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.

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.

Water availability dictates how plant traits predict demographic rates.

A major goal in ecology is to make generalizable predictions of organism responses to environmental variation based on their traits. However, straightforward relationships between traits and fitness are rare and likely to vary with environmental context. Characterizing how traits mediate demographic responses to the environment may enhance the predictions of organism responses to global change. We synthesized 15 years of demographic data and species-level traits in a shortgrass steppe to determine whether the effects of leaf and root traits on growth and survival depended on seasonal water availability. We predicted that (1) species with drought-tolerant traits, such as lower leaf turgor loss point (TLP) and higher leaf and root dry matter content (LDMC and RDMC), would be more likely to survive and grow in drier years due to higher wilting resistance, (2) these traits would not predict fitness in wetter years, and (3) traits that more directly measure physiological mechanisms of water use such as TLP would best predict demographic responses. We found that graminoids with more negative TLP and higher LDMC and RDMC had higher survival rates in drier years. Forbs demonstrated similar yet more variable responses. Graminoids grew larger in wetter years, regardless of traits. However, in both wet and dry years, graminoids with more negative TLP and higher LDMC and RDMC grew larger than less negative TLP and low LDMC and RDMC species. Traits significantly mediated the impact of drought on survival, but not growth, suggesting that survival could be a stronger driver of species' drought response in this system. TLP predicted survival in drier years, but easier to measure LDMC and RDMC were equal or better predictors. These results advance our understanding of the mechanisms by which drought drives population dynamics, and show that abiotic context determines how traits drive fitness.

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.

Cover and density of southwestern ponderosa pine understory plants in permanent chart quadrats (2002-2020).

This data set consists of 101 permanent 1 m × 1 m (1-m2 ) quadrats located within southwestern ponderosa pine ecosystems near Flagstaff, Arizona, USA. Individual plants in these quadrats were identified and mapped annually for 19 years (2002-2020). The original chart quadrats were established between 1912 and 1927 to determine the effects of domestic livestock grazing on herbaceous plants and pine seedlings. Today these data provide opportunities to examine the effects of climate and land-use change on plant demography, population dynamics, and community processes. We provide the following data and data formats: (1) digitized maps of all plant locations in shapefile and geodatabase format, (2) shapefiles showing annual locations of each individual plant species, (3) annual maps of each quadrat in TIFF and PDF format, (4) annual basal area of each species per quadrat for species mapped as polygons, (5) tabular representation of polygon areas and centroid locations for plant species mapped as polygons, (6) tabular representation of point locations for plant species mapped as points, (7) plot-scale 20 m × 20 m overstory tree canopy cover, tree basal area, parent material, and elevation, (8) quadrat-scale information (e.g., quadrat site and number, coordinates in UTM Zone 12 and latitude/longitude, and descriptive comments for each quadrat), (9) plant species list, (10) summary of plant species observed in each quadrat, (11) summary of quadrats mapped by site and year, and (12) data formatted for use in Integral Projection Models (IPM) and plant population analyses. There are no copyright restrictions; please cite this paper and the associated data set when data are used in publications.

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.

Root traits explain plant species distributions along climatic gradients yet challenge the nature of ecological trade-offs.

Ecological theory is built on trade-offs, where trait differences among species evolved as adaptations to different environments. Trade-offs are often assumed to be bidirectional, where opposite ends of a gradient in trait values confer advantages in different environments. However, unidirectional benefits could be widespread if extreme trait values confer advantages at one end of an environmental gradient, whereas a wide range of trait values are equally beneficial at the other end. Here, we show that root traits explain species occurrences along broad gradients of temperature and water availability, but model predictions only resembled trade-offs in two out of 24 models. Forest species with low specific root length and high root tissue density (RTD) were more likely to occur in warm climates but species with high specific root length and low RTD were more likely to occur in cold climates. Unidirectional benefits were more prevalent than trade-offs: for example, species with large-diameter roots and high RTD were more commonly associated with dry climates, but species with the opposite trait values were not associated with wet climates. Directional selection for traits consistently occurred in cold or dry climates, whereas a diversity of root trait values were equally viable in warm or wet climates. Explicit integration of unidirectional benefits into ecological theory is needed to advance our understanding of the consequences of trait variation on species responses to environmental change.

Linking functional traits and demography to model species-rich communities.

It has long been anticipated that relating functional traits to species demography would be a cornerstone for achieving large-scale predictability of ecological systems. If such a relationship existed, species demography could be modeled only by measuring functional traits, transforming our ability to predict states and dynamics of species-rich communities with process-based community models. Here, we introduce a new method that links empirical functional traits with the demographic parameters of a process-based model by calibrating a transfer function through inverse modeling. As a case study, we parameterize a modified Lotka-Volterra model of a high-diversity mountain grassland with static plant community and functional trait data only. The calibrated trait-demography relationships are amenable to ecological interpretation, and lead to species abundances that fit well to the observed community structure. We conclude that our new method offers a general solution to bridge the divide between trait data and process-based models in species-rich ecosystems.

