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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: Alexandra Tyukavina; Nancy L. Harris; Alessandro Baccini; Sassan Saatchi; +14 Authors

    Managing forests for climate change mitigation requires action by diverse stakeholders undertaking different activities with overlapping objectives and spatial impacts. To date, several forest carbon monitoring systems have been developed for different regions using various data, methods and assumptions, making it difficult to evaluate mitigation performance consistently across scales. Here, we integrate ground and Earth observation data to map annual forest-related greenhouse gas emissions and removals globally at a spatial resolution of 30 m over the years 2001–2019. We estimate that global forests were a net carbon sink of −7.6 ± 49 GtCO2e yr−1, reflecting a balance between gross carbon removals (−15.6 ± 49 GtCO2e yr−1) and gross emissions from deforestation and other disturbances (8.1 ± 2.5 GtCO2e yr−1). The geospatial monitoring framework introduced here supports climate policy development by promoting alignment and transparency in setting priorities and tracking collective progress towards forest-specific climate mitigation goals with both local detail and global consistency.

    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 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
    Nature Climate Change
    Article . 2021 . Peer-reviewed
    License: Springer TDM
    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 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
      Nature Climate Change
      Article . 2021 . Peer-reviewed
      License: Springer TDM
      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: 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).

    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/ ZENODOarrow_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/
    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
    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/
    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
    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/
    ZENODO
    Dataset . 2022
    License: CC BY
    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/ ZENODOarrow_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/
      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: ZENODO
      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/
      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
      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/
      ZENODO
      Dataset . 2022
      License: CC BY
      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: Gert-Jan Nabuurs; Nancy Harris; Douglas Sheil; Marc Palahi; +5 Authors

    Commitments made at COP26 in Glasgow shine a spotlight on how changes in global tree cover are defined, monitored and accounted for. Signed by 141 countries, the Glasgow Leaders’ Declaration on Forests and Land Use1 commits signatories to collectively “halt and reverse forest loss and land degradation by 2030 while delivering sustainable development”. This declaration recognizes that land use and land management are responsible for an estimated 23% of global anthropogenic greenhouse gas emissions and that any plausible scenario to limit global warming to 1.5 °C by 2100 must maintain and expand tree cover2. It also recognizes that sustainable land use requires transformative international-to-local action covering relevant global production and consumption systems while simultaneously empowering smallholders, Indigenous peoples and local communities2. However, timely and effective monitoring of such transformative actions requires improved, open and shared data and new collective modes of ownership for forest information.

    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
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    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
    Nature Climate Change
    Article . 2022 . Peer-reviewed
    License: Springer TDM
    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 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
      Nature Climate Change
      Article . 2022 . Peer-reviewed
      License: Springer TDM
      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: 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/ Nature Communication...arrow_drop_down
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    Nature Communications
    Article . 2022 . 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/
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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/ Nature Communication...arrow_drop_down
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      Nature Communications
      Article . 2022 . Peer-reviewed
      License: CC BY
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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/
      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 . 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
    Article . 2022 . 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/
    Environmental Research Letters
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    Environmental Research Letters
    Article . 2022
    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/
    Wageningen Staff Publications
    Article . 2022
    License: CC BY
    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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      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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    Authors: Arnan Araza; Martin Herold; Sytze de Bruin; Philippe Ciais; +26 Authors

