Date of Graduation
Spring 2019
Degree
Master of Science in Biology
Department
Biology
Committee Chair
Sean Maher
Abstract
The risk of tick-borne infection is increasing across the United States, and in Missouri, ticks are expanding into novel regions due to climate change, habitat fragmentation, and biodiversity loss. Regions in which ticks are encroaching experience novel vectors for lineage associated pathogens. Novel tick detection can be low due to sampling practices targeting known ticks, which can lead to unreliable distribution maps and poor predictive distribution models. Such models should account for biotic factors, abiotic factors, and their interactions to provide a dynamic view of their impact on tick abundance and identify variables that can serve as indicators. Further, a simple comparison of sampling methods in different habitats for tick abundance, diversity, and life stage allows for the determination of the most effective sampling technique to gain a holistic view of tick communities. I completed a set of surveys to account for biotic factors, abiotic factors, and sampling design in tick distribution in Southwest Missouri. I used tick drags and sampled the following biotic and abiotic factors: small mammals, ants, ambient temperature, relative humidity, litter depth, and canopy cover. Factors were tested directly on tick abundance using generalized linear models, and indirect relationships, like the effect of location, were analyzed using a linear mixed effect model. To test method efficiency, I executed drags and carbon-dioxide traps in two different habitat types, forest and grassland, and compared captures in terms of abundance, species, and life stages. Indirect relationships and location explained tick abundance more clearly than direct relationship and two methods of sampling resulted in more effective analysis of tick communities. Understanding tick communities and the driving forces behind the movement of tick populations is needed to increase the awareness of public health programs of tick-borne diseases in the region.
Keywords
tick, abiotic, biotic, ants, abundance, sampling methods, generalized linear model, linear mixed effect model, Missouri
Subject Categories
Biology
Copyright
© Casey L. Adkins
Recommended Citation
Adkins, Casey L., "The Assessment of Predictor Variables for Hard Tick Abundance in Southwestern Missouri" (2019). MSU Graduate Theses. 3344.
https://bearworks.missouristate.edu/theses/3344
