@Article{MouraBGDESGBOS:2020:CaStUs,
               author = "Moura, Yhasmin Mendes de and Balzter, Heiko and Galv{\~a}o, 
                         L{\^e}nio Soares and Dalagnol da Silva, Ricardo and 
                         Esp{\'{\i}}rito-Santo, Fernando and Santos, Erone G. and Garcia, 
                         Mariano and Bispo, Polyanna da Concei{\c{c}}{\~a}o and Oliveira 
                         J{\'u}nior, Raimundo C. and Shimabukuro, Yosio Edemir",
          affiliation = "{University of Leicester} and {University of Leicester} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {University of 
                         Leicester} and {University of Helsinki} and {Universidad de 
                         Alcal{\'a}} and {University of Manchester} and {Empresa 
                         Brasileira de Pesquisa Agropecu{\'a}ria (EMBRAPA)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Carbon dynamics in a human-modified tropical forest: a case study 
                         using multi-temporal LiDAR data",
              journal = "Remote Sensing",
                 year = "2020",
               volume = "12",
               number = "3",
                pages = "e430",
                month = "feb.",
             keywords = "airborne LiDAR, Amazon forest, aboveground carbon, canopy height, 
                         forest disturbance.",
             abstract = "Tropical forests hold significant amounts of carbon and play a 
                         critical role on Earth ' s climate system. To date, carbon 
                         dynamics over tropical forests have been poorly assessed, 
                         especially over vast areas of the tropics that have been affected 
                         by some type of disturbance (e.g., selective logging, understory 
                         fires, and fragmentation). Understanding the multi-temporal 
                         dynamics of carbon stocks over human-modified tropical forests 
                         (HMTF) is crucial to close the carbon cycle balance in the 
                         tropics. Here, we used multi-temporal and high-spatial resolution 
                         airborne LiDAR data to quantify rates of carbon dynamics over a 
                         large patch of HMTF in eastern Amazon, Brazil. We described a 
                         robust approach to monitor changes in aboveground forest carbon 
                         stocks between 2012 and 2018. Our results showed that this 
                         particular HMTF lost 0.57 myr(-1) in mean forest canopy height and 
                         1.38 MgCha(-1)yr(-1) of forest carbon between 2012 and 2018. 
                         LiDAR-based estimates of Aboveground Carbon Density (ACD) showed 
                         progressive loss through the years, from 77.9 MgCha(-1) in 2012 to 
                         53.1 MgCha(-1) in 2018, thus a decrease of 31.8%. Rates of carbon 
                         stock changes were negative for all time intervals analyzed, 
                         yielding average annual carbon loss rates of -1.34 
                         MgCha(-1)yr(-1). This suggests that this HMTF is acting more as a 
                         source of carbon than a sink, having great negative implications 
                         for carbon emission scenarios in tropical forests. Although more 
                         studies of forest dynamics in HMTFs are necessary to reduce the 
                         current remaining uncertainties in the carbon cycle, our results 
                         highlight the persistent effects of carbon losses for the study 
                         area. HMTFs are likely to expand across the Amazon in the near 
                         future. The resultant carbon source conditions, directly 
                         associated with disturbances, may be essential when considering 
                         climate projections and carbon accounting methods.",
                  doi = "10.3390/rs12030430",
                  url = "http://dx.doi.org/10.3390/rs12030430",
                 issn = "2072-4292",
             language = "en",
           targetfile = "moura_carbon.pdf",
        urlaccessdate = "27 abr. 2024"
}