Modeling forest stand dynamics from optimal balances of carbon and nitrogen

Dynamically optimizing stomatal conductance for maximum turgor-driven growth over diel and seasonal cycles

Stomata have recently been theorized to have evolved strategies that maximize turgor-driven growth over plants' lifetimes, finding support through steady-state solutions in which gas exchange, carbohydrate storage and growth have all reached equilibrium. However, plants do not operate near steady state as plant responses and environmental forcings vary diurnally and seasonally. It remains unclear how gas exchange, carbohydrate storage and growth should be dynamically coordinated for stomata to maximize growth. We simulated the gas exchange, carbohydrate storage and growth that dynamically maximize growth diurnally and annually. Additionally, we test whether the growth-optimization hypothesis explains nocturnal stomatal opening, particularly through diel changes in temperature, carbohydrate storage and demand. Year-long dynamic simulations captured realistic diurnal and seasonal patterns in gas exchange as well as realistic seasonal patterns in carbohydrate storage and growth, improving upon unrealistic carbohydrate responses in steady-state simulations. Diurnal patterns of carbohydrate storage and growth in day-long simulations were hindered by faulty modelling assumptions of cyclic carbohydrate storage over an individual day and synchronization of the expansive and hardening phases of growth, respectively. The growth-optimization hypothesis cannot currently explain nocturnal stomatal opening unless employing corrective 'fitness factors' or reframing the theory in a probabilistic manner, in which stomata adopt an inaccurate statistical 'memory' of night-time temperature. The growth-optimization hypothesis suggests that diurnal and seasonal patterns of stomatal conductance are driven by a dynamic carbon-use strategy that seeks to maintain homeostasis of carbohydrate reserves.

Do stomata optimize turgor-driven growth? A new framework for integrating stomata response with whole-plant hydraulics and carbon balance

Every existing optimal stomatal model uses photosynthetic carbon assimilation as a proxy for plant evolutionary fitness. However, assimilation and growth are often decoupled, making assimilation less ideal for representing fitness when optimizing stomatal conductance to water vapor and carbon dioxide. Instead, growth should be considered a closer proxy for fitness. We hypothesize stomata have evolved to maximize turgor-driven growth, instead of assimilation, over entire plants' lifetimes, improving their abilities to compete and reproduce. We develop a stomata model that dynamically maximizes whole-stem growth following principles from turgor-driven growth models. Stomata open to assimilate carbohydrates that supply growth and osmotically generate turgor, while stomata close to prevent losses of turgor and growth due to negative water potentials. In steady state, the growth optimization model captures realistic stomatal, growth, and carbohydrate responses to environmental cues, reconciles conflicting interpretations within existing stomatal optimization theories, and explains patterns of carbohydrate storage and xylem conductance observed during and after drought. Our growth optimization hypothesis introduces a new paradigm for stomatal optimization models, elevates the role of whole-plant carbon use and carbon storage in stomatal functioning, and has the potential to simultaneously predict gross productivity, net productivity, and plant mortality through a single, consistent modeling framework.

Integrating terrestrial laser scanning with functional-structural plant models to investigate ecological and evolutionary processes of forest communities

BACKGROUND

Woody plants (trees and shrubs) play an important role in terrestrial ecosystems, but their size and longevity make them difficult subjects for traditional experiments. In the last 20 years functional-structural plant models (FSPMs) have evolved: they consider the interplay between plant modular structure, the immediate environment and internal functioning. However, computational constraints and data deficiency have long been limiting factors in a broader application of FSPMs, particularly at the scale of forest communities. Recently, terrestrial laser scanning (TLS), has emerged as an invaluable tool for capturing the 3-D structure of forest communities, thus opening up exciting opportunities to explore and predict forest dynamics with FSPMs.

SCOPE

The potential synergies between TLS-derived data and FSPMs have yet to be fully explored. Here, we summarize recent developments in FSPM and TLS research, with a specific focus on woody plants. We then evaluate the emerging opportunities for applying FSPMs in an ecological and evolutionary context, in light of TLS-derived data, with particular consideration of the challenges posed by scaling up from individual trees to whole forests. Finally, we propose guidelines for incorporating TLS data into the FSPM workflow to encourage overlap of practice amongst researchers.

