Rooting depth and xylem vulnerability are independent woody plant traits jointly selected by aridity, seasonality, and water table depth.

Evolutionary radiations of woody taxa within arid environments were made possible by multiple trait innovations including deep roots and embolism-resistant xylem, but little is known about how these traits have coevolved across the phylogeny of woody plants or how they jointly influence the distribution of species. We synthesized global trait and vegetation plot datasets to examine how rooting depth and xylem vulnerability across 188 woody plant species interact with aridity, precipitation seasonality, and water table depth to influence species occurrence probabilities across all biomes. Xylem resistance to embolism and rooting depth are independent woody plant traits that do not exhibit an interspecific trade-off. Resistant xylem and deep roots increase occurrence probabilities in arid, seasonal climates over deep water tables. Resistant xylem and shallow roots increase occurrence probabilities in arid, nonseasonal climates over deep water tables. Vulnerable xylem and deep roots increase occurrence probabilities in arid, nonseasonal climates over shallow water tables. Lastly, vulnerable xylem and shallow roots increase occurrence probabilities in humid climates. Each combination of trait values optimizes occurrence probabilities in unique environmental conditions. Responses of deeply rooted vegetation may be buffered if evaporative demand changes faster than water table depth under climate change.

Testing the hierarchy of predictability in grassland restoration across a gradient of environmental severity.

Ecological restoration is critical for recovering degraded ecosystems but is challenged by variable success and low predictability. Understanding which outcomes are more predictable and less variable following restoration can improve restoration effectiveness. Recent theory asserts that the predictability of outcomes would follow an order from most to least predictable from coarse to fine community properties (physical structure > taxonomic diversity > functional composition > taxonomic composition) and that predictability would increase with more severe environmental conditions constraining species establishment. We tested this "hierarchy of predictability" hypothesis by synthesizing outcomes along an aridity gradient with 11 grassland restoration projects across the United States. We used 1829 vegetation monitoring plots from 227 restoration treatments, spread across 52 sites. We fit generalized linear mixed-effects models to predict six indicators of restoration outcomes as a function of restoration characteristics (i.e., seed mixes, disturbance, management actions, time since restoration) and used variance explained by models and model residuals as proxies for restoration predictability. We did not find consistent support for our hypotheses. Physical structure was among the most predictable outcomes when the response variable was relative abundance of grasses, but unpredictable for total canopy cover. Similarly, one dimension of taxonomic composition related to species identities was unpredictable, but another dimension of taxonomic composition indicating whether exotic or native species dominated the community was highly predictable. Taxonomic diversity (i.e., species richness) and functional composition (i.e., mean trait values) were intermittently predictable. Predictability also did not increase consistently with aridity. The dimension of taxonomic composition related to the identity of species in restored communities was more predictable (i.e., smaller residuals) in more arid sites, but functional composition was less predictable (i.e., larger residuals), and other outcomes showed no significant trend. Restoration outcomes were most predictable when they related to variation in dominant species, while those responding to rare species were harder to predict, indicating a potential role of scale in restoration predictability. Overall, our results highlight additional factors that might influence restoration predictability and add support to the importance of continuous monitoring and active management beyond one-time seed addition for successful grassland restoration in the United States.

Predictions of biodiversity are improved by integrating trait-based competition with abiotic filtering.

All organisms must simultaneously tolerate the environment and access limiting resources if they are to persist. Approaches to understanding abiotic filtering and competitive interactions have generally been developed independently. Consequently, integrating those factors to predict species abundances and community structure remains an unresolved challenge. We introduce a new synthetic framework that models both abiotic filtering and competition by using functional traits. First, our framework estimates species carrying capacities along abiotic gradients. Second, it estimates pairwise competitive interactions as a function of species trait differences. Applied to the study of a complex wetland community, our combined approach more than doubles the explained variance of species abundances compared to a model of abiotic tolerances alone. Trait-based integration of competitive interactions and abiotic filtering improves our ability to predict species abundances, bringing us closer to more accurate predictions of biodiversity structure in a changing world.

Plant functional traits have globally consistent effects on competition.

