@InProceedings{DalagnolWPGOASGA:2019:FoCaGa,
               author = "Dalagnol, Ricardo and Wagner, Fabien Hubert and Phillips, Oliver 
                         L. and Gloor, Emanuel Ulrich and Ometto, Jean Pierre Henry Balbaud 
                         and Assis, Mauro L{\'u}cio Rodrigues de and Sato, Luciane Yumie 
                         and Galv{\~a}o, L{\^e}nio Soares and Arag{\~a}o, Luiz Eduardo 
                         Oliveira e Cruz de",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {University of Leeds} 
                         and {University of Leeds} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Forest Canopy Gap Dynamics Vary Across a Climatic Gradient in the 
                         Brazilian Amazon",
                 year = "2019",
         organization = "AGU Fall Meeting",
             abstract = "The limited knowledge on tropical tree mortality - or gap dynamics 
                         - constrains our ability to accurately model earth system 
                         processes and predict future states of ecosystems under 
                         environmental and climate change scenarios. While site-based 
                         studies have analyzed local drivers of canopy gap dynamics in 
                         neotropical forests, regional-scale climate drivers remain to be 
                         explained. Here, to describe the variability of canopy gaps and 
                         explore its relationship with climate drivers, we used 20 
                         transects of 15 x 0.6 km (180 kmē) airborne LiDAR data acquired in 
                         2016 across a precipitation gradient in the Brazilian Amazon. Gaps 
                         were delineated considering areas with less than 10 m height, and 
                         within the sizes of 1 mē and 0.5 ha. The gap size-frequency 
                         distribution was quantified by fitting a discrete power-law 
                         probability (Zeta distribution) to the data - described by the 
                         \λ parameter (low \λ indicate a higher frequency of 
                         large gaps, and vice-versa). To describe the climatic gradient, we 
                         used a time series (1998-2017) of the TRMM-3B43V7 and computed for 
                         each site the mean monthly rainfall (R) and two descriptors of 
                         seasonality: Feng index (S, varies from 0 to 0.2) and the dry 
                         season length (DSL, number of months with rainfall below 100 mm). 
                         A narrow range of \λ was observed varying from 1.42 to 1.63 
                         (mean gap sizes of 37 and 7 mē, respectively). Our highest 
                         \λ occurred at the north-west, an area with high R (284 mm) 
                         and almost no seasonality (S and DSL = ~0). By contrast, the 
                         lowest \λ occurred at the south-east, an area with lower R 
                         (170 mm) and high seasonality (S = 0.12, DSL = 7 mo). The 
                         variability of \λ was largely explained by seasonality by 
                         DSL (Rē = 0.56) and S (Rē = 0.48) with negative relationships, and 
                         also by R (Rē = 0.55) with a positive relationship. While these 
                         relationships are not necessarily causal, rainfall mean and 
                         seasonality seem to play important roles for regional-scale gap 
                         dynamics. They are likely linked to forest structure variability 
                         and turnover. Regions with lower seasonality offer abundant 
                         resources and should be more prone to high growth, faster turnover 
                         and occurrence of smaller individuals (small gaps), while regions 
                         with higher seasonality might favor slow growth, slower turnover 
                         and occurrence of fewer but larger trees (large gaps). Future 
                         investigations should consider topographic and soil effects over 
                         canopy gap dynamics.",
  conference-location = "San Francisco, CA",
      conference-year = "09-13 dec.",
             language = "en",
           targetfile = "dalagnol_forest.pdf",
        urlaccessdate = "25 abr. 2024"
}