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Tang S, Tian D, Wang J, Zhang R, Wang S, Song J, Wan S, Zhang J, Zhang S, Li Z, Niu S. Synergistic effects of multiple global change drivers on terrestrial ecosystem carbon sink. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167554. [PMID: 37820794 DOI: 10.1016/j.scitotenv.2023.167554] [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: 01/04/2023] [Revised: 09/25/2023] [Accepted: 09/30/2023] [Indexed: 10/13/2023]
Abstract
Multiple global change drivers typically co-occur in terrestrial ecosystems, usually with complex interactions on ecosystem carbon fluxes. However, how they interactively impact terrestrial carbon sinks remains unknown. Here, we synthesized 82 field experiments that studied the individual and pairwise effects among nitrogen addition (N), increased precipitation (IP), elevated CO2 (eCO2) and warming, with direct measurements of net ecosystem productivity (NEP), gross ecosystem productivity (GEP) and ecosystem respiration (ER). We found that synergistic interactions mostly occurred between pairs of global change drivers on carbon fluxes. Moreover, these interactions varied with treatment magnitude, experimental duration and background precipitation. Specifically, the synergistic effect of N × IP became stronger with experimental precipitation magnitude and background rainfall. With an increasing N addition rate, N and eCO2 had weaker interactive effects on NEP. Warming and IP were more synergic to enhance NEP with higher levels of warming magnitude. However, the interactive effects of N × eCO2 on ER decreased over the experimental duration. Overall, this study provides new insights into the context-dependent occurrence of interactions among multiple global change drivers on ecosystem carbon sinks. These new findings are valuable to validate land C-cycle models with complex global change interactions and advance the next generations of future experimental design.
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Affiliation(s)
- Shiming Tang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Key Laboratory for Model Innovation in Forage Production Efficiency, Ministry of Agriculture and Rural Affuirs, Institute of Grassland Research, Chinese Academy of Agricultural Sciences, Hohhot 010010, China
| | - Dashuan Tian
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Yuquanlu, Beijing 100049, China.
| | - Jinsong Wang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Yuquanlu, Beijing 100049, China
| | - Ruiyang Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Song Wang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Jian Song
- College of Life Sciences, Hebei University, Baoding, Hebei 071002, China
| | - Shiqiang Wan
- College of Life Sciences, Hebei University, Baoding, Hebei 071002, China
| | - Jinxin Zhang
- Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry/Grassland Research Center, National Forestry and Grassland Administration, Beijing 100091, China
| | - Shuang Zhang
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
| | - Zhaolei Li
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Shuli Niu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Yuquanlu, Beijing 100049, China
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Montagnani L, Badraghi A, Speak AF, Wellstein C, Borruso L, Zerbe S, Zanotelli D. Evidence for a non-linear carbon accumulation pattern along an Alpine glacier retreat chronosequence in Northern Italy. PeerJ 2019; 7:e7703. [PMID: 31616581 PMCID: PMC6790226 DOI: 10.7717/peerj.7703] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Accepted: 08/19/2019] [Indexed: 11/20/2022] Open
Abstract
Background The glaciers in the Alps, as in other high mountain ranges and boreal zones, are generally retreating and leaving a wide surface of bare ground free from ice cover. This early stage soil is then colonized by microbes and vegetation in a process of primary succession. It is rarely experimentally examined whether this colonization process is linear or not at the ecosystem scale. Thus, to improve our understanding of the variables involved in the carbon accumulation in the different stages of primary succession, we conducted this research in three transects on the Matsch glacier forefield (Alps, N Italy) at an altitude between 2,350 and 2,800 m a.s.l. Methods In three field campaigns (July, August and September 2014) a closed transparent chamber was used to quantify the net ecosystem exchange (NEE) between the natural vegetation and the atmosphere. On the five plots established in each of the three transects, shading nets were used to determine ecosystem response function to variable light conditions. Ecosystem respiration (Reco) and gross ecosystem exchange (GEE) was partitioned from NEE. Following the final flux measurements, biometric sampling was conducted to establish soil carbon (C) and nitrogen (N) content and the biomass components for each transect. Results A clear difference was found between the earlier and the later successional stage. The older successional stages in the lower altitudes acted as a stronger C sink, where NEE, GEE and Reco were significantly higher than in the earlier successional stage. Of the two lower transects, the sink capacity of intermediate-succession plots exceeded that of the plots of older formation, in spite of the more developed soil. Total biomass (above- and belowground) approached its maximum value in the intermediate ecosystem, whilst the later stage of succession predominated in the corresponding belowground organic mass (biomass, N and C). Outlook We found that the process of carbon accumulation along a glacier retreat chronosequence is not linear, and after a quite rapid increase in carbon accumulation capacity in the first 150 years, in average 9 g C m−2 year−1, it slows down, taking place mainly in the belowground biomass components. Concurrently, the photosynthetic capacity peaks in the intermediate stage of ecosystem development. If confirmed by further studies on a larger scale, this study would provide evidence for a predominant effect of plant physiology over soil physical characteristics in the green-up phase after glacier retreat, which has to be taken into account in the creation of scenarios related to climate change and future land use.
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Affiliation(s)
- Leonardo Montagnani
- Faculty of Science and Technology, Free University of Bozen-Bolzano, Bolzano, Italy.,Forest Services, Autonomous Province of Bolzano, Bolzano, Italy
| | - Aysan Badraghi
- Faculty of Science and Technology, Free University of Bozen-Bolzano, Bolzano, Italy
| | - Andrew Francis Speak
- Faculty of Science and Technology, Free University of Bozen-Bolzano, Bolzano, Italy
| | - Camilla Wellstein
- Faculty of Science and Technology, Free University of Bozen-Bolzano, Bolzano, Italy
| | - Luigimaria Borruso
- Faculty of Science and Technology, Free University of Bozen-Bolzano, Bolzano, Italy
| | - Stefan Zerbe
- Faculty of Science and Technology, Free University of Bozen-Bolzano, Bolzano, Italy
| | - Damiano Zanotelli
- Faculty of Science and Technology, Free University of Bozen-Bolzano, Bolzano, Italy
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