Climate and plant trait strategies determine tree carbon allocation to leaves and mediate future forest productivity

Forest leaf area has enormous leverage on the carbon cycle because it mediates both forest productivity and resilience to climate extremes. Despite widespread evidence that trees are capable of adjusting to changes in environment across both space and time through modifying carbon allocation to leaves, many vegetation models use fixed carbon allocation schemes independent of environment, which introduces large uncertainties into predictions of future forest responses to atmospheric CO₂ fertilization and anthropogenic climate change. Here, we develop an optimization‐based model, whereby tree carbon allocation to leaves is an emergent property of environment and plant hydraulic traits. Using a combination of meta‐analysis, observational datasets, and model predictions, we find strong evidence that optimal hydraulic–carbon coupling explains observed patterns in leaf allocation across large environmental and CO₂ concentration gradients. Furthermore, testing the sensitivity of leaf allocation strategy to a diversity in hydraulic and economic spectrum physiological traits, we show that plant hydraulic traits in particular have an enormous impact on the global change response of forest leaf area. Our results provide a rigorous theoretical underpinning for improving carbon cycle predictions through advancing model predictions of leaf area, and underscore that tree‐level carbon allocation to leaves should be derived from first principles using mechanistic plant hydraulic processes in the next generation of vegetation models.     

Observed and modelled historical trends in the water‐use efficiency of plants and ecosystems

Plant water‐use efficiency (WUE, the carbon gained through photosynthesis per unit of water lost through transpiration) is a tracer of the plant physiological controls on the exchange of water and carbon dioxide between terrestrial ecosystems and the atmosphere. At the leaf level, rising CO₂ concentrations tend to increase carbon uptake (in the absence of other limitations) and to reduce stomatal conductance, both effects leading to an increase in leaf WUE. At the ecosystem level, indirect effects (e.g. increased leaf area index, soil water savings) may amplify or dampen the direct effect of CO₂. Thus, the extent to which changes in leaf WUE translate to changes at the ecosystem scale remains unclear. The differences in the magnitude of increase in leaf versus ecosystem WUE as reported by several studies are much larger than would be expected with current understanding of tree physiology and scaling, indicating unresolved issues. Moreover, current vegetation models produce inconsistent and often unrealistic magnitudes and patterns of variability in leaf and ecosystem WUE, calling for a better assessment of the underlying approaches. Here, we review the causes of variations in observed and modelled historical trends in WUE over the continuum of scales from leaf to ecosystem, including methodological issues, with the aim of elucidating the reasons for discrepancies observed within and across spatial scales. We emphasize that even though physiological responses to changing environmental drivers should be interpreted differently depending on the observational scale, there are large uncertainties in each data set which are often underestimated. Assumptions made by the vegetation models about the main processes influencing WUE strongly impact the modelled historical trends. We provide recommendations for improving long‐term observation‐based estimates of WUE that will better inform the representation of WUE in vegetation models.     

Implementing plant hydraulic architecture within the LPJ Dynamic Global Vegetation Model

Aim To implement plant hydraulic architecture within the Lund–Potsdam–Jena Dynamic Global Vegetation Model (LPJ–DGVM), and to test the model against a set of observational data. If the model can reproduce major patterns in vegetation and ecosystem processes, we consider this to be an important linkage between plant physiology and larger‐scale ecosystem dynamics. Location The location is global, geographically distributed. Methods A literature review was carried out to derive model formulations and parameter values for representing the hydraulic characteristics of major global plant functional types (PFTs) in a DGVM. After implementing the corresponding formulations within the LPJ–DGVM, present‐day model output was compared to observational data. Results The model reproduced observed broad‐scale patterns in potential natural vegetation, but it failed to distinguish accurately between different types of grassland and savanna vegetation, possibly related to inadequate model representations of water fluxes in the soil and wildfire effects. Compared to a version of the model using an empirical formulation for calculating plant water supply without considering plant hydraulic architecture, the new formulation improved simulated patterns of vegetation in particular for dry shrublands. Global‐scale simulation results for runoff and actual evapotranspiration (AET) corresponded well to available data. The model also successfully reproduced the magnitude and seasonal cycle of AET for most EUROFLUX forests, while modelled variation in NPP across a large number of sites spanning several biomes showed a strong correlation with estimates from field measurements. Main conclusions The model was generally confirmed by comparison to observational data. The novel model representation of water flow within plants makes it possible to resolve mechanistically the effects of hydraulic differences between plant functional groups on vegetation structure, water cycling, and competition. This may be an advantage when predicting ecosystem responses to nonextant climates, in particular in areas dominated by dry shrubland vegetation.     