The fungal collaboration gradient dominates the root economics space in plants.

Plant economics run on carbon and nutrients instead of money. Leaf strategies aboveground span an economic spectrum from "live fast and die young" to "slow and steady," but the economy defined by root strategies belowground remains unclear. Here, we take a holistic view of the belowground economy and show that root-mycorrhizal collaboration can short circuit a one-dimensional economic spectrum, providing an entire space of economic possibilities. Root trait data from 1810 species across the globe confirm a classical fast-slow "conservation" gradient but show that most variation is explained by an orthogonal "collaboration" gradient, ranging from "do-it-yourself" resource uptake to "outsourcing" of resource uptake to mycorrhizal fungi. This broadened "root economics space" provides a solid foundation for predictive understanding of belowground responses to changing environmental conditions.

The Net Effect of Functional Traits on Fitness.

Generalizing the effect of traits on performance across species may be achievable if traits explain variation in population fitness. However, testing relationships between traits and vital rates to infer effects on fitness can be misleading. Demographic trade-offs can generate variation in vital rates that yield equal population growth rates, thereby obscuring the net effect of traits on fitness. To address this problem, we describe a diversity of approaches to quantify intrinsic growth rates of plant populations, including experiments beyond range boundaries, density-dependent population models built from long-term demographic data, theoretical models, and methods that leverage widely available monitoring data. Linking plant traits directly to intrinsic growth rates is a fundamental step toward rigorous predictions of population dynamics and community assembly.

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.

Macroclimate and Topography Interact to Influence the Abundance of Divaricate Plants in New Zealand.

The abundance of the divaricate growth form in New Zealand has been interpreted as either (a) the response of an isolated flora to cool, dry, Plio-Pleistocene climates; or (b) a defense against large browsing birds (moa) that were hunted to extinction shortly after human arrival during the last millennium. We used patterns of divaricate plant abundance across present-day landscapes to test a novel synthetic hypothesis: that the divaricate form is of most value to plants on fertile soils that attract herbivores, on sites where climatic constraints prevent plants from quickly growing out of the browse zone. This hypothesis predicts that divaricate species should be most abundant on terraces (landforms that are both fertile and frost-prone) in regions that are cold and dry, and should be scarce across all topographic positions in the warmest (largely frost-free) regions. To address our hypothesis, we first tested the influence of topography on frost regimes and nutrient levels by measuring temperatures and soil total C, N, and P at four standard topographic positions at five localities differing widely in macroclimate. We then extracted a dataset of 236 surveys comprising 9,877 relevé plots from the New Zealand National Vegetation Survey databank. We calculated the proportion of arborescent species with a divaricate growth form and the proportion of total arborescentcover contributed by divaricates on each plot; we then fitted linear mixed-effect models predicting these response variables as functions of topographic position and climate. The number of frosts recorded averaged <1 yr-1 at the warmest of the five sites studied, to >60 yr-1 on all topographic positions at the coldest site. Terraces were subject to more frequent and harder frosts than any other topographic position. Topography had no significant influence on total N or C:N, but total P was higher on terraces and in gullies than on faces or ridges. Frost-free period was the dominant influence on both species representation and cover of divaricate plants throughout the country. The effect of topography was also significant, but weaker. The effect of frost-free period was stronger on sites with water deficits than on sites where precipitation exceeded evapotranspiration. Divaricates made their largest contributions on terraces in cold, dry regions; as predicted, they were scarce on all topographic positions on sites with frost-free periods >300 days. Our hypothesis was generally supported, although the effect of topography on divaricate abundance was not as strong as some previous studies led us to expect. Divaricates made their largest contributions to arborescent species richness and cover on sites where climatic restrictions on growth coincide with relatively high nutrient availability. The contemporary distribution of the divaricate form across New Zealand landscapes thus appears to be reasonably well explained by the hypothesized interaction of climate and fertility-mediated browsing, although experiments may provide more conclusive tests of this hypothesis.

Abiotic factors influence patterns of bacterial diversity and community composition in the Dry Valleys of Antarctica.

The Dry Valleys of Antarctica are a unique ecosystem of simple trophic structure, where the abiotic factors that influence soil bacterial communities can be resolved in the absence of extensive biotic interactions. This study evaluated the degree to which aspects of topographic, physicochemical and spatial variation explain patterns of bacterial richness and community composition in 471 soil samples collected across a 220 square kilometer landscape in Southern Victoria Land. Richness was most strongly influenced by physicochemical soil properties, particularly soil conductivity, though significant trends with several topographic and spatial variables were also observed. Structural equation modeling (SEM) supported a final model in which variation in community composition was best explained by physicochemical variables, particularly soil water content, and where the effects of topographic variation were largely mediated through their influence on physicochemical variables. Community dissimilarity increased with distance between samples, and though most of this variation was explained by topographic and physicochemical variation, a small but significant relationship remained after controlling for this environmental variation. As the largest survey of terrestrial bacterial communities of Antarctica completed to date, this work provides fundamental knowledge of the Dry Valleys ecosystem, and has implications globally for understanding environmental factors that influence bacterial distributions.

