@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 = "21 maio 2024"
}