Ph.D., Antioch University, 2019, Antioch New England: Environmental Studies

Over the past two centuries, large terrestrial carnivores have suffered extreme population declines and range contractions resulting from the synergistic anthropogenic threats of land-use change and indirect effects of climate change. In Panama, rapid land use conversion coupled with climate change is predicted to negatively impact jaguar (Panthera onca) and puma (Puma concolor). This dissertation examined the environmental variables and scales influencing jaguar and puma habitat selection by season (annual, wet, and dry), using multi-scale optimized habitat suitability models and a machine-learning algorithm (Random Forests), in the narrowest section of Panama. The models derived from the data of an intensive camera trapping effort (2016–2018) captured a wide spectrum of ecological relationships for the sympatric felid species. Jaguar habitat selection was limited by secondary forest at a broad scale (home range), suggesting that jaguars preferred primary forest. Therefore, the persistence of primary forest in the narrowest section of the country is key for the long-term survival of the species. Pumas incorporated primary forest at a fine scale (patch) and agropecuary (agriculture and livestock) at broad scales (home range), providing evidence of the plasticity and adaptability of the species to a diverse range of landscapes. Seasonal differences in habitat suitability were evident for both species which is most likely related to prey availability. The models also provided a set of seasonal habitat suitability maps (annual, wet season and dry season) from which spatial information on jaguar and puma distribution are presented. This study improves our understanding of species-environment relationships and habitat selection of jaguars and pumas in eastern Panama, and contributes to the growing number of studies that demonstrate the strong conceptual and inferential advantages of a multi-scale approach. Further, I examined the implications of the potential relocation (open full item for complete abstract)

Committee: Beth Kaplin Ph.D. (Committee Chair); Peter Palmiotto D.F. (Committee Member); Marcella Kelly Ph.D. (Committee Member) Subjects: Conservation; Ecology; Wildlife Conservation

PhD, University of Cincinnati, 2017, Arts and Sciences: Geography

The Earth stands on the precipice of the sixth mass extinction. This extinction risk has triggered a growing crisis and urgent need to save the world's biodiversity. Considering the accelerated rates of biodiversity loss and extinction, we need simple but efficient methods to quickly identify threatened areas. This dissertation research was undertaken with this in mind—to benefit the conservation community, either through the delivery of biogeographic methods or information to further the restoration or maintenance of biodiversity. As a primary goal, this dissertation endeavored to fill those research gaps and offer some simpler and more effective useful and usable geospatial techniques for biodiversity conservation analyses. Secondary goals of the research were (1) to contribute to specific conservation programs for critically endangered species, (2) to inform about the status of habitat, and (3) to address top conservation research priorities. While not a specific objective, the research outcomes may influence public policy. This three-article dissertation introduces two novel techniques: (1) development of a habitat suitability model in ArcGIS using kernel density estimation and a mortality-risk weighting factor on road density, the delimiting variable; and (2) a rapid hybrid change detection technique using ENVI's SPEAR Vegetation Delineation tool or classifying live green vegetation and ArcGIS to compare and quantify changes in time. For the latter, two studies incorporated the change detection technique. The pilot study performed the change detection with color-infrared aerial photography, while the follow-up investigation tested the feasibility of the method to handle high resolution multi-sensor data, given the difficulty obtaining data from the same or similar sensors. These studies represent the first of their kind. This dissertation research provides widely applicable, practical, and employable geospatial models to perform habitat assessment (open full item for complete abstract)

Committee: Tak Yung Tong Ph.D. (Committee Chair); Richard Beck Ph.D. (Committee Member); Theresa Culley Ph.D. (Committee Member); Nicholas Dunning Ph.D. (Committee Member); Hongxing Liu Ph.D. (Committee Member) Subjects: Geography

