Abstract
Abstract. 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.
Highlights
Climate-change-related feedbacks from the terrestrial biosphere are an important and highly uncertain component of global change (Friedlingstein et al, 2013; Gregory et al, 2009)
We conduct an ensemble of single-plant functional types (PFTs) simulations to generate a set of possible forests, each of which is comprised of trees sharing a single set of traits
The joint distribution of gross primary productivity (GPP) and leaf area index (LAI) (Fig. 5a) shows that the overall ensemble spread is roughly centered around the observed values, though with wide spread and a tail that extends to low-productivity, lowLAI simulations
Summary
Climate-change-related feedbacks from the terrestrial biosphere are an important and highly uncertain component of global change (Friedlingstein et al, 2013; Gregory et al, 2009). Most ESMs use prescribed vegetation distributions, and/or do not represent the functional diversity that exists within tropical forests, and/or impose static vegetation turnover times. Each of these assumptions may substantially bias model results. Assuming all tropical forests are comprised of a single set of plant traits may lead to overly abrupt changes in response to an imposed forcing, as compared to approaches that allow community-wide shifts in the trait composition of forests (Levine et al, 2016; Powell et al, 2018; Sakschewski et al, 2016). Assuming fixed turnover times for vegetation may bias the responses to both elevated CO2 and climate change, as doing so does not permit changes to mortality rates that may result from changes to climate and resource competition (Friend et al, 2014; Koven et al, 2015; McDowell et al, 2018; Powell et al, 2013; Walker et al, 2015), which may be already underway in tropical forests (Brienen et al, 2015)
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