Capturing functional strategies and compositional dynamics in vegetation demographic models

Abstract. Plant community composition influences carbon, water, and
energy fluxes at regional to global scales. Vegetation demographic models
(VDMs) allow investigation of the effects of changing climate and
disturbance regimes on vegetation composition and fluxes. Such investigation
requires that the models can accurately resolve these feedbacks to simulate
realistic composition. Vegetation in VDMs is composed of plant functional
types (PFTs), which are specified according to plant traits. Defining PFTs
is challenging due to large variability in trait observations within and
between plant types and a lack of understanding of model sensitivity to
these traits. Here we present an approach for developing PFT
parameterizations that are connected to the underlying ecological processes
determining forest composition in the mixed-conifer forest of the Sierra
Nevada of California, USA. We constrain multiple relative trait
values between PFTs, as opposed to randomly sampling within the range of
observations. An ensemble of PFT parameterizations are then filtered based
on emergent forest properties meeting observation-based ecological criteria
under alternate disturbance scenarios. A small ensemble of alternate PFT
parameterizations is identified that produces plausible forest composition
and demonstrates variability in response to disturbance frequency and
regional environmental variation. Retaining multiple PFT parameterizations
allows us to quantify the uncertainty in forest responses due to variability
in trait observations. Vegetation composition is a key emergent outcome from
VDMs and our methodology provides a foundation for robust PFT
parameterization across ecosystems.


effect on the light environment and direct mortality; and 3) forest composition is sensitive to variation in water availability, with 70 less pine in areas with low water availability compared with greater water availability.

Modeling Framework
FATES was developed through integration of the Ecosystem Demography (ED) model Moorcroft et al., 2001) with the Community Land Model (Oleson et al., 2013), with initial testing focused in Eastern U.S. forests (Fisher et al., 75 2015) and Panama tropical forest (Koven et al., 2020;Massoud et al., 2019). FATES resolves vegetation demographics at the level of the cohort, which represents the density of individuals of a given PFT, size, and canopy position. PFTs are defined by functional traits that describe plant physiology (e.g., photosynthesis, respiration, carbon allocation and turnover) and sensitivity to disturbance and environmental variation. Patches can contain multiple cohorts of plants and patch age is tracked according to time since last disturbance. The number of patches and cohorts is dynamic during a simulation. Allocation of carbon to 80 reproduction creates new cohorts within a patch. Disturbances caused by tree mortality, fire or harvest splits existing patches to create a new patch. Growth rates for each cohort are determined by carbon assimilation and allocation, which are affected by light and water availability and climate. Mortality is based on fire, carbon starvation, hydraulic failure, and cold-stress, along with a background mortality rate representing mortality sources not yet incorporated into the model. FATES computes physiological processes on half-hourly time-steps, and growth, mortality, regeneration, and disturbance on daily time-steps. Here 85 we have coupled FATES to the Community Land Model version 5 (Lawrence et al., 2019), which allows for a dynamic relationship between soil water availability and evapotranspiration that is governed by PFT water stress tolerance and soil physical properties. A full description of physiological and demographic processes in FATES can be found in Fisher et al. (2015), Koven et al. (2020) and the FATES Technical Note online at 10.5281/zenodo.3517271.
The simulation of wildfire in FATES is adapted from SPITFIRE, a forest fire behavior and effects model meant for use 90 at regional to global scales (Thonicke et al. 2010). As implemented in FATES, fires are initiated based on a lightning ignitions dataset (Li et al., 2013) and once ignited are modulated for climate control with the Nesterov fire danger index. Fire behaviors, including rate of spread, duration, and intensity, depend on six classes of ground fuels and their moisture status. Scorch height is estimated for each cohort of trees, determining crown damage. Cambial damage, which is modulated by traits such as bark thickness, canopy damage and cambial heating determine the probability of tree mortality. The amount of biomass consumed is 95 calculated based on fire intensity and rate of spread.

