An Estimate of Backcountry Day Use of Glacier National Park

Estimates the number of people entering the Glacier National Park backcountry for the summer season of 1988 using infrared beam-activated photography, embedded vibration sensing counters, and trailhead registration validated by personal observation. The study also developed an equation to estimate use levels in future seasons at low cost

Grizzly Bear Population Trend Estimated Using Genetic Detection

We use genetic detection data from natural bear rub sites to estimate annual rate of change for a threatened grizzly bear (Ursus arctos) population in the 33,300 km2 Northern Continental Divide Ecosystem (NCDE) in northwestern Montana, USA). Bear rubs were surveyed twice annually in 2004, 2009-2012 (3,580 – 4,805 rubs).  We detected approximately 1/3 of the grizzly bear population annually. Using spatially explicit capturerecapture (SCR) models in a maximum likelihood framework, we estimate growth rate from the slope of a linear regression fit to the log of density estimates.  To evaluate the usefulness of our estimates, we compare them to estimates of ? made using independent data from known-fate telemetry monitoring for our population.  Total annual population rate of change was 1.056 (95% CI = 1.033-1.079). The large sample sizes generated by genetic detection provided information on variation in density and trend within the NCDE useful for designing monitoring and management strategies tailored to area-specific needs and priorities.  Local rates of change within the NCDE were higher in areas of lower density and population expansion than in Glacier NP, the area with highest density.  As density increased, the amount of space used by bears estimated by the SCR models, ?, decreased. Hair collection from natural bear rub sites was an efficient sampling approach able to generate precise estimates of annual growth rate from 2 years of data

Balancing precision and risk: Should multiple detection methods be analyzed separately in N-mixture models?

Using multiple detection methods can increase the number, kind, and distribution of individuals sampled, which may increase accuracy and precision and reduce cost of population abundance estimates. However, when variables influencing abundance are of interest, if individuals detected via different methods are influenced by the landscape differently, separate analysis of multiple detection methods may be more appropriate. We evaluated the effects of combining two detection methods on the identification of variables important to local abundance using detections of grizzly bears with hair traps (systematic) and bear rubs (opportunistic). We used hierarchical abundance models (N-mixture models) with separate model components for each detection method. If both methods sample the same population, the use of either data set alone should (1) lead to the selection of the same variables as important and (2) provide similar estimates of relative local abundance. We hypothesized that the inclusion of 2 detection methods versus either method alone should (3) yield more support for variables identified in single method analyses (i.e. fewer variables and models with greater weight), and (4) improve precision of covariate estimates for variables selected in both separate and combined analyses because sample size is larger. As expected, joint analysis of both methods increased precision as well as certainty in variable and model selection. However, the single-method analyses identified different variables and the resulting predicted abundances had different spatial distributions. We recommend comparing single-method and jointly modeled results to identify the presence of individual heterogeneity between detection methods in N-mixture models, along with consideration of detection probabilities, correlations among variables, and tolerance to risk of failing to identify variables important to a subset of the population. The benefits of increased precision should be weighed against those risks. The analysis framework presented here will be useful for other species exhibiting heterogeneity by detection method

An Ecosystem-Scale Model for the Spread of a Host-Specific Forest Pathogen in the Greater Yellowstone Ecosystem

The introduction of nonnative pathogens is altering the scale, magnitude, and persistence of forest disturbance regimes in the western United States. In the high-altitude whitebark pine (Pinus albicaulis) forests of the Greater Yellowstone Ecosystem (GYE), white pine blister rust (Cronartium ribicola) is an introduced fungal pathogen that is now the principal cause of tree mortality in many locations. Although blister rust eradication has failed in the past, there is nonetheless substantial interest in monitoring the disease and its rate of progression in order to predict the future impact of forest disturbances within this critical ecosystem. This study integrates data from five different field-monitoring campaigns from 1968 to 2008 to create a blister rust infection model for sites located throughout the GYE. Our model parameterizes the past rates of blister rust spread in order to project its future impact on high-altitude whitebark pine forests. Because the process of blister rust infection and mortality of individuals occurs over the time frame of many years, the model in this paper operates on a yearly time step and defines a series of whitebark pine infection classes: susceptible, slightly infected, moderately infected, and dead. In our analysis, we evaluate four different infection models that compare local vs. global density dependence on the dynamics of blister rust infection. We compare models in which blister rust infection is: (1) independent of the density of infected trees, (2) locally density-dependent, (3) locally density-dependent with a static global infection rate among all sites, and (4) both locally and globally density-dependent. Model evaluation through the predictive loss criterion for Bayesian analysis supports the model that is both locally and globally density-dependent. Using this best-fit model, we predicted the average residence times for the four stages of blister rust infection in our model, and we found that, on average, whitebark pine trees within the GYE remain susceptible for 6.7 years, take 10.9 years to transition from slightly infected to moderately infected, and take 9.4 years to transition from moderately infected to dead. Using our best-fit model, we project the future levels of blister rust infestation in the GYE at critical sites over the next 20 years