CONCLUSIONS

We conclude that TLS is a feasible tool to help shift FSPMs from an individual-level modelling technique to a community-level one. The ability to scan multiple trees, of multiple species, in a short amount of time, is paramount to gathering the detailed structural information required for parameterizing FSPMs for forest communities. Conventional techniques, such as repeated manual forest surveys, have their limitations in explaining the driving mechanisms behind observed patterns in 3-D forest structure and dynamics. Therefore, other techniques are valuable to explore how forests might respond to environmental change. A robust synthesis between TLS and FSPMs provides the opportunity to virtually explore the spatial and temporal dynamics of forest communities.

Eco-evolutionary optimality as a means to improve vegetation and land-surface models

Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. However, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generates parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental change.

What Would a Tree Say About Its Size?

When developing theories, designing studies, and interpreting the results, researchers are influenced by their perception of tree size. For example, we may compare two trees of the same size belonging to different species, and attribute any differences to dissimilarities between the species. However, the meaning of “same size” depends on the measures of size used. Wood density influences certain measures, such as biomass, but does not influence e.g., trunk diameter. Therefore, the choice of the measure of size can reverse any conclusions. Hence, it is import to consider which measure of size should be used. I argue that the most common measure of size, i.e., trunk diameter, is often a bad choice when wood density varies, as diameter is then not directly related to processes important in evolution. When trees with equal diameters but differing wood densities are compared, the tree with denser wood is larger if the measure of size is related to construction cost or trunk strength, a proxy of leaf area. From this perspective, the comparison is then conducted between a biologically larger heavy-wooded tree and a smaller light-wooded tree, and the differences between the trees may be caused by size instead of wood density. Therefore, trunk biomass and strength may often be more suitable measures of size, as they reflect the construction cost and biomechanical potency linked to leaf area crown height, often too challenging to estimate more directly. To assess how commonly inadequate measures of tree size have been used, I reviewed 10 highly cited journal articles. None of these 10 articles discussed the impact of wood density on biological size, and instead based the analyses on diameters or basal areas. This led to conclusions that could change or even reverse in an analysis based on biomass or strength. Overall, I do not suggest avoiding the use of diameter, but I recommend considering result sensitivity to the measure of size, particularly in studies ones with variable wood densities.

Global patterns and climatic drivers of above- and belowground net primary productivity in grasslands

Understanding patterns and determinants of net primary productivity (NPP) in global grasslands is ongoing challenges, especially for belowground NPP (BNPP) and its fraction (f_BNPP). By developing a comprehensive field-based dataset, we revealed that, along with gradients of mean annual precipitation, actual evapotranspiration, and aridity, aboveground NPP (ANPP), BNPP, and total NPP (TNPP) exhibited hump-shaped patterns, whereas f_BNPP showed an opposite trend. ANPP and TNPP showed positive correlations with mean annual temperature, but f_BNPP was negatively correlated with it. The relationship between BNPP and climatic factors was considerably weak, indicating that BNPP was relatively stable regardless of the climate conditions. We also observed that the sensitivities of ANPP and BNPP to interannual temperature variability and those of BNPP to interannual precipitation fluctuations exhibited large variations among different study sites, and differed from those at the spatial scale. In contrast, the temporal sensitivities of ANPP to interannual precipitation variability were highly similar across all the individual sites and much smaller than those at the spatial scale. Overall, these results highlight that precipitation, temperature and evapotranspiration all play vital roles in shaping ANPP pattern and its partitioning to belowground and that the patterns of BNPP along climatic gradients do not mirror those of the ANPP.

Organizing principles for vegetation dynamics

Plants and vegetation play a critical-but largely unpredictable-role in global environmental changes due to the multitude of contributing processes at widely different spatial and temporal scales. In this Perspective, we explore approaches to master this complexity and improve our ability to predict vegetation dynamics by explicitly taking account of principles that constrain plant and ecosystem behaviour: natural selection, self-organization and entropy maximization. These ideas are increasingly being used in vegetation models, but we argue that their full potential has yet to be realized. We demonstrate the power of natural selection-based optimality principles to predict photosynthetic and carbon allocation responses to multiple environmental drivers, as well as how individual plasticity leads to the predictable self-organization of forest canopies. We show how models of natural selection acting on a few key traits can generate realistic plant communities and how entropy maximization can identify the most probable outcomes of community dynamics in space- and time-varying environments. Finally, we present a roadmap indicating how these principles could be combined in a new generation of models with stronger theoretical foundations and an improved capacity to predict complex vegetation responses to environmental change.