Study Area and Forest Type
We simulated the two dominant conifer genera in California's mixed conifer forest: pine and incense cedar. The pine species in this forest, including ponderosa (Pinus ponderosa), Jeffrey (Pinus jeffreyii) and sugar (Pinus lambertiana) pine, are shade intolerant and highly resistant to fire (North et al., 2016). Incense cedar (Calocedrus decurrens) is more shade-and drought-100 tolerant, but less fire-resistant (North et al., 2016). Surface fires, and the creation of microclimates suitable for pine regeneration are thought to be important for promoting pine dominance in the Sierra Nevada ( Van de Water and Safford, 2011;Yeaton, 1983).
We conducted a parameter sensitivity analysis and developed PFT parameterizations with FATES simulations at the Soaproot Saddle flux tower site (O'Geen et al., 2018). We evaluated simulated forest composition, model biases, and https://doi.org/10.5194/bg-2021-54 Preprint. Discussion started: 23 March 2021 c Author(s) 2021. CC BY 4.0 License. environmental controls on coexistence across a regional domain that is dominated by the combination of pine (ponderosa, 105 Jeffrey, and sugar) and incense cedar according to data produced by the Landscape Ecology, Modeling and Mapping Analysis (LEMMA) project (Ohmann et al., 2011) (Figure 1).

Trait Data
We compiled a database of trait observations by tree species, starting with the TRY database (Kattge et al., 2011) and supplementing with data from additional literature where necessary (included in data archive https://doi.org/10.6078/D15M5X).
To limit variability in trait values resulting from diverse geographic locations, we focused our literature search on California, and 120 72% of the collected pine and cedar trait observations came from studies conducted in the Sierra Nevada Mountains. The remaining observations were from elsewhere in the Western US. We queried existing databases for allometric observations (Jenkins et al., 2004;Chojnacky et al., 2014;Falster et al., 2015).

