From plant traits to plant communities: a statistical mechanistic approach to biodiversity

Decreases in average bacterial community rRNA operon copy number during succession

Trait-based studies can help clarify the mechanisms driving patterns of microbial community assembly and coexistence. Here, we use a trait-based approach to explore the importance of rRNA operon copy number in microbial succession, building on prior evidence that organisms with higher copy numbers respond more rapidly to nutrient inputs. We set flasks of heterotrophic media into the environment and examined bacterial community assembly at seven time points. Communities were arrayed along a geographic gradient to introduce stochasticity via dispersal processes and were analyzed using 16 S rRNA gene pyrosequencing, and rRNA operon copy number was modeled using ancestral trait reconstruction. We found that taxonomic composition was similar between communities at the beginning of the experiment and then diverged through time; as well, phylogenetic clustering within communities decreased over time. The average rRNA operon copy number decreased over the experiment, and variance in rRNA operon copy number was lowest both early and late in succession. We then analyzed bacterial community data from other soil and sediment primary and secondary successional sequences from three markedly different ecosystem types. Our results demonstrate that decreases in average copy number are a consistent feature of communities across various drivers of ecological succession. Importantly, our work supports the scaling of the copy number trait over multiple levels of biological organization, ranging from cells to populations and communities, with implications for both microbial ecology and evolution.

Functional and environmental determinants of bark thickness in fire-free temperate rain forest communities

PREMISE OF THE STUDY

In fire-prone ecosystems, variation in bark thickness among species and communities has been explained by fire frequency; thick bark is necessary to protect cambium from lethal temperatures. Elsewhere this investment is deemed unnecessary, and thin bark is thought to prevail. However, in rain forest ecosystems where fire is rare, bark thickness varies widely among species and communities, and the causes of this variation remain enigmatic. We tested for functional explanations of bark thickness variation in temperate rain forest species and communities.

METHODS

We measured bark thickness in 82 tree species throughout New Zealand temperate rain forests that historically have experienced little fire and applied two complementary analyses. First, we examined correlations between bark traits and leaf habit, and leaf and stem traits. Second, we calculated community-weighted mean (CWM) bark thickness for 272 plots distributed throughout New Zealand to identify the environments in which thicker-barked communities occur.

KEY RESULTS

Conifers had higher size-independent bark thickness than evergreen angiosperms. Species with thicker bark or higher bark allocation coefficients were not associated with "slow economic" plant traits. Across 272 forest plots, communities with thicker bark occurred on infertile soils, and communities with thicker bark and higher bark allocation coefficients occurred in cooler, drier climates.

CONCLUSIONS

In non-fire-prone temperate rain forest ecosystems, investment in bark is driven by soil resources, cool minimum temperatures, and seasonal moisture stress. The role of these factors in fire-prone ecosystems warrants testing.

Spatial predictions at the community level: from current approaches to future frameworks

A fundamental goal of ecological research is to understand and model how processes generate patterns so that if conditions change, changes in the patterns can be predicted. Different approaches have been proposed for modelling species assemblage, but their use to predict spatial patterns of species richness and other community attributes over a range of spatial and temporal scales remains challenging. Different methods emphasize different processes of structuring communities and different goals. In this review, we focus on models that were developed for generating spatially explicit predictions of communities, with a particular focus on species richness, composition, relative abundance and related attributes. We first briefly describe the concepts and theories that span the different drivers of species assembly. A combination of abiotic processes and biotic mechanisms are thought to influence the community assembly process. In this review, we describe four categories of drivers: (i) historical and evolutionary, (ii) environmental, (iii) biotic, and (iv) stochastic. We discuss the different modelling approaches proposed or applied at the community level and examine them from different standpoints, i.e. the theoretical bases, the drivers included, the source data, and the expected outputs, with special emphasis on conservation needs under climate change. We also highlight the most promising novelties, possible shortcomings, and potential extensions of existing methods. Finally, we present new approaches to model and predict species assemblages by reviewing promising 'integrative frameworks' and views that seek to incorporate all drivers of community assembly into a unique modelling workflow. We discuss the strengths and weaknesses of these new solutions and how they may hasten progress in community-level modelling.

