Barred owls recently expanded their range and now completely overlap that of the northern spotted owl. Current declines in northern spotted owl populations are largely attributable to this sympatry with barred owls. Lethal removal of barred owls is being considered and tested as a method of managing the negative impacts on spotted owls. The size and distribution of removal areas may influence the efficacy and efficiency with which an area can be maintained free of barred owls. I created an individual-based spatially-explicit population model to compare alternative spatial strategies for removing barred owls in a localized area. Large, continuous removal areas maintain lower barred owl occupancy and require fewer owls to be removed than smaller fragmented removal areas for a given level of removal effort. The model is most sensitive to adult and subadult survival as well as reproduction and the range over which an owl can detect a potential mate, of which the latter two parameters do not have empirical field estimates. This model could be adapted to answer further questions regarding barred owl removal and also incorporate geographic information system data to evaluate removal strategies on real-world properties.

Sea level rise is predicted to have a negative effect on shorebird populations living in coastal environments. At Humboldt Bay, the availability of tidal flats that serve as habitat to many shorebirds throughout the year may become increasingly limited as higher sea levels permanently inundate lower elevation tidal flats. The Long-billed Curlew (Numenius americanus) is amongst the shorebird species at Humboldt Bay that may face reductions in population as feeding habitat becomes less available. I estimate how curlews will react to habitat change by developing a model that simulates the dynamics between the curlews, their prey, and their environment at Humboldt Bay. To understand how curlews are affected by habitat change due to sea level rise, I introduce predicted changes in habitat to the model. To predict how the habitat changes, I use the Sea Level Affecting Marshes Model, SLAMM, to estimate how different extents of sea level rise change intertidal habitat area. Based on the observed local sea level rise at Humboldt County, SLAMM predicts that mean sea level will increase 0.2-0.9 m over the next hundred years. This corresponds to a loss of 17-64% of current intertidal habitat area. Less dominant curlews are predicted to be strongly affected by the changes in the habitat and will have significant decreases in foraging time, overall weight, and overwinter success. In contrast, higher dominant curlews are more resistant to changes in the habitat and will be less affected by moderate changes in habitat. Given the maximum sea level rise scenario, overwinter success of higher dominant curlews may drop to 50% of the present value. In the same conditions, only 5% of low dominance curlews are expected to be successful. The model predicts that the maximum carrying capacity of Humboldt Bay will stay above 90% given moderate increases in sea level, while maximum carrying capacity will drop below 40% given the maximum sea level rise scenario. The loss of intertidal habitat at Humboldt Bay will not only affect the Long-billed Curlew population, but will also limit other shorebird species. Modeling the effects of habitat change on Long-billed Curlew is a first step in understanding how shorebirds will respond to sea level rise. My methods can be extended to other shorebird species in the future to predict how overall abundance and diversity at Humboldt Bay will change in response to sea level rise.

The African wild dog (Lycaon pictus) is facing a high risk of extinction with fewer than 5,000 individuals living in fragmented landscapes. After an absence of nearly 50 years, several sub-populations of wild dogs have been reintroduced into isolated, fenced game reserves in the province of KwaZulu-Natal (KZN), South Africa. To better understand the effect of natural dispersal on the African wild dog population in KZN, we developed a spatially explicit individual-based model employing the software NetLogo. Wild dogs reintroduced into Phinda Munyawan Conservancy, Greater St. Lucia Wetland Park and Zululand Rhino Reserve had the greatest dispersal success while wild dogs reintroduced into Ithala Game Reserve, Ndumo Game Reserve and Tembe Elephant Park displayed the least successful dispersal and persistence. This information will aid researchers and wildlife managers in determining effective, cost-efficient management plans for the KZN wild dog population and can be further extended to all of South Africa.