Experimental Design and Analysis
Our approach combines of observations of plant traits and changes in forest composition under different disturbance scenarios 125 with ensembles of model simulations to select robust parameterizations ( Figure 1). After an initial parameter sensitivity analysis, we filter an ensemble of potential PFT parameterizations based on ecological criteria at a single site. We then evaluate simulated forest composition in the ensemble of retained parameterizations across a regional domain and explore model biases and environmental controls on composition and PFT-specific vital rates to suggest avenues for improving simulated forest composition. 130 All FATES simulations were forced with 4x4 km spatial resolution daily climate data from 1979(Abatzoglou, 2013 disaggregated to 3-hourly intervals (Rupp and Buotte, 2020). Soil texture and organic carbon content were taken from the best available soils data for our domain, as described in Buotte et al. (2018), and, due to a lack of adequate spatially resolved soil data and no representation of root access to regolith water sources in FATES, soil depth was set to 10 m for all grid cells (O'Geen et al., 2018;Klos et al., 2018). 135 Because FATES had not been previously exercised in the temperate mixed conifer forest, we assessed the sensitivity of simulated coexistence to 46 PFT trait and model parameters (Table S1). We defined two hypothetical PFTs, with trait values (Table S1) drawn from distributions of trait observations of all conifer species present at the flux tower site (SI trait database), to create a 720-member ensemble of FATES parameterizations. We randomly sampled the parameter space based on Latin Hypercube sampling. We first divided each parameter range into intervals with equal probability and randomly sampled values 140 from these intervals. We then ordered the sampled parameter values to maintain specified rank correlation among different parameters (Xu and Gertner, 2008). Some parameters, such as the target carbon allocated to storage reserves, are not observable; others are observable but regionally specific data are scarce or non-existent. For such parameters, ranges were determined based on previous sensitivity studies (Fisher et al., 2015;Koven et al., 2020;Massoud et al., 2019). We started these simulations from bare ground and ran the ensemble for 100 years with fire active, recycling the 1979-2009 climate forcing. 145 https://doi.org/10.5194/bg-2021-54 Preprint. Discussion started: 23 March 2021 c Author(s) 2021. CC BY 4.0 License.
We quantified composition as the ratio of the basal area of PFT #1 to the total basal area. This ratio therefore varies between 0, indicating complete PFT #2 dominance, to 1, indicating complete PFT #1 dominance. We used univariate, non-linear generalized additive models to quantify the variance in composition explained by the differences between PFT #1 and PFT #2 parameter values. Because each parameter is varied over its full range of realistic values, variable importance as measured by R 2 (coefficient of determination, or variance explained) is also a measure of parameter sensitivity. 150 Next, we created an ensemble of parameterizations for a shade-intolerant, fire-resistant pine and a shade-tolerant, drought-tolerant, less fire-resistant incense cedar (Table S1). The parameter sensitivity results, along with the availability of observations, informed our decision of which trait parameters to vary. We varied eight trait parameters to capture the differences in these two ecological strategies. We represented plant response to the light environment with four trait parameters: the specific leaf area at the top of the canopy (SLA top), the maximum possible specific leaf area (SLA max), the maximum rate of 155 carboxylation (Vc max), and leaf nitrogen (leaf N), which affects leaf respiration in FATES. The soil matric potential at which stomata close (SMPSC) controlled drought tolerance, and bark thickness (bark) controlled fire resistance. We varied two additional trait parameters, leaf lifespan (leaf life) and wood density (wood den), that differ between these two strategies (Niinemets, 2010;Kozlowski and Pallardy, 1997) but are not easily tied to light availability, water availability, or fire resistance in FATES. 160 We constrained the eight trait parameter values to the distributions of observations of pine and incense cedar (Table S1), as opposed to the full range of conifer trait values as in the 720-member ensemble used in the parameter sensitivity analysis. All other trait parameters were held constant between the two PFTs as the mean of the combined pine and cedar observations. Although some of these trait parameters were found to be influential (e.g. allometric parameters), observations were insufficient to distinguish between pine and incense cedar. Non-trait model parameters were set based on previous research with FATES 165 (Table S1). Following the same sampling methods that maintain rank correlation between trait parameters as above, we created a 360-member ensemble of PFT parameterizations. We ran this ensemble for 100 years for a total of four scenarios: from bare ground and from initialized stands, with fire both active and inactive. Initialized stands began with an even proportion of pine and cedar, with the size structure based on census data from the flux tower site (included in data archive https://doi.org/10.6078/D15M5X). 170 Observations allow us to devise ecological criteria, or expectations, for how the composition of trees with these two ecological strategies should respond to disturbance. To ensure the PFT definitions represented the intended ecological strategies, we filtered the ensemble of parameterizations based on eight criteria. In the mixed conifer forest of the Sierra Nevada, pine dominates when fire is present on the landscape (North et al., 2016), and incense cedar increases in dominance when fire is excluded (Dolanc et al., 2014a;Dolanc et al., 2014b). From these observations we created six criteria based on pine and incense 175 cedar basal area according to initial conditions and the presence of fire (Table 1). We included two criteria based on observations of leaf area index and carbon use efficiency (Table 1). We filtered the 360-member ensemble and retained ensemble members that met all eight criteria. Shade-tolerant trees tend to have lower maximum rate of carboxylation (Vc max), lower dark respiration rates, higher 185 specific leaf area (SLA), and longer leaf lifespan than shade-intolerant trees (Kozlowski and Pallardy, 1997;Niinemets, 2010).
However, filtering the 360-member ensemble retained only one parameterization that preserved these relative trait parameter values for pine and incense cedar.
We therefore created a 72-member ensemble of pine and incense cedar parameterizations using the same eight trait parameters varied in the 360-member ensemble, but further constrained to enforce the appropriate relative differences between 190 these functional types (Table S1, Figure 1). Parameter values were drawn from pine and incense cedar trait observation distributions that were centered on the filtered parameterization from the 360-member ensemble, spanned one standard deviation of the mean, maintained between-trait correlations, and retained the appropriate relative differences between pine and incense cedar traits. This ensemble was run for 100 years for each of the four scenarios of initial stand conditions and fire at the flux tower site. The results were filtered based on the eight criteria in Table 1 to identify the pine and incense cedar 195 parameterizations most consistent with the eight expected ecological outcomes. This filtering retained four plausible parameterizations.
To evaluate performance of these parameterizations across a wide range of environmental conditions, we ran the four plausible parameterizations across our regional domain from bare ground with fire on, for 100 years. We compared the simulated ratio of pine basal area to total basal area (hereafter referred to as pine fraction) with the LEMMA data (Ohmann et al., 200 2011), and evaluated area burned with data from the Monitoring Trends in Burn Severity (MTBS) data (Eldenshenk et al., 2007).
We classified each FATES grid cell as having a reasonable pine fraction if it was within one standard deviation of the mean of the 30m LEMMA grid cells encompassed by the FATES grid cell. We compared simulated and observed annual area burned over the domain with probability density functions and boxplots of each distribution.
We evaluated model biases as the binary correct/not correct response as a multivariate, non-linear function of average 205 annual temperature, total annual precipitation, and simulated annual area burned. Climate variables were averaged over the range of climate forcing data, 1979-2009, for each 4-km grid cell. We evaluated the environmental controls on simulated forest composition across the mixed conifer forest type in the Sierra Nevada. We statistically modeled the pine fraction as a multivariate, non-linear function of annual precipitation, average annual temperature, and soil characteristics (percent sand, clay, https://doi.org/10.5194/bg-2021-54 Preprint. Discussion started: 23 March 2021 c Author(s) 2021. CC BY 4.0 License. and organic carbon). All statistical analyses were performed using the mgcv package (Wood, 2011) in R version 3.6.2 (R Core 210 Team, 2019).

