Roots are responsible for soil water uptake, yet little is known about how variation in fine-root traits relates to whole-tree water movement, particularly during periods of drought. By combining a 3-yr dataset monitoring sap flow rates with measures of fine-root biomass, length, and morphology across 10 tree species, we addressed hypotheses concerning the role of fine-root system size and morphology in determining tree responses to summer drought as well as potential changes in their relative importance under more severe droughts. Greater fine-root biomass and length did not enable trees to maintain high rates of sap flow during drought, whereas the morphological traits, specific root length and specific root area, were linked to sustained sap flow rates during drought. We found that all species, irrespective of root traits, progressively reduced their sap flow under more extreme drought conditions, although more acquisitive root morphology was still associated with smaller reductions. Our results run counter to long-standing assumptions that larger root systems are better able to access soil water and maintain photosynthetic activity during drought. Instead, we find evidence that root morphology at least partially determines the capacity for water uptake and movement as soil moisture declines.

Plant domestication studies have traditionally focused on morphological factors that are under direct selection, e.g., fruit size, overlooking the consequences of domestication on ecosystem services. We addressed this knowledge gap by documenting for first time the soil carbon (C) sequestration potential in wild relatives and domesticated cultivars of breadfruit (Artocarpus), a long-lived tree crop. We evaluated aggregate-bound and bulk organic C pools in breadfruit wild relatives and domesticates in soils that varied in nitrogen (N) and phosphorus (P) fertility with management practices (fertilizer and mulch). We determined whether C levels were linked to plant domestication, abiotic factors (N, P, pH, and texture), or biotic factors with known links to C accrual (arbuscular mycorrhizal fungi (AMF), and microbial biomass). In low N or N: P soils, increasing breadfruit domestication was associated with reductions in macroaggregate C (by 50%) and bulk C (host determinism); these shifts were associated with AMF hyphal productivity (50% lower than in wild relatives), soil N and P, and microbial biomass. With a high soil N fertility, the levels of aggregate and bulk soil C were similar between wild relatives and domesticates (plasticity). Despite the limited number of cultivars sampled (n = 10) and the different management practices among sites, our findings suggest domestication effects on ecosystem services, especially those modulated by AMF and soil N fertility. The calculated soil C stocks averaged 99.5 Mg C/ha (range 70-122 Mg C/ha), supporting the possibility of C accrual in breadfruit agroforestry.

We constructed a generalizable grassland model of within-plant carbon allocation strategies with the objective of furthering understanding of the evolutionary ecology of perenniality and illuminating possibilities for breeding high-yielding, long-lived crops in the service of regenerative agriculture. The grassland Perfect Plasticity Approximation model handles space-filling, recruitment, and carbon balance to determine the within-plant allocation of carbon given trade-offs involving perenniality. We used our model to conduct (1) a gametheoretic analysis of evolutionarily stable strategies to determine the effects of natural selection on perenniality and annual reproductive yield, and (2) analyses of physiological feasibility and sensitivity to determine the range of allocational strategies that might be achievable through breeding. Model results suggest that natural selection already maximizes annual reproductive yield in plants that have adapted to the evolutionarily stable strategy in the context of constraints of carbon allocation to foliage, roots, stems, and growth, leaving little room for yield improvement without also breeding a reduction in carbon allocation elsewhere. Breeding reductions in stem mass and root mass show promise for increasing annual reproductive yield. Further research is needed, however, to understand how reductions in root or stem mass would affect a perennial's provisioning of ecosystem services.

Quantifying nitrogen uptake rates across different forest types is critical for a range of ecological questions, including the parameterization of global climate change models. However, few measurements of forest nitrogen uptake rates are available due to the intensive labor required to collect in situ data. Here, we seek to optimize data collection efforts by identifying measurements that must be made in situ and those that can be omitted or approximated from databases. We estimated nitrogen uptake rates in 18 mature monodominant forest stands comprising 13 species of diverse taxonomy at the Morton Arboretum in Lisle, IL, USA. We measured all nitrogen concentrations, foliage allocation, and fine root biomass in situ. We estimated wood biomass increments by in situ stem diameter and stem core measurements combined with allometric equations. We estimated fine root turnover rates from database values. We analyzed similar published data from monodominant forest FACE sites. At least in monodominant forests, accurate estimates of forest nitrogen uptake rates appear to require in situ measurements of fine root productivity and are appreciably better paired with in situ measurements of foliage productivity. Generally, wood productivity and tissue nitrogen concentrations may be taken from trait databases at higher taxonomic levels. Careful sorting of foliage or fine roots to species is time consuming but has little effect on estimates of nitrogen uptake rate. By directing research efforts to critical in situ measurements only, future studies can maximize research effort to identify the drivers of varied nitrogen uptake patterns across gradients.