Doctor of Philosophy, Miami University, 2009, Zoology

Habitat loss and alteration is a major cause of population declines; thus, habitat conservation is essential for preventing species extinctions. Habitat conservation, however, can be hindered by an inadequate understanding of species' habitat requirements. Pond-breeding amphibians have a biphasic life history, which requires both aquatic and terrestrial habitats; thus, pond-breeding amphibians are particularly vulnerable to habitat alteration because they experience its effects in multiple habitats during successive life stages. The goal of this dissertation was to examine the importance of habitat structure (i.e., vegetation structure, canopy cover) for larval and juvenile pond-breeding amphibians. In the first and second chapters, I assessed how aquatic vegetation structure mediates biotic interactions (competition and predation) for larval amphibians. In the second, third, and fourth chapters, I established that aquatic and terrestrial canopy cover can strongly influence growth and survival of amphibian larvae, as well as locomotor performance, growth, and survival of terrestrial juveniles. Taken together, the findings of my research suggest that, although habitat structure influences growth and survival of larvae, some pond-breeding amphibians appear to be more sensitive to the suitability of their terrestrial habitat; thus, successful conservation of pond-breeding amphibians must involve the preservation of high-quality (i.e., closed canopy) terrestrial habitat and the maintenance of corridors that facilitate juvenile dispersal from natal wetlands to suitable terrestrial habitat.

Committee: Michelle Boone PhD (Advisor); Thomas Crist PhD (Committee Member); Maria Gonzalez PhD (Committee Member); Ann Rypstra PhD (Committee Member); Robert Noble PhD (Committee Member) Subjects: Animals; Behaviorial Sciences; Biology; Ecology; Freshwater Ecology; Zoology

Master of Science, University of Toledo, 2021, Biology (Ecology)

The Sandusky River, Ohio, is one of the major tributaries of Lake Erie that supports walleye (Sander vitreus) reproduction. The goal of this study was to assess spawning habitat in the Sandusky River following the removal of the Ballville Dam and to determine if walleye can access habitat that was previously unavailable by migrating past a series of ice control structures. To determine the quantity of spawning habitat, a Habitat Suitability Index was calculated from the mouth of the river in Muddy Creek Bay to the first low-head dam in Tiffin, Ohio. A fine scale model was created that encompassed the ice control structures area and swim speed comparisons were done to determine if the area was passable. This study shows that there is suitable spawning habitat for walleye upstream and downstream of the former Ballville Dam, and that walleye can migrate passed the ice control structure area during certain conditions.

Committee: Jonathan Bossenbroek (Advisor); J. Brian Alford (Committee Member); Kennedy Doro (Committee Member) Subjects: Biology; Ecology; Freshwater Ecology

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2020, Biological Sciences

Many taxa suffer from habitat loss, spread of invasive species, and climate change; however, reptiles are especially vulnerable because they are constrained physiologically from their ectothermic nature in addition to global population declines. Like other taxa, reptilian basic ecology requirements are influenced by ecological neighborhoods, which shape the abundance of critical resources and their movement patterns. My goal was to better understand reptilian movement patterns across spatial and temporal scales to facilitate conservation efforts within Oak Openings Region (OOR), of northwestern Ohio and southeastern Michigan, using a combination of field surveys, remote sensing data and modeling. My research examined (1) climate change, (2) distribution patterns, (3) habitat use, and (4) movement patterns. At the regional scale, we found moderate increases in suitable habitat for box turtles within the future scenarios based on climatic suitability models. Individuals may be more displaced or vulnerable from temperature change during the driest quarter of the year. Dispersal is feasible; box turtles, based on tracking of individuals, can move large distances within their lifetime but the physical barriers, like roads, on the landscape may greatly hinder these movements. I modeled habitat suitability for a suite of reptiles based on occupancy data and climate, habitat, elevation, and structural features. Currently, suitable habitat was less than half the area within OOR and was more restricted for two species of concern. There is a need to examine the range of limitations, i.e., minimum and maximum models, when planning conservation efforts for a suite of species, especially emphasizing the protection of wet and dry forest. At the local scale, I found using radio telemetry that box turtles displayed typical average home range sizes; however, some were much larger than other studies. This is likely a difference in landscape heterogeneity where home range size increase (open full item for complete abstract)

Committee: Karen Root PhD (Advisor); Michael Decker PhD (Other); Kevin McCluney PhD (Committee Member); Helen Michaels PhD (Committee Member); Enrique Gomezdelcampo PhD (Committee Member) Subjects: Biology; Conservation; Ecology

