RT-QuIC detection of chronic wasting disease prion in platelet samples of white-tailed deer.

BACKGROUND: Chronic wasting disease (CWD) is a prion disease of captive and free-ranging cervids. Currently, a definitive diagnosis of CWD relies on immunohistochemistry detection of PrPSc in the obex and retropharyngeal lymph node (RPLN) of the affected cervids. For high-throughput screening of CWD in wild cervids, RPLN samples are tested by ELISA followed by IHC confirmation of positive results. Recently, real-time quacking-induced conversion (RT-QuIC) has been used to detect CWD positivity in various types of samples. To develop a blood RT-QuIC assay suitable for CWD diagnosis, this study evaluated the assay sensitivity and specificity with and without ASR1-based preanalytical enrichment and NaI as the main ionic component in assay buffer. RESULTS: A total of 23 platelet samples derived from CWD-positive deer (ELISA + /IHC +) and 30 platelet samples from CWD-negative (ELISA-) deer were tested. The diagnostic sensitivity was 43.48% (NaCl), 65.22% (NaI), 60.87% (NaCl-ASR1) or 82.61% (NaI-ASR1). The diagnostic specificity was 96.67% (NaCl), 100% (NaI), 100% (NaCl-ASR1), or 96.67% (NaI-ASR1). The probability of detecting CWD prion in platelet samples derived from CWD-positive deer was 0.924 (95% CRI: 0.714, 0.989) under NaI-ASR1 experimental condition and 0.530 (95% CRI: 0.156, 0.890) under NaCl alone condition. The rate of amyloid formation (RFA) was greatest under the NaI-ASR1 condition at 10-2 (0.01491, 95% CRI: 0.00675, 0.03384) and 10-3 (0.00629, 95% CRI: 0.00283, 0.01410) sample dilution levels. CONCLUSIONS: Incorporation of ASR1-based preanalytical enrichment and NaI as the main ionic component significantly improved the sensitivity of CWD RT-QuIC on deer platelet samples. Blood test by the improved RT-QuIC assay may be used for antemortem and postmortem diagnosis of CWD.

Joint analysis of structured and semi-structured community science data improves precision of relative abundance but not trends in birds.

Estimating absolute and relative abundance of wildlife populations is critical to addressing ecological questions and conservation needs, yet obtaining reliable estimates can be challenging because surveys are often limited spatially or temporally. Community science (i.e., citizen science) provides opportunities for semi-structured data collected by the public (e.g., eBird) to improve capacity of relative abundance estimation by complementing structured survey data collected by trained observers (e.g., North American breeding bird survey [BBS]). We developed two state-space models to estimate relative abundance and population trends: one using BBS data and the other jointly analyzing BBS and eBird data. We applied these models to seven bird species with diverse life history characteristics. Joint analysis of eBird and BBS data improved precision of mean and year-specific relative abundance estimates for all species, but the BBS-only model produced more precise trend estimates compared to the joint model for most species. The relative abundance estimates of the joint model were particularly more precise than the BBS-only estimates in areas where species detectability was low resulting from either low BBS survey effort or low abundance. These results suggest that community science data can be a valuable resource for cost-effective improvement in wildlife abundance estimation.

Variable precipitation leads to dynamic range limits of forest songbirds at a forest-grassland ecotone.

Boundaries between vegetation types, known as ecotones, can be dynamic in response to climatic changes. The North American Great Plains includes a forest-grassland ecotone in the southcentral United States that has expanded and contracted in recent decades in response to historical periods of drought and pluvial conditions. This dynamic region also marks a western distributional limit for many passerine birds that typically breed in forests of the eastern United States. To better understand the influence that variability can exert on broad-scale biodiversity, we explored historical longitudinal shifts in the western extent of breeding ranges of eastern forest songbirds in response to the variable climate of the southern Great Plains. We used climatic niche modeling to estimate current distributional limits of nine species of forest-breeding passerines from 30-year average climate conditions from 1980 to 2010. During this time, the southern Great Plains experienced an unprecedented wet period without periodic multi-year droughts that characterized the region's long-term climate from the early 1900s. Species' climatic niche models were then projected onto two historical drought periods: 1952-1958 and 1966-1972. Threshold models for each of the three time periods revealed dramatic breeding range contraction and expansion along the forest-grassland ecotone. Precipitation was the most important climate variable defining breeding ranges of these nine eastern forest songbirds. Range limits extended farther west into southern Great Plains during the more recent pluvial conditions of 1980-2010 and contracted during historical drought periods. An independent dataset from BBS was used to validate 1966-1972 range limit projections. Periods of lower precipitation in the forest-grassland ecotone are likely responsible for limiting the western extent of eastern forest songbird breeding distributions. Projected increases in temperature and drought conditions in the southern Great Plains associated with climate change may reverse range expansions observed in the past 30 years.

Resource selection and movement by northern bobwhite broods varies with age and explains survival.

Resource selection is a dynamic process driven by habitat valuation and risk avoidance in heterogeneous landscapes. Resource selection and movement decisions of individuals may be sensitive to intrinsic factors, such as body condition, and variation in these choices may have consequences on subsequent survival. We evaluated northern bobwhite (Colinus virginianus) brood resource selection patterns to quantify utility of different cover types during the development period using integrated step-selection analysis in a Bayesian hierarchical modeling framework with three brood stages: flightless broods ≤ 14 days old, dependent broods 15-35 days old, and independent broods over 35 days old. Broods showed strongest selection for native grasslands that were burned and grazed at least once in the previous two years, and agricultural fields. Brood mobility improved with age; broods > 35 days old travelled farther on average and took daily steps > 200 m more frequently than younger broods. Young broods ≤ 14 days old did not select for idle native grasslands, while broods > 35 days old did select for that cover type. Young broods also selected areas farther from trees compared to older broods. We evaluated the survival consequences of resource selection by comparing patterns in choices of broods that succeeded to choices of broods that failed to survive to 35 days. Successful broods chose habitats with more shrub cover and areas farther from trees compared to failed broods. Our results suggest that conservation planning should consider age-specific patterns in habitat use and demographic consequences of habitat choice for greatest effectiveness.