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

Species' traits do not converge on optimum values in preferred habitats

Plant trait expression is shaped by filters, which can alter trait means and variances, theoretically driving species toward an "optimum" trait value for a set of environmental conditions. Recent research has highlighted the ubiquity of intraspecific variation in functional traits, which can cause plants to diverge from a hypothesized "optimum". We examined whether species occurring in "core" habitats (where they occur frequently, abundantly, and consistently) express traits that are nearer to "optimum", as captured by the community-weighted mean (CWM). We also asked whether trait variance showed signs of environmental filtering. We used cluster analysis to group plots based on environmental factors along a wet-to-dry ecotone. We used indicator species analysis to identify species with strong associations within each cluster. Trait means and variances were compared, and evidence of variance filtering was tested using a null-model approach. Trait means and trait variances respond to local-scale environmental filtering and species in core habitats were not necessarily nearer to the CWM than in other habitats. Intraspecific trait variability shows a strong signal of filtering, as variability was reduced for nearly all species and all traits compared to estimates of variability generated in the absence of environmental filtering. Our results provide strong evidence that species traits are not necessarily near "optimum" trait values in core habitats, and that trait distributions within species are strongly shaped by the environment. Future analyses should account for this divergence when calculating metrics of functional diversity, and extrapolating to ecosystem function.

Traits Without Borders: Integrating Functional Diversity Across Scales

Owing to the conceptual complexity of functional diversity (FD), a multitude of different methods are available for measuring it, with most being operational at only a small range of spatial scales. This causes uncertainty in ecological interpretations and limits the potential to generalize findings across studies or compare patterns across scales. We solve this problem by providing a unified framework expanding on and integrating existing approaches. The framework, based on trait probability density (TPD), is the first to fully implement the Hutchinsonian concept of the niche as a probabilistic hypervolume in estimating FD. This novel approach could revolutionize FD-based research by allowing quantification of the various FD components from organismal to macroecological scales, and allowing seamless transitions between scales.

Phylogenetic turnover during subtropical forest succession across environmental and phylogenetic scales

Although spatial and temporal patterns of phylogenetic community structure during succession are inherently interlinked and assembly processes vary with environmental and phylogenetic scales, successional studies of community assembly have yet to integrate spatial and temporal components of community structure, while accounting for scaling issues. To gain insight into the processes that generate biodiversity after disturbance, we combine analyses of spatial and temporal phylogenetic turnover across phylogenetic scales, accounting for covariation with environmental differences. We compared phylogenetic turnover, at the species- and individual-level, within and between five successional stages, representing woody plant communities in a subtropical forest chronosequence. We decomposed turnover at different phylogenetic depths and assessed its covariation with between-plot abiotic differences. Phylogenetic turnover between stages was low relative to species turnover and was not explained by abiotic differences. However, within the late-successional stages, there was high presence-/absence-based turnover (clustering) that occurred deep in the phylogeny and covaried with environmental differentiation. Our results support a deterministic model of community assembly where (i) phylogenetic composition is constrained through successional time, but (ii) toward late succession, species sorting into preferred habitats according to niche traits that are conserved deep in phylogeny, becomes increasingly important.

Trait-abundance relation in response to nutrient addition in a Tibetan alpine meadow: The importance of species trade-off in resource conservation and acquisition

In competition‐dominated communities, traits promoting resource conservation and competitive ability are expected to have an important influence on species relative abundance (SRA). Yet, few studies have tested the trait‐abundance relations in the line of species trade‐off in resource conservation versus acquisition, indicating by multiple traits coordination. We measured SRA and key functional traits involving leaf economic spectrum (SLA, specific leaf area; LDMC, leaf dry matter content; LCC, leaf carbon concentration; LNC, leaf nitrogen concentration; LPC, leaf phosphorus concentration; Hs, mature height) for ten common species in all plots subjected to addition of nitrogen fertilizer (N), phosphorus fertilizer (P), or both of them (NP) in a Tibetan alpine meadow. We test whether SRA is positively related with traits promoting plant resource conservation, while negatively correlated with traits promoting plant growth and resource acquisition. We found that species were primarily differentiated along a trade‐off axis involving traits promoting nutrient acquisition and fast growth (e.g., LPC and SLA) versus traits promoting resource conservation and competition ability (e.g., large LDMC). We further found that SRA was positively correlated with plant height, LDMC, and LCC, but negatively associated with SLA and leaf nutrient concentration irrespective of fertilization. A stronger positive height‐SRA was found in NP‐fertilized plots than in other plots, while negative correlations between SRA and SLA and LPC were found in N or P fertilized plots. The results indicate that species trade‐off in nutrient acquisition and resource conservation was a key driver of SRA in competition‐dominated communities following fertilization, with the linkage between SRA and traits depending on plant competition for specific soil nutrient and/or light availability. The results highlight the importance of competitive exclusion in plant community assembly following fertilization and suggest that abundant species in local communities become dominated at expense of growth while infrequent species hold an advantage in fast growth and dispersals to neighbor meta‐communities.

