Date of Award


Document Type


Degree Name

Master of Science (MS)

Legacy Department

Forest Resources

Committee Member

Dr. Elena Mikhailova

Committee Member

Dr. Christopher Post

Committee Member

Dr. Patrick McMillan


Spatio-temporal patterns of flowering in forest ecosystems are hard to quantify and monitor. The objectives of this study were to investigate spatio-temporal patterns (e.g. soils, simple slope classes, slope aspect, and flow accumulation) of flowering around Lake Issaqueena, SC using a plant-flowering database collected with GPS-enabled cameras (stored in Picasa 3 web albums and project website) on a monthly basis in 2012. Pacolet fine sandy loam had the highest flowering count, followed by Madison sandy loam, both dominant soil types around the lake. The highest flowering counts were on moderately steep (17-30%) and gently sloping (4-8%) slopes. The highest flowering counts were on west (247.5-292.5°), southwest (202.5-247.5°), and northwest (292.5-337.5°) aspects. The highest flowering counts were associated with minimum and maximum flows within the landscape. The Chi-Square test indicated that the differences in the distributions of the proportions of flowering counts were significant by soil type, slope, aspect, and flow accumulation for each month (February-November), for all months (overall), and across months. The Chi-Square test on area-normalized data indicated significant differences for all months and individual differences by each month with some months not statistically significant. Nine plant families with the most flowering counts were identified (number of flowering counts): Asteraceae (533), Fabaceae (299), Liliaceae (132), Melastomataceae (115), Ericaceae (105), Lamiaceae (101), Campanulaceae (97), Clusiaceae (84), and Caryophyllaceae (82). Cluster analysis on flowering counts for the nine plant families with the most flowering counts indicated no unique separation by cluster, but indicated that they were flowering on strongly sloping (9-16%) slopes, on southwest (202.5-247.5°) aspects, and flow accumulation averaging 57. Spatio-temporal analysis can be of great value for phenological studies and monitoring.



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