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.

Nothing in Evolution Makes Sense Except in the Light of Biology.

A key question in biology is the predictability of the evolutionary process. If we can correctly predict the outcome of evolution, we may be better equipped to anticipate and manage species' adaptation to climate change, habitat loss, invasive species, or emerging infectious diseases, as well as improve our basic understanding of the history of life on Earth. In the present article, we ask the questions when, why, and if the outcome of future evolution is predictable. We first define predictable and then discuss two conflicting views: that evolution is inherently unpredictable and that evolution is predictable given the ability to collect the right data. We identify factors that generate unpredictability, the data that might be required to make predictions at some level of precision or at a specific timescale, and the intellectual and translational value of understanding when prediction is or is not possible.

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.

Theory predicts plants grow roots to compete with only their closest neighbours.

The combination of individual-based selection with shared access to resources drives individuals to invest more than necessary in taking up their share of resources due to the threat of other individuals doing the same (competitive overinvestments). This evolutionary escalation of investment is common, from deer antlers and peacock feathers to tree height and plant roots. Because plant roots seem to be well intermingled belowground, the simplifying assumption that belowground resources are perfectly well mixed is often made in models-a condition that favours maximal fine-root overinvestments. Here, I develop simple models to investigate the role of space in determining the overlap among individuals belowground and resulting fine-root biomass. Without costs of growing roots through space, evolutionary optimization leads individuals to intermingle their fine roots perfectly and to invest just as much in these roots, whether there are two individuals competing or many. However, if there are any costs of sending roots through soil, investment in fine roots is constrained in amount and spatial extent. Dominant individuals are those that keep their roots in the soil closest to their own stem and the stems of their closest neighbours. These results highlight the importance of space in determining individual strategies as well as competitive networks.

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.

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.

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 .

Tree demographic strategies largely overlap across succession in Neotropical wet and dry forest communities.

Secondary tropical forests play an increasingly important role in carbon budgets and biodiversity conservation. Understanding successional trajectories is therefore imperative for guiding forest restoration and climate change mitigation efforts. Forest succession is driven by the demographic strategies-combinations of growth, mortality and recruitment rates-of the tree species in the community. However, our understanding of demographic diversity in tropical tree species stems almost exclusively from old-growth forests. Here, we assembled demographic information from repeated forest inventories along chronosequences in two wet (Costa Rica, Panama) and two dry (Mexico) Neotropical forests to assess whether the ranges of demographic strategies present in a community shift across succession. We calculated demographic rates for >500 tree species while controlling for canopy status to compare demographic diversity (i.e., the ranges of demographic strategies) in early successional (0-30 years), late successional (30-120 years) and old-growth forests using two-dimensional hypervolumes of pairs of demographic rates. Ranges of demographic strategies largely overlapped across successional stages, and early successional stages already covered the full spectrum of demographic strategies found in old-growth forests. An exception was a group of species characterized by exceptionally high mortality rates that was confined to early successional stages in the two wet forests. The range of demographic strategies did not expand with succession. Our results suggest that studies of long-term forest monitoring plots in old-growth forests, from which most of our current understanding of demographic strategies of tropical tree species is derived, are surprisingly representative of demographic diversity in general, but do not replace the need for further studies in secondary forests.

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.

Life history, nest longevity, sex ratio, and nest architecture of the fungus-growing ant Mycetosoritis hartmanni (Formicidae: Attina).

Mycetosoritis hartmanni is a rarely collected fungus-farming ant of North America. We describe life history and nest architecture for a M. hartmanni population in central Texas, USA. Colonies are monogynous with typically less than 100 workers (average 47.6 workers, maximum 148 workers). Nests occur always in sand and have a uniform architecture with 1-3 underground garden chambers arranged along a vertical tunnel, with the deepest gardens 50-70 cm deep. Foragers are active primarily between April and October. After reduced activity between November and February, egg laying by queens resumes in April, and the first worker pupae develop in early June. Reproductive females and males are reared primarily in July and August, with proportionally more females produced early in summer (protogyny). Mating flights and founding of new nests by mated females occur in late June to August, but may extend through September. For a cohort of 150 established nests (nests that had survived at least one year after nest founding), the estimated mortality rate was 0.41-0.53, the estimated average lifespan for these nests was 1.9-2.5 years, and the longest-living nests were observed to live for 6 years. These life-history parameters for M. hartmanni in central Texas are consistent with information from additional M. hartmanni nests observed throughout the range of this species from eastern Louisiana to southern Texas. Throughout its range in the USA, M. hartmanni can be locally very abundant in sun-exposed, sandy soil. Abundance of M. hartmanni seems so far relatively unaffected by invasive fire ants, and at present M. hartmanni does not appear to be an endangered species.

