CATS regression – a model‐based approach to studying trait‐based community assembly

Tracking climate vulnerability across spatial distribution and functional traits in Magnolia gentryi in the Peruvian tropical montane cloud forest

PREMISE

Understanding the responses of functional traits in tree species to climate variability is essential for predicting the future of tropical montane cloud forest (TMCF) tree species, especially in Andean montane environments where fog pockets act as moisture traps.

METHODS

We studied the distribution of Magnolia gentryi, measured its spatial arrangement, identified local hotspots, and evaluated the extent to which climate-related factors are associated with its distribution. We then analyzed the variation in 13 functional traits of M. gentryi and the relationship with climate.

RESULTS

Andean TMCF climatic factors constrain M. gentryi spatial distribution with significant patches or gaps that are associated with high precipitation and mean minimum temperature. The functional traits of M. gentryi are limited by the Andean TMCF climatic factors, resulting in reduced within-species variation in traits associated with water deficit.

CONCLUSIONS

The association between functional traits and climate oscillation is crucial for understanding the growth conditions of relict-endemic species and is essential for conservation efforts. Forest trait diversity and species composition change because of fluctuations in hydraulic safety-efficiency gradients.

Meso-scale environmental heterogeneity drives plant trait distributions in fragmented dry grasslands

Environmental heterogeneity shapes the patterns of resources and limiting factors and therefore can be an important driver of plant community composition through the selection of the most adaptive functional traits. In this study, we explored plant trait-environment relationships in environmentally heterogeneous microsite complexes at the meso-scale (few meters), and used ancient Bulgarian and Hungarian burial mounds covered by dry grasslands as a model habitat. We assessed within-site trait variability typical of certain microsites with different combinations of environmental parameters (mound slopes with different aspects, mound tops, and surrounding plain grasslands) using a dataset of 480 vegetation plots. For this we calculated community-weighted means (CWMs) and abundance models. We found that despite their small size, the vegetation on mounds was characterized by different sets of functional traits (higher canopy, higher level of clonality, and heavier seeds) compared to the plain grasslands. North-facing slopes with mild environmental conditions were characterized by perennial species with light seeds, short flowering period, and a high proportion of dwarf shrubs sharply contrasted from the plain grasslands and from the south-facing slopes and mound tops with harsh environmental conditions. Patterns predicted by CWMs and abundance models differed in the case of certain traits (perenniality, canopy height, and leaf dry matter content), suggesting that environmental factors do not necessarily affect trait optima directly, but influence them indirectly through correlating traits. Due to the large relative differences in environmental parameters, contrasts in trait composition among microsites were mostly consistent and independent from the macroclimate. Mounds with high environmental heterogeneity can considerably increase variability in plant functional traits and ecological strategies at the site and landscape levels. The large trait variation on topographically heterogeneous landscape features can increase community resilience against climate change or stochastic disturbances, which underlines their conservation importance.

Extending the CWM approach to intraspecific trait variation: how to deal with overly optimistic standard tests?

Community weighted means (CWMs) are widely used to study the relationship between community-level functional traits and environment. For certain null hypotheses, CWM-environment relationships assessed by linear regression or ANOVA and tested by standard parametric tests are prone to inflated Type I error rates. Previous research has found that this problem can be solved by permutation tests (i.e., the max test). A recent extension of the CWM approach allows the inclusion of intraspecific trait variation (ITV) by the separate calculation of fixed, site-specific, and intraspecific CWMs. The question is whether the same Type I error rate inflation exists for the relationship between environment and site-specific or intraspecific CWM. Using simulated and real-world community datasets, we show that site-specific CWM-environment relationships have also inflated Type I error rate, and this rate is negatively related to the relative ITV magnitude. In contrast, for intraspecific CWM-environment relationships, standard parametric tests have the correct Type I error rate, although somewhat reduced statistical power. We introduce an ITV-extended version of the max test, which can solve the inflation problem for site-specific CWM-environment relationships and, without considering ITV, becomes equivalent to the "original" max test used for the CWM approach. We show that this new ITV-extended max test works well across the full possible magnitude of ITV on both simulated and real-world data. Most real datasets probably do not have intraspecific trait variation large enough to alleviate the problem of inflated Type I error rate, and published studies possibly report overly optimistic significance results.