A parameterization of leaf phenology for the terrestrial ecosystem component of climate models

Leaf phenology remains one of the most difficult processes to parameterize in terrestrial ecosystem models because our understanding of the physical processes that initiate leaf onset and senescence is incomplete. While progress has been made at the molecular level, for example by identifying genes that are associated with senescence and flowering for selected plant species, a picture of the processes controlling leaf phenology is only beginning to emerge. A variety of empirical formulations have been used with varying degrees of success in terrestrial ecosystem models for both extratropical and tropical biomes. For instance, the use of growing degree‐days (GDDs) to initiate leaf onset has received considerable recognition and this approach is used in a number of models. There are, however, limitations when using GDDs and other empirically based formulations in global transient climate change simulations. The phenology scheme developed for the Canadian Terrestrial Ecosystem Model (CTEM), designed for inclusion in the Canadian Centre for Climate Modelling and Analysis coupled general circulation model, is described. The representation of leaf phenology is general enough to be applied over the globe and sufficiently robust for use in transient climate change simulations. Leaf phenology is functionally related to the (possibly changing) climate state and to atmospheric composition rather than to geographical boundaries or controls implicitly based on current climate. In this approach, phenology is controlled by environmental conditions as they affect the carbon balance. A carbon‐gain‐based scheme initiates leaf onset when it is beneficial for the plant, in carbon terms, to produce new leaves. Leaf offset is initiated by unfavourable environmental conditions that incur carbon losses and these include shorter day length, cooler temperatures, and dry soil moisture conditions. The comparison of simulated leaf onset and offset times with observation‐based estimates for temperate and boreal deciduous, tropical evergreen, and tropical deciduous plant functional types at selected locations indicates that the phenology scheme performs satisfactorily. Model simulated leaf area index and stem and root biomass are also compared with observational estimates to illustrate the performance of CTEM.     

Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space

• 1 Advances in dynamic ecosystem modelling have made a number of different approaches to vegetation dynamics possible. Here we compare two models representing contrasting degrees of abstraction of the processes governing dynamics in real vegetation.
• 2 Model (a) (GUESS) simulates explicitly growth and competition among individual plants. Differences in crown structure (height, depth, area and LAI) influence relative light uptake by neighbours. Assimilated carbon is allocated individually by each plant to its leaf, fine root and sapwood tissues. Carbon allocation and turnover of sapwood to heartwood in turn govern height and diameter growth.
• 3 Model (b) (LPJ) incorporates a ‘dynamic global vegetation model’ (DGVM) architecture, simulating growth of populations of plant functional types (PFTs) over a grid cell, integrating individual‐level processes over the proportional area (foliar projective cover, FPC) occupied by each PFT. Individual plants are not simulated, but are replaced by explicit parameterizations of their growth and interactions.
• 4 The models are identical in their representation of core physiological and biogeochemical processes. Both also use the same set of PFTs, corresponding to the major woody plant groups in Europe, plus a grass type.
• 5 When applied at a range of locations, broadly spanning climatic variation within Europe, both models successfully predicted PFT composition and succession within modern natural vegetation. However, the individual‐based model performed better in areas where deciduous and evergreen types coincide, and in areas subject to pronounced seasonal water deficits, which would tend to favour grasses over drought‐intolerant trees.
• 6 Differences in model performance could be traced to their treatment of individual‐level processes, in particular light competition and stress‐induced mortality.
• 7 Our results suggest that an explicit individual‐based approach to vegetation dynamics may be an advantage in modelling of ecosystem structure and function at the resolution required for regional‐ to continental‐scale studies.