Ph.D., Antioch University, 2019, Antioch New England: Environmental Studies

Golden Eagles (Aquila chrysaetos) have a broad range globally and in general are well-studied. However, Arizona's Golden Eagle population remained essentially unstudied until 2011, when Arizona Game and Fish Department (AZGFD) began nest surveys for cliff nesting Golden Eagles throughout the state. As a result of this data collection, the natural history of Arizona's Golden Eagles is finally revealing itself. This dissertation outlined a reliable description of their nesting phenology that provides a framework for timing surveys and a baseline to monitor the effects of climate change on Golden Eagles. The mean date for egg-laying was February 14 and pairs nesting in the high desert initiate nesting about ten days later than their southern counterparts. A brief study collecting prey remains determined that Black-tailed Jack Rabbit (Lepus californicus) was the central prey species for Golden Eagles in northern Arizona. The results of a multiscale habitat suitability model (HSM) determined that slope between 18º-28º was the most important habitat characteristics for Golden Eagles and the sagebrush landcover was the least important. The multiscale productivity prediction model did not predict with high accuracy; however, the results did reveal some data gaps and provided guidance for adjustments in the future. The results of this entire dissertation can guide future research priorities for Golden Eagles in Arizona. For example, more research on Golden Eagle prey dynamics is needed to determine the impact prey have on their nesting success. Additional research should focus on adding human impact factors such as recreational activity or elemental mining as possible factors that negatively influence nesting productivity. Finally, quantifying climate features on a finer temporal scale should be considered and continued nest site data collection will increase the sample size for more informative results.

Committee: Peter Palmiotto DF (Committee Chair); Lisabeth Willey PhD (Committee Member); Todd Katzner PhD (Committee Member); Tyler Coleman PhD (Committee Member) Subjects: Animals; Biology; Conservation; Ecology; Environmental Management; Wildlife Conservation; Wildlife Management

Doctor of Philosophy, University of Toledo, 2018, Biology (Ecology)

Biodiversity and ecological function are increasingly threatened by human impacts including fragmented systems, modified water and sediment flow, pollution, habitat degradation and alteration, overexploitation of species, and invasive species introduction. These impacts necessitate the need for conservation and restoration practices to protect natural resources and biodiversity. This dissertation outlines the development and implementation of habitat suitability index (HSI) models as tools to support species reintroduction efforts and monitor populations of imperiled species. Lake sturgeon (Acipenser fulvescens), a state listed species in Ohio, are a candidate for reintroduction in the Maumee River, Ohio, where they were historically abundant, but are now functionally extirpated. The goal of my dissertation was to determine if current habitat quantity and quality in the Maumee River are sufficient to support lake sturgeon reintroduction using habitat suitability index models for two important life stages: spawning adult and age-0 fish. The models I developed, using substrate, water velocity, and water depth, indicated that habitat quality, quantity, and connectivity for both spawning adult and age-0 lake sturgeon would support efforts to reintroduce this species. The results of these HSI models were used in the development of a reintroduction plan to summarize important elements for successful reintroduction efforts. The reintroduction plan provided a comprehensive outline incorporating biological, managerial, and societal perspectives, to identify potential barriers to lake sturgeon reintroduction and highlight direct actions to increase success. HSI models are valuable tools for reinforcing species restoration plans and improve conservation monitoring. After the development of the lake sturgeon HSI models for the Maumee River, I wanted to further investigate if the model structure and habitat data could be utilized for other species in the Maumee River. I tested m (open full item for complete abstract)

Committee: Jonathan Bossenbroek PhD (Committee Chair); Christine Mayer PhD (Committee Member); Daryl Moorhead PhD (Committee Member); Todd Crail PhD (Committee Member); Christopher Vandergoot PhD (Committee Member) Subjects: Conservation; Freshwater Ecology

Master of Environmental Science, Miami University, 2016, Environmental Sciences

A species distribution model (SDM) was developed to predict the presence and suitable habitat of the federally threatened plant, Euphorbia telephioides, in northwest Florida using data acquired from the U.S. Fish & Wildlife Service. I used two machine-learning models, MaxEnt and boosted regression trees (BRTs), as previous research has shown them to yield high predictability, especially with presence-only data and different types of predictor variables. Different methods were used to reduce effects of spatial autocorrelation and sampling bias in the model predictions since E. telephioides populations are strictly located along the coast. The 29 predictor variables were a combination of categorical, continuous, and distance-based variables. Both the MaxEnt and BRT models had high accuracy as measured by area under the curve (AUC), sensitivity, specificity, and true skill statistic (TSS), but the BRTs had a much lower deviance. The BRT models were also validated with the discovery of a new population in an area predicted as high probability of occurrence. This study demonstrates that machine-learning SDMs can be used by conservation organizations as cost-effective tools to find and protect new populations of threatened or endangered species.

