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  • Authors: Jeffrey R. Smith; Evelyn M. Beaury; Susan C. Cook-Patton; Jonathan M. Levine;

    Pathways to achieving net zero carbon emissions commonly involve deploying reforestation, afforestation, and bioenergy crops across millions of hectares of land. It is often assumed that by helping to mitigate climate change, these strategies indirectly benefit biodiversity. Here, we modeled the climate and habitat requirements of 14,234 vertebrate species and show that the impact of these strategies on species’ habitat area tends not to arise through climate mitigation, but rather through habitat conversion. Across locations, reforestation tends to provide species more habitat through both land-cover change and climate mitigation, whereas habitat loss from afforestation and bioenergy cropping typically outweighs the climate mitigation benefits. This work shows how and where land-based mitigation strategies can be deployed without inadvertently reducing the area of habitat for global biodiversity.

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    Science
    Article . 2025 . Peer-reviewed
    Data sources: Crossref
    Science
    Article . 2025
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      Science
      Article . 2025 . Peer-reviewed
      Data sources: Crossref
      Science
      Article . 2025
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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: Kristina J. Anderson‐Teixeira; Valentine Herrmann; Madison Williams; Teagan Tinuviel; +3 Authors

    Societal Impact StatementHuman interactions with forests have shaped Earth's climate for millennia and will continue to do so as we target net‐zero emission goals. Accurately characterizing these climate impacts requires making reliable forest carbon data available for forest monitoring and planning. Here, we develop a semi‐automated process for submitting forest carbon measurements from the largest relevant scientific database to the International Panel on Climate Change's Emission Factor Database, which currently has sparse forest carbon data. Building this bridge from scientific research to international policy is an important step towards managing forests in a net‐zero motivated future.Abstract Humans have been influencing Earth's climate via transformative impacts on forests for millennia, and forests are now recognized as critical to climate change mitigation under the Paris Agreement. The efficacy of climate change mitigation planning and reporting depends on quality data on forest carbon (C) stocks and changes. The Emission Factor Database (EFDB) of the International Panel on Climate Change (IPCC) is intended to be a definitive source for such data, but needs comprehensive and well‐documented data to be so. To facilitate submission of forest C estimates from scientific studies to EFDB, we develop and document a process for semi‐automated data submission from the Global Forest C database (ForC v4.0), which is the largest compilation of ground‐based forest C estimates. We then assess the data currently available through ForC and provide recommendations for improving forest data collection, analysis, and reporting. As of September 2024, ForC contained ~19,286 records potentially relevant to EFDB, 1068 of which had been submitted and posted to EFDB. These represented 19% of the total EFDB records for forest land. Records were unevenly distributed across variables and geographic regions. ForC records (37%) reviewed could not be submitted because the original publication lacked required information. In the future, ground‐based forest C estimates should target gaps in the record, and studies should ensure that they report all information necessary for inclusion in EFDB. Given that climate change is rapidly impacting the world's forests, timely reporting of recent estimates will be critical to accurate forest C inventories.

    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/ Plants, People, Plan...arrow_drop_down
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    Plants, People, Planet
    Article . 2024 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    Plants, People, Planet
    Article . 2025
    Data sources: DOAJ
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      Plants, People, Planet
      Article . 2024 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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      Plants, People, Planet
      Article . 2025
      Data sources: DOAJ
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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: Jacob J. Bukoski; Susan C. Cook-Patton; Cyril Melikov; Hongyi Ban; +4 Authors

    AbstractRestoring forest cover is a key action for mitigating climate change. Although monoculture plantations dominate existing commitments to restore forest cover, we lack a synthetic view of how carbon accumulates in these systems. Here, we assemble a global database of 4756 field-plot measurements from monoculture plantations across all forested continents. With these data, we model carbon accumulation in aboveground live tree biomass and examine the biological, environmental, and human drivers that influence this growth. Our results identify four-fold variation in carbon accumulation rates across tree genera, plant functional types, and biomes, as well as the key mediators (e.g., genus of tree, endemism of species, prior land use) of variation in these rates. Our nonlinear growth models advance our understanding of carbon accumulation in forests relative to mean annual rates, particularly during the next few decades that are critical for mitigating climate change.

