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Winter recreation and tourism continue to expand worldwide, and where these activities overlap with valuable wildlife habitat, there is greater potential for conservation concerns. Wildlife populations can be particularly vulnerable to disturbance in alpine habitats as helicopters and snowmachines are increasingly used to access remote backcountry terrain. Brown bears (Ursus arctos) have adapted hibernation strategies to survive this period when resources and energy reserves are limited, and disturbance could negatively impact fitness and survival. To help identify areas of potential conflict between helicopter skiing and denning brown bears in Alaska, we developed a model to predict alpine denning habitat and an associated data-based framework for mitigating disturbance activities. Following den emergence in spring, we conducted three annual aerial surveys (2015-2017) and used locations from three GPS-collared bears (2008-2014) to identify 89 brown bear dens above the forest line. We evaluated brown bear den site selection of land cover, terrain, and climate factors using resource selection function (RSF) models. Our top model supported the hypothesis that bears selected dens based on terrain and climate factors that maximized thermal efficiency. Brown bears selected den sites characterized by steep slopes at moderate elevations in smooth, well-drained topographies that promoted vegetation and deep snow. We used the RSF model to map relative probability of den selection and found 85% of dens occurred within terrain predicted as prime denning habitat. Brown bear exposure to helicopter disturbance was evident as moderate to high intensities of helicopter flight tracking data overlapped prime denning habitat, and we quantified where the risk of these impact was greatest. We also documented evidence of late season den abandonment due to disturbance from helicopter skiing. The results from this study provide valuable insights into bear denning habitat requirements in subalpine and alpine landscapes. Our quantitative framework can be used to support conservation planning for winter recreation industries operating in habitats occupied by denning brown bears.

Understanding patterns of animal space use and range fidelity has important implications for species and habitat conservation. For species that live in highly seasonal environments, such as mountain goats (Oreamnos americanus), spatial use patterns are expected to vary in relation to seasonal changes in environmental conditions and sex‐ or age‐specific selection pressures. To address hypotheses about sex, age, and seasonality influence on space‐use ecology, we collected GPS location data from 263 radio‐collared mountain goats (males, n = 140; females, n = 123) in coastal Alaska during 2005–2016. Location data were analyzed to derive seasonal and sex‐specific fixed‐kernel home range estimates and to quantify the degree of seasonal range and utilization distribution overlap. Overall, we determined that home range size was smallest during winter, expanded coincident with the onset of green‐up and parturition, and was largest during summer. Home range size of males and females did not differ significantly during winter, but females had larger home ranges than males during summer, a relationship that was switched during the mating season. Pairwise comparisons involving individual females across subsequent years indicated home ranges were significantly smaller during years when they gave birth to offspring. Mountain goats exhibited a strong degree of range fidelity, and 99% (n = 138) of individual animals returned to their previous year's seasonal range with an average annual Bhattacharyya's affinity utilization distribution overlap index of 68%. Similarity of seasonal home range utilization distributions varied in relation to sex and season in some respects. Home range overlap was highest during the summer vegetation growing season, particularly among females. These findings advance our understanding about how environmental variation and sex‐ and age‐related reproductive constraints influence space use and range fidelity among alpine ungulates. Documentation of the high degree of range fidelity among mountain goats has important conservation implications in landscapes increasingly altered by anthropogenic activities. We created seasonal and sex‐specific fixed‐kernel home range estimates to quantify seasonal home range size and utilization distribution overlap of mountain goats in southeast Alaska. We documented a high degree of range fidelity among mountain goats, which has conservation implications on a landscapes increasingly altered by anthropogenic activities.

