Gabriella Damasceno

Predicting which non-native plant species will become established and where is critical for conserving and managing biodiversity. Theory suggests that the mycorrhizal strategy of non-native plants may predict their establishment success. Here we combine a global dataset of 440,788 vegetation plots with data on plant native status and mycorrhizal type to assess mycorrhizal strategy of non-native plants. The mycorrhizal strategy of non-native plants varies strongly across biomes. Across grassland and desert biomes, non-native species are more frequently non-mycorrhizal than native species, whereas in other biomes non-native species are more likely to be mycorrhizal, most commonly arbuscular-mycorrhizal. Disturbance type and intensity are key predictors of mycorrhizal strategy of non-native species, as mycorrhizal species are favoured by landscape modification and non-mycorrhizal species by natural and human-caused disturbance events. Facultatively mycorrhizal species are consistently under-represented among non-native plants compared with natives, suggesting that symbiotic flexibility does not confer an advantage for non-natives as previously expected. Our study shows that non-native mycorrhizal strategy varies across biogeographical contexts and disturbance, highlighting the need for region-specific prevention and management approaches to plant species introductions.

Despite widespread concern over global biodiversity loss, the balance between gains and losses within local plant communities remains contentious, largely due to a scarcity of integrative, long-term and large-scale analyses across different habitats and multiple facets of biodiversity. Here, we analyse 57,390 vegetation-plot time series of vascular plants across Europe to quantify the average and habitat-specific trends in taxonomic, functional, phylogenetic, and gamma diversity, alongside with changes in threatened Red List, non-native, and specialist versus generalist species. We find that, over the last 100 years, plant communities gained on average 0.7% in vegetation cover and 0.2% in species number per year, associated with gains in functional and phylogenetic diversity, non-native, Red List, and generalist species. Diversity changes are most pronounced in mire and wetland communities. Differences among habitat types and habitat-change trajectory (stable, successional, disturbed), together with the most recent observation year, explain 2.1%–36.6% of the variation in diversity trends. Habitat-specific gamma diversity showed no general trends and only increased in stable grasslands and successional sparsely vegetated habitats. By integrating habitat types and change trajectories, we reconcile some of the conflicting narratives on local biodiversity change in favour of a more nuanced understanding of the observed variation in local biodiversity change.

While the negative effects of landscape fragmentation on biodiversity are well documented, recent evidence shows that positive or neutral effects may also be common. Understanding the mechanisms underlying these contrasting outcomes requires evaluating how species traits mediate their responses to landscape and patch characteristics. Here, we show that three key elements can improve predictions of fragmentation effects on biodiversity across scales: (1) the trait distribution of the regional species pool; (2) the relationship between taxonomic and trait diversity; and (3) the influence of the landscape matrix on the distribution of species traits. To demonstrate how these hypotheses can be tested at multiple spatial scales, we present a fully reproducible framework that integrates survey data from global datasets, remote‐sensing products, and analytical tools. As a proof of concept, we analyzed 120 fragmented landscapes in forest ecoregions spanning several biomes. We focused on forest‐dependent plant and bird species using survey data from 410 plots and species lists extracted from eBird and sPlot. Our results show that variation in the trait diversity of regional species pools across regions and ecosystems explains both the direction and magnitude of fragmentation effects on functional and taxonomic diversity. Notably, the relationship between taxonomic and functional diversity determines whether different facets of biodiversity show convergent or divergent responses to fragmentation. When functional diversity saturates rapidly with increasing taxonomic diversity, species assemblages show a narrow range of responses to fragmentation. In these cases, few species are able to colonize small patches or exploit resources in the landscape matrix, resulting in assemblages with low species richness and reduced trait diversity. Depending on the spatial scale and the region considered, fragmentation effects can be positive, neutral, or negative for species with different traits related to dispersal, life history, and resource acquisition. The implementation of our framework will support the development of generalizable hypotheses about the consequences of fragmentation across diverse taxonomic groups and regions, with broad implications for ecology and conservation.

Questions: Invasive African grasses threaten native plant communities and hinder ecological restoration in the Cerrado region, in Brazil. Their aboveground impacts are well described, but their belowground effects are less known. Because native species rely on bud‐bearing belowground organs for their persistence, changes in belowground components and structure can reveal hidden effects of the invader. Thus, we investigated whether the presence of an invasive African grass ( Urochloa brizantha ) affects Cerrado belowground components, both functionally by the proportion of fine roots and structurally by the abundance of different types of belowground organs. Location: Cerrado open savannahs in southeastern Brazil (22°14′40′′S, 47°52′29′′W, 700 m a.s.l.). Methods: We selected five invaded patches (minimum patch size = 10 m ² ), which were individually paired with an adjacent non‐invaded patch as a control (totaling 10 patches). In every patch, we established 2 plots (0.25 × 0.25 m) to collect belowground organs until 0.3 m deep. Fine roots and soil were sampled beside each plot, every 10 cm until 1 m deep. Buds were counted, roots and belowground organs were oven‐dried and weighed, and soil nutrients were analyzed. We fitted generalized linear mixed models (GLMM) for each response variable to investigate the differences between invaded and non‐invaded patches. Results: The belowground component of invaded areas was dominated by Urochloa brizantha 's fine roots and non‐woody rhizomes. The bud bank density was lower for all growth forms in invaded areas, except for the invaders' non‐woody rhizomes, pointing to changes in the system's regeneration capacity. Fine root biomass was higher in the upper layers of the soil in invaded areas, indicating higher space occupancy and faster nutrient cycling. Conclusions: The belowground component of invaded areas is functionally and structurally different from non‐invaded areas, resulting in different plant community dynamics and resilience. Such differences could persist as legacy effects after the invader's removal.