    La biomasse aérienne (AGB) est considérée comme une variable climatique essentielle qui sous-tend nos connaissances et nos informations sur le rôle des forêts dans l'atténuation du changement climatique. La disponibilité des produits AGB et AGB change (ΔAGB) par satellite a augmenté ces dernières années. Ici, nous avons évalué le ΔAGB net de la dernière décennie dérivé de quatre cartes AGB multi-dates mondiales récentes : cartes ESA-CCI, modèle WRI-Flux, séries temporelles JPL et séries temporelles SMOS-LVOD. Nos évaluations explorent et utilisent différentes sources de données de référence avec des réévaluations de la biomasse au cours de la dernière décennie. Les données de référence comprennent les données des placettes de l'Inventaire forestier national (INF), les cartes ΔAGB locales du LiDAR aéroporté et certaines données de pays de l'Évaluation des ressources forestières provenant de pays dotés de capacités de suivi bien développées. Des comparaisons entre la carte et les données de référence ont été effectuées à des niveaux allant de 100 m à 25 km d'échelle spatiale. Les comparaisons ont révélé que les données LiDAR se comparaient le plus raisonnablement aux cartes, tandis que les comparaisons utilisant NFI ne montraient que quelques accords à des niveaux d'agrégation <10 km. Quel que soit le niveau d'agrégation, les pertes et les gains d'AGB selon les comparaisons cartographiques étaient systématiquement inférieurs aux données de référence. Les comparaisons de cartes à 25 km ont mis en évidence que les cartes capturaient systématiquement les pertes d'AGB dans les points chauds de déforestation connus. Les comparaisons ont également identifié plusieurs régions de puits de carbone systématiquement détectées par toutes les cartes. Cependant, les désaccords entre les cartes sont encore importants dans les régions forestières clés telles que le bassin amazonien. La corrélation croisée globale des cartes ΔAGB entre les cartes variait entre 0,11 et 0,29 (r). Les magnitudes ΔAGB déclarées étaient les plus grandes dans les ensembles de données à haute résolution, y compris les méthodes de différentiation de carte CCI (variation de stock) et de modèle de flux (gain-perte), tandis qu'elles étaient les plus petites selon les produits de séries chronologiques LVOD et JPL à résolution plus grossière, en particulier pour les gains AGB. Nos résultats suggèrent que le ΔAGB évalué à partir des cartes actuelles peut être biaisé et toute utilisation des estimations devrait en tenir compte. Actuellement, les données de référence ΔAGB sont rares, en particulier sous les tropiques, mais ce déficit peut être atténué par les réseaux de données LiDAR à venir dans le contexte des Supersites et des GEO-Trees. La biomasa sobre el suelo (AGB) se considera una variable climática esencial que sustenta nuestro conocimiento e información sobre el papel de los bosques en la mitigación del cambio climático. La disponibilidad de productos AGB y AGB change (ΔAGB) basados en satélites ha aumentado en los últimos años. Aquí evaluamos la ΔAGB neta de la última década derivada de cuatro mapas AGB globales de múltiples fechas recientes: mapas ESA-CCI, modelo WRI-Flux, series de tiempo JPL y series de tiempo SMOS-LVOD. Nuestras evaluaciones exploran y utilizan diferentes fuentes de datos de referencia con nuevas mediciones de biomasa en la última década. Los datos de referencia comprenden datos de parcelas del Inventario Forestal Nacional (NFI), mapas locales ΔAGB de LiDAR aerotransportado y datos de países seleccionados de Evaluación de Recursos Forestales de países con capacidades de monitoreo bien desarrolladas. Las comparaciones del mapa con los datos de referencia se realizaron a niveles que van desde una escala espacial de 100 m a 25 km. Las comparaciones revelaron que los datos LiDAR se compararon más razonablemente con los mapas, mientras que las comparaciones utilizando NFI solo mostraron algunos acuerdos a niveles de agregación <10 km. Independientemente del nivel de agregación, las pérdidas y ganancias de AGB de acuerdo con las comparaciones del mapa fueron consistentemente menores que los datos de referencia. Las comparaciones mapa-mapa a 25 km destacaron que los mapas capturaron consistentemente las pérdidas de AGB en puntos críticos de deforestación conocidos. Las comparaciones también identificaron varias regiones sumideras de carbono detectadas consistentemente por todos los mapas. Sin embargo, el desacuerdo entre los mapas sigue siendo grande en regiones forestales clave como la cuenca del Amazonas. La correlación cruzada general del mapa ΔAGB entre los mapas varió en el rango de 0.11-0.29 (r). Las magnitudes ΔAGB informadas fueron las más grandes en los conjuntos de datos de alta resolución, incluidos los métodos de diferenciación