Alternative designs and tropical tree seedling growth performance landscapes.

The functional trait values that constitute a whole-plant phenotype interact with the environment to determine demographic rates. Current approaches often fail to explicitly consider trait × trait and trait × environment interactions, which may lead to missed information that is valuable for understanding and predicting the drivers of demographic rates and functional diversity. Here, we consider these interactions by modeling growth performance landscapes that span multidimensional trait spaces along environmental gradients. We utilize individual-level leaf, stem, and root trait data combined with growth data from tree seedlings along soil nutrient and light gradients in a hyper-diverse tropical rainforest. We find that multiple trait combinations in phenotypic space (i.e., alternative designs) lead to multiple growth performance peaks that shift along light and soil axes such that no single or set of interacting traits consistently results in peak growth performance. Evidence from these growth performance peaks also generally indicates frequent independence of above- and belowground resource acquisition strategies. These results help explain how functional diversity is maintained in ecological communities and question the practice of utilizing a single trait or environmental variable, in isolation, to predict the growth performance of individual trees.

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.

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.

Biotic interactions are an unexpected yet critical control on the complexity of an abiotically driven polar ecosystem.

Abiotic and biotic factors control ecosystem biodiversity, but their relative contributions remain unclear. The ultraoligotrophic ecosystem of the Antarctic Dry Valleys, a simple yet highly heterogeneous ecosystem, is a natural laboratory well-suited for resolving the abiotic and biotic controls of community structure. We undertook a multidisciplinary investigation to capture ecologically relevant biotic and abiotic attributes of more than 500 sites in the Dry Valleys, encompassing observed landscape heterogeneities across more than 200 km2. Using richness of autotrophic and heterotrophic taxa as a proxy for functional complexity, we linked measured variables in a parsimonious yet comprehensive structural equation model that explained significant variations in biological complexity and identified landscape-scale and fine-scale abiotic factors as the primary drivers of diversity. However, the inclusion of linkages among functional groups was essential for constructing the best-fitting model. Our findings support the notion that biotic interactions make crucial contributions even in an extremely simple ecosystem.

An experimental test of the Community Assembly by Trait Selection (CATS) model.

The Community Assembly by Trait Selection (CATS) model of community assembly predicts species abundances along environmental gradients in relatively undisturbed vegetation. Here we ask whether this model, when calibrated with data from natural plant communities, can predict the abundances of five dominant grass species (Bouteloua gracilis, Elymus elymoides, Festuca arizonica, Muhlenbergia montana, and Poa fendleriana) in a greenhouse experiment that manipulated light and soil properties. To address this question, we used generalized additive models (GAMs) to model community-weighted mean (CWM) seed mass, mean Julian flowering date, and specific root length (SRL) as non-linear functions of two environmental variables (soil pH and pine basal area) in natural vegetation. The model-fitted CWM traits were then used as constraints in the CATS model to predict the relative abundance of the five grass species that were seeded in a mixture at equal densities into a 2×2 factorial experiment with soil parent material and light level as crossed factors. Light was the most important factor influencing seedling community composition, especially the abundances of Bouteloua gracilis and Poa fendleriana. The model-predicted relative abundances were significantly correlated with the observed relative abundances, and the model accurately predicted the dominant species in every treatment. P. fendleriana was correctly predicted to be the most abundant species in both shade treatments and the sun-basalt treatment, and B. gracilis was correctly predicted to be the most abundant species in the sun-limestone treatment. Our results provide experimental evidence that environmental filtering of the species pool occurs in the early stages of community assembly (including germination, emergence, and early growth), and that trait-based models calibrated with data from natural plant communities can be used to predict the outcome of the early stages of community assembly under experimental conditions.

Phylogenetic patterns and phenotypic profiles of the species of plants and mammals farmed for food.

The origins of agriculture were key events in human history, during which people came to depend for their food on small numbers of animal and plant species. However, the biological traits determining which species were domesticated for food provision, and which were not, are unclear. Here, we investigate the phylogenetic distribution of livestock and crops, and compare their phenotypic traits with those of wild species. Our results indicate that phylogenetic clustering is modest for crop species but more intense for livestock. Domesticated species explore a reduced portion of the phenotypic space occupied by their wild counterparts and have particular traits in common. For example, herbaceous crops are globally characterized by traits including high leaf nitrogen concentration and tall canopies, which make them fast-growing species and proficient competitors. Livestock species are relatively large mammals with low basal metabolic rates, which indicate moderate to slow life histories. Our study therefore reveals ecological differences in domestication potential between plants and mammals. Domesticated plants belong to clades with traits that are advantageous in intensively managed high-resource habitats, whereas domesticated mammals are from clades adapted to moderately productive environments. Combining comparative phylogenetic methods with ecologically relevant traits has proven useful to unravel the causes and consequences of domestication.