Distance decay of similarity,effects of environmental noise and ecological heterogeneity among species in the spatio‐temporal dynamics of a dispersal‐limited community

The joint spatial and temporal fluctuations in community structure may be due to dispersal, variation in environmental conditions, ecological heterogeneity among species and demographic stochasticity. These factors are not mutually exclusive, and their relative contribution towards shaping species abundance distributions and in causing species fluctuations have been hard to disentangle. To better understand community dynamics when the exchange of individuals between localities is very low, we studied the dynamics of the freshwater zooplankton communities in 17 lakes located in independent catchment areas, sampled at end of summer from 2002 to 2008 in Norway. We analysed the joint spatial and temporal fluctuations in the community structure by fitting the two‐dimensional Poisson lognormal model under a two‐stage sampling scheme. We partitioned the variance of the distribution of log abundance for a random species at a random time and location into components of demographic stochasticity, ecological heterogeneity among species, and independent environmental noise components for the different species. Non‐neutral mechanisms such as ecological heterogeneity among species (20%) and spatiotemporal variation in the environment (75%) explained the majority of the variance in log abundances. Overdispersion relative to Poisson sampling and demographic stochasticity had a small contribution to the variance (5%). Among a set of environmental variables, lake acidity was the environmental variable that was most strongly related to decay of community similarity in space and time.     

Non‐neutrality in forest communities: evolutionary and ecological determinants of tree species abundance distributions

The unified neutral theory of biodiversity and biogeography provides a promising framework that can be used to integrate stochastic and ecological processes operating in ecological communities. Based on a mechanistic non‐neutral model that incorporates density‐dependent mortality, we evaluated the deviation from a neutral pattern in tree species abundance distributions and explored the signatures of historical and ecological processes that have shaped forest biomes. We compiled a dataset documenting species abundance distributions in 1168 plots encompassing 16 973 tree species across tropical, temperate, and boreal forests. We tested whether deviations from neutrality of species abundance distributions vary with climatic and historical conditions, and whether these patterns differ among regions. Non‐neutrality in species abundance distributions was ubiquitous in tropical, temperate, and boreal forests, and regional differences in patterns of non‐neutrality were significant between biomes. Species abundance evenness/unevenness caused by negative density‐dependent or abiotic filtering effects had no clear macro‐scale climatic drivers, although temperature was non‐linearly correlated with species abundance unevenness on a global scale. These findings were not significantly biased by heterogeneity of plot data (the differences of plot area, measurement size, species richness, and the number of individuals sampled). Therefore, our results suggest that environmental filtering is not universally increasing from warm tropical to cold boreal forests, but might affect differently tree species assembly between and within biomes. Ecological processes generating particularly dominant species in local communities might be idiosyncratic or region‐specific and may be associated with geography and climate. Our study illustrates that stochastic dynamical models enable the analysis of the interplay of historical and ecological processes that influence community assemblies and the dynamics of biodiversity.     

Demographic stochasticity alters expected outcomes in experimental and simulated non‐neutral communities

Theory has shown that the effects of demographic stochasticity on communities may depend on the magnitude of fitness differences between species. In particular, it has been suggested that demographic stochasticity has the potential to significantly alter competitive outcomes when fitness differences are small (nearly neutral), but that it has negligible effects when fitness differences are large (highly non‐neutral). Here we test such theory experimentally and extend it to examine how demographic stochasticity affects exclusion frequency and mean densities of consumers in simple, but non‐neutral, consumer–resource communities. We used experimental microcosms of protists and rotifers feeding on a bacterial resource to test how varying absolute population sizes (a driver of demographic stochasticity) affected the probability of competitive exclusion of the weakest competitor. To explore whether demographic stochasticity could explain our experimental results, and to generalize beyond our experiment, we paired the experiment with a continuous‐time stochastic model of resource competition, which we simulated for 11 different fitness inequalities between competiting consumers. Consistent with theory, in both our experiments and our simulations we found that demographic stochasticity altered competitive outcomes in communities where fitness differences were small. However, we also found that demographic stochasticity alone could affect communities in other ways, even when fitness differences between competitors were large. Specifically, demographic stochasticity altered mean densities of both weak and strong competitors in experimental and simulated communities. These findings highlight how demographic stochasticity can change both competitive outcomes in non‐neutral communities and the processes underlying overall community dynamics.     

