Chris Grinter

The Mojave and Sonoran Deserts, recognized as a global hotspot for bee biodiversity, are experiencing habitat degradation from urbanization, utility‐scale solar energy (USSE) development, and climate change. In this study, we evaluated the current and future distribution of bee diversity, assessed how protected areas safeguard bee species richness, and predicted how global change may affect bees across the region. Using Joint Species Distribution Models (JSDMs) of 148 bee species, we project changes in species distributions, occurrence area, and richness under four global change scenarios between 1971 and 2050. We evaluated the threat posed by USSE development and predicted how climate change will affect the suitability of protected areas for conservation. Our findings indicate that changes in temperature and precipitation do not uniformly affect bee richness. Lower elevation protected areas are projected to experience mean losses of up to 5.8 species, whereas protected areas at higher elevations and transition zones may gain up to 7.8 species. Areas prioritized for future USSE development have an average species richness of 4.2 species higher than the study area average, and lower priority “variance” areas have 8.2 more species. USSE zones are expected to experience declines of up to 8.0 species by 2050 due to climate change alone. Despite the importance of solitary bees for pollination, their diversity is often overlooked in land management decisions. Our results show the utility of JSDMs for leveraging existing collection records to ease the inclusion of data‐limited insect species in land management decision‐making.

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.

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.

BACKGROUND Kissing bugs are the vectors of Trypanosoma cruzi, the etiological agent of Chagas disease (CD). Despite their epidemiological relevance, kissing bug species are under sampled in terms of their diversity and it is unclear what biases exist in available kissing bug data. Under climate change, range maps for kissing bugs may become less accurate as species shift their ranges to track climatic tolerance. OBJECTIVES Quantify inventory completeness in available kissing bug data. Assess how well range maps are at conveying information about current distributions and potential future distributions subject to shift under climate change. Intersect forecasted changes in kissing bug distributions with contemporary sampling gaps to identify regions for future sampling of the group. Identify whether a phylogenetic signal is present in expert range knowledge as more closely related species may be similarly well or lesser understood. METHODS We used species distribution models (SDM), specifically constructed from Bayesian additive regression trees, with Bioclim variables, to forecast kissing bug distributions into 2100 and intersect these with current sampling gaps to identify priority regions for sampling. Expert range maps were assessed by the agreement between the expert map and SDM generated occurrence probability. We used classical hypothesis testing methods as well as tests of phylogenetic signal to meet our objectives. FINDINGS Expert range maps vary in their quality of depicting current kissing bug distributions. Most expert range maps decline in their ability to convey information about kissing bug occurrence over time, especially in under sampled areas. We found limited evidence for a phylogenetic signal in expert range map performance. MAIN CONCLUSIONS Expert range maps are not a perfect account of species distributions and may degrade in their ability to accurately convey distribution knowledge under future climates. We identify regions where future sampling of kissing bugs will be crucial for completing biodiversity inventories.

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.

Ecological theory predicts that species that can utilise a greater diversity of resources and, therefore, have wider niche breadths should also occupy larger geographic areas (the ‘niche breadth-range size hypothesis’). Here, we tested this hypothesis for a blood-sucking group of insects of medical significance: the Triatominae (aka ‘kissing bugs’) (Hemiptera: Reduviidae). Given that niches can be viewed from different perspectives, we tested this hypothesis based on both dietary and climatic niches. We assembled the most complete dataset of triatomine feeding patterns to date by reviewing 143 studies from the literature up to 2021 and tested whether the niche breadth-range size hypothesis held for this group for both dietary and climatic components of the niche. Temperature and precipitation niche breadths were estimated from macro-environmental variables, while diet breadth was calculated based on literature data that used PCR and/or ELISA to identify different types of hosts as blood sources per triatomine species. Our results showed that temperature and precipitation niche breadths, but not dietary breadth, were positively correlated with range sizes, independent of evolutionary history among species. These findings support the predictions from the range size-niche breadth hypothesis concerning climate but not diet, in Triatominae. It also shows that support for the niche breadth-range size hypothesis is dependent upon the niche axis under consideration, which can explain the mixed support for this hypothesis in the ecological literature.

Growing degree‐days (GDD), an estimate of an organism's growing season length, has been shown to be an important predictor of Lepidopteran species' distributions and could be influencing Lepidopteran range shifts to climate change. Yet, one understudied simplification in this literature is that the same thermal threshold is used in the calculations of GDD for all species instead of a species‐specific threshold. By characterizing the phenological process influenced by climate, a species‐specific estimate of GDD should improve the accuracy of species distribution models (SDMs). To test this hypothesis, we used published, experimentally estimated thermal thresholds and modeled the current geographic distribution of 30 moth species native to North America. We found that the predictive performance of models based on a species‐specific estimate of GDD was indistinguishable from models based on a standard estimate of GDD. This is likely because GDD was not an important predictor of these species' distributions. Our findings suggest that experimentally estimated thermal thresholds may not always scale up to be predictive at broad scales and that more work is needed to leverage the data from lab experiments into SDMs to accurately predict species' range shifts in response to climate change.

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.

The introduction of bees for agricultural production in distinct parts of the world and poor management have led to invasion processes that affect biodiversity, significantly impacting native species. Different Bombus species with invasive potential have been recorded spreading in different regions worldwide, generating ecological and economic losses. We applied environmental niche and potential distribution analyses to four species of the genus Bombus to evaluate the similarities and differences between their native and invaded ranges. We found that B. impatiens has an extended environmental niche, going from dry environmental conditions in the native range to warmer and wetter conditions in the invaded range. Bombus ruderatus also exhibited an extended environmental niche with drier and warmer conditions in the invaded range than in its native range. Bombus subterraneus expanded its environmental niche from cooler and wetter conditions in the native range to drier and warmer conditions in the invaded range. Finally, B. terrestris showed the most significant variation in the environmental niche, extending to areas with similar and different environmental conditions from its native range. The distribution models agreed with the known distributions for the four Bombus species, presenting geographic areas known to be occupied by each species in different regions worldwide. The niche analysis indicate shifts in the niches from the native to the invaded distribution area of the bee species. Still, niche similarities were observed in the areas of greatest suitability in the potential distribution for B. ruderatus, B. subterraneus, and B. terrestris, and to a lesser degree in the same areas with B. impatiens. These species require similar environmental conditions as in their native ranges to be established in their introduced ranges. Still, they can adapt to changes in temperature and humidity, allowing them to expand their ranges into new climatic conditions.

The Mexican Transition Zone is a biogeographically complex area where old and new lineages of Neotropical and Nearctic affinities overlap. Its biota was assembled by successive dispersal events of cenocrons, which are sets of taxa that dispersed during a given time interval from both North and South America and then diversified in the area. The Mexican Plateau cenocron, with Neotropical affinities, is found in temperate and dry climates in the Nearctic region. We hypothesised that it underwent an adaptive shift in environmental niche. We tested this hypothesis using a phylogenetic comparative framework, measuring phylogenetic signal and fitting to single optima macroevolutionary models, and an Ornstein‐Uhlenbeck macroevolutionary model with multiple optima. We used phylogenetic and distributional information of the tribe Phanaeini to assess whether there exists a distinction in conservatism between the earliest (Mexican Plateau) and most recent (Typical Neotropical) cenocrons within the Mexican Transition Zone (MTZ) as this tribe stands as a classic example of the dispersal and diversification patterns of cenocrons originating in the Neotropics. We identified different shifts in environmental requirements that match the niche description of the Mexican Plateau cenocron, suggesting that it was established through multiple adaptive shifts in the Mexican Transition Zone.