Earth system models (ESMs) have a limited capacity to represent plant functional diversity and shifts in trait distributions. Approaches to improving the representation of this complexity in ESMs include (i) optimality-based approaches that predict trait-environment responses and (ii) explicitly modelling coexistence and community assembly. These approaches are expected to converge only when optimality-based approaches identify competitively dominant strategies, which often differ from strategies that maximize ecosystem functioning or fitness components in monoculture. We used two models, LM3-PPA (a vegetation demographic model designed as an ESM component) and BiomeE (a computationally efficient analog for LM3-PPA), to explore how water limitation affects carbon allocation strategies of canopy trees. We compared competitive allocation strategies and those that maximize biomass or productivity in monoculture. We did not explicitly model coexistence or community assembly. Rather, we used model experiments to identify competitive and maximizing strategies in a two-dimensional trait space under different precipitation and mortality scenarios. At 10 eastern US locations, we simulated historical, wet and dry climate scenarios, novel drought and three different mortality scenarios (low, medium or high sensitivity to water deficit). For each site and scenario, we identified the competitive strategy and three maximizing strategies (maximum biomass, productivity or drought-tolerance). Root: leaf ratios tended to increase and leaf area tended to decrease with increasing water stress (increasing water limitation and its effects on mortality). However, relative to maximizing strategies, competitive strategies shifted towards greater allocation to roots and leaves with increasing water stress. Competitive overinvestments (greater allocation to roots and leaves by competitive strategies compared with maximizing strategies) were robust across different modelling contexts, including vegetation parameter sets (Acer vs. Populus), models (LM3-PPA vs. BiomeE) and uncalibrated vsersus calibrated BiomeE versions. Synthesis: The theoretical prediction that competitive and maximizing allocation strategies differ under water limitation is confirmed for a demographic model designed as an ESM component. Optimality-based trait predictions can simplify representing trait diversity in ESMs but do not always correspond to competitive outcomes. Explicitly modelling coexistence and community assembly in ESMs is challenging but is likely the most general approach to representing trait diversity. A key challenge for Earth system models is improving the representation of plant functional diversity. Experiments with vegetation demographic models show that water limitation leads to divergence between tree allocation strategies that are most competitive versus those that maximize biomass or productivity in monoculture.image

Urban forests are an essential part of adaptation and mitigation solutions for climate change. To understand the relationship between carbon storage, sequestration, and stand density in the most heavily-managed aspect of the urban forest—street trees—we modified the parameters and algorithms of a rural forest dynamics model, the perfect plasticity approximation (PPA), to reflect urban street tree conditions. The main changes in the new street tree PPA are the maintenance of a prescribed stand density via management of recruitment, the possibility of crown-roof overlap, and increased mortality rates. Using the street tree PPA, we explored overall productivity, crown allometry relative to stem diameter, and mortality rate to test each mechanism’s impact on urban street tree carbon storage and sequestration across a gradient of prescribed stand density, with the goal of finding conditions in which street tree carbon storage and sequestration are optimized. We compared the qualitative trends in storage from the street tree PPA to those found in the U.S. Forest Service’s Urban Forest Inventory Analysis data. We found that carbon storage and sequestration increase with prescribed density up to a point where carbon storage and sequestration saturate. Optimized carbon storage and sequestration result from a stand with high productivity, maximized crown allometry relative to stem diameter, and a low mortality rate. These insights can be used to inform urban street tree maintenance strategies that effectively increase carbon storage and sequestration within a given city, such as focusing afforestation campaigns on adequate areas with the lowest street tree densities.