Commonness, rarity, and intraspecific variation in traits and performance in tropical tree seedlings

One of the few rules in ecology is that communities are composed of many rare and few common species. Trait-based investigations of abundance distributions have generally focused on species-mean trait values with mixed success. Here, using large tropical tree seedling datasets in China and Puerto Rico, we take an alternative approach that considers the magnitude of intraspecific variation in traits and growth as it relates to species abundance. We find that common species are less variable in their traits and growth. Common species also occupy core positions within community trait space indicating that they are finely tuned for the available conditions. Rare species are functionally peripheral and are likely transients struggling for success in the given environment. The work highlights the importance of considering intraspecific variation in trait-based ecology and demonstrates asymmetry in the magnitude of intraspecific variation among species is critical for understanding of how traits are related to abundance.

Extant-only comparative methods fail to recover the disparity preserved in the bird fossil record

Most extant species are in clades with poor fossil records, and recent studies of comparative methods show they have low power to infer even highly simplified models of trait evolution without fossil data. Birds are a well-studied radiation, yet their early evolutionary patterns are still contentious. The fossil record suggests that birds underwent a rapid ecological radiation after the end-Cretaceous mass extinction, and several smaller, subsequent radiations. This hypothesized series of repeated radiations from fossil data is difficult to test using extant data alone. By uniting morphological and phylogenetic data on 604 extant genera of birds with morphological data on 58 species of extinct birds from 50 million years ago, the "halfway point" of avian evolution, I have been able to test how well extant-only methods predict the diversity of fossil forms. All extant-only methods underestimate the disparity, although the ratio of within- to between-clade disparity does suggest high early rates. The failure of standard models to predict high early disparity suggests that recent radiations are obscuring deep time patterns in the evolution of birds. Metrics from different models can be used in conjunction to provide more valuable insights than simply finding the model with the highest relative fit.

Plant Functional Diversity Can Be Independent of Species Diversity: Observations Based on the Impact of 4-Yrs of Nitrogen and Phosphorus Additions in an Alpine Meadow

Past studies have widely documented the decrease in species diversity in response to addition of nutrients, however functional diversity is often independent from species diversity. In this study, we conducted a field experiment to examine the effect of nitrogen and phosphorus fertilization ((NH₄)₂ HPO₄) at 0, 15, 30 and 60 g m^-2 yr^-1 (F0, F15, F30 and F60) after 4 years of continuous fertilization on functional diversity and species diversity, and its relationship with productivity in an alpine meadow community on the Tibetan Plateau. To this purpose, three community-weighted mean trait values (specific leaf area, SLA; mature plant height, MPH; and seed size, SS) for 30 common species in each fertilization level were determined; three components of functional diversity (functional richness, FRic; functional evenness, FEve; and Rao’s index of quadratic entropy, FRao) were quantified. Our results showed that: (i) species diversity sharply decreased, but functional diversity remained stable with fertilization; (ii) community-weighted mean traits (SLA and MPH) had a significant increase along the fertilization level; (iii) aboveground biomass was not correlated with functional diversity, but it was significantly correlated with species diversity and MPH. Our results suggest that decreases in species diversity due to fertilization do not result in corresponding changes in functional diversity. Functional identity of species may be more important than functional diversity in influencing aboveground productivity in this alpine meadow community, and our results also support the mass ratio hypothesis; that is, the traits of the dominant species influenced the community biomass production.