Assessing the relative importance of neutral stochasticity in ecological communities

A central current debate in community ecology concerns the relative importance of deterministic versus stochastic processes underlying community structure. However, the concept of stochasticity presents several profound philosophical, theoretical and empirical challenges, which we address here. The philosophical argument that nothing in nature is truly stochastic can be met with the following operational concept of neutral stochasticity in community ecology: change in the composition of a community (i.e. community dynamics) is neutrally stochastic to the degree that individual demographic events – birth, death, immigration, emigration – which cause such changes occur at random with respect to species identities. Empirical methods for identifying the stochastic component of community dynamics or structure include null models and multivariate statistics on observational species‐by‐site data (with or without environmental or trait data), and experimental manipulations of ‘stochastic’ species colonization order or relative densities and frequencies of competing species. We identify the fundamental limitations of each method with respect to its ability to allow inferences about stochastic community processes. Critical future needs include greater precision in articulating the link between results and ecological inferences, a comprehensive theoretical assessment of the interpretation of statistical analyses of observational data, and experiments focusing on community size and on natural variation in species colonization order. Synthesis Community structure and dynamics have often been described as being underlain by ‘stochastic’ or ‘neutral’ processes, but there is great confusion as to what exactly this means. We attempt to provide conceptual clarity by specifying precisely what focal ecological variable (e.g. species distributions, community composition, demography) is considered to be stochastic with respect to what other variables (e.g. other species' distributions, traits, environment) when using different empirical methods. We clarify what inferences can be drawn by different observational and experimental approaches, and we suggest future avenues of research to better understand the role of neutral stochasticity in community ecology.     

Analyzing tropical forest tree species abundance distributions using a nonneutral model and through approximate Bayesian inference

The neutral theory of biodiversity challenges the classical niche-based view of ecological communities, where species attributes and environmental conditions jointly determine community composition. Functional equivalence among species, as assumed by neutral ecological theory, has been recurrently falsified, yet many patterns of tropical tree communities appear consistent with neutral predictions. This may mean that neutral theory is a good first-approximation theory or that species abundance data sets contain too little information to reject neutrality. Here we present a simple test of neutrality based on species abundance distributions in ecological communities. Based on this test, we show that deviations from neutrality are more frequent than previously thought in tropical forest trees, especially at small spatial scales. We then develop a nonneutral model that generalizes Hubbell's dispersal-limited neutral model in a simple way by including one additional parameter of frequency dependence. We also develop a statistical method to infer the parameters of this model from empirical data by approximate Bayesian computation. In more than half of the permanent tree plots, we show that our new model fits the data better than does the neutral model. Finally, we discuss whether observed deviations from neutrality may be interpreted as the signature of environmental filtering on tropical tree species abundance distributions.     

A coalescence approach to spatial neutral ecology

Neutral models in ecology have attracted much attention in recent literature. They can provide considerable insight into the roles of non-species-specific factors (e.g. stochasticity, dispersal, speciation) on community dynamics but often require intensive simulations, particularly in spatial settings. Here, we clearly explain existing techniques for modelling spatially explicit neutral processes in ecology using coalescence. Furthermore, we present several novel extensions to these methods including procedures for dealing with system boundaries which enable improved investigation of the effects of dispersal. We also present a semi-analytical algorithm that calculates the expected species richness in a sample, for any speciation rate. By eliminating the effect of stochasticity in the speciation process, we reduce the variance in estimates of species richness. Our benchmarks show that the combination of existing coalescence theory and our extensions produces higher quality results in vastly shorter time scales than previously possible: years of simulation time are reduced to minutes. As an example application, we find parameters for a spatially explicit neutral model to approximate the species richness of a tropical forest dataset.     

Extinction–immigration dynamics lag behind environmental filtering in shaping the composition of tropical dry forests within a changing landscape

