Search

Climate, species composition, and soils are thought to control carbon cycling and forest structure in Amazonian forests. Here, we add a demographics scheme (tree recruitment, growth, and mortality) to a recently developed non-demographic model—the Trait-based Forest Simulator (TFS)—to explore the roles of climate and plant traits in controlling forest productivity and structure. We compared two sites with differing climates (seasonal vs. aseasonal precipitation) and plant traits. Through an initial validation simulation, we assessed whether the model converges on observed forest properties (productivity, demographic and structural variables) using datasets of functional traits, structure, and climate to model the carbon cycle at the two sites. In a second set of simulations, we tested the relative importance of climate and plant traits for forest properties within the TFS framework using the climate from the two sites with hypothetical trait distributions representing two axes of functional variation (“fast” vs. “slow” leaf traits, and high vs. low wood density). The adapted model with demographics reproduced observed variation in gross (GPP) and net (NPP) primary production, and respiration. However, NPP and respiration at the level of plant organs (leaf, stem, and root) were poorly simulated. Mortality and recruitment rates were underestimated. The equilibrium forest structure differed from observations of stem numbers suggesting either that the forests are not currently at equilibrium or that mechanisms are missing from the model. Findings from the second set of simulations demonstrated that differences in productivity were driven by climate, rather than plant traits. Contrary to expectation, varying leaf traits had no influence on GPP. Drivers of simulated forest structure were complex, with a key role for wood density mediated by its link to tree mortality. Modeled mortality and recruitment rates were linked to plant traits alone, drought-related mortality was not accounted for. In future, model development should focus on improving allocation, mortality, organ respiration, simulation of understory trees and adding hydraulic traits. This type of model that incorporates diverse tree strategies, detailed forest structure and realistic physiology is necessary if we are to be able to simulate tropical forest responses to global change scenarios.

Fire has a historical role in tropical forests related to past climate and ancient land use spanning the Holocene; however, it is unclear from charcoal records how fire varied at different spatiotemporal scales and what sampling strategies are required to determine fire history and their effects. We evaluated fire variation in structurally intact, terra-firme Amazon forests, by intensive soil charcoal sampling from three replicate soil pits in sites in Guyana and northern and southern Peru. We used radiocarbon (14C) measurement to assess (1) locally, how the timing of fires represented in our sample varied across the surface of forest plots and with soil depth, (2) basin-wide, how the age of fires varies across climate and environmental gradients, and (3) how many samples are appropriate when applying the 14C approach to assess the date of last fire. Considering all 14C dates (n = 33), the most recent fires occurred at a similar time at each of the three sites (median ages: 728–851 cal years BP), indicating that in terms of fire disturbance at least, these forests could be considered old-growth. The number of unique fire events ranged from 1 to 4 per pit and from 4 to 6 per site. Based upon our sampling strategy, the N-Peru site—with the highest annual precipitation—had the most fire events. Median fire return intervals varied from 455 to 2,950 cal years BP among sites. Based on available dates, at least three samples (1 from the top of each of 3 pits) are required for the sampling to have a reasonable likelihood of capturing the most recent fire for forests with no history of a recent fire. The maximum fire return interval for two sites was shorter than the time since the last fire, suggesting that over the past ∼800 years these forests have undergone a longer fire-free period than the past 2,000–3,500 years. Our analysis from terra-firme forest soils helps to improve understanding of changes in fire regime, information necessary to evaluate post-fire legacies on modern vegetation and soil and to calibrate models to predict forest response to fire under climate change.