When Do Traits Tell More Than Species about a Metacommunity? A Synthesis across Ecosystems and Scales

AbstractLinking species traits with the variation in species assemblages across habitats has often proved useful for developing a more mechanistic understanding of species distributions in metacommunities. However, summarizing the rich tapestry of a species in all of its nuance with a few key ecological traits can also lead to an abstraction that provides less predictability than when using taxonomy alone. As a further complication, taxonomic and functional diversities can be inequitably compared, either by integrating taxonomic-level information into the calculation of how functional aspects of communities vary or by detecting spurious trait-environment relationships. To remedy this, we here synthesize analyses of 80 datasets on different taxa, ecosystems, and spatial scales that include information on abundance or presence/absence of species across sites with variable environmental conditions and the species' traits. By developing analyses that treat functional and taxonomic diversity equitably, we ask when functional diversity helps to explain metacommunity structure. We found that patterns of functional diversity explained metacommunity structure and response to environmental variation in only 25% of the datasets using a multitrait approach but up to 59% using a single-trait approach. Nevertheless, an average of only 19% (interquartile range = 0%-29%) of the traits showed a significant signal across environmental gradients. Species-level traits, as typically collected and analyzed through functional diversity patterns, often do not bring predictive advantages over what the taxonomic information already holds. While our assessment of a limited advantage of using traits to explain variation in species assemblages was largely true across ecosystems, traits played a more useful role in explaining variation when many traits were used and when trait constructs were more related to species' status, life history, and mobility. We propose future research directions to make trait-based approaches and data more helpful for inference in metacommunity ecology.

Prey selection along a predators' body size gradient evidences the role of different trait-based mechanisms in food web organization

An increase in prey richness, prey size and predator trophic position with predator body size has been consistently reported as prime features of food web organization. These trends have been explained by non-exclusive mechanisms. First, the increase in energy demand with body size determines that larger predators must reduce prey selectivity for achieving the required number of resources, being consumption relationships independent of prey traits. Second, when consumption is restricted by gape limitation, small predators are constrained to select among small prey. However, this selection weakens over large predators, which progressively consume more and larger prey. Finally, the optimal foraging mechanism predicts that larger predators optimize their diet by selecting only large prey with high energy reward. Each one of these mechanisms can individually explain the increase in prey richness, prey size and predator trophic position with predator body size but their relative importance or the direct evidence for their combined role was seldom considered. Here we use the community assembly by trait selection (CATS) theory for evaluating the support for each one of these mechanisms based on the prey selection patterns that they predict. We analyzed how prey body size and trophic guild determine prey selection by predators of increasing body size in a killifish guild from a temporary pond system. Results support the combination of the three mechanisms to explain the structural trends in our food web, although their strength is contingent on prey trophic group. Overall, high energy prey are preferred by larger predators, and small predators select small prey of all trophic status. However, large predators prefer large primary producers and avoid large carnivorous prey, probably because of the inherent risk of consuming other carnivorous. Our study provides a mechanistic understanding of how predator traits determine the selection of prey traits affecting food web assembly.