Niche and Neutral Processes Together Determine Diversity Loss in Response to Fertilization in an Alpine Meadow Community

Fertilization via nutrient deposition and agricultural inputs is one of the most important factors driving decreases in plant diversity. However, we still do not fully understand which processes (niche process or neutral process) are more important in leading to decreases in plant diversity caused by fertilization. A hypothesis-based approach was used to test the relative importance of niche versus neutral processes along a fertilization gradient in an alpine meadow community on the eastern Tibetan plateau, China. Niche overlap values were calculated for species biomass, and the null model was used to generate the values of niche overlap expected at random. A linear regression modeling was used to evaluate the relationship between functional traits (specific leaf area, leaf dry matter content, and leaf total nitrogen concentration) and species relative abundance. Our results demonstrated that observed niche overlap for species biomass was significantly higher than expected at lower fertilization gradients. Moreover, we also found a significantly negative correlation between species relative abundance and specific leaf area and leaf dry matter content, but a significantly positive correlation between relative abundance and leaf nitrogen concentration at lower fertilization gradients. However, these relationships were not significant at higher fertilization gradients. We concluded that community assembly is dynamic progression along the environmental gradients, and niche and neutral processes may together determine species diversity loss in response to fertilization.

Population dynamics and competitive outcome derive from resource allocation statistics: The governing influence of the distinguishability of individuals

Model predictions for species competition outcomes highly depend on the assumed form of the population growth function. In this paper we apply an alternative inferential method based on statistical mechanics, maximizing Boltzmann entropy, to predict resource-constrained population dynamics and coexistence. Within this framework, population dynamics and competition outcome can be determined without assuming any particular form of the population growth function. The dynamics of each species is determined by two parameters: the mean resource requirement θ (related to the mean metabolic rate) and individual distinguishability Dr (related to intra- compared to interspecific functional variation). Our theory clarifies the condition for the energetic equivalence rule (EER) to hold, and provide a statistical explanation for the importance of species functional variation in determining population dynamics and coexistence patterns.

Predicting communities from functional traits

Species traits influence where species live and how they interact. While there have been many advances in describing the functional composition and diversity of communities, only recently do researchers have the ability to predict community composition and diversity. This predictive ability can offer fundamental insights into ecosystem resilience and restoration.

Predicting Changes in Macrophyte Community Structure from Functional Traits in a Freshwater Lake: A Test of Maximum Entropy Model

Trait-based approaches have been widely applied to investigate how community dynamics respond to environmental gradients. In this study, we applied a series of maximum entropy (maxent) models incorporating functional traits to unravel the processes governing macrophyte community structure along water depth gradient in a freshwater lake. We sampled 42 plots and 1513 individual plants, and measured 16 functional traits and abundance of 17 macrophyte species. Study results showed that maxent model can be highly robust (99.8%) in predicting the species relative abundance of macrophytes with observed community-weighted mean (CWM) traits as the constraints, while relative low (about 30%) with CWM traits fitted from water depth gradient as the constraints. The measured traits showed notably distinct importance in predicting species abundances, with lowest for perennial growth form and highest for leaf dry mass content. For tuber and leaf nitrogen content, there were significant shifts in their effects on species relative abundance from positive in shallow water to negative in deep water. This result suggests that macrophyte species with tuber organ and greater leaf nitrogen content would become more abundant in shallow water, but would become less abundant in deep water. Our study highlights how functional traits distributed across gradients provide a robust path towards predictive community ecology.

Fitness of multidimensional phenotypes in dynamic adaptive landscapes

Phenotypic traits influence species distributions, but ecology lacks established links between multidimensional phenotypes and fitness for predicting species responses to environmental change. The common focus on single traits rather than multiple trait combinations limits our understanding of their adaptive value, and intraspecific trait covariation has been neglected in ecology despite its importance in evolutionary theory and its likely impact on species distributions. Here, we extend the adaptive landscape framework to ecological sorting of multidimensional phenotypes across environments and discuss how two analytical approaches can be used to quantify fitness as a function of the interaction between the phenotype and the environment. We encourage ecologists to consider how phenotypic integration will constrain species responses to environmental change.

Framework for analyzing ecological trait-based models in multidimensional niche spaces

We develop a theoretical framework for analyzing ecological models with a multidimensional niche space. Our approach relies on the fact that ecological niches are described by sequences of symbols, which allows us to include multiple phenotypic traits. Ecological drivers, such as competitive exclusion, are modeled by introducing the Hamming distance between two sequences. We show that a suitable transform diagonalizes the community interaction matrix of these models, making it possible to predict the conditions for niche differentiation and, close to the instability onset, the asymptotically long time population distributions of niches. We exemplify our method using the Lotka-Volterra equations with an exponential competition kernel.

