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In 1953, investigators at the Rocky Mountain Laboratories in Hamilton, MT, described the isolation of a spotted fever group Rickettsia (SFGR) species from Dermacentor parumapertus ticks collected from black-tailed jackrabbits (Lepus californicus) in northern Nevada. Several decades later, investigators characterized this SFGR (designated the parumapertus agent) by using mouse serotyping methods and determined that it represented a distinct rickettsial serotype closely related to Rickettsia parkeri; nonetheless, the parumapertus agent was not further characterized or studied. To our knowledge, no isolates of the parumapertus agent remain in any rickettsial culture collection, which precludes contemporary phylogenetic placement of this enigmatic SFGR. To rediscover the parumapertus agent, adult-stage D. parumapertus ticks were collected from black-tailed jackrabbits shot or encountered as roadkills in Arizona, Utah, or Texas from 2011 to 2016. A total of 339 ticks were collected and evaluated for infection with Rickettsia species. Of 112 D. parumapertus ticks collected in south Texas, 16 (14.3%) contained partial ompA sequences with the closest identity (99.6%) to Rickettsia sp. strain Atlantic rainforest Aa46, an SFGR that is closely related or identical to an SFGR species that causes a mild rickettsiosis in several states of Brazil. A pure isolate, designated strain Black Gap, was cultivated in Vero E6 cells, and sequence analysis of the rrs, gltA, sca0, sca5, and sca4 genes also revealed the closest genetic identity to Rickettsia sp. Atlantic rainforest Aa46. Phylogenetic analysis of the five concatenated rickettsial genes place Rickettsia sp. strain Black Gap and Rickettsia sp. Atlantic rainforest Aa46 with R. parkeri in a distinct and well-supported clade.IMPORTANCE We suggest that Rickettsia sp. Black Gap and Rickettsia sp. Atlantic rainforest Aa46 represent nearly identical strains of R. parkeri and that Rickettsia sp. Black Gap or a very similar strain of R. parkeri represents the parumapertus agent. The close genetic relatedness among these taxa, as well as the response of guinea pigs infected with the Black Gap strain, suggests that R. parkeri Black Gap could cause disease in humans. The identification of this organism could also account, at least in part, for the remarkable differences in severity ascribed to Rocky Mountain spotted fever (RMSF) among various regions of the American West during the early 20th century. We suggest that the wide variation in case fatality rates attributed to RMSF could have occurred by the inadvertent inclusion of cases of milder disease caused by R. parkeri Black Gap.

Remote cameras have become a widespread data‐collection tool for terrestrial mammals, but classifying images can be labor intensive and limit the usefulness of cameras for broad‐scale population monitoring. Machine learning algorithms for automated image classification can expedite data processing, but image misclassifications may influence inferences. Here, we used camera data for three sympatric species with disparate body sizes and life histories – black‐tailed jackrabbits (Lepus californicus), kit foxes (Vulpes macrotis), and pronghorns (Antilocapra americana) – as a model system to evaluate the influence of competing image classification approaches on estimates of occupancy and inferences about space use. We classified images with: (i) single review (manual), (ii) double review (manual by two observers), (iii) an automated‐manual review (machine learning to cull empty images and single review of remaining images), (iv) a pretrained machine‐learning algorithm that classifies images to species (base model), (v) the base model accepting only classifications with ≥95% confidence, (vi) the base model trained with regional images (trained model), and (vii) the trained model accepting only classifications with ≥95% confidence. We compared species‐specific results from alternative approaches to results from double review, which reduces the potential for misclassifications and was assumed to be the best approximation of truth. Despite high classification success, species‐level misclassification rates for the base and trained models were sufficiently high to produce erroneous occupancy estimates and inferences related to space use across species. Increasing the confidence thresholds for image classification to 95% did not consistently improve performance. Classifying images as empty (or not) offered a reasonable approach to reduce effort (by 97.7%) and facilitated a semi‐automated workflow that produced reliable estimates and inferences. Thus, camera‐based monitoring combined with machine learning algorithms for image classification could facilitate monitoring with limited manual image classification. [ABSTRACT FROM AUTHOR]

Golden eagles Aquila chrysaetos are a long‐lived and wide‐ranging species believed to be stable or in slight decline across North America. Golden eagles have an extended subadult stage (4–5 years) that is critical to maintaining recruitment into the breeding population and population viability. Compared to adult golden eagles, the ecology of subadult golden eagles (hereafter, subadults) has received little attention. We investigated patterns of resource selection for subadults in the Great Basin Desert of the western United States during summer and winter, 2013–2019. We monitored 46 subadults with GPS transmitters and related locations (n = 99 037) with predictors hypothesized to influence seasonal patterns of space use with mixed‐effects logistic regression. Subadults selected for ridges and upper slopes in summer and winter, but higher elevations in summer. Subadults showed weak selection for lower ridge density in summer, which was likely facilitated by selection for areas with greater thermal wind current potential. In contrast, subadults showed strong selection for higher ridge density in winter. Subadults selected areas further from roads in summer and closer to roads and electrical transmission lines in winter, which may be related to winter scavenging of road‐killed ungulates. Resource selection functions suggested subadults selected for shrublands and woodlands in both seasons, but odds ratios revealed that during winter subadults avoided shrublands and increased selection of woodlands relative to summer. Subadults selected for areas with infrequent fires in both seasons; areas with frequent fires were avoided in summer but selected for in winter. Seasonal changes in resource selection suggested that subadults used woodlands more than expected, potentially reflecting spatial partitioning by subadults to lower‐quality habitats to minimize competition with breeding adults during winter when energetic demands for thermoregulation were presumably higher and prey more limited. [ABSTRACT FROM AUTHOR]

Eared Grebes ( Podiceps nigricollis) staging at the Great Salt Lake, Utah, USA, sometimes experience weather-induced downings where many individuals are killed. Downings of Eared Grebes moving south during the fall have been reported for decades; however, spring downings are rare and underrepresented in the literature. On 15 April 2013, 13,500 Eared Grebes flying northward encountered inclement weather, were attracted to lights on Dugway Proving Ground, and downed. This spring downing was documented, and population characteristics were compared with those observed in previous downings. An estimated 38% were killed outright. Rescue efforts promoted the survival of 88% of those not killed on impact. Grebes that were 9-10 months old were, on average, 10% lighter than adults in the same flight, perhaps indicating slow growth or age differences in foraging efficiency. Adults dominated all downings, supporting previous information that adults and young migrate on different schedules. The sex ratio in the North American population appears to be 1:1. Downings occur when Eared Grebes encounter inclement weather and are attracted to lights. Knowledge of the route, migration period, and flight speed of Eared Grebes allows predictions about when and where downings are likely to occur. Reducing the number and intensity of lights on snowy nights in high risk areas may decrease mortality. [ABSTRACT FROM AUTHOR]