Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Alterations in water availability and drought events as predicted by climate change scenarios will increasingly impact natural communities with effects already emerging at present. Water deficit leads to increasing physiological stress in plants, likely affecting floral development and causing changes in floral morphology, nectar and pollen production or scent. Understanding how these floral traits are altered by water deficit is necessary to predict changes in plant–pollinator interactions and how communities are impacted in the future. Here we employ a meta‐analysis approach to synthesize the current evidence of experimental water deficit on floral traits and plant–pollinator interactions. Furthermore, we explore experimental factors potentially increasing heterogeneity between studies and provide ideas how to enhance comparability between studies. In the end, we highlight future directions and knowledge gaps for floral traits and plant–pollinator interactions under water deficit. Our analysis showed consistent decreases in floral size, number of flowers and nectar volume to reduced water availability. Other floral traits such as the start of flowering or herkogamy showed no consistent pattern. This indicates that effects of reduced water availability differ between specific traits that are potentially involved in different functions such as pollinator attraction or efficiency. We found no general decreasing visitation rates with water deficit for flower–visitor interactions. Furthermore, the comparison of available studies suggests that increased reporting of plant stress severity and including more hydraulic and physiological measurements will improve the comparability across experiments and aid a more mechanistic understanding of plant–pollinator interactions under altered environmental conditions. Overall, our results show that water deficit has the potential to strongly affect plant–pollinator interactions via changes in specific floral traits. Linking these changes to pollination services and pollinator performance is one crucial step for understanding how changing water availability and drought events under climate change will alter plant and pollinator communities.

Aim: Intraspecific trait variation (ITV) within natural plant communities can be large, influencing local ecological processes and dynamics. Here, we shed light on how ITV in vegetative and floral traits responds to large‐scale abiotic and biotic gradients (i.e., climate and species richness). Specifically, we tested whether associations of ITV with temperature, precipitation and species richness were consistent with any of four hypotheses relating to stress tolerance and competition. Furthermore, we estimated the degree of correlation between ITV in vegetative and floral traits and how they vary along the gradients.Location: Global.Time period: 1975–2016.Major taxa studied: Herbaceous and woody plants.Methods: We compiled a dataset of 18,401 measurements of the absolute extent of ITV (measured as the coefficient of variation) in nine vegetative and seven floral traits from 2,822 herbaceous and woody species at 2,372 locations.Results: Large‐scale associations between ITV and climate were trait specific and more prominent for vegetative traits, especially leaf morphology, than for floral traits. The ITV showed pronounced associations with climate, with lower ITV values in colder areas and higher values in drier areas. The associations of ITV with species richness were inconsistent across traits. Species‐specific associations across gradients were often idiosyncratic, and covariation in ITV was weaker between vegetative and floral traits than within the two trait groups.Main conclusions: Our results show that, depending on the traits considered, ITV either increased or decreased with climate stress and species richness, suggesting that both factors can constrain or enhance ITV, which might foster plant‐population persistence in stressful conditions. Given the species‐specific responses and covariation in ITV, associations can be hard to predict for traits and species not yet studied. We conclude that consideration of ITV can improve our understanding of how plants cope with stressful conditions and environmental change across spatial and biological scales.

Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small “many analyst” study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future.

Reduced water availability can cause physiological stress in plants that affects floral development leading to changes in floral morphology and traits that mediate interactions with pollinators. As pollinators can detect small changes in trait expressions, drought-induced changes in floral traits could affect pollinator visitations. However, the linkage between changes in floral traits and pollinator visitations under drought conditions is not well explored. We, therefore, tested whether drought-induced changes in floral morphology and abundance of flowers are linked to changes in pollinator visitations. We conducted flight cage experiments with a radio frequency identification system for automated visitation recordings with bumble bees (Bombus terrestris) and common charlock (Sinapis arvensis) as the model system. In total, we recorded interactions for 31 foraging bumble bees and 6569 flower visitations. We found that decreasing soil moisture content correlated with decreasing size of all measured morphological traits except stamen length and nectar tube width. The reductions in floral size, petal width and length, nectar tube depth and number of flowers resulted in decreasing visitation rates by bumble bees. These decreasing visitations under lower soil moisture availability might be explained by lower numbers of flowers and thus a reduced attractiveness and/or by increased difficulties experienced by bumble bees in handling smaller flowers. Whether these effects act additively or synergistically on pollinator behaviour and whether this leads to changes in pollen transfer and to different selectionp ressures require further investigation.