Phenotypic traits and their associated trade-offs have been shown to have globally consistent effects on individual plant physiological functions, but how these effects scale up to influence competition, a key driver of community assembly in terrestrial vegetation, has remained unclear. Here we use growth data from more than 3 million trees in over 140,000 plots across the world to show how three key functional traits--wood density, specific leaf area and maximum height--consistently influence competitive interactions. Fast maximum growth of a species was correlated negatively with its wood density in all biomes, and positively with its specific leaf area in most biomes. Low wood density was also correlated with a low ability to tolerate competition and a low competitive effect on neighbours, while high specific leaf area was correlated with a low competitive effect. Thus, traits generate trade-offs between performance with competition versus performance without competition, a fundamental ingredient in the classical hypothesis that the coexistence of plant species is enabled via differentiation in their successional strategies. Competition within species was stronger than between species, but an increase in trait dissimilarity between species had little influence in weakening competition. No benefit of dissimilarity was detected for specific leaf area or wood density, and only a weak benefit for maximum height. Our trait-based approach to modelling competition makes generalization possible across the forest ecosystems of the world and their highly diverse species composition.

An integrated framework of plant form and function: the belowground perspective.

Plant trait variation drives plant function, community composition and ecosystem processes. However, our current understanding of trait variation disproportionately relies on aboveground observations. Here we integrate root traits into the global framework of plant form and function. We developed and tested an overarching conceptual framework that integrates two recently identified root trait gradients with a well-established aboveground plant trait framework. We confronted our novel framework with published relationships between above- and belowground trait analogues and with multivariate analyses of above- and belowground traits of 2510 species. Our traits represent the leaf and root conservation gradients (specific leaf area, leaf and root nitrogen concentration, and root tissue density), the root collaboration gradient (root diameter and specific root length) and the plant size gradient (plant height and rooting depth). We found that an integrated, whole-plant trait space required as much as four axes. The two main axes represented the fast-slow 'conservation' gradient on which leaf and fine-root traits were well aligned, and the 'collaboration' gradient in roots. The two additional axes were separate, orthogonal plant size axes for height and rooting depth. This perspective on the multidimensional nature of plant trait variation better encompasses plant function and influence on the surrounding environment.

Climatic limits of temperate rainforest tree species are explained by xylem embolism resistance among angiosperms but not among conifers.

Hydraulic failure explains much of the increased rates of drought-induced tree mortality around the world, underlining the importance of understanding how species distributions are shaped by their vulnerability to embolism. Here we determined which physiological traits explain species climatic limits among temperate rainforest trees in a region where chronic water limitation is uncommon. We quantified the variation in stem embolism vulnerability and leaf turgor loss point among 55 temperate rainforest tree species in New Zealand and tested which traits were most strongly related to species climatic limits. Leaf turgor loss point and stem P50 (tension at which hydraulic conductance is at 50% of maximum) were uncorrelated. Stem P50 and hydraulic safety margin were the most strongly related physiological traits to climatic limits among angiosperms, but not among conifers. Morphological traits such as wood density and leaf dry matter content did not explain species climatic limits. Stem embolism resistance and leaf turgor loss point appear to have evolved independently. Embolism resistance is the most useful predictor of the climatic limits of angiosperm trees. High embolism resistance in the curiously overbuilt New Zealand conifers suggests that their xylem properties may be more closely related to growing slowly under nutrient limitation and to resistance to microbial decomposition.

Assessing the reliability of predicted plant trait distributions at the global scale.