     

Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model

The Lund–Potsdam–Jena Dynamic Global Vegetation Model (LPJ) combines process‐based, large‐scale representations of terrestrial vegetation dynamics and land‐atmosphere carbon and water exchanges in a modular framework. Features include feedback through canopy conductance between photosynthesis and transpiration and interactive coupling between these ‘fast’ processes and other ecosystem processes including resource competition, tissue turnover, population dynamics, soil organic matter and litter dynamics and fire disturbance. Ten plants functional types (PFTs) are differentiated by physiological, morphological, phenological, bioclimatic and fire‐response attributes. Resource competition and differential responses to fire between PFTs influence their relative fractional cover from year to year. Photosynthesis, evapotranspiration and soil water dynamics are modelled on a daily time step, while vegetation structure and PFT population densities are updated annually. Simulations have been made over the industrial period both for specific sites where field measurements were available for model evaluation, and globally on a 0.5°° × 0.5°° grid. Modelled vegetation patterns are consistent with observations, including remotely sensed vegetation structure and phenology. Seasonal cycles of net ecosystem exchange and soil moisture compare well with local measurements. Global carbon exchange fields used as input to an atmospheric tracer transport model (TM2) provided a good fit to observed seasonal cycles of CO₂ concentration at all latitudes. Simulated inter‐annual variability of the global terrestrial carbon balance is in phase with and comparable in amplitude to observed variability in the growth rate of atmospheric CO₂. Global terrestrial carbon and water cycle parameters (pool sizes and fluxes) lie within their accepted ranges. The model is being used to study past, present and future terrestrial ecosystem dynamics, biochemical and biophysical interactions between ecosystems and the atmosphere, and as a component of coupled Earth system models.     

Improving plant functional groups for dynamic models of biodiversity: at the crossroads between functional and community ecology

The pace of on‐going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid‐DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process‐based models, are able to involve an intermediate number of well‐chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid‐DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid‐DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling.     

A global analysis of plant recovery performance from water stress

Plant post‐drought recovery performance is essential to predict shifts in ecosystem dynamics and production during frequent climate change‐driven drought events. Yet, it is not clear how post‐drought recovery is related to evolutionary and geographic variations in plants. In this study, we generated a global data set of post‐drought recovery performance in 140 plant species from published studies. We quantified the plant post‐drought recovery performance by calculating a recovery index for multiple plant physiological and hydraulic parameters, including leaf water potential, net photosynthetic rate, leaf hydraulic conductance and shoot biomass. The magnitude of recovery among four plant functional types (deciduous angiosperms, evergreen angiosperms, gymnosperms, and crops), two plant growth forms (shrubs and trees), two water management strategies (isohydric and anisohydric), four xylem porosity types (diffuse, ring, semi‐ring and tracheid), and four major biomes (dry sclerophyll forest, boreal forest, temperate forest and tropical/subtropical forest) were compared. We found the inability to completely recover immediately after severe water stress is ubiquitous across all plant functional types and growth forms, while the rate and magnitude of post‐drought recovery varied greatly across different plant taxonomic categories and geographic ranges. In general, plant hydraulic architecture, leaf anatomy and physiology affect plants’ propensity towards recovery, and reflect evolutionary consequences of plant adaptation to their habitat. Due to the essential role of plant functional traits in regulating carbon storage in each biome, a better understanding plant post‐drought recovery performance could improve our predictions on ecosystem productivity in a rapidly changing climate.     

Widespread drought‐induced tree mortality at dry range edges indicates that climate stress exceeds species' compensating mechanisms

Drought‐induced tree mortality is projected to increase due to climate change, which will have manifold ecological and societal impacts including the potential to weaken or reverse the terrestrial carbon sink. Predictions of tree mortality remain limited, in large part because within‐species variations in ecophysiology due to plasticity or adaptation and ecosystem adjustments could buffer mortality in dry locations. Here, we conduct a meta‐analysis of 50 studies spanning >100 woody plant species globally to quantify how populations within species vary in vulnerability to drought mortality and whether functional traits or climate mediate mortality patterns. We find that mortality predominantly occurs in drier populations and this pattern is more pronounced in species with xylem that can tolerate highly negative water potentials, typically considered to be an adaptive trait for dry regions, and species that experience higher variability in water stress. Our results indicate that climate stress has exceeded physiological and ecosystem‐level tolerance or compensating mechanisms by triggering extensive mortality at dry range edges and provides a foundation for future mortality projections in empirical distribution and mechanistic vegetation models.     

Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model

Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to plant functional types (PFTs) with constant parameters. Here, we develop an individual‐ and trait‐based version of the DGVM LPJmL (Lund‐Potsdam‐Jena managed Land) called LPJmL‐ flexible individual traits (LPJmL‐FIT) with flexible individual traits) which we apply to generate plant trait maps for the Amazon basin. LPJmL‐FIT incorporates empirical ranges of five traits of tropical trees extracted from the TRY global plant trait database, namely specific leaf area (SLA), leaf longevity (LL), leaf nitrogen content (N_area), the maximum carboxylation rate of Rubisco per leaf area (), and wood density (WD). To scale the individual growth performance of trees, the leaf traits are linked by trade‐offs based on the leaf economics spectrum, whereas wood density is linked to tree mortality. No preselection of growth strategies is taking place, because individuals with unique trait combinations are uniformly distributed at tree establishment. We validate the modeled trait distributions by empirical trait data and the modeled biomass by a remote sensing product along a climatic gradient. Including trait variability and trade‐offs successfully predicts natural trait distributions and achieves a more realistic representation of functional diversity at the local to regional scale. As sites of high climatic variability, the fringes of the Amazon promote trait divergence and the coexistence of multiple tree growth strategies, while lower plant trait diversity is found in the species‐rich center of the region with relatively low climatic variability. LPJmL‐FIT enables to test hypotheses on the effects of functional biodiversity on ecosystem functioning and to apply the DGVM to current challenges in ecosystem management from local to global scales, that is, deforestation and climate change effects.     

Inclusion of ecologically based trait variation in plant functional types reduces the projected land carbon sink in an earth system model

Earth system models demonstrate large uncertainty in projected changes in terrestrial carbon budgets. The lack of inclusion of adaptive responses of vegetation communities to the environment has been suggested to hamper the ability of modeled vegetation to adequately respond to environmental change. In this study, variation in functional responses of vegetation has been added to an earth system model (ESM) based on ecological principles. The restriction of viable mean trait values of vegetation communities by the environment, called ‘habitat filtering’, is an important ecological assembly rule and allows for determination of global scale trait–environment relationships. These relationships were applied to model trait variation for different plant functional types (PFTs). For three leaf traits (specific leaf area, maximum carboxylation rate at 25 °C, and maximum electron transport rate at 25 °C), relationships with multiple environmental drivers, such as precipitation, temperature, radiation, and CO₂, were determined for the PFTs within the Max Planck Institute ESM. With these relationships, spatiotemporal variation in these formerly fixed traits in PFTs was modeled in global change projections (IPCC RCP8.5 scenario). Inclusion of this environment‐driven trait variation resulted in a strong reduction of the global carbon sink by at least 33% (2.1 Pg C yr^?1) from the 2nd quarter of the 21st century onward compared to the default model with fixed traits. In addition, the mid‐ and high latitudes became a stronger carbon sink and the tropics a stronger carbon source, caused by trait‐induced differences in productivity and relative respirational costs. These results point toward a reduction of the global carbon sink when including a more realistic representation of functional vegetation responses, implying more carbon will stay airborne, which could fuel further climate change.     

The ecological significance of long-distance water transport: short-term regulation, long-term acclimation and the hydraulic costs of stature across plant life forms

Plant hydraulic conductance, namely the rate of water flow inside plants per unit time and unit pressure difference, varies largely from plant to plant and under different environmental conditions. Herein the main factors affecting: (a) the scaling between whole‐plant hydraulic conductance and leaf area; (b) the relationship between gas exchange at the leaf level and leaf‐specific xylem hydraulic conductance; (c) the short‐term physiological regulation of plant hydraulic conductance under conditions of ample soil water, and (d) the long‐term structural acclimation of xylem hydraulic conductance to changes in environmental conditions are reviewed. It is shown that plant hydraulic conductance is a highly plastic character that varies as a result of multiple processes acting at several time scales. Across species ranging from coniferous and broad‐leaved trees to shrubs, crop and herbaceous species, and desert subshrubs, hydraulic conductance scaled linearly with leaf area, as expected from first principles. Despite considerable convergence in the scaling of hydraulic properties, significant differences were apparent across life forms that underlie their different abilities to conduct gas exchange at the leaf level. A simple model of carbon allocation between leaves and support tissues explained the observed patterns and correctly predicted the inverse relationships with plant height. Therefore, stature appears as a fundamental factor affecting gas exchange across plant life forms. Both short‐term physiological regulation and long‐term structural acclimation can change the levels of hydraulic conductance significantly. Based on a meta‐analysis of the existing literature, any change in environmental parameters that increases the availability of resources (either above‐ or below‐ground) results in the long‐term acclimation of a less efficient (per unit leaf area) hydraulic system.     