Species traits and connectivity constrain stochastic community re-assembly

All communities may re-assemble after disturbance. Predictions for re-assembly outcomes are, however, rare. Here we model how fish communities in an extremely variable Australian desert river re-assemble following episodic floods and drying. We apply information entropy to quantify variability in re-assembly and the dichotomy between stochastic and deterministic community states. Species traits were the prime driver of community state: poor oxygen tolerance, low dispersal ability, and high fecundity constrain variation in re-assembly, shifting assemblages towards more stochastic states. In contrast, greater connectivity, while less influential than the measured traits, results in more deterministic states. Ecology has long recognised both the stochastic nature of some re-assembly trajectories and the role of evolutionary and bio-geographic processes. Our models explicitly test the addition of species traits and landscape linkages to improve predictions of community re-assembly, and will be useful in a range of different ecosystems.

Demographic drivers of functional composition dynamics

Mechanisms of community assembly and ecosystem function are often analyzed using community-weighted mean trait values (CWMs). We present a novel conceptual framework to quantify the contribution of demographic processes (i.e., growth, recruitment, and mortality) to temporal changes in CWMs. We used this framework to analyze mechanisms of secondary succession in wet tropical forests in Mexico. Seed size increased over time, reflecting a trade-off between colonization by small seeds early in succession, to establishment by large seeds later in succession. Specific leaf area (SLA) and leaf phosphorus content decreased over time, reflecting a trade-off between fast growth early in succession vs. high survival late in succession. On average, CWM shifts were driven mainly (70%) by growth of surviving trees that comprise the bulk of standing biomass, then mortality (25%), and weakly by recruitment (5%). Trait shifts of growing and recruiting trees mirrored the CWM trait shifts, and traits of dying trees did not change during succession, indicating that these traits are important for recruitment and growth, but not for mortality, during the first 30 yr of succession. Identifying the demographic drivers of functional composition change links population dynamics to community change, and enhances insights into mechanisms of succession.

Comparing species interaction networks along environmental gradients

Knowledge of species composition and their interactions, in the form of interaction networks, is required to understand processes shaping their distribution over time and space. As such, comparing ecological networks along environmental gradients represents a promising new research avenue to understand the organization of life. Variation in the position and intensity of links within networks along environmental gradients may be driven by turnover in species composition, by variation in species abundances and by abiotic influences on species interactions. While investigating changes in species composition has a long tradition, so far only a limited number of studies have examined changes in species interactions between networks, often with differing approaches. Here, we review studies investigating variation in network structures along environmental gradients, highlighting how methodological decisions about standardization can influence their conclusions. Due to their complexity, variation among ecological networks is frequently studied using properties that summarize the distribution or topology of interactions such as number of links, connectance, or modularity. These properties can either be compared directly or using a procedure of standardization. While measures of network structure can be directly related to changes along environmental gradients, standardization is frequently used to facilitate interpretation of variation in network properties by controlling for some co-variables, or via null models. Null models allow comparing the deviation of empirical networks from random expectations and are expected to provide a more mechanistic understanding of the factors shaping ecological networks when they are coupled with functional traits. As an illustration, we compare approaches to quantify the role of trait matching in driving the structure of plant-hummingbird mutualistic networks, i.e. a direct comparison, standardized by null models and hypothesis-based metaweb. Overall, our analysis warns against a comparison of studies that rely on distinct forms of standardization, as they are likely to highlight different signals. Fostering a better understanding of the analytical tools available and the signal they detect will help produce deeper insights into how and why ecological networks vary along environmental gradients.

