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A foundational assumption of trait-based ecology is that individual performances should be predicted by its functional traits. However, the trait—performance relationships reported in literature were typically weak, probably due to the ignorance of interactions between traits and environments, intraspecific trait variability, and hard traits (directly linked to physiological processes of interest). We conducted an experiment of planting 900 seedlings of six tree species separately (one seedling per pot) along experimentally manipulated light and water gradients, monitored their survival and growth, and measured their morphological, photosynthetic, and hydraulic traits. Most trait–performance relationships depended on the environments, either marginally changing (weak trait × environment interaction) or even reversing (strong trait × environment interaction) along light or water gradients in our experiment. Such trait × environment interactions were more likely to be detected in growth models using individual-level traits than models using species mean traits, but seedling growth was not better modeled with individual-level traits than species mean traits. Additionally, none of the hard traits (photosynthetic and hydraulic traits) were better predictors than soft traits (morphological traits) modeling seedling growth and survival along light and water gradients. Our study highlights the necessities of considering trait × environment interactions when predicting response of plants to changing environments. The benefits of using individual-level traits or hard traits to predict plant performance might be reduced or even canceled if their measurement errors are not well controlled.

ABSTRACT Theoretical and empirical ecology have recently explored the role of intraspecific trait variation (ITV) in structuring ecological communities. Such trait variation may be correlated with high environmental variability within a site or across a species' range. Here we explore the relationship between ITV, spatial and temporal environmental heterogeneity, and the breadth of species' environmental distributions for 33 tree species across eight sites occurring along marked environmental gradients in Puerto Rico. Specifically, we asked (1) If within‐site ITV is positively correlated with site‐level temporal and spatial environmental variation, and (2) How across‐site ITV relates to the breadth of species' environmental distributions on the island. Two key plant traits, leaf mass per area (LMA) and wood density, were used to understand the association between ITV and environmental variation. We examined ITV across species and sites using statistical models to assess the relationship between (1) within‐site ITV and site‐level spatial (topography) and temporal (rainfall) environmental variability; (2) across‐site ITV and environmental variation across the species geographic range on the island. We also assessed the relationship between across‐site mean trait values and island‐wide environmental ranges. (1) Across all species, we did not find any significant associations between within‐site ITV and site‐level temporal or spatial variability. (2) Greater ITV values of LMA and wood density were associated with larger environmental ranges. We also found that species with high wood density, a trait associated with a conservative growth strategy, had narrower ranges across climatic conditions, but this pattern was not evident for LMA. Our findings emphasize the complexity of the relationships between ITV and species distributions with respect to environmental heterogeneity at different spatial and temporal scales. These complexities are important for research on species distributions and range‐shift dynamics. Here we explore the relationship between ITV, spatial and temporal environmental heterogeneity, and the breadth of species' environmental distributions for 33 tree species across eight sites across marked environmental gradients in Puerto Rico. Species with greater across‐site ITV in wood density and LMA occurred over broader ranges of potential evapotranspiration but lower elevation ranges. We also found that species with high wood density, a trait associated with a conservative growth strategy, had narrower ranges across climatic conditions, while there were no consistent patterns for species with high LMA.

• That functional traits should affect individual performance and, in turn, determine fitness and population growth, is a foundational assumption of trait-based ecology. This assumption is, however, not supported by a strong empirical base. • Here, we measured simultaneously two individual performance metrics (survival and growth), seven traits and 10 environmental properties for each of 3981 individuals of 205 species in a 50-ha stem-mapped subtropical forest. We then modelled survival/growth as a function of traits, environments and trait × environment interactions, and quantified their relative importance at both the species and individual levels. • We found evidence of alternative functional designs and multiple performance peaks along environmental gradients, indicating the presence of complicated trait × environment interactions. However, such interactions were relatively unimportant in our site, which had relatively low environmental variations. Moreover, individual performance was not better predicted, and trait × environment interactions were not more likely detected, at the individual level than at the species level. • Although the trait × environment interactions might be safely ignored in relatively homogeneous environments, we encourage future studies to test the interactive effects of traits and environments on individual performances and lifelong fitness at larger spatial scales or along experimentally manipulated environmental gradients.

