Kjell Magne Olsen

Island ecosystems have significant conservation value owing to their higher endemic biotas. Moreover, studies of regional communities that compare differences in species composition (species dissimilarity) among islands and the mainland suggest that community assembly on islands is different from that on the mainland. However, the uniqueness of island biotic assembly has been little studied at the global scale, nor have phylogenetic information or alien species been considered in these patterns. We evaluate taxonomic and phylogenetic change from one community to the next, focusing on differences in species composition between mainland-mainland (M-M) pairs compared to differences between mainland-island pairs (M-I) and between island-island pairs (I-I), using herpetofauna on islands and adjacent mainland areas worldwide. Our analyses detect greater taxonomic and phylogenetic dissimilarity for M-I and I-I comparisons than predicted by M-M model, indicating different island herpetofauna assembly patterns compared with mainland counterparts across the world. However, this higher M-I dissimilarity has been significantly decreased after considering alien species. Our results provide global evidence on the importance of island biodiversity conservation from the aspect of both the taxonomic and phylogenetic uniqueness of island biotic assembly.

Predicting global change effects poses significant challenges due to the intricate interplay between climate change and anthropogenic stressors in shaping ecological communities and their function, such as pest outbreak risk. Termites are ecosystem engineers, yet some pest species are causing worldwide economic losses. While habitat fragmentation seems to drive pest-dominated termite communities, its interaction with climate change effect remains unknown. We test whether climate and habitat fragmentation interactively alter interspecific competition that may limit pest termite risk. Leveraging global termite co-occurrence including 280 pest species, we found that competitively superior termite species (e.g., large bodied) increased in large and continuous habitats solely at high precipitation. While competitive species suppressed pest species globally, habitat fragmentation drove pest termite risk only in humid biomes. Unfortunately, hu- mid tropics have experienced vast forest fragmentation and rainfall reduction over the past decades. These stressors, if not stopped, may drive pest termite risk, potentially via competitive release.

AbstractInvasive alien plants cause severe global problems; therefore, determining the factors that lead to the success or failure of invasion is a critical question in the field of invasion ecology. In this study, we aimed to determine the factors underlying differences in the distribution range of alien plants in Japan by investigating why Loliummultiflorum thrives in a wide range of habitats while L.rigidum is mainly distributed on sandy beaches. We initially evaluated environmental niche suitability through species distribution modelling and subsequently examined whether species traits influence the differences in range expansion between the two species. We used MaxEnt modelling to identify potential environmental niches for both species. The analysis revealed that L.rigidum was considerably less suited to the Japanese climate compared to L.multiflorum, with high summer precipitation in Japan identified as one of the climatic factors limiting the distribution of L.rigidum. Given that these winter annual plants remain dormant as seeds during summer, in subsequent experiments, we buried seeds in paddy field soil and sandy beach sand during summer and evaluated their survival rate in autumn. The survival rate of L.rigidum seeds was significantly lower than that of L.multiflorum, particularly in paddy soil. Factors contributing to seed mortality may include the decay or early germination of L.rigidum seeds under Japan’s high rainfall conditions. This study emphasises the importance of considering local environmental factors alongside climate niche modelling in the risk assessment of invasive species. Moreover, the integration of species distribution modelling for large-scale evaluations and manipulation experiments for fine-scale assessments proved effective in identifying climatic conditions and species traits influencing the success or failure of alien species invasion.

The Khanka Lowland forest-steppe is the most eastern outpost of the Eurasian steppe biome. It includes unique grassland plant communities with rare steppe species. These coenosis have changed under the influence of anthropogenic activity, especially during the last 100 years and included both typical steppe species and nemoral mesophytic species. To distinguish these ecological groups of plants the random forest method with three datasets of environmental variables was applied. Specifically, a model of classification with the most important bioindices to predict a mesophytic ecological group of plants with a sensitivity greater than 80% was constructed. The data demonstrated the presence of steppe species that arrived at different times in the Primorye Territory. Most of these species are associated with the Mongolian-Daurian relict steppe complex and habit in the Khanka Lowland. Other species occur only in mountains in Primorye Territory and do not persist in the Khanka Lowland. These findings emphasize the presence of relict steppe communities with a complex of true steppe species in the Khanka Lowland. Steppe communities exhibit features of anthropogenic influence definitely through the long land use period but are not anthropogenic in origin. The most steppe species are located at the eastern border of distribution in the Khanka Lowlands and are valuable in terms of conservation and sources of information about steppe species origin and the emergence of the steppe biome as a whole.

