In a 10-year (1996-2005) biodiversity experiment, the mechanisms underlying the increasingly positive effect of biodiversity on plant biomass production shifted from sampling to complementarity over time. The effect of diversity on plant biomass was associated primarily with the accumulation of higher total plant nitrogen pools (N g m-2) and secondarily with more efficient N use at higher diversity. The accumulation of N in living plant biomass was significantly increased by the presence of legumes, C4 grasses, and their combined presence. Thus, these results provide clear evidence for the increasing effects of complementarity through time and suggest a mechanism whereby diversity increases complementarity through the increased input and retention of N, a commonly limiting nutrient.

Summary 1.Competition for resources has long been considered a prevalent force in structuring plant communities and natural selection, yet our understanding of the mechanisms that underlie resource competition is still developing. 2. The complexity of resource competition is derived not only from the variability of resource limitation in space and time and among species, but also from the complexity of the resources themselves. Nutrients, water and light each differ in their properties, which generates unique ways that plants compete for these resources. 3. Here, we discuss the roles of supply pre-emption and availability reduction in competition for the three resources when supplied evenly in space and time. Plants compete for nutrients by pre-empting nutrient supplies from coming into contact with neighbours, which requires maximizing root length. Although water is also a soil resource, competition for water is generally considered to occur by availability reduction, favouring plants that can withstand the lowest water potential. Because light is supplied from above plants, individuals that situate their leaves above those of neighbours benefit directly from increased photosynthetic rates and indirectly by reducing the growth of those neighbours via shade. In communities where juveniles recruit in the shade of adults, traits of the most competitive species are biased towards those that confer greater survivorship and growth at the juvenile stage, even if those traits come at the expense of adult performance. 4. Understanding the mechanisms of competition also reveals how competition has influenced the evolution of plant species. For example, nutrient competition has selected for plants to maintain higher root length and light competition plants that are taller, with deeper, flatter canopies than would be optimal in the absence of competition. 5. In all, while more research is needed on competition for heterogeneous resource supplies as well as for water, understanding the mechanisms of competition increases the predictability of interspecific interactions and reveals how competition has altered the evolution of plants.

We present a model that scales from the physiological and structural traits of individual trees competing for light and nitrogen across a gradient of soil nitrogen to their community-level consequences. The model predicts the most competitive (i.e., the evolutionarily stable strategy [ESS]) allocations to foliage, wood, and fine roots for canopy and understory stages of trees growing in old-growth forests. The ESS allocations, revealed as analytical functions of commonly measured physiological parameters, depend not on simple root-shoot relations but rather on diminishing returns of carbon investment that ensure any alternate strategy will underperform an ESS in monoculture because of the competitive environment that the ESS creates. As such, ESS allocations do not maximize nitrogen-limited growth rates in monoculture, highlighting the underappreciated idea that the most competitive strategy is not necessarily the "best," but rather that which creates conditions in which all others are "worse." Data from 152 stands support the model's surprising prediction that the dominant structural trade-off is between fine roots and wood, not foliage, suggesting the "root-shoot" trade-off is more precisely a "root-stem" trade-off for long-lived trees. Assuming other resources are abundant, the model predicts that forests are limited by both nitrogen and light, or nearly so.

We review approaches to predicting carbon and nitrogen allocation in forest models in terms of their underlying assumptions and their resulting strengths and limitations. Empirical and allometric methods are easily developed and computationally efficient, but lack the power of evolution-based approaches to explain and predict multifaceted effects of environmental variability and climate change. In evolution-based methods, allocation is usually determined by maximization of a fitness proxy, either in a fixed environment, which we call optimal response (OR) models, or including the feedback of an individual's strategy on its environment (game-theoretical optimization, GTO). Optimal response models can predict allocation in single trees and stands when there is significant competition only for one resource. Game-theoretical optimization can be used to account for additional dimensions of competition, e.g., when strong root competition boosts root allocation at the expense of wood production. However, we demonstrate that an OR model predicts similar allocation to a GTO model under the root-competitive conditions reported in free-air carbon dioxide enrichment (FACE) experiments. The most evolutionarily realistic approach is adaptive dynamics (AD) where the allocation strategy arises from eco-evolutionary dynamics of populations instead of a fitness proxy. We also discuss emerging entropy-based approaches that offer an alternative thermodynamic perspective on allocation, in which fitness proxies are replaced by entropy or entropy production. To help develop allocation models further, the value of wide-ranging datasets, such as FLUXNET, could be greatly enhanced by ancillary measurements of driving variables, such as water and soil nitrogen availability.

Abstract. 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.

The dependence of forest productivity and community composition on rainfall is the result of complex interactions at multiple scales, from the physiology of carbon gain and water loss to competition among individuals and species. In an effort to understand the role of these multiscale interactions in the dependence of forest structure on rainfall, we build a tractable model of individual plant competition for water and light. With game-theoretic analyses, we predict the dominant plant allocation strategy, forest productivity, and carbon storage. We find that the amount and timing of rainfall are critical to forest structure. Comparing two forests that differ only in the total time plants spend in water saturation, the model predicts that the wetter forest has fewer fine roots, more leaves, and more woody biomass than the drier forest. In contrast, if two forests differ only in the amount of water available during water limitation, the model predicts that the wetter forest has more fine roots than the drier forest and equivalent leaves and woody biomass. The difference in these responses to increases in water availability has significant implications for potential carbon sinks with rising atmospheric CO2. We predict that enhanced productivity from increased leaf-level water-use efficiency during water limitation will be allocated to fine roots if plants respond competitively, producing only a small and short-lived carbon sink.

The fixed and plastic traits possessed by a plant, which may be collectively thought of as its strategy, are commonly modelled as density-independent adaptations to its environment. However, plant strategies may also represent density-or frequency-dependent adaptations to the strategies used by neighbours. Game theory provides the tools to characterise such density-and frequency-dependent interactions. Here, we review the contributions of game theory to plant ecology. After briefly reviewing game theory from the perspective of plant ecology, we divide our review into three sections. First, game theoretical models of allocation to shoots and roots often predict investment in those organs beyond what would be optimal in the absence of competition. Second, game theoretical models of enemy defence suggest that an individual's investment in defence is not only a means of reducing its own tissue damage but also a means of deflecting enemies onto competitors. Finally, game theoretical models of trade with mutualistic partners suggest that the optimal trade may reflect competition for access to mutualistic partners among plants. In short, our review provides an accessible entrance to game theory that will help plant ecologists enrich their research with its worldview and existing predictions.

No abstract