Data and code associated with “Supporting Adaptive Management with Ecological Forecasting: Chronic Wasting Disease in the Jackson Elk Herd”

Final_Data.zip contains several spreadsheets representing data collected by both the Wyoming Game and Fish Department and the US Fish and Wildlife Service for elk management: Jackson feedground census, 1998-2016; Harvest data, 1997-2015; Hunt area census, 1998-2016; Chronic wasting disease test results, 1998-2015. Final_Code.zip contains several Program R scripts written for data analysis and model fitting as described in the full associated article.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 (l) 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.Data collection was funded as part of management efforts by the Wyoming Game and Fish Department and the US Fish and Wildlife Service. Data analysis and work for publication was funded by the US Fish and Wildlife Service and the National Park Service

CreechTylerFisheriesWildlifeUsingNetworkTheory_SupplementaryMaterial.pdf

Connectivity models using empirically-derived landscape resistance maps can predict potential linkages among fragmented animal and plant populations. However, such models have rarely been used to guide systematic decision-making, such as identifying the most important habitat patches and dispersal corridors to protect or restore in order to maximize regional connectivity. Combining resistance models with network theory offers one means of prioritizing management for connectivity, and we applied this approach to a metapopulation of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave Desert of the southwestern United States. We used a genetic-based landscape resistance model to construct network models of genetic connectivity (potential for gene flow) and demographic connectivity (potential for colonization of empty habitat patches), which may differ because of sex-biased dispersal in bighorn sheep. We identified high-priority habitat patches and corridors and found that the type of connectivity and the network metric used to quantify connectivity had substantial effects on prioritization results, although some features ranked highly across all combinations. Rankings were also sensitive to our empirically-derived estimates of maximum effective dispersal distance, highlighting the importance of this often-ignored parameter. Patch-based analogs of our network metrics predicted both neutral and mitochondrial genetic diversity of 25 populations within the study area. This study demonstrates that network theory can enhance the utility of landscape resistance models as tools for conservation, but it is critical to consider the implications of sex-biased dispersal, the biological relevance of network metrics, and the uncertainty associated with dispersal range and behavior when using this approach.Keywords: Landscape resistance, Dispersal, Habitat patch, Graph theory, Fragmented population, Connectivity, Gene flow, Extinction, Colonizatio

CreechPredictingDietQualityAppendixA.pdf

Diet quality influences ungulate population dynamics but is difficult to measure at fine temporal or spatial resolution using field-intensive methods such as fecal nitrogen (FN). Increasingly, the remotely sensed vegetation index NDVI is used to represent potential ungulate diet quality, but NDVI's relationship with diet quality has yet to be examined for herbivores in desert environments. We evaluated how strongly NDVI was associated with diet quality of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave Desert using FN data from multiple years and populations. We considered effects of temporal resolution, geographic variability, and NDVI spatial summary statistic on the NDVI-diet quality relationship. NDVI was more reliably associated with diet quality over the entire growing season than with instantaneous diet quality for a population. NDVI was also positively associated with population genetic diversity, a proxy for long-term, population-level effects of diet quality. We conclude that NDVI is a useful diet quality indicator for Mojave Desert bighorn sheep and potentially other desert ungulates. However, it may not reliably track diet quality if NDVI data are too spatially coarse to detect microhabitats providing high-quality forage, or if diet is strongly influenced by forage items that are weakly correlated with landscape greenness.Keywords: Bighorn sheep, Mojave Desert, Fecal nitrogen, ForageKeywords: Bighorn sheep, Mojave Desert, Fecal nitrogen, Forag

Effects of GonaCon Immunocontraceptive Vaccine in Free-Ranging Female Rocky Mountain elk (\u3ci\u3eCervus elaphus nelsoni\u3c/i\u3e)

Duration of efficacy and prevalence of side-effects associated with GonaCon Immunocontraceptive Vaccine (GonaCon) in free-ranging female elk (Cervus elaphus) are unknown. In January 2008, we captured 120 mature female elk in Rocky Mountain National Park (CO, USA), determined pregnancy status, and randomly assigned them to treated (n=60; 1.5 mL of GonaCon) or control (n=60; 1.5 mL of saline) groups. During the following 3 winters we recaptured, collected blood for antibody concentrations, and euthanized 10–20 elk in each group. At necropsy, we determined pregnancy and collected tissues from organs associated with the hypothalamic–pituitary–gonadal axis. We relocated injection sites, collected muscle tissue, and performed bacterial culture when inflammation was present. Proportion of pregnant elk among control females ranged from 0.75 to 0.90. Proportion pregnant after treatment with GonaCon was 0.00 (95% CI=0.0–0.22) in year 1, 0.31 (CI=0.09–0.61) in year 2, and 0.65 (CI=0.41–0.85) in year 3. Antibody concentrations were higher in non-pregnant than pregnant treated females. We found no antemortem evidence of lameness or swelling at the injection site; however, at necropsy all treated females had pyogranulomatous inflammation at the injection site. We observed no consistent changes within the hypothalamic–pituitary–gonadal axis. We conclude that GonaCon is effective at reducing pregnancy for 1–2 years post-vaccination and is strongly associated with sterile inflammation at the site of injection. Similar to other species, the vaccine is less effective in elk under free-ranging conditions than those in a captive environment

