The population ecology of sunflowers (Helianthus annuus) through space and time

Explicitly incorporating space and time into population ecology has offered insight into environmental influences on population processes. In this dissertation, I explored the population ecology of wild, annual sunflowers (Helianthus annuus L., Asteraceae) at three spatial scales, using multi-year studies.; In Chapter 1, I experimentally examined, at the 1.3 m scale, the roles of soil disturbance and seed density on seed bank formation and resulting populations. I found that seedling establishment required large soil disturbances, and soil disturbances following seed dispersal were essential for forming seed banks. Larger seed banks increased seedling emergence the following year, but, due to densitydependent survival and reproduction, larger seed banks did not produce more inflorescences.; Scaling-down methods provide a way to estimate fine-scale ecological patterns from data collected at coarser scales. In Chapter 2, I applied fractal-based scaling-down methods to occupancy and to the dynamics processes of colonization and extinction. Using multi-year surveys of roadside sunflower populations in both Kansas (24 km) and Nebraska (19 km), I predicted colonization and extinction rates at the 80 m scale from data at coarser scales. I applied these methods to data from roadside surveys of Silene latifolia Poir. (Caryophyllaceae). In general, scaling of occupancy and colonizations was more successful than for extinctions, and all three variables scaled better in Helianthus than in Silene. Several possible explanations exist. For example, the greater reliance of sunflower establishment on disturbance and on the seed bank for colonizations may contribute to the differential scaling success between Helianthus and Silene.; Modeling the ecological niche of generalist species, like sunflowers, is difficult because they have broad climatic tolerances. For Chapter 3, I collected extensive records of observed sunflower presence and absence (every 1.6 km for 5333 km in the Great Plains) and used these data and high resolution satellite imagery (500m) to develop highly accurate ecological niche models using GARP (Genetic Algorithm for Rule-Set Production). Models particularly predicted the absence of sunflowers in the eastern portion and the presence of the plant in the western portion of the study area well.