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  • Energy Research

  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: orcid Zhen Yu;
    Zhen Yu
    ORCID
    Harvested from ORCID Public Data File

    Zhen Yu in OpenAIRE
    orcid bw Shirong Liu;
    Shirong Liu
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Shirong Liu in OpenAIRE
    Haikui Li; orcid Jingjing Liang;
    Jingjing Liang
    ORCID
    Harvested from ORCID Public Data File

    Jingjing Liang in OpenAIRE
    +10 Authors

    AbstractForest carbon sequestration capacity in China remains uncertain due to underrepresented tree demographic dynamics and overlooked of harvest impacts. In this study, we employ a process-based biogeochemical model to make projections by using national forest inventories, covering approximately 415,000 permanent plots, revealing an expansion in biomass carbon stock by 13.6 ± 1.5 Pg C from 2020 to 2100, with additional sink through augmentation of wood product pool (0.6-2.0 Pg C) and spatiotemporal optimization of forest management (2.3 ± 0.03 Pg C). We find that statistical model might cause large bias in long-term projection due to underrepresentation or neglect of wood harvest and forest demographic changes. Remarkably, disregarding the repercussions of harvesting on forest age can result in a premature shift in the timing of the carbon sink peak by 1–3 decades. Our findings emphasize the pressing necessity for the swift implementation of optimal forest management strategies for carbon sequestration enhancement.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Nature Communication...arrow_drop_down
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    Nature Communications
    Article . 2024 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    https://dx.doi.org/10.60692/61...
    Other literature type . 2024
    Data sources: Datacite
    https://dx.doi.org/10.60692/db...
    Other literature type . 2024
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Nature Communication...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Nature Communications
      Article . 2024 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      https://dx.doi.org/10.60692/61...
      Other literature type . 2024
      Data sources: Datacite
      https://dx.doi.org/10.60692/db...
      Other literature type . 2024
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: orcid bw Dominic Fawcett;
    Dominic Fawcett
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Dominic Fawcett in OpenAIRE
    orcid bw Stephen Sitch;
    Stephen Sitch
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Stephen Sitch in OpenAIRE
    orcid bw Philippe Ciais;
    Philippe Ciais
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Philippe Ciais in OpenAIRE
    orcid Jean Pierre Wigneron;
    Jean Pierre Wigneron
    ORCID
    Harvested from ORCID Public Data File

    Jean Pierre Wigneron in OpenAIRE
    +10 Authors

    AbstractIn the Amazon, deforestation and climate change lead to increased vulnerability to forest degradation, threatening its existing carbon stocks and its capacity as a carbon sink. We use satellite L‐Band Vegetation Optical Depth (L‐VOD) data that provide an integrated (top‐down) estimate of biomass carbon to track changes over 2011–2019. Because the spatial resolution of L‐VOD is coarse (0.25°), it allows limited attribution of the observed changes. We therefore combined high‐resolution annual maps of forest cover and disturbances with biomass maps to model carbon losses (bottom‐up) from deforestation and degradation, and gains from regrowing secondary forests. We show an increase of deforestation and associated degradation losses since 2012 which greatly outweigh secondary forest gains. Degradation accounted for 40% of gross losses. After an increase in 2011, old‐growth forests show a net loss of above‐ground carbon between 2012 and 2019. The sum of component carbon fluxes in our model is consistent with the total biomass change from L‐VOD of 1.3 Pg C over 2012‐2019. Across nine Amazon countries, we found that while Brazil contains the majority of biomass stocks (64%), its losses from disturbances were disproportionately high (79% of gross losses). Our multi‐source analysis provides a pessimistic assessment of the Amazon carbon balance and highlights the urgent need to stop the recent rise of deforestation and degradation, particularly in the Brazilian Amazon.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CGIAR CGSpace (Consu...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Global Change Biology
    Article . 2022 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CGIAR CGSpace (Consu...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Global Change Biology
      Article . 2022 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: orcid Stephen Sitch;
    Stephen Sitch
    ORCID
    Harvested from ORCID Public Data File

    Stephen Sitch in OpenAIRE
    Andrew D. B. Leakey; Jens Kattge; Alistair Rogers; +13 Authors