Soil disturbance as a grassland restoration measure-effects on plant species composition and plant functional traits

Soil disturbance is recognized as an important driver of biodiversity in dry grasslands, and can therefore be implemented as a restoration measure. However, because community re-assembly following disturbance includes stochastic processes, a focus only on species richness or establishment success of particular species will not inform on how plant communities respond ecologically to disturbance. We therefore evaluated vegetation development following disturbance by quantifying species richness, species composition and functional trait composition. Degraded calcareous sandy grassland was subjected to experimental disturbance treatments (ploughing or rotavation), and the vegetation was surveyed during four subsequent years of succession. Treated plots were compared with control plots representing untreated grassland, as well as nearby plots characterized by plant communities representing the restoration target. Species richness and functional diversity both increased in response to soil disturbance, and rotavation, but not ploughing, had a persistent positive effect on the occurrence of specialist species of calcareous sandy grassland. However, no type of soil disturbance caused the plant species composition to develop towards the target vegetation. The disturbance had an immediate and large impact on the vegetation, but the vegetation developed rapidly back towards the control sites. Plant functional composition analysis indicated that the treatments created habitats different both from control sites and target sites. Community-weighted mean Ellenberg indicator values suggested that the observed plant community response was at least partially due to an increase in nitrogen and water availability following disturbance. This study shows that a mild type of disturbance, such as rotavation, may be most successful in promoting specialist species in calcareous sandy grassland, but that further treatments are needed to reduce nutrient availability. We conclude that a functional trait based analysis provides additional information of the vegetation response and the abiotic conditions created, complementing the information from the species composition.

Explaining forest productivity using tree functional traits and phylogenetic information: two sides of the same coin over evolutionary scale?

Given evidences that diverse ecosystems provide more services than depauperate ones, much attention has now turned toward finding meaningful and operational diversity indices. We ask two questions: (1) Does phylogenetic diversity contain additional information not explained by functional traits? And (2) What are the strength and nature of the correlation between phylogeny and functional traits according to the evolutionary scale considered? We used data from permanent forest plots of northeastern Canada for which these links have been demonstrated and important functional traits identified. We show that the nature of the relationship between traits and phylogeny varies dramatically among traits, but also according to the evolutionary distance considered. The demonstration that different characters show phylogenetic autocorrelation at different evolutionary depths suggests that phylogenetic content of traits may be too crude to determine whether phylogenies contain relevant information. However, our study provides support for the use of phylogenies to assess ecosystem functioning when key functional traits are unavailable. We also highlight a potentially important contribution of phylogenetics for conservation and the study of the impact of biodiversity loss on ecosystem functioning and the provision of services, given the accumulating evidence that mechanisms promoting diversity effects shift over time to involve different traits.

Community functional responses to soil and climate at multiple spatial scales: when does intraspecific variation matter?

Despite increasing evidence of the importance of intraspecific trait variation in plant communities, its role in community trait responses to environmental variation, particularly along broad-scale climatic gradients, is poorly understood. We analyzed functional trait variation among early-successional herbaceous plant communities (old fields) across a 1200-km latitudinal extent in eastern North America, focusing on four traits: vegetative height, leaf area, specific leaf area (SLA), and leaf dry matter content (LDMC). We determined the contributions of species turnover and intraspecific variation to between-site functional dissimilarity at multiple spatial scales and community trait responses to edaphic and climatic factors. Among-site variation in community mean trait values and community trait responses to the environment were generated by a combination of species turnover and intraspecific variation, with species turnover making a greater contribution for all traits. The relative importance of intraspecific variation decreased with increasing geographic and environmental distance between sites for SLA and leaf area. Intraspecific variation was most important for responses of vegetative height and responses to edaphic compared to climatic factors. Individual species displayed strong trait responses to environmental factors in many cases, but these responses were highly variable among species and did not usually scale up to the community level. These findings provide new insights into the role of intraspecific trait variation in plant communities and the factors controlling its relative importance. The contribution of intraspecific variation to community trait responses was greatest at fine spatial scales and along edaphic gradients, while species turnover dominated at broad spatial scales and along climatic gradients.