AIM: Predictions of plant traits over space and time are increasingly used to improve our understanding of plant community responses to global environmental change. A necessary step forward is to assess the reliability of global trait predictions. In this study, we predict community mean plant traits at the global scale and present a systematic evaluation of their reliability in terms of the accuracy of the models, ecological realism and various sources of uncertainty. LOCATION: Global. TIME PERIOD: Present. MAJOR TAXA STUDIED: Vascular plants. METHODS: We predicted global distributions of community mean specific leaf area, leaf nitrogen concentration, plant height and wood density with an ensemble modelling approach based on georeferenced, locally measured trait data representative of the plant community. We assessed the predictive performance of the models, the plausibility of predicted trait combinations, the influence of data quality, and the uncertainty across geographical space attributed to spatial extrapolation and diverging model predictions. RESULTS: Ensemble predictions of community mean plant height, specific leaf area and wood density resulted in ecologically plausible trait-environment relationships and trait-trait combinations. Leaf nitrogen concentration, however, could not be predicted reliably. The ensemble approach was better at predicting community trait means than any of the individual modelling techniques, which varied greatly in predictive performance and led to divergent predictions, mostly in African deserts and the Arctic, where predictions were also extrapolated. High data quality (i.e., including intraspecific variability and a representative species sample) increased model performance by 28%. MAIN CONCLUSIONS: Plant community traits can be predicted reliably at the global scale when using an ensemble approach and high-quality data for traits that mostly respond to large-scale environmental factors. We recommend applying ensemble forecasting to account for model uncertainty, using representative trait data, and more routinely assessing the reliability of trait predictions.

Mapping local and global variability in plant trait distributions.

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.

Large leaves in warm, moist environments confer an advantage in seedling light interception efficiency.

Leaf size varies conspicuously along environmental gradients. Small leaves help plants cope with drought and frost, because of the effect of leaf size on boundary layer conductance; it is less clear what advantage large leaves confer in benign environments. We asked if large leaves give species of warm climates an advantage in seedling light interception efficiency over small-leaved species from colder environments. We measured seedling leaf, architectural and biomass distribution traits of 18 New Zealand temperate rainforest evergreens; we then used a 3-D digitiser and the Yplant program to model leaf area display and light interception. Species associated with mild climates on average had larger leaves and larger specific leaf areas (SLA) than those from cold climates, and displayed larger effective foliage areas per unit of aboveground biomass, indicating higher light interception efficiency at whole-plant level. This reflected differences in total foliage area, rather than in self-shading. Our findings advance the understanding of leaf size by showing that large leaves enable seedlings of species with highly conductive (but frost-sensitive) xylem to deploy large foliage areas without increasing self-shading. Leaf size variation along temperature gradients in humid forests may therefore reflect a trade-off between seedling light interception efficiency and susceptibility to frost.

Survival rates indicate that correlations between community-weighted mean traits and environments can be unreliable estimates of the adaptive value of traits.

Correlations between community-weighted mean (CWM) traits and environmental gradients are often assumed to quantify the adaptive value of traits. We tested this assumption by comparing these correlations with models of survival probability using 46 perennial species from long-term permanent plots in pine forests of Arizona. Survival was modelled as a function of trait × environment interactions, plant size, climatic variation and neighbourhood competition. The effect of traits on survival depended on the environmental conditions, but the two statistical approaches were inconsistent. For example, CWM-specific leaf area (SLA) and soil fertility were uncorrelated. However, survival was highest for species with low SLA in infertile soil, a result which agreed with expectations derived from the physiological trade-off underpinning leaf economic theory. CWM trait-environment relationships were unreliable estimates of how traits affected survival, and should only be used in predictive models when there is empirical support for an evolutionary trade-off that affects vital rates.

Frost and leaf-size gradients in forests: global patterns and experimental evidence.

Explanations of leaf size variation commonly focus on water availability, yet leaf size also varies with latitude and elevation in environments where water is not strongly limiting. We provide the first conclusive test of a prediction of leaf energy balance theory that may explain this pattern: large leaves are more vulnerable to night-time chilling, because their thick boundary layers impede convective exchange with the surrounding air. Seedlings of 15 New Zealand evergreens spanning 12-fold variation in leaf width were exposed to clear night skies, and leaf temperatures were measured with thermocouples. We then used a global dataset to assess several climate variables as predictors of leaf size in forest assemblages. Leaf minus air temperature was strongly correlated with leaf width, ranging from -0.9 to -3.2°C in the smallest- and largest-leaved species, respectively. Mean annual temperature and frost-free period were good predictors of evergreen angiosperm leaf size in forest assemblages, but no climate variable predicted deciduous leaf size. Although winter deciduousness makes large leaves possible in strongly seasonal climates, large-leaved evergreens are largely confined to frost-free climates because of their susceptibility to radiative cooling. Evergreen leaf size data can therefore be used to enhance vegetation models, and to infer palaeotemperatures from fossil leaf assemblages.