Aim: It is widely recognized that the prediction of invasion success at large biogeographical scales requires jointly accounting for alien species traits and local community filters, such as abiotic conditions, biotic interactions and propagule pressure. Despite this recognition, interactions between traits and community filters are generally neglected. Here, we aim to address this limitation by developing a hierarchical framework that builds on trait-based theory to model occurrences of alien species as a function of spatially explicit variables, filtering invasions and their interactions with species traits. Location: Herbaceous communities throughout France. Time period: c. 1960–2012 (mostly after 1990). Major taxa studied: Herbaceous plants. Methods: Based on a large dataset of >50,000 community plots, we built a multispecies hierarchical model of the distribution of the 10 most widespread alien plants in French grasslands. In this model, we explicitly account for how plant height, specific leaf area (SLA) and seed mass affect the occurrence of alien species along gradients of human pressure, environmental conditions and native community composition. Finally, we contrast the results to native species responses along the same gradients. Results: We show that two out of three traits significantly modulate the responses of species along these broad gradients. Alien plants with exploitative traits (i.e., tall and with high SLA) were less dependent on human pressure, more efficient in resource-rich environments and better at avoiding competition from native species. These trait–gradient interactions were often unique to alien plants (e.g., human pressure was important only for supporting alien species with low SLA), even though trait ranges of alien and native species were comparable. Ultimately, the modelling of trait–gradient interactions allows spatially explicit estimations of invasion risks by novel species with particular sets of traits. Main conclusions: By taking the best from multispecies distribution modelling and trait-based theory, our framework paves the way for a generalized mechanistic understanding of how traits influence the success of alien plants and their spatial distributions.

Variation in community structure is mediated by interactions between species traits and a site's environmental characteristics. Previously, data on community composition at sites has been employed to correlate trait and environmental variables (e.g., RLQ analysis) and to predict community-level expression of quantitative traits (i.e., community aggregated traits). Here, we demonstrate that the selection ratio, a method originating in animal resource selection studies, can estimate the ecological filters that site conditions impose on species traits by combining observed community aggregated traits with null models of species availability. This flexible, nonparametric approach expresses the filter at each site as a probability density function for the selection of individuals possessing a given trait value. By doing so, it generalizes the community aggregated trait concept to include categorical as well as continuous traits and allows for both intraspecific variation in trait expression and differences in species availability among sites. The resulting site-level filter functions can be related to environmental covariates by standard statistical approaches (e.g., regression). The method complements existing techniques for analyzing trait—environment interactions in community ecology.

Surface mining for coal represents a significant form of anthropogenic disturbance on the landscape. Currently there are more than one million hectares of former mined land in the United States. New reclamation procedures are being examined to accelerate forest succession on former coal mine sites in eastern Appalachia. Our study was conducted on public lands that had been previously surface-mined for coal, reclaimed in 1978, and re-mined and reclaimed using new methods in 2007. We planted 535 American chestnut seeds in March 2008 at the study site in 107 blocks. Each block contained five seeds from five different genetic lines including Pure American, Pure Chinese, and three intergraded hybrid Chinese-American lines. We saw few significant differences in performance between pure American chestnuts and more advanced backcrossed generations of hybrid trees. However, Chinese chestnut and early-generation hybrids showed significantly better growth and survival measurements. The American Chestnut Foundation's breeding program appears to have been successful at capturing a morphological fidelity between the latest hybrids and pure American trees. Trees with a greater percentage of Chinese parental material possess a suite of leaf characters that may make those hybrids better suited for the arid, high light conditions found on reclaimed mine sites (particularly thickness, length to width ratio, and pubescence). Development of goal-specific cultivars by the American Chestnut Foundation might aid in more successful restoration attempts but also may limit genetic diversity in those lines if intensive inbreeding or cultural cloning is utilized. Additionally, restoration at end-dump sites may need to pursue a phased system of introduction after initial extreme environmental conditions have been ameliorated by the use of early successional species in order to ensure the success of desirable species.