Sensitivity of PFT Composition to Trait and Model Parameters
Coexistence between two hypothetical conifer PFTs was most influenced by trait parameters controlling gross primary productivity and carbon allocation, as controlled in part by allometry ( Figure S1). Allometric parameters, and wood density, set 215 the growth rates of stem diameter and thus tree height growth per unit of biomass gained. Non-trait model parameters controlling the creation of new patches from tree-fall (Disturb Frac), and height sorting to determine canopy position (Comp Excln) were among the least important ( Figure S1). We used these sensitivity results to focus further analysis on the influential trait parameters that distinguish pine and cedar strategies, and ensure we held sensitive but observationally unconstrained parameters constant between the two PFTs. 220

Constraining Potential Pine and Incense Cedar PFT Parameterizations
Only one of the 360 ensemble members had the appropriate relative differences in pine and incense cedar trait values and met all eight ecological criteria. This single ensemble member was used as the center point for generating the 72-member ensemble in which the relative trait parameter values for pine and incense cedar were additionally constrained according to the ecological strategies represented by each PFT (Figure 2). When between-PFT constraints were not enforced in sampling the observations, 225 many ensemble members (grey points in Figure 2) fell outside of the range of relative trait values that represent these two ecological strategies.  Table 2 are shown in colors.
Filtering the 72-member ensemble based on ecological criteria with and without fire was critical for selecting parameterizations that yielded the correct pine fraction under alternate fire regimes (Figure 3). While many ensemble members (parameterizations) met individual ecological criteria, four members met all criteria regarding the effects of fire ( Figure 3) and 235 also were within the range of observed leaf area index and carbon use efficiency (not shown). After continuing simulations with these four parameterizations for another 100 years, all four still met the ecological criteria. Because these parameterizations span a range of observed pine and cedar trait values (Figure 2), they show differences in the magnitude of the effect of fire on the pine fraction ( Figure 4). All four parameterizations show a decrease in pine fraction when fire is excluded (Figure 4), and all four have the appropriate relative trait values (Figure 2). Retaining multiple, plausible PFT definitions allows us to quantify the 240 uncertainty in simulated outcomes due to variability in trait observations. For example, when starting from even stands of pine and incense cedar, variability in observed traits leads to a 26-84% decline in the total pine fraction when fire is inactive ( Figure   4). Taking canopy position into account, variability in observed traits leads to a 24-102% increase in the fraction of incense cedar in the canopy and 56-178% increase in the understory when fire is inactive (Figure 4).

Evaluation of Regional Forest Composition
When we applied the 4-member ensemble of PFT parameterizations across the Sierra Nevada mixed-conifer domain, 79% of all 255 grid cells were classified as having the correct (within one standard deviation of observed) ratio of pine to total basal area in all four simulations ( Figure 5). In each simulation, over 85% of the incorrect grid cells under-represented pine basal area. Annual area burned and fire size were similar to observations, although FATES lacked representation of very large fires ( Figure S2).
Regression analyses indicated that all four parameterizations underestimated the pine fraction where precipitation was the lowest