Demographic synthesis for global tree species conservation.

Conserving the tree species of the world requires syntheses on which tree species are most vulnerable to pressing threats, such as climate change, invasive pests and pathogens, or selective logging. Here, we review the population and forest dynamics models that, when parameterized with data from population studies, forest inventories, or tree rings, have been used for identifying life-history strategies of species and threat-related changes in population demography and dynamics. The available evidence suggests that slow-growing and/or long-lived species are the most vulnerable. However, a lack of comparative, multi-species studies still challenges more precise predictions of the vulnerability of tree species to threats. Improving data coverage for mortality and recruitment, and accounting for interactions among threats, would greatly advance vulnerability assessments for conservation prioritizations of trees worldwide.

The early life of a leaf-cutter ant colony constrains symbiont vertical transmission and favors horizontal transmission.

Colonial organisms host a large diversity of symbionts (collectively, parasites, mutualists, and commensals) that use vertical transmission (from parent colony to offspring colony) and/or horizontal transmission to disperse between host colonies. The early life of some colonies, characterized by the dispersal and establishment of solitary individuals, may constrain vertical transmission and favor horizontal transmission between large established colonies. We explore this possibility with the miniature cockroach Attaphila fungicola, a symbiont of leaf-cutter ants and the mutualist fungal gardens they cultivate. The early life of a leaf-cutter colony is characterized by the dispersal of a female alate (winged "queen") carrying a fungal pellet, and the subsequent establishment of a foundress (workerless "queen") raising her incipient fungal garden and colony. Roaches hitchhike on female alates during leaf-cutter nuptial flights, which strongly suggests that roaches are vertically transmitted to foundresses and their incipient colonies; however, weak compatibility between roaches and incipient gardens may constrain roach vertical transmission. Reciprocally, opportunities for horizontal transmission between large established colonies with abundant fungal gardens may weaken selection against roach-induced harm (virulence) of incipient gardens. We use a laboratory experiment, behavioral observations, field surveys, and a transmission model to estimate the effect roaches have on the survivorship of incipient gardens and the frequency of roach vertical transmission. Contrary to traditional assumptions, our results indicate that roaches harm incipient gardens and predominantly use horizontal transmission between established leaf-cutter colonies. Ultimately, "costs of generalism" associated with infecting disparate stages of a host's lifecycle (e.g., incipient vs. established colonies) may constrain the vertical transmission of roaches and a broad range of symbionts.

Predator complementarity dampens variability of phytoplankton biomass in a diversity-stability trophic cascade.

Trophic cascades - indirect effects of predators that propagate down through food webs - have been extensively documented in many ecosystem types. It has also been shown that predator diversity can mediate these trophic cascades and, separately, that herbivore biomass can influence the stability of primary producers. However, whether predator diversity can cause cascading effects on the stability of lower trophic levels has not yet been studied. We conducted a laboratory microcosm experiment and a field mesocosm experiment manipulating the presence and coexistence of two heteropteran predators and measuring their effects on zooplankton herbivores and phytoplankton basal resources. We predicted that if the predators partitioned their zooplankton prey, for example by size, then the co-presence of the predators would reduce zooplankton prey mass and lead to (1) increased biomass of, and (2) decreased temporal variability of phytoplankton basal resources. We present evidence that the predators partitioned their zooplankton prey, leading to a synergistic suppression of zooplankton. In turn, this enhanced zooplankton suppression led to only a weak, non-significant increase in the central tendency of phytoplankton biomass, but significantly reduced its variability. Our results demonstrate that predator diversity may indirectly stabilize basal resource biomass via a "diversity-stability trophic cascade," seemingly dependent on predator complementarity, even when there is no significant classic trophic cascade altering the central tendency of biomass. Therefore predator diversity, especially if correlated with diversity of prey use, could play a role in regulating ecosystem stability. This link between predator diversity and producer stability has implications for conservation and for potential biological control methods to improve crop yield reliability.

Multidimensional tropical forest recovery.

Tropical forests disappear rapidly because of deforestation, yet they have the potential to regrow naturally on abandoned lands. We analyze how 12 forest attributes recover during secondary succession and how their recovery is interrelated using 77 sites across the tropics. Tropical forests are highly resilient to low-intensity land use; after 20 years, forest attributes attain 78% (33 to 100%) of their old-growth values. Recovery to 90% of old-growth values is fastest for soil (<1 decade) and plant functioning (<2.5 decades), intermediate for structure and species diversity (2.5 to 6 decades), and slowest for biomass and species composition (>12 decades). Network analysis shows three independent clusters of attribute recovery, related to structure, species diversity, and species composition. Secondary forests should be embraced as a low-cost, natural solution for ecosystem restoration, climate change mitigation, and biodiversity conservation.

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.

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.