de mapas CCI (cambio de stock) y modelo de flujo (ganancia-pérdida), mientras que fueron las más pequeñas de acuerdo con los productos de series de tiempo LVOD y JPL de resolución más gruesa, especialmente para las ganancias AGB. Nuestros resultados sugieren que la ΔAGB evaluada a partir de los mapas actuales puede estar sesgada y cualquier uso de las estimaciones debe tenerlo en cuenta. Actualmente, los datos de referencia de ΔAGB son escasos, especialmente en los trópicos, pero ese déficit puede aliviarse con las próximas redes de datos LiDAR en el contexto de los supersitios y los árboles GEO. Above-ground biomass (AGB) is considered an essential climate variable that underpins our knowledge and information about the role of forests in mitigating climate change. The availability of satellite-based AGB and AGB change (ΔAGB) products has increased in recent years. Here we assessed the past decade net ΔAGB derived from four recent global multi-date AGB maps: ESA-CCI maps, WRI-Flux model, JPL time series, and SMOS-LVOD time series. Our assessments explore and use different reference data sources with biomass re-measurements within the past decade. The reference data comprise National Forest Inventory (NFI) plot data, local ΔAGB maps from airborne LiDAR, and selected Forest Resource Assessment country data from countries with well-developed monitoring capacities. Map to reference data comparisons were performed at levels ranging from 100 m to 25 km spatial scale. The comparisons revealed that LiDAR data compared most reasonably with the maps, while the comparisons using NFI only showed some agreements at aggregation levels <10 km. Regardless of the aggregation level, AGB losses and gains according to the map comparisons were consistently smaller than the reference data. Map-map comparisons at 25 km highlighted that the maps consistently captured AGB losses in known deforestation hotspots. The comparisons also identified several carbon sink regions consistently detected by all maps. However, disagreement between maps is still large in key forest regions such as the Amazon basin. The overall ΔAGB map cross-correlation between maps varied in the range 0.11–0.29 (r). Reported ΔAGB magnitudes were largest in the high-resolution datasets including the CCI map differencing (stock change) and Flux model (gain-loss) methods, while they were smallest according to the coarser-resolution LVOD and JPL time series products, especially for AGB gains. Our results suggest that ΔAGB assessed from current maps can be biased and any use of the estimates should take that into account. Currently, ΔAGB reference data are sparse especially in the tropics but that deficit can be alleviated by upcoming LiDAR data networks in the context of Supersites and GEO-Trees. تعتبر الكتلة الحيوية فوق الأرض (AGB) متغيرًا مناخيًا أساسيًا يدعم معرفتنا ومعلوماتنا حول دور الغابات في التخفيف من تغير المناخ. زاد توافر منتجات تغيير AGB و AGB المستندة إلى الأقمار الصناعية (ΔAGB) في السنوات الأخيرة. هنا قمنا بتقييم صافي ΔAGB للعقد الماضي المستمد من أربع خرائط AGB عالمية حديثة متعددة التواريخ: خرائط ESA - CCI، ونموذج WRI - Flowx، والسلاسل الزمنية JPL، والسلاسل الزمنية SMOS - LVOD. تستكشف تقييماتنا وتستخدم مصادر بيانات مرجعية مختلفة مع إعادة قياس الكتلة الحيوية خلال العقد الماضي. تشمل البيانات المرجعية بيانات قطع الأراضي الوطنية للغابات (NFI)، وخرائط ΔAGB المحلية من LiDAR المحمولة جواً، وبيانات قطرية مختارة لتقييم الموارد الحرجية من البلدان ذات قدرات الرصد المتطورة. تم إجراء مقارنات بين الخريطة والبيانات المرجعية على مستويات تتراوح من 100 متر إلى 25 كم على نطاق مكاني. كشفت المقارنات أن بيانات ليدار قارنت بشكل معقول مع الخرائط، في حين أن المقارنات باستخدام المواد غير الغذائية أظهرت فقط بعض الاتفاقات عند مستويات التجميع <10 كم. بغض النظر عن مستوى التجميع، كانت خسائر ومكاسب AGB وفقًا لمقارنات الخريطة أصغر باستمرار من البيانات المرجعية. سلطت مقارنات الخرائط على بعد 25 كم الضوء على أن الخرائط سجلت باستمرار خسائر AGB في النقاط الساخنة المعروفة لإزالة الغابات. كما حددت المقارنات العديد من مناطق بالوعة الكربون التي تم اكتشافها باستمرار من قبل جميع الخرائط. ومع ذلك، لا يزال الخلاف بين الخرائط كبيرًا في مناطق الغابات الرئيسية مثل حوض الأمازون. اختلف الارتباط التبادلي العام لخريطة ΔAGB بين الخرائط في النطاق 0.11–0.29 (r). كانت مقادير ΔAGB المبلغ عنها هي الأكبر في مجموعات البيانات عالية الدقة بما في ذلك اختلافات خريطة CCI (تغيير الأسهم) وطرق نموذج Flux (الربح والخسارة)، في حين كانت أصغر وفقًا لمنتجات السلاسل الزمنية LVOD و JPL ذات الدقة الخشنة، خاصة بالنسبة لمكاسب AGB. تشير نتائجنا إلى أن ΔAGB المقيّمة من الخرائط الحالية يمكن أن تكون متحيزة وأي استخدام للتقديرات يجب أن يأخذ ذلك في الاعتبار. في الوقت الحالي، البيانات المرجعية ΔAGB متناثرة خاصة في المناطق الاستوائية ولكن يمكن تخفيف هذا العجز من خلال شبكات بيانات ليدار القادمة في سياق المواقع الفائقة والأشجار الجغرافية.

