Thesis (Ph. D.)--University of Wisconsin--Madison, 1969. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Doctor of Philosophy / Department of Biology / Brett K. Sandercock / Greater prairie-chicken (Tympanuchus cupido) populations have been reduced by >70% since the turn of the 20th century due to large-scale conversion of native prairie habitats to cultivated agriculture and other human development. Although Kansas is considered a stronghold for greater prairie-chickens, statewide populations have declined >30% in the last 30 years. Goals of this dissertation were to determine the demographic mechanisms for apparent population declines and evaluate how regional variations in landscape composition and grassland management affect the demography, habitat use, life-history, and population viability of three populations of greater prairie-chickens. First, I found that, despite high reproductive potential, poor reproductive success prevented populations from being self-sustaining. All three populations were projected to decline but finite rates of population declines were different among populations (λ = 0.49, 0.54, and 0.74). I found that grassland fragmentation and rangeland management practices influence nearly every aspect of greater prairie-chicken population ecology and dynamics. A population in a contiguous prairie landscape managed with annual spring burning and intensive early stocking of cattle (South) was characterized by delayed breeding, low nest and brood survival (0.08–0.18 and 0.27, respectively), high annual survival of mature females (0.64–0.71), projected age-ratios heavily skewed toward adults, and longer generation times. Conversely, a population in grasslands heavily fragmented by cultivation and managed with longer fire-return intervals and moderate grazing (Smoky) initiated nests earlier, had higher nest and brood survival rates (0.16–0.31 and 0.34, respectively), produced significantly larger eggs, and had low annual survival (0.34–0.42) and shorter generation times. A site with intermediate levels of fragmentation, burning and grazing (North) had intermediate demography. Finite population change was more sensitive to changes in adult survival at all sites, but the relative influence of fecundity parameters on projected population change was not similar among study populations. Data indicate that differences in rates of decline among populations were largely due to variation in adult survival mediated by human landscape alteration. Human-mediated changes to grasslands impact the demography and viability of prairie-chicken populations, influence population sensitivities to changes in vital rates, and mediate changes in the life-history strategies of a grassland-sensitive species.

Thesis (Ph.D.)--Tufts University, 2005. / Adviser: J. Michael Reed. Submitted to the Dept. of Biology. Includes bibliographical references (leaves 126-135). Access restricted to members of the Tufts University community. Also available via the World Wide Web;

Thesis (M.S.)--Wildlife and Fisheries Sciences Dept., South Dakota State University, 2009. / Includes bibliographical references (leaves 74-85). Also available via the World Wide Web.

<p>Greater prairie-chickens (<i>Tympanuchus cupido pinnatus</i>; GPC) have declined throughout large areas in the eastern portion of their range. I used species distribution modeling to predict most appropriate areas of translocation of GPC in and around Kankakee Sands, a tallgrass prairie in northwest Indiana, USA. I used MaxEnt for modelling the predictions based on relevant environmental predictors along with occurrence points of 54 known lek sites. I created four models inspired by Hovick et al. (2015): Universal, Environmental, Anthropogenic-Landcover, and Anthropogenic-MODIS. The Universal, Environmental, and Anthropogenic-MODIS models possessed passable AUC scores with low omission error rates. However, only the Universal model performed better than the null model according to binomial testing. I created maps of all models with passing AUC scores along with an overlay map displaying the highest predictions across all passing models. MaxEnt predicted high relative likelihoods of occurrence for the entirety of Kankakee Sands and many areas in the nearby landscape, including the surrounding agricultural matrix. With implementation of some management suggestions and potential cooperation with local farmers, GPC translocation to the area appears plausible.</p> <p>Franklin’s ground squirrels (<i>Poliocitellus franklinii</i>; FGS) have declined throughout a large portion of the eastern periphery of their range. Because of this, The Nature Conservancy is interested in establishing a new population of these animals via translocation. The area of interest is tallgrass prairie in northwest Indiana, USA: Kankakee Sands and the surrounding landscape. Species distribution modelling can help identify areas that are suitable for translocation. I used MaxEnt, relevant environmental variables, and 44 known occurrence points to model the potential for translocation of FGS to Kankakee Sands and the surrounding area. I created four models inspired by Hovick et al. (2015): Universal, Environmental, Anthropogenic-Landcover, and Anthropogenic-MODIS. I created maps of models with passing AUC scores. The final map was an overlay map displaying the highest relative likelihood of occurrence predictions for the area in all passing models. Only the Universal and Anthropogenic-MODIS models had passable AUC scores. Both had acceptable omission error rates. However, none of the models performed better than the null model (p < 0.05). MaxEnt predicted that a few areas in and outside of Kankakee Sands possess high relative likelihoods of occurrence of FGS in both the Universal and Anthropogenic-MODIS models. However, MaxEnt predicted high relative likelihoods in the surrounding agricultural matrix in the Universal Model. FGS prefer to cross through agricultural areas via unmowed roadside instead of open fields (Duggan et al. 2011). Because of this, high predictions in agricultural matrices in the Universal model are irrelevant. High relative likelihood predictions for linear sections that are obviously roads are disregardable in the context of my modeling efforts. Because of my low sample size, none of the models are really reliable in predicting relative likelihoods of occurrence for this area. Despite high relative likelihood predictions, the appropriateness of a translocation effort to the area is inconclusive.</p>