Ectomycorrhizal diversity, taxon-specific traits and root N uptake in temperate beech forests

Roots of forest trees are colonized by a diverse spectrum of ectomycorrhizal (EM) fungal species differing in their nitrogen (N) acquisition abilities. Here, we hypothesized that root N gain is the result of EM fungal diversity or related to taxon-specific traits for N uptake. To test our hypotheses, we traced ¹⁵ N enrichment in fine roots, coarse roots and taxon-specific ectomycorrhizas in temperate beech forests in two regions and three seasons, feeding 1 mM NH₄ NO₃ labelled with either ¹⁵ NH₄ ⁺ or ¹⁵ NO₃ ^- . We morphotyped > 45 000 vital root tips and identified 51 of 53 detected EM species by sequencing. EM root tips exhibited strong, fungal taxon-specific variation in ¹⁵ N enrichment with higher NH₄ ⁺ than NO₃ ^- enrichment. The translocation of N into the upper parts of the root system increased with increasing EM fungal diversity. Across the growth season, influential EM species predicting root N gain were not identified, probably due to high temporal dynamics of the species composition of EM assemblages. Our results support that root N acquisition is related to EM fungal community-level traits and highlight the importance of EM diversity for tree N nutrition.

Ontogenetic trait variation and metacommunity effects influence species relative abundances during tree community assembly

Predicting species abundance is one of the most fundamental pursuits of ecology. Combining the information encoded in functional traits and metacommunities provides a new perspective to predict the abundance of species in communities. We applied a community assembly via trait selection model to predict quadrat-scale species abundances using functional trait variation on ontogenetic stages and metacommunity information for over 490 plant species in a subtropical forest and a lowland tropical forest in Yunnan, China. The relative importance of trait-based selection, mass effects, and stochasticity in shaping local species abundances is evaluated using different null models. We found both mass effects and trait selection contribute to local abundance patterns. Trait selection was detectable at all studied spatial scales (0.04-1 ha), with its strength stronger at larger scales and in the subtropical forest. In contrast, the importance of stochasticity decreased with spatial scale. A significant mass effect of the metacommunity was observed at small spatial scales. Our results indicate that tree community assembly is primarily driven by ontogenetic traits and metacommunity effects. Our findings also demonstrate that including ontogenetic trait variation into predictive frameworks allows ecologists to infer ecological mechanisms operating in community assembly at the individual level.

Small mammal responses to fire severity mediated by vegetation characteristics and species traits

The frequency of large, high‐severity “mega‐fires” has increased in recent decades, with numerous consequences for forest ecosystems. In particular, small mammal communities are vulnerable to post‐fire shifts in resource availability and play critical roles in forest ecosystems. Inconsistencies in previous observations of small mammal community responses to fire severity underscore the importance of examining mechanisms regulating the effects of fire severity on post‐fire recovery of small mammal communities. We compared small mammal abundance, diversity, and community structure among habitats that burned at different severities, and used vegetation characteristics and small mammal functional traits to predict community responses to fire severity three years after one mega‐fire in the Sierra Nevada, California. Using a model‐based fourth‐corner analysis, we examined how interactions between vegetation variables and small mammal traits associated with their resource use were associated with post‐fire small mammal community structure among fire severity categories. Small mammal abundance was similar across fire severity categories, but diversity decreased and community structure shifted as fire severity increased. Differences in small mammal communities were large only between unburned and high‐severity sites. Three highly correlated fire‐dependent vegetation variables affected by fire and the volume of soft coarse woody debris were associated with small mammal community structures. Furthermore, we found that interactions between vegetation variables and three small mammal traits (feeding guild, primary foraging mode, and primary nesting habit) predicted community structure across fire severity categories. We concluded that resource use was important in regulating small mammal recovery after the fire because vegetation provided required resources to small mammals as determined by their functional traits. Given the mechanistic nature of our analyses, these results may be applicable to other fire‐prone forest systems, although it will be important to conduct studies across large biogeographic regions and over long post‐fire time periods to assess generality.

The acquisitive-conservative axis of leaf trait variation emerges even in homogeneous environments

BACKGROUND AND AIMS

The acquisitive-conservative axis of plant ecological strategies results in a pattern of leaf trait covariation that captures the balance between leaf construction costs and plant growth potential. Studies evaluating trait covariation within species are scarcer, and have mostly dealt with variation in response to environmental gradients. Little work has been published on intraspecific patterns of leaf trait covariation in the absence of strong environmental variation.

