A Model for Changes in Germination Synchrony and Its Implements to Study Weed Population Dynamics: A Case Study of Brassicaceae

Abstract

In every agricultural system, weed seeds can be found in every cubic centimeter of soil. Weed seeds, as a valuable trait underlying the fate of weed populations, exhibit differing levels of seed dormancy, ensuring their survival under uncertain conditions. Seed dormancy is considered as an innate mechanism that constrains germination under suitable conditions that would otherwise stimulate germination of nondormant seeds. This work provides new insight into changes in germination patterns along the dormant to nondormancy continuum in seeds with physiological dormancy. Notable findings are: (1) germination synchrony can act as a new parameter that quantitatively describes dormancy patterns and, subsequently, weed population dynamics, (2) germination synchrony is dynamic, suggesting that the more dormancy decreases, the more synchrony is obtainable, (3) after-ripening and stratification can function as a synchronizing agent that regulates germination behavior. Freshly harvested seeds of Brassica napus with type 3 of non-deep physiological dormancy showed the most synchronous germination, with a value of 3.14, while a lower level of germination asynchrony was found for newly harvested seeds of Sinapis arvensis with type 1 of non-deep physiological dormancy, with an asynchrony value of 2.25. After-ripening and stratification can act as a synchronizing factor through decreasing the asynchrony level and increasing synchrony. There is a firm relationship between seed dormancy cycling and germination synchrony patterns, ensuring their survival and reproductive strategies. By germinating in synchrony, which is accompanied by cycling mechanisms, weeds have more opportunities to persist. The synchrony model used in the present study predicts germination behavior and synchrony along the dormant to nondormancy continuum in weed seeds with physiological dormancy, suggesting a useful method for the quantification of germination strategies and weed population dynamics.