    SummaryAccurate representation of photosynthesis in terrestrial biosphere models (TBMs) is essential for robust projections of global change. However, current representations vary markedly between TBMs, contributing uncertainty to projections of global carbon fluxes. Here we compared the representation of photosynthesis in seven TBMs by examining leaf and canopy level responses of photosynthetic CO2 assimilation (A) to key environmental variables: light, temperature, CO2 concentration, vapor pressure deficit and soil water content. We identified research areas where limited process knowledge prevents inclusion of physiological phenomena in current TBMs and research areas where data are urgently needed for model parameterization or evaluation. We provide a roadmap for new science needed to improve the representation of photosynthesis in the next generation of terrestrial biosphere and Earth system models.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Australian National ...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    New Phytologist
    Article
    Data sources: UnpayWall
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    MPG.PuRe
    Article . 2017
    Data sources: MPG.PuRe
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    New Phytologist
    Article . 2016 . Peer-reviewed
    License: Wiley Online Library User Agreement
    Data sources: Crossref
    New Phytologist
    Article . 2018
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    392
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    downloaddownloads95
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Australian National ...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      New Phytologist
      Article
      Data sources: UnpayWall
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      MPG.PuRe
      Article . 2017
      Data sources: MPG.PuRe
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      New Phytologist
      Article . 2016 . Peer-reviewed
      License: Wiley Online Library User Agreement
      Data sources: Crossref
      New Phytologist
      Article . 2018
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: orcid Anna B. Harper;
    Anna B. Harper
    ORCID
    Harvested from ORCID Public Data File

    Anna B. Harper in OpenAIRE
    orcid Peter M. Cox;
    Peter M. Cox
    ORCID
    Harvested from ORCID Public Data File

    Peter M. Cox in OpenAIRE
    orcid Pierre Friedlingstein;
    Pierre Friedlingstein
    ORCID
    Harvested from ORCID Public Data File

    Pierre Friedlingstein in OpenAIRE
    Andy J. Wiltshire; +17 Authors

    Abstract. Dynamic global vegetation models are used to predict the response of vegetation to climate change. They are essential for planning ecosystem management, understanding carbon cycle–climate feedbacks, and evaluating the potential impacts of climate change on global ecosystems. JULES (the Joint UK Land Environment Simulator) represents terrestrial processes in the UK Hadley Centre family of models and in the first generation UK Earth System Model. Previously, JULES represented five plant functional types (PFTs): broadleaf trees, needle-leaf trees, C3 and C4 grasses, and shrubs. This study addresses three developments in JULES. First, trees and shrubs were split into deciduous and evergreen PFTs to better represent the range of leaf life spans and metabolic capacities that exists in nature. Second, we distinguished between temperate and tropical broadleaf evergreen trees. These first two changes result in a new set of nine PFTs: tropical and temperate broadleaf evergreen trees, broadleaf deciduous trees, needle-leaf evergreen and deciduous trees, C3 and C4 grasses, and evergreen and deciduous shrubs. Third, using data from the TRY database, we updated the relationship between leaf nitrogen and the maximum rate of carboxylation of Rubisco (Vcmax), and updated the leaf turnover and growth rates to include a trade-off between leaf life span and leaf mass per unit area.Overall, the simulation of gross and net primary productivity (GPP and NPP, respectively) is improved with the nine PFTs when compared to FLUXNET sites, a global GPP data set based on FLUXNET, and MODIS NPP. Compared to the standard five PFTs, the new nine PFTs simulate a higher GPP and NPP, with the exception of C3 grasses in cold environments and C4 grasses that were previously over-productive. On a biome scale, GPP is improved for all eight biomes evaluated and NPP is improved for most biomes – the exceptions being the tropical forests, savannahs, and extratropical mixed forests where simulated NPP is too high. With the new PFTs, the global present-day GPP and NPP are 128 and 62 Pg C year−1, respectively. We conclude that the inclusion of trait-based data and the evergreen/deciduous distinction has substantially improved productivity fluxes in JULES, in particular the representation of GPP. These developments increase the realism of JULES, enabling higher confidence in simulations of vegetation dynamics and carbon storage.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ University of Wester...arrow_drop_down
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    Geoscientific Model Development (GMD)
    Article . 2016 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    Geoscientific Model Development (GMD)
    Article
    License: CC BY
    Data sources: UnpayWall
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    Geoscientific Model Development
    Other literature type . 2018
    Data sources: Copernicus
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Geoscientific Model Development
    Article . 2016
    Data sources: DOAJ
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    MPG.PuRe
    Article . 2016
    Data sources: MPG.PuRe
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Wageningen Staff Publications
    Article . 2016
    License: CC BY
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  • Authors: Lisa Emberson; orcid Stephen Sitch;
    Stephen Sitch
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    Stephen Sitch in OpenAIRE
    Elizabeth A. Ainsworth; orcid Craig R. Yendrek;
    Craig R. Yendrek
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    Craig R. Yendrek in OpenAIRE
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    Tropospheric ozone (O3) is a global air pollutant that causes billions of dollars in lost plant productivity annually. It is an important anthropogenic greenhouse gas, and as a secondary air pollutant, it is present at high concentrations in rural areas far from industrial sources. It also reduces plant productivity by entering leaves through the stomata, generating other reactive oxygen species and causing oxidative stress, which in turn decreases photosynthesis, plant growth, and biomass accumulation. The deposition of O3 into vegetation through stomata is an important sink for tropospheric O3, but this sink is modified by other aspects of environmental change, including rising atmospheric carbon dioxide concentrations, rising temperature, altered precipitation, and nitrogen availability. We review the atmospheric chemistry governing tropospheric O3 mass balance, the effects of O3 on stomatal conductance and net primary productivity, and implications for agriculture, carbon sequestration, and climate change.

