggests further that the conceptual application of the consistent development curve, such as the combining of different scale measurements, has the potential to predict GPP better than the common practice of utilizing simple linear models, when seeking to estimate the critical parameters that influence carbon gain and agricultural yields.
Collapse
Affiliation(s)
- Bora Lee
- Warm Temperate and Subtropical Forest Research CenterNational Institute of Forest ScienceSeogwipo‐si63582South Korea
| | - Hyojung Kwon
- Forest Ecosystems & SocietyOregon State UniversityCovallisOregonUSA
| | - Peng Zhao
- Department of Health and Environmental Sciences, Plant EcologyJiaotong‐Liverpool UniversityXi'an, SuzhouP.R. China
| | | |
Collapse
|
48
|
Chang X, Xing Y, Gong W, Yang C, Guo Z, Wang D, Wang J, Yang H, Xue G, Yang S. Evaluating gross primary productivity over 9 ChinaFlux sites based on random forest regression models, remote sensing, and eddy covariance data. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 875:162601. [PMID: 36882141 DOI: 10.1016/j.scitotenv.2023.162601] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 02/27/2023] [Accepted: 02/28/2023] [Indexed: 06/18/2023]
Abstract
Accurate modeling of Gross Primary Productivity (GPP) in terrestrial ecosystems is a major challenge in quantifying the carbon cycle. Many light use efficiency (LUE) models have been developed, but the variables and algorithms used for environmental constraints in different models vary importantly. It is still unclear whether the models can be further improved by machine learning methods and the combination of different variables. Here, we have developed a series of RFR-LUE models, which used the random forest regression (RFR) algorithm based on variables of LUE models, to explore the potential of estimating site-level GPP. Based on remote sensing indices, eddy covariance and meteorological data, we applied RFR-LUE models to evaluate the effects of different variables combined on GPP on daily, 8-day, 16-day and monthly scales, respectively. Cross-validation analyses revealed performances of RFR-LUE models varied significantly among sites with R2 of 0.52-0.97. Slopes of the regression relationship between simulated and observed GPP ranged from 0.59 to 0.95. Most models performed better in capturing the temporal changes and magnitude of GPP in mixed forests and evergreen needle-leaf forests than in evergreen broadleaf forests and grasslands. Performances were improved at the longer temporal scale, with the average R2 for four-time resolutions of 0.81, 0.87, 0.88, and 0.90, respectively. Additionally, the importance of the variables showed that temperature and vegetation indices were critical variables for RFR-LUE models, followed by radiation and moisture variables. The importance of moisture variables was higher in non-forests than in forests. A comparison with four GPP products indicated that RFR-LUE model predicted GPP better matcher observed GPP across sites. The study provided an approach to deriving GPP fluxes and evaluating the extent to which variables affect GPP estimation. It may be used for predicting vegetation GPP at the regional scales and for calibration and evaluation of land surface process models.
Collapse
Affiliation(s)
- Xiaoqing Chang
- Centre for Forest Operations and Environment, Northeast Forestry University, Harbin 150040, China
| | - Yanqiu Xing
- Centre for Forest Operations and Environment, Northeast Forestry University, Harbin 150040, China.
| | - Weishu Gong
- Department of Geographical Sciences, University of Maryland, College Park, MD, USA
| | - Cheng Yang
- Centre for Forest Operations and Environment, Northeast Forestry University, Harbin 150040, China
| | - Zhen Guo
- Centre for Forest Operations and Environment, Northeast Forestry University, Harbin 150040, China
| | - Dejun Wang
- Centre for Forest Operations and Environment, Northeast Forestry University, Harbin 150040, China
| | - Jiaqi Wang
- Centre for Forest Operations and Environment, Northeast Forestry University, Harbin 150040, China
| | - Hong Yang
- Centre for Forest Operations and Environment, Northeast Forestry University, Harbin 150040, China
| | - Gang Xue
- Centre for Forest Operations and Environment, Northeast Forestry University, Harbin 150040, China
| | - Shuhang Yang
- Centre for Forest Operations and Environment, Northeast Forestry University, Harbin 150040, China
| |
Collapse
|
49
|
Zhang Z, Cescatti A, Wang YP, Gentine P, Xiao J, Guanter L, Huete AR, Wu J, Chen JM, Ju W, Peñuelas J, Zhang Y. Large diurnal compensatory effects mitigate the response of Amazonian forests to atmospheric warming and drying. SCIENCE ADVANCES 2023; 9:eabq4974. [PMID: 37235657 DOI: 10.1126/sciadv.abq4974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 04/25/2023] [Indexed: 05/28/2023]
Abstract
Photosynthesis and evapotranspiration in Amazonian forests are major contributors to the global carbon and water cycles. However, their diurnal patterns and responses to atmospheric warming and drying at regional scale remain unclear, hindering the understanding of global carbon and water cycles. Here, we used proxies of photosynthesis and evapotranspiration from the International Space Station to reveal a strong depression of dry season afternoon photosynthesis (by 6.7 ± 2.4%) and evapotranspiration (by 6.1 ± 3.1%). Photosynthesis positively responds to vapor pressure deficit (VPD) in the morning, but negatively in the afternoon. Furthermore, we projected that the regionally depressed afternoon photosynthesis will be compensated by their increases in the morning in future dry seasons. These results shed new light on the complex interplay of climate with carbon and water fluxes in Amazonian forests and provide evidence on the emerging environmental constraints of primary productivity that may improve the robustness of future projections.