Committee: Mary Henry (Advisor); David Gorchov (Committee Member); Thomas Crist (Committee Member) Subjects: Conservation; Environmental Science; Geographic Information Science; Statistics

MA, University of Cincinnati, 2009, Arts and Sciences : Geography

The red wolf (Canis rufus) is a keystone species because of its important ecological role as a top predator. Its restoration to historic ranges may help to promote ecosystem integrity, balance, diversity and health. However, as already outlined in the 2007 United States Fish and Wildlife Service Red Wolf Recovery Progress Report, at least two additional reintroduction sites within the species' historic ranges are still required to support viable populations of red wolves. This thesis research aimed to contribute to the Red Wolf Species Survival Plan by identifying and evaluating potential sites within the Daniel Boone National Forest in eastern Kentucky for the reestablishment of red wolves. In previous wolf habitat prediction models, road density served as the criteria for suitability. Researchers calculated simple road densities; however, the logistic regression models thus derived did not accurately predict wolf occupation. Roads with higher traffic volumes and areas with greater road densities should, in theory, pose greater risks to wolf mortality, and simple road density may not be an adequate measure to such purpose. This research, therefore, ranked roads by mortality risk and utilized kernel density estimation in Geographic Information Systems as a means to weight the road density and to predict suitable wolf habitat. This method may provide a better picture of the spatial reality of road influence. By using the red wolf habitat suitability model based on the rank class and kernel density estimation, nine potential restoration sites were predicted; whereas the suitability model based only on the simple density function failed to predict any sites. However, the results of this research are not final. The human and coyote factors remain unknown, and validation of the model is impractical due to the lack of data and time constraints. Yet, efforts such as field verification have been made in an attempt to validate the model. If data are available, follow-up (open full item for complete abstract)

Committee: Susanna Tong PhD (Committee Chair); Changjoo Kim PhD (Committee Member); Stephen Matter PhD (Committee Member) Subjects: Animals; Ecology; Environmental Science; Geography

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2012, Biological Sciences

Oak savannas of the Midwestern U.S. are among the most imperiled North American plant communities. The 478-km2 Oak Openings region of Northwestern Ohio is one of the few landscape-scale savanna systems remaining in the Midwest. Despite conversion of large portions of the Oak Openings for human land uses, the region still supports high levels of floristic diversity. However, regional patterns of Oak Openings plant diversity within the modern landscape are not well understood. My research objectives were 1) to determine the current extent and distribution of Oak Openings plant communities, 2) to quantify multiscale patterns of plant species richness within the context of the surrounding landscape, and 3) to build predictive species distribution models of rare plants to evaluate regional patterns in habitat suitability. First, using multi-seasonal Landsat images, I determined that <3% of the Oak Openings remains covered by native savannas, prairies, and barrens, while three-fourths of the region has been converted for urban, residential, and agricultural uses. Second, using measures of spatial heterogeneity derived from field data and remote sensing, I developed models of native and exotic plant species richness at two spatial extents and at four ecological levels for the Oak Openings. These models consistently explained more variation in exotic richness (better explained at the larger spatial extent) than in native richness (better explained at the smaller spatial extent). At all ecological levels, percentage of human-modified land cover in the surrounding landscape (negatively correlated with native richness, positively correlated with exotic richness) was a strong predictor of species richness. Finally, I developed species distribution models for nine rare plant species within the Oak Openings region using the Maxent modeling algorithm. Proportional land cover surrounding species occurrences accounted for a large proportion of the predictive power of all models. As (open full item for complete abstract)

Committee: Karen V. Root PhD (Advisor); Enrique Gomezdelcampo PhD (Committee Member); Helen J. Michaels PhD (Committee Member); Jeffery G. Miner PhD (Committee Member); Robert K. Vincent PhD (Committee Member) Subjects: Biology; Ecology; Natural Resource Management