    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 Califo...arrow_drop_down
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    Nature Communications
    Article . 2022 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    Nature Communications
    Article . 2022
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    Authors: Danaë M. A. Rozendaal; Daniela Requena Suárez; Véronique De Sy; Valerio Avitabile; +53 Authors

    Abstract For monitoring and reporting forest carbon stocks and fluxes, many countries in the tropics and subtropics rely on default values of forest aboveground biomass (AGB) from the Intergovernmental Panel on Climate Change (IPCC) guidelines for National Greenhouse Gas (GHG) Inventories. Default IPCC forest AGB values originated from 2006, and are relatively crude estimates of average values per continent and ecological zone. The 2006 default values were based on limited plot data available at the time, methods for their derivation were not fully clear, and no distinction between successional stages was made. As part of the 2019 Refinement to the 2006 IPCC Guidelines for GHG Inventories, we updated the default AGB values for tropical and subtropical forests based on AGB data from >25 000 plots in natural forests and a global AGB map where no plot data were available. We calculated refined AGB default values per continent, ecological zone, and successional stage, and provided a measure of uncertainty. AGB in tropical and subtropical forests varies by an order of magnitude across continents, ecological zones, and successional stage. Our refined default values generally reflect the climatic gradients in the tropics, with more AGB in wetter areas. AGB is generally higher in old-growth than in secondary forests, and higher in older secondary (regrowth >20 years old and degraded/logged forests) than in young secondary forests (⩽20 years old). While refined default values for tropical old-growth forest are largely similar to the previous 2006 default values, the new default values are 4.0–7.7-fold lower for young secondary forests. Thus, the refined values will strongly alter estimated carbon stocks and fluxes, and emphasize the critical importance of old-growth forest conservation. We provide a reproducible approach to facilitate future refinements and encourage targeted efforts to establish permanent plots in areas with data gaps.

    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/ COREarrow_drop_down
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    Environmental Research Letters
    Article . 2022 . Peer-reviewed
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    Environmental Research Letters
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    Environmental Research Letters
    Article . 2022
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    Agritrop
    Article . 2022
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    Research@WUR
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    Article . 2022
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    Wageningen Staff Publications
    Article . 2022
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    St Andrews Research Repository
    Article . 2022 . Peer-reviewed
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    Environmental Research Letters
    Article . 2022 . Peer-reviewed
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      Environmental Research Letters
      Article . 2022 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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      Environmental Research Letters
      Article
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      Data sources: UnpayWall
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      Environmental Research Letters
      Article . 2022
      Data sources: DOAJ
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      Agritrop
      Article . 2022
      License: CC BY
      Data sources: Agritrop
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      Research@WUR
      Article . 2022
      License: CC BY
      Data sources: Research@WUR
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      Research@WUR
      Other literature type . 2022
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      Data sources: Research@WUR
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      UCL Discovery
      Article . 2022
      Data sources: UCL Discovery
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      Wageningen Staff Publications
      Article . 2022
      License: CC BY
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      St Andrews Research Repository
      Article . 2022 . Peer-reviewed
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      Environmental Research Letters
      Article . 2022 . Peer-reviewed
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      Environmental Research Letters
      Article
      License: CC BY
      Data sources: Sygma
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      https://dx.doi.org/10.60692/gw...
      Other literature type . 2022
      Data sources: Datacite
      https://dx.doi.org/10.60692/5e...
      Other literature type . 2022
      Data sources: Datacite
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    Authors: Bukoski, Jacob; Cook-Patton, Susan C.; Melikov, Cyril; Ban, Hongyi; +4 Authors

    This project systematically reviewed the literature for measurements of aboveground carbon stocks in monoculture plantation forests. The data compiled here are for monoculture (single-species) plantation forests, which are a subset of a broader review to identify empirical measurements of carbon stocks across all forest types. The database is structured similarly to that of the ForC (https://forc-db.github.io/) and GROA databases (https://github.com/forc-db/GROA). When using these data, please cite: Bukoski, J.J., Cook-Patton, S.C., Melikov, C., Ban, H., Liu, J.C., Harris, N., Goldman, E., and Potts, M.D. 2022. Rates and drivers of aboveground carbon accumulation in global monoculture plantation forests. Nature Communications 13(4206). doi: 10.1038/s41467-022-31380-7 The code for all analyses in Bukoski et al., 2022 (paper associated with this dataset) is available at https://github.com/jbukoski/GPFC (doi: 10.5281/zenodo.6588710).

