Predicting the Effectiveness of Phragmites Control Measures using a Rhizome Growth Potential Bioassay

Abstract

In the last century, Phragmites australis (common reed) has expanded from a minor component of the mid-Atlantic tidal wetlands to a dominant species in many locations. Expansion of Phragmites results in decreased plant diversity and alterations to the tidal characteristics of the marsh, resulting in decreased wetland value. Management efforts have used a variety of strategies in an attempt to control its expansion. We tested a greenhouse bioassay that provided insight into the rhizome vitality of six herbicide-treated sites in the Alloway Creek Watershed, NJ well in advance of the growing season. At three sites, rhizomes were exhumed and classified by depth (0–25 cm and 25–75 cm) and appearance (color and firmness). Concurrently, the same protocol was followed, but conducted on an areal basis at three additional sites. Material was grown in sand under greenhouse conditions void of nutrient supplements for 70 days, after which shoots were removed and the rhizomes replanted for 30 days. Effectiveness of control strategies was quantified by examining rhizome color, vitality, and shoot densities in the field. Color was indicative of quality of rhizome reserves. Less than 0.2% of the firm, brown rhizomes produced shoots upon initial planting and none produced shoots upon replanting, whereas 50.9% of white rhizomes produced shoots on initial planting. Rhizome vitality was quantified by examining shoot emergence and the morphology of the shoots. Coupling rhizome vitality with observed field densities resulted in a predictive capability, and shoot density and biomass predictions were compared to field measurements in July 2001. We tested and accurately predicted the relative shoot densities and shoot biomass of the three sites for which we collected rhizome material on an areal basis. The result is a rapid, valuable, and cost-effective monitoring tool that can quickly quantify the effects of past control methods and predict future growth potential.