The Effect and Relative Importance of Neutral Genetic Diversity for Predicting Parasitism Varies across Parasite Taxa

<div><p>Understanding factors that determine heterogeneity in levels of parasitism across individuals is a major challenge in disease ecology. It is known that genetic makeup plays an important role in infection likelihood, but the mechanism remains unclear as does its relative importance when compared to other factors. We analyzed relationships between genetic diversity and macroparasites in outbred, free-ranging populations of raccoons (<em>Procyon lotor</em>). We measured heterozygosity at 14 microsatellite loci and modeled the effects of both multi-locus and single-locus heterozygosity on parasitism using an information theoretic approach and including non-genetic factors that are known to influence the likelihood of parasitism. The association of genetic diversity and parasitism, as well as the relative importance of genetic diversity, differed by parasitic group. Endoparasite species richness was better predicted by a model that included genetic diversity, with the more heterozygous hosts harboring fewer endoparasite species. Genetic diversity was also important in predicting abundance of replete ticks (<em>Dermacentor variabilis</em>). This association fit a curvilinear trend, with hosts that had either high or low levels of heterozygosity harboring fewer parasites than those with intermediate levels. In contrast, genetic diversity was not important in predicting abundance of non-replete ticks and lice (<em>Trichodectes octomaculatus</em>). No strong single-locus effects were observed for either endoparasites or replete ticks. Our results suggest that in outbred populations multi-locus diversity might be important for coping with parasitism. The differences in the relationships between heterozygosity and parasitism for the different parasites suggest that the role of genetic diversity varies with parasite-mediated selective pressures.</p> </div

Prion Amplification and Hierarchical Bayesian Modeling Refine Detection of Prion Infection

Prions are unique infectious agents that replicate without a genome and cause neurodegenerative diseases that include chronic wasting disease (CWD) of cervids. Immunohistochemistry (IHC) is currently considered the gold standard for diagnosis of a prion infection but may be insensitive to early or sub-clinical CWD that are important to understanding CWD transmission and ecology. We assessed the potential of serial protein misfolding cyclic amplification (sPMCA) to improve detection of CWD prior to the onset of clinical signs. We analyzed tissue samples from free-ranging Rocky Mountain elk (Cervus elaphus nelsoni) and used hierarchical Bayesian analysis to estimate the specificity and sensitivity of IHC and sPMCA conditional on simultaneously estimated disease states. Sensitivity estimates were higher for sPMCA (99.51%, credible interval (CI) 97.15–100%) than IHC of obex (brain stem, 76.56%, CI 57.00–91.46%) or retropharyngeal lymph node (90.06%, CI 74.13–98.70%) tissues, or both (98.99%, CI 90.01–100%). Our hierarchical Bayesian model predicts the prevalence of prion infection in this elk population to be 18.90% (CI 15.50–32.72%), compared to previous estimates of 12.90%. Our data reveal a previously unidentified sub-clinical prion-positive portion of the elk population that could represent silent carriers capable of significantly impacting CWD ecology

Ranking of models estimating abundance of (a) replete and (b) non-replete ticks (n = 259) and (c) lice (n = 307) in raccoons, including non-genetic and genetic terms.

<p>Analyses were conducted separately for each species and category within species. Models included represent the 90% confidence set (∑weight >0.90) used to calculate the model averages. k = number of model parameters, <i>W</i>_i =Akaikés weight, Δ_i = evidence ratio, log (l) = log-likelihood value.</p

Relationship between multi-locus genetic diversity (internal relatedness, IR) and individual parasite load.

<p>A- replete tick abundance; B- non-replete tick abundance; C- lice abundance and D- endoparasite richness.</p

Effect sizes of single-locus for endoparasite richness and replete-ticks abundance.

<p>Effect sizes were calculated for each of the 14 microsatellite loci. Each effect size includes 95% Confidence Interval. Open circles represent the effect size for endoparasite richness and closed circles for replete tick abundance.</p