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    Authors: Clare Enright; orcid Chris Huntingford;
    Chris Huntingford
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    Chris Huntingford in OpenAIRE
    orcid Peter Levy;
    Peter Levy
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    Peter Levy in OpenAIRE
    orcid Atul K. Jain;
    Atul K. Jain
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    Atul K. Jain in OpenAIRE
    +33 Authors

    Abstract. Accurate assessments of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the climate policy process, and project future climate change. Present-day analysis requires the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. Here we describe datasets and a methodology developed by the global carbon cycle science community to quantify all major components of the global carbon budget, including their uncertainties. We discuss changes compared to previous estimates, consistency within and among components, and methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (EFF) are based on energy statistics, while emissions from Land-Use Change (ELUC), including deforestation, are based on combined evidence from land cover change data, fire activity in regions undergoing deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. Finally, the global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms. For the last decade available (2002–2011), EFF was 8.3 ± 0.4 PgC yr−1, ELUC 1.0 ± 0.5 PgC yr−1, GATM 4.3 ± 0.1 PgC yr−1, SOCEAN 2.5 ± 0.5 PgC yr−1, and SLAND 2.6 ± 0.8 PgC yr−1. For year 2011 alone, EFF was 9.5 ± 0.5 PgC yr−1, 3.0 percent above 2010, reflecting a continued trend in these emissions; ELUC was 0.9 ± 0.5 PgC yr−1, approximately constant throughout the decade; GATM was 3.6 ± 0.2 PgC yr−1, SOCEAN was 2.7 ± 0.5 PgC yr−1, and SLAND was 4.1 ± 0.9 PgC yr−1. GATM was low in 2011 compared to the 2002–2011 average because of a high uptake by the land probably in response to natural climate variability associated to La Niña conditions in the Pacific Ocean. The global atmospheric CO2 concentration reached 391.31 ± 0.13 ppm at the end of year 2011. We estimate that EFF will have increased by 2.6% (1.9–3.5%) in 2012 based on projections of gross world product and recent changes in the carbon intensity of the economy. All uncertainties are reported as ±1 sigma (68% confidence assuming Gaussian error distributions that the real value lies within the given interval), reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. This paper is intended to provide a baseline to keep track of annual carbon budgets in the future. All data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_V2013). Global carbon budget 2013

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    Earth System Science Data (ESSD)
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    Earth System Science Data Discussions
    Article . 2012 . Peer-reviewed
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    Article . 2013
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    MPG.PuRe
    Article . 2013
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    Bergen Open Research Archive - UiB
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    http://dx.doi.org/10.5194/essd...
    Article . 2012 . Peer-reviewed
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      Article . 2013
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      MPG.PuRe
      Article . 2013
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      Bergen Open Research Archive - UiB
      Article . 2013 . Peer-reviewed
      License: CC BY
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      http://dx.doi.org/10.5194/essd...
      Article . 2012 . Peer-reviewed
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    Authors: Piao, Shilong; Fang, Jingyun; Ciais, Philippe; orcid Peylin, Philippe;
    Peylin, Philippe
    ORCID
    Harvested from ORCID Public Data File

