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.

Environmental exposure to active pharmaceutical ingredients (APIs) can have negative effects on the health of ecosystems and humans. While numerous studies have monitored APIs in rivers, these employ different analytical methods, measure different APIs, and have ignored many of the countries of the world. This makes it difficult to quantify the scale of the problem from a global perspective. Furthermore, comparison of the existing data, generated for different studies/regions/continents, is challenging due to the vast differences between the analytical methodologies employed. Here, we present a global-scale study of API pollution in 258 of the world’s rivers, representing the environmental influence of 471.4 million people across 137 geographic regions. Samples were obtained from 1,052 locations in 104 countries (representing all continents and 36 countries not previously studied for API contamination) and analyzed for 61 APIs. Highest cumulative API concentrations were observed in sub-Saharan Africa, south Asia, and South America. The most contaminated sites were in low- to middle-income countries and were associated with areas with poor wastewater and waste management infrastructure and pharmaceutical manufacturing. The most frequently detected APIs were carbamazepine, metformin, and caffeine (a compound also arising from lifestyle use), which were detected at over half of the sites monitored. Concentrations of at least one API at 25.7% of the sampling sites were greater than concentrations considered safe for aquatic organisms, or which are of concern in terms of selection for antimicrobial resistance. Therefore, pharmaceutical pollution poses a global threat to environmental and human health, as well as to delivery of the United Nations Sustainable Development Goals.

Methods of reconstructing changes in plant traits over long time scales are needed to understand the impact of changing environmental conditions on ecosystem processes and services. Although Holocene pollen have been extensively used to provide records of vegetation history, few studies have adopted a functional trait approach that is pertinent to changes in ecosystem processes. Here, for woody and herbaceous fen peatland communities, we use modern pollen and vegetation data combined with pollen records from Holocene deposits to reconstruct vegetation functional dynamics. The six traits chosen (measures of leaf area-to-mass ratio and leaf nutrient content) are known to modulate species’ fitness and to vary with changes in ecosystem processes. We fitted linear mixed effects models between community weighted mean (CWM) trait values of the modern pollen and vegetation to determine whether traits assigned to pollen types could be used to reconstruct traits found in the vegetation from pollen assemblages. We used relative pollen productivity (RPP) correction factors in an attempt to improve this relationship. For traits showing the best fit between modern pollen and vegetation, we applied the model to dated Holocene pollen sequences from Fenland and Romney Marsh in eastern and southern England and reconstructed temporal changes in trait composition. RPP adjustment did not improve the linear relationship between modern pollen and vegetation. Leaf nutrient traits (leaf C and N) were generally more predictable from pollen data than mass-area traits. We show that inferences about biomass accumulation and decomposition rates can be made using Holocene trait reconstructions. While it is possible to reconstruct community-level trends for some leaf traits from pollen assemblages preserved in sedimentary archives in wetlands, we show the importance of testing methods in modern systems first and encourage further development of this approach to address issues concerning the pollen-plant abundance relationship and pollen source area.

Edge effects are among the most significant consequences of forest fragmentation. Therefore, understanding the impacts of edge creation on biodiversity is crucial for forest management and biological conservation. In this study, we used trait‐based and phylogenetic approaches to examine the effects of fragmentation on components of diversity and above‐ground biomass of rainforest tree communities in Madagascar in forest edge vs. interior habitats. Tree communities in forest edges showed lower phylogenetic diversity relative to those in interior habitats, suggesting that some clades may be more vulnerable to environmental filtering than others. Functional diversity was also significantly lower on the edge for productivity traits, but not for dispersal traits. Tree communities in the forest edge showed higher divergence of dispersal traits and lower divergence in productivity traits than expected, while functional diversity in interior forest did not differ from random expectations. This suggests that separate mechanisms affect productivity traits vs. dispersal traits in edge habitats. There was no significant difference in above‐ground biomass between edge and interior habitats, suggesting that edge effects have not yet negatively influenced the forest's potential for carbon storage. However, these changes may not have occurred yet, given the slow turnover of tree communities. Synthesis and applications. Our results highlight the role of edge effects in the erosion of functional and phylogenetic diversity of highly diverse tree communities. While above‐ground biomass did not appear to be affected by forest edge in our study, we suggest long‐term monitoring of forests for potential changes in ecosystem functioning. These findings also indicate the need to reduce edge creation and buffer existing edges for holistic biodiversity conservation.

In the move to decarbonise energy supplies to meet Net Zero targets, ground-mounted solar farms have proliferated around the world, with uncertain implications for hosting ecosystems. We provide some of the first evidence on the effects of ground-mounted solar panels on plant and soil properties in temperate agricultural systems. We sampled 32 solar farms in England and Wales in summer 2021. Plant cover and aboveground biomass, as well as soil nutrients and physiochemical properties, were quantified on land underneath solar panels, in the gaps between rows of solar arrays, and in control land (pasture) adjacent to three solar farms. Plant cover and aboveground biomass were significantly lower under solar panels than in the gaps between solar arrays and in pastures. Soil compaction was 14.4% and 15.5% higher underneath solar panels than in gaps and pastures, respectively. Soil organic carbon was 9% lower under solar panels than in gaps, while particulate organic matter was 29.1% and 23.6% lower under solar panels than in gaps and pastures, respectively. Soil mineral nitrogen was 30.5% higher under solar panels than in gaps, while soil (plant-available) phosphorus was approximately 60% higher in solar farm soils than in pasture soils. Reductions in solar radiation and changes to microclimate caused by solar panels may be driving lower plant productivity and growth, with consequences for nutrient cycling and soil properties. However, impacts must be considered in light of the previous land use and the total land area under solar panels, in the gaps between solar arrays, and around the margins of the solar farm. Our findings can inform solar farm design and management options (e.g. increase the proportion of land unaffected by solar panels, enhance plant cover under solar panels) to ensure the long-term provision of ecosystem services (e.g. soil carbon storage) within this fast-growing land use.