We developed a demographic vegetation model, BiomeE, to improve the modeling of vegetation dynamics and ecosystem biogeochemical cycles in the NASA Goddard Institute of Space Studies' ModelE Earth system model. This model includes the processes of plant growth, mortality, reproduction, vegetation structural dynamics, and soil carbon and nitrogen storage and transformations. The model combines the plant physiological processes of ModelE's original vegetation model, Ent, with the plant demographic and ecosystem nitrogen processes that have been represented in the Geophysical Fluid Dynamics Laboratory's LM3-PPA. We used nine plant functional types to represent global natural vegetation functional diversity, including trees, shrubs, and grasses, and a new phenology model to simulate vegetation seasonal changes with temperature and precipitation fluctuations. Competition for light and soil resources is individual based, which makes the modeling of transient compositional dynamics and vegetation succession possible. Overall, the BiomeE model simulates, with fidelity comparable to other models, the dynamics of vegetation and soil biogeochemistry, including leaf area index, vegetation structure (e.g., height, tree density, size distribution, and crown organization), and ecosystem carbon and nitrogen storage and fluxes. This model allows ModelE to simulate transient and long-term biogeophysical and biogeochemical feedbacks between the climate system and land ecosystems. Furthermore, BiomeE also allows for the eco-evolutionary modeling of community assemblage in response to past and future climate changes with its individual-based competition and demographic processes.

Mounting evidence suggests that plant-soil feedbacks (PSF) may determine plant community structure. However, we still have a poor understanding of how predictions from short-term PSF experiments compare with outcomes of long-term field experiments involving competing plants. We conducted a reciprocal greenhouse experiment to examine how the growth of prairie grass species depended on the soil communities cultured by conspecific or heterospecific plant species in the field. The source soil came from monocultures in a long-term competition experiment (LTCE; Cedar Creek Ecosystem Science Reserve, MN, USA). Within the LTCE, six species of perennial prairie grasses were grown in monocultures or in eight pairwise competition plots for 12 years under conditions of low or high soil nitrogen availability. In six cases, one species clearly excluded the other; in two cases, the pair appeared to coexist. In year 15, we gathered soil from all 12 soil types (monocultures of six species by two nitrogen levels) and grew seedlings of all six species in each soil type for 7 weeks. Using biomass estimates from this greenhouse experiment, we predicted coexistence or competitive exclusion using pairwise PSFs, as derived by Bever and colleagues, and compared model predictions to observed outcomes within the LTCE. Pairwise PSFs among the species pairs ranged from negative, which is predicted to promote coexistence, to positive, which is predicted to promote competitive exclusion. However, these short-term PSF predictions bore no systematic resemblance to the actual outcomes of competition observed in the LTCE. Other forces may have more strongly influenced the competitive interactions or critical assumptions that underlie the PSF predictions may not have been met. Importantly, the pairwise PSF score derived by Bever et al. is only valid when the two species exhibit an internal equilibrium, corresponding to the Lotka-Volterra competition outcomes of stable coexistence and founder control. Predicting the other two scenarios, competitive exclusion by either species irrespective of initial conditions, requires measuring biomass in uncultured soil, which is methodologically challenging. Subject to several caveats that we discuss, our results call into question whether long-term competitive outcomes in the field can be predicted from the results of short-term PSF experiments.

Incorporating perennial crops into agroecosystems has been shown to mitigate soil degradation and improve soil health by enhancing soil aggregation and soil organic carbon (SOC) accrual. However, our understanding of the ability and timeframe for perennial crop systems to build soil health within the context of conversion from abandoned crop land remains limited. Here, we examined changes in soil health in the first year following the conversion of an abandoned crop field into an agroecosystem planted with various treatments, including: novel perennial grain (intermediate wheatgrass, IWG; Thinopyrum intermedium), IWG/ alfalfa biculture, forage grass, tallgrass prairie, or annual wheat. We analyzed factors considered central to the concept of mitigating soil degradation to improve soil health (soil aggregation, aggregate organic carbon (OC), bulk SOC) and their soil biological and physicochemical correlates throughout the first growing season. Comparisons between treatments showed that both annual and perennial treatments rapidly and significantly improved soil health metrics including aggregation, aggregate stability, and OC levels compared to pre-conversion conditions. Such increases were positively correlated with the abundance of arbuscular mycorrhizal fungi (AMF hyphae, root colonization), labile SOC and microbial activity. Notably, IWG/ alfalfa biculture resulted in significantly higher levels of macroaggregate OC in comparison to other treatments, including tallgrass prairie, supporting the potential of perennial grasses to contribute to soil carbon gains. Overall, the conversion of this abandoned land to an agroecosystem produced rapid and substantial increases in soil health in the first year after planting.