    Peylin, Philippe in OpenAIRE
    +3 Authors

    Global terrestrial ecosystems absorbed carbon at a rate of 1-4 Pg yr(-1) during the 1980s and 1990s, offsetting 10-60 per cent of the fossil-fuel emissions. The regional patterns and causes of terrestrial carbon sources and sinks, however, remain uncertain. With increasing scientific and political interest in regional aspects of the global carbon cycle, there is a strong impetus to better understand the carbon balance of China. This is not only because China is the world's most populous country and the largest emitter of fossil-fuel CO(2) into the atmosphere, but also because it has experienced regionally distinct land-use histories and climate trends, which together control the carbon budget of its ecosystems. Here we analyse the current terrestrial carbon balance of China and its driving mechanisms during the 1980s and 1990s using three different methods: biomass and soil carbon inventories extrapolated by satellite greenness measurements, ecosystem models and atmospheric inversions. The three methods produce similar estimates of a net carbon sink in the range of 0.19-0.26 Pg carbon (PgC) per year, which is smaller than that in the conterminous United States but comparable to that in geographic Europe. We find that northeast China is a net source of CO(2) to the atmosphere owing to overharvesting and degradation of forests. By contrast, southern China accounts for more than 65 per cent of the carbon sink, which can be attributed to regional climate change, large-scale plantation programmes active since the 1980s and shrub recovery. Shrub recovery is identified as the most uncertain factor contributing to the carbon sink. Our data and model results together indicate that China's terrestrial ecosystems absorbed 28-37 per cent of its cumulated fossil carbon emissions during the 1980s and 1990s.

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    Nature
    Article . 2009 . Peer-reviewed
    License: Springer TDM
    Data sources: Crossref
    Nature
    Article . 2009
    Nature
    Article . 2008
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      Nature
      Article . 2009 . Peer-reviewed
      License: Springer TDM
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      Nature
      Article . 2009
      Nature
      Article . 2008
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    Authors: orcid bw Hui Yang;
    Hui Yang
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Hui Yang in OpenAIRE
    orcid Chris Huntingford;
    Chris Huntingford
    ORCID
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    Chris Huntingford in OpenAIRE
    orcid bw Andy Wiltshire;
    Andy Wiltshire
    ORCID
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    Andy Wiltshire in OpenAIRE
    orcid bw Stephen Sitch;
    Stephen Sitch
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Stephen Sitch in OpenAIRE
    +1 Authors

    Abstract River runoff is a key attribute of the land surface, that additionally has a strong influence on society by the provision of freshwater. Yet various environmental factors modify runoff levels, and some trends could be detrimental to humanity. Drivers include elevated CO2 concentration, climate change, aerosols and altered land-use. Additionally, nitrogen deposition and tropospheric ozone changes influence plant functioning, and thus runoff, yet their importance is less understood. All these effects are now included in the JULES-CN model. We first evaluate runoff estimates from this model against 42 large basin scales, and then conduct factorial simulations to investigate these mechanisms individually. We determine how different drivers govern the trends of runoff over three decades for which data is available. Numerical results suggest rising atmospheric CO2 concentration is the most important contributor to the global mean runoff trend, having a significant mean increase of +0.18 ± 0.006 mm yr−2 and due to the overwhelming importance of physiological effects. However, at the local scale, the dominant influence on historical runoff trends is climate in 82% of the global land area. This difference is because climate change impacts, mainly due to precipitation changes, can be positive (38% of global land area) or negative (44% of area), depending on location. For other drivers, land use change leads to increased runoff trends in wet tropical regions and decreased runoff in Southeast China, Central Asia and the eastern USA. Modelling the terrestrial nitrogen cycle in general suppresses runoff decreases induced by the CO2 fertilization effect, highlighting the importance of carbon–nitrogen interactions on ecosystem hydrology. Nitrogen effects do, though, induce decreasing trend components for much of arid Australia and the boreal regions. Ozone influence was mainly smaller than other drivers.

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    Environmental Research Letters
    Article . 2019 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    Environmental Research Letters
    Article
    License: CC BY
    Data sources: UnpayWall
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    Environmental Research Letters
    Article . 2019
    Data sources: DOAJ
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    https://dx.doi.org/10.60692/ds...
    Other literature type . 2019
    Data sources: Datacite
    https://dx.doi.org/10.60692/jt...
    Other literature type . 2019
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      Environmental Research Letters
      Article . 2019 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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      Environmental Research Letters
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      Environmental Research Letters
      Article . 2019
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      https://dx.doi.org/10.60692/ds...
      Other literature type . 2019
      Data sources: Datacite
      https://dx.doi.org/10.60692/jt...
      Other literature type . 2019
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    Authors: orcid Ronny Lauerwald;
    Ronny Lauerwald
    ORCID
    Harvested from ORCID Public Data File