The impact of rapid habitat loss and fragmentation on biodiversity is a major issue. However, we still lack an integrative understanding of how these changes influence biodiversity dynamics over time. In this study, we investigate the effects of these changes in terms of both niche-based and neutral dynamics. We hypothesize that habitat loss has delayed effects on neutral immigration–extinction dynamics, while edge effects and environmental heterogeneity in habitat patches have rapid effects on niche-based dynamics. We analyzed taxonomic and functional composition of 100 tree communities in a tropical dry forest landscape of New-Caledonia subject to habitat loss and fragmentation. We designed an original, process-based simulation framework, and performed Approximate Bayesian Computation to infer the influence of niche-based and neutral processes. Then, we performed partial regressions to evaluate the relationships between inferred parameter values of communities and landscape metrics (distance to edge, patch area, and habitat amount around communities), derived from either recent or past (65 yr ago) aerial photographs, while controlling for the effect of soil and topography. We found that landscape structure influences both environmental filtering and immigration. Immigration rate was positively related to past habitat amount surrounding communities. In contrast, environmental filtering was mostly affected by present landscape structure and mainly influenced by edge vicinity and topography. Our results highlight that landscape changes have contrasting spatio-temporal influences on niche-based and neutral assembly dynamics. First, landscape-level habitat loss and community isolation reduce immigration and increase demographic stochasticity, resulting in slow decline of local species diversity and extinction debt. Second, recent edge creation affects environmental filtering, incurring rapid changes in community composition by favoring species with edge-adapted strategies. Our study brings new insights about temporal impacts of landscape changes on biodiversity dynamics. We stress that landscape history critically influences these dynamics and should be taken into account in conservation policies.     

Reconciling neutral community models and environmental filtering: theory and an empirical test

It is widely believed that the neutral theory of biodiversity cannot be used for parameter inference if the assumption of neutrality is not met. The goal of this work is to extend this neutral framework to quantify the intensity of recruitment limitation (limited dispersal plus environmental filtering) in natural species assemblages. We model several local communities as part of a larger metacommunity, and we assume that neutrality holds in each local community, but not in the metacommunity. The immigration rate m does not only reflect dispersal limitation into a given local community, but also the intensity of environmental filtering. We develop a novel statistical method to infer the immigration parameter m in each local community. Using simulated datasets, we show that m indeed depends on both dispersal limitation and on the intensity of environmental filtering. We then apply this method to a network of tropical tree plots in central Panama. Inferred recruitment rates m were positively correlated with the fraction of trees dispersed by mammals, and with annual rainfall, possibly due to a weaker environmental filtering as rainfall increases. Finally, m, as estimated from trees greater than 1 cm trunk diameter, were significantly larger than an estimation based on trees greater than 10 cm trunk diameter. This suggests a cumulative effect of environmental filtering upon trees throughout their ontogeny.     

A 7000‐year history of changing plant trait composition in an Amazonian landscape; the role of humans and climate

Tropical forests are shifting in species and trait composition, but the main underlying causes remain unclear because of the short temporal scales of most studies. Here, we develop a novel approach by linking functional trait data with 7000 years of forest dynamics from a fossil pollen record of Lake Sauce in the Peruvian Amazon. We evaluate how climate and human disturbances affect community trait composition. We found weak relationships between environmental conditions and traits at the taxon level, but strong effects for community‐mean traits. Overall, community‐mean traits were more responsive to human disturbances than to climate change; human‐induced erosion increased the dominance of dense‐wooded, non‐zoochorous species with compound leaves, and human‐induced fire increased the dominance of tall, zoochorous taxa with large seeds and simple leaves. This information can help to enhance our understanding of forest responses to past environmental changes, and improve predictions of future changes in tropical forest composition.     

Species synchrony and its drivers: neutral and nonneutral community dynamics in fluctuating environments

Independent species fluctuations are commonly used as a null hypothesis to test the role of competition and niche differences between species in community stability. This hypothesis, however, is unrealistic because it ignores the forces that contribute to synchronization of population dynamics. Here we present a mechanistic neutral model that describes the dynamics of a community of equivalent species under the joint influence of density dependence, environmental forcing, and demographic stochasticity. We also introduce a new standardized measure of species synchrony in multispecies communities. We show that the per capita population growth rates of equivalent species are strongly synchronized, especially when endogenous population dynamics are cyclic or chaotic, while their long-term fluctuations in population sizes are desynchronized by ecological drift. We then generalize our model to nonneutral dynamics by incorporating temporal and nontemporal forms of niche differentiation. Niche differentiation consistently decreases the synchrony of species per capita population growth rates, while its effects on the synchrony of population sizes are more complex. Comparing the observed synchrony of species per capita population growth rates with that predicted by the neutral model potentially provides a simple test of deterministic asynchrony in a community.     