Reinterpreting maximum entropy in ecology: a null hypothesis constrained by ecological mechanism

Simplified mechanistic models in ecology have been criticised for the fact that a good fit to data does not imply the mechanism is true: pattern does not equal process. In parallel, the maximum entropy principle (MaxEnt) has been applied in ecology to make predictions constrained by just a handful of state variables, like total abundance or species richness. But an outstanding question remains: what principle tells us which state variables to constrain? Here we attempt to solve both problems simultaneously, by translating a given set of mechanisms into the state variables to be used in MaxEnt, and then using this MaxEnt theory as a null model against which to compare mechanistic predictions. In particular, we identify the sufficient statistics needed to parametrise a given mechanistic model from data and use them as MaxEnt constraints. Our approach isolates exactly what mechanism is telling us over and above the state variables alone.

Hierarchical filters determine community assembly of urban species pools

The majority of humanity now lives in cities or towns, with this proportion expected to continue increasing for the foreseeable future. As novel ecosystems, urban areas offer an ideal opportunity to examine multi-scalar processes involved in community assembly as well as the role of human activities in modulating environmental drivers of biodiversity. Although ecologists have made great strides in recent decades at documenting ecological relationships in urban areas, much remains unknown, and we still need to identify the major ecological factors, aside from habitat loss, behind the persistence or extinction of species and guilds of species in cities. Given this paucity of knowledge, there is an immediate need to facilitate collaborative, interdisciplinary research on the patterns and drivers of biodiversity in cities at multiple spatial scales. In this review, we introduce a new conceptual framework for understanding the filtering processes that mold diversity of urban floras and faunas. We hypothesize that the following hierarchical series of filters influence species distributions in cities: (1) regional climatic and biogeographical factors; (2) human facilitation; (3) urban form and development history; (4) socioeconomic and cultural factors; and (5) species interactions. In addition to these filters, life history and functional traits of species are important in determining community assembly and act at multiple spatial scales. Using these filters as a conceptual framework can help frame future research needed to elucidate processes of community assembly in urban areas. Understanding how humans influence community structure and processes will aid in the management, design, and planning of our cities to best support biodiversity.

Integrating ecological theories and traits in process-based modeling of macroinvertebrate community dynamics in streams

Predicting the composition and dynamics of communities is a challenging but useful task to efficiently support ecosystem management. Community ecology has developed a number of promising theories, including food webs, metabolic theory, ecological stoichiometry, and environmental filtering. Their joint implementation in a mechanistic modeling framework should help us to bring community ecology to a new level by improving its predictive abilities. One of the challenges lies in the proper consideration of model uncertainty. In this paper, we contribute to this challenging task by modeling the temporal dynamics of macroinvertebrate communities in a stream subjected to hydropeaking in Switzerland. To this end, we extended the mechanistic model Streambugs regarding flood-induced drift processes and the use of trait information to define performance filters. Model predictions without any calibration were in the right order of magnitude but did not reflect the dynamics of most of the invertebrate taxa well. Bayesian inference drastically improved the model fit. It revealed that a large share of total model output uncertainty can be attributed to observation errors, which exceeded model parameter uncertainty. Observed and simulated community-aggregated traits helped to identify and understand model deficits. The combination of different ecological theories and trait information in a single mechanistic modeling framework combined with Bayesian inference can thus help to predict responses of communities to environmental changes, which can support ecosystem management.

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.

Similarity of plant functional traits and aggregation pattern in a subtropical forest

The distribution of species and communities in relation to environmental heterogeneity is a central focus in ecology. Co-occurrence of species with similar functional traits is an indication that communities are determined in part by environmental filters. However, few studies have been designed to test how functional traits are selectively filtered by environmental conditions at local scales. Exploring the relationship between soil characteristics and plant traits is a step toward understanding the filtering hypothesis in determining plant distribution at local scale. Toward this end, we mapped all individual trees (diameter >1 cm) in a one-ha subtropical forest of China in 2007 and 2015. We measured topographic and detailed soil properties within the field site, as well as plant leaf functional traits and demographic rates of the seven most common tree species. A second one-ha study plot was established in 2015, to test and validate the general patterns that were drawn from first plot. We found that variation in species distribution at local scale can be explained by soil heterogeneity and plant functional traits. (From first plot). (1) Species dominant in habitats with high soil ammonium nitrogen and total phosphorus tended to have high specific leaf area (SLA) and relative growth rate (RGR). (2) Species dominant in low-fertility habitats tended to have high leaf dry matter content (LDMC), ratio of chlorophyll a and b (ratioab), and leaf thickness (LT). The hypothesis that functional traits are selected in part by environmental filters and determine plant distribution at local scale was confirmed by the data of the first plot and a second regional site showed similar species distribution patterns.