Environmental Controls on Forest Composition
Regional variation in forest composition was most sensitive to precipitation (Figure 7a expectations. Forest composition was less sensitive to soil characteristics, but cedar tended to dominate on soils with higher sand and clay content, and pine on soils with higher organic matter content (Figure 8b-d).   Forest composition was sensitive to differences between pine and incense cedar vital rates (Figure 7b). PFT-differences in growth rates could be offset by opposite PFT-differences in mortality rates to prevent pine or incense cedar from excluding the other, and the degree of compensation possible varied among the four parameterizations ( Figure 9). When pine growth rates 290 were moderately faster than incense cedar, higher pine mortality rates allowed incense cedar to persist in the canopy and understory (Figure 9). Differences among trait values in the four parameterizations ( Figure 2) allowed for varying degrees of compensation between growth and mortality rates (Figure 9). PFT-differences in growth rates were sensitive to precipitation and temperature ( Figure S3). Pine growth rates were faster than incense cedar growth rates in wetter and cooler areas ( Figure S4).
Incense cedar growth rates were faster than pine growth rates in the driest areas, regardless of temperature ( Figure S4). 295  Fire was the primary source of mortality across the mixed conifer forest domain in all four simulations ( Figure S5). 300 However, PFT-differences in fire mortality rates were less than PFT-differences in carbon starvation mortality rates (Figure 10), leading to PFT-differences in fire mortality rates having less influence on regional forest composition than PFT-differences in carbon starvation mortality rates (Figure 7b). Fire-caused mortality rates were similar between small pine and incense cedar trees, but higher for incense cedar among larger trees ( Figure 10a). Pine had higher carbon starvation mortality rates across all size classes (Figure 10b). PFT-differences in carbon starvation mortality rates were sensitive to climate ( Figure S3), with a sharp 305 increase in pine mortality at the lowest precipitation levels ( Figure S6), where pine growth rates were much lower than incense cedar ( Figure S4). PFT-differences in fire-caused mortality rates were less sensitive to climate ( Figure S3).

Approach for Defining PFTs
Creating PFT definitions that accurately resolve community composition is essential for simulating the Earth System 315 (Wullschleger et al., 2014). We developed and applied a novel approach for assuring PFT definitions have high fidelity to the emergent properties of their intended ecological strategies. First we extended the common practice of sampling trait parameter observations based on observed correlations among traits within a PFT (Lebauer et al., 2013) by incorporating between-PFT parameter constraints. Secondly, we introduced an ensemble filtering process based on expected compositional changes in response to alternate initial condition and disturbance scenarios, and the emergent properties of leaf area index and carbon use 320 efficiency. Finally, we evaluated the robustness of the resulting plausible PFT definitions across a wide range of environmental conditions, comparing simulations to observationally-constrained forest composition (Ohmann et al., 2011). Several methods for parameter estimation are commonly employed, including Bayesian (Lebauer et al., 2013), maximum likelihood iteration (Hudiburg et al., 2009). However, these methods do not ensure that simulated composition, even when accurate, is a result of the mechanisms that drive composition (Williams et al., 2009). 325 Employing between-PFT parameter constraints and filtering simulations by process outcomes connects the PFT definitions to the processes that drive community composition. In the mixed conifer forest of the Sierra Nevada, pine dominates when fire is present on the landscape (North et al., 2016), and incense cedar increases in dominance when fire is excluded (Dolanc et al., 2014a;Dolanc et al., 2014b). This knowledge allows us to create eight criteria based on pine and incense cedar basal area according to initial conditions and the presence of fire (Table 1). We found many PFT parameterizations that met one of these 330 criteria. However, fewer parameterizations met all eight criteria. Further filtering based on ecophysiological constraints (here, carbon use efficiency) and emergent properties (here, leaf area index) provide additional connections to field-based understanding of how the ecological strategies we are representing interact to determine community composition.
Our understanding of the importance of constraining between-PFT parameter values emerged during the course of our analysis. Even though the trait parameter values in the 360-member ensemble were drawn from observations subject to observed 335 within-PFT trait correlations, filtering retained only one parameterization with the appropriate relative pine and incense cedar values across all eight trait parameters. In contrast, filtering the 72-member ensemble, in which between-PFT constraints were applied, resulted in four plausible parameterizations and allowed us to quantify uncertainty in simulated forest composition due to variability in trait observations. A greater proportion of the potential parameters were retained in the 72-member ensemble because the between-PFT trait constraints ensured pine would respond to the environment as the less shade-tolerant, less 340 drought-resistant, and more fire-resistant PFT as compared to incense cedar. Including between-PFT trait constraints ensures that the PFT responses to environmental conditions are in accordance with the ecological strategies the PFTs represent. The process would be more efficient if between-PFT constraints were enforced before filtering an ensemble, as depicted by the center box with heavy outline in Figure 1.
We developed a set of plausible PFT parameterizations at a single site, and then applied those parameterizations across 345 a regional domain with variability in climate. Starting with FATES simulations at a single site allowed us to reduce the computational cost of simulating hundreds of potential parameterizations. Evaluating the retained parameterizations across the regional domain allowed us to use model biases to determine if the retained parameterizations were robust across temperature and precipitation gradients, and devise options for improving model performance.
Our approach could be easily applied in other ecosystems, with ecological expectations and scenarios developed in 350 accordance with the accumulated knowledge of the controls on community composition. We suggest conducting an initial parameter sensitivity analysis to ensure influential parameters can either be estimated based on observations or held constant. In our 720-member ensemble, trait parameters were bounded by observations of all conifer species present at the site, ensuring trait parameters spanned a broad range, and thus limiting the potential for missing influential parameters due to a lack of variability.
However, a sensitivity analysis could be run on the ensemble created by sampling with inter-trait and inter-PFT constraints 355 instead.
Coupling VDMs to Earth System Models is providing new opportunities for global change research , and defining global PFTs is a critical component of this integration. Current vegetation distributions are the result of particular sequences of climate, disturbances, and dispersal events (Jackson et al., 2009) would be an efficient means of arriving at robust global PFT definitions. First, an ensemble of potential PFT definitions would be created, maintaining the appropriate inter-trait and inter-PFT correlations. Next, sites could be selected to represent conditions with known coexistence and known competitive exclusion among two or more PFTs. It may be useful to stratify sites 365 based on the limitations of temperature, radiation, and water (Nemani et al., 2003), and to capture distinct disturbance regimes.
Ecological expectations would then be developed for each site-PFT combination to filter the ensemble of potential PFT definitions. The filtered parameterizations can then be evaluated across a larger domain with gradients of climate and soils to determine if additional modifications are necessary before investing in global simulations.