Niche opportunities for invasive annual plants in dryland ecosystems are controlled by disturbance, trophic interactions, and rainfall.

Resource availability and biotic interactions control opportunities for the establishment and expansion of invasive species. Studies on biotic resistance to plant invasions have typically focused on competition and occasionally on herbivory, while resource-oriented studies have focused on water or nutrient pulses. Through synthesizing these approaches, we identify conditions that create invasion opportunities. In a nested fully factorial experiment, we examined how chronic alterations in water availability and rodent density influenced the density of invasive species in both the Mojave Desert and the Great Basin Desert after fire. We used structural equation modeling to examine the direct and mediated effects controlling the density of invasives in both deserts. In the first 2 years after our controlled burn in the Great Basin, we observed that fire had a direct effect on increasing the invasive forb Halogeton glomeratus as well as a mediated effect through reducing rodent densities and herbivory. 4 years after the burn, the invasive annual grass Bromus tectorum was suppressing Halogeton glomeratus in mammal exclusion plots. There was a clear transition from years where invasives were controlled by disturbance and trophic interactions to years were resource availability and competition controlled invasive density. Similarly, in the Mojave Desert we observed a strong early influence of trophic processes on invasives, with Schismus arabicus benefitted by rodents and Bromus rubens negatively influenced by rodents. In the Mojave Desert, post-fire conditions became less important in controlling the abundance of invasives over time, while Bromus rubens was consistently benefitted by increases in fall rainfall.

Constraints on trait combinations explain climatic drivers of biodiversity: the importance of trait covariance in community assembly.

Trade-offs maintain diversity and structure communities along environmental gradients. Theory indicates that if covariance among functional traits sets a limit on the number of viable trait combinations in a given environment, then communities with strong multidimensional trait constraints should exhibit low species diversity. We tested this prediction in winter annual plant assemblages along an aridity gradient using multilevel structural equation modelling. Univariate and multivariate functional diversity measures were poorly explained by aridity, and were surprisingly poor predictors of community richness. By contrast, the covariance between maximum height and seed mass strengthened along the aridity gradient, and was strongly associated with richness declines. Community richness had a positive effect on local neighbourhood richness, indicating that climate effects on trait covariance indirectly influence diversity at local scales. We present clear empirical evidence that declines in species richness along gradients of environmental stress can be due to increasing constraints on multidimensional phenotypes.

Tree mortality across biomes is promoted by drought intensity, lower wood density and higher specific leaf area.

Drought events are increasing globally, and reports of consequent forest mortality are widespread. However, due to a lack of a quantitative global synthesis, it is still not clear whether drought-induced mortality rates differ among global biomes and whether functional traits influence the risk of drought-induced mortality. To address these uncertainties, we performed a global meta-analysis of 58 studies of drought-induced forest mortality. Mortality rates were modelled as a function of drought, temperature, biomes, phylogenetic and functional groups and functional traits. We identified a consistent global-scale response, where mortality increased with drought severity [log mortality (trees trees-1  year-1 ) increased 0.46 (95% CI = 0.2-0.7) with one SPEI unit drought intensity]. We found no significant differences in the magnitude of the response depending on forest biomes or between angiosperms and gymnosperms or evergreen and deciduous tree species. Functional traits explained some of the variation in drought responses between species (i.e. increased from 30 to 37% when wood density and specific leaf area were included). Tree species with denser wood and lower specific leaf area showed lower mortality responses. Our results illustrate the value of functional traits for understanding patterns of drought-induced tree mortality and suggest that mortality could become increasingly widespread in the future.

Regeneration patterns, environmental filtering and tree species coexistence in a temperate forest.