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    Authors: Nancy L. Harris; Adam Duncan; Rebecca K. Runting; James E. M. Watson; +11 Authors

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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/ The University of Me...arrow_drop_down
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      Science Advances
      Article . 2019 . Peer-reviewed
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      Science Advances
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      Science Advances
      Article . 2020
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7 Research products
  • 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: Alexandra Tyukavina; Nancy L. Harris; Alessandro Baccini; Sassan Saatchi; +14 Authors

    Managing forests for climate change mitigation requires action by diverse stakeholders undertaking different activities with overlapping objectives and spatial impacts. To date, several forest carbon monitoring systems have been developed for different regions using various data, methods and assumptions, making it difficult to evaluate mitigation performance consistently across scales. Here, we integrate ground and Earth observation data to map annual forest-related greenhouse gas emissions and removals globally at a spatial resolution of 30 m over the years 2001–2019. We estimate that global forests were a net carbon sink of −7.6 ± 49 GtCO2e yr−1, reflecting a balance between gross carbon removals (−15.6 ± 49 GtCO2e yr−1) and gross emissions from deforestation and other disturbances (8.1 ± 2.5 GtCO2e yr−1). The geospatial monitoring framework introduced here supports climate policy development by promoting alignment and transparency in setting priorities and tracking collective progress towards forest-specific climate mitigation goals with both local detail and global consistency.

    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 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
    Nature Climate Change
    Article . 2021 . Peer-reviewed
    License: Springer TDM
    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 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
      Nature Climate Change
      Article . 2021 . Peer-reviewed
      License: Springer TDM
      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: 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).

