Golden-winged Warbler habitat model validation for northern Wisconsin and central Minnesota

Between 1966 and 2003, the Golden-winged Warbler (Vermivora chrysoptera) experienced declines of 3.4% per year in large parts of the breeding range and has been identified by Partners in Flight as one of 28 land birds requiring expedient action to prevent its continued decline. It is currently being considered for listing under the Endangered Species Act. A major step in advancing our understanding of the status and habitat preferences of Golden-winged Warbler populations in the Upper Midwest was initiated by the publication of new predictive spatially explicit Golden-winged Warbler habitat models for the northern Midwest. Here, I use original data on observed Golden-winged Warbler abundances in Wisconsin and Minnesota to compare two population models: the hierarchical spatial count (HSC) model with the Habitat Suitability Index (HSI) model. I assessed how well the field data compared to the model predictions and found that within Wisconsin, the HSC model performed slightly better than the HSI model whereas both models performed relatively equally in Minnesota. For the HSC model, I found a 10% error of commission in Wisconsin and a 24.2% error of commission for Minnesota. Similarly, the HSI model has a 23% error of commission in Minnesota; in Wisconsin due to limited areas where the HSI model predicted absences, there was incomplete data and I was unable to determine the error of commission for the HSI model. These are sites where the model predicted presences and the Golden-winged Warbler did not occur. To compare predicted abundance from the two models, a 3x3 contingency table was used. I found that when overlapped, the models do not complement one another in identifying Golden-winged Warbler presences. To calculate discrepancy between the models, the error of commission shows that the HSI model has only a 6.8% chance of correctly classifying absences in the HSC model. The HSC model has only 3.3% chance of correctly classifying absences in the HSI model. These findings highlight the importance of grasses for nesting, shrubs used for cover and foraging, and trees for song perches and foraging as key habitat characteristics for breeding territory occupancy by singing males.

Treatment of osteoporosis in a mouse model of Duchenne muscular dystrophy using black bear parathyroid hormone

Duchenne muscular dystrophy (DMD) is a progressive disease affecting skeletal and cardiac muscle, as well as bone. Long term disuse and glucocorticoid treatments cause progressive osteoporosis in DMD patients, leading to an increase in fracture incidence. Treatments for osteoporosis in these patients have not been widely explored. Parathyroid hormone (PTH), an anabolic treatment for post-menopausal osteoporosis, could benefit DMD patients by improving skeletal properties and reducing fracture risk. Other PTH analogues are not currently FDA approved to treat osteoporosis, but may have improved osteogenic effects compared to the human analogue. Black bear PTH is especially promising as an osteoporosis treatment for the DMD population. Black bears are unique models of bone maintenance during disuse, since during six months of inactivity (hibernation), they maintain skeletal properties, unlike other hibernators. Additionally, black bear PTH has been correlated to bone formation markers during hibernation, indicating it may be, at least in part, the mechanism by which bears maintain bone during disuse. Employing black bear PTH as a treatment for osteoporosis in DMD patients could greatly improve quality of life for these individuals, and reduce the pain and expense associated with frequent fractures.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

DEVELOPMENT OF A 2-DIMENSIONAL FINITE VOLUME MODEL TO ASSESS HYDRODYNAMIC AND MICROBIAL CONTROLS ON DNAPL DISSOLUTION AND DETOXIFICATION

Tetrachloroethene (PCE) and trichloroethene (TCE) form dense non-aqueous phase liquids (DNAPLs), which are persistent groundwater contaminants. DNAPL dissolution can be "bioenhanced" via dissolved contaminant biodegradation at the DNAPL-water interface. This research hypothesized that: (1) competitive interactions between different dehalorespiring strains can significantly impact the bioenhancement effect, and extent of PCE dechlorination; and (2) hydrodynamics will affect the outcome of competition and the potential for bioenhancement and detoxification. A two-dimensional coupled flowtransport model was developed, with a DNAPL pool source and multiple microbial species. In the scenario presented, Dehalococcoides mccartyi 195 competes with Desulfuromonas michiganensis for the electron acceptors PCE and TCE. Simulations under biostimulation and low velocity (vx) conditions suggest that the bioenhancement with Dsm. michiganensis alone was modestly increased by Dhc. mccartyi 195. However, the presence of Dhc. mccartyi 195 enhanced the extent of PCE transformation. Hydrodynamic conditions impacted the results by changing the dominant population under low and high vx conditions.