Trait dimensionality and population choice alter estimates of phenotypic dissimilarity

The ecological niche is a multi-dimensional concept including aspects of resource use, environmental tolerance, and interspecific interactions, and the degree to which niches overlap is central to many ecological questions. Plant phenotypic traits are increasingly used as surrogates of species niches, but we lack an understanding of how key sampling decisions affect our ability to capture phenotypic differences among species. Using trait data of ecologically distinct monkeyflower (Mimulus) congeners, we employed linear discriminant analysis to determine how (1) dimensionality (the number and type of traits) and (2) variation within species influence how well measured traits reflect phenotypic differences among species. We conducted analyses using vegetative and floral traits in different combinations of up to 13 traits and compared the performance of commonly used functional traits such as specific leaf area against other morphological traits. We tested the importance of intraspecific variation by assessing how population choice changed our ability to discriminate species. Neither using key functional traits nor sampling across plant functions and organs maximized species discrimination. When using few traits, vegetative traits performed better than combinations of vegetative and floral traits or floral traits alone. Overall, including more traits increased our ability to detect phenotypic differences among species. Population choice and the number of traits used had comparable impacts on discriminating species. We addressed methodological challenges that have undermined cross-study comparability of trait-based approaches. Our results emphasize the importance of sampling among-population trait variation and suggest that a high-dimensional approach may best capture phenotypic variation among species with distinct niches.

Predicting habitat affinities of herbaceous dicots to soil wetness based on physiological traits of drought tolerance

Background and Aims

Soil water availability is an important mechanism filtering plant species but the functional basis of this filtering in herbaceous dicots is poorly studied. The authors address three questions: Which physiological traits best predict different levels of drought tolerance or avoidance in herbaceous dicots? To what degree can species' habitat preferences along the gradient of soil moisture availability be predicted by their physiological responses to drought? What are the direct and indirect relationships between the physiological traits and how do they interact to determine the species' habitat preferences?

Methods

Twenty-five species of herbaceous dicots whose field distributions span a gradient of soil moisture from continually moist to dry were chosen. Under controlled conditions, watering was stopped in a treatment group, the plants were monitored until death of the above-ground tissues and compared with a control group watered at field capacity. Fourteen traits related to plant water economy were measured, including stomatal conductance, net photosynthesis and the visual wilting of leaves. Traits were then analysed using a cumulative link model and path analysis.

Key Results

Five physiological traits (stomatal conductance and net photosynthesis measured at soil field capacity, water use efficiency, stomatal conductance and soil water potential measured when leaves begin to wilt) related to the ability to acquire resources (when water is not limiting) or conserve water (when it is limiting) best predicted different levels of drought tolerance or avoidance in herbaceous dicots.

Conclusions

Species' habitat preferences can be fairly predicted by their physiological responses to drought ( R 2  = 0·48). Strong direct and indirect relationships between the five identified traits (plus net photosynthesis at wilting and the time until death) led to synergistic and antagonistic relationship in a path analysis model. To allow better prediction of species distributions along a wetness gradient, the next step would be to link these physiological traits to more accessible functional traits.

Predicting species establishment using absent species and functional neighborhoods

Species establishment within a community depends on their interactions with the local environment and resident community. Such environmental and biotic filtering is frequently inferred from functional trait and phylogenetic patterns within communities; these patterns may also predict which additional species can establish. However, differentiating between environmental and biotic filtering can be challenging, which may complicate establishment predictions. Creating a habitat‐specific species pool by identifying which absent species within the region can establish in the focal habitat allows us to isolate biotic filtering by modeling dissimilarity between the observed and biotically excluded species able to pass environmental filters. Similarly, modeling the dissimilarity between the habitat‐specific species pool and the environmentally excluded species within the region can isolate local environmental filters. Combined, these models identify potentially successful phenotypes and why certain phenotypes were unsuccessful. Here, we present a framework that uses the functional dissimilarity among these groups in logistic models to predict establishment of additional species. This approach can use multivariate trait distances and phylogenetic information, but is most powerful when using individual traits and their interactions. It also requires an appropriate distance‐based dissimilarity measure, yet the two most commonly used indices, nearest neighbor (one species) and mean pairwise (all species) distances, may inaccurately predict establishment. By iteratively increasing the number of species used to measure dissimilarity, a functional neighborhood can be chosen that maximizes the detection of underlying trait patterns. We tested this framework using two seed addition experiments in calcareous grasslands. Although the functional neighborhood size that best fits the community's trait structure depended on the type of filtering considered, selecting these functional neighborhood sizes allowed our framework to predict up to 50% of the variation in actual establishment from seed. These results indicate that the proposed framework may be a powerful tool for studying and predicting species establishment.