Does morphology predict trophic position and habitat use of ant species and assemblages?

A functional traits-based theory of organismal communities is critical for understanding the principles underlying community assembly, and predicting responses to environmental change. This is particularly true for terrestrial arthropods, of which only 20% are described. Using epigaeic ant assemblages, we asked: (1) can we use morphological variation among species to predict trophic position or preferred microhabitat; (2) does the strength of morphological associations suggest recent trait divergence; (3) do environmental variables at site scale predict trait sets for whole assemblages? We pitfall-trapped ants from a revegetation chronosequence and measured their morphology, trophic position [using C:N stoichiometry and stable isotope ratios (δ)] and characteristics of microhabitat and macrohabitat. We found strong associations between high trophic position (low C:N and high δ(15)N) in body tissue and morphological traits: predators were larger, had more laterally positioned eyes, more physical protection and tended to be monomorphic. In addition, morphological traits were associated with certain microhabitat features, e.g. smaller heads were associated with the bare ground microhabitat. Trait-microhabitat relationships were more pronounced when phylogenetic adjustments were used, indicating a strong influence of recent trait divergences. At the assemblage level, our fourth corner analysis revealed associations between the prevalence of traits and macrohabitat, although these associations were not the same as those based on microhabitat associations. This study shows direct links between species-level traits and both diet and habitat preference. Trait-based prediction of ecological roles and community structure is thus achievable when integrating stoichiometry, morphology and phylogeny, but scale is an important consideration in such predictions.

Maximum information entropy: a foundation for ecological theory

The maximum information entropy (MaxEnt) principle is a successful method of statistical inference that has recently been applied to ecology. Here, we show how MaxEnt can accurately predict patterns such as species-area relationships (SARs) and abundance distributions in macroecology and be a foundation for ecological theory. We discuss the conceptual foundation of the principle, why it often produces accurate predictions of probability distributions in science despite not incorporating explicit mechanisms, and how mismatches between predictions and data can shed light on driving mechanisms in ecology. We also review possible future extensions of the maximum entropy theory of ecology (METE), a potentially important foundation for future developments in ecological theory.

The microbial contribution to macroecology

There has been a recent explosion of research within the field of microbial ecology that has been fueled, in part, by methodological improvements that make it feasible to characterize microbial communities to an extent that was inconceivable only a few years ago. Furthermore, there is increasing recognition within the field of ecology that microorganisms play a critical role in the health of organisms and ecosystems. Despite these developments, an important gap still persists between the theoretical framework of macroecology and microbial ecology. We highlight two idiosyncrasies of microorganisms that are fundamental to understanding macroecological patterns and their mechanistic drivers. First, high dispersal rates provide novel opportunities to test the relative importance of niche, stochastic, and historical processes in structuring biological communities. Second, high speciation rates potentially lead to the convergence of ecological and evolutionary time scales. After reviewing these unique aspects, we discuss strategies for improving the conceptual integration of microbes into macroecology. As examples, we discuss the use of phylogenetic ecology as an integrative approach to explore patterns across the tree of life. Then we demonstrate how two general theories of biodiversity (i.e., the recently developed theory of stochastic geometry and the neutral theory) can be adapted to microorganisms. We demonstrate how conceptual models that integrate evolutionary and ecological mechanisms can contribute to the unification of microbial ecology and macroecology.