METHODS

We analysed covariation of four leaf functional traits [specific leaf area (SLA) leaf dry matter content (LDMC), force to tear (Ft) and leaf nitrogen content (Nm)] in six Poaceae and four Fabaceae species common in the dry Chaco forest of Central Argentina, growing in the field and in a common garden. We compared intraspecific covariation patterns (slopes, correlation and effect size) of leaf functional traits with global interspecific covariation patterns. Additionally, we checked for possible climatic and edaphic factors that could affect the intraspecific covariation pattern.

KEY RESULTS

We found negative correlations for the LDMC-SLA, Ft-SLA, LDMC-Nm and Ft-Nm trait pairs. This intraspecific covariation pattern found both in the field and in the common garden and not explained by climatic or edaphic variation in the field follows the expected acquisitive-conservative axis. At the same time, we found quantitative differences in slopes among different species, and between these intraspecific patterns and the interspecific ones. Many of these differences seem to be idiosyncratic, but some appear consistent among species (e.g. all the intraspecific LDMC-SLA and LDMC-Nm slopes tend to be shallower than the global pattern).

CONCLUSIONS

Our study indicates that the acquisitive-conservative leaf functional trait covariation pattern occurs at the intraspecific level even in the absence of relevant environmental variation in the field. This suggests a high degree of variation-covariation in leaf functional traits not driven by environmental variables.

Devil in the details: how can we avoid potential pitfalls of CATS regression when our data do not follow a Poisson distribution?

BACKGROUND

Community assembly by trait selection (CATS) allows for the detection of environmental filtering and estimation of the relative role of local and regional (meta-community-level) effects on community composition from trait and abundance data without using environmental data. It has been shown that Poisson regression of abundances against trait data results in the same parameter estimates. Abundance data do not necessarily follow a Poisson distribution, and in these cases, other generalized linear models should be fitted to obtain unbiased parameter estimates.

AIMS

This paper discusses how the original algorithm for calculating the relative role of local and regional effects has to be modified if Poisson model is not appropriate.

RESULTS

It can be shown that the use of the logarithm of regional relative abundances as an offset is appropriate only if a log-link function is applied. Otherwise, the link function should be applied to the product of local total abundance and regional relative abundances. Since this product may be outside the domain of the link function, the use of log-link is recommended, even if it is not the canonical link. An algorithm is also suggested for calculating the offset when data are zero-inflated. The relative role of local and regional effects is measured by Kullback-Leibler R2. The formula for this measure presented by Shipley (2014) is valid only if the abundances follow a Poisson distribution. Otherwise, slightly different formulas have to be applied. Beyond theoretical considerations, the proposed refinements are illustrated by numerical examples. CATS regression could be a useful tool for community ecologists, but it has to be slightly modified when abundance data do not follow a Poisson distribution. This paper gives detailed instructions on the necessary refinement.

Trait-Environment Relationships Reveal the Success of Alien Plants Invasiveness in an Urbanized Landscape

Urban areas are being affected by rapidly increasing human-made pressures that can strongly homogenize biodiversity, reduce habitat heterogeneity, and facilitate the invasion of alien species. One of the key concerns in invaded urban areas is comparing the trait–environment relationships between alien and native species, to determine the underlying causes of invasiveness. In the current study, we used a trait–environment dataset of 130 native plants and 33 alien plants, recorded in 100 plots covering 50 urban areas and 50 non-urban ones in an urbanization gradient in the arid mountainous Saint-Katherine protected area in Egypt. We measured eleven morphological plant traits for each plant species and ten environmental variables in each plot, including soil resources and human-made pressures, to construct trait–environment associations using a fourth-corner analysis. In addition, we measured the mean functional and phylogenetic distances between the two species groups along an urbanization gradient. Our results revealed strongly significant relationships of alien species traits with human-made pressures and soil resources in urban areas. However, in non-urban areas, alien species traits showed weak and non-significant associations with the environment. Simultaneously, native plants showed consistency in their trait–environment relationships in urban and non-urban areas. In line with these results, the functional and phylogenetic distances declined between the aliens and natives in urban areas, indicating biotic homogenization with increasing urbanization, and increased in non-urban areas, indicating greater divergence between the two species groups. Thereby, this study provided evidence that urbanization can reveal the plasticity of alien species and can also be the leading cause of homogenization in an arid urban area. Future urban studies should investigate the potential causes of taxonomic, genetic, and functional homogenization in species composition in formerly more diverse urbanized areas.

