Lars Ove Hansen

This study assesses the impact of climate change on the distribution of Ixodes ricinus, which transmits Lyme disease, a growing public health concern. Utilizing ensemble models from the R package ‘flexsdm’ and climate data from WorldClim, ENVIREM, and CliMond, we project habitat suitability changes for the focus species. The models, validated against Lyme disease incidence rates, predict a 1.5-fold increase in suitable habitats in Latvia, contrasted with a 4.5-fold decrease in suitable habitats within Ukraine over the coming decades. SHAP values are analyzed to determine the most influential climatic features affecting tick distribution, providing insights for future vector control and disease prevention strategies. The optimal bioclimatic environment for I. ricinus seems to be an intricate balance of moderate temperatures, high humidity, and sufficient rainfall (bio7, 14, 18, 29). Also, radiation during the wettest quarter (bio24) significantly influences tick distribution in northern countries. This implies an increased presence of ticks in Scandinavian countries, Baltic states, etc. These findings largely coincide with our projections regarding bioclimatic suitability for ticks in Latvia and Ukraine. These shifts reflect broader patterns of vector redistribution driven by global warming, highlighting the urgent need to adapt public health planning to the evolving landscape of vector-borne diseases under climate change.

Globally, vector‐borne diseases are increasing in distribution and frequency, affecting humans, domestic animals, and wildlife. Science‐based management and prevention of these diseases requires a sound understanding of the distribution and environmental requirements of the vectors and hosts involved in disease transmission. Integrated Species Distribution Models (ISDM) account for diverse data types through hierarchical modeling and represent a significant advancement in species distribution modeling. We assessed the distribution of the soft tick subspecies Ornithodoros turicata americanus. This tick species is a potential vector of African swine fever virus (ASFV), a pathogen responsible for an ongoing global epizootic that threatens agroindustry worldwide. Given the novelty of this method, we compared the results to a conventional Maxent SDM and validated the results through data partitioning. Our input for the model consisted of systematically collected detection data from 591 sampled field sites and 12 historical species records, as well as four variables describing climatic and soil characteristics. We found that a combination of climatic variables describing seasonality and temperature extremes, along with the amount of sand in the soil, determined the predicted intensity of occurrence of this tick species. When projected in geographic space, this distribution model predicted 62% of Florida as suitable habitat for this tick species. The ISDM presented a higher TSS and AUC than the Maxent conventional model, while sensitivity was similar between both models. Our case example shows the utility of ISDMs in disease ecology studies and highlights the broad range of geographic suitability for this important disease vector. These results provide important foundational information to inform future risk assessment work for tick‐borne relapsing fever surveillance and potential ASF introduction and maintenance in the United States.

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.

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.

Sarcophagid experts have made several efforts to associate biodiversity data and comprehend where each species occurs, but comprehensive faunal inventories remain scarce. Our aim was to provide a list of distributional patterns and endemic species and allow assessment of the sampling effort conducted within Brazilian biomes. We produced a dataset of Brazilian sarcophagids and overlaid with a biome map, to investigate distributional patterns, endemism and to build species accumulation curves. Additionally, we calculated nonparametric asymptotic species richness estimators and extrapolation of species diversity (Hill numbers). Our dataset comprised 288 sarcophagid species, which 21 were identified as endemic. The biomes with the highest species richness were the Atlantic Rainforest and the Amazon Forest, and no biome exhibited a stabilized asymptotic curve. This is the first proposal of listing Sarcophagidae species by biomes and essential to understand the spatial distribution of this family in Brazil. We present maps and richness estimators that allow identifying gaps and guiding survey planning.

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.

Paederus fuscipes Curtis, 1826, belongs to the Coleoptera order, Staphylinidae family, and Paederus genus (Fabricius, 1775). It has a wide distribution and strong invasive and environmental adaptation capabilities. As a predatory natural enemy of agricultural and forestry pests, understanding its suitable habitat is crucial for the control of other pests. This study, for the first time, uses the MaxEnt model and ArcGIS software, combining known distribution information of P. fuscipes and climate environmental factors to predict the current and future suitable habitat distribution of this insect. The key environmental variables affecting the distribution of P. fuscipes have been identified as mean diurnal range (mean of monthly (max temp-min temp)) (bio2), isothermality (Bio2/Bio7) (*100) (bio3), minimum temperature of the coldest month (bio6), temperature annual range (bio5-bio6) (bio7), mean temperature of the driest quarter (bio9), mean temperature of the coldest quarter (bio11), precipitation of the wettest month (bio13), precipitation of the driest month (bio14), and precipitation seasonality (coefficient of variation) (bio15). The highly suitable areas for P. fuscipes in China are mainly distributed in the hilly regions of Shandong, the North China Plain, and the middle and lower reaches of the Yangtze River Plain, with a total suitable area of 118.96 × 104 km2, accounting for 12.35% of China’s total area. According to future climate change scenarios, it is predicted that the area of highly and lowly suitable regions will significantly decrease, while moderately suitable regions will increase (except for the 2090s, SSP2-4.5 scenario). These research findings provide important theoretical support for pest control and ecological conservation applications.

Insects are the most diverse group of organisms, but their large number of species and the lack of specialists to study them have made this group particularly vulnerable to the main limitations in biological diversity, such as the Wallacean deficit. This study will contribute to the geographical knowledge of an insect trophic guild that has been widely used as an indicator group, the Scarabaeoidea and Silphidae copro-necrophagous beetles, emphasizing their geographical distribution in two Mexican national parks (Iztaccíhuatl-Popocatepetl and La Malinche) and the intermediate region, which includes sky-island ecosystems in central Mexico. Geographic records of the 32 species that have been previously recorded in the study region were compiled and used to generate potential distribution models aiming to generate potential alpha (species richness) and beta (total beta diversity, nestedness and replacement) diversity maps. The greatest predicted species richness was found between 3,000 and 3,500 m a.s.l. in the study region. Potential species richness ranged from 2 to 24 species. Total beta diversity was low in the study region (mean 0.1), while nestedness was the most important component of beta diversity (0.8). The maximum alpha and beta diversity values were predicted outside the national parks. Consequently, we consider that the studied national parks are not able to protect completely the regional alpha and beta diversities by themselves. Implications for insect conservation: Our results show that the highest alfa and beta diversity values of copro-necrophagous beetles might occur outside the national parks, and a suitable way to protect them could be the Archipelago reserve model as an alternative to protect the regional diversity.