Competition alters predicted forest carbon cycle responses to nitrogen availability and elevated CO2: simulations using an explicitly competitive, game-theoretic vegetation demographic model

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

How are nitrogen availability, fine-root mass, and nitrogen uptake related empirically? Implications for models and theory

We gratefully acknowledge funding from Loyola University Chicago; suggestions for improvement by David Robinson and anonymous peer reviewers; logistical support from K. Erickson; help with maintenance and harvests from O. Urbanski, L. Papaioannou, H. Roudebush, & V. Roudebush; and tissue and substrate analyses from Z. Zhu. The authors have no conflicts of interest to report.Peer reviewedPostprin

Demographic trade-offs predict tropical forest dynamics

Understanding tropical forest dynamics and planning for their sustainable management require efficient, yet accurate, predictions of the joint dynamics of hundreds of tree species. With increasing information on tropical tree life histories, our predictive understanding is no longer limited by species data but by the ability of existing models to make use of it. Using a demographic forest model, we show that the basal area and compositional changes during forest succession in a neotropical forest can be accurately predicted by representing tropical tree diversity (hundreds of species) with only five functional groups spanning two essential trade-offs—the growth-survival and stature-recruitment trade-offs. This data-driven modeling framework substantially improves our ability to predict consequences of anthropogenic impacts on tropical forests

Scaling from individual trees to forests in an Earth system modeling framework using a mathematically tractable model of height-structured competition

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

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

The function-dominance correlation drives the direction and strength of biodiversity-ecosystem functioning relationships

Community composition is a primary determinant of how biodiversity change influences ecosystem functioning and, therefore, the relationship between biodiversity and ecosystem functioning (BEF). We examine the consequences of community composition across six structurally realistic plant community models. We find that a positive correlation between species' functioning in monoculture versus their dominance in mixture with regard to a specific function (the "function-dominance correlation") generates a positive relationship between realised diversity and ecosystem functioning across species richness treatments. However, because realised diversity declines when few species dominate, a positive function-dominance correlation generates a negative relationship between realised diversity and ecosystem functioning within species richness treatments. Removing seed inflow strengthens the link between the function-dominance correlation and BEF relationships across species richness treatments but weakens it within them. These results suggest that changes in species' identities in a local species pool may more strongly affect ecosystem functioning than changes in species richness

Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0)

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

Predicting vegetation type through physiological and environmental interactions with leaf traits: evergreen and deciduous forests in an earth system modeling framework

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

Optimal stomatal drought response shaped by competition for water and hydraulic risk can explain plant trait covariation

The classical theory of stomatal optimization stipulates that stomata should act to maximize photosynthesis while minimizing transpiration. This theory, despite its remarkable success in reproducing empirical patterns, does not account for the fact that the available water to plants is dynamically regulated by plants themselves, and that plants compete for water in most locations. Here, we develop an alternative theory in which plants maximize the expected carbon gain under stochastic rainfall in a competitive environment. We further incorporate xylem hydraulic limitation as an additional constraint to transpiration and evaluate its impacts on stomatal optimization by incorporating the direct carbon cost of xylem recovery and the opportunity cost of reduced future photosynthesis as a result of irrecoverable xylem damage. We predict stomatal behaviour to be more conservative with a higher cost induced by xylem damage. By varying the unit carbon cost and extent of xylem recovery, characterizing the direct and opportunity cost of xylem damage, respectively, our model can reproduce several key patterns of stomatal-hydraulic trait covariations. By addressing the key elements of water limitation in plant gas exchange simultaneously, including plants’ self-regulation of water availability, competition for water and hydraulic risk, our study provides a comprehensive theoretical basis for understanding stomatal behaviour