Grizzly Bear Abundance and Density in The Cabinet-Yaak Ecosystem

We use genetic detection data from concurrent hair corral and bear rub sampling to provide abundance and density estimates for the threatened grizzly bear (Ursus arctos) populations in the Cabinet Mountain and Yaak regions in northwestern Montana and northern Idaho collectively known as the Cabinet-Yaak Ecosystem (CYE). We used Huggins models in Program MARK and model averaging to generate region- and sex-specific abundance estimates. To estimate the average number of bears present, we estimated mean bear residency on our sampling grid from telemetry data and used it to correct our super population estimates for lack of geographic closure. Total grizzly bear abundance in the CYE in 2012 was 49 (95% CI: 44-62) with an average of 45 (95% CI: 42-65) present at any one time. Population size in the Cabinet and Yaak regions was equal: Cabinet: 22 (95% CI: 20-36); Yaak: 22 (95% CI: 22-39). Grizzly bear density in the CYE was 4.5 (95% CI: 3.7-5.3) grizzly bears/1000 km2. With parentage analysis, we document the first natural migrants to the critically low and interbred Cabinet population and the Yaak population by bears born to parents in neighboring populations. These events support data from other sources suggesting that the expansion of neighboring populations may eventually help sustain the CYE populations

American Black Bear Population Fragmentation Determined Through Pedigrees in the Trans-Border Canada-United States Region

Fragmentation of species with large numbers of individuals in adjacent areas can be challenging to detect using genetic tools as there often is no differentiation because genetic drift occurs very slowly. We used a genetic-based pedigree analysis to detect fragmentation in the American black bear (Ursus americanus) across 2 highways with large adjacent populations. We used 20 locus microsatellite genotypes to detect parent-offspring and full sibling pairs within a sample of 388 black bears. We used the spatial patterns of capture locations of these first order relatives relative to US Highway 2 in northwest Montana and Highway 3 in southeast British Columbia to estimate the number of close relatives sampled across the highways (migrants/km of highway length) as an index of fragmentation. We compared these values to an expected migrant/km rate derived from the mean values of simulated fractures in the Highway 2 and Highway 3 region. We found evidence that these highway corridors were fragmenting black bear populations, but not completely. The observed migrant/km rate for Highway 2 was 0.05, while the expected rate was 0.21 migrants/km. Highway 3 had an observed migrant/km rate of 0.09 compared to the expected rate of 0.26. None of the 16 bears carrying GPS radio collars for 1 year crossed Highway 2, yet 6 of 18 crossed Highway 3. Pedigree and telemetry results were more closely aligned in the Highway 2 system evidencing more intense fragmentation than we found along Highway 3. Our results demonstrate that pedigree analysis may be a useful tool for investigating population fragmentation in situations where genetic signals of differentiation are too weak to determine migration rates using individual-based methods, such as population assignment

SVEP1 is an endogenous ligand for the orphan receptor PEAR1

Sushi, von Willebrand factor type A, EGF and pentraxin domain containing 1 (SVEP1) is an extracellular matrix protein that causally promotes vascular disease and associates with platelet reactivity in humans. Here, using a human genomic and proteomic approach, we identify a high affinity, disease-relevant, and potentially targetable interaction between SVEP1 and the orphan receptor Platelet and Endothelial Aggregation Receptor 1 (PEAR1). This interaction promotes PEAR1 phosphorylation and disease associated AKT/mTOR signaling in vascular cells and platelets. Mice lacking SVEP1 have reduced platelet activation, and exogenous SVEP1 induces PEAR1-dependent activation of platelets. SVEP1 and PEAR1 causally and concordantly relate to platelet phenotypes and cardiovascular disease in humans, as determined by Mendelian Randomization. Targeting this receptor-ligand interaction may be a viable therapeutic strategy to treat or prevent cardiovascular and thrombotic disease

Whole-body microbiota of newborn calves and their response to prenatal vitamin and mineral supplementation

Early life microbial colonization and factors affecting colonization patterns are gaining interest due to recent developments suggesting that early life microbiome may play a role in Developmental Origins of Health and Disease. In cattle, limited information exists on the early microbial colonization of anatomical sites involved in bovine health beyond the gastrointestinal tract. Here, we investigated 1) the initial microbial colonization of seven different anatomical locations in newborn calves and 2) whether these early life microbial communities and 3) serum cytokine profiles are influenced by prenatal vitamin and mineral (VTM) supplementation. Samples were collected from the hoof, liver, lung, nasal cavity, eye, rumen (tissue and fluid), and vagina of beef calves that were born from dams that either received or did not receive VTM supplementation throughout gestation (n = 7/group). Calves were separated from dams immediately after birth and fed commercial colostrum and milk replacer until euthanasia at 30 h post-initial colostrum feeding. The microbiota of all samples was assessed using 16S rRNA gene sequencing and qPCR. Calf serum was subjected to multiplex quantification of 15 bovine cytokines and chemokines. Our results indicated that the hoof, eye, liver, lung, nasal cavity, and vagina of newborn calves were colonized by site-specific microbiota, whose community structure differed from the ruminal-associated communities (0.64 ≥ R2 ≥ 0.12, p ≤ 0.003). The ruminal fluid microbial community was the only one that differed by treatment (p < 0.01). However, differences (p < 0.05) by treatment were detected in microbial richness (vagina); diversity (ruminal tissue, fluid, and eye); composition at the phylum and genus level (ruminal tissue, fluid, and vagina); and in total bacterial abundance (eye and vagina). From serum cytokines evaluated, concentration of chemokine IP-10 was greater (p = 0.02) in VTM calves compared to control calves. Overall, our results suggest that upon birth, the whole-body of newborn calves are colonized by relatively rich, diverse, and site-specific bacterial communities. Noticeable differences were observed in ruminal, vaginal, and ocular microbiota of newborn calves in response to prenatal VTM supplementation. These findings can derive future hypotheses regarding the initial microbial colonization of different body sites, and on maternal micronutrient consumption as a factor that may influence early life microbial colonization