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.

Accurate delimitation of species is crucial for a stable taxonomy, which provides the foundation for the study of evolutionary biology, ecology, and essentially all biological disciplines. Several approaches toward impartial and repeatable taxonomic practices are available but all existing methods have potentially unacceptable shortcomings. In particular, problems can arise when the underlying model assumptions are violated, for instance, in the presence of reduced gene flow. This is observed in the context of sex-biased dispersal, which is a common but underappreciated feature in many groups of organisms. Previously, simulations have indicated that sex-biased dispersal may lead to erroneous estimations of the true species numbers. However, this phenomenon has never been examined using empirical data. We evaluate the bias introduced by extreme female philopatry on a range of de novo [GMYC, PTP, ABGD, statistical parsimony, trinomial distribution of triplets model (tr2)] and validation (STACEY, iBPP) approaches to species delimitation in the scarab beetle genus Pachypus. Since female philopatry exhibited in this genus in particular can affect mitochondrial gene flow, we compared the results from analyses of single loci, mitochondrial loci, nuclear loci and combined data, as well as the performance of morphometric data as a secondary data source in a fully integrative Bayesian framework. Large overestimation of species numbers was observed across all analyses of combined and mitochondrial DNA data sets, suggesting specimens from nearly every sampling location as separate species. The use of nuclear data resulted in more reasonable estimations of species boundaries, which were largely supported by morphometrics of linear measurements, while geometric morphometrics of body outlines resulted in stronger splitting. Simulations of population divergence with migration, corresponding to the biology of Pachypus, showed that female philopatry strongly increases reciprocal monophyly of mitochondrial markers and may substantially contribute to over-splitting in species delimitation. Robust results recovered using nuclear DNA and morphological data nevertheless enabled us to reach novel conclusions about species boundaries in Pachypus. Our findings suggest that mitochondrial DNA will be less suited to species delimitation in many cases, in particular in the presence of sex-biased dispersal.

Accurate structural information about forests, including canopy heights and diameters, is crucial for quantifying tree volume, biomass, and carbon stocks, enabling effective forest ecosystem management, particularly in response to changing environmental conditions. Since late 2018, NASA’s Global Ecosystem Dynamics Investigation (GEDI) mission has monitored global canopy structure using a satellite Light Detection and Ranging (LiDAR) instrument. While GEDI has collected billions of LiDAR shots across a near-global range (between 51.6°N and >51.6°S), their spatial distribution remains dispersed, posing challenges for achieving complete forest coverage. This study proposes and evaluates an approach that generates high-resolution canopy height maps by integrating GEDI data with Sentinel-1, Sentinel-2, and topographical ancillary data through three machine learning (ML) algorithms: random forests (RF), gradient tree boost (GB), and classification and regression trees (CART). To achieve this, the secondary aims included the following: (1) to assess the performance of three ML algorithms, RF, GB, and CART, in predicting canopy heights, (2) to evaluate the performance of our canopy height maps using reference canopy height from canopy height models (CHMs), and (3) to compare our canopy height maps with other two existing canopy height maps. RF and GB were the top-performing algorithms, achieving the best 13.32% and 16% root mean squared error for broadleaf and coniferous forests, respectively. Validation of the proposed approach revealed that the 100th and 98th percentile, followed by the average of the 75th, 90th, 95th, and 100th percentiles (AVG), were the most accurate GEDI metrics for predicting real canopy heights. Comparisons between predicted and reference CHMs demonstrated accurate predictions for coniferous stands (R-squared = 0.45, RMSE = 29.16%).

According to projects and practices that the Italian botanists and ecologists are carrying out for bringing “more nature in the city”, new insights for a factual integration between ecological perspectives and more consolidated aesthetic and agronomic approaches to the sustainable planning and management of urban green areas are provided.

Despite the importance for scientific and conservation purposes, the knowledge of the Italian territory is far from exhaustive. New chorological data for 87 vascular taxa regarding the central-southern part of Italy and its two main islands (Sicilia and Sardegna) are presented. Among these taxa, Epilobium nummularifolium, Metrosideros excelsa, and Salvinia minima are recorded as casual aliens for the first time in Europe (excluding Azores and Madeira for M. excelsa), while Cyclamen balearicum and Polygala rupestris are reported for the first time and confirmed for Italian native flora, respectively. Furthermore, several taxa are new or confirmed at regional level. Finally, Lathyrus cirrhosus, Urginea fugax, and Linum tenuifolium are excluded from Italy, continental and peninsular Italy, and Sardegna, respectively.