Plants produce an enormous diversity of secondary metabolites, but the evolutionary mechanisms that maintain this diversity are still unclear. The interaction diversity hypothesis suggests that complex chemical phenotypes are maintained because different metabolites benefit plants in different pairwise interactions with a diversity of other organisms. In this synthesis, we extend the interaction diversity hypothesis to consider that fruits, as potential hotspots of interactions with both antagonists and mutualists, are likely important incubators of phytochemical diversity. We provide a case study focused on the Neotropical shrub Piper reticulatum that demonstrates: 1) secondary metabolites in fruits have complex and cascading effects for shaping the outcome of both mutualistic and antagonistic fruit–frugivore interactions, and; 2) fruits can harbor substantially higher levels of phytochemical diversity than leaves, even though leaves have been the primary focus of plant chemical ecology research for decades. We then suggest a number of research priorities for integrating chemical ecology with fruit–frugivore interaction research and make specific, testable predictions for patterns that should emerge if fruit interaction diversity has helped shape phytochemical diversity. Testing these predictions in a range of systems will provide new insight into the mechanisms driving frugivory and seed dispersal and shape an improved, whole‐plant perspective on plant chemical trait evolution.

Understanding resource uptake as a function of fine-root mass is important for both basic ecological theory and applied biogeochemical cycling models. We measured plant population nitrogen uptake rate (PP-NUR), and, for the first time in any species, plant population water uptake rate (PP-WUR) and plant population phosphorus uptake rate (PP-PUR). We grew greenhouse microcosms of Poa pratensis in two closely related experiments ("high-nutrient microcosms" and "low-nutrient microcosms") under combination of nitrogen, water, and phosphorus limitation. We determined PP-NUR, PP-WUR, and PP-PUR and related all three to fine-root mass. In high-nutrient microcosms, PP-NUR, PP-WUR, and PP-PUR saturated with increasing fine-root mass. In low-nutrient microcosms, they showed a mix of linear (more often for PP-WUR) and independent (more often for PP-NUR and PP-PUR) relationships with fine-root mass. A complex mix of independent, linear, and saturating relationships between resource uptake rate and fine-root mass under different combinations of resource limitation prevent easy generalizations, but uptake was clearly independent of fine-root mass at larger fine-root masses.

Large-scale afforestation is regarded as an effective natural climate solution. However, afforestation-induced changes in soil organic C (SOC) are poorly quantified due to the paucity of large-scale sampling data. Here, we provide the first comprehensive assessment of the afforestation impact on SOC stocks with a pairwise comparative study of samples from 619 control-and-afforested plot pairs in northern China. We found context-dependent effects of afforestation on SOC: afforestation increases SOC density (SOCD) in C-poor soils but decreases SOCD in C-rich soils, especially in deeper soil. Thus, the fixed biomass/SOC ratio assumed in previous studies could overestimate the SOC enhancement by afforestation. By extrapolating the sampling data to the entire region, we estimate that afforestation increased SOC stocks in northern China by only 234.9 ± 9.6 TgC over the last three decades. The study highlights the importance of including pre-afforestation soil properties in models of soil carbon dynamics and carbon sink projections.

Competition is a major driver of carbon allocation to different plant tissues (e.g., wood, leaves, fine roots), and allocation, in turn, shapes vegetation structure. To improve their modeling of the terrestrial carbon cycle, many Earth system models now incorporate vegetation demographic models (VDMs) that explicitly simulate the processes of individual-based competition for light and soil resources. Here, in order to understand how these competition processes affect predictions of the terrestrial carbon cycle, we simulate forest responses to elevated atmospheric CO2 concentration [CO2] along a nitrogen availability gradient, using a VDM that allows us to compare fixed allocation strategies vs. competitively optimal allocation strategies. Our results show that competitive and fixed strategies predict opposite fractional allocation to fine roots and wood, though they predict similar changes in total net primary production (NPP) along the nitrogen gradient. The competitively optimal allocation strategy predicts decreasing fine root and increasing wood allocation with increasing nitrogen, whereas the fixed strategy predicts the opposite. Although simulated plant biomass at equilibrium increases with nitrogen due to increases in photosynthesis for both allocation strategies, the increase in biomass with nitrogen is much steeper for competitively optimal allocation due to its increased allocation to wood. The qualitatively opposite fractional allocation to fine roots and wood of the two strategies also impacts the effects of elevated [CO2] on plant biomass. Whereas the fixed allocation strategy predicts an increase in plant biomass under elevated [CO2] that is approximately independent of nitrogen availability, competition leads to higher plant biomass response to elevated [CO2] with increasing nitrogen availability. Our results indicate that the VDMs that explicitly include the effects of competition for light and soil resources on allocation may generate significantly different ecosystem-level predictions of carbon storage than those that use fixed strategies.