High severity fire may promote or reduce plant understory diversity in forests. However, few empirical studies have tested long-standing theoretical predictions that productivity may help to explain observed variation in post-fire plant diversity. Support for the influence of productivity on disturbance-diversity relationships is found predominantly in experimental grasslands, while tests over large areas with natural disturbance and productivity gradients are few and have yielded inconsistent results. Here, we measured the response of post-fire understory plant diversity to natural gradients of fire severity and productivity in a large-scale observational study in California’s subalpine forests. We found that plant species richness increased with increasing fire severity and that this trend was stronger at high productivity. We used plant traits to investigate whether release from competition might contribute to increasing diversity and found that short-lived and far-dispersing species benefited more from high severity fire than their long-lived and near-dispersing counterparts. For far-dispersing species only, the benefit from high severity fire was stronger in high productivity plots where unburned species richness was lowest. Our results support theoretical connections between fire severity, productivity and plant communities that are key to predicting the consequences of increasing fire severity and frequency on diversity in the coming decades.

Question In functional biogeography studies, generalizable patterns in the relationship between plant traits and the environment have yet to emerge. Local drivers (i.e., soil, land use, vegetation structure) can increase our understanding of the trait–environment relationship. What is the role of climate and local drivers in shaping abundance‐weighted trait patterns of forest understories at biogeographic scales? Location Italian forests. Methods We selected 201 sites that are statistically representative for the heterogeneity of Italian forests across three biogeographic regions (alpine, continental, and mediterranean). Understorey vegetation was recorded for each site on an area of 400 m2, together with 25 environmental variables related to climate, soil, land use and forest structure. Specific leaf area (SLA), plant height (H) and seed mass (SM) were obtained from databases. Community‐weighted mean (CWM) values were calculated. Variance partitioning was used to identify the relative role of groups of environmental variables on the CWM of traits. Generalized Additive Models were used to assess the relationship between traits and single variables. Results Climate alone and climate–soil interactions explained the largest proportion of the variation of all the traits (13.7% to 22.8%). Temperature‐related factors as well as soil N and P availability were the climatic and edaphic explanatory variables most correlated to trait variation. Forest structure and land use accounted for a smaller percentage of the variation in traits. Land‐use factors alone were important in explaining only SLA variation. Conclusions While climate plays a major role in trait–environment relationships in forest understories, our results highlighted the need to integrate at least soil properties as local drivers of trait variation in broad scale functional biogeography studies of these systems. Climate and climate–soil interactions play a major role in trait–environment relationships in Italian forest understories. Temperature‐related factors as well as soil N and P availability were the climatic and edaphic explanatory variables most correlated to trait variation. Forest structure and land use accounted for a smaller percentage of the variation in traits.

Question: The community-weighted mean (CWM) approach is an easy way of analysing trait–environment association by regressing (or correlating) the mean trait per plot against an environmental variable and assessing the statistical significance of the slope or the associated correlation coefficient. However, the CWM approach does not yield valid tests, as random traits (or random indicator values) are far too often judged significantly related to the environmental variable, even when the trait and environmental variable are extrinsic to (not derived from) the community data. Existing solutions are the ZS (Zelený & Schaffers) modified test and the max (or sequential) test based on the fourth-corner correlation. Both tests are based on permutations which become cumbersome when many tests need to be carried out and many permutations are required, as in methods that correct for multiple testing. The main goal of this study was to compare these existing permutation-based solutions and to develop a quick and easy parametric test that can replace them. Methods: This study decomposes the fourth-corner correlation in two ways, which suggests a simple parametric approach consisting of assessing the significances of two linear regressions, one plot-level test as in the CWM approach and one species-level test, the reverse of the CWM approach, that regresses the environmental mean per species (i.e. the species niche centroid) on to the trait. The tests are combined by taking the maximum p-value. The type I error rates and power of this parametric max test are examined by simulation of one- and two-dimensional Gaussian models and log-linear models. Results: The ZS-modified test and the fourth-corner max test are conservative in different scenarios, the ZS-modified test being even more conservative than the fourth-corner. The new parametric max test is shown to control the type I error and has equal or even higher power than permutation tests based on the fourth-corner, the ZS-modified test and variants thereof. A weighted version of the new test showed inflated type I error. Conclusion: The combination of two simple regressions is a good alternative to the fourth-corner and the ZS-modified test. This combination is also applicable when multiple trait measurements are made per plot.