Tracking lags in historical plant species' shifts in relation to regional climate change

Can species shift their distributions fast enough to track changes in climate? We used abundance data from the 1950s and the 2000s in Wisconsin to measure shifts in the distribution and abundance of 78 forest-understory plant species over the last half-century and compare these shifts to changes in climate. We estimated temporal shifts in the geographic distribution of each species using vectors to connect abundance-weighted centroids from the 1950s and 2000s. These shifts in distribution reflect colonization, extirpation, and changes in abundance within sites, separately quantified here. We then applied climate analog analyses to compute vectors representing the climate change that each species experienced. Species shifted mostly to the northwest (mean: 49 ± 29 km) primarily reflecting processes of colonization and changes in local abundance. Analog climates for these species shifted even further to the northwest, however, exceeding species' shifts by an average of 90 ± 40 km. Most species thus failed to match recent rates of climate change. These lags decline in species that have colonized more sites and those with broader site occupancy, larger seed mass, and higher habitat fidelity. Thus, species' traits appear to affect their responses to climate change, but relationships are weak. As climate change accelerates, these lags will likely increase, potentially threatening the persistence of species lacking the capacity to disperse to new sites or locally adapt. However, species with greater lags have not yet declined more in abundance. The extent of these threats will likely depend on how other drivers of ecological change and interactions among species affect their responses to climate change.

Do community-weighted mean functional traits reflect optimal strategies?

The notion that relationships between community-weighted mean (CWM) traits (i.e. plot-level trait values weighted by species abundances) and environmental conditions reflect selection towards locally optimal phenotypes is challenged by the large amount of interspecific trait variation typically found within ecological communities. Reconciling these contrasting patterns is a key to advancing predictive theories of functional community ecology. We combined data on geographical distributions and three traits (wood density, leaf mass per area and maximum height) of 173 tree species in Puerto Rico. We tested the hypothesis that species are more likely to occur where their trait values are more similar to the local CWM trait values (the'CWM-optimality' hypothesis) by comparing species occurrence patterns (as a proxy for fitness) with the functional composition of forest plots across a precipitation gradient. While 70% of the species supported CWM-optimality for at least one trait, nearly 25% significantly opposed it for at least one trait, thereby contributing to local functional diversity. The majority (85%) of species that opposed CWM-optimality did so only for one trait and few species opposed CWM-optimality in multivariate trait space. Our study suggests that constraints to local functional variation act more strongly on multivariate phenotypes than on univariate traits.

Temperate rain forest species partition fine-scale gradients in light availability based on their leaf mass per area (LMA)

BACKGROUND AND AIMS

Ecologists are increasingly using plant functional traits to predict community assembly, but few studies have linked functional traits to species' responses to fine-scale resource gradients. In this study, it was tested whether saplings of woody species partition fine-scale gradients in light availability based on their leaf mass per area (LMA) in three temperate rain forests and one Mediterranean forest in southern Chile.

METHODS

LMA was measured under field conditions of all woody species contained in approx. 60 plots of 2 m² in each site, and light availability, computed as the gap light index (GLI), was determined. For each site, species' pairwise differences in mean LMA (Δ LMA) and abundance-weighted mean GLI (Δ light response) of 2 m² plots were calculated and it was tested whether they were positively related using Mantel tests, i.e. if species with different LMA values differed in their response to light availability. Additionally linear models were fitted to the relationship between plot-level mean LMA and GLI across plots for each site.

KEY RESULTS

A positive and significant relationship was found between species' pairwise differences in mean LMA and differences in light response across species for all temperate rain forests, but not for the Mediterranean forest. The results also indicated a significant positive interspecific link between LMA and light availability for all forests. This is in contrast to what is traditionally reported and to expectations from the leaf economics spectrum.

