Tree mode of death and mortality risk factors across Amazon forests

Abstract

The carbon sink capacity of tropical forests is substantially affected by tree mortality. However, the main drivers of tropical tree death remain largely unknown. Here we present a pan-Amazonian assessment of how and why trees die, analysing over 120,000 trees representing > 3800 species from 189 long-term RAINFOR forest plots. While tree mortality rates vary greatly Amazon-wide, on average trees are as likely to die standing as they are broken or uprooted-modes of death with different ecological consequences. Species-level growth rate is the single most important predictor of tree death in Amazonia, with faster-growing species being at higher risk. Within species, however, the slowest-growing trees are at greatest risk while the effect of tree size varies across the basin. In the driest Amazonian region species-level bioclimatic distributional patterns also predict the risk of death, suggesting that these forests are experiencing climatic conditions beyond their adaptative limits. These results provide not only a holistic pan-Amazonian picture of tree death but large-scale evidence for the overarching importance of the growth-survival trade-off in driving tropical tree mortality.

Fig. 1. Tree mortality rates and mode of death across Amazonia and adjacent lowland forests.

Circles show the mean mortality rate across the entire time series available for each plot (% year⁻¹). Pie charts show the proportion of dead trees found standing (darker shading) and broken/uprooted (paler shading). Different colours represent the four geological regions: Northern (green), East-Central (red), Western (yellow) and Southern (blue). Mortality rates per plot were calculated as the mean value across all censuses weighted by the census-interval length.

Fig. 2. Tree mortality rates in Amazonia.

a Stem mortality rates per region. b Mean proportions and 95% confidence intervals (error bars) of dead trees found standing or broken/uprooted (faded colours). c Stem mortality rates for trees that died standing. d Stem mortality rates for trees that died broken or uprooted. Different colours represent the four Amazonian geological regions: Northern (green), East-Central (red), Western (yellow) and Southern (blue). Mortality rates per plot were calculated as the mean value per plot across all censuses weighted by the census-interval length. In a, c and d, boxplots show the median, 25th and 75th quantile and whiskers represent 5th and 95th quantile or mortality rates across plots. Letters in a–d show the results from post hoc Tukey’s tests comparing the proportions and rates among the different regions. Note that in b comparisons are independent for standing and for broken/uprooted dead trees. The proportion in b and the mortality rates in c, d were calculated based on 125 plots where at least 50% of dead trees and at least 5 trees had their mode of death registered.

Fig. 3. Risk factors of Amazon tree death.

Cox proportional model outputs for the risk factors associated with the tree-level characteristics: a stem diameter size and b relative stem growth rates; and for species traits: c maximum stem diameter size (max D), d mean stem diameter growth rate, e wood density and f drought tolerance represented as water-deficit affiliation, WDA. The WDA values were obtained from a previous study, calculated as the mean of maximum cumulative water-deficit (mm year⁻¹) where the species occurred weighted by its abundance. More negative values indicate that the species occur under drier conditions, and had greater survival in drought experiments. Inserts show the coefficients and respective 95% confidence intervals for each variable in every region. Black lines show the models for the entire basin and different colours represent the four Amazonian geological regions: Northern (green), East-Central (red), Western (yellow) and Southern (blue). Shaded area represents the standard error for each coefficient and dotted lines represent non-significant risk factors. Note that for visualisation purposes, we restricted the figure to the 95th quantile of the distribution of each variable.