Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from 5 years of monthly drone data for a 50 ha plot
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Published:2021-12-20
Issue:24
Volume:18
Page:6517-6531
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ISSN:1726-4189
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Container-title:Biogeosciences
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language:en
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Short-container-title:Biogeosciences
Author:
Araujo Raquel Fernandes, Grubinger Samuel, Celes Carlos Henrique Souza, Negrón-Juárez Robinson I.ORCID, Garcia Milton, Dandois Jonathan P., Muller-Landau Helene C.ORCID
Abstract
Abstract. A mechanistic understanding of how tropical-tree mortality
responds to climate variation is urgently needed to predict how tropical-forest carbon pools will respond to anthropogenic global change, which
is altering the frequency and intensity of storms, droughts, and other
climate extremes in tropical forests. We used 5 years of approximately
monthly drone-acquired RGB (red–green–blue) imagery for 50 ha of mature tropical forest on
Barro Colorado Island, Panama, to quantify spatial structure; temporal
variation; and climate correlates of canopy disturbances, i.e., sudden and
major drops in canopy height due to treefalls, branchfalls, or the collapse of
standing dead trees. Canopy disturbance rates varied strongly over time and
were higher in the wet season, even though wind speeds were lower in the wet
season. The strongest correlate of monthly variation in canopy disturbance
rates was the frequency of extreme rainfall events. The size distribution of
canopy disturbances was best fit by a Weibull function and was close to a
power function for sizes above 25 m2. Treefalls accounted for 74 %
of the total area and 52 % of the total number of canopy disturbances in
treefalls and branchfalls combined. We hypothesize that extremely high
rainfall is a good predictor because it is an indicator of storms having
high wind speeds, as well as saturated soils that increase uprooting risk.
These results demonstrate the utility of repeat drone-acquired data for
quantifying forest canopy disturbance rates at fine temporal and spatial
resolutions over large areas, thereby enabling robust tests of how temporal
variation in disturbance relates to climate drivers. Further insights could
be gained by integrating these canopy observations with high-frequency
measurements of wind speed and soil moisture in mechanistic models to better
evaluate proximate drivers and with focal tree observations to quantify the
links to tree mortality and woody turnover.
Publisher
Copernicus GmbH
Subject
Earth-Surface Processes,Ecology, Evolution, Behavior and Systematics
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