Applying trait-based models to achieve functional targets for theory-driven ecological restoration

Manipulating community assemblages to achieve functional targets is a key component of restoring degraded ecosystems. The response-and-effect trait framework provides a conceptual foundation for translating restoration goals into functional trait targets, but a quantitative framework has been lacking for translating trait targets into assemblages of species that practitioners can actually manipulate. This study describes new trait-based models that can be used to generate ranges of species abundances to test theories about which traits, which trait values and which species assemblages are most effective for achieving functional outcomes. These models are generalisable, flexible tools that can be widely applied across many terrestrial ecosystems. Examples illustrate how the framework generates assemblages of indigenous species to (1) achieve desired community responses by applying the theories of environmental filtering, limiting similarity and competitive hierarchies, or (2) achieve desired effects on ecosystem functions by applying the theories of mass ratios and niche complementarity. Experimental applications of this framework will advance our understanding of how to set functional trait targets to achieve the desired restoration goals. A trait-based framework provides restoration ecology with a robust scaffold on which to apply fundamental ecological theory to maintain resilient and functioning ecosystems in a rapidly changing world.

Toward quantitative understanding on microbial community structure and functioning: a modeling-centered approach using degradation of marine oil spills as example

Molecular ecology approaches are rapidly advancing our insights into the microorganisms involved in the degradation of marine oil spills and their metabolic potentials. Yet, many questions remain open: how do oil-degrading microbial communities assemble in terms of functional diversity, species abundances and organization and what are the drivers? How do the functional properties of microorganisms scale to processes at the ecosystem level? How does mass flow among species, and which factors and species control and regulate fluxes, stability and other ecosystem functions? Can generic rules on oil-degradation be derived, and what drivers underlie these rules? How can we engineer oil-degrading microbial communities such that toxic polycyclic aromatic hydrocarbons are degraded faster? These types of questions apply to the field of microbial ecology in general. We outline how recent advances in single-species systems biology might be extended to help answer these questions. We argue that bottom-up mechanistic modeling allows deciphering the respective roles and interactions among microorganisms. In particular constraint-based, metagenome-derived community-scale flux balance analysis appears suited for this goal as it allows calculating degradation-related fluxes based on physiological constraints and growth strategies, without needing detailed kinetic information. We subsequently discuss what is required to make these approaches successful, and identify a need to better understand microbial physiology in order to advance microbial ecology. We advocate the development of databases containing microbial physiological data. Answering the posed questions is far from trivial. Oil-degrading communities are, however, an attractive setting to start testing systems biology-derived models and hypotheses as they are relatively simple in diversity and key activities, with several key players being isolated and a high availability of experimental data and approaches.

Statistical thermodynamics concepts and mathematical tools for a multi-agent ecosystem

Finding the distribution of systems over their possible states is a mathematical problem. One possible solution is the method of the most probable distribution developed by Boltzmann. This method has been instrumental in developing statistical mechanics and explaining the origin of many thermodynamics concepts, like entropy or temperature, but is also applicable in many other fields like ecology or economics. Artificial ecosystems have many features in common with ecological or economic systems, but surprisingly the method does not appear to have been very successful in this field of application. The hypothesis of this article is that this failure is due to the incorrect interpretation of the method's concepts and mathematical tools. We propose to review and reinterpret the method so that it can be correctly applied and all its potential exploited in order to study and characterize the global behavior of an artificial multi-agent ecosystem.

Characterizing scale-dependent community assembly using the functional-diversity--area relationship

Phenotypic traits mediate organisms' interactions with the environment and determine how they affect and are affected by their biotic and abiotic milieu. Thus, dispersion of trait values, or functional diversity (FD) of a community can offer insights into processes driving community assembly. For example, underdispersion of FD suggests that habitat "filtering" of species with unfavorable trait values restricts the species that can exist in a particular habitat, while even spacing of FD suggests that interspecific competition, or biotic "sorting," discourages the coexistence of species with similar trait values. Since assembly processes are expected to vary as a function of spatial scale, we should also expect patterns of FD to reflect scale dependence in filtering and biotic sorting. Here we present the concept of the functional-diversity-area relationship (FAR), which is similar to the species-area relationship but plots a measure of phenotypic trait diversity as a function of spatial scale. We develop a set of null model tests that discriminate between FARs generated predominantly by filtering or biotic sorting and indicate the scales at which these effects are pronounced. The utility of the FAR for addressing long-standing issues in ecology is illustrated with several examples. A multi-scale examination of FD and its pattern relative to null expectations provides an important tool for ecologists interested in understanding the scale dependence of community assembly processes.