Evaluation of climate‐related carbon turnover processes in global vegetation models for boreal and temperate forests

Turnover concepts in state‐of‐the‐art global vegetation models (GVMs) account for various processes, but are often highly simplified and may not include an adequate representation of the dominant processes that shape vegetation carbon turnover rates in real forest ecosystems at a large spatial scale. Here, we evaluate vegetation carbon turnover processes in GVMs participating in the Inter‐Sectoral Impact Model Intercomparison Project (ISI‐MIP, including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT) using estimates of vegetation carbon turnover rate (k) derived from a combination of remote sensing based products of biomass and net primary production (NPP). We find that current model limitations lead to considerable biases in the simulated biomass and in k (severe underestimations by all models except JeDi and VISIT compared to observation‐based average k), likely contributing to underestimation of positive feedbacks of the northern forest carbon balance to climate change caused by changes in forest mortality. A need for improved turnover concepts related to frost damage, drought, and insect outbreaks to better reproduce observation‐based spatial patterns in k is identified. As direct frost damage effects on mortality are usually not accounted for in these GVMs, simulated relationships between k and winter length in boreal forests are not consistent between different regions and strongly biased compared to the observation‐based relationships. Some models show a response of k to drought in temperate forests as a result of impacts of water availability on NPP, growth efficiency or carbon balance dependent mortality as well as soil or litter moisture effects on leaf turnover or fire. However, further direct drought effects such as carbon starvation (only in HYBRID4) or hydraulic failure are usually not taken into account by the investigated GVMs. While they are considered dominant large‐scale mortality agents, mortality mechanisms related to insects and pathogens are not explicitly treated in these models.     

Allometric constraints and competition enable the simulation of size structure and carbon fluxes in a dynamic vegetation model of tropical forests (LM3PPA‐TV)

Tropical forests are a key determinant of the functioning of the Earth system, but remain a major source of uncertainty in carbon cycle models and climate change projections. In this study, we present an updated land model (LM3PPA‐TV) to improve the representation of tropical forest structure and dynamics in Earth system models (ESMs). The development and parameterization of LM3PPA‐TV drew on extensive datasets on tropical tree traits and long‐term field censuses from Barro Colorado Island (BCI), Panama. The model defines a new plant functional type (PFT) based on the characteristics of shade‐tolerant, tropical tree species, implements a new growth allocation scheme based on realistic tree allometries, incorporates hydraulic constraints on biomass accumulation, and features a new compartment for tree branches and branch fall dynamics. Simulation experiments reproduced observed diurnal and seasonal patterns in stand‐level carbon and water fluxes, as well as mean canopy and understory tree growth rates, tree size distributions, and stand‐level biomass on BCI. Simulations at multiple sites captured considerable variation in biomass and size structure across the tropical forest biome, including observed responses to precipitation and temperature. Model experiments suggested a major role of water limitation in controlling geographic variation forest biomass and structure. However, the failure to simulate tropical forests under extreme conditions and the systematic underestimation of forest biomass in Paleotropical locations highlighted the need to incorporate variation in hydraulic traits and multiple PFTs that capture the distinct floristic composition across tropical domains. The continued pressure on tropical forests from global change demands models which are able to simulate alternative successional pathways and their pace to recovery. LM3PPA‐TV provides a tool to investigate geographic variation in tropical forests and a benchmark to continue improving the representation of tropical forests dynamics and their carbon storage potential in ESMs.     

