Search

Introduction: Terrestrial species in riverine ecosystems face unique constraints leading to diverging patterns of population structure, connectivity, and disease dynamics. Desert bighorn sheep (Ovis canadensis nelsoni) in Grand Canyon National Park, a large native population in the southwestern USA, offer a unique opportunity to evaluate population patterns and processes in a remote riverine system with ongoing anthropogenic impacts. We integrated non-invasive, invasive, and citizen-science methods to address questions on abundance, distribution, disease status, genetic structure, and habitat fragmentation. Methods: We compiled bighorn sightings collected during river trips by park staff, commercial guides, and private citizens from 2000-2018 and captured bighorn in 2010-2016 to deploy GPS collars and test for disease. From 2011-2015, we noninvasively collected fecal samples and genotyped them at 9-16 microsatellite loci for individual identification and genetic structure. We used assignment tests to evaluate genetic structure and identify subpopulations, then estimated gene flow and recent migration to evaluate fragmentation. We used spatial capturerecapture to estimate annual population size, distribution, and trends after accounting for spatial variation in detection with a resource selection function model. Results and discussion: From 2010-2018, 3,176 sightings of bighorn were reported, with sightings of 56-145 bighorn annually on formal surveys. From 2012-2016, bighorn exhibiting signs of respiratory disease were observed along the river throughout the park. Of 25 captured individuals, 56% were infected by Mycoplasma ovipneumoniae, a key respiratory pathogen, and 81% were recently exposed. Pellet sampling for population estimation from 2011-2015 yielded 1,250 genotypes and 453 individuals. We detected 6 genetic clusters that exhibited mild to moderate genetic structure (FST 0.022-0.126). The river, distance, and likely topography restricted recent gene flow, but we detected cross-river movements in one section via genetic recaptures, no subpopulation appeared completely isolated, and genetic diversity was among the highest reported. Recolonization of one large stretch of currently empty habitat appears limited by the constrained topology of this system. Annual population estimates ranged 536-552 (95% CrI range 451-647), lamb:ewe ratios varied, and no significant population decline was detected. We provide a multi-method sampling framework useful for sampling other wildlife in remote riverine systems. [ABSTRACT FROM AUTHOR]

Adaptive management has emerged as the prevailing approach for combining environmental research and management to advance science and policy. Adaptive management, as originally formulated by Carl Walters in 1986, depends on the use of Bayesian models to provide a framework to accumulate knowledge. The emergence of ecological forecasting using the Bayesian framework has provided robust tools and supports a new approach to informing adaptive management, which can be particularly useful in developing policy for managing infectious disease in wildlife. We used the potential infection of elk populations with chronic wasting disease in the Jackson Valley of Wyoming and the National Elk Refuge as a model system to show how Bayesian forecasting can support adaptive management in anticipation of management challenges. The core of our approach resembles the sex‐ and age‐structured, discrete time models used to support management decisions on elk harvest throughout western North America. Our model differs by including stages for CWD‐infected and unaffected animals. We used data on population counts, sex and age classification, and CWD testing, as well as results from prior research, in a Bayesian statistical framework to predict model parameters and the number of animals in each age, sex, and disease stage over time. Initial forecasts suggested CWD may reach a mean prevalence in the population of 12%, but uncertainty in this forecast is large and we cannot rule out a mean forecasted prevalence as high as 20%. Using recruitment rates observed during the last two decades, the model predicted that a CWD prevalence of 7% in females would cause the population growth rate (λ) to drop below 1, resulting in population declines even when female harvest was zero. The primary value of this ecological forecasting approach is to provide a framework to assimilate data with understanding of disease processes to enable continuous improvement in understanding the ecology of CWD and its management. [ABSTRACT FROM AUTHOR]

