Seeking Out the Hoary Marmot: Habitat Characteristics of an Alpine Obligate

Alpine ecosystems likely will be impacted by climate change, which will shift distributions of alpine species. To predict these shifts reliably, an increased understanding about the habitat characteristics that are important to alpine species will be necessary to manage for their continued presence on the landscape. We have very limited information about habitat for hoary marmots (Marmota caligata) in Montana. To address this knowledge gap, we investigated the relative importance of habitat characteristics for marmot occupancy. During the summers of 2014 and 2015, we surveyed 184 sites in 5 mountain ranges throughout western Montana. We surveyed each site 2-5 times (average = 4.25 surveys/site) and detected marmots in 61 sites using two survey methods. Wind speed, survey method, cloud cover, and percent of the site that was visible all influenced detection probability. We estimated that marmots occurred in 36% of all sites (95% CI = 29-46%).  Occupancy of marmots increased with snow and shrub cover and decreased with slope and distance to water. Given that snowpack, precipitation, and water sources are predicted to be impacted by climate change, our results begin to illustrate where this species of concern may become susceptible. If snowpack and the number of water sources decrease or shift geographically, this may reduce or alter the available habitat for marmots. We hope to augment the paucity of information about hoary marmots at the southern end of their distribution and aid management of this species under an uncertain climate future

Influence of Boulder Size on Occupancy and Detection of Hoary Marmots (Poster)

Hoary marmots (Marmota caligata) can be found in boulder fields throughout alpine areas of western Montana, but we know little about their specific habitat requirements. We sought to determine the influence of boulder size on occupancy and detection probability of the hoary marmot during occupancy surveys. We conducted 532 visual occupancy surveys of 147 sites between June and September 2015. We estimated variation in occupancy and detection probability based on four size categories of boulders. We did not detect differences in occupancy of marmots as the size composition of boulders changed. Detection probability was most influenced by medium and large boulders. Probability of detecting a marmot was 38% (95% CI=0.24–0.53) when medium boulders were absent, but decreased to 3% as the proportion of medium boulders increased to 60% (95% CI=0–0.15). Probability of detecting a marmot was 16% when large boulders were absent (95% CI=0.1–0.24) but increased to 92% when just 5% of the site consisted of large boulders (95% CI=0.61–0.99). Accounting for this variation in detection probability with changes in boulder size will be important for designing a long-term monitoring protocol that can produce accurate estimates of occupancy for hoary marmots. A monitoring protocol incorporating key habitat requirements would be valuable for the future management and conservation of a species living in harsh alpine environments where climate change is predicted to occur rapidly

Monitoring Hoary Marmots: Matching Objectives to Available Effort

Monitoring provides information necessary for managers to make informed decisions related to the status of populations. However, collecting sufficient data to reliably detect trends in abundance over a large area is costly in time and resources. Instead, detecting changes in distribution may be a more feasible goal, while still providing useful information. Hoary marmots are alpine obligates, patchily distributed throughout the mountains of western North America. This species requires deep winter snowpack to survive during winter and populations at the edges of their distribution are most likely to be vulnerable to changes in climate. We sought to design a monitoring plan that could identify changes in distribution of hoary marmot populations. We used occupancy methods to create a predictive habitat map for hoary marmots in western Montana. We evaluated designs that could be implemented by existing staff or with 2 dedicated technicians and assessed tradeoffs in the number of sites and surveys needed to detect a change in distribution. We also evaluated the effort needed to sample throughout Montana or within selected mountain ranges. Based on our analyses, managers will need to complete surveys at ?65 sites at least twice a season and without dedicated technicians, the area sampled will be limited. Hoary marmots likely will be negatively impacted by climate change, especially in isolated mountain ranges at the southern extent of their distribution. Assessing the magnitude of these changes will be impossible without sufficient data, highlighting the importance of identifying monitoring objectives before data collection begins

Investigating Habitat Characteristics Important to Hoary Marmots in Montana

Alpine ecosystems will be impacted by climate change, which will shift distributions of alpine species on the landscape. Understanding which habitat characteristics are important to alpine species will be necessary to predict changes in distribution reliably. The hoary marmot (Marmota caligata) is an alpine obligate whose range extends from Alaska into western Montana. Although hoary marmots are relatively abundant, they are a potential species of concern in Montana because we lack information on their distribution and habitat requirements. We initiated a project to investigate the genetic connectivity and habitat characteristics that promote occupancy of marmots. Between June and August 2014, we visited five mountain ranges in search of hoary marmots. At two to three sites per mountain range, we trapped marmots for genetic samples and surveyed areas visually to quantify occupancy. We sampled 47 sites during 79 surveys; at least one marmot was detected by at least one observer in 12 of these surveys (15%). Marmots were more likely to occupy sites with increased cover of boulders and wet meadow and less likely to occupy sites with increased cover of shrubs and grasses. Overall, the probability of detecting a marmot was 0.59 (SE = 0.10) and the probability of occupancy across all sites was 0.27 (SE = 0.10). Our work will provide information about non-game species in alpine environments and inform the design of monitoring programs that can aid managers as they begin to understand where hoary marmots are on the landscape and where they could be in the future

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

BackgroundFuture trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050.MethodsUsing forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline.FindingsIn the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]).InterpretationGlobally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions.FundingBill & Melinda Gates Foundation.</p