Cellular therapy to treat heart failure is an ongoing focus of intense research, but progress toward structural and functional recovery remains modest. Engineered augmentation of established cellular effectors overcomes impediments to enhance reparative activity. Such ‘next generation’ implementation includes delivery of combinatorial cell populations exerting synergistic effects. Concurrent isolation and expansion of three distinct cardiac-derived interstitial cell types from human heart tissue, previously reported by our group, prompted design of a 3D structure that maximizes cellular interaction, allows for defined cell ratios, controls size, enables injectability, and minimizes cell loss. Herein, mesenchymal stem cells (MSCs), endothelial progenitor cells (EPCs) and c-Kit + cardiac interstitial cells (cCICs) when cultured together spontaneously form scaffold-free 3D microenvironments termed CardioClusters. scRNA-Seq profiling reveals CardioCluster expression of stem cell-relevant factors, adhesion/extracellular-matrix molecules, and cytokines, while maintaining a more native transcriptome similar to endogenous cardiac cells. CardioCluster intramyocardial delivery improves cell retention and capillary density with preservation of cardiomyocyte size and long-term cardiac function in a murine infarction model followed 20 weeks. CardioCluster utilization in this preclinical setting establish fundamental insights, laying the framework for optimization in cell-based therapeutics intended to mitigate cardiomyopathic damage. Despite recent progress to advance cardiac cell-based therapy for patients, heart failure mortality rivals most cancers. Here, the authors describe an approach to control and pattern 3 distinct human cardiac cell populations to promote superior repair and regeneration after myocardial infarction.

We report the development and performance of a novel genomics platform, TempO-LINC, for conducting high-throughput transcriptomic analysis on single cells and nuclei. TempO-LINC works by adding cell-identifying molecular barcodes onto highly selective and high-sensitivity gene expression probes within fixed cells, without having to first generate cDNA. Using an instrument-free combinatorial indexing approach, all probes within the same fixed cell receive an identical barcode, enabling the reconstruction of single-cell gene expression profiles across as few as several hundred cells and up to 100,000 + cells per sample. The TempO-LINC approach is easily scalable based on the number of barcodes and rounds of barcoding performed; however, for the experiments reported in this study, the assay utilized over 5.3 million unique barcodes. TempO-LINC offers a robust protocol for fixing and banking cells and displays high-sensitivity gene detection from multiple diverse sample types. We show that TempO-LINC has a multiplet rate of less than 1.1% and a cell capture rate of ~ 50%. Although the assay can accurately profile the whole transcriptome (19,683 human, 21,400 mouse and 21,119 rat genes), it can be targeted to measure only actionable/informative genes and molecular pathways of interest – thereby reducing sequencing requirements. In this study, we applied TempO-LINC to profile the transcriptomes of more than 90,000 cells across multiple species and sample types, including nuclei from mouse lung, kidney and brain tissues. The data demonstrated the ability to identify and annotate more than 50 unique cell populations and positively correlate expression of cell type-specific molecular markers within them. TempO-LINC is a robust new single-cell technology that is ideal for large-scale applications/studies with high data quality.

The community of microorganisms in the gut is affected by host species, diet and environment and is linked to normal functioning of the host organism. Although the microbiome fluctuates in response to host demands and environmental changes, there are core groups of microorganisms that remain relatively constant throughout the hosts lifetime. Ruminants are mammals that rely on highly specialized digestive and metabolic modifications, including microbiome adaptations, to persist in extreme environments. Here, we assayed the fecal microbiome of four mountain goat (Oreamnos americanus) populations in western North America. We quantified fecal microbiome diversity and composition among groups in the wild and captivity, across populations and in a single group over time. There were no differences in community evenness or diversity across groups, although we observed a decreasing diversity trend across summer months. Pairwise sample estimates grouped the captive population distinctly from the wild populations, and moderately grouped the southern wild group distinctly from the two northern wild populations. We identified 33 genera modified by captivity, with major differences in key groups associated with cellulose degradation that likely reflect differences in diet. Our findings are consistent with other ruminant studies and provide baseline microbiome data in this enigmatic species, offering valuable insights into the health of wild alpine ungulates.

