Theodore Henry Frison

Given the heightened vulnerability of deserts to climate change, this study aims to provide a comprehensive analysis of avian species diversity across ten global deserts to identify distinct diversity gradients and relatedness. Identify the difference from global patterns in avian migratory proportions and the underlying drivers for assessing the vulnerability and resilience of these desert ecosystems. Crowd-sourced avian diversity data of 2374 species from GBIF.org was used as a key analytical tool to study the diversity gradient across the ten major deserts. The variance in correlation patterns between avian ecological and behavioral traits across deserts were analyzed employing data of 1930 common avian species from AVONET. The analysis included comparisons of bird diversity, migratory patterns and trophic niches between Tropic of Cancer (TCan) and Tropic of Capricorn (TCap) deserts. Significant variations in bird diversity among the deserts were found. Deserts near the TCan exhibited higher bird diversity than in TCap deserts. TCan deserts had a higher prevalence of migratory species, facilitated by a broader niche breadth among sedentary species, which reduces niche competition and allows the influx of migratory invertivores. Proportion of migratory birds is higher in TCan deserts due to wider trophic niche but is significantly lower than the global average for the same latitude range. The findings highlight the need for targeted conservation strategies to protect avian diversity in the TCan deserts and mitigate extinction risks in TCap deserts, ensuring the resilience of these critical ecosystems.

Abstract Mason bees, subgenus Osmia Panzer (Hymenoptera: Megachilidae), are economically and ecologically significant pollinators. In eastern North America, the rapid spread of 2 non-native species from Asia, Osmia cornifrons Radoszkowski and Osmia taurus Smith, has coincided with declines in native Osmia populations, raising concern about the effects of further exotic arrivals. Here we investigate the recent establishment in British Columbia, Canada of the European orchard bee, Osmia cornuta Latreille, previously thought to be limited to Europe and its periphery. We document O. cornuta records ranging more than 170 km, including sightings of live adults and the discovery of a multigenerational nest with hundreds of cocoons. We tested whether these cocoons could be discriminated from other Osmia species by training a machine learning classifier on features extracted from images. The best performing model could not reliably discriminate cocoons by species, raising the possibility O. cornuta could be inadvertently intermingled in future commercial shipments. Recent occurrence records of O. cornifrons and O. taurus were spatially isolated, suggesting ongoing anthropogenic dispersal of these species. We predicted the suitability of North American habitats for O. cornuta by estimating its native climate niche. This analysis indicated broad regions of the Pacific Northwest and eastern North America contain potentially suitable habitat. Our findings document the establishment of O. cornuta in North America and the potential for its expansion. Our study demonstrates the utility of accessible biodiversity data archives and public observation programs in tracking non-native species spread and highlights the need for future monitoring of exotic Osmia.

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.

AbstractBees (Hymenoptera: Apoidea) are vital components of global ecosystems, yet knowledge of their distribution is limited in many regions. Washington state is located in an ecologically diverse part of North America and encompasses habitat types and plant communities known for high bee species richness. To establish a baseline for future studies on bee communities in the state, we used published and unpublished datasets to develop a preliminary annotated checklist of bees occurring in Washington state. We document, with high confidence, 565 species of bees in Washington and identify an additional 102 species likely to occur in the state. We anticipate future research survey efforts, such as the newly initiated Washington Bee Atlas, will discover several species that have the potential to occur in Washington and provide new data for 84 species which have not been recorded in more than 50 years.

We assessed changes in fundamental climate‐niche space for lizard and snake species in western North America under modeled climate scenarios to inform natural resource managers of possible shifts in species distributions. We generated eight distribution models for each of 130 snake and lizard species in western North America under six time‐by‐climate scenarios. We combined the highest‐performing models per species into a single ensemble model for each scenario. Maps were generated from the ensemble models to depict climate‐niche space for each species and scenario. Patterns of species richness based on climate suitability and niche shifts were calculated from the projections at the scale of the entire study area and individual states and provinces, from Canada to Mexico. Squamate species' climate‐niche space for the recent‐time climate scenario and published known ranges were highly correlated (r = 0.81). Overall, reptile climate‐niche space was projected to move northward in the future. Sixty‐eight percent of species were projected to expand their current climate‐niche space rather than to shift, contract, or remain stable. Only 8.5% of species were projected to lose climate‐niche space in the future, and these species primarily occurred in Mexico and the southwestern U.S. We found few species were projected to lose all suitable climate‐niche space at the state or province level, although species were often predicted to occupy novel areas, such as at higher elevations. Most squamate species were projected to increase their climate‐niche space in future climate scenarios. As climate niches move northward, species are predicted to cross administrative borders, resulting in novel conservation issues for local landowners and natural resource agencies. However, information on species dispersal abilities, landscape connectivity, biophysical tolerances, and habitat suitability is needed to contextualize predictions relative to realized future niche expansions.

