Stephen J. TulowieckiAssistant Professor of Geography
Steve is a GIScientist and biogeographer who studies forested ecosystems, with a focus on forests prior to European settlement in the Northeastern US Steve's research examines the factors that shaped past geographic distributions of tree species, as well as methodological issues surrounding this area of inquiry (e.g. spatial representations of ecological phenomena, positional uncertainty in species data). His research utilizes geospatial tools and quantitative methods, such as geographic information systems (GIS), predictive modeling, statistical computing, and programming. Steve's research also utilizes – and studies the usefulness of – unconventional or "found" data sources, such as original land survey records of the 17th to 19th centuries CE. His dissertation explored the impacts of Native American settlement upon tree species composition in Chautauqua County, New York (ca. 1800 CE). Steve's teaching interests include GIS, environmental issues, and geospatial and statistical software. Future research interests are in applying recent methods and paradigms in geographic study – such as information retrieval, text mining, and citizen science – to the pursuit of comprehending past forest conditions in the Northeast.
National Science Foundation (NSF)-funded research
ENVR 124: S/Environmental Issues
This introductory course is an interdisciplinary examination of historical and contemporary environmental problems. It examines the impact of human activity on the environment and the complex interrelationships between people and the natural world. It also explores the socioeconomic and political dimensions behind environmental change, and evaluates solutions to environmental dilemmas such as deforestation, soil erosion, air and water pollution, and biodiversity loss.
GEOG 278: R/Statistics in Geography
An introduction to statistical research methods in geography. This course covers classical and spatial statistics as applied to research in physical and human geography. Topics covered include description, inference, significance, and prediction based on samples drawn from geographic data. (Students may not receive credit for more than one 200-level statistics course, including credit for more than one of the following courses: ECON 205, GEOG 278, MATH 242, PLSC 251, PSYC 250, and SOCL 211.) Prerequisites: GEOG 102 or GEOG 111 and GEOG 112 or GEOG 123 or permission of instructor. Offered every year
GEOG 386: App-GISc:Modeling&Raster Analy
This course provides the opportunity for in-depth applications of Geographic Information Science, including Geographic Information Systems (GIS), spatial analysis, remote sensing, and cartography, to selected research problems and data sets. This course will introduce students to both conceptual and practical aspects of developing GIScience applications. May be taken for credit twice under different subtitles. Prerequisites: GEOG 286. Not offered on a regular basis.