Collapse
Affiliation(s)
- Zhaoying Zhang
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, International Institute for Earth System Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
- Yuxiu Postdoctoral Institute, Nanjing University, Nanjing, Jiangsu 210023, China
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu 210023, China
| | | | - Ying-Ping Wang
- CSIRO, Oceans and Atmosphere, Private Bag 1, Aspendale, Victoria 3195, Australia
| | - Pierre Gentine
- Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
| | - Luis Guanter
- Research Institute of Water and Environmental Engineering (IIAMA), Department of Applied Physics, Polytechnic University of Valencia, Valencia, Spain
| | - Alfredo R Huete
- School of Life Sciences, University of Technology Sydney, Sydney, New South Wales, Australia
| | - Jin Wu
- School of Biological Sciences, The University of Hong Kong, Pokfulam, Hong Kong
- State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Jing M Chen
- Department of Geography and Planning, University of Toronto, Toronto, Ontario, Canada
| | - Weimin Ju
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, International Institute for Earth System Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Josep Peñuelas
- CSIC, Global ecology Unit CREAF-CSIC-UAB, Bellaterra 08193, Catalonia, Spain
- CREAF, Cerdanyola del Vallès 08193, Catalonia, Spain
| | - Yongguang Zhang
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, International Institute for Earth System Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu 210023, China
- International Joint Carbon Neutrality Laboratory, Nanjing University, Nanjing, Jiangsu 210023 China
| |
Collapse
|
50
|
Zhang J, Zhang Y, Cong N, Tian L, Zhao G, Zheng Z, Gao J, Zhu Y, Zhang Y. Coarse spatial resolution remote sensing data with AVHRR and MODIS miss the greening area compared with the Landsat data in Chinese drylands. FRONTIERS IN PLANT SCIENCE 2023; 14:1129665. [PMID: 37265636 PMCID: PMC10230077 DOI: 10.3389/fpls.2023.1129665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 04/10/2023] [Indexed: 06/03/2023]
Abstract
The warming-wetting climates in Chinese drylands, together with a series of ecological engineering projects, had caused apparent changes to vegetation therein. Regarding the vegetation greening trend, different remote sensing data had yielded distinct findings. It was critical to evaluate vegetation dynamics in Chinese drylands using a series of remote sensing data. By comparing the three most commonly used remote sensing datasets [i.e., MODIS, Advanced Very High Resolution Radiometer (AVHRR), and Landsat], this study comprehensively investigated vegetation dynamics for Chinse drylands. All three remote sensing datasets exhibited evident vegetation greening trends from 2000 to 2020 in Chinese drylands, especially in the Loess Plateau and Northeast China. However, Landsat identified the largest greening areas (89.8%), while AVHRR identified the smallest greening area (58%). The vegetation greening areas identified by Landsat comprise more small patches than those identified by MODIS and AVHRR. The MODIS data exhibited a higher consistency with Landsat than with AVHRR in terms of detecting vegetation greening areas. The three datasets exhibited high consistency in identifying vegetation greening in Northeast China, Loess Plateau, and Xinjiang. The percentage of inconsistent areas among the three datasets was 39.56%. The vegetation greening areas identified by Landsat comprised more small patches. Sensors and the atmospheric effect are the two main reasons responsible for the different outputs from each NDVI product. Ecological engineering projects had a great promotion effect on vegetation greening, which can be detected by the three NDVI datasets in Chinese drylands, thereby combating desertification and reducing dust storms.
Collapse
Affiliation(s)
- Jianshuang Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Yangjian Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
- CAS Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing, China
| | - Nan Cong
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Li Tian
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Guang Zhao
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Zhoutao Zheng
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Jie Gao
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yixuan Zhu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yu Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| |
Collapse
|