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Browsing by Author "White, Gary C., advisor"

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    Bayesian analysis of age-at-harvest data with focus on wildlife monitoring programs
    (Colorado State University. Libraries, 2007) Conn, Paul Bayne, author; White, Gary C., advisor
    State and federal agencies often collect hunter harvest data at check stations. When age- and sex-classes can be determined at the time of harvest, such data provide a wealth of information about population structure. For instance, such summaries are used extensively in quantitative fisheries stock assessment. However, statistically defensible approaches for using age-at-harvest data to monitor terrestrial wildlife populations have not appeared until quite recently, and are deficient in several respects. The primary focus of this dissertation is on developing better methods for analyzing wildlife age-at-harvest data, and on applying these methods to real and hypothetical populations. Chapter one starts by developing statistical methods necessary for fitting population dynamics models to age-at-harvest data. As an example, I analyze marking and harvest records from female black bears (Ursus americanus) in Pennsylvania. In chapter two, I describe numerical implementation issues, as well as results from several extensive rounds of simulation testing. I show that Markov chains will typically need to be quite long to accurately summarize the posterior distribution of model parameters. Nonetheless, estimators are shown to display little bias, to have satisfactory credible interval coverage, and to have a high degree of precision. I show that abundance estimators are quite robust to aging errors, although using data from marked animals twice may lead to overstated measures of precision. In chapter three, I conduct a power analysis to determine if it would be feasible to monitor black bear in Colorado with age-at-harvest and radio telemetry data. My focus in this chapter is on detecting and estimating population trend for varying levels of effort. I show that five year studies are typically too short for all anticipated levels of marking effort, but that ten year studies can yield meaningful estimates of population trend. In chapter four, I address methods that can be used to correct age-at-harvest data for misclassification errors. When the aging criterion is inexact, it is possible to correct for errors if additional information is available on error rates. I illustrate proposed methodology with a black bear dataset from Pennsylvania.
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    Density, demography, and seasonal movement of snowshoe hares in central Colorado
    (Colorado State University. Libraries, 2011) Ivan, Jacob Scott, author; White, Gary C., advisor; Shenk, Tanya M., committee member; Wilson, Kenneth R., committee member; Doherty, Paul F., committee member; Romme, William H., committee member
    To view the abstract, please see the full text of the document.
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    Effect of enhanced nutrition during winter on the Uncompahgre Plateau mule deer population
    (Colorado State University. Libraries, 2007) Bishop, Chad Jeffrey, author; White, Gary C., advisor
    Mule deer (Odocoileus hemionus) populations declined across much of the West during the 1990s, prompting state wildlife agencies to explore mule deer limiting factors. The greatest concern of agencies and sportsmen was whether declining habitat quality, predation, or both were responsible for the observed declines. In Colorado, the Uncompahgre Plateau mule deer population received the most attention because of a steep population decline from the 1980s through the late 1990s. Biologists hypothesized that poor quality of the pinyon (Pirns edulis) and juniper (Juniperus osteosperma) winter range was the primary cause of the observed decline. In contrast, many of the Colorado Division of Wildlife’s (CDOW) constituents hypothesized that high predation rates were keeping the mule deer herd below nutritional carrying capacity. These hypotheses represented very different paradigms of population limitation. Perhaps more importantly, the competing views suggested that CDOW should pursue one of two very different management strategies: 1) implement habitat improvements in the pinyon-juniper winter range, or 2) implement efforts to reduce predator populations, particularly coyote (Canis latrans) populations. Information was needed to guide the decision process. I therefore evaluated the effect of enhanced nutrition during winter on the Uncompahgre deer population as a way to evaluate the importance of habitat quality versus that of predation.
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    Generalized mixed effects models for estimating demographic parameters with mark-resight data
    (Colorado State University. Libraries, 2008) McClintock, Brett Thomas, author; White, Gary C., advisor
    Mark-resight methods constitute a slightly different type of data than found in traditional mark-recapture, but they are in the same spirit of accounting for imperfect detection towards reliably estimating demographic parameters. Compared to mark-recapture, mark-resight can often be a less expensive and less invasive alternative in long-term population monitoring programs. However, the mark-resight estimators developed to date do not provide a flexible framework allowing the efficient use of covariates in modeling the detection process, information-theoretic model selection and multimodel inference, and the joint estimation of abundance and related demographic parameters. Here I develop a series of mark-relight models for the sampling conditions most often encountered in these studies that address this need for a more generalized framework. In Chapter 1, I introduce the the logit-normal mixed effects model (LNE) for estimating abundance when sampling is without replacement and the number of marked individuals in the population is known exactly. I compare the model to other mark-resight abundance estimators when applied to mainland New Zealand robin (Petroica australis) data recently collected in Eglinton Valley. Fiordland National Park. I also summarize its relative performance in simulation experiments. It can often be difficult to achieve sampling without replacement or to know the exact number of harked individuals in a population. In Chapter 2, I address these limitations of LNE by introducing the (zero-truncated) Poisson-log normal mixed effects abundance model, (Z)PNE. I demonstrate the use and advantages of (Z)PNE using black-tailed prairie dog (Cynomys ludovicianus) data recently collected in Colorado. I also investigate the expected relative performance of the model in simulation experiments. In Chapter 3, I extend (Z)PNE to a full-likelihood robust design model analogous to that used in mark-recapture for the simultaneous estimation of abundance, apparent survival, and transition probabilities between observable and unobservable states. I illustrate the use of the model with additional New Zealand robin data collected in Fiordland National Park, New Zealand. I also report on a series of simulation experiments evaluating the performance of the model under a variety of sampling conditions.