@Article{BustamanteRAAAAABBCCFFFKMMMOPPSTV:2016:ToInMo,
               author = "Bustamante, Mercedes M. C. and Roitman, Iris and Aide, T. Mitchell 
                         and Alencar, Ane and Anderson, Liana O. and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de and Asner, Gregory P. and Barlow, Jos 
                         and Berenguer, Erika and Chambers, Jeffrey and Costa, Marcos H. 
                         and Fanin, Thierry and Ferreira, Laerte G. and Ferreira, Joice and 
                         Keller, Michael and Magnusson, William E. and Morales-Barquero, 
                         Lucia and Morton, Douglas and Ometto, Jean Pierre Henry Balbaud 
                         and Palace, Michael and Peres, Carlos A . and Silverio, Divino and 
                         Trumbore, Susan and Vieira, Ima C. G.",
          affiliation = "{Universidade de Bras{\'{\i}}lia (UNB)} and {Universidade de 
                         Bras{\'{\i}}lia (UNB)} and {Universidad Puerto Rico} and {Amazon 
                         Environm Res Inst IPAM} and {Natl Ctr Monitoring \& Early Warning 
                         Nat Disasters} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Carnegie Inst Sci} and {University of Lancaster} and 
                         {University of Lancaster} and {Univ Calif Berkeley} and 
                         {Universidade Federal de Vicosa} and {Vrije Univ Amsterdam} and 
                         {Universidade Federal de Goias} and {Embrapa Amazonia Oriental} 
                         and {US Forest Serv} and {Instituto Nacional de Pesquisas da 
                         Amazonia (INPA)} and {Bangor University} and NASA and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and UNH, Inst Study Earth 
                         Oceans \& Space and {Univ E Anglia} and {Universidade de 
                         Bras{\'{\i}}lia (UNB)} and {Max Planck Inst Biogeochem} and 
                         {Museu Paraense Emilio Goeldi}",
                title = "Toward an integrated monitoring framework to assess the effects of 
                         tropical forest degradation and recovery on carbon stocks and 
                         biodiversity",
              journal = "Global Change Biology",
                 year = "2016",
               volume = "22",
               number = "1",
                pages = "92--109",
                month = "Jan.",
             keywords = "carbon emissions, ecosystem modeling, field inventories, forest 
                         dynamics, remote sensing.",
             abstract = "Tropical forests harbor a significant portion of global 
                         biodiversity and are a critical component of the climate system. 
                         Reducing deforestation and forest degradation contributes to 
                         global climate-change mitigation efforts, yet emissions and 
                         removals from forest dynamics are still poorly quantified. We 
                         reviewed the main challenges to estimate changes in carbon stocks 
                         and biodiversity due to degradation and recovery of tropical 
                         forests, focusing on three main areas: (1) the combination of 
                         field surveys and remote sensing; (2) evaluation of biodiversity 
                         and carbon values under a unified strategy; and (3) research 
                         efforts needed to understand and quantify forest degradation and 
                         recovery. The improvement of models and estimates of changes of 
                         forest carbon can foster process-oriented monitoring of forest 
                         dynamics, including different variables and using spatially 
                         explicit algorithms that account for regional and local 
                         differences, such as variation in climate, soil, nutrient content, 
                         topography, biodiversity, disturbance history, recovery pathways, 
                         and socioeconomic factors. Generating the data for these models 
                         requires affordable large-scale remote-sensing tools associated 
                         with a robust network of field plots that can generate spatially 
                         explicit information on a range of variables through time. By 
                         combining ecosystem models, multiscale remote sensing, and 
                         networks of field plots, we will be able to evaluate forest 
                         degradation and recovery and their interactions with biodiversity 
                         and carbon cycling. Improving monitoring strategies will allow a 
                         better understanding of the role of forest dynamics in 
                         climate-change mitigation, adaptation, and carbon cycle feedbacks, 
                         thereby reducing uncertainties in models of the key processes in 
                         the carbon cycle, including their impacts on biodiversity, which 
                         are fundamental to support forest governance policies, such as 
                         Reducing Emissions from Deforestation and Forest Degradation.",
                  doi = "10.1111/gcb.13087",
                  url = "http://dx.doi.org/10.1111/gcb.13087",
                 issn = "1354-1013",
                label = "self-archiving-INPE-MCTI-GOV-BR",
             language = "en",
           targetfile = "bustamante_toward.pdf",
        urlaccessdate = "27 abr. 2024"
}