    Ronny Lauerwald in OpenAIRE
    orcid Ana Bastos;
    Ana Bastos
    ORCID
    Harvested from ORCID Public Data File

    Ana Bastos in OpenAIRE
    orcid Matthew J. McGrath;
    Matthew J. McGrath
    ORCID
    Harvested from ORCID Public Data File

    Matthew J. McGrath in OpenAIRE
    orcid Ana Maria Roxana Petrescu;
    Ana Maria Roxana Petrescu
    ORCID
    Harvested from ORCID Public Data File

    Ana Maria Roxana Petrescu in OpenAIRE
    +40 Authors

    AbstractIn the framework of the RECCAP2 initiative, we present the greenhouse gas (GHG) and carbon (C) budget of Europe. For the decade of the 2010s, we present a bottom‐up (BU) estimate of GHG net‐emissions of 3.9 Pg CO2‐eq. yr−1 (using a global warming potential on a 100 years horizon), which are largely dominated by fossil fuel emissions. In this decade, terrestrial ecosystems acted as a net GHG sink of 0.9 Pg CO2‐eq. yr−1, dominated by a CO2 sink that was partially counterbalanced by net emissions of CH4 and N2O. For CH4 and N2O, we find good agreement between BU and top‐down (TD) estimates from atmospheric inversions. However, our BU land CO2 sink is significantly higher than the TD estimates. We further show that decadal averages of GHG net‐emissions have declined by 1.2 Pg CO2‐eq. yr−1 since the 1990s, mainly due to a reduction in fossil fuel emissions. In addition, based on both data driven BU and TD estimates, we also find that the land CO2 sink has weakened over the past two decades. A large part of the European CO2 and C sinks is located in Northern Europe. At the same time, we find a decreasing trend in sink strength in Scandinavia, which can be attributed to an increase in forest management intensity. These are partly offset by increasing CO2 sinks in parts of Eastern Europe and Northern Spain, attributed in part to land use change. Extensive regions of high CH4 and N2O emissions are mainly attributed to agricultural activities and are found in Belgium, the Netherlands and the southern UK. We further analyzed interannual variability in the GHG budgets. The drought year of 2003 shows the highest net‐emissions of CO2 and of all GHGs combined.

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    Global Biogeochemical Cycles
    Article . 2024 . Peer-reviewed
    License: CC BY
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    https://dx.doi.org/10.5445/ir/...
    Article . 2024
    License: CC BY
    Data sources: Datacite
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    Wageningen Staff Publications
    Article . 2024
    License: CC BY
    https://doi.org/10.22541/essoa...
    Article . 2024 . Peer-reviewed
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      Global Biogeochemical Cycles
      Article . 2024 . Peer-reviewed
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      https://dx.doi.org/10.5445/ir/...
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      Wageningen Staff Publications
      Article . 2024
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      https://doi.org/10.22541/essoa...
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    Authors: orcid bw László Nagy;
    László Nagy
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    László Nagy in OpenAIRE
    orcid bw Cleiton B. Eller;
    Cleiton B. Eller
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Cleiton B. Eller in OpenAIRE
    orcid Lina M. Mercado;
    Lina M. Mercado
    ORCID
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    Lina M. Mercado in OpenAIRE
    orcid Francisco Cuesta;
    Francisco Cuesta
    ORCID
    Harvested from ORCID Public Data File