Forest carbon allocation modelling under climate change

Carbon allocation plays a key role in ecosystem dynamics and plant adaptation to changing environmental conditions. Hence, proper description of this process in vegetation models is crucial for the simulations of the impact of climate change on carbon cycling in forests. Here we review how carbon allocation modelling is currently implemented in 31 contrasting models to identify the main gaps compared with our theoretical and empirical understanding of carbon allocation. A hybrid approach based on combining several principles and/or types of carbon allocation modelling prevailed in the examined models, while physiologically more sophisticated approaches were used less often than empirical ones. The analysis revealed that, although the number of carbon allocation studies over the past 10 years has substantially increased, some background processes are still insufficiently understood and some issues in models are frequently poorly represented, oversimplified or even omitted. Hence, current challenges for carbon allocation modelling in forest ecosystems are (i) to overcome remaining limits in process understanding, particularly regarding the impact of disturbances on carbon allocation, accumulation and utilization of nonstructural carbohydrates, and carbon use by symbionts, and (ii) to implement existing knowledge of carbon allocation into defence, regeneration and improved resource uptake in order to better account for changing environmental conditions.

Quantifying the contribution of mass flow to nitrogen acquisition by an individual plant root

The classic model of nitrogen (N) flux into roots is as a Michaelis-Menten (MM) function of soil-N concentration at root surfaces. Furthermore, soil-N transport processes that determine soil-N concentration at root surfaces are seen as a bottleneck for plant nutrition. Yet, neither the MM relationship nor soil-N transport mechanisms are represented in current terrestrial biosphere models. Processes governing N supply to roots - diffusion, mass flow, N immobilization by soil microbes - are incorporated in a model of root-N uptake. We highlight a seldom considered interaction between these processes: nutrient traverses the rhizosphere more quickly in the presence of mass flow, reducing the probability of its immobilization before reaching the root surface. Root-N uptake is sensitive to the rate of mass flow for widely spaced roots with high N uptake capacity, but not for closely spaced roots or roots with low uptake capacity. The results point to a benefit of root switching from high- to low-affinity N transport systems in the presence of mass flow. Simulations indicate a strong impact of soil water uptake on N delivery to widely spaced roots through transpirationally driven mass flow. Furthermore, a given rate of N uptake per unit soil volume may be achieved by lower root biomass in the presence of mass flow.

Explaining ontogenetic shifts in root-shoot scaling with transient dynamics

BACKGROUND AND AIMS

Simple models of herbaceous plant growth based on optimal partitioning theory predict, at steady state, an isometric relationship between shoot and root biomass during plant ontogeny, i.e. a constant root-shoot ratio. This prediction has received mixed empirical support, suggesting either that optimal partitioning is too coarse an assumption to model plant biomass allocation, or that additional processes need to be modelled to account for empirical findings within the optimal partitioning framework. In this study, simulations are used to compare quantitatively two potential explanations for observed non-isometric relationships, namely nutrient limitation during the experiments and initial developmental constraints.

METHODS

A simple plant growth model was built to simulate the growth of herbaceous species, based on optimal partitioning theory combined with empirically measured plant functional traits. Its ability to reproduce plant relative growth rate and final root weight ratio was assessed against previously published data. Predicted root-shoot ratios during plant ontogeny were compared with experimental observations. The effects of nutrient limitation and initial developmental constraints on root-shoot ratios were then tested.

KEY RESULTS

The model was found to reproduce overall plant growth patterns accurately, but failed, in its simplest form, at explaining non-isometric growth trajectories. Both nutrient limitation and ontogenetic developmental constraints were further shown to cause transient dynamics resulting in a deviation from isometry. Nitrogen limitation alone was not sufficient to explain the observed trajectories of most plant species. The inclusion of initial developmental constraints (fixed non-optimal initial root-shoot ratios) enabled the reproduction of the observed trajectories and were consistent with observed initial root-shoot ratios.