Quantifying the relationship linking the community-weighted means of plant traits and soil fertility

Is it possible to generalize relationships between certain plant traits and soil fertility? In particular, are there quantitative relationships between community-weighted mean (CWM) trait values of leaf dry-matter content (LDMC), specific leaf area (SLA), plant height, and Grime's competitor-stress tolerator-ruderal (CSR) strategy scores and the generalized soil fertility, F_G (i.e., the capacity of a soil to produce biomass when all nonsoil variables are held constant) that are generalizable across different species assemblages and geographical areas? We assessed F_G in 21 sites in southern Quebec and 7 sites in southern France using a previously published method based on structural equation modeling. We then determined the CWM values of LDMC, SLA, plant height, and CSR scores in the 21 Quebec sites to obtain quantitative relationships between F_G and these CWM traits. Using these relationships, we independently tested the generality of the trait-fertility relationships using data from French sites. The relationships between F_G and the CWM traits were nonlinear, but displayed the expected qualitative trends as reported in the literature. In particular, the S score and CWM LDMC decreased with increasing soil fertility, and the R score and CWM SLA increased. CWM traits were more strongly correlated to measures of F_G (r² up to 0.48) than to measures of other soil characteristics (r² up to 0.17 for nitrogen flux). Importantly, the independently tested French F_G -trait relationships showed no significant deviations from these quantitative relationships. Further investigation is necessary to confirm if the same trend applies to other regions and or ecosystems.

Meiofauna in a Potential Deep-Sea Mining Area—Influence of Temporal and Spatial Variability on Small-Scale Abundance Models

In large areas of the Clarion Clipperton Fracture Zone (northeast Pacific), exploration of deep-sea polymetallic nodules as a potential source of high-technology metals is ongoing. Deep-sea mining may have a severe impact on the benthic communities. Here, we investigated meiofauna communities in the abyss at the scale of a prospective mining operation area. Random forest regressions were computed to spatially predict continuous layers of environmental variables as well as the distribution of meiofauna abundance across the area. Significant models could be computed for 26 sediment and polymetallic nodule parameters. Meiofauna abundance, taxon richness and diversity were also modelled, as well as abundance of the taxon Nematoda. Spatial correlation is high if the predictions of meiofauna are either based on bathymetry and backscatter or include sediment and nodule variables; Pearson’s correlation coefficient varies between 0.42 and 0.91. Comparison of differences in meiofauna abundance between different years shows that spatial patterns do change, with an elevated abundance of meiofauna in the eastern part of the study area in 2013. On the spatial scale of a potential mining operation, distribution models prove to be a useful tool to gain insight into both temporal variability and the influence of potential environmental drivers on meiofauna distribution.

MAcroecological Framework for Invasive Aliens (MAFIA): disentangling large-scale context dependence in biological invasions

