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.

Highlights

  • Moist tropical forests account for 40 % of the global biomass carbon stocks (Xu et al, 2021), and uncertainty regarding the future of these stocks is a major contributor to uncertainty in the future global carbon cycle (Cavaleri et al, 2015)

  • We identified 1048 canopy disturbances with a combined area of 56 134.37 m2 (5.61 ha) that affected the area within the Barro Colorado Island (BCI) 50 ha plot between 2 October 2014 and 28 November 2019 (Fig. 2)

  • A mechanistic understanding of the controls on woody residence time in tropical forests is urgently needed to predict the future of tropical-forest carbon stocks and biodiversity under global change (Johnson et al, 2016; McDowell et al, 2018; Muller-Landau et al, 2021)

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Summary

Introduction

Moist tropical forests account for 40 % of the global biomass carbon stocks (Xu et al, 2021), and uncertainty regarding the future of these stocks is a major contributor to uncertainty in the future global carbon cycle (Cavaleri et al, 2015). Tropical-forest carbon stocks depend critically on tree mortality rates, and recent studies suggest tropical-tree mortality rates may be increasing due to anthropogenic global change (Brienen et al, 2015; McDowell et al, 2018). Tropical-tree mortality can be caused by a diversity of drivers including windthrow (Fontes et al, 2018), droughts (McDowell et al, 2018; Silva et al, 2018), fires (Silva et al, 2018), lightning. An improved understanding of the processes of forest disturbance is critical to constrain estimates of current and future carbon cycling in tropical forests under climate change (Leitold et al, 2018; Johnson et al, 2016; Muller-Landau et al, 2021)

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