Natural Resources, School of

 

Date of this Version

12-2013

Citation

Williams, J.B. 2013. Predicting Invasion Risk of Non-Native Plants Using a Modified I-Rank Assessment. M.S. Thesis. University of Nebraska-Lincoln.

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Natural Resource Sciences, Under the Supervision of Professor Craig R. Allen. Lincoln, Nebraska: December, 2013

Copyright (c) 2013 Justin B. Williams

Abstract

Biological invasions are a global problem responsible for native species declines worldwide. Understanding the invasion risk from non-native species is important in establishing management goals and making decisions for managing native ecosystems. Useful modeling methods for quantifying or predicting invasion risk should consider research needs, data availability, and operate at an appropriate scale. I evaluated risk assessment methods towards answering a specific research question; which plant species pose the greatest risk of becoming invasive or having the greatest negative impact in Nebraska? I selected the I-Rank assessment method, which consists of 20 questions grouped into four risk categories or Subranks: impact on native species/ecosystems, current distribution/abundance, trend in distribution/abundance, and management difficulty. I used information from herbaria collections, agency reports, literature review, online databases, and expert opinion surveys to evaluate 56 non-native plant species. I modified the I-Rank method to operate at the state-level scale by adapting I-Rank questions for Nebraska. I also compared results from this state-level I-Rank assessment to results from an analysis conducted at the national scale. A distinct feature of the I-Rank assessment is that a range of possible answers is acceptable for each question. This feature allows for the incorporation of uncertainty and reduces the amount of inherent subjectivity, but also presents a