The costs and benefits of alternative migratory strategies are often framed in the context of top-down and bottom-up effects on individual fitness. This occurs because migration is considered a costly behavioral strategy that presumably confers explicit benefits to migrants in the form of either decreased predation risk (predation risk avoidance hypothesis) or increased nutrition (forage maturation hypothesis). To test these hypotheses, we studied a partially migratory moose ( Alces alces ) population and contrasted explicit measures of predation risk (i.e., offspring survival) and nutrition (i.e., accumulation of endogenous energy reserves) between resident and migratory subpopulations. We relied on data collected from migratory and nonmigratory radio-marked moose ( n = 67) that inhabited a novel study system located in coastal Alaska between 2004 and 2010. In this area, 30% of the population resides year-round on a coastal foreland area, while 48% migrate to either a small island archipelago or a subalpine ridge system (the remainder exhibited one of six different low-occurrence strategies). Overall, we determined that accumulation of body fat during the growing season did not differ between migratory or resident modalities. However, calf survival was 2.6-2.9 times higher for individuals that migrated (survival, islands = 0.49 ± 0.16 [mean ± SE], n = 35; ridge = 0.52 ± 0.16, n = 33) than those that did not (survival, resident = 0.19 ± 0.08, n = 57). Our results support the predation risk avoidance hypotheses, and suggest that migration is a behavioral strategy that principally operates to reduce the risk of calf predation and does not confer explicit nutritional benefits. We did not directly detect trade-offs between predation risk and nutrition for migratory individuals. Yet we identify an indirect life history mechanism that may mildly dampen the apparent fitness benefits of migration. The proximate factors accounting for differences in migration-specific neonate survival are likely linked to accessibility of refugial habitats for moose at local and landscape scales, landscape factors that affect hunting efficacy of large carnivores, and interactions with rural human communities. Conservation of ungulate populations can be aided by integrating knowledge about migratory behavior, life history strategies, and factors that alter ungulate vulnerability, particularly those induced by human activity.

Despite effective antiretroviral therapy, HIV co-morbidities remain where central nervous system (CNS) neurocognitive disorders and cardiovascular disease (CVD)-pathology that are linked with myeloid activation are most prevalent. Comorbidities such as neurocogntive dysfunction and cardiovascular disease (CVD) remain prevalent among people living with HIV. We sought to investigate if cardiac pathology (inflammation, fibrosis, cardiomyocyte damage) and CNS pathology (encephalitis) develop together during simian immunodeficiency virus (SIV) infection and if their co-development is linked with monocyte/macrophage activation. We used a cohort of SIV-infected rhesus macaques with rapid AIDS and demonstrated that SIV encephalitis (SIVE) and CVD pathology occur together more frequently than SIVE or CVD pathology alone. Their co-development correlated more strongly with activated myeloid cells, increased numbers of CD14+CD16+ monocytes, plasma CD163 and interleukin-18 (IL-18) than did SIVE or CVD pathology alone, or no pathology. Animals with both SIVE and CVD pathology had greater numbers of cardiac macrophages and increased collagen and monocyte/macrophage accumulation, which were better correlates of CVD-pathology than SIV-RNA. Animals with SIVE alone had higher levels of activated macrophage biomarkers and cardiac macrophage accumulation than SIVnoE animals. These observations were confirmed in HIV infected individuals with HIV encephalitis (HIVE) that had greater numbers of cardiac macrophages and fibrosis than HIV-infected controls without HIVE. These results underscore the notion that CNS and CVD pathologies frequently occur together in HIV and SIV infection, and demonstrate an unmet need for adjunctive therapies targeting macrophages.

