BioEnergy Research

, Volume 8, Issue 2, pp 471–481

Bioenergy Feedstocks at Low Risk for Invasion in the USA: a “White List” Approach

Authors

    • Energy Biosciences InstituteUniversity of Illinois
  • Doria R. Gordon
    • The Nature Conservancy, Department of BiologyUniversity of Florida
  • Aviva Glaser
    • National Wildlife Federation
  • Deah Lieurance
    • Center for Aquatic and Invasive PlantsUniversity of Florida/IFAS
  • S. Luke Flory
    • Agronomy DepartmentUniversity of Florida
Article

DOI: 10.1007/s12155-014-9503-z

Cite this article as:
Quinn, L.D., Gordon, D.R., Glaser, A. et al. Bioenerg. Res. (2015) 8: 471. doi:10.1007/s12155-014-9503-z

Abstract

Proposed introductions of non-native bioenergy feedstocks have resulted in disagreements among industry, regulators, and environmental groups over unintended consequences, including invasion. Attempting to ban or “black list” known or high probability invasive species creates roadblocks without offering clear alternatives to industry representatives wishing to choose low invasion risk feedstocks. Therefore, a “white list” approach may offer a proactive policy solution for federal and state agencies seeking to incentivize the cultivation of promising new feedstocks without increasing the probability of non-native plant invasions in natural systems. We assessed 120 potential bioenergy feedstock taxa using weed risk assessment tools and generated a white list of 25 non-native taxa and 24 native taxa of low invasion risk in the continental USA. The list contains feedstocks that can be grown across various geographic regions in the USA and converted to a wide variety of fuel types. Although the white list is not exhaustive and will change over time as new plants are developed for bioenergy, the list and the methods used to create it should be immediately useful for breeders, regulators, and industry representatives as they seek to find common ground in selecting feedstocks.

Keywords

BiofuelEnergy cropInvasive plantWeed risk assessmentWhite list

Copyright information

© Springer Science+Business Media New York 2014