Spatial autocorrelation analysis allows disentangling the balance between neutral and niche processes in metacommunities

One of the most popular approaches for investigating the roles of niche and neutral processes driving metacommunity patterns consists of partitioning variation in species data into environmental and spatial components. The logic is that the distance decay of similarity in communities is expected under neutral models. However, because environmental variation is often spatially structured, the decay could also be attributed to environmental factors that are missing from the analysis. Here, we use a spatial autocorrelation analysis protocol, previously developed to detect isolation‐by‐distance in allele frequencies, to evaluate patterns of species abundances under neutral dynamics. We show that this protocol can be linked with variation partitioning analyses. Moreover, in an attempt to test the neutral model, we derive three predictions to be applied both to original species abundances and to abundances predicted by a pure spatial model species abundances will be uncorrelated; Moran's I correlograms will reveal similar short‐distance autocorrelation patterns; an increasing degree of non‐neutrality will tend to generate patterns of correlation among abundances within groups of species with similar correlograms (i.e. within species with neutral and non‐neutral dynamics). We illustrate our protocol by analyzing spatial patterns in abundance of 28 terrestrially breeding anuran species from Central Amazonia. We recommend that researchers should investigate spatial autocorrelation patterns of abundances predicted by pure spatial models to identify similar patterns of spatial autocorrelation at short distances and lack of correlation between species abundances. Therefore, the hypothesis that spatial patterns in abundances are primarily due to pure neutral dynamics (rather than to missing spatiallystructured environmental factors) can be confirmed after taking environmental variables into account.     

Accounting for spatial autocorrelation in null models of tree species association

A commonly used null model for species association among forest trees is a well‐mixed community (WMC). A WMC represents a non‐spatial, or spatially implicit, model, in which species form nearest‐neighbor pairs at a rate equal to the product of their community proportions. WMC models assume that the outcome of random dispersal and demographic processes is complete spatial randomness (CSR) in the species’ spatial distributions. Yet, stochastic dispersal processes often lead to spatial autocorrelation (SAC) in tree species densities, giving rise to clustering, segregation, and other nonrandom patterns. Although methods exist to account for SAC in spatially‐explicit models, its impact on non‐spatial models often remains unaccounted for. To investigate the potential for SAC to bias tests based upon non‐spatial models, we developed a spatially‐heterogeneous (SH) modelling approach that incorporates measured levels of SAC. Using the mapped locations of individuals in a tropical tree community, we tested the hypothesis that the identity of nearest‐neighbors represents a random draw from neighborhood species pools. Correlograms of Moran's I confirmed that, for 50 of 51 dominant species, stem density was significantly autocorrelated over distances ranging from 50 to 200 m. The observed patterns of SAC were consistent with dispersal limitation, with most species occurring in distinct patches. For nearly all of the 106 species in the community, the frequency of pairwise association was statistically indistinguishable from that projected by the null models. However, model comparisons revealed that non‐spatial models more strongly underestimated observed species‐pair frequencies, particularly for conspecific pairs. Overall, the CSR models projected more significant facilitative interactions than did SH models, yielding a more liberal test of niche differences. Our results underscore the importance of accounting for stochastic spatial processes in tests of association, regardless of whether spatial or non‐spatial models are employed.     

Environmentally‐induced noise dampens and reddens with increasing trophic level in a complex food web

Stochastic variability of key abiotic factors including temperature, precipitation and the availability of light and nutrients greatly influences species’ ecological function and evolutionary fate. Despite such influence, ecologists have typically ignored the effect of abiotic stochasticity on the structure and dynamics of ecological networks. Here we help to fill that gap by advancing the theory of how abiotic stochasticity, in the form of environmental noise, affects the population dynamics of species within food webs. We do this by analysing an allometric trophic network model of Lake Constance subjected to positive (red), negative (blue), and non‐autocorrelated (white) abiotic temporal variability (noise) introduced into the carrying capacity of basal species. We found that, irrespective of the colour of the introduced noise, the temporal variability of the species biomass within the network both reddens (i.e. its positive autocorrelation increases) and dampens (i.e. the magnitude of variation decreases) as the environmental noise is propagated through the food web by its feeding interactions from the bottom to the top. The reddening reflects a buffering of the noise‐induced population variability by complex food web dynamics such that non‐autocorrelated oscillations of noise‐free deterministic dynamics become positively autocorrelated. Our research helps explain frequently observed red variability of natural populations by suggesting that ecological processing of environmental noise through food webs with a range of species’ body sizes reddens population variability in nature.     

