Biological invasions pose a rapidly expanding threat to the persistence, functioning and service provisioning of ecosystems globally, and to socio‐economic interests. The stages of successful invasions are driven by the same mechanism that underlies adaptive changes across species in general—via natural selection on intraspecific variation in traits that influence survival and reproductive performance (i.e., fitness). Surprisingly, however, the rapid progress in the field of invasion science has resulted in a predominance of species‐level approaches (such as deny lists), often irrespective of natural selection theory, local adaptation and other population‐level processes that govern successful invasions. To address these issues, we analyse non‐native species dynamics at the population level by employing a database of European freshwater macroinvertebrate time series, to investigate spreading speed, abundance dynamics and impact assessments among populations. Our findings reveal substantial variability in spreading speed and abundance trends within and between macroinvertebrate species across biogeographic regions, indicating that levels of invasiveness and impact differ markedly. Discrepancies and inconsistencies among species‐level risk screenings and real population‐level data were also identified, highlighting the inherent challenges in accurately assessing population‐level effects through species‐level assessments. In recognition of the importance of population‐level assessments, we urge a shift in invasive species management frameworks, which should account for the dynamics of different populations and their environmental context. Adopting an adaptive, region‐specific and population‐focused approach is imperative, considering the diverse ecological contexts and varying degrees of susceptibility. Such an approach could improve and refine risk assessments while promoting mechanistic understandings of risks and impacts, thereby enabling the development of more effective conservation and management strategies.

Non‐native trees may have significant impacts on the carbon sink capacity of forested lands. However, large‐scale patterns of the relative capacity of native and non‐native forests to uptake and store carbon remain poorly described in the literature, and this information is urgently needed to support management decisions. In this study, we analyzed 17,065 plots from the Spanish Forest Inventory (covering c. 30 years) to quantify carbon storage and sequestration of natural forests and plantations of native and non‐native trees under contrasting climate types, while controlling for the effects of environmental factors (forest structure, climate, soil, topography, and management). We found that forest origin (non‐native vs. native) highly influenced carbon storage and sequestration, but such effect was dependent on climate. Carbon storage was greater in non‐native than in native forests in both wet and dry climates. Non‐native forests also had greater carbon sequestration than native ones in the wet climate, due to higher carbon gains by tree growth. However, in the dry climate, native forests had greater carbon gains by tree ingrowth and lower carbon loss by tree mortality than non‐native ones. Furthermore, forest type (classified by the dominant species) and natural forests versus tree plantations were important determinants of carbon storage and sequestration. Native and non‐nativePinusspp. forests had low carbon storage, whereas non‐nativeEucalyptusspp. forests and nativeQuercusspp.,Fagus sylvatica, and Eurosiberian mixed forests (especially not planted ones) had high carbon storage. Carbon sequestration was greatest inEucalyptus globulus,Quercus ilex, andPinus pinasterforests. Overall, our findings suggest that the relative capacity of native and non‐native forests to uptake and store carbon depends on climate, and that the superiority of non‐native forests over native ones in terms of carbon sequestration declines as the abiotic filters become stronger (i.e., lower water availability and higher climate seasonality).

Invasive alien species have widespread impacts on native biodiversity and ecosystem services. Since the number of introductions worldwide is continuously rising, it is essential to prevent the entry, establishment and spread of new alien species through a systematic examination of future potential threats. Applying a three-step horizon scanning consensus method, we evaluated non-established alien species that could potentially arrive, establish and cause major ecological impact in Spain within the next 10 years. Overall, we identified 47 species with a very high risk (e.g. Oreochromis niloticus, Popillia japonica, Hemidactylus frenatus, Crassula helmsii or Halophila stipulacea), 61 with high risk, 93 with moderate risk, and 732 species with low risk. Many of the species categorized as very high or high risk to Spanish biodiversity are either already present in Europe and neighbouring countries or have a long invasive history elsewhere. This study provides an updated list of potential invasive alien species useful for prioritizing efforts and resources against their introduction. Compared to previous horizon scanning exercises in Spain, the current study screens potential invaders from a wider range of terrestrial, freshwater, and marine organisms, and can serve as a basis for more comprehensive risk analyses to improve management and increase the efficiency of the early warning and rapid response framework for invasive alien species. We also stress the usefulness of measuring agreement and consistency as two different properties of the reliability of expert scores, in order to more easily elaborate consensus ranked lists of potential invasive alien species.

Invasive species are widely recognized as a major threat to global diversity and an important factor associated with global change. Species distribution models (SDMs) have been widely applied to determine the range that invasive species could potentially occupy, but most examples focus on predictive variables at a single spatial scale. In this study, we simultaneously considered a broad range of variables related to climate, topography, land cover, land use, and propagule pressure to predict what areas in the southeastern United States are more susceptible to invasion by 45 invasive terrestrial plant species. Using expert-verified occurrence points from EDDMapS, we modeled invasion susceptibility at 30-m resolution for each species using a maximum entropy (MaxEnt) modeling approach. We then analyzed how environmental predictors affected susceptibility to invasion at different spatial scales. Climatic and land-use variables, especially minimum temperature of coldest month and distance to developed areas, were good predictors of landscape susceptibility to invasion. For most of the species tested, human-disturbed systems such as developed areas and barren lands were more prone to be invaded than areas that experienced minimal human interference. As expected, we found that landscape heterogeneity and the presence of corridors for propagule dispersal significantly increased landscape susceptibility to invasion for most species. However, we also found a number of species for which the susceptibility to invasion increased in landscapes with large core areas and/or less-aggregated patches. These exceptions suggest that even though we found the expected general patterns for susceptibility to invasion among most species, the influence of landscape composition and configuration on invasion risk is species specific.