We analysed the wild bee community sampled from 1921 to 2018 at a nature preserve in southern Michigan, USA, to study long-term community shifts in a protected area. During an intensive survey in 1972 and 1973, Francis C. Evans detected 135 bee species. In the most recent intensive surveys conducted in 2017 and 2018, we recorded 90 species. Only 58 species were recorded in both sampling periods, indicating a significant shift in the bee community. We found that the bee community diversity, species richness and evenness were all lower in recent samples. Additionally, 64% of the more common species exhibited a more than 30% decline in relative abundance. Neural network analysis of species traits revealed that extirpation from the reserve was most likely for oligolectic ground-nesting bees and kleptoparasitic bees, whereas polylectic cavity-nesting bees were more likely to persist. Having longer phenological ranges also increased the chance of persistence in polylectic species. Further analysis suggests a climate response as bees in the contemporary sampling period had a more southerly overall distribution compared to the historic community. Results exhibit the utility of both long-term data and machine learning in disentangling complex indicators of bee population trajectories.

Given the high number of non-native plants that are being introduced worldwide and the time required to process formal pest risk analyses, a framework for the prioritization of management actions is urgently required. We therefore propose a framework for a replicable and standardized prioritization for management actions (eradication, control and monitoring) of invasive non-native plants, combining expert knowledge, current and future climatic suitability estimated by species distribution models (SDMs), clustering and ordination techniques. Based on expert consultation and using Italy as case study, invasive non-native plant species were selected and three categories of management actions were identified: eradication, control and containment, and monitoring. Finally, two further classes of priorities were proposed for each of the management actions: “high” and “low” priority. Overall, SDMs highlighted a high and very high suitability for Continental and Mediterranean bioregions for most invasive plants. Cluster analysis revealed three distinct clusters with varying levels of suitability for the Italian bioregions. Cluster 1 exhibited a higher suitability across all Italian bioregions, whereas non-native plants grouped in Cluster 2 predominantly featured high suitability in Mediterranean areas. Finally, Cluster 3 showed the lowest suitability values. Two ordination analysis highlighted the variability in bioclimatic suitability for each non-native plant within each cluster, as well as their current distribution pattern. Lastly, a third ordination, integrating bioclimatic suitability and spatial patterns, has allowed the differentiation of management actions for each non-native plant at both national and bioregional scales. Specifically, seven non-native plants were earmarked for eradication action, six for monitoring action, while the remaining species were deemed suitable for control and containment. Our results and the methodology proposed meet the demand for replicable new early warning tools; that is to predict the location of new outbreaks, to establish priorities for eradication, control and containment, and to monitor invasive non-native species.

Species are often expected to shift their distributions either poleward or upslope to evade warming climates and colonise new suitable climatic niches. However, from 18‐years of fixed transect monitoring data on 88 species of butterfly in the midwestern United States, we show that butterflies are shifting their centroids in all directions, except towards regions that are warming the fastest (southeast).Butterflies shifted their centroids at a mean rate of 4.87 km year−1. The rate of centroid shift was significantly associated with local climate change velocity (temperature by precipitation interaction), but not with mean climate change velocity throughout the species' ranges.Species tended to shift their centroids at a faster rate towards regions that are warming at slower velocities but increasing in precipitation velocity.Surprisingly, species' thermal niche breadth (range of climates butterflies experience throughout their distribution) and wingspan (often used as metric for dispersal capability) were not correlated with the rate at which species shifted their ranges.We observed high phylogenetic signal in the direction species shifted their centroids. However, we found no phylogenetic signal in the rate species shifted their centroids, suggesting less conserved processes determine the rate of range shift than the direction species shift their ranges.This research shows important signatures of multidirectional range shifts (latitudinal and longitudinal) and uniquely shows that local climate change velocities are more important in driving range shifts than the mean climate change velocity throughout a species' entire range.

