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.