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Call number: LD2668 .T4 1985 C34 / Master of Science

Call number: LD2668 .T4 1961 G79

Call number: LD2668 .T4 1979 P482 / Master of Science

Call number: LD2668 .T4 1985 R62 / Master of Landscape Architecture

Call number: LD2668 .T4 1952 D31 / Master of Science

Master of Science / Department of Horticulture and Natural Resources / Adam A. Ahlers / The Flint Hills ecoregion in Kansas, USA, represents the largest remaining tract of native tallgrass prairie in North America. Anthropogenic landscape change (e.g., urbanization, agricultural production) is affecting native biodiversity in this threatened ecosystem. Our understanding of how landscape change affects spatial distributions of carnivores (i.e., species included in the Order ‘Carnivora’) in this ecosystem is limited. I investigated the influence of landscape structure and composition on site occupancy dynamics of 3 native carnivores (coyote [Canis latrans]; bobcat [Lynx rufus]; and striped skunk [Mephitis mephitis]) and 1 nonnative carnivore (domestic cat, [Felis catus]) across an urbanization gradient in the Flint Hills during 2016-2017. I also examined how the relative influence of various landscape factors affected native carnivore species richness and diversity. I positioned 74 camera traps across 8 urban-rural transects in the 2 largest cities in the Flint Hills (Manhattan, pop. > 55,000; Junction City, pop. > 31,000) to assess presence/absence of carnivores. Cameras were activated for 28 days in each of 3 seasons (Summer 2016, Fall 2016, Winter 2017) and I used multisession occupancy models and an information-theoretic approach to assess the importance of various landscape factors on carnivore site occupancy dynamics. Based on previous research in other ecosystems, I expected a negative relationship between both coyote and bobcat occurrence with increasing urban development but a positive relationship for domestic cat and skunk occurrence with increasing urban landcover. I also predicted grassland landcover to positively influence site occupancy for all carnivores except domestic cats. I expected that coyotes, the apex predator in this ecoregion, may limit domestic cat distributions through intraguild competition. Thus, I predicted a negative relationship between site occupancy of domestic cats and coyote occupancy probabilities. Because urban development results in habitat loss and fragmentation, I expected native species richness and diversity to decline with increased urban development. Coyotes had lower occupancy and colonization rates in areas with increased urban landcover. Bobcat occupancy was insensitive to urban landcover and colonization rates were greater in grassland landcover and row-crop agriculture fields. Site occupancy of bobcats was highly influence by forested areas and greater edge densities. Contrary to my hypothesis, striped skunk occupancy and colonization rates were negatively related to urban landcover. As expected, domestic cats were more likely to occur in and colonize sites with increased urban development and less likely to occur at sites with high coyote occupancy probabilities. Native carnivore species diversity and richness were negatively related to urban landcover. Occupancy dynamics of carnivores were shown to be influenced by landscape structure and composition as well as intraguild interactions. My results show urban landcover has a strong influence on the spatial distributions of carnivores in the northern extent of the Flint Hills.

Master of Arts / Department of Geography / J. M. Shawn Hutchinson / Grasslands of the Flint Hills are often burned as a land management practice. Remote sensing can be used to help better manage prairie landscapes by providing useful information about the long-term trends in grassland vegetation greenness and helping to quantify regional differences in vegetation development. Using MODIS 16-day NDVI composite imagery between the years 2001-10 for the entire Flint Hills ecoregion, BFAST was used to determine trend, seasonal, and noise components of the image time series. To explain the trend, 4 factors were considered including hydrologic soil group, burn frequency, and precipitation deviation from the 30 year normal. In addition, the time series data was processed using TIMESAT to extract eight different phenometrics: Growing season length, start of season, end of season, middle of season, maximum value, small integral, left derivative, and right derivative. Phenometrics were produced for each year of the study and an ANOVA was performed on the means of all eight phenometrics to assess if significant differences existed across the study area. A K-means cluster analysis was also performed by aggregating pixel-level phenometrics at the county level to identify administrative divisions exhibiting similar vegetation development. For the study period, the area of negatively and positively trending grassland were similar (41-43%). Logistic regression showed that the log odds of a pixel experiencing a negative trend were higher in sites with clay soils and higher burning frequencies and lower for pixels having higher than normal precipitation and loam soils. Significant differences existed for all phenometrics when considering the ecoregion as a whole. On a phenometric-by-phenometric basis, unexpected groupings of counties often showed statistically similar values. Similarly, when considering all phenometrics at the same time, counties clustered in surprising patterns. Results suggest that long-term trends in grassland conditions warrant further attention and may rival other sources of grassland change (e.g., conversion, transition to savannah) in importance. Analyses of phenometrics indicates that factors other than natural gradients in temperature and precipitation play a significant role in the annual cycle of grassland vegetation development. Unanticipated, and sometimes geographically disparate, groups of counties were shown to be similar in the context of specific phenology metrics and this may prove useful in future implementations of smoke management plans within the Flint Hills.

Call number: LD2668 .T4 1985 J36 / Master of Science

Master of Arts / Department of Geography / Douglas G. Goodin / My thesis characterizes the temporal and spatial behavior of ozone and fine particulate matter in the Kansas City metropolitan area. I also investigate the capability of a synoptic weather typing scheme, the Spatial Synoptic Classification, to characterize and explain the behavior of ozone and fine particulate matter in the Kansas City area. Daily maximum ozone concentrations from nine active ozone monitoring stations and daily average particulate concentrations six active PM2.5 monitoring stations were compared to daily SSC weather type records from 2004-2010. Analysis of Variance (ANOVA) tests were conducted on the ozone and PM2.5 data to analyze temporal and spatial behavior. A non-parametric recursive partitioning technique was used to create a conditional inference tree-based regression model to analyze the association between the different SSC weather types and the selected pollutants. The ANOVA results showed significant seasonal trends with both pollutants. In general, ozone concentrations are typically lower in the spring and autumn months and higher during the summer months. PM2.5 concentrations were not as dependent on the season, however, they did tend to be higher in the late summer months and lower in the autumn months. The results also showed significant differences for both pollutants in average concentration depending on location. The ozone concentrations generally tended to be higher in the areas that are located downwind of Kansas City and lowest at the station located in the middle of the urban area. Fine particulates also seemed to be highest in the downwind portion of the urban area and lowest in the region upwind of the city. The conditional inference tree showed that higher concentrations of both pollutants are associated with tropical air masses and lower concentrations are associated with polar air masses.