Statistical patterns in tropical tree cover explained by the different water demand of individual trees and grasses

Tree cover varies enormously across tropical ecosystems-from arid savannas to closed rain forests-and yet a general predictive theory of tropical tree cover remains elusive. Here we use the maximum-entropy method to predict the most likely sample frequency distribution of ecosystems with different tree and grass fractional cover if balance between water supply and demand were the dominant constraint on community assembly. Assuming a hierarchy of individual plant water demand in which trees require more water than grasses, we reproduce observed trends in the means and the upper and lower limits of tropical tree and grass cover across the entire spectrum of tropical ecosystem water supply. Finer details not captured by our predictions indicate the influence of additional factors, such as disturbance. Our results challenge the view that tropical tree-grass coexistence is largely sustained by disturbances in moist environments ("unstable" coexistence) with water supply playing a dominant role only in arid conditions ("stable" coexistence). More generally, they suggest that macroecological patterns can be understood and predicted as the most likely outcome of a large number of stochastic processes being played out within a relatively small number of ecological constraints.

Functional traits explain variation in plant life history strategies

Ecologists seek general explanations for the dramatic variation in species abundances in space and time. An increasingly popular solution is to predict species distributions, dynamics, and responses to environmental change based on easily measured anatomical and morphological traits. Trait-based approaches assume that simple functional traits influence fitness and life history evolution, but rigorous tests of this assumption are lacking, because they require quantitative information about the full lifecycles of many species representing different life histories. Here, we link a global traits database with empirical matrix population models for 222 species and report strong relationships between functional traits and plant life histories. Species with large seeds, long-lived leaves, or dense wood have slow life histories, with mean fitness (i.e., population growth rates) more strongly influenced by survival than by growth or fecundity, compared with fast life history species with small seeds, short-lived leaves, or soft wood. In contrast to measures of demographic contributions to fitness based on whole lifecycles, analyses focused on raw demographic rates may underestimate the strength of association between traits and mean fitness. Our results help establish the physiological basis for plant life history evolution and show the potential for trait-based approaches in population dynamics.

Advances in modeling trait-based plant community assembly

In this review, we examine two new trait-based models of community assembly that predict the relative abundance of species from a regional species pool. The models use fundamentally different mathematical approaches and the predictions can differ considerably. Maxent obtains the most even probability distribution subject to community-weighted mean trait constraints. Traitspace predicts low probabilities for any species whose trait distribution does not pass through the environmental filter. Neither model maximizes functional diversity because of the emphasis on environmental filtering over limiting similarity. Traitspace can test for the effects of limiting similarity by explicitly incorporating intraspecific trait variation. The range of solutions in both models could be used to define the range of natural variability of community composition in restoration projects.

Energy, ecology and the distribution of microbial life

Mechanisms that govern the coexistence of multiple biological species have been studied intensively by ecologists since the turn of the nineteenth century. Microbial ecologists in the meantime have faced many fundamental challenges, such as the lack of an ecologically coherent species definition, lack of adequate methods for evaluating population sizes and community composition in nature, and enormous taxonomic and functional diversity. The accessibility of powerful, culture-independent molecular microbiology methods offers an opportunity to close the gap between microbial science and the main stream of ecological theory, with the promise of new insights and tools needed to meet the grand challenges humans face as planetary engineers and galactic explorers. We focus specifically on resources related to energy metabolism because of their direct links to elemental cycling in the Earth's history, engineering applications and astrobiology. To what extent does the availability of energy resources structure microbial communities in nature? Our recent work on sulfur- and iron-oxidizing autotrophs suggests that apparently subtle variations in the concentration ratios of external electron donors and acceptors select for different microbial populations. We show that quantitative knowledge of microbial energy niches (population-specific patterns of energy resource use) can be used to predict variations in the abundance of specific taxa in microbial communities. Furthermore, we propose that resource ratio theory applied to micro-organisms will provide a useful framework for identifying how environmental communities are organized in space and time.