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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.

A main goal of ecological and evolutionary biology is understanding and predicting interactions between populations and both abiotic and biotic environments, the spatial and temporal variation of these interactions, and the effects on population dynamics and performance. Trait-based approaches can help to model these interactions and generate a comprehensive understanding of ecosystem functioning. A central tool is the collation of databases that include species trait information. Such centralized databases have been set up for a number of organismal groups but is lacking for one of the most important groups of predators in terrestrial ecosystems – spiders. Here we promote the collation of an open spider traits database, integrated into the global Open Traits Network. We explore the current collation of spider data and cover the logistics of setting up a global database, including which traits to include, the source of data, how to input data, database governance, geographic cover, accessibility, quality control and how to make the database sustainable long-term. Finally, we explore the scope of research questions that could be investigated using a global spider traits database.

Summary Competitor, stress‐tolerator, ruderal ( CSR ) theory is a prominent plant functional strategy scheme previously applied to local floras. Globally, the wide geographic and phylogenetic coverage of available values of leaf area ( LA ), leaf dry matter content ( LDMC ) and specific leaf area ( SLA ) (representing, respectively, interspecific variation in plant size and conservative vs . acquisitive resource economics) promises the general application of CSR strategies across biomes, including the tropical forests hosting a large proportion of Earth's diversity. We used trait variation for 3068 tracheophytes (representing 198 families, six continents and 14 biomes) to create a globally calibrated CSR strategy calculator tool and investigate strategy–environment relationships across biomes world‐wide. Due to disparity in trait availability globally, co‐inertia analysis was used to check correspondence between a ‘wide geographic coverage, few traits’ data set and a ‘restricted coverage, many traits’ subset of 371 species for which 14 whole‐plant, flowering, seed and leaf traits (including leaf nitrogen content) were available. CSR strategy/environment relationships within biomes were investigated using fourth‐corner and RLQ analyses to determine strategy/climate specializations. Strong, significant concordance ( RV = 0·597; P < 0·0001) was evident between the 14 trait multivariate space and when only LA , LDMC and SLA were used. Biomes such as tropical moist broadleaf forests exhibited strategy convergence (i.e. clustered around a CS / CSR median; C:S:R = 43:42:15%), with CS ‐selection associated with warm, stable situations (lesser temperature seasonality), with greater annual precipitation and potential evapotranspiration. Other biomes were characterized by strategy divergence: for example, deserts varied between xeromorphic perennials such as Larrea divaricata, classified as S‐selected (C:S:R = 1:99:0%) and broadly R‐selected annual herbs (e.g. Claytonia perfoliata ; R/ CR ‐selected; C:S:R = 21:0:79%). Strategy convergence was evident for several growth habits (e.g. trees) but not others (forbs). The CSR strategies of vascular plants can now be compared quantitatively within and between biomes at the global scale. Through known linkages between underlying leaf traits and growth rates, herbivory and decomposition rates, this method and the strategy–environment relationships it elucidates will help to predict which kinds of species may assemble in response to changes in biogeochemical cycles, climate and land use.

Functional traits have long been considered the ‘holy grail’ in community ecology due to their potential to link phenotypic variation with ecological processes. Advancements across taxonomic disciplines continue to support functional ecology's objective to approach generality in community assembly. However, a divergence of definitions, aims and methods across taxa has created discord, limiting the field's predictive capacity. Here, we provide a guide to support functional ecological comparisons across taxa. We describe advances in cross‐taxa functional research, identify gaps in approaches, synthesize definitions and unify methodological considerations. When deciding which traits to compare, particularly response traits, we advocate selecting functionally analogous traits that relate to community assembly processes. Finally, we describe at what scale and for which questions functional comparisons across taxa are useful and when other approaches may be more constructive. Our approach promotes standardized methods for integrative research across taxa to identify broad trends in community assembly.

The classification of plant species according to the CSR ecological strategy scheme has been proposed as a common language that allows comparison among species, communities, and floras. Although several studies on European continent have demonstrated a consistent association between CSR strategies and key ecosystem processes, studies of this type are still lacking in other ecoregions worldwide. For the first time, the CSR strategy scheme is applied in a tropical plant community. In a Brazilian mountain grassland ecosystem characterized by both high biodiversity and environmental stress, we sampled various functional traits of 48 herbaceous species in stony and sandy grasslands, and evaluated the relationship between CSR strategies and functional traits with several environmental parameters. The extremely infertile soils in the two studied habitats may have acted as a major environmental filter leading to a clear predominance of the stress-tolerant strategy in both communities. However, fine-scale environmental differences between the two communities resulted in the filtering of distinct functional trait values. The sites with coarser soil texture, lower percentage of plant cover and (paradoxically) higher mineral nutrient concentrations favored plants with narrower leaves, higher stress tolerance, lower competitiveness, and higher sclerophylly (i.e., lower specific leaf area and higher leaf dry matter content). The comparison between the functional character of stony and sandy communities evidenced the influence of soil texture and water availability in the environmental filtering. This study highlighted the validity of the CSR classification outside the temperate region where it was originally developed and corroborated.