陆地碳循环研究中植物生理生态过程模拟进展

植物生理生态过程的模拟是陆地碳循环模型研究中的关键过程之一,就与碳循环过程密切相关的3个关键的植物生理生态过程;光合作用,碳分配和物候等过程的数学模式进行分类：（1）光合作用模式,根据光合作用模式基础的不同把光合作用模式分为：半经验模式;机理模式和使用卫星遥感资料的模式等;（2）植物碳分配模式介绍了功能平衡模式;运输-阻力模式;光合作用与生长模式;环境反应模式和大尺度生态系统模式等5类。（3）植被物候模式;根据观测和参数化方法的不同可以将现有的物候数值模式分为两类;观测统计模式和使用卫星遥感资料的物候模式,对各类模式的主要控制方程,研究进展和应用分别进行了简要评述。     

Vegetation demographics in Earth System Models: A review of progress and priorities

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. Here, we review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real‐world ecosystems. We argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first‐generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter‐disciplinary communication.     

Comparing and evaluating process-based ecosystem model predictions of carbon and water fluxes in major European forest biomes

Process‐based models can be classified into: (a) terrestrial biogeochemical models (TBMs), which simulate fluxes of carbon, water and nitrogen coupled within terrestrial ecosystems, and (b) dynamic global vegetation models (DGVMs), which further couple these processes interactively with changes in slow ecosystem processes depending on resource competition, establishment, growth and mortality of different vegetation types. In this study, four models – RHESSys, GOTILWA+, LPJ‐GUESS and ORCHIDEE – representing both modelling approaches were compared and evaluated against benchmarks provided by eddy‐covariance measurements of carbon and water fluxes at 15 forest sites within the EUROFLUX project. Overall, model‐measurement agreement varied greatly among sites. Both modelling approaches have somewhat different strengths, but there was no model among those tested that universally performed well on the two variables evaluated. Small biases and errors suggest that ORCHIDEE and GOTILWA+ performed better in simulating carbon fluxes while LPJ‐GUESS and RHESSys did a better job in simulating water fluxes. In general, the models can be considered as useful tools for studies of climate change impacts on carbon and water cycling in forests. However, the various sources of variation among models simulations and between models simulations and observed data described in this study place some constraints on the results and to some extent reduce their reliability. For example, at most sites in the Mediterranean region all models generally performed poorly most likely because of problems in the representation of water stress effects on both carbon uptake by photosynthesis and carbon release by heterotrophic respiration (R_h). The use of flux data as a means of assessing key processes in models of this type is an important approach to improving model performance. Our results show that the models have value but that further model development is necessary with regard to the representation of the some of the key ecosystem processes.     

A dynamic global vegetation model for use with climate models: concepts and description of simulated vegetation dynamics

Changes in vegetation structure and biogeography due to climate change feedback to alter climate by changing fluxes of energy, moisture, and momentum between land and atmosphere. While the current class of land process models used with climate models parameterizes these fluxes in detail, these models prescribe surface vegetation and leaf area from data sets. In this paper, we describe an approach in which ecological concepts from a global vegetation dynamics model are added to the land component of a climate model to grow plants interactively. The vegetation dynamics model is the Lund–Potsdam–Jena (LPJ) dynamic global vegetation model. The land model is the National Center for Atmospheric Research (NCAR) Land Surface Model (LSM). Vegetation is defined in terms of plant functional types. Each plant functional type is represented by an individual plant with the average biomass, crown area, height, and stem diameter (trees only) of its population, by the number of individuals in the population, and by the fractional cover in the grid cell. Three time‐scales (minutes, days, and years) govern the processes. Energy fluxes, the hydrologic cycle, and carbon assimilation, core processes in LSM, occur at a 20 min time step. Instantaneous net assimilated carbon is accumulated annually to update vegetation once a year. This is carried out with the addition of establishment, resource competition, growth, mortality, and fire parameterizations from LPJ. The leaf area index is updated daily based on prevailing environmental conditions, but the maximum value depends on the annual vegetation dynamics. The coupling approach is successful. The model simulates global biogeography, net primary production, and dynamics of tundra, boreal forest, northern hardwood forest, tropical rainforest, and savanna ecosystems, which are consistent with observations. This suggests that the model can be used with a climate model to study biogeophysical feedbacks in the climate system related to vegetation dynamics.