Macroecology is the study of patterns, and the processes that determine those patterns, in the distribution and abundance of organisms at large scales, whether they be spatial (from hundreds of kilometres to global), temporal (from decades to centuries), and organismal (numbers of species or higher taxa). In the context of invasion ecology, macroecological studies include, for example, analyses of the richness, diversity, distribution, and abundance of alien species in regional floras and faunas, spatio-temporal dynamics of alien species across regions, and cross-taxonomic analyses of species traits among comparable native and alien species pools. However, macroecological studies aiming to explain and predict plant and animal naturalisations and invasions, and the resulting impacts, have, to date, rarely considered the joint effects of species traits, environment, and socioeconomic characteristics. To address this, we present the MAcroecological Framework for Invasive Aliens (MAFIA). The MAFIA explains the invasion phenomenon using three interacting classes of factors – alien species traits, location characteristics, and factors related to introduction events – and explicitly maps these interactions onto the invasion sequence from transport to naturalisation to invasion. The framework therefore helps both to identify how anthropogenic effects interact with species traits and environmental characteristics to determine observed patterns in alien distribution, abundance, and richness; and to clarify why neglecting anthropogenic effects can generate spurious conclusions. Event-related factors include propagule pressure, colonisation pressure, and residence time that are important for mediating the outcome of invasion processes. However, because of context dependence, they can bias analyses, for example those that seek to elucidate the role of alien species traits. In the same vein, failure to recognise and explicitly incorporate interactions among the main factors impedes our understanding of which macroecological invasion patterns are shaped by the environment, and of the importance of interactions between the species and their environment. The MAFIA is based largely on insights from studies of plants and birds, but we believe it can be applied to all taxa, and hope that it will stimulate comparative research on other groups and environments. By making the biases in macroecological analyses of biological invasions explicit, the MAFIA offers an opportunity to guide assessments of the context dependence of invasions at broad geographical scales.

Trait–environment relationships of plant species at different stages of the introduction process

The success of alien plant species can be attributed to differences in functional traits compared to less successful aliens as well as to native species, and thus their adaptation to environmental conditions. Studies have shown that alien (especially invasive) plant species differ from native species in traits such as specific leaf area (SLA), height, seed size or flowering period, where invasive species showed significantly higher values for these traits. Different environmental conditions, though, may promote the success of native or alien species, leading to competitive exclusion due to dissimilarity in traits between the groups. However, native and alien species can also be similar, with environmental conditions selecting for the same set of traits across species. So far, the effect of traits on invasion success has been studied without considering environmental conditions. To understand this interaction we examined the trait–environment relationship within natives, and two groups of alien plant species differing in times of introduction (archaeophytes vs. neophytes). Further, we investigated the difference between non-invasive and invasive neophytes. We analyzed the relationship between functional traits of 1,300 plant species occurring in 1000 randomly selected grid-cells across Germany and across different climatic conditions and land-cover types. Our results show that temperature, precipitation, the proportion of natural habitats, as well as the number of land-cover patches and geological patches affect archaeophytes and neophytes differently, regarding their level of urbanity (in neophytes negative for all non-urban land covers) and self-pollination (mainly positive for archaeophytes). Similar patterns were observed between non-invasive and invasive neophytes, where additionally, SLA, storage organs and the beginning of flowering were strongly related to several environmental factors. Native species did not express any strong relationship between traits and environment, possibly due to a high internal heterogeneity within this group of species. The relationship between trait and environment was more pronounced in neophytes compared to archaeophytes, and most pronounced in invasive plants. The alien species at different stages of the invasion process showed both similarities and differences in terms of the relationship between traits and the environment, showing that the success of introduced species is context-dependent.

Soil and root nutrient chemistry structure root-associated fungal assemblages in temperate forests

Root-associated fungi (RAF) link nutrient fluxes between soil and roots and thus play important roles in ecosystem functioning. To enhance our understanding of the factors that control RAF, we fitted statistical models to explain variation in RAF community structure using data from 150 temperate forest sites covering a broad range of environmental conditions and chemical root traits. We found that variation in RAF communities was related to both root traits (e.g., cations, carbohydrates, NO₃ ^- ) and soil properties (pH, cations, moisture, C/N). The identified drivers were the combined result of distinct response patterns of fungal taxa (determined at the rank of orders) to biotic and abiotic factors. Our results support that RAF community variation is related to evolutionary adaptedness of fungal lineages and consequently, drivers of RAF communities are context-dependent.

