1. Most population dynamics studies are geographically restricted, yet species ranges are large. We performed multiyear roadside surveys of the sunflower, Helianthus annuus, at two locations that differ in precipitation (eastern Kansas, KS; western Nebraska, NE). Our goals were to (i) document if there was geographic variation in dynamics and evaluate the role of habitat variables and the landscape matrix; (ii) determine the likely amount of occupiable habitat and (iii) explore the role of seed banks in dynamics.
2. Geographical variation: Occupancy and mean numbers of plants per occupied roadside unit were generally higher in NE than KS. Sunflower abundance was linearly related to spring precipitation in NE but not in KS. Soil disturbance was associated with increased occupancy and apparent colonization, and reduced apparent extinction. Variation in the landscape adjacent to roads had a larger effect on occupancy in KS than in NE. In KS, smaller populations were more prone to apparent extinction; NE results were more variable. Note that we refer to ‘apparent’ colonization or extinction because seed banks may persist even when above-ground plants are absent.
3. Occupiable habitat: 25% of the roadside was never occupied by sunflowers in KS, despite surveying for 6 years. An asymptotic limit to occupancy in NE was not apparent, but fewer years were surveyed.
4. Seed banks: Seed banks appear prevalent. The strongest evidence comes from a year following a spring drought in NE, when 100s to 1000s of plants were found in units that lacked plants the year before.
5. Synthesis. We found both geographical similarities (role of soil disturbance, seed banks) and differences (response to rainfall variation, importance of landscape matrix) in sunflower dynamics. Our work suggests that for appropriate species (including many weedy and invasive plants), replicate roadside surveys are an efficient way to evaluate geographic variation in dynamics, the landscape matrix and habitat characteristics across a broad geographic area. Such data help bridge the gap between broad-scale distributional studies and small experimental plot studies, and provide insights on the population dynamics that underlie species ranges.