Sierra Nevada Forest Composition 370
Enforcing the relative parameter constraints and filtering based on ecological criteria resulted in PFT definitions that led to realistic emergent dynamics and forest composition that met all three of our driving expectations. Given the historical occurrence of seasonal drought and frequent surface fires in the mixed conifer forest region of the Sierra Nevada Mountains (North et al., 2016), we expected that composition of tree functional types in FATES would be sensitive to parameters related to shade-tolerance, drought-tolerance, and fire-resistance. Our results described a simulated ecosystem where forest composition is 375 driven by available light and water and the presence of fire. Forest composition in FATES was sensitive to differences between the PFTs in specific leaf area, V c,max , and leaf respiration, reflecting the importance of the light environment (Kozlowski and Pallardy, 1997). We found composition was also sensitive to variation in bark thickness. Within FATES (following Thonicke et al 2010), thicker bark provides insulation against cambial damage from fire and thereby lowers tree mortality due to fire. Unlike in tropical forest, composition was not sensitive to parameters that control patch creation from small-scale disturbances (Koven 380 et al., 2020), indicating the landscape-scale disturbance from fire was more important than disturbances such as tree fall. FATES was not sensitive to differences in the parameter controlling the soil matric potential at which stomata close (SMPSC). However, differences in PFT dominance according to precipitation and soil characteristics that define the water holding capacity indicate water availability affected composition.
Simulated between-PFT differences in regional growth and mortality met our expectations of the influence of the fire 385 regime and water availability on forest composition, and increased our confidence in FATES' ability to represent the ecological dynamics in the Sierra Nevada mixed conifer forest. Our filtering process forced the expected changes in pine and cedar abundance due to fire. The emergent responses in growth and mortality, however, were not enforced yet conformed to our expectations. When fire is active in the model, tree mortality from fire should open canopy gaps, increasing light availability and favoring pine (Yeaton, 1983;North et al., 2016). Conversely, when fire is inactive, the canopy should close, reducing light 390 availability and favoring incense cedar (North et al., 2016;Dolanc et al., 2014a). The combination of increasing pine dominance with increasing area burned, and increasing pine dominance with greater differences between pine and cedar growth rates supports these expectations. Fire was the dominant source of mortality, with large incense cedars experiencing relatively greater mortality from fire than pines did. Our filtering process did not force the expected pine and cedar dominance along the precipitation gradient. Yet, our regional simulations reflect the expected drought-tolerance strategies: pine was more dominant 395 in wetter areas and pine growth rate was lower and carbon starvation mortality rate was higher than incense cedar in drier areas.
Exploration of model biases across the regional ensemble, along with analyses of the environmental controls on forest composition and between-PFT differences in vital rates revealed a deficiency in our current simulations in regards to water availability. In all four parameterizations, pine was underrepresented at the lowest precipitation levels. This could indicate that, given the range of observed variability in pine carbon allocation and drought tolerance (DeLucia et al., 2000), further delineation 400 of a dry pine PFT may be necessary to simulate this forest type across its full range in the Sierra Nevada. Another possibility is https://doi.org/10.5194/bg-2021-54 Preprint. Discussion started: 23 March 2021 c Author(s) 2021. CC BY 4.0 License. that variability in root-depth distributions, in conjunction with improved soil definitions, may be necessary. Root distributions were held constant between the pine and cedar PFTs due to a lack of observations. Recent analysis with FATES at the Soaproot Saddle site (Ding et al., in revision) indicates that increasing rooting depth yields higher pine productivity in dry conditions compared with shallow rooting depth. Alternatively, this model bias may indicate a structural deficiency in how drought stress 405 is represented. In our simulations, water stress is represented with a scaling factor that reduces potential productivity (Oleson et al., 2013). Incorporating an explicit representation of the flow of water through the soil-plant-atmosphere continuum Our domain has historically experienced a surface fire regime ( Van de Water and Safford, 2011;North et al., 2016). Our simulations represented a surface regime, with frequent, small fires in all parameterizations. However, canopy fuels are not included in the calculations of fire behavior and characteristics and observations indicate forest composition is changing in ways that may promote increases in canopy fire (Menning and Stephens, 2007). Given the important role of fire in filtering ensemble members, fire behavior algorithms should be updated to allow for the inclusion of canopy fuels. As these changes may influence 415 competitive ability, pine and incense cedar parameterizations may require further updates. Our approach provides an efficient, albeit computationally demanding, means of updating PFT definitions as new developments are incorporated into FATES.