Addressing trait selection patterns in temporary ponds in response to wildfire disturbance and seasonal succession

Mediterranean ecosystems are increasingly threatened by disturbances such as wildfires. These disturbances are expected to shift the selective pressures that determine trait-dependent community assembly. In addition, the stochasticity in species assembly may decrease because of the introduction of strong selection regimes or may increase because of random variation in recruitment. However, these changes in the selection profile and stochasticity in disturbed communities have seldom been evaluated. We examined the relative roles of wildfire disturbance, local conditions and successional dynamics on the assembly of aquatic macroinvertebrate communities. We used the theory of community assembly by trait selection (CATS) to identify traits under selection and to estimate their dependence on wildfire disturbance and environmental gradients. We took advantage of a natural wildfire that partially burned a Mediterranean system of temporary ponds, which were surveyed before and after the wildfire, creating a natural before-after-control-impact design. Before the wildfire, the burned and unburned ponds did not show differences in the selected traits. After the wildfire event, species with larger body sizes and scrapers were favoured in the burned ponds, while collectors and active dispersers were underrepresented. Nonetheless, local environmental conditions and successional dynamics had greater relevance in the selection of traits than the wildfire. This suggests that assembly mechanisms were largely determined by seasonal successional changes regardless of wildfire disturbance. Finally, the relevance of the analysed traits diminished during the hydroperiod, suggesting more stochastic assemblages and/or a replacement in the set of selected traits. Despite the prominent role of seasonal succession over wildfire, this disturbance was associated with a change in the selection strength over specific traits related with feeding strategies and species life histories. Both hydroperiod and wildfire highlighted a strong role of trait-mediated processes (i.e. niche assembly). Therefore, the predicted increase in the frequency and intensity of wildfires is likely to result in community functional shifts. Furthermore, stochasticity was also important for community assembly, particularly from the middle towards the end of the hydroperiod. Our results evidenced the strong relevance of successional changes in trait-mediated assembly mechanisms and its interplay with wildfire disturbance in temporary pond communities.

Changing bird communities of an agricultural landscape: declines in arboreal foragers, increases in large species

Birds are declining in agricultural landscapes around the world. The causes of these declines can be better understood by analysing change in groups of species that share life-history traits. We investigated how land-use change has affected birds of the Tasmanian Midlands, one of Australia's oldest agricultural landscapes and a focus of habitat restoration. We surveyed birds at 72 sites, some of which were previously surveyed in 1996-1998, and tested relationships of current patterns of abundance and community composition to landscape and patch-level environmental characteristics. Fourth-corner modelling showed strong negative responses of aerial foragers and exotics to increasing woodland cover; arboreal foragers were positively associated with projective foliage cover; and small-bodied species were reduced by the presence of a hyperaggressive species of native honeyeater, the noisy miner (Manorina melanocephala). Analysis of change suggests increases in large-bodied granivorous or carnivorous birds and declines in some arboreal foragers and nectarivores. Changes in species richness were best explained by changes in noisy miner abundance and levels of surrounding woodland cover. We encourage restoration practitioners to trial novel planting configurations that may confer resistance to invasion by noisy miners, and a continued long-term monitoring effort to reveal the effects of future land-use change on Tasmanian birds.

Environment and past land use together predict functional diversity in a temperate forest

Environment and human land use both shape forest composition. Abiotic conditions sift tree species from a regional pool via functional traits that influence species' suitability to the local environment. In addition, human land use can modify species distributions and change functional diversity of forests. However, it is unclear how environment and land use simultaneously shape functional diversity of tree communities. Land-use legacies are especially prominent in temperate forest landscapes that have been extensively modified by humans in the last few centuries. Across a 900-ha temperate deciduous forest in the northeastern United States, comprising a mosaic of different-aged stands due to past human land use, we used four key functional traits-maximum height, rooting depth, wood density, and seed mass-to examine how multiple environmental and land-use variables influenced species distributions and functional diversity. We sampled ~40,000 trees >8 cm DBH within 485 plots totaling 137 ha. Species within plots were more functionally similar than expected by chance when we estimated functional diversity using all traits together (multi-trait), and to a lesser degree, with each trait separately. Multi-trait functional diversity was most strongly correlated with distance from the perennial stream, elevation, slope, and forest age. Environmental and land-use predictors varied in their correlation with functional diversities of the four individual traits. Landscape-wide change in abundances of individual species also correlated with both environment and land-use variables, but magnitudes of trait-environment interactions were generally stronger than trait interactions with land use. These findings can be applied for restoration and assisted regeneration of human-modified temperate forests by using traits to predict which tree species would establish well in relation to land-use history, topography, and soil conditions.