Understanding the effects of global change in terrestrial communities requires an understanding of how limiting resources interact with plant traits to affect productivity. Here, we focus on nitrogen and ask whether plant community nitrogen uptake rate is determined (a) by nitrogen availability alone or (b) by the product of nitrogen availability and fine-root mass. Surprisingly, this is not empirically resolved. We performed controlled microcosm experiments and reanalyzed published pot experiments and field data to determine the relationship between community-level nitrogen uptake rate, nitrogen availability, and fine-root mass for 46 unique combinations of species, nitrogen levels, and growing conditions. We found that plant community nitrogen uptake rate was unaffected by fine-root mass in 63% of cases and saturated with fine-root mass in 29% of cases (92% in total). In contrast, plant community nitrogen uptake rate was clearly affected by nitrogen availability. The results support the idea that although plants may over-proliferate fine roots for individual-level competition, it comes without an increase in community-level nitrogen uptake. The results have implications for the mechanisms included in coupled carbon-nitrogen terrestrial biosphere models (CN-TBMs) and are consistent with CN-TBMs that operate above the individual scale and omit fine-root mass in equations of nitrogen uptake rate but inconsistent with the majority of CN-TBMs, which operate above the individual scale and include fine-root mass in equations of nitrogen uptake rate. For the much smaller number of CN-TBMs that explicitly model individual-based belowground competition for nitrogen, the results suggest that the relative (not absolute) fine-root mass of competing individuals should be included in the equations that determine individual-level nitrogen uptake rates. By providing empirical data to support the assumptions used in CN-TBMs, we put their global climate change predictions on firmer ground.

Increasing anthropogenic nitrogen (N) deposition will affect the global carbon (C) cycle, although the mechanisms and magnitudes of its effects are not yet fully understood. Soil respiration (Rs) and its components (i.e., heterotrophic (Rh) and autotrophic (Ra) respiration) represent the largest flux of carbon dioxide (CO2) from terrestrial ecosystems to the atmosphere. However, the potentially interactive effect of N addition and stand age on Rs in forests remains unclear. We conducted a 7-year (2010-2016) field experiment in three differently-aged larch plantations (11-, 20-, and 45-year-old, representing sapling, intermediate, and mature stands) to investigate the effects of different N addition rates (control: no N addition; low-N addition, N20: 20 kg N ha(-1) year(-1); and high-N addition, N50: 50 kg N ha(-1) year(-1)) on Rs. We found significant seasonal variation in Rs, Rh, and Ra, with levels highest in summer and lowest in autumn. Rs correlated strongly with soil temperature and weakly with soil moisture, and Its, Rh, and Ra increased exponentially with soil temperature. The temperature sensitivity (Q(10)) of Rs was lowest in the mature stand, which suggests that it will sequester relatively more C in a warmer climate. The Q u o of Rs was higher than that of Rh, indicating that it contributed proportionally more to the total soil CO2 efflux. N addition had no significant effect on Q(10). Rs in the intermediate stand was significantly lower than Rs in the sapling and mature stands, which may be due to its lower soil temperature and poorer substrate quality. N addition decreased Rs by an average of 9%, but significant effects were only observed in the sapling and intermediate stands. The negative influence of N addition on Rs was largely dependent on soil temperature, with more negative effects observed in the summer when temperatures were higher, and attributable to a reduction in either Ra in the intermediate stand or Rh in the sapling stand. We hypothesize that N limitation in the young trees was alleviated by fertilization, which decreased C allocation to roots, whereas N addition may have exerted a more negative influence on soil microbial activity in the sapling stand. In summary, our results highlight the importance of stand age in regulating the negative effects of N addition on Rs and its components, which has implications for projecting the global C-climate feedback in the future.