CONCLUSIONS

This study highlights the fact that considering transient dynamics enables theoretical predictions based on optimal partitioning to be reconciled with empirically measured ontogenetic root-shoot allometries. The transient dynamics cannot be solely explained by nutrient limitation during the experiments, pointing to a likely role for initial developmental constraints in the observed non-isometric growth trajectories.

Where does the carbon go? A model-data intercomparison of vegetation carbon allocation and turnover processes at two temperate forest free-air CO2 enrichment sites

Elevated atmospheric CO2 concentration (eCO2) has the potential to increase vegetation carbon storage if increased net primary production causes increased long-lived biomass. Model predictions of eCO2 effects on vegetation carbon storage depend on how allocation and turnover processes are represented. We used data from two temperate forest free-air CO2 enrichment (FACE) experiments to evaluate representations of allocation and turnover in 11 ecosystem models. Observed eCO2 effects on allocation were dynamic. Allocation schemes based on functional relationships among biomass fractions that vary with resource availability were best able to capture the general features of the observations. Allocation schemes based on constant fractions or resource limitations performed less well, with some models having unintended outcomes. Few models represent turnover processes mechanistically and there was wide variation in predictions of tissue lifespan. Consequently, models did not perform well at predicting eCO2 effects on vegetation carbon storage. Our recommendations to reduce uncertainty include: use of allocation schemes constrained by biomass fractions; careful testing of allocation schemes; and synthesis of allocation and turnover data in terms of model parameters. Data from intensively studied ecosystem manipulation experiments are invaluable for constraining models and we recommend that such experiments should attempt to fully quantify carbon, water and nutrient budgets.

New insights into carbon allocation by trees from the hypothesis that annual wood production is maximized

Allocation of carbon (C) between tree components (leaves, fine roots and woody structures) is an important determinant of terrestrial C sequestration. Yet, because the mechanisms underlying C allocation are poorly understood, it is a weak link in current earth-system models. We obtain new theoretical insights into C allocation from the hypothesis (MaxW) that annual wood production is maximized. MaxW is implemented using a model of tree C and nitrogen (N) balance with a vertically resolved canopy and root system for stands of Norway spruce (Picea abies). MaxW predicts optimal vertical profiles of leaf N and root biomass, optimal canopy leaf area index and rooting depth, and the associated optimal pattern of C allocation. Key insights include a predicted optimal C-N functional balance between leaves at the base of the canopy and the deepest roots, according to which the net C export from basal leaves is just sufficient to grow the basal roots required to meet their N requirement. MaxW links the traits of basal leaves and roots to whole-tree C and N uptake, and unifies two previous optimization hypotheses (maximum gross primary production, maximum N uptake) that have been applied independently to canopies and root systems.

Urban tree species show the same hydraulic response to vapor pressure deficit across varying tree size and environmental conditions

Background

The functional convergence of tree transpiration has rarely been tested for tree species growing under urban conditions even though it is of significance to elucidate the relationship between functional convergence and species differences of urban trees for establishing sustainable urban forests in the context of forest water relations.

Methodology/Principal Findings

We measured sap flux of four urban tree species including Cedrus deodara, Zelkova schneideriana, Euonymus bungeanus and Metasequoia glyptostroboides in an urban park by using thermal dissipation probes (TDP). The concurrent microclimate conditions and soil moisture content were also measured. Our objectives were to examine 1) the influence of tree species and size on transpiration, and 2) the hydraulic control of urban trees under different environmental conditions over the transpiration in response to VPD as represented by canopy conductance. The results showed that the functional convergence between tree diameter at breast height (DBH) and tree canopy transpiration amount (E_c) was not reliable to predict stand transpiration and there were species differences within same DBH class. Species differed in transpiration patterns to seasonal weather progression and soil water stress as a result of varied sensitivity to water availability. Species differences were also found in their potential maximum transpiration rate and reaction to light. However, a same theoretical hydraulic relationship between G_c at VPD = 1 kPa (G_cref) and the G_c sensitivity to VPD (−dG_c/dlnVPD) across studied species as well as under contrasting soil water and R_s conditions in the urban area.

Conclusions/Significance

We concluded that urban trees show the same hydraulic regulation over response to VPD across varying tree size and environmental conditions and thus tree transpiration could be predicted with appropriate assessment of G_cref.