Forest response to increased disturbance in the Central Amazon and comparison to Western Amazonian forests

Abstract:

Uncertainties surrounding vegetation response to increased disturbance rates associated with climate change remains a major global change issue for Amazon forests. Additionally, turnover rates in the Western Amazon are doubled compared to the Central Amazon, and notable gradients currently exist in specific wood density and aboveground biomass (AGB). This study investigates the extent to which the variation in disturbance regimes contributes to these regional gradients. To address these issues, we evaluated disturbance-recovery processes under scenarios of increased disturbance rates in a Central Amazon forest using first ZELIG-TROP, a dynamic vegetation gap model which we calibrated using long-term inventory data, and second using the Community Land Model (CLM), a global land surface model. Upon doubling the mortality rate in the Central Amazon to mirror the disturbance regime in the Western Amazon of ~2% mortality, the two regions continued to differ in multiple forest processes. With the inclusion of elevated natural disturbances, at steady-state, AGB significantly decreased by 41.9% with no significant difference between modeled AGB and empirical AGB from the western Amazon datasets (104 vs. 107 Mg C ha^-1). However, different processes were responsible for the reductions in AGB between the models and empirical dataset. The empirical dataset suggests that a decrease in wood density drives the reduction in AGB. While decreased stand basal area was the driver of AGB loss in ZELIG-TROP, and decreased leaf area index (LAI) was the driver in CLM, two forest attributes that do not significantly vary across the Amazon Basin. Further comparisons found that stem density, specific wood density, and growth rates differed between the two Amazonian regions. This suggests that: 1) the variability between regions cannot be entirely explained by the variability in disturbance regime, but rather potentially sensitive to intrinsic environmental factors; or 2) the models are not accurately simulating all forest characteristics in response to increased disturbances. Next we evaluated the fidelity of elevated tree mortality in CLM. Similar to ZELIG-TROP, CLM predicted a net carbon loss of 49.9%, getting the correct answer for the wrong reason, and the temporal variability in carbon stock and fluxes was not replicated in CLM.