Conclusions
Plant functional type definitions determine vegetation demographic models' ability to accurately simulate plant composition. Traditional means of parameterization, such as iteration, do not guarantee ecologically robust PFT definitions, and 420 can be extremely slow when many parameters interact to determine outcomes. Imposing between-PFT trait parameter constraints and filtering an ensemble of parameterizations based on a discrete set of criteria for outcomes under alternate disturbance or environmental scenarios ensures that PFTs are representing their intended ecological strategies. We applied this approach to define four plausible PFT parameterizations for a shade-intolerant, fire-resistant pine and a shade-intolerant, drought-tolerant, less fire-resistant incense cedar. All four parameterizations produced robust simulations of forest composition 425 across the mixed conifer forest in the Sierra Nevada Mountains. Analyses of parameter sensitivity and PFT-specific vital rates indicate FATES simulated the expected interactions among the fire regime and light and water availability in this ecosystem.
This approach could be applied in any ecosystem, or scaled up to define global PFTs. Robust resolution of community composition will allow us to use VDMs to address important questions related to future climate and management effects on forest structure, composition, and carbon storage and feedbacks within the Earth system. 430

Data Availability
Data not otherwise referenced in the text is available at https://datadryad.org/stash/dataset/doi:10.6078/D15M5X. Source code for the Community Land Model version used here is available at https://zenodo.org/badge/latestdoi/344922587 and FATES code is available at https://zenodo.org/badge/latestdoi/344935673. thereby retaining PFT parameterizations that conform to their intended ecological niches. The retained parameterizations are applied to a regional domain to evaluate model performance, model biases, and environmental controls, which can indicate potential for improvements to PFT definitions or forcing data, or representation of processes within the model. Retaining an ensemble of parameterizations allows for quantification of uncertainty in simulated outcomes due to variability in trait observations. 765  Table 2 are shown in colors. 770  . Variance in the fraction of pine basal area relative to the total basal area of pine and incense cedar that is explained by environmental variables (a), and the difference between pine and incense cedar (pine minus cedar) growth and mortality rates (b), for each of four pine and cedar parameterizations over a regional domain in the Sierra Nevada mixed conifer forest, starting from bare ground and run with fire active for 100 years. Pine fraction was calculated for the final year and rates were averaged 790 over the duration of the simulations. bare ground and run with fire active over a regional domain in the Sierra Nevada mixed conifer forest for 100 years. Each 795 simulation uses one of the four parameterizations retained after filtering the outcomes of 72 parameterizations run at a single site according to the criteria in Table 1. Figure 9. Effects of differences (pine minus cedar) in (a) canopy and (b) understory growth and mortality rates on the fraction of pine basal area to the total basal area of pine and incense cedar at the end of four simulations started from bare ground and run 800 with fire active over a regional domain in the Sierra Nevada mixed conifer forest for 100 years.