Forest ecologists researching the functional basis of tree regeneration patterns and species coexistence often attempt to correlate traits with light-gradient partitioning. However, an exclusive focus on light can overlook other important drivers of forest dynamics. We measured light, temperatures, humidity and sapling densities in each of four phases of a forest dynamic mosaic in New Zealand: shaded understoreys, tree-fall gaps, treefern groves and clearings. We then measured leaf, wood and seed traits, as potential predictors of species' regeneration patterns. Saplings of 18 out of 21 species were significantly associated with one or other of the four phases, and associations were best predicted by a two-trait model (leaf size, wood density) explaining 51% of observed variation. Species associated with treefall gaps had traits favouring light pre-emption (large leaves, low-density wood), whereas those establishing in clearings mostly had small leaves and dense wood, traits probably conferring resistance to the frosts and summer water deficits that saplings were exposed to there. The dynamics of some forests cannot be explained adequately by light-gradient partitioning through a growth vs shade tolerance tradeoff, underpinned by the leaf economics spectrum. Consideration of multiple environmental filters and multiple traits will enhance understanding of regeneration patterns and species coexistence.

Invasive species' leaf traits and dissimilarity from natives shape their impact on nitrogen cycling: a meta-analysis.

Many exotic species have little apparent impact on ecosystem processes, whereas others have dramatic consequences for human and ecosystem health. There is growing evidence that invasions foster eutrophication. We need to identify species that are harmful and systems that are vulnerable to anticipate these consequences. Species' traits may provide the necessary insights. We conducted a global meta-analysis to determine whether plant leaf and litter functional traits, and particularly leaf and litter nitrogen (N) content and carbon: nitrogen (C : N) ratio, explain variation in invasive species' impacts on soil N cycling. Dissimilarity in leaf and litter traits among invaded and noninvaded plant communities control the magnitude and direction of invasion impacts on N cycling. Invasions that caused the greatest increases in soil inorganic N and mineralization rates had a much greater litter N content and lower litter C : N in the invaded than the reference community. Trait dissimilarities were better predictors than the trait values of invasive species alone. Quantifying baseline community tissue traits, in addition to those of the invasive species, is critical to understanding the impacts of invasion on soil N cycling.

Exotic weeds and fluctuating microclimate can constrain native plant regeneration in urban forest restoration.

Restoring forest structure and composition is an important component of urban land management, but we lack clear understanding of the mechanisms driving restoration success. Here we studied two indicators of restoration success in temperate rainforests: native tree regeneration and epiphyte colonization. We hypothesized that ecosystem properties such as forest canopy openness, abundance of exotic herbaceous weeds, and the microclimate directly affect the density and diversity of native tree seedlings and epiphytes. Relationships between environmental conditions and the plant community were investigated in 27 restored urban forests spanning 3-70 years in age and in unrestored and remnant urban forests. We used structural equation modelling to determine the direct and indirect drivers of native tree regeneration and epiphyte colonization in the restored forests. Compared to remnant forest, unrestored forest had fewer native canopy tree species, significantly more light reaching the forest floor annually, and higher exotic weed cover. Additionally, epiphyte density was lower and native tree regeneration density was marginally lower in the unrestored forests. In restored forests, light availability was reduced to levels found in remnant forests within 20 years of restoration planting, followed shortly thereafter by declines in herbaceous exotic weeds and reduced fluctuation of relative humidity and soil temperatures. Contrary to expectations, canopy openness was only an indirect driver of tree regeneration and epiphyte colonization, but it directly regulated weed cover and microclimatic fluctuations, both of which directly drove the density and richness of regeneration and epiphyte colonization. Epiphyte density and diversity were also positively related to forest basal area, as large trees provide physical habitat for colonization. These results imply that ecosystem properties change predictably after initial restoration plantings, and that reaching critical thresholds in some ecosystem properties makes conditions suitable for the regeneration of late successional species, which is vital for restoration success and long-term ecosystem sustainability. Abiotic and biotic conditions that promote tree regeneration and epiphyte colonization will likely be present in forests with a basal area ≥27 m2 /ha. We recommend that urban forest restoration plantings be designed to promote rapid canopy closure to reduce light availability, suppress herbaceous weeds, and stabilize the microclimate.

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.