CONCLUSIONS

In environments subjected to light limitation, interspecific differences in a leaf trait (LMA) can explain the fine-scale partitioning of light availability gradients by woody plant species. This niche partitioning potentially facilitates species coexistence at the within-community level. The high frequency of evergreen shade-intolerant species in these forests may explain the positive correlation between light availability and LMA.

Relationships between functional diversity and aboveground biomass production in the Northern Tibetan alpine grasslands

Functional diversity, the extent of functional differences among species in a community, drives biodiversity–ecosystem function (BEF) relationships. Here, four species traits and aboveground biomass production (ABP) were considered. We used two community-wide measures of plant functional composition, (1) community weighted means of trait values (CWM) and (2) functional trait diversity based on Rao’s quadratic diversity (FD_Q) to evaluate the effects of functional diversity on the ABP in the Northern Tibetan alpine grasslands. Both species and functional diversity were positively related to the ABP. Functional trait composition had a larger predictive power for the ABP than species diversity and FD_Q, indicating a primary dependence of ecosystem property on the identity of dominant species in our study system. Multivariate functional diversity was ineffective in predicting ecosystem function due to the trade-offs among different traits or traits selection criterions. Our study contributes to a better understanding of the mechanisms driving the BEF relationships in stressed ecosystems, and especially emphasizes that abiotic and biotic factors affect the BEF relationships in alpine grasslands.

Summer dormancy, drought survival and functional resource acquisition strategies in California perennial grasses

BACKGROUND AND AIMS

Evidence suggests drought severity is increasing due to climate change, but strategies promoting severe drought survival in perennial grasses have been seldom explored. This is particularly true of summer dormancy, an adaptation common in summer-dry Mediterranean-type climates. In addition, though theory predicts superior drought survival results in lower potential productivity, studies rarely measure both drought survival and growth under optimal conditions.

METHODS

Physiological and functional ecological approaches were integrated to quantify interspecific variation in foliar and root traits in a suite of eight California perennial grass species. In a glasshouse experiment, summer dormancy, foliar functional trait variation, and seasonal growth and phenology under non-limiting water conditions and dehydration tolerance under progressive drought were quantified. In a second glasshouse study, root functional traits were quantified under non-limiting water conditions in rhizotrons.

KEY RESULTS

Summer dormancy was associated with higher dehydration tolerance, and negatively associated with traits conferring dehydration avoidance. Species with greater summer dormancy were characterized by greater springtime productivity, earlier reproduction, and a shallow and fine root system, which are indicative of dehydration escape. Summer dormancy was associated with an acquisitive, competitive functional strategy in spring, and a conservative strategy in summer.

CONCLUSIONS

Both the escape and acquisitive springtime strategies observed in summer dormant perennial taxa are typically associated with annual grasses. California grasslands were once dominated by perennial species, but have been overtaken by non-native Mediterranean annual grasses, which are expected to be further favoured by climate change. Owing to functional similarity with these exotic annuals, it is suggested that native summer dormant taxa may play an important ecological role in the future of both natural and restored California grasslands.

Comparing process-based and constraint-based approaches for modeling macroecological patterns

Ecological patterns arise from the interplay of many different processes, and yet the emergence of consistent phenomena across a diverse range of ecological systems suggests that many patterns may in part be determined by statistical or numerical constraints. Differentiating the extent to which patterns in a given system are determined statistically, and where it requires explicit ecological processes, has been difficult. We tackled this challenge by directly comparing models from a constraint-based theory, the Maximum Entropy Theory of Ecology (METE) and models from a process-based theory, the size-structured neutral theory (SSNT). Models from both theories were capable of characterizing the distribution of individuals among species and the distribution of body size among individuals across 76 forest communities. However, the SSNT models consistently yielded higher overall likelihood, as well as more realistic characterizations of the relationship between species abundance and average body size of conspecific individuals. This suggests that the details of the biological processes contain additional information for understanding community structure that are not fully captured by the METE constraints in these systems. Our approach provides a first step towards differentiating between process- and constraint-based models of ecological systems and a general methodology for comparing ecological models that make predictions for multiple patterns.