    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/ ZENODOarrow_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/
    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
    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/
    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
    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/
    ZENODO
    Dataset . 2022
    License: CC BY
    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/ ZENODOarrow_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/
      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: ZENODO
      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/
      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
      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/
      ZENODO
      Dataset . 2022
      License: CC BY
      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: Gert-Jan Nabuurs; Nancy Harris; Douglas Sheil; Marc Palahi; +5 Authors

    Commitments made at COP26 in Glasgow shine a spotlight on how changes in global tree cover are defined, monitored and accounted for. Signed by 141 countries, the Glasgow Leaders’ Declaration on Forests and Land Use1 commits signatories to collectively “halt and reverse forest loss and land degradation by 2030 while delivering sustainable development”. This declaration recognizes that land use and land management are responsible for an estimated 23% of global anthropogenic greenhouse gas emissions and that any plausible scenario to limit global warming to 1.5 °C by 2100 must maintain and expand tree cover2. It also recognizes that sustainable land use requires transformative international-to-local action covering relevant global production and consumption systems while simultaneously empowering smallholders, Indigenous peoples and local communities2. However, timely and effective monitoring of such transformative actions requires improved, open and shared data and new collective modes of ownership for forest information.

    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 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
    Nature Climate Change
    Article . 2022 . Peer-reviewed
    License: Springer TDM
    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 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
      Nature Climate Change
      Article . 2022 . Peer-reviewed
      License: Springer TDM
      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: 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/ Nature Communication...arrow_drop_down
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    Nature Communications
    Article . 2022 . 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/
    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 . 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/ 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 . 2022 . 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/
      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 . 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.

    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
    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/
    Environmental Research Letters
    Article
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    Environmental Research Letters
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    Authors: Arnan Araza; Martin Herold; Sytze de Bruin; Philippe Ciais; +26 Authors