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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5 Research products
  • Authors: Jeffrey R. Smith; Evelyn M. Beaury; Susan C. Cook-Patton; Jonathan M. Levine;

    Pathways to achieving net zero carbon emissions commonly involve deploying reforestation, afforestation, and bioenergy crops across millions of hectares of land. It is often assumed that by helping to mitigate climate change, these strategies indirectly benefit biodiversity. Here, we modeled the climate and habitat requirements of 14,234 vertebrate species and show that the impact of these strategies on species’ habitat area tends not to arise through climate mitigation, but rather through habitat conversion. Across locations, reforestation tends to provide species more habitat through both land-cover change and climate mitigation, whereas habitat loss from afforestation and bioenergy cropping typically outweighs the climate mitigation benefits. This work shows how and where land-based mitigation strategies can be deployed without inadvertently reducing the area of habitat for global biodiversity.

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    Science
    Article . 2025 . Peer-reviewed
    Data sources: Crossref
    Science
    Article . 2025
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      Science
      Article . 2025 . Peer-reviewed
      Data sources: Crossref
      Science
      Article . 2025
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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: Kristina J. Anderson‐Teixeira; Valentine Herrmann; Madison Williams; Teagan Tinuviel; +3 Authors

    Societal Impact StatementHuman interactions with forests have shaped Earth's climate for millennia and will continue to do so as we target net‐zero emission goals. Accurately characterizing these climate impacts requires making reliable forest carbon data available for forest monitoring and planning. Here, we develop a semi‐automated process for submitting forest carbon measurements from the largest relevant scientific database to the International Panel on Climate Change's Emission Factor Database, which currently has sparse forest carbon data. Building this bridge from scientific research to international policy is an important step towards managing forests in a net‐zero motivated future.Abstract Humans have been influencing Earth's climate via transformative impacts on forests for millennia, and forests are now recognized as critical to climate change mitigation under the Paris Agreement. The efficacy of climate change mitigation planning and reporting depends on quality data on forest carbon (C) stocks and changes. The Emission Factor Database (EFDB) of the International Panel on Climate Change (IPCC) is intended to be a definitive source for such data, but needs comprehensive and well‐documented data to be so. To facilitate submission of forest C estimates from scientific studies to EFDB, we develop and document a process for semi‐automated data submission from the Global Forest C database (ForC v4.0), which is the largest compilation of ground‐based forest C estimates. We then assess the data currently available through ForC and provide recommendations for improving forest data collection, analysis, and reporting. As of September 2024, ForC contained ~19,286 records potentially relevant to EFDB, 1068 of which had been submitted and posted to EFDB. These represented 19% of the total EFDB records for forest land. Records were unevenly distributed across variables and geographic regions. ForC records (37%) reviewed could not be submitted because the original publication lacked required information. In the future, ground‐based forest C estimates should target gaps in the record, and studies should ensure that they report all information necessary for inclusion in EFDB. Given that climate change is rapidly impacting the world's forests, timely reporting of recent estimates will be critical to accurate forest C inventories.

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    Plants, People, Planet
    Article . 2024 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    Plants, People, Planet
    Article . 2025
    Data sources: DOAJ
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      Plants, People, Planet
      Article . 2024 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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      Plants, People, Planet
      Article . 2025
      Data sources: DOAJ
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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: Jacob J. Bukoski; Susan C. Cook-Patton; Cyril Melikov; Hongyi Ban; +4 Authors

    AbstractRestoring forest cover is a key action for mitigating climate change. Although monoculture plantations dominate existing commitments to restore forest cover, we lack a synthetic view of how carbon accumulates in these systems. Here, we assemble a global database of 4756 field-plot measurements from monoculture plantations across all forested continents. With these data, we model carbon accumulation in aboveground live tree biomass and examine the biological, environmental, and human drivers that influence this growth. Our results identify four-fold variation in carbon accumulation rates across tree genera, plant functional types, and biomes, as well as the key mediators (e.g., genus of tree, endemism of species, prior land use) of variation in these rates. Our nonlinear growth models advance our understanding of carbon accumulation in forests relative to mean annual rates, particularly during the next few decades that are critical for mitigating climate change.