Abstract: Accurate assessment of abundance forms a central challenge in population ecology and wildlife management. Many statistical techniques have been developed to estimate population sizes because populations change over time and space and to correct for the bias resulting from animals that are present in a study area but not observed. The mobility of individuals makes it difficult to design sampling procedures that account for movement into and out of areas with fixed jurisdictional boundaries. Aerial surveys are the gold standard used to obtain data of large mobile species in geographic regions with harsh terrain, but these surveys can be prohibitively expensive and dangerous. Estimating abundance with ground‐based census methods have practical advantages, but it can be difficult to simultaneously account for temporary emigration and observer error to avoid biased results. Contemporary research in population ecology increasingly relies on telemetry observations of the states and locations of individuals to gain insight on vital rates, animal movements, and population abundance. Analytical models that use observations of movements to improve estimates of abundance have not been developed. Here we build upon existing multi‐state mark–recapture methods using a hierarchical N‐mixture model with multiple sources of data, including telemetry data on locations of individuals, to improve estimates of population sizes. We used a state‐space approach to model animal movements to approximate the number of marked animals present within the study area at any observation period, thereby accounting for a frequently changing number of marked individuals. We illustrate the approach using data on a population of elk (Cervus elaphus nelsoni) in Northern Colorado, USA. We demonstrate substantial improvement compared to existing abundance estimation methods and corroborate our results from the ground based surveys with estimates from aerial surveys during the same seasons. We develop a hierarchical Bayesian N‐mixture model using multiple sources of data on abundance, movement and survival to estimate the population size of a mobile species that uses remote conservation areas. The model improves accuracy of inference relative to previous methods for estimating abundance of open populations. [ABSTRACT FROM AUTHOR]

Inventory and Monitoring Programs in the National Park Service (NPS) provide information needed to support wise planning, management, and decision making. Mathematical and statistical models play a critical role in this process by integrating data from multiple sources in a way that is honest about uncertainty. We show the utility of Bayesian hierarchical models for supporting decisions on managing natural resources of national parks. These models can assimilate monitoring data to provide true forecasts, resulting in probabilistic predictions of future states of park ecosystems accompanied by rigorous estimates of uncertainty. We discuss a novel approach for communicating these forecasts to decision makers who need to evaluate the probability that NPS goals will be met given different management actions, including the null model of no action. We illustrate how this approach has been used successfully to inform decisions on the elk (Cervus elaphus nelsoni) population management in Rocky Mountain National Park based on 47 yr of monitoring data. Forecasts from a discrete time, stage-structured population model assimilated with annual census and sex and age classifications are being used annually to help park managers decide on actions needed to meet goals for elk and vegetation. In particular, park managers were able to determine the probability that the elk population would fall within a desired population range, which led to both population reduction actions and no action depending on the year of interest. Moreover, this approach allowed multiple survey methodologies from the last 47 years to be incorporated into a single model with associated estimates of uncertainty. Models like this one are especially useful for adaptive management where continuous improvement in models and data results in long-term improvement in the wisdom of policy and management. [ABSTRACT FROM AUTHOR]

Trypanosoma cruzi, the causative agent of Chagas' disease, is a substantial public health concern in Latin America. Although rare in humans and domestic animals in the United States, T. cruzi is commonly detected in some wildlife species, most commonly raccoons (Procyon lotor) and Virginia opossums (Didelphis virginiana). To increase our understanding of the reservoir host species range and geographic distribution, 11 species of mammals from six states spanning the known range of T. cruzi (Arizona, California, Florida, Georgia, Missouri, and Virginia) were tested for antibodies to T. cruzi using indirect immunofluorescent antibody testing. In addition, culture isolation attempts were conducted on a limited number of animals from Georgia and Florida. Evidence of T. cruzi was found in every state except California; however, low numbers of known reservoirs were tested in California. In general, the highest seroprevalence rates were found in raccoons (0-68%) and opossums (17-52%), but antibodies to T. cruzi were also detected in small numbers of striped skunks (Mephitis mephitis) from Arizona and Georgia, bobcats (Lynx rufus) from Georgia, two coyotes (Canis latrans) from Georgia and Virginia, and a ringtail (Bassariscus astutus) from Arizona. Culture-based prevalence rates for raccoons were significantly greater than those for opossums; however, seroprevalences of raccoons and opossums from several geographic locations in Georgia and Florida were not different, indicating that exposure rates of these two species are similar within these areas. For both raccoons and opossums, seroprevalence was significantly higher in females than in males. No difference was detected in seroprevalence between adults and juveniles and between animals caught in urban and rural locations. Our results indicate that T. cruzi prevalence varies by host species, host characteristics, and geographic region and provides data to guide future studies on the natural history of T. cruzi in the United States.