    La biomasse aérienne (AGB) est considérée comme une variable climatique essentielle qui sous-tend nos connaissances et nos informations sur le rôle des forêts dans l'atténuation du changement climatique. La disponibilité des produits AGB et AGB change (ΔAGB) par satellite a augmenté ces dernières années. Ici, nous avons évalué le ΔAGB net de la dernière décennie dérivé de quatre cartes AGB multi-dates mondiales récentes : cartes ESA-CCI, modèle WRI-Flux, séries temporelles JPL et séries temporelles SMOS-LVOD. Nos évaluations explorent et utilisent différentes sources de données de référence avec des réévaluations de la biomasse au cours de la dernière décennie. Les données de référence comprennent les données des placettes de l'Inventaire forestier national (INF), les cartes ΔAGB locales du LiDAR aéroporté et certaines données de pays de l'Évaluation des ressources forestières provenant de pays dotés de capacités de suivi bien développées. Des comparaisons entre la carte et les données de référence ont été effectuées à des niveaux allant de 100 m à 25 km d'échelle spatiale. Les comparaisons ont révélé que les données LiDAR se comparaient le plus raisonnablement aux cartes, tandis que les comparaisons utilisant NFI ne montraient que quelques accords à des niveaux d'agrégation <10 km. Quel que soit le niveau d'agrégation, les pertes et les gains d'AGB selon les comparaisons cartographiques étaient systématiquement inférieurs aux données de référence. Les comparaisons de cartes à 25 km ont mis en évidence que les cartes capturaient systématiquement les pertes d'AGB dans les points chauds de déforestation connus. Les comparaisons ont également identifié plusieurs régions de puits de carbone systématiquement détectées par toutes les cartes. Cependant, les désaccords entre les cartes sont encore importants dans les régions forestières clés telles que le bassin amazonien. La corrélation croisée globale des cartes ΔAGB entre les cartes variait entre 0,11 et 0,29 (r). Les magnitudes ΔAGB déclarées étaient les plus grandes dans les ensembles de données à haute résolution, y compris les méthodes de différentiation de carte CCI (variation de stock) et de modèle de flux (gain-perte), tandis qu'elles étaient les plus petites selon les produits de séries chronologiques LVOD et JPL à résolution plus grossière, en particulier pour les gains AGB. Nos résultats suggèrent que le ΔAGB évalué à partir des cartes actuelles peut être biaisé et toute utilisation des estimations devrait en tenir compte. Actuellement, les données de référence ΔAGB sont rares, en particulier sous les tropiques, mais ce déficit peut être atténué par les réseaux de données LiDAR à venir dans le contexte des Supersites et des GEO-Trees. La biomasa sobre el suelo (AGB) se considera una variable climática esencial que sustenta nuestro conocimiento e información sobre el papel de los bosques en la mitigación del cambio climático. La disponibilidad de productos AGB y AGB change (ΔAGB) basados en satélites ha aumentado en los últimos años. Aquí evaluamos la ΔAGB neta de la última década derivada de cuatro mapas AGB globales de múltiples fechas recientes: mapas ESA-CCI, modelo WRI-Flux, series de tiempo JPL y series de tiempo SMOS-LVOD. Nuestras evaluaciones exploran y utilizan diferentes fuentes de datos de referencia con nuevas mediciones de biomasa en la última década. Los datos de referencia comprenden datos de parcelas del Inventario Forestal Nacional (NFI), mapas locales ΔAGB de LiDAR aerotransportado y datos de países seleccionados de Evaluación de Recursos Forestales de países con capacidades de monitoreo bien desarrolladas. Las comparaciones del mapa con los datos de referencia se realizaron a niveles que van desde una escala espacial de 100 m a 25 km. Las comparaciones revelaron que los datos LiDAR se compararon más razonablemente con los mapas, mientras que las comparaciones utilizando NFI solo mostraron algunos acuerdos a niveles de agregación <10 km. Independientemente del nivel de agregación, las pérdidas y ganancias de AGB de acuerdo con las comparaciones del mapa fueron consistentemente menores que los datos de referencia. Las comparaciones mapa-mapa a 25 km destacaron que los mapas capturaron consistentemente las pérdidas de AGB en puntos críticos de deforestación conocidos. Las comparaciones también identificaron varias regiones sumideras de carbono detectadas consistentemente por todos los mapas. Sin embargo, el desacuerdo entre los mapas sigue siendo grande en regiones forestales clave como la cuenca del Amazonas. La correlación cruzada general del mapa ΔAGB entre los mapas varió en el rango de 0.11-0.29 (r). Las magnitudes ΔAGB informadas fueron las más grandes en los conjuntos de datos de alta resolución, incluidos los métodos de diferenciación de mapas CCI (cambio de stock) y modelo de flujo (ganancia-pérdida), mientras que fueron las más pequeñas de acuerdo con los productos de series de tiempo LVOD y JPL de resolución más gruesa, especialmente para las ganancias AGB. Nuestros