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

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.

Decreased water limitation under elevated CO2 amplifies potential for forest carbon sinks.

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.

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.

Increased forest carbon storage with increased atmospheric CO2 despite nitrogen limitation: a game-theoretic allocation model for trees in competition for nitrogen and light.

Changes in resource availability often cause competitively driven changes in tree allocation to foliage, wood, and fine roots, either via plastic changes within individuals or through turnover of individuals with differing strategies. Here, we investigate how optimally competitive tree allocation should change in response to elevated atmospheric CO2 along a gradient of nitrogen and light availability, together with how those changes should affect carbon storage in living biomass. We present a physiologically-based forest model that includes the primary functions of wood and nitrogen. From a tree's perspective, wood is an offensive and defensive weapon used against neighbors in competition for light. From a biogeochemical perspective, wood is the primary living reservoir of stored carbon. Nitrogen constitutes a tree's photosynthetic machinery and the support systems for that machinery, and its limited availability thus reduces a tree's ability to fix carbon. This model has been previously successful in predicting allocation to foliage, wood, and fine roots along natural productivity gradients. Using game theory, we solve the model for competitively optimal foliage, wood, and fine root allocation strategies for trees in competition for nitrogen and light as a function of CO2 and nitrogen mineralization rate. Instead of down-regulating under nitrogen limitation, carbon storage under elevated CO2 relative to carbon storage at ambient CO2 is approximately independent of the nitrogen mineralization rate. This surprising prediction is a consequence of both increased competition for nitrogen driving increased fine root biomass and increased competition for light driving increased allocation to wood under elevated CO2 .

Neighborhoods have little effect on fungal attack or insect predation of developing seeds in a grassland biodiversity experiment.

Numerous observational studies have documented conspecific negative density-dependence that is consistent with the Janzen-Connell Hypothesis (JCH) of diversity maintenance. However, there have been few experimental tests of a central prediction of the JCH: that removing host-specific enemies should lead to greater increases in per capita recruitment in areas of higher host density or lower relative phylogenetic diversity. Using spatially randomized plots of high and low host biomass in a temperate grassland biodiversity experiment, we treated developing seedheads of six prairie perennials to factorial applications of fungicide and insecticide. We measured predispersal seed production, seed viability, and seedling biomass. Results were highly species-specific and idiosyncratic. Effects of insect seed predators and fungal pathogens on predispersal responses varied with neither conspecific biomass nor phylogenetic diversity, suggesting that-at least at the predispersal stage and for the insect and fungal seed predators we were able to exclude-the JCH is not sufficient to contribute to negative conspecific density-dependence for these dominant prairie species.

Game theory and plant ecology.

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.

Competition for water and light in closed-canopy forests: a tractable model of carbon allocation with implications for carbon sinks.

Abstract 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.

Interspecific vs intraspecific patterns in leaf nitrogen of forest trees across nitrogen availability gradients.

Leaf nitrogen content (δ) coordinates with total canopy N and leaf area index (LAI) to maximize whole-crown carbon (C) gain, but the constraints and contributions of within-species plasticity to this phenomenon are poorly understood. Here, we introduce a game theoretic, physiologically based community model of height-structured competition between late-successional tree species. Species are constrained by an increasing, but saturating, relationship between photosynthesis and leaf N per unit leaf area. Higher saturating rates carry higher fixed costs. For a given whole-crown N content, a C gain-maximizing compromise exists between δ and LAI. With greater whole-crown N, both δ and LAI increase within species. However, a shift in community composition caused by reduced understory light at high soil N availability (which competitively favors species with low leaf costs and consequent low optimal δ) counteracts the within-species response, such that community-level δ changes little with soil N availability. These model predictions provide a new explanation for the changes in leaf N per mass observed in data from three dominant broadleaf species in temperate deciduous forests of New England. Attempts to understand large-scale patterns in vegetation often omit competitive interactions and intraspecific plasticity, but here both are essential to an understanding of ecosystem-level patterns.

Resource limitation in a competitive context determines complex plant responses to experimental resource additions.

