What is the fate of a Central Amazon forest under increased disturbance regimes and how does it compare to Western Amazon forests?

Background/Question/Methods:

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 basin are doubled when compared to the Central Amazon, and notable gradients currently exist in specific wood density and aboveground biomass (AGB) between the regions. We would like to understand the extent to which the variation in disturbance regimes contributes to these variations between the two regions. To address these issues, we evaluated disturbance-recovery processes under two scenarios of increased disturbance rates in a complex Central Amazon forest using ZELIG-TROP, a dynamic vegetation gap model, which we parameterized and calibrated using long-term inventory data. Last, to help quantify the impacts of increased disturbances on climate and the earth system, we evaluated the fidelity of tree mortality and disturbance in a global land surface model (the Community Land Model, CLM).

Results/Conclusions:

For a 100% increase in annual mortality rate [i.e. high disturbance treatment] both ZELIG-TROP and CLM were in close agreement with each other and predicted a net carbon loss of 41.9% and 49.9%, respectively, with an insignificant effect on aboveground net primary productivity (ANPP). A 20% increase in mortality every 50 years [i.e. periodic disturbance treatment] resulted in a reciprocal biomass loss of 18.3% and 18.7% in ZELIG-TROP and CLM respectively. When comparing the Central Amazon under a similar disturbance regime to the Western Amazon (~2% mortality), at steady-state, there was no significant difference between modeled AGB (104 Mg C ha^-1) and empirical AGB from the western Amazon datasets (107 Mg C ha^-1), consistent with carbon loss associated with higher turnover. However, different processes were responsible for the reductions in AGB between the models and empirical datasets. We observed that increased turnover in wood density drives the reduction in AGB in empirical datasets. However, stand basal area was the driver of the drop in AGB in ZELIG-TROP, and leaf area index (LAI) was the driver in CLM. Further comparisons found that stem density, specific wood density, and basal area 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; 2) the models are not accurately simulating all forest characteristics in response to increased disturbances; and 3) wood density should be included in AGB allometric equations.