A genomic perspective on stoichiometric regulation of soil carbon cycling

Similar to plant growth, soil carbon (C) cycling is constrained by the availability of nitrogen (N) and phosphorus (P). We hypothesized that stoichiometric control over soil microbial C cycling may be shaped by functional guilds with distinct nutrient substrate preferences. Across a series of rice fields spanning 5-25% soil C (N:P from 1:12 to 1:70), C turnover was best correlated with P availability and increased with experimental N addition only in lower C (mineral) soils with N:P⩽16. Microbial community membership also varied with soil stoichiometry but not with N addition. Shotgun metagenome data revealed changes in community functions with increasing C turnover, including a shift from aromatic C to carbohydrate utilization accompanied by lower N uptake and P scavenging. Similar patterns of C, N and P acquisition, along with higher ribosomal RNA operon copy numbers, distinguished that microbial taxa positively correlated with C turnover. Considering such tradeoffs in genomic resource allocation patterns among taxa strengthened correlations between microbial community composition and C cycling, suggesting simplified guilds amenable to ecosystem modeling. Our results suggest that patterns of soil C turnover may reflect community-dependent metabolic shifts driven by resource allocation strategies, analogous to growth rate-stoichiometry coupling in animal and plant communities.

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.

A critical issue in model-based inference for studying trait-based community assembly and a solution

Statistical testing of trait-environment association from data is a challenge as there is no common unit of observation: the trait is observed on species, the environment on sites and the mediating abundance on species-site combinations. A number of correlation-based methods, such as the community weighted trait means method (CWM), the fourth-corner correlation method and the multivariate method RLQ, have been proposed to estimate such trait-environment associations. In these methods, valid statistical testing proceeds by performing two separate resampling tests, one site-based and the other species-based and by assessing significance by the largest of the two p-values (the p_max test). Recently, regression-based methods using generalized linear models (GLM) have been proposed as a promising alternative with statistical inference via site-based resampling. We investigated the performance of this new approach along with approaches that mimicked the p_max test using GLM instead of fourth-corner. By simulation using models with additional random variation in the species response to the environment, the site-based resampling tests using GLM are shown to have severely inflated type I error, of up to 90%, when the nominal level is set as 5%. In addition, predictive modelling of such data using site-based cross-validation very often identified trait-environment interactions that had no predictive value. The problem that we identify is not an “omitted variable bias” problem as it occurs even when the additional random variation is independent of the observed trait and environment data. Instead, it is a problem of ignoring a random effect. In the same simulations, the GLM-based p_max test controlled the type I error in all models proposed so far in this context, but still gave slightly inflated error in more complex models that included both missing (but important) traits and missing (but important) environmental variables. For screening the importance of single trait-environment combinations, the fourth-corner test is shown to give almost the same results as the GLM-based tests in far less computing time.

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.

Reinforcing loose foundation stones in trait-based plant ecology

The promise of "trait-based" plant ecology is one of generalized prediction across organizational and spatial scales, independent of taxonomy. This promise is a major reason for the increased popularity of this approach. Here, we argue that some important foundational assumptions of trait-based ecology have not received sufficient empirical evaluation. We identify three such assumptions and, where possible, suggest methods of improvement: (i) traits are functional to the degree that they determine individual fitness, (ii) intraspecific variation in functional traits can be largely ignored, and (iii) functional traits show general predictive relationships to measurable environmental gradients.

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.