Mathematics

The Double Entry Journals were probably of the most benefit to me. I hate writing journals but these were not your typical journals and I was able to organize my thoughts with what I was seeing [in the field] and reading. This was the best journaling technique I've ever used. – Julie
Students are slowly gathering their books and handing in their final course evaluations for our 3-credit hour mathematics methods course for pre-service middle level mathematics teachers. We are reading Julie's and other students' final course evaluations and are happy to see positive comments related to our Theory-into-Practice (TIP) project. We designed this project to address our students' expressed frustrations at the perceived disconnect between theory and practice. The project combined course readings, journaling, collaboratively created observation protocols, and classroom observation into a semester-long iterative assignment. Our students' work on this project, and the resulting impact on professional capital, is the focus of this study.

Wild hogs (Sus scrofa) are an invasive species that have occupied Great Smoky Mountains National Park since the early 1900s. The population is in direct competition with native species, inflicts unprecedented damage to plant communities , and is a reservoir for disease. The Park implemented a control program in 1959 and has kept detailed geographic records on each removal since 1980, producing over 1500 unique presence locations. To extract the geographic preferences exhibited by the presence locations, we conducted a niche factor analysis by pairing the data with relevant environmental predictors. We then mapped these preferences spatially to create two maps that depict suitable locations to support wild hog presence. Results from this project will inform control efforts and improve our understanding of the population of wild hogs that resides in the Park. K E Y W O R D S distribution modeling, Great Smoky Mountains National Park, invasive wild hog population, niche factor analysis, suitable habitat Recommendations for Resource Managers • We relate presence locations to environmental predictors to quantify preferences exhibited by wild hog removal data points. • The strongest preferences exhibited by the data points are related to understory vegetation and slope. Natural Resource Modeling. 2017;e12132. wileyonlinelibrary.com/journal/nrm • The data points are most sensitive to changes in elevation and temperature. • Two map products depicting potential wild hog presence were derived. • Map products can be used to better understand the population and to guide future control efforts.