Integrating DNA fingerprinting of invasive watermilfoil strains into aquatic vegetation monitoring and assessment

Abstract

Eurasian watermilfoil (Myriophyllum spicatum L.) and its hybrids with native northern watermilfoil (Myriophyllum spicatum L. x Myriophyllum sibiricum) (invasive watermilfoils) are among the most heavily managed invasive aquatic plants in the United States. Within invasive watermilfoils there are distinct strains which are produced through sexual reproduction and can be maintained indefinitely by clonal propagation. Different strains can differ in their invasiveness (e.g., growth and potential for spread) and response to herbicides. However, strain identification is not routinely implemented as part of management planning or evaluation. In this thesis, we integrated molecular fingerprinting that can distinguish different Eurasian and hybrid watermilfoil strains into aquatic vegetation monitoring in eight Minnesota lakes over the course of three years. We provide proof of concept that by tracking strain incidence over time it is possible 1) to detect changes in strain composition of invasive watermilfoil populations, and 2) to identify priority strains for future growth and herbicide assays. This study demonstrates that integrating genetic fingerprinting into aquatic vegetation management and evaluation holds promise to inform management decisions by identifying those strains that have the most invasive potential. As far as we are aware, this is the first published study to examine the strain composition of invasive watermilfoil populations over time.