The recovery of the endangered Colorado pikeminnow (Ptychocheilus lucius) has been threatened by compounding effects of habitat alteration including water depletion, chemical contamination of water, hydroelectric operations, and the introduction of non-native species. I used an individual-based model to examine the response of juvenile (age-0) pikeminnow to the interacting effects of dam-induced within-day flow fluctuations and the non-native red shiner (Cyprinella lutrensis). The model incorporates a spatially explicit nursery habitat, a temperature model, an invertebrate production model, and a model of fish competition, predation, and bioenergetics. I varied within-day flow fluctuation magnitude (0%, 1%, 5%, 10%, 20%, and 40% around mean baseflow) and red shiner density (0-5 fish/m^2) to evaluate combined stress on pikeminnow survival, defined as the proportion of initial fish surviving and growing to 30 mm or above at the end of a simulation. Simulations showed complex, non-linear results from the combined effects of flow fluctuations and red shiner density. Throughout all model experiments, red shiner density had noticeable impacts on pikeminnow survival. In the absence of red shiners, the magnitude of flow fluctuation had little impact on pikeminnow survival. As red shiner density was increased, however, additional stress from flow fluctuations became highly noticeable. There were physical characteristics of the nursery habitat that often mitigated the combined effect of the two factors, including mean depth and mean temperature. This study suggests that juvenile pikeminnow survival may be elevated by controlling population levels of non-native fish and the utilization of flow regimes that maintain suitable nursery habitat by providing adequate water depth, surface area, and temperature.

The Hawaiian hawksbill sea turtle (Eretmochelys imbricata) is a critically endangered species, with an observed adult female population of approximately 6-20, nesting each year at known nesting sites on the big island of Hawaii. To create efficient management strategies for the survival of the species, a better understanding of habitat selection in the early stages of the hawksbill’s life is needed. We investigate an individual-based, advection-diffusion, larval transport model, as it applies to the Hawaiian hawksbill population in the greater Hawaiian Archipelago. The model considers the release time and location, size, foraging behavior, and geographic location of the hawksbill hatchlings first three years of life, over a six year period of study, and how their habitat selection may be affected by the geostrophic currents, sea surface temperatures, and chlorophyll-a concentrations that they encounter. Results indicate that the inclusion of simple behavior rules significantly (p < 0.01) increases retention, exposure to higher sea surface temperatures, and exposure to higher chlorophyll-a concentrations. Statistical analysis suggests a need to consider all three environmental parameters of the ocean surface currents, sea surface temperature, and chlorophyll-a concentration to better predict the resulting distribution of the individuals.

This thesis addresses a significant problem in modeling aquatic ecosystems by developing methods to use available regional data to produce site-specific input for fish models and minimize field data requirements for modeling. The stream channel synthesis and hydraulic simulation methods include creating habitat type sequences and channel shapes, identifying calibration flows, calibrating HEC-RAS, and producing depth and velocity rating curves for each cell. We then conduct experiments using an individual based model (inStream) to simulate trout populations in virtual stream channels throughout a watershed.

Individual-based models (IBMs) are a relatively new way to perform population modeling of a particular species. In this type of modeling, population level dynamics emerge as the result of actions of individuals, as members of the population make choices regarding habitat due to influence by environmental factors as well as competition from other members of the species. There are very few, if any, sensitivity analyses of individual-based ecological models reported in the literature. This is in part due to the recent advent of this type of modeling, as well as the overall complexity of the models themselves. The intention here is to demonstrate a method of analyzing an IBM so that relevant information is provided to the modeler regarding the strong and weak points of the model in the face of the uncertainty in parameter values, while consuming a minimum of time and computational resources. In addition, this type of information will be useful to resource managers looking to support management decisions, as it will provide indications of how much confidence can be put into model output because the effects of parameter uncertainty on alternative management actions will be included in the ranking with regards to the efficacy of each proposed action. In this fashion, the model will aid resource managers to better understand the risk of making false predictions. An individual-based model, inSTREAM v.4.05 (Railsback et al, 2004), was used to model a population of northern California coastal cutthroat trout in Little Jones Creek, a third order tributary of the Smith River in northern California. In this model, trout make daily habitat selection choices to maximize their fitness. The decision rules that govern these choices are influenced by the daily conditions within the modeled stream, various mortality risks, as well as factors concerning respiration, growth and reproduction. The uncertainty in 90 parameters of the model was analyzed. Effects of parameter uncertainty were investigated in a three-phase process. The first phase ranked the parameters based on a sensitivity index which reflected how much the uncertainty in parameter value affected model output. In the second phase, the relative level of higher-order interactions amongst the parameters with the highest sensitivity index was assessed. The third phase tested the robustness of model output, by varying all of the most sensitive parameters simultaneously, when evaluating proposed alterations to the watershed. The model was found highly sensitive to some parameters, moderately sensitive to most, and not sensitive at all to a few. Although varying two high-sensitivity parameters at a time did generally have a non-linear effect on model output, the model was able to reproduce the same population trends under multiple parameter perturbation as it did when only calibrated parameter settings were used.