Earth system models are incorporating plant trait diversity into their land components to better predict vegetation dynamics in a changing climate. However, extant plant trait distributions will not allow extrapolations to novel community assemblages in future climates, which will require a mechanistic understanding of the trade-offs that determine trait diversity. In this study, we show how physiological trade-offs involving leaf mass per unit area (LMA), leaf lifespan, leaf nitrogen, and leaf respiration may explain the distribution patterns of evergreen and deciduous trees in the temperate and boreal zones based on (1) an evolutionary analysis of a simple mathematical model and (2) simulation experiments of an individual-based dynamic vegetation model (i.e., LM3-PPA). The evolutionary analysis shows that these leaf traits set up a trade-off between carbon- and nitrogen-use efficiency at the scale of individual trees and therefore determine competitively dominant leaf strategies. As soil nitrogen availability increases, the dominant leaf strategy switches from one that is high in nitrogen-use efficiency to one that is high in carbon-use efficiency or, equivalently, from high-LMA/long-lived leaves (i.e., evergreen) to low-LMA/short-lived leaves (i.e., deciduous). In a region of intermediate soil nitrogen availability, the dominant leaf strategy may be either deciduous or evergreen depending on the initial conditions of plant trait abundance (i.e., founder controlled) due to feedbacks of leaf traits on soil nitrogen mineralization through litter quality. Simulated successional patterns by LM3-PPA from the leaf physiological trade-offs are consistent with observed successional dynamics of evergreen and deciduous forests at three sites spanning the temperate to boreal zones.

Increasing atmospheric CO2 concentrations and changing rainfall regimes are creating novel environments for plant communities around the world. The resulting changes in plant productivity and allocation among tissues will have significant impacts on forest carbon storage and the global carbon cycle, yet these effects may depend on mechanisms not included in global models. Here we focus on the role of individual-level competition for water and light in forest carbon allocation and storage across rainfall regimes. We find that the complexity of plant responses to rainfall regimes in experiments can be explained by individual-based competition for water and light within a continuously varying soil moisture environment. Further, we find that elevated CO2 leads to large amplifications of carbon storage when it alleviates competition for water by incentivizing competitive plants to divert carbon from short-lived fine roots to long-lived woody biomass. Overall, we find that plant dependence on rainfall regimes and plant responses to added CO2 are complex, but understandable. The insights developed here will serve as an important foundation as we work to predict the responses of plants to the full, multidimensional reality of climate change, which involves not only changes in rainfall and CO2 but also changes in temperature, nutrient availability, and disturbance rates, among others.

The long-term and large-scale dynamics of ecosystems are in large part determined by the performances of individual plants in competition with one another for light, water, and nutrients. Woody biomass, a pool of carbon (C) larger than 50% of atmospheric CO2, exists because of height-structured competition for light. However, most of the current Earth system models that predict climate change and C cycle feedbacks lack both a mechanistic formulation for height-structured competition for light and an explicit scaling from individual plants to the globe. In this study, we incorporate height-structured competition for light, competition for water, and explicit scaling from individuals to ecosystems into the land model version 3 (LM3) currently used in the Earth system models developed by the Geophysical Fluid Dynamics Laboratory (GFDL). The height-structured formulation is based on the perfect plasticity approximation (PPA), which has been shown to accurately scale from individual-level plant competition for light, water, and nutrients to the dynamics of whole communities. Because of the tractability of the PPA, the coupled LM3-PPA model is able to include a large number of phenomena across a range of spatial and temporal scales and still retain computational tractability, as well as close linkages to mathematically tractable forms of the model. We test a range of predictions against data from temperate broadleaved forests in the northern USA. The results show the model predictions agree with diurnal and annual C fluxes, growth rates of individual trees in the canopy and understory, tree size distributions, and species-level population dynamics during succession. We also show how the competitively optimal allocation strategy – the strategy that can competitively exclude all others – shifts as a function of the atmospheric CO2 concentration. This strategy is referred to as an evolutionarily stable strategy (ESS) in the ecological literature and is typically not the same as a productivity- or growth-maximizing strategy. Model simulations predict that C sinks caused by CO2 fertilization in forests limited by light and water will be down-regulated if allocation tracks changes in the competitive optimum. The implementation of the model in this paper is for temperate broadleaved forest trees, but the formulation of the model is general. It can be expanded to include other growth forms and physiologies simply by altering parameter values.