From the largest nesting aggregation ever recorded for the genus Melissodes, we took diverse bionomic measurements of Melissodes bimaculatus (Two-spotted Longhorn Bee). Our results show a protandrous reproductive strategy occurring from July through August in New York. We observed parasitism by the kleptoparasitic bee Triepeolus simplex as well as nest-architecture modifications to ease this burden that support the selfish-herd hypothesis. In this population, we also found a proclivity for grass (Poaceae) pollen, a previously undocumented diet preference for Two-spotted Longhorn Bees. We further showed that this bee species has widespread climatically suitable habitat, with expected range expansion under future climate conditions. Altogether, our results offer novel insights into the ecology of theTwo-spotted Longhorn Bee and its gregarious nesting behavior.

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.

The Nearctic aphid genus Drepanaphis Del Guercio, 1909, the largest within the subfamily Drepanosiphinae (Hemiptera: Aphididae), is characterised by distinctive dorsal abdominal tubercles. This study presents a comprehensive taxonomic revision of the genus, expanding the recognised species to 18, including the newly described Drepanaphis robinsoni Malik sp. nov. Detailed descriptions and figures for 44 morphs, encompassing alate viviparous females, oviparous females and males, are provided, with new identification keys for all known species and morphs. The sexual morphs of 15 species, particularly oviparous females, are documented for the first time. Morphometric and principal component analyses (PCA) are employed to distinguish the studied taxa. This study identifies and corrects numerous misidentifications in museum collections, previously labelled as D. acerifoliae, D. choanotricha, D. kanzensis, D. knowltoni, D. parva, D. sabrinae or D. tissoti. Furthermore, it revalidates the distinct status of D. nigricans and D. tissoti, which had been synonymised in earlier works. Current range maps for all species and images of key morphological features obtained through light and scanning electron microscopy are also presented, providing a more complete understanding of this understudied genus.

Biodiversity loss amplifies the need for taxonomic understanding at global, regional, and local scales. The United Nations Environmental Programme Sustainable Development Goals are explicit in their demand for greater accountability with respect to ecosystem management, and Sustainable Development Goal 15, Life on Land, specifically calls for a halt to biodiversity loss. Pollinators (bees and butterflies) are two functional groups with public attention for protection, yet little long-term data availability. National Parks, including those in the United States, act as optimal sites to study biodiversity loss, but historic data tends to vary in availability. This study addresses systematic taxonomic and digitalization biases present within historic (museum), modern (citizen science), and non-digitized (private collection) datasets for Yellowstone and Grand Teton National Parks from 1900 to 2021. We find that, although database record availability is representative of butterfly and bumble bee groups known for the area, categories such as data rescue, digitalization/availability, and management/archiving vary across database types. These findings on virtual datasets offer opportunities for conservationists to understand the efficacy of digitized collections in addressing questions of species loss over time, including the strengths and pitfalls of digitized data repositories. Additionally, virtual datasets can be utilized to monitor biodiversity under Sustainable Development Goal 15 targets while also promoting broader access to resources such as museum collections for educational purposes. Natural history collections (NHCs) work to preserve biodiversity but tend to hold taxonomic biases. The rapid digitalization of species occurrence data works to improve biodiversity understanding. Pollinator NHCs can inform conservation targets like SDG 15, but only for a subset of species. Additional funding towards data digitalization will broaden the understanding of lesser-known taxa. Virtual museum resources should become more readily accessible to educate and engage the public in species conservation work; citizen science applications can act as an additional educational tool to promote public conservation interest. International biodiversity sampling efforts should be encouraged to document species decline.