Plant functional traits are fundamental to ecosystem dynamics and Earth system processes, but their global characterization is limited by available field surveys and trait measurements. Recent expansions in biodiversity data aggregation—including vegetation surveys, citizen science observations, and trait measurements—offer new opportunities to overcome these constraints. Here we demonstrate that combining these diverse data sources with high-resolution Earth observation data enables accurate modeling of key plant traits at up to 1 km ² resolution. Our approach achieves correlations up to 0.63 (15 of 31 traits exceeding 0.50) and improved spatial transferability, effectively bridging gaps in under-sampled regions. By capturing a broad range of traits with high spatial coverage, these maps can enhance understanding of plant community properties and ecosystem functioning, while serving as tools for modeling global biogeochemical processes and informing conservation efforts. Our framework highlights the power of crowdsourced biodiversity data in addressing longstanding extrapolation challenges in global plant trait modeling, with continued advancements in data collection and remote sensing poised to further refine trait-based understanding of the biosphere.

Despite widespread concern over global biodiversity change 1,2, the gains and losses at local plant communities remain contentious 3–5, primarily due to the lack of integrative, large-scale analyses across different habitats and multiple facets of plant diversity. Here, we analysed 55,975 vegetation time series across Europe to quantify the general and habitat-specific trends in taxonomic, functional, and phylogenetic plant diversity, alongside changes in Red List species and European species pools. We found that, over the last 100 years, plant communities have gained 0.15 species year-1, accompanied by increases in Faith’s phylogenetic diversity and decreases in functional trait evenness. Local diversity trends were strongest in disturbed wetland and disturbed forest communities and varied substantially by habitat type, habitat-change trajectory (classified as stable, successional, or disturbed), and the year of the last observation in a time series – which collectively explained 2–24% of the observed variation. Species pool richness increased most in disturbed grassland and in successional sparsely-vegetated and man-made habitats but was otherwise stable. By accounting for the ecological context and the multiple facets of plant diversity, our findings provide a more nuanced understanding that is necessary to reconcile some of the conflicting narratives of local biodiversity change.

Aims: Root traits are critical for resource acquisition, particularly in nutrient‐limited environments such as open savannahs, and any changes in these traits can impact ecological processes. However, it is poorly understood whether invasive species outcompete natives by competitive superiority in nutrient acquisition (‘exploitation competition’) or by interfering with natives by space occupancy (‘interference competition’).Location: Cerrado, south‐eastern Brazil.Methods: We selected five sites of open savannahs, each consisting of two paired subsites, that is, non‐invaded or invaded by Urochloa grass species. We assessed community‐level root biomass and depth distribution in the upper 1 m of soil. We measured root biomass and functional traits for fine roots (< 2 mm) classified as absorptive and transport roots in the uppermost soil layers (0–30 cm).Results: Invaded and non‐invaded plant communities differed primarily in root trait and biomass in the upper soil layer (0–10 cm). Invaded communities showed higher root biomass and root length density (RLD) compared to non‐invaded communities, evidencing space occupancy through a larger root system. Species in invaded communities had roots with larger diameters, but lower root tissue density (RTD) and lower root dry mass content (RDMC), commonly associated with fast root spreading and expansion, compared to species in non‐invaded communities. Contrarily, non‐invaded communities presented a higher proportion of absorptive roots.Conclusions: Functional dissimilarities in traits related to space occupancy indicate that interference competition plays a bigger role than exploitation competition in the invasion of Cerrado by Urochloa species. Invaded savannahs are characterized by root traits and biomass allowing effective neighbor suppression. As changes in root traits such as RTD can cause modifications in ecosystem functioning, our results suggest that invasive species may modify ecosystem processes that hamper the restoration of invaded savannahs.

Motivation: Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database.Main Types of Variables Included: The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years.Spatial Location and Grain: Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size.Time Period and Grain: The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric.Major Taxa and Level of Measurement: The database includes any eukaryotic taxa, with a combined total of 56,400 taxa.Software Format: csv and. SQL.

The iDiv Female Scientists initiative at the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig in Germany was set up to connect women in science and to raise awareness of gender inequity. In this article we discuss the impact of the workplace environment on women in academia. Our experiences indicate that supportive workplace environments are more likely to discuss gender inequity, enabling “bottom-up” approaches where individual researchers can propose solutions to the problem. In contrast, unsupportive environments are less receptive to such discussions, so “top-down” approaches driven by legislation policies are required to improve the situation. We also make recommendations of actions that can be taken by individuals, institutions and policymakers to promote gender equity.

Understanding global patterns of functional diversity is essential for exploring ecosystem functioning, yet our current knowledge is limited to specific regions and geographically restricted datasets.. Meanwhile, rapidly growing citizen science initiatives, such as iNaturalist or Pl@ntNet, have generated millions of ground-level species observations across the globe. Despite citizen science species observations being noisy and opportunistically sampled, previous studies have shown that integrating them with large functional trait databases enables the creation of global trait maps with promising accuracy. However, aggregating citizen science data only allows for the generation of relatively sparse and coarse trait maps, e.g. at 0.2 to 2.0 degree spatial resolution.Here, by using such citizen science data in concert with vegetation surveys and high-resolution Earth observation data, we extend this approach to model the relationships between functional traits and their structural and environmental determinants, providing global trait maps with globally continuous coverage and high spatial resolution (up to 1km). This fusion of ground-based citizen science and continuous satellite data allows us not only to map more than 30 ecologically relevant traits but also to derive crucial functional diversity metrics at a global scale. These metrics—such as functional richness and evenness—provide new opportunities to explore the role of functional diversity in ecosystem processes, particularly in areas previously lacking in data availability.Our approach presents a scalable framework to advance understanding of plant functional traits and diversity, opening the door to new insights on how ecosystems may respond to an increasingly variable and extreme climate.