Almost all models of plant resource limitation are grounded in either one or both of two simple conceptual models: Liebig's Minimum Hypothesis (LMH), the idea that plants are limited by the resource in shortest supply, and the Multiple Limitation Hypothesis (MLH), the idea that plants should adjust to their environment so that all essential resources are equally limiting. Despite the differences in their predictions, experiments have so far failed to discriminate between them. In a simple factorial nitrogen and water addition experiment in a Minnesota grassland, we observed shifts in allocation that, as in previous studies, are not all explained by a single theory. We found that leaf biomass responded positively to nitrogen additions but did not respond to water additions. We found that fine-root biomass increased in response to water additions, but only at low nitrogen levels, and that fine-root biomass decreased in response to nitrogen additions, but only at high water levels. To understand these responses we built a physiologically based model of plant competition for water, nitrogen, and space to predict plant allocation to fine roots and leaves. Critically, we include in our model the inherent variability of soil moisture and treat light, water, and nitrogen as resources with distinct mechanistic roles. Experimental results showed that plants were nitrogen and water limited. The model explains the experimental results, under conditions of co-limitation, as follows. Foliage increases with nitrogen additions but not water additions because leaf construction is constrained by nitrogen uptake. When water is added, plants spend a larger fraction of the growing season limited by light (and effectively nitrogen) than by water. Thus, water additions cause fine-root biomass to increase because of the increased importance of nitrogen limitation. The response of fine-root biomass to water additions decreases with nitrogen additions because these additions reduce nitrogen limitation. In general, our results are explained by sequential resource limitation. The rate of carbon assimilation may be limited by a single resource at any one moment, but the identity of the limiting resource(s) changes throughout the growing season.

Short-term plant-soil feedback experiment fails to predict outcome of competition observed in long-term field experiment.

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.

Evolutionarily stable strategy carbon allocation to foliage, wood, and fine roots in trees competing for light and nitrogen: an analytically tractable, individual-based model and quantitative comparisons to data.

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.

Resource use patterns predict long-term outcomes of plant competition for nutrients and light.

An 11-year competition experiment among combinations of six prairie perennial plant species showed that resource competition theory generally predicted the long-term outcome of competition. We grew each species in replicated monocultures to determine its requirements for soil nitrate (R*) and light (I*). In six pairwise combinations, the species with the lower R* and I* excluded its competitor, as predicted by theory. In the remaining two pairwise combinations, one species had a lower R*, and the second had a lower I*; these species pairs coexisted, although it is unclear whether resource competition alone was responsible for their coexistence. Smaller differences in R* or I* between competing species led to slower rates of competitive exclusion, and the influence of R* differences on the rate of competitive exclusion was more pronounced on low-nitrogen soils, while the influence of I* differences was more pronounced on high-nitrogen (low-light) soils. These results were not explained by differences in initial species abundances or neutrality. However, only a few of our paired species coexisted under our experimentally imposed conditions (homogeneous soils, high seeding densities, minimal disturbance, regular water, and low herbivory levels), suggesting that other coexistence mechanisms help generate the diversity observed in natural communities.

From selection to complementarity: shifts in the causes of biodiversity-productivity relationships in a long-term biodiversity experiment.

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.

Modeling carbon allocation in trees: a search for principles.

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.

Soil fertility increases with plant species diversity in a long-term biodiversity experiment.

Most explanations for the positive effect of plant species diversity on productivity have focused on the efficiency of resource use, implicitly assuming that resource supply is constant. To test this assumption, we grew seedlings of Echinacea purpurea in soil collected beneath 10-year-old, experimental plant communities containing one, two, four, eight, or 16 native grassland species. The results of this greenhouse bioassay challenge the assumption of constant resource supply; we found that bioassay seedlings grown in soil collected from experimental communities containing 16 plant species produced 70% more biomass than seedlings grown in soil collected beneath monocultures. This increase was likely attributable to greater soil N availability, which had increased in higher diversity communities over the 10-year-duration of the experiment. In a distinction akin to the selection/complementarity partition commonly made in studies of diversity and productivity, we further determined whether the additive effects of functional groups or the interactive effects of functional groups explained the increase in fertility with diversity. The increase in bioassay seedling biomass with diversity was largely explained by a concomitant increase in N-fixer, C4 grass, forb, and C3 grass biomass with diversity, suggesting that the additive effects of these four functional groups at higher diversity contributed to enhance N availability and retention. Nevertheless, diversity still explained a significant amount of the residual variation in bioassay seedling biomass after functional group biomass was included in a multiple regression, suggesting that interactions also increased fertility in diverse communities. Our results suggest a mechanism, the fertility effect, by which increased plant species diversity may increase community productivity over time by increasing the supply of nutrients via both greater inputs and greater retention.