Drivers of productivity and its temporal stability in a tropical tree diversity experiment

There is increasing evidence that mixed‐species forests can provide multiple ecosystem services at a higher level than their monospecific counterparts. However, most studies concerning tree diversity and ecosystem functioning relationships use data from forest inventories (under noncontrolled conditions) or from very young plantation experiments. Here, we investigated temporal dynamics of diversity–productivity relationships and diversity–stability relationships in the oldest tropical tree diversity experiment. Sardinilla was established in Panama in 2001, with 22 plots that form a gradient in native tree species richness of one‐, two‐, three‐ and five‐species communities. Using annual data describing tree diameters and heights, we calculated basal area increment as the proxy of tree productivity. We combined tree neighbourhood‐ and community‐level analyses and tested the effects of both species diversity and structural diversity on productivity and its temporal stability. General patterns were consistent across both scales indicating that tree–tree interactions in neighbourhoods drive observed diversity effects. From 2006 to 2016, mean overyielding (higher productivity in mixtures than in monocultures) was 25%–30% in two‐ and three‐species mixtures and 50% in five‐species stands. Tree neighbourhood diversity enhanced community productivity but the effect of species diversity was stronger and increased over time, whereas the effect of structural diversity declined. Temporal stability of community productivity increased with species diversity via two principle mechanisms: asynchronous responses of species to environmental variability and overyielding. Overyielding in mixtures was highest during a strong El Niño‐related drought. Overall, positive diversity–productivity and diversity–stability relationships predominated, with the highest productivity and stability at the highest levels of diversity. These results provide new insights into mixing effects in diverse, tropical plantations and highlight the importance of analyses of temporal dynamics for our understanding of the complex relationships between diversity, productivity and stability. Under climate change, mixed‐species forests may provide both high levels and high stability of production.     

Trophic interactions affect the population dynamics and risk of extinction of basal species in food webs

This paper addresses effects of trophic complexity on basal species, in a Lotka–Volterra model with stochasticity. We use simple food web modules, with three trophic levels, and expose every species to random environmental stochasticity and analyze (1) the effect of the position of strong trophic interactions on temporal fluctuations in basal species’ abundances and (2) the relationship between fluctuation patterns and extinction risk. First, the numerical simulations showed that basal species do not simply track the environment, i.e. species dynamics do not simply mirror the characteristics of the applied environmental stochasticity. Second, the extinction risk of species was related to the fluctuation patterns of the species.More specifically, we show (i) that despite being forced by random stochasticity without temporal autocorrelation (i.e. white noise), there is significant temporal autocorrelation in the time series of all basal species’ abundances (i.e. the spectra of basal species are red-shifted), (ii) the degree of temporal autocorrelation in basal species time series is affected by food web structure and (iii) the degree of temporal autocorrelation tend to be correlated to the extinction risks of basal species.Our results emphasize the role of food web structure and species interactions in modifying the response of species to environmental variability. To shed some light on the mechanisms we compare the observed pattern in abundances of basal species with analytically predicted patterns and show that the change in the predicted pattern due to the addition of strong trophic interactions is correlated to the extinction risk of the basal species. We conclude that much remain to be understood about the mechanisms behind the interaction among environmental variability, species interactions, population dynamics and vulnerability before we quantitatively can predict, for example, effects of climate change on species and ecological communities. Here, however, we point out a new possible approach for identifying species that are vulnerable to environmental stochasticity by checking the degree of temporal autocorrelation in the time series of species. Increased autocorrelation in population fluctuations can be an indication of increased extinction risk.     

A novel genealogical approach to neutral biodiversity theory

Current neutral theory in community ecology views local biodiversity as a result of the interplay between speciation, extinction and immigration. Simulations and a mean‐field approximation have been used to study this neutral theory. As simulations have limitations of convergence and the mean‐field approximation ignores dependencies between species’ abundances when applied to species‐abundance data, there is still no final conclusion whether the neutral theory or the traditional lognormal model describes community structure best. We present a novel analytical framework, based on the genealogy of individuals in the local community, to overcome the problems of previous approaches, and show, using Bayesian statistics, that the lognormal model provides a slightly better fit to the species‐abundance distribution of a much‐discussed tropical tree community. A key feature of our approach is that it shows the tight link between genetic and species diversity, which creates important perspectives to future integration of evolutionary and community ecological theory.     