    Francisco Cuesta in OpenAIRE
    +16 Authors

    Contexte : La surveillance basée sur des placettes a fourni de nombreuses informations sur la diversité taxonomique et le stockage du carbone (C) dans les forêts tropicales de plaine du bassin amazonien. Cela a permis de mieux comprendre la relation entre la dynamique de la biomasse forestière des plaines et les facteurs du changement mondial, tels que le changement climatique et la concentration atmosphérique de CO 2. Beaucoup moins d'attention a été accordée aux écosystèmes montagneux d'Amérique du Sud qui comprennent les forêts montagnardes et la végétation alpine (páramo, puna, prairies des hautes Andes, zones humides et bruyère alpine).Ce complexe de végétation fournit une variété de services écosystémiques et forme un laboratoire naturel le long de divers gradients d'histoire/biogéographie physiographique, géologique et évolutive, et d'histoire de l'utilisation des terres.Images : Ici, nous passons en revue la compréhension empirique existante et les approches basées sur des modèles pour quantifier la contribution des écosystèmes de montagne à la fourniture de services écosystémiques dans le contexte socio-écologique en évolution rapide des montagnes sud-américaines.L' objectif de cet article est de définir une feuille de route générale pour la mise en œuvre de la végétation de montagne dans des modèles dynamiques de végétation mondiale (DGVM) à utiliser dans les modèles du système terrestre (ESM), sur la base de notre compréhension actuelle de leur structure et de leur fonction et de leur réactivité aux facteurs du changement global.Nous identifions également les processus de la limite des arbres, critiques dans les écosystèmes de montagne, comme des éléments manquants clés dans les DGVM/mes, et explorons ainsi en outre un modèle de limite des arbres.Méthodes : Un bilan de la disponibilité des données empiriques a été entrepris à partir de huit sites de recherche le long des Andes et dans le sud-est du Brésil.Parmi huit sites, deux (un au Venezuela et un au Brésil) avaient potentiellement des données climatiques, écologiques et écophysiologiques convenant au paramétrage d'une DGVM.Les données sur la biomasse des arbres étaient disponibles pour six sites.Une évaluation préliminaire de la DGVM du Joint UK Land Environment Simulator (JULES) a été réalisée pour identifier les lacunes dans les données disponibles et leurs impacts sur le paramétrage et l'étalonnage du modèle.En outre, l'élévation potentielle de la limite des arbres déterminée par le climat a été modélisée pour vérifier la DGVM quant à sa capacité à identifier la transition entre la forêt montagnarde et la végétation alpine.Résultats : Les résultats de l'évaluation du modèle de surface terrestre JULES ont identifié les processus clés suivants dans les forêts montagnardes : diminution liée à la température de la production primaire nette, respiration et allocation à la biomasse aérienne et augmentation des stocks de C dans le sol avec l'altitude.Il y avait un accord variable entre la biomasse simulée et celles dérivées des mesures sur le terrain via des équations allométriques.Conclusions : Nous avons identifié des écarts majeurs entre la disponibilité des données et les besoins de modélisation basée sur les processus de la végétation de montagne sud-américaine et de sa dynamique dans les DGVM.Pour combler cet écart, nous proposons un réseau transdisciplinaire, composé de membres des communautés théoriques/de modélisation et scientifiques empiriques, pour étudier la dynamique naturelle des écosystèmes de montagne et leurs réponses aux facteurs de changement mondiaux au niveau local, régional et continental, dans un cadre de système socio-écologique.Les travaux présentés ici constituent la base de la conception de la collecte de données à partir des mesures sur le terrain et des stations de surveillance instrumentales pour paramétrer et vérifier les DGVM.Le réseau est conçu pour collaborer et compléter les recherches à long terme existantes Antecedentes: El monitoreo basado en parcelas ha arrojado mucha información sobre la diversidad taxonómica y el almacenamiento de carbono (C) en los bosques tropicales de tierras bajas de la cuenca amazónica. Esto ha resultado en una mejor comprensión de la relación entre la dinámica de la biomasa forestal de las tierras bajas y los impulsores del cambio global, como el cambio climático y la concentración atmosférica de CO 2. Se ha prestado mucha menos atención a los ecosistemas de montaña de América del Sur que comprenden bosques montanos y vegetación alpina (páramo, puna, pastizales altoandinos, humedales y brezales alpinos).Este complejo de vegetación proporciona una variedad de servicios ecosistémicos y forma un laboratorio natural a lo largo de varios