Biological invasions are among the threats to global biodiversity and social sustainability, especially on islands. Identifying the threshold of area at which non-native species begin to increase abruptly is crucial for early prevention strategies. The small-island effect (SIE) was proposed to quantify the nonlinear relationship between native species richness and area but has not yet been applied to non-native species and thus to predict the key breakpoints at which established non-native species start to increase rapidly. Based on an extensive global dataset, including 769 species of non-native birds, mammals, amphibians and reptiles established on 4277 islands across 54 archipelagos, we detected a high prevalence of SIEs across 66.7% of archipelagos. Approximately 50% of islands have reached the threshold area and thus may be undergoing a rapid increase in biological invasions. SIEs were more likely to occur in those archipelagos with more non-native species introduction events, more established historical non-native species, lower habitat diversity and larger archipelago area range. Our findings may have important implications not only for targeted surveillance of biological invasions on global islands but also for predicting the responses of both non-native and native species to ongoing habitat fragmentation under sustained land-use modification and climate change.

Spatial truncation in species distribution models (SDMs) might cause niche truncation and model transferability issues, particularly when extrapolating models to non‐analog environmental conditions. While broad calibration extents reduce truncation issues, they usually overlook local ecological factors driving species distributions at finer resolution. Spatially‐nested hierarchical SDMs (HSDMs) address truncation by merging (a) a global model calibrated with broadly extended, yet typically low‐resolution, basic, and imprecise data; and (b) a regional model calibrated with spatially restricted but more precise and reliable data. This study aimed to examine HSDMs' efficacy to overcome spatial truncation in national‐scale studies. We compared two hierarchical strategies (‘covariate', which uses the global model output as a covariate for the regional model, and ‘multiply', which calculates the geometric mean of the global and regional models) and a non‐hierarchical strategy. The three strategies were compared in terms of niche truncation, environmental extrapolation, model performance, species' predicted distributions and shifts, and trends in species richness. We examined the consistency of the results over two study areas (Spain and Switzerland), 108 tree species, and four future climate scenarios. Only the non‐hierarchical strategy was susceptible to niche truncation, and environmental extrapolation issues. Hierarchical strategies, particularly the ‘covariate' one, presented greater model accuracy than non‐hierarchical strategies. The non‐hierarchical strategy predicted the highest overall values and the lowest decreases over time in species distribution ranges and richness. Differences between strategies were more evident in Switzerland, which was more affected by niche truncation issues. Spain was more negatively affected by climate change and environmental extrapolation. The ‘covariate' strategy exhibited higher model performance than the ‘multiply' one. However, uncertainties regarding model temporal transferability advocate for adopting and further examining multiple hierarchical approaches. This research underscores the importance of adopting spatially‐nested hierarchical SDMs given the compromised reliability of non‐hierarchical approaches due to niche truncation and extrapolation issues.

Staphylinidae, or rove beetles, are one of the mega-diverse and abundant families of the ground-living terrestrial arthropods that is taxonomically poorly known even in the regions adjacent to Europe where the fauna has been investigated for the longest time. Since DNA barcoding is a tool to accelerate biodiversity research, here we explored if the currently-available COI barcode libraries are representative enough for the study of rove beetles of West Siberia. This is a vast region adjacent to Europe with poorly-known fauna of rove beetles and from where not a single DNA barcode has hitherto been produced for Staphylinidae. First, we investigated the faunal similarity between the rove beetle faunas of the climatically compatible West Siberia in Asia, Fennoscandia in Europe and Canada and Alaska in North America. Second, we investigated barcodes available for Staphylinidae from the latter two regions in BOLD and GenBank, the world's largest DNA barcode libraries. We conclude that the rather different rove beetle faunas of Fennoscandia, on the one hand and Canada and Alaska on the other hand, are well covered in both barcode libraries that complement each other. We also find that even without any barcodes originating from specimens collected in West Siberia, this coverage is helpful for the study of rove beetles there due to the significant number of widespread species shared between West Siberia and Fennoscandia and due to the even larger number of shared genera amongst all three investigated regions. For the first time, we compiled a literature-based checklist for 726 species of the West Siberian Staphylinidae supplemented by their occurrence dataset submitted to GBIF. Our script written for mining unique (i.e. not redundant) barcodes for a given geographic area across global libraries is made available here and can be adopted for any other regions.