Emerging infectious diseases are a threat to wildlife populations and conservation efforts. One example of this is the amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), which causes the disease chytridiomycosis and has been linked to amphibian populations declines worldwide. There have been numerous attempts to mitigate the effects of Bd on amphibians, all with mixed results. Two factors that have previously been found to correlate with Bd infection intensity and prevalence are the amphibian skin bacterial communities and environmental temperatures. Some naturally occurring bacteria on the skin of amphibians and warmer temperatures can limit Bd infection. For my dissertation research, I aimed to 1) assess the amphibian skin bacterial communities across species, developmental stage, infection status, and different local environments, and 2) understand and predict the effect of a natural, varying temperature regime on the growth of Bd from constant temperature data. In Chapter 1, I reviewed the amphibian chytrid fungus and the effects of varying temperature on organisms' performance or trait rates. In Chapter 2, I sampled bacterial communities on ranid tadpoles and three ranid frog species at Mianus River Gorge Preserve in Bedford, New York, USA. I found that tadpoles had significantly different bacterial alpha diversity measurements than adult frogs, with higher Faith's phylogenetic diversity, Shannon diversity, and amplicon sequence variant (ASV) richness. Bacterial communities between the three different adult frogs species were not different. Additionally, infected frogs did not have significantly different bacterial communities than uninfected frogs. In Chapter 3, I predicted Bd growth in three varying temperature environments with Bayesian hierarchical models assuming different thermal performance curves. My predictions overestimated the growth of Bd in varying temperature environments, and the choice of thermal performance curve used in the models strongly impacted the predictions by altering the implied relationship between Bd's growth rate and temperature. In Chapter 4, I aimed to improve modeling methods for predicting in vitro Bd growth in varying temperature environments by adding additional features to the model based on observed biological phenomena, specifically a temperature-dependent delay period for Bd development. However, the model parameters were unidentifiable with this added complexity when only optical density data are available to quantify growth, highlighting the need to match the appropriate data to the complexity of the model. In Chapter 5, I created a mechanistic model that was parameterized by a combination of optical density, MTT assays (a metabolic assay), and zoospore count data to learn more about Bd growth dynamics. I also examined how many days of zoospore count data are needed to fit the mechanistic model. By combining these three data sources, I increased the ability to estimate most model parameters. My dissertation added to both the amphibian skin bacterial community literature, supporting differences between tadpoles and adult frog bacterial communities, and added new data from a previously unsurveyed area. Attempts are being made to use bacterial communities to limit diseases in many wildlife populations, through a probiotic. To use skin bacterial communities, factors that shape these communities need to be understood to ensure the successful application of a probiotic. My dissertation also added to the thermal ecology literature, showing that current methods and my optical density Bayesian hierarchical model do not accurately predict performance in varying temperature environments. As temperatures are changing around the world and temperature variability is expected to increase in many places, predicting how organisms will perform in new thermal environments is becoming increasingly important. / Doctor of Philosophy / Infectious diseases around the world have led to wildlife population declines. Chytridiomycosis is a disease in amphibians caused by the amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd). Bd infects the skin of amphibians and can cause death. The composition of amphibian skin bacterial communities, bacteria that live on the skin of amphibians, can limit the growth of Bd on amphibians and reduce disease. Due to some species of bacteria inhibiting Bd growth, attempts have been made to try to use bacteria to limit disease in amphibians. But, we still do not know to what extent some host and environmental factors influence host bacterial communities, and how this might influence disease in amphibians. Warmer environmental temperatures have also been associated with reduced chytridiomycosis in amphibians. However, the effect of temperature is often studied at constant temperatures instead of natural, varying temperatures. The impact of varying temperature on Bd growth dynamics is still not fully understood. My dissertation research examined 1) differences in amphibian bacterial communities in different species and at different developmental stages (tadpoles vs. frogs), and 2) whether I can accurately predict Bd growth in varying temperature environments. First, I examined skin bacterial communities of three frog species at Mianus River Gorge, in Bedford, NY. I found that tadpoles had more diverse bacterial communities than adult frogs and that adults from the three species had similar bacterial communities, and that Bd infection status did not correlate with skin bacterial community composition. Second, I examined how temperature impacts the growth of Bd and whether we can predict how Bd grows in natural, fluctuating temperature conditions. Specifically, I used data from lab experiments in which I grew Bd at constant temperatures to fit a model and then predict how Bd grew in temperatures that fluctuate over the day as they would in nature. I found that current methods that use constant temperature data to predict how Bd grows in natural temperature scenarios are not accurate. Third, I attempted to improve modeling methods to predict Bd growth in natural temperature scenarios by specifying that Bd development is dependent on temperature. I found that the increasing model complexity without the correct type or amount of data leads to not being able to fit the model. Lastly, I combined three different types of Bd growth data to fit a new model that describes Bd growth. Fitting this new model with three data sources, I learned more about Bd growth and was more certain about the values of the parameters in the model. Additionally, this model has parameters and model components directly related to Bd growth, unlike in the previous Chapters' models. Using this model will allow us to examine how temperature influences specific Bd growth stages in future studies. My dissertation examined host and environmental factors that influence skin bacterial communities. Determine how these factors shape and change host bacterial communities will allow scientists to successfully use bacteria to reduce disease in amphibians and other wildlife. Additionally, I examined methods in the literature and built my own model to predict Bd growth in varying temperature environments. I found that taking constant temperature data from the lab to predict Bd growth in more natural varying temperature environments is not accurate and future studies need to improve these methods. Developing these methods is becoming more important as temperatures change around the world and organisms are exposed to new temperatures. Improving these methods would allow more accurate predictions about organisms' performance in new environmental conditions.