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    Nature Communications
    Article . 2022 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    Nature Communications
    Article . 2022
    Data sources: DOAJ
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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: Danaë M. A. Rozendaal; Daniela Requena Suárez; Véronique De Sy; Valerio Avitabile; +53 Authors

    Abstract For monitoring and reporting forest carbon stocks and fluxes, many countries in the tropics and subtropics rely on default values of forest aboveground biomass (AGB) from the Intergovernmental Panel on Climate Change (IPCC) guidelines for National Greenhouse Gas (GHG) Inventories. Default IPCC forest AGB values originated from 2006, and are relatively crude estimates of average values per continent and ecological zone. The 2006 default values were based on limited plot data available at the time, methods for their derivation were not fully clear, and no distinction between successional stages was made. As part of the 2019 Refinement to the 2006 IPCC Guidelines for GHG Inventories, we updated the default AGB values for tropical and subtropical forests based on AGB data from >25 000 plots in natural forests and a global AGB map where no plot data were available. We calculated refined AGB default values per continent, ecological zone, and successional stage, and provided a measure of uncertainty. AGB in tropical and subtropical forests varies by an order of magnitude across continents, ecological zones, and successional stage. Our refined default values generally reflect the climatic gradients in the tropics, with more AGB in wetter areas. AGB is generally higher in old-growth than in secondary forests, and higher in older secondary (regrowth >20 years old and degraded/logged forests) than in young secondary forests (⩽20 years old). While refined default values for tropical old-growth forest are largely similar to the previous 2006 default values, the new default values are 4.0–7.7-fold lower for young secondary forests. Thus, the refined values will strongly alter estimated carbon stocks and fluxes, and emphasize the critical importance of old-growth forest conservation. We provide a reproducible approach to facilitate future refinements and encourage targeted efforts to establish permanent plots in areas with data gaps.

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    Environmental Research Letters
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    UCL Discovery
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    Wageningen Staff Publications
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    St Andrews Research Repository
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    Environmental Research Letters
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    Environmental Research Letters
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    https://dx.doi.org/10.60692/gw...
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      Environmental Research Letters
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      Environmental Research Letters
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      Environmental Research Letters
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      Agritrop
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      UCL Discovery
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      Environmental Research Letters
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      Environmental Research Letters
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      https://dx.doi.org/10.60692/gw...
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      https://dx.doi.org/10.60692/5e...
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    Authors: Bukoski, Jacob; Cook-Patton, Susan C.; Melikov, Cyril; Ban, Hongyi; +4 Authors

    This project systematically reviewed the literature for measurements of aboveground carbon stocks in monoculture plantation forests. The data compiled here are for monoculture (single-species) plantation forests, which are a subset of a broader review to identify empirical measurements of carbon stocks across all forest types. The database is structured similarly to that of the ForC (https://forc-db.github.io/) and GROA databases (https://github.com/forc-db/GROA). When using these data, please cite: Bukoski, J.J., Cook-Patton, S.C., Melikov, C., Ban, H., Liu, J.C., Harris, N., Goldman, E., and Potts, M.D. 2022. Rates and drivers of aboveground carbon accumulation in global monoculture plantation forests. Nature Communications 13(4206). doi: 10.1038/s41467-022-31380-7 The code for all analyses in Bukoski et al., 2022 (paper associated with this dataset) is available at https://github.com/jbukoski/GPFC (doi: 10.5281/zenodo.6588710).

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2022
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    Data sources: Datacite
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    ZENODO
    Dataset . 2022
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    Data sources: Datacite
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      ZENODO
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      ZENODO
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