Efficacy of treatments against garlic mustard (Alliaria petiolata) and effects on forest understory plant diversity

Lindsey M. Shartell, Linda M. Nagel, Andrew J. Storer

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Garlic mustard, an invasive exotic biennial herb, has been identified in the Upper Peninsula of Michigan, but is not yet widely distributed. We tested the effectiveness and impact of management tools for garlic mustard in northern hardwood forests. Six treatment types (no treatment control, hand-pull, herbicide, hand-pull/herbicide, scorch, and hand-pull/scorch) were applied within a northern hardwood forest invaded by garlic mustard. We sampled understory vegetation within plots to compare garlic mustard abundance (distinguishing first and second year plants) and native plant diversity before and after treatment. Results immediately following treatment indicated that garlic mustard seedling abundance was significantly reduced by herbicide, hand-pull/herbicide, scorch, and hand-pull/scorch treatments, and that adult abundance was reduced by all treatments. However, sampling of treatment sites one year later showed an increase in seedling abundance in herbicide and hand-pull/herbicide plots. Adult garlic mustard abundance after one year was lower than the control with the exception of the hand-pull plots where adult abundance did not differ. After one year, understory species richness and Shannon's Diversity were lower in the herbicide and pull/herbicide treatments. Based on these results, we conclude that single-year treatment of garlic mustard with hand-pulling, herbicide, and/or scorching is ineffective in reducing garlic mustard abundance and may inadvertently increase the success of garlic mustard, while negatively impacting native understory species.

Original languageEnglish (US)
Pages (from-to)605-613
Number of pages9
JournalForests
Volume3
Issue number3
DOIs
StatePublished - 2012

Keywords

  • Invasive plants
  • Northern hardwoods
  • Upper michigan

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