Effects of Crop Rotation on Common Waterhemp Population Dynamics: A Periodic Matrix Model Example
Date:
Huong Nguyen and Matt Liebman
Crop biophysical characteristics and management practices can affect weed population dynamics in various ways. To track changes a common waterhemp (Amaranthus tuberculatus (Moq.) J.D. Sauer) population from seed in the soil seedbank to new seed deposition to the soil seedbank, we used a chain of six periodic matrices in each of nine crop environments crossed with two corn weed management regimes to project population trajectories in two scenarios of plant fecundity, representing two levels of weed control efficacy (high and low). The chain of periodic matrices described the response to crop management activities of the population of interest throughout a calendar year. To parameterize the model, we used values derived from both scientific literature and our own field observations. Each crop environment identified a crop species (corn, soybean, oat, or alfalfa) in a rotation (2-year, 3-year, or 4-year). The crop sequences in the 2-year, 3-year, and 4-year rotations were, respectively, corn - soybean; corn - soybean - oat intercropped with red clover; and corn - soybean - oat intercropped with alfalfa - alfalfa. When waterhemp control efficacy was high, the 3-year rotation appeared to be the most reliable in depleting the soil seedbank. When waterhemp control efficacy was low, the 4-year rotation appeared to be the least risky for preventing waterhemp outbreaks. The slower rates of population growth in the more diverse rotation were attributed to lower population growth rate (λ) in the oat, red clover, and alfalfa crop environments (cool-season crops). In addition to population projection, we determined thresholds for mature plant density in the three rotations for stabilizing population size using the parameter inputs from the low control efficacy scenario. The differences in mature plant density thresholds were more pronounced between the 2-year and 4-year rotations than any other pairwise comparison.