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The globalization of trade and increased human mobility have facilitated the introduction and spread of nonnative species, posing significant threats to biodiversity and human well-being. As centers of global trade and human populations, cities are foci for the introduction, establishment, and spread of nonnative species. We present a global synthesis of urban characteristics that drive biological invasions within and across cities, focusing on four axes: (a) connectivity, (b) physical properties, (c) culture and socioeconomics, and (d) biogeography and climate. Urban characteristics such as increased connectivity within and among cities, city size and age, and wealth emerged as important drivers of nonnative species diversity and spread, while the relative importance of biogeographic and climate drivers varied considerably. Elaborating how these characteristics shape biological invasions in cities is crucial for designing and implementing strategies to mitigate the impacts of invasions on ecological systems and human well-being. 

ABSTRACT AimsThe community composition of native and alien plant species is influenced by the environment (e.g., nutrient addition and changes in temperature or precipitation). A key objective of our study is to understand how differences in the traits of alien and native species vary across diverse environmental conditions. For example, the study examines how changes in nutrient availability affect community composition and functional traits, such as specific leaf area and plant height. Additionally, it seeks to assess the vulnerability of high‐nutrient environments, such as grasslands, to alien species colonization and the potential for alien species to surpass natives in abundance. Finally, the study explores how climatic factors, including temperature and precipitation, modulate the relationship between traits and environmental conditions, shaping species success. LocationIn our study, we used data from a globally distributed experiment manipulating nutrient supplies in grasslands worldwide (NutNet). MethodsWe investigate how temporal shifts in the abundance of native and alien species are influenced by species‐specific functional traits, including specific leaf area (SLA) and leaf nutrient concentrations, as well as by environmental conditions such as climate and nutrient treatments, across 17 study sites. Mixed‐effects models were used to assess these relationships. ResultsAlien and native species increasing in their abundance did not differ in their leaf traits. We found significantly lower specific leaf area (SLA) with an increase in mean annual temperature and lower leaf Potassium with mean annual precipitation. For trait–environment relationships, when compared to native species, successful aliens exhibited an increase in leaf Phosphorus and a decrease in leaf Potassium with an increase in mean annual precipitation. Finally, aliens' SLA decreased in plots with higher mean annual temperatures. ConclusionsTherefore, studying the relationship between environment and functional traits may portray grasslands' dynamics better than focusing exclusively on traits of successful species, per se. 

Species introduced through human-related activities beyond their native range, termed alien species, have various impacts worldwide. The IUCN Environmental Impact Classification for Alien Taxa (EICAT) is a global standard to assess negative impacts of alien species on native biodiversity. Alien species can also positively affect biodiversity (for instance, through food and habitat provisioning or dispersal facilitation) but there is currently no standardized and evidence-based system to classify positive impacts. We fill this gap by proposing EICAT+, which uses 5 semiquantitative scenarios to categorize the magnitude of positive impacts, and describes underlying mechanisms. EICAT+ can be applied to all alien taxa at different spatial and organizational scales. The application of EICAT+ expands our understanding of the consequences of biological invasions and can inform conservation decisions. 

Abstract. Advancing our understanding of Earth system dynamics (ESD) depends on thedevelopment of models and other analytical tools that apply physical,biological, and chemical data. This ambition to increase understanding anddevelop models of ESD based on site observations was the stimulus forcreating the networks of Long-Term Ecological Research (LTER), Critical ZoneObservatories (CZOs), and others. We organized a survey, the results of whichidentified pressing gaps in data availability from these networks, inparticular for the future development and evaluation of models that representESD processes, and provide insights for improvement in both data collectionand model integration. From this survey overview of data applications in the context of LTER andCZO research, we identified three challenges: (1) widen application ofterrestrial observation network data in Earth system modelling,(2) develop integrated Earth system models that incorporate processrepresentation and data of multiple disciplines, and (3) identifycomplementarity in measured variables and spatial extent, and promotingsynergies in the existing observational networks. These challenges lead toperspectives and recommendations for an improved dialogue between theobservation networks and the ESD modelling community, including co-locationof sites in the existing networks and further formalizing theserecommendations among these communities. Developing these synergies willenable cross-site and cross-network comparison and synthesis studies, whichwill help produce insights around organizing principles, classifications,and general rules of coupling processes with environmental conditions. 

Abstract Urban areas are foci for the introduction of non‐native plant species, and they often act as launching sites for invasions into the wider environment. Although interest in biological invasions in urban areas is growing rapidly, and the extent and complexity of problems associated with invasions in these systems have increased, data on the composition and numbers of non‐native plants in urbanized areas remain scattered and idiosyncratic.We assembled data from multiple sources to create the Global Urban Biological Invasions Compendium (GUBIC) for vascular plants representing 553 urban centres from 61 countries across every continent except Antarctica.The GUBIC repository includes 8140 non‐native plant species from 253 families. The number of urban centres in which these non‐native species occurred had a log‐normal distribution, with 65.2% of non‐native species occurring in fewer than 10 urban centres.Practical implications: The dataset has wider applications for urban ecology, invasion biology, macroecology, conservation, urban planning and sustainability. We hope this dataset will stimulate future research in invasion ecology related to the diversity and distributional patterns of non‐native flora across urban centres worldwide. Further, this information should aid the early detection and risk assessment of potential invasive species, inform policy development and assist in setting management priorities. 

Abstract Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass – define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date.