In salmon‐rich environments, which once spanned much of the Northern Hemisphere, bears occur at exceptionally high densities. Salmon, by growing bear populations, have the potential to exert wide‐ranging effects on ecosystem processes. Salmon‐supported bears provide seed dispersal services to plants, and bear scats containing thousands of seeds may then be efficient nutritional resources for granivorous small mammals that also function as secondary seed dispersers while hoarding seeds for winter. We taxonomically identified and enumerated seeds in individual bear scats to characterize patterns of bear frugivory. We then combined estimates of seed abundance and digestible energy content to quantify the energy available to granivorous small mammals, and we quantified the proportion of the mouse population that could be supported by locally abundant bear populations in lowland salmon systems. We additionally monitored seed‐filled bear scats with remote cameras to quantify small mammal visitation rates, and live‐trapped small mammals seasonally to determine whether rodents visited bear scats proportional to their densities or whether some species preferentially selected for bear scats, and to assess whether seasonal variation in scat visitation was driven by density or selection. Bears were an important initial dispersal agent for 12 species of fruit, particularly devil's club (Oplopanax horridus) and blueberry (Vaccinium spp.), which occurred in 80% (5839 seeds/scat) and 50% (10,719 seeds/scat) of scats, respectively. Seeds in bear scats were intensively utilized and dispersed by small mammals, primarily scatter‐hoarding northwestern deer mice (Peromyscus keeni; 8.5 visits per day/4295 total visits) and larder‐hoarding northern red‐backed voles (Myodes rutilus; 2.2 visits per day/1099 total visits), with visitation rates proportional to the seasonal density of each species. Small mammals likely incurred significant nutritional benefits from seeds deposited in bear scats (kcal/scat, mean = 114, n = 71). In coastal Alaska riparian areas, bears are potentially capable of indirectly subsidizing the energy needs of 45–65% of local deer mouse populations. Thus, this work helps elucidate the role that salmon, by supporting abundant bears, plays in ecological communities via influencing seed dispersal and resource subsidies to the small mammals that compose the base of the food web.

Landscape heterogeneity plays an integral role in shaping ecological and evolutionary processes. Despite links between the two disciplines, ecologists and population geneticists have taken different approaches to evaluating habitat selection, animal movement, and gene flow across the landscape. Ecologists commonly use statistical models such as resource selection functions (RSFs) to identify habitat features disproportionately selected by animals, whereas population genetic approaches model genetic differentiation according to the distribution of habitat variables. We combined ecological and genetic approaches by using RSFs to predict genetic relatedness across a heterogeneous landscape. We constructed sex- and season-specific resistance surfaces based on RSFs estimated using data from 102 GPS (global positioning system) radio-collared mountain goats ( Oreamnos americanus ) in southeast Alaska, USA. Based on mountain goat ecology, we hypothesized that summer and male surfaces would be the best predictors of relatedness. All individuals were genotyped at 22 microsatellite loci, which we used to estimate genetic relatedness. Summer resistance surfaces derived from RSFs were the best predictors of genetic relatedness, and winter models the poorest. Mountain goats generally selected for areas close to escape terrain and with a high heat load (a metric related to vegetative productivity and snow depth), while avoiding valleys. Male- and female-specific surfaces were similar, except for winter, for which male habitat selection better predicted genetic relatedness. The null models of isolation-by-distance and barrier only outperformed the winter models. This study merges high-resolution individual locations through GPS telemetry and genetic data, that can be used to validate and parameterize landscape genetics models, and further elucidates the relationship between landscape heterogeneity and genetic differentiation.

Snow is a major, climate-sensitive feature of the Earth’s surface and catalyst of fundamentally important ecosystem processes. Understanding how snow influences sentinel species in rapidly changing mountain ecosystems is particularly critical. Whereas effects of snow on food availability, energy expenditure, and predation are well documented, we report how avalanches exert major impacts on an ecologically significant mountain ungulate - the coastal Alaskan mountain goat ( Oreamnos americanus ). Using long-term GPS data and field observations across four populations (421 individuals over 17 years), we show that avalanches caused 23−65% of all mortality, depending on area. Deaths varied seasonally and were directly linked to spatial movement patterns and avalanche terrain use. Population-level avalanche mortality, 61% of which comprised reproductively important prime-aged individuals, averaged 8% annually and exceeded 22% when avalanche conditions were severe. Our findings reveal a widespread but previously undescribed pathway by which snow can elicit major population-level impacts and shape demographic characteristics of slow-growing populations of mountain-adapted animals. Snow avalanches—a direct physical process—represent a major source of mortality and comprise a previously undescribed pathway by which climate-linked mechanisms impact demographics of slow-growing populations of mountain-adapted animals.