Trait-based approaches have led to significant advances in plant ecology, but are currently biased toward above-ground traits. It is becoming clear that a stronger emphasis on below-ground traits is needed to better predict future changes in plant biodiversity and their consequences for ecosystem functioning. Here I propose six ‘below-ground frontiers’ in traitbased plant ecology, with an emphasis on traits governing soil nutrient acquisition: redefining fine roots; quantifying root trait dimensionality; integrating mycorrhizas; broadening the suite of root traits; determining linkages between root traits and abiotic and biotic factors; and understanding ecosystem-level consequences of root traits. Focusing research efforts along these frontiers should help to fulfil the promise of trait-based ecology: enhanced predictive capacity across ecological scales.

We present a series of competing path models relating interspecific patterns between specific leaf area, leaf nitrogen content, net photosynthesis and stomatal conductance and test these against data from 22 species of herbaceous plants grown under controlled conditions with contrasting irradiance and nutrient supply rates. We then compare these results with two previous data sets, one based on field measures and one based on glasshouse measures, to determine the robustness of the results. Only one model was able to account for the patterns of direct and indirect effects between the four variables to all data sets. In this model specific leaf area is the forcing variable that directly affects both leaf nitrogen levels and net photosynthetic rates. Leaf nitrogen then directly affects net photosynthetic rates which in turn then affect stomatal conductance to water.

Questions: One central assumption of trait screening approaches in comparative plant ecology, i.e. simultaneous measurement of traits on a large number of species or populations, is that the species level captures a major part of trait variation. The current development of large databases has led to a new screening approach that relies on the extraction of trait values from databases, rather than on measurement of traits in the field. We tested this assumption with the following questions: (1) is the magnitude of intra-specific variability of co-occurring species lower than inter-specific variability for a given trait, in comparisons at different spatial scales; (2) is species hierarchy based on trait values conserved across different spatial scales and data sets (stable species hierarchy hypothesis); and (3) when we compare different traits, what is the more stable trait that is conserved across different spatial scales and data sets? Methods: We combined approaches commonly used in functional ecology, i.e. experimental data, field observations and extraction of data from a global database, and analysed the magnitude of intra-specific and inter-specific trait variations for a large number of traits across contrasting environmental conditions for 18-39 (mostly) herbaceous species, according to the data set used. Results: For most traits, inter-specific variability was higher than intra-specific variability, and species ranking was conserved across different data sets and spatial scales. However, we also detected important differential responses in terms of intra-specific trait variability, depending on the trait examined: SLA, LDMC, SM, seed N concentration and onset of flowering were more stable, whereas leaf chemical traits and RH were more flexible traits. Conclusions: Our study validated, for the species studied, the stable species hierarchy hypothesis in the case of several, but not all, widely used traits. The main conclusion is that the strength of the species signal is strong enough for some traits to allow values to be used from different data sets (experiments, databases) to characterize local populations of species: for SM, seed N concentration, RH, SLA and LDMC.

1. Westoby's [Plant and Soil (1998), 199, 213] Leaf-Height-Seed (LHS) plant strategy scheme quantifies the strategy of a plant based on its location in a three-dimensional space defined by three functional traits: specific leaf area (SLA), height, and seed mass. This scheme is based on aboveground traits and may neglect strategies of belowground resource capture if root functioning is not mirrored in any of the axes. How then do fine roots fit into the LHS scheme? 2. We measured 10 functional traits on 133 plant species in a ponderosa pine forest in northern Arizona, USA. This data set was used to evaluate how well the LHS scheme accounts for the variation in above and belowground traits. 3. The three most important plant strategies were composed of multiple correlated traits, but SLA, seed mass, and height loaded on separate principle components. The first axis reflected the widely observed 'leaf economics spectrum'. Species at the high end of this spectrum had high SLA, high leaf and fine root nitrogen (N) concentration, and low leaf dry matter content. The second axis reflected variation in seed mass and fine root morphology. Plants at the positive end of this spectrum were plants with large seeds and low specific root length (SRL). The third axis reflected variation in height and phenology. Plants at the positive end of this spectrum were tall species that flower late in the growing season. 4. Leaf N concentration was positively correlated with fine root N concentration. SRL was weakly positively correlated with SLA. SRL was not correlated with fine root N concentration. Leaf litter decomposition rate was positively correlated with the leaf economics spectrum and was negatively correlated with the height and phenology spectrum. 5. Leaf traits, seed mass, and height appear to be integrating properties of species that reflect much of the variation in plant function, including root function. Fine root N concentration was positively mirrored by the leaf economics spectrum, and SRL was inversely mirrored by seed mass. The leaf and height axes play a role in controlling leaf litter decomposability, indicating that these strategy axes have important consequences for ecosystem functioning.