Engineering topics

Needham, Jessica F.

Publications and source records attributed to Needham, Jessica F..

4 records

DOE OSTI2022

Tree crown damage and its effects on forest carbon cycling in a tropical forest

Abstract Crown damage can account for over 23% of canopy biomass turnover in tropical forests and is a strong predictor of tree mortality; yet, it is not typically represented in vegetation models. We incorporate crown damage into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to evaluate how lags between damage and tree recovery or death alter demographic rates and patterns of carbon turnover. We represent crown damage as a reduction in a tree's crown area and leaf and branch biomass, and allow associated variation in the ratio of aboveground to belowground plant tissue. We compare simulations with crown damage to simulations with equivalent instant increases in mortality and benchmark results against data from Barro Colorado Island (BCI), Panama. In FATES, crown damage causes decreases in growth rates that match observations from BCI. Crown damage leads to increases in carbon starvation mortality in FATES, but only in configurations with high root respiration and decreases in carbon storage following damage. Crown damage also alters competitive dynamics, as plant functional types that can recover from crown damage outcompete those that cannot. This is a first exploration of the trade‐off between the additional complexity of the novel crown damage module and improved predictive capabilities. At BCI, a tropical forest that does not experience high levels of disturbance, both the crown damage simulations and simulations with equivalent increases in mortality does a reasonable job of capturing observations. The crown damage module provides functionality for exploring dynamics in forests with more extreme disturbances such as cyclones and for capturing the synergistic effects of disturbances that overlap in space and time.

Needham, Jessica F.↗

DOE OSTI2022

Demographic composition, not demographic diversity, predicts biomass and turnover across temperate and tropical forests

The growth and survival of individual trees determine the physical structure of a forest with important consequences for forest function. However, given the diversity of tree species and forest biomes, quantifying the multitude of demographic strategies within and across forests and the way that they translate into forest structure and function remains a significant challenge. Here, we quantify the demographic rates of 1961 tree species from temperate and tropical forests and evaluate how demographic diversity (DD) and demographic composition (DC) differ across forests, and how these differences in demography relate to species richness, aboveground biomass (AGB), and carbon residence time. We find wide variation in DD and DC across forest plots, patterns that are not explained by species richness or climate variables alone. There is no evidence that DD has an effect on either AGB or carbon residence time. Rather, the DC of forests, specifically the relative abundance of large statured species, predicted both biomass and carbon residence time. Our results demonstrate the distinct DCs of globally distributed forests, reflecting biogeography, recent history, and current plot conditions. Linking the DC of forests to resilience or vulnerability to climate change, will improve the precision and accuracy of predictions of future forest composition, structure, and function.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Forest responses to simulated elevated CO 2 under alternate hypotheses of size- and age-dependent mortality

Elevated atmospheric carbon dioxide (eCO 2 ) is predicted to increase growth rates of forest trees. The extent to which increased growth translates to changes in biomass is dependent on the turnover time of the carbon, and thus tree mortality rates. Size- or age-dependent mortality combined with increased growth rates could result in either decreased carbon turnover from a speeding up of tree life cycles, or increased biomass from trees reaching larger sizes, respectively. However, most vegetation models currently lack any representation of size- or age-dependent mortality and the effect of eCO 2 on changes in biomass and carbon turnover times is thus a major source of uncertainty in predictions of future vegetation dynamics. Using a reduced-complexity form of the vegetation demographic model the Functionally Assembled Terrestrial Ecosystem Simulator to simulate an idealised tropical forest, we find increases in biomass despite reductions in carbon turnover time in both size- and age-dependent mortality scenarios in response to a hypothetical eCO 2 -driven 25% increase in woody net primary productivity (wNPP). Carbon turnover times decreased by 9.6% in size-dependent mortality scenarios due to a speeding up of tree life cycles, but also by 2.0% when mortality was age-dependent, as larger crowns led to increased light competition. Increases in aboveground biomass (AGB) were much larger when mortality was age-dependent (24.3%) compared with size-dependent (13.4%) as trees reached larger sizes before death. In simulations with a constant background mortality rate, carbon turnover time decreased by 2.1% and AGB increased by 24.0%, however, absolute values of AGB and carbon turnover were higher than in either size- or age-dependent mortality scenario. The extent to which AGB increases and carbon turnover decreases will thus depend on the mechanisms of large tree mortality: if increased size itself results in elevated mortality rates, then this could reduce by about half the increase in AGB relative to the increase in wNPP.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama

Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While single-PFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early- and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs.

54 ENVIRONMENTAL SCIENCES↗