gradientes fisiográficos, geológicos y evolutivos de historia/biogeografía e historia del uso de la tierra. Objetivos: Aquí, revisamos la comprensión empírica existente y los enfoques basados en modelos para cuantificar la contribución de los ecosistemas de montaña a la prestación de servicios ecosistémicos en el entorno socioecológico rápidamente cambiante de las montañas sudamericanas. El objetivo de este documento es esbozar una amplia hoja de ruta para la implementación de la vegetación de montaña en modelos dinámicos de vegetación global (DGVM) para su uso en Modelos del Sistema Terrestre (ESM), basados en nuestra comprensión actual de su estructura y función y de su capacidad de respuesta a los impulsores del cambio global. También identificamos los procesos arbóreos, críticos en los ecosistemas de montaña, como elementos clave que faltan en las DGVM/ESM, y por lo tanto exploramos además un modelo arbóreo. Métodos: Se realizó un inventario de la disponibilidad de datos empíricos de ocho sitios de investigación a lo largo de los Andes y en el sureste de Brasil. De los ocho sitios, dos (uno en Venezuela y otro en Brasil) tenían algunos datos climáticos, ecológicos y ecofisiológicos potencialmente adecuado para parametrizar una DGVM. Se disponía de datos de biomasa de árboles para seis sitios. Se realizó una evaluación preliminar de la DGVM del Simulador Conjunto de Medio Ambiente Terrestre del Reino Unido (JULES) para identificar lagunas en los datos disponibles y sus impactos en la parametrización y calibración del modelo. Además, se modeló la posible elevación determinada por el clima de la línea de árboles para verificar la DGVM en cuanto a su capacidad para identificar la transición entre el bosque montano y la vegetación alpina. Resultados: Los resultados de la evaluación del modelo de superficie terrestre de JULES identificaron los siguientes procesos clave en los bosques montanos: disminución relacionada con la temperatura en la producción primaria neta, la respiración y la asignación a la biomasa sobre el suelo y aumento de las poblaciones de suelo C con elevación. Hubo un acuerdo variable entre la biomasa simulada y las derivadas de las mediciones de campo a través de ecuaciones alométricas. Conclusiones: Identificamos grandes brechas entre la disponibilidad de datos y las necesidades de modelado basado en procesos de la vegetación de montaña sudamericana y su dinámica en las DGVM. Para cerrar esta brecha, proponemos una red transdisciplinaria, compuesta por miembros de las comunidades científicas teóricas/de modelado y empíricas, para estudiar la dinámica natural de los ecosistemas de montaña y sus respuestas a los impulsores del cambio global a nivel local, regional y continental, dentro de un marco de sistema socioecológico. El trabajo presentado aquí forma la base para el diseño de la recopilación de datos a partir de mediciones de campo y estaciones de monitoreo instrumental para parametrizar y verificar las DGVM. La red está diseñada para colaborar y complementar la investigación existente a largo plazo. Background: Plot-based monitoring has yielded much information on the taxonomic diversity and carbon (C) storage in tropical lowland forests of the Amazon basin.This has resulted in an improved understanding of the relationship between lowland forest biomass dynamics and global change drivers, such as climate change and atmospheric CO 2 concentration.Much less attention has been paid to the mountain ecosystems of South America that comprise montane forests and alpine vegetation (páramo, puna, high Andean grasslands, wetlands, and alpine heath).This vegetation complex provides a variety of ecosystem services and forms a natural laboratory along various physiographic, geological and evolutionary history/biogeography, and land use history gradients.Aims: Here, we review existing empirical understanding and model-based approaches to quantify the contribution of mountain ecosystems to ecosystem service provision in the rapidly changing socioecological setting of the South American mountains.The objective of this paper is to outline a broad road map for the implementation of mountain vegetation into dynamic global vegetation models (DGVM) for use in Earth System Models (ESM), based on our current understanding of their structure and function and of their responsiveness to global change drivers.We also identify treeline processes, critical in mountain ecosystems, as key missing elements in DGVMs/ESMs, and thus explore in addition a treeline model.Methods: Stocktaking of the availability of empirical data was undertaken from eight research sites along the Andes and in south-eastern Brazil.Out of eight sites, two (one each in Venezuela and Brazil) had some climate, ecological and ecophysiological data