Occupancy and overlap in trait space along a successional gradient in Mediterranean old fields

PREMISE OF THE STUDY

Secondary succession is a worldwide phenomenon affecting plant communities. Studying functional variation during succession aids in understanding the mechanisms through which environmental shifts drive succession. We investigated changes in the functional space occupied by herbaceous communities during succession. Furthermore, since different traits are differently affected by environmental conditions, we asked how considering different sets of plant traits impacts those changes.

METHODS

Using a chronosequence of Mediterranean old fields (2-42 yr after abandonment), we analyzed shifts of the occupied functional space during succession, how the volume of occupied functional space varies compared with null expectations, and the functional overlap between communities of different successional status. We repeated these analyses considering (1) the leaf-height-seed functional dimensions separately and together and (2) different sets of traits representing those dimensions.

KEY RESULTS

From early to late succession, a shift toward nutrient conservative-light competitive species occurred. Functional strategies of mid-successional communities appeared more diverse than expected by chance and less diverse than expected for early and late communities. Early and middle stages overlapped the most. These patterns were generally robust to the choice of functional axes, though important trait-specific exceptions occurred.

CONCLUSIONS

We showed evidence for a well-defined history of successive dominance of different assembly mechanisms along succession, resulting in a generally stronger functional diversification in mid-succession. We also demonstrated that different traits typically grouped under one functional dimension can substantially affect the results, discouraging the use of surrogate traits from the same dimension.

The meaning of functional trait composition of food webs for ecosystem functioning

There is a growing interest in using trait-based approaches to characterize the functional structure of animal communities. Quantitative methods have been derived mostly for plant ecology, but it is now common to characterize the functional composition of various systems such as soils, coral reefs, pelagic food webs or terrestrial vertebrate communities. With the ever-increasing availability of distribution and trait data, a quantitative method to represent the different roles of animals in a community promise to find generalities that will facilitate cross-system comparisons. There is, however, currently no theory relating the functional composition of food webs to their dynamics and properties. The intuitive interpretation that more functional diversity leads to higher resource exploitation and better ecosystem functioning was brought from plant ecology and does not apply readily to food webs. Here we appraise whether there are interpretable metrics to describe the functional composition of food webs that could foster a better understanding of their structure and functioning. We first distinguish the various roles that traits have on food web topology, resource extraction (bottom-up effects), trophic regulation (top-down effects), and the ability to keep energy and materials within the community. We then discuss positive effects of functional trait diversity on food webs, such as niche construction and bottom-up effects. We follow with a discussion on the negative effects of functional diversity, such as enhanced competition (both exploitation and apparent) and top-down control. Our review reveals that most of our current understanding of the impact of functional trait diversity on food web properties and functioning comes from an over-simplistic representation of network structure with well-defined levels. We, therefore, conclude with propositions for new research avenues for both theoreticians and empiricists.

Predicting the Responses of Soil Nitrite-Oxidizers to Multi-Factorial Global Change: A Trait-Based Approach

Soil microbial diversity is huge and a few grams of soil contain more bacterial taxa than there are bird species on Earth. This high diversity often makes predicting the responses of soil bacteria to environmental change intractable and restricts our capacity to predict the responses of soil functions to global change. Here, using a long-term field experiment in a California grassland, we studied the main and interactive effects of three global change factors (increased atmospheric CO₂ concentration, precipitation and nitrogen addition, and all their factorial combinations, based on global change scenarios for central California) on the potential activity, abundance and dominant taxa of soil nitrite-oxidizing bacteria (NOB). Using a trait-based model, we then tested whether categorizing NOB into a few functional groups unified by physiological traits enables understanding and predicting how soil NOB respond to global environmental change. Contrasted responses to global change treatments were observed between three main NOB functional types. In particular, putatively mixotrophic Nitrobacter, rare under most treatments, became dominant under the ‘High CO₂+Nitrogen+Precipitation’ treatment. The mechanistic trait-based model, which simulated ecological niches of NOB types consistent with previous ecophysiological reports, helped predicting the observed effects of global change on NOB and elucidating the underlying biotic and abiotic controls. Our results are a starting point for representing the overwhelming diversity of soil bacteria by a few functional types that can be incorporated into models of terrestrial ecosystems and biogeochemical processes.

