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      Large carbon sink potential of secondary forests in the Brazilian Amazon to mitigate climate change

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          Abstract

          Tropical secondary forests sequester carbon up to 20 times faster than old-growth forests. This rate does not capture spatial regrowth patterns due to environmental and disturbance drivers. Here we quantify the influence of such drivers on the rate and spatial patterns of regrowth in the Brazilian Amazon using satellite data. Carbon sequestration rates of young secondary forests (<20 years) in the west are ~60% higher (3.0 ± 1.0 Mg C ha −1 yr −1) compared to those in the east (1.3 ± 0.3 Mg C ha −1 yr −1). Disturbances reduce regrowth rates by 8–55%. The 2017 secondary forest carbon stock, of 294 Tg C, could be 8% higher by avoiding fires and repeated deforestation. Maintaining the 2017 secondary forest area has the potential to accumulate ~19.0 Tg C yr −1 until 2030, contributing ~5.5% to Brazil’s 2030 net emissions reduction target. Implementing legal mechanisms to protect and expand secondary forests whilst supporting old-growth conservation is, therefore, key to realising their potential as a nature-based climate solution.

          Abstract

          This study uses regional and global remote sensing data to assess the regrowth of secondary forests in the Brazilian Amazon biome. The authors find differences of regrowth rates due to climate, forest fires and deforestation actions and further quantify their carbon capture potential.

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          A large and persistent carbon sink in the world's forests.

          The terrestrial carbon sink has been large in recent decades, but its size and location remain uncertain. Using forest inventory data and long-term ecosystem carbon studies, we estimate a total forest sink of 2.4 ± 0.4 petagrams of carbon per year (Pg C year(-1)) globally for 1990 to 2007. We also estimate a source of 1.3 ± 0.7 Pg C year(-1) from tropical land-use change, consisting of a gross tropical deforestation emission of 2.9 ± 0.5 Pg C year(-1) partially compensated by a carbon sink in tropical forest regrowth of 1.6 ± 0.5 Pg C year(-1). Together, the fluxes comprise a net global forest sink of 1.1 ± 0.8 Pg C year(-1), with tropical estimates having the largest uncertainties. Our total forest sink estimate is equivalent in magnitude to the terrestrial sink deduced from fossil fuel emissions and land-use change sources minus ocean and atmospheric sinks.
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            A Flexible Growth Function for Empirical Use

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              The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes

              The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset builds on previous approaches to ‘smart’ interpolation techniques and high resolution, long period of record precipitation estimates based on infrared Cold Cloud Duration (CCD) observations. The algorithm i) is built around a 0.05° climatology that incorporates satellite information to represent sparsely gauged locations, ii) incorporates daily, pentadal, and monthly 1981-present 0.05° CCD-based precipitation estimates, iii) blends station data to produce a preliminary information product with a latency of about 2 days and a final product with an average latency of about 3 weeks, and iv) uses a novel blending procedure incorporating the spatial correlation structure of CCD-estimates to assign interpolation weights. We present the CHIRPS algorithm, global and regional validation results, and show how CHIRPS can be used to quantify the hydrologic impacts of decreasing precipitation and rising air temperatures in the Greater Horn of Africa. Using the Variable Infiltration Capacity model, we show that CHIRPS can support effective hydrologic forecasts and trend analyses in southeastern Ethiopia.
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                Author and article information

                Contributors
                viola.heinrich@bristol.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                19 March 2021
                19 March 2021
                2021
                : 12
                : 1785
                Affiliations
                [1 ]GRID grid.5337.2, ISNI 0000 0004 1936 7603, School of Geographical Sciences, , University of Bristol, ; Bristol, UK
                [2 ]GRID grid.419222.e, ISNI 0000 0001 2116 4512, Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), ; São José dos Campos, Brazil
                [3 ]GRID grid.8391.3, ISNI 0000 0004 1936 8024, College of Life and Environmental Sciences, , University of Exeter, ; Exeter, UK
                [4 ]GRID grid.5337.2, ISNI 0000 0004 1936 7603, Cabot institute, , University of Bristol, ; Bristol, UK
                [5 ]GRID grid.5600.3, ISNI 0000 0001 0807 5670, School of Earth and Environmental Sciences, , Cardiff University, ; Cardiff, UK
                [6 ]GRID grid.419222.e, ISNI 0000 0001 2116 4512, Amazon Regional Center, , National Institute for Space Research (INPE), ; Belém, Brazil
                [7 ]National Center for Monitoring and Early Warning of Natural Disaster (CEMADEN), São José dos Campos, Brazil
                Author information
                http://orcid.org/0000-0003-0501-0032
                http://orcid.org/0000-0001-6728-4712
                http://orcid.org/0000-0002-1052-5551
                http://orcid.org/0000-0001-5719-8407
                http://orcid.org/0000-0003-4576-3960
                http://orcid.org/0000-0003-1821-8561
                http://orcid.org/0000-0003-4247-4477
                http://orcid.org/0000-0001-9545-5136
                Article
                22050
                10.1038/s41467-021-22050-1
                7979697
                33741981
                021eab4e-dedf-4ed3-bda9-6cd69283ebeb
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 11 September 2020
                : 19 February 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000270, RCUK | Natural Environment Research Council (NERC);
                Award ID: NE/L002434
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100003593, Ministry of Science, Technology and Innovation | Conselho Nacional de Desenvolvimento Científico e Tecnológico (National Council for Scientific and Technological Development);
                Award ID: 160286/2019-0
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100010897, Newton Fund;
                Award ID: CSSP Brazil
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100011110, Inter-American Institute for Global Change Research (Instituto Interamericano para la Investigación del Cambio Global);
                Award ID: SGP-HW 016
                Award Recipient :
                Funded by: Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) FAPESP: 2018/14423-4 FAPESP: 2019/21662-8 Royal Newton Advanced Fellowship: NAF/R1/180405 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior : 001 FAPESP: 2018/15001-6
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                forest ecology,carbon cycle,climate-change mitigation
                Uncategorized
                forest ecology, carbon cycle, climate-change mitigation

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