Large populations of Silver Carp (Hypophthalmichthys molitrix) and Bighead Carp (H. nobilis), collectively called bigheaded carps, may have significant impacts where they are invasive. In the Lower Mississippi Alluvial Valley (LMAV), bigheaded carps have been documented in major rivers; however, knowledge of their distribution in oxbow lakes is lacking. Species distribution models are tools that can be used to estimate species distribution with presence data and environmental variables. As a cost-effective alternative to onsite sampling, I administered a questionnaire to biologists to inventory bigheaded carp presence and obtained environmental data from existing datasets. I used Maximum Entropy (Maxent) to illustrate predicted bigheaded carp distribution and identify drivers of that distribution. Carp presence was predicted in about 60% of lakes. Small lakes with greater inundation index and shorter distance to a river were predicted most likely to have carp present, and the greatest mean predicted carp presence was in the northwest LMAV.

Accounts of species’ range shifts in response to climate change, most often as latitudinal shifts towards the poles or upslope shifts to higher elevations, are rapidly accumulating. These range shifts are often attributed to species ‘tracking’ their thermal niches as temperatures in their native ranges increase. Our objective was to estimate the degree to which climate change-driven shifts in water temperature may increase the exposure of West Virginia’s native freshwater fishes to mountaintop removal surface coal mining. Mid-century shifts in habitat suitability for nine non-game West Virginia fishes were projected via Maximum Entropy species distribution modeling, using a combination of physical habitat, historical climate conditions, and future climate data. Modeling projections for a high-emissions scenario (Representative Concentration Pathway 8.5) predict that habitat suitability will increase in high elevation streams for eight of nine species, with marginal increases in habitat suitability ranging from 46-418%. We conclude that many West Virginia fishes will be at risk of increased exposure to mountaintop removal surface coal mining if climate change continues at a rapid pace.

This master thesis deals with the potential of GIS to provide a sophisticated model of newt occurence that would allow an evaluation of appropriateness of state driven subsidies granted to build new water tanks. The main purpose was especially to show what parameters that determine presence of newts should be further implemented into the founding documentation of environmental projects aimed to support amphibian populations.

Background: The mosquito Aedes aegypti has long been a vector for human illness in the Southeastern United States. In the past, it has been responsible for outbreaks of dengue, chikungunya, and yellow fever and, very recently, the Zika virus that has been introduced to the region. Multiple studies have modeled the geographic distribution of Ae. aegypti as a function of climate factors; however, this ignores the importance of humans to the anthropophilic biter. Furthermore, Ae. aegypti thrives in areas where humans have created standing water sites, such as water storage containers and trash. As models are developed to examine the potential impact of climate change, it becomes increasingly important to include the most comprehensive set of predictors possible. Results: This study uses Maxent, a species distribution model, to evaluate the effects of adding poverty and population density to climate-only models. Performance was evaluated through model fit statistics, such as AUC, omission, and commission, as well as individual variable contributions and response curves. Models which included both population density and poverty exhibited better predictive power and produced more precise distribution maps. Furthermore, the two human population characteristics accounted for much of the model contribution-more so than climate variables. Conclusions: Modeling mosquito distributions without accounting for their dependence on local human populations may miss factors that are very important to niche realization and subsequent risk of infection for humans. Further research is needed to determine if additional human characteristics should be evaluated for model inclusion.

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Woodpeckers are a group of avian species that cause damage to wooden power utility structures. In the southeastern United States, Tennessee Valley Authority (TVA), has accrued an estimated $5 million USD annually from woodpecker damage. Previous work has focused on effectiveness of reactive mitigation and restoration efforts with little investigation of preventative methods. To address this knowledge gap, this study will i) use species distribution model techniques to predict damage suitability across the TVA service area, ii) use Bayesian hierarchical community model techniques to estimate species richness of the woodpecker community in the service area, and iii) recommend target areas for increased preventative measures in the service area. The suitability map indicated that damage was most likely to occur in the southwestern portions of the TVA service area. Woodpecker species richness was stable across the environmental covariate values estimated with 2-3 species found throughout the service area.

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Species distribution models (SDMs) can be important tools for proactive conservation management if they are realistic. Unfortunately, achieving and assessing SDM realism is challenging given the general limitations of scientific models and empirical species data. We addressed the issue of achieving realism with high model quality and reproducibility by reviewing 200 SDMs and cataloguing methods for data availability, response and predictor variables, model fitting, and model performance. We addressed the issue of assessing SDM realism by comparing known and predicted distributions of habitat suitability with simulated data for various model fitting choices. Finally, we applied and compared subsequent lessons to empirical, ensemble SDMs for the exotic ball python (Python regius) and invasive Argentine black and white tegu (Salvator merianae) as case studies for Florida mitigation management practices. Fundamental SDM standards were addressed inconsistently in the literature and lacked transparency and replicability. This decreases SDM quality and increases method confusion. We provided a new checklist with well-supported guidelines to aid in greater method consistency (thus quality and reproducibility) and realism. Model realism varied based on algorithm choice but was consistent across sample sizes and species types. No algorithm was perfectly realistic, but eight consistently produced high rates of realism and performance (and the two were not strongly correlated). Ensemble strategies were consistently more robust than individual algorithms, so we recommended a new ensemble based on those eight high-performing algorithms. We applied this ensemble strategy to our empirical SDMs along with other ensemble groupings (including the most popular individual algorithm) from the literature to inform novel SDMs. Ensemble SDMs consistently performed well with the empirical data and outperformed the individual algorithm. Results here help inform general SDM method guidance for a variety of native and nonnative species (with both simulated and empirical demonstrations) to improve SDM realism and applications in the future.

With exploding human populations and landscapes that are changing, an increasing number of wildlife species are brought to the brink of extinction. In Canada, the eastern hog-nosed snake, 'Heterodon platirhinos', is found in a limited portion of southern Ontario. Designated as threatened by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC), this reptile has been losing its habitat at an alarming rate. Due to the increase in development of southern Ontario, it is crucial to document what limits the snake’s habitat to direct conservation efforts better, for the long-term survival of this species. The goals of this study are: 1) to examine what environmental parameters are linked to the presence of the species at a landscape scale; 2) to predict where the snakes can be found in Ontario through GIS-based habitat suitability models (HSMs); and 3) to assess the role of biotic interactions in HSMs. Three models with high predictive power were employed: Maxent, Boosted Regression Trees (BRTs), and the Genetic Algorithm for Rule-set Production (GARP). Habitat suitability maps were constructed for the eastern hog-nosed snake for its entire Canadian distribution and models were validated with both threshold dependent and independent metrics. Maxent and BRT performed better than GARP and all models predict fewer areas of high suitability when landscape variables are used with current occurrences. Forest density and maximum temperature during the active season were the two variables that contributed the most to models predicting the current distribution of the species. Biotic variables increased the performance of models not by representing a limiting resource, but by representing the inequality of sampling and areas where forest remains. Although habitat suitability models rely on many assumptions, they remain useful in the fields of conservation and landscape management. In addition to help identify critical habitat, HSMs may be used as a tool to better manage land to allow for the survival of species at risk.