resultados sugieren que la ΔAGB evaluada a partir de los mapas actuales puede estar sesgada y cualquier uso de las estimaciones debe tenerlo en cuenta. Actualmente, los datos de referencia de ΔAGB son escasos, especialmente en los trópicos, pero ese déficit puede aliviarse con las próximas redes de datos LiDAR en el contexto de los supersitios y los árboles GEO. Above-ground biomass (AGB) is considered an essential climate variable that underpins our knowledge and information about the role of forests in mitigating climate change. The availability of satellite-based AGB and AGB change (ΔAGB) products has increased in recent years. Here we assessed the past decade net ΔAGB derived from four recent global multi-date AGB maps: ESA-CCI maps, WRI-Flux model, JPL time series, and SMOS-LVOD time series. Our assessments explore and use different reference data sources with biomass re-measurements within the past decade. The reference data comprise National Forest Inventory (NFI) plot data, local ΔAGB maps from airborne LiDAR, and selected Forest Resource Assessment country data from countries with well-developed monitoring capacities. Map to reference data comparisons were performed at levels ranging from 100 m to 25 km spatial scale. The comparisons revealed that LiDAR data compared most reasonably with the maps, while the comparisons using NFI only showed some agreements at aggregation levels <10 km. Regardless of the aggregation level, AGB losses and gains according to the map comparisons were consistently smaller than the reference data. Map-map comparisons at 25 km highlighted that the maps consistently captured AGB losses in known deforestation hotspots. The comparisons also identified several carbon sink regions consistently detected by all maps. However, disagreement between maps is still large in key forest regions such as the Amazon basin. The overall ΔAGB map cross-correlation between maps varied in the range 0.11–0.29 (r). Reported ΔAGB magnitudes were largest in the high-resolution datasets including the CCI map differencing (stock change) and Flux model (gain-loss) methods, while they were smallest according to the coarser-resolution LVOD and JPL time series products, especially for AGB gains. Our results suggest that ΔAGB assessed from current maps can be biased and any use of the estimates should take that into account. Currently, ΔAGB reference data are sparse especially in the tropics but that deficit can be alleviated by upcoming LiDAR data networks in the context of Supersites and GEO-Trees. تعتبر الكتلة الحيوية فوق الأرض (AGB) متغيرًا مناخيًا أساسيًا يدعم معرفتنا ومعلوماتنا حول دور الغابات في التخفيف من تغير المناخ. زاد توافر منتجات تغيير AGB و AGB المستندة إلى الأقمار الصناعية (ΔAGB) في السنوات الأخيرة. هنا قمنا بتقييم صافي ΔAGB للعقد الماضي المستمد من أربع خرائط AGB عالمية حديثة متعددة التواريخ: خرائط ESA - CCI، ونموذج WRI - Flowx، والسلاسل الزمنية JPL، والسلاسل الزمنية SMOS - LVOD. تستكشف تقييماتنا وتستخدم مصادر بيانات مرجعية مختلفة مع إعادة قياس الكتلة الحيوية خلال العقد الماضي. تشمل البيانات المرجعية بيانات قطع الأراضي الوطنية للغابات (NFI)، وخرائط ΔAGB المحلية من LiDAR المحمولة جواً، وبيانات قطرية مختارة لتقييم الموارد الحرجية من البلدان ذات قدرات الرصد المتطورة. تم إجراء مقارنات بين الخريطة والبيانات المرجعية على مستويات تتراوح من 100 متر إلى 25 كم على نطاق مكاني. كشفت المقارنات أن بيانات ليدار قارنت بشكل معقول مع الخرائط، في حين أن المقارنات باستخدام المواد غير الغذائية أظهرت فقط بعض الاتفاقات عند مستويات التجميع <10 كم. بغض النظر عن مستوى التجميع، كانت خسائر ومكاسب AGB وفقًا لمقارنات الخريطة أصغر باستمرار من البيانات المرجعية. سلطت مقارنات الخرائط على بعد 25 كم الضوء على أن الخرائط سجلت باستمرار خسائر AGB في النقاط الساخنة المعروفة لإزالة الغابات. كما حددت المقارنات العديد من مناطق بالوعة الكربون التي تم اكتشافها باستمرار من قبل جميع الخرائط. ومع ذلك، لا يزال الخلاف بين الخرائط كبيرًا في مناطق الغابات الرئيسية مثل حوض الأمازون. اختلف الارتباط التبادلي العام لخريطة ΔAGB بين الخرائط في النطاق 0.11–0.29 (r). كانت مقادير ΔAGB المبلغ عنها هي الأكبر في مجموعات البيانات عالية الدقة بما في ذلك اختلافات خريطة CCI (تغيير الأسهم) وطرق نموذج Flux (الربح والخسارة)، في حين كانت أصغر وفقًا لمنتجات السلاسل الزمنية LVOD و JPL ذات الدقة الخشنة، خاصة بالنسبة لمكاسب AGB. تشير نتائجنا إلى أن ΔAGB المقيّمة من الخرائط الحالية يمكن أن تكون متحيزة وأي استخدام للتقديرات يجب أن يأخذ ذلك في الاعتبار. في الوقت الحالي، البيانات المرجعية ΔAGB متناثرة خاصة في المناطق الاستوائية ولكن يمكن تخفيف هذا العجز من خلال شبكات بيانات ليدار القادمة في سياق المواقع الفائقة والأشجار الجغرافية.

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    Authors: Nancy L. Harris; Adam Duncan; Rebecca K. Runting; James E. M. Watson; +11 Authors

    More complete accounting reveals how intact tropical forest loss plays a larger-than-realized role in exacerbating climate change.

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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/ The University of Me...arrow_drop_down
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