potentially suitable to parametrise a DGVM.Tree biomass data were available for six sites.A preliminary assessment of the Joint UK Land Environment Simulator (JULES) DGVM was made to identify gaps in available data and their impacts on model parametrisation and calibration.Additionally, the potential climate-determined elevation of the treeline was modelled to check the DGVM for its ability to identify the transition between the montane forest and alpine vegetation.Results: Outcomes of the evaluation of the JULES land surface model identified the following key processes in montane forests: temperature-related decrease in net primary production, respiration, and allocation to above-ground biomass and increase in soil C stocks with elevation.There was a variable agreement between simulated biomass and those derived from field measurements via allometric equations.Conclusions: We identified major gaps between data availability and the needs for process-based modelling of South American mountain vegetation and its dynamics in DGVMs.To bridge this gap, we propose a transdisciplinary network, composed of members of the theoretical/modelling and empirical scientific communities, to study the natural dynamics of mountain ecosystems and their responses to global change drivers locally, regionally and at the continental scale, within a social-ecological system framework.The work presented here forms the basis for the design of data collection from field measurements and instrumental monitoring stations to parametrise and verify DGVMs.The network is designed to collaborate with and complement existing long-term research معلومات أساسية: أسفر الرصد القائم على قطعة الأرض عن الكثير من المعلومات حول التنوع التصنيفي وتخزين الكربون (C) في غابات الأراضي المنخفضة الاستوائية في حوض الأمازون. وقد أدى ذلك إلى فهم أفضل للعلاقة بين ديناميات الكتلة الحيوية للغابات المنخفضة ومحركات التغير العالمي، مثل تغير المناخ وتركيز ثاني أكسيد الكربون في الغلاف الجوي. وقد تم إيلاء اهتمام أقل بكثير للنظم الإيكولوجية الجبلية في أمريكا الجنوبية التي تشمل الغابات الجبلية والغطاء النباتي في جبال الألب (بارامو، بونا، الأراضي العشبية في أعالي الأنديز، الأراضي الرطبة، وصحة جبال الألب). يوفر مجمع الغطاء النباتي هذا مجموعة متنوعة من خدمات النظام الإيكولوجي ويشكل مختبرًا طبيعيًا على طول مختلف التاريخ الفيزيائي والجيولوجي والتطوري/الجغرافيا الحيوية، وتدرجات تاريخ استخدام الأراضي. الأهداف: نستعرض هنا الفهم التجريبي الحالي والنهج القائمة على النماذج لقياس مساهمة النظم الإيكولوجية الجبلية في توفير خدمات النظام الإيكولوجي في البيئة الاجتماعية والبيئية المتغيرة بسرعة لجبال أمريكا الجنوبية. الهدف من هذه الورقة هو تحديد خريطة طريق واسعة لتنفيذ الغطاء النباتي الجبلي في نماذج نباتية عالمية ديناميكية (DGVM) لاستخدامها في نماذج نظام الأرض (ESM)، بناءً على فهمنا الحالي من هيكلها ووظيفتها واستجابتها لمحركات التغير العالمي. كما نحدد عمليات خطوط الأشجار، الحرجة في النظم الإيكولوجية الجبلية، كعناصر رئيسية مفقودة في DGVMs/ESMs، وبالتالي نستكشف بالإضافة إلى ذلك نموذج خط الأشجار. الأساليب: تم إجراء جرد لتوافر البيانات التجريبية من ثمانية مواقع بحثية على طول جبال الأنديز وفي جنوب شرق البرازيل. من بين ثمانية مواقع، كان لدى موقعين (واحد في كل من فنزويلا والبرازيل) بعض البيانات المناخية والبيئية والفسيولوجية البيئية المحتملة مناسبة لتحديد معالم DGVM. كانت بيانات الكتلة الحيوية الثلاثية متاحة لستة مواقع. تم إجراء تقييم أولي لمحاكي بيئة الأراضي المشترك في المملكة المتحدة (JULES) DGVM لتحديد الثغرات في البيانات المتاحة وتأثيراتها على تحديد معالم النموذج ومعايرته. بالإضافة إلى ذلك، تم نمذجة الارتفاع المحتمل المحدد بالمناخ لخط الأشجار للتحقق من DGVM لقدرته على تحديد الانتقال بين الغابة الجبلية والغطاء النباتي في جبال الألب. النتائج: حددت نتائج تقييم نموذج سطح الأرض JULES العمليات الرئيسية التالية في الغابات الجبلية: الانخفاض المرتبط بدرجة الحرارة في صافي الإنتاج الأولي، والتنفس، والتخصيص للكتلة الحيوية فوق الأرض و زيادة مخزونات التربة C مع الارتفاع. كان هناك اتفاق متغير بين الكتلة الحيوية المحاكية وتلك المستمدة من القياسات الميدانية عبر المعادلات المتجانسة. الاستنتاجات: حددنا الفجوات الرئيسية بين توافر البيانات والاحتياجات إلى النمذجة القائمة على العمليات للغطاء النباتي الجبلي في أمريكا الجنوبية وديناميكياته في DGVM. لسد هذه الفجوة، نقترح شبكة متعددة التخصصات، تتألف من أعضاء المجتمعات العلمية النظرية/النمذجة والتجريبية، لدراسة الديناميكيات الطبيعية للنظم الإيكولوجية الجبلية واستجاباتها لمحركات التغيير العالمي محليًا وإقليميًا وعلى المستوى القاري، ضمن إطار النظام الاجتماعي الإيكولوجي. يشكل العمل المقدم هنا الأساس لتصميم جمع البيانات من القياسات الميدانية ومحطات المراقبة الآلية إلى بارامتير والتحقق من DGVM. تم تصميم الشبكة للتعاون مع البحوث القائمة طويلة الأجل واستكمالها

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    Plant Ecology & Diversity
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      Plant Ecology & Diversity
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