Modelling the multidimensional niche by linking functional traits to competitive performance

Linking competitive outcomes to environmental conditions is necessary for understanding species' distributions and responses to environmental change. Despite this importance, generalizable approaches for predicting competitive outcomes across abiotic gradients are lacking, driven largely by the highly complex and context-dependent nature of biotic interactions. Here, we present and empirically test a novel niche model that uses functional traits to model the niche space of organisms and predict competitive outcomes of co-occurring populations across multiple resource gradients. The model makes no assumptions about the underlying mode of competition and instead applies to those settings where relative competitive ability across environments correlates with a quantifiable performance metric. To test the model, a series of controlled microcosm experiments were conducted using genetically related strains of a widespread microbe. The model identified trait microevolution and performance differences among strains, with the predicted competitive ability of each organism mapped across a two-dimensional carbon and nitrogen resource space. Areas of coexistence and competitive dominance between strains were identified,and the predicted competitive outcomes were validated in approximately 95% of the pairings. By linking trait variation to competitive ability, our work demonstrates a generalizable approach for predicting and modelling competitive outcomes across changing environmental contexts.

Phenological variation of leaf functional traits within species

A basic assumption of the trait-based approach in plant ecology is that differences in functional trait values are greater between species than within species. We questioned this assumption by assessing (1) the relative extent of inter- and intraspecific leaf trait variation throughout a complete growing season (phenological variation) in a group of deciduous and evergreen woody species, and (2) whether species rankings based on leaf traits were maintained across the growing season. We analysed leaf mass per area (LMA) and leaf nutrient concentrations (C, N, P), including the C:N and N:P ratios. Intraspecific trait variation (ITV) due to phenology was significantly greater than interspecific variation for leaf N concentration on a mass basis (Nm; 68.90 %) and for the leaf C:N ratio (60.60 %), whereas interspecific variation was significantly higher than ITV for LMA (62.30 %) and for leaf C concentration on a mass (Cm) and area (Ca) basis (Cm 70.40 %; Ca 65.30 %). ITV was particularly low for LMA (<20 %). Species rankings were highly modified by phenology for a number of leaf traits (Pm, N:P ratio) but were relatively well conserved throughout the growing season for others (LMA, Nm). Patterns of ITV across the growing season differed significantly between deciduous and evergreen species for all traits except leaf P but did not vary between native and exotic species. Overall, our results show that intraspecific phenological variation in leaf traits may be similar to or greater than interspecific variation and that temporal patterns of ITV vary considerably among traits and species, especially for leaf nutrient concentrations, factors which can potentially affect quantitative interspecific relationships.

Similarity in the difference: changes in community functional features along natural and anthropogenic stress gradients

The effect of stressors on biodiversity can vary in relation to the degree to which biological communities have adapted over evolutionary time. We compared the responses of functional features of stream insect communities along chronic stress gradients with contrasting time persistence. Water salinity and land use intensification were used as examples of natural (long-term persistent) and anthropogenic (short-term persistent) stressors, respectively. A new trait-based approach was applied to quantify functional diversity components and functional redundancy within the same multidimensional space, using metrics at the taxon and community levels. We found similar functional responses along natural and anthropogenic stress gradients. In both cases, the mean taxon functional richness and functional similarity between taxa increased with stress, whereas community functional richness and functional redundancy decreased. Despite the differences in evolutionary persistence, both chronic stressors act as strong nonrandom environmental filters, producing convergent functional responses. These results can improve our ability to predict functional effects of novel stressors at ecoloiical and evolutionary scales.

Linking changes in community composition and function under climate change

Climate change is expected to directly alter the composition of communities and the functioning of ecosystems across the globe. Improving our understanding of links between biodiversity and ecosystem functioning across large spatial scales and rapid global change is a major priority to help identify management responses that will retain diverse, functioning systems. Here we address this challenge by linking projected changes in plant community composition and functional attributes (height, leaf area, seed mass) under climate change across Tasmania, Australia. Using correlative community-level modeling, we found that projected changes in plant community composition were not consistently related to projected changes in community mean trait values. In contrast, we identified specific mechanisms through which alternative combinations of projected functional and compositional change across Tasmania could be realized, including loss/replacement of functionally similar species (lowland grasslands/grassy woodlands) and loss of a small number of functionally unique species (lowland forests). Importantly, we demonstrate how these linked projections of change in community composition and functional attributes can be utilized to inform specific management actions that may assist in maintaining diverse, functioning ecosystems under climate change.