Phylogenetic clustering increases with succession for lianas in a Chinese tropical montane rain forest

Previous research found that phylogenetic clustering increased with disturbance for tropical trees, suggesting that community assembly is mainly influenced by abiotic factors during early succession. Lianas are an important additional component of tropical forests, but their phylogenetic community structure has never been investigated. Unlike tropical trees, liana abundance is often high in disturbed forests and diversity can peak in old secondary forest. Therefore, phylogenetic structure along a disturbance gradient might also differ from tropical tree communities. Here we determined phylogenetic community structure of lianas along a disturbance gradient in a tropical montane forest in China, using the net relatedness index (NRI) from 100 equivalent phylogenies with varying branch length that were constructed using DNA‐barcode sequences. Three additional phylogenetic indices were also considered for comparison. When NRI was used as index phylogenetic clustering of liana communities decreased with decreasing tree basal area, suggesting that liana competitive interactions dominate during early succession, which is in contrast to the pattern reported for trees. Liana communities in mature forests, on the other hand, were phylogenetic clustered, which could be caused by dispersal limitation and/or environmental filtering. The three additional phylogenetic indices identified different, sometimes contradicting predictors of phylogenetic community structure, indicating that caution is needed when generalizing interpretations of studies based on a single phylogenetic community structure index. Our study provides a more nuanced picture of non‐random assembly along disturbance gradients by focusing on a non‐tree forest component.     

Frequent,low‐amplitude disturbances drive high tree turnover rates on a remote,cyclone‐prone Polynesian island

Aim How important are frequent, low‐intensity disturbances to tree community dynamics of a cyclone‐prone forest? We tested the following hypotheses concerning the ‘inter‐cataclysm’ period on a remote Polynesian island: (1) tree turnover would be high and recruitment rates would be significantly higher than mortality; (2) low‐intensity disturbance would result in a marginal increase in tree mortality in the short term; (3) turnover would vary among species and would be associated with plant traits linked to differences in life history; and (4) mortality and recruitment events would be spatially non‐random. Location Tutuila, a volcanic island in the Samoan Archipelago, Polynesia. Methods We censused the tree (stem diameter ≥ 10 cm) community in 3.9 ha of tropical forest three times over a 10‐year period, 1998–2008. We calculated annual mortality, recruitment and turnover rates for 36 tree species. We tested for non‐random spatial patterns and predictors of mortality, and non‐random spatial patterns of tree recruitment. A 2004 cyclone passing within 400 km allowed us to measure the effects of a non‐cataclysmic disturbance on vital rates. Results Annual turnover was 2.8% and annual recruitment was 3.6%; these are some of the highest rates in the tropics, and likely to be a response to a cyclone that passed < 50 km from Tutuila in 1991. Species turnover rates over 10 years were negatively correlated with wood specific gravity, and positively correlated with annual stem diameter increment. Mortality was spatially aggregated, and a function of site, species and an individual’s growth rate. Recruitment was highest on ground with low slope. The low‐magnitude cyclone disturbance in 2004 defoliated 29% of all trees, but killed only 1.8% of trees immediately and increased annual mortality over 5 years by 0.7%. Main conclusions The inter‐cataclysm period on Tutuila is characterized by frequent, low‐amplitude disturbances that promote high rates of tree recruitment and create a dynamic, non‐equilibrium or disturbed island disequilibrium tree community. Species with low wood density and fast growth rates have enhanced opportunities for recruitment between cataclysms, but also higher probabilities of dying. Our results suggest that increases in the frequency of cyclone activity could shift relative abundances towards disturbance‐specialist species and new forest turnover rates.     

A core‐transient framework for trait‐based community ecology: an example from a tropical tree seedling community

Trait‐based studies in community ecology have generally focused on the community as a unit where all species occur due to stochasticity, determinism or some mixture of the two. However, the processes governing population dynamics may vary greatly among species. We propose a core‐transient framework for trait‐based community studies where a core group of species has a strong link to the local environment while transient species have weaker responses to the environment. Consistent with the expectations of the framework, we found that common species exhibit clear linkages between performance and their environment and traits while rare species tend to have weaker or non‐significant relationships. Ultimately, trait‐based ecology should move beyond applying a set of processes to a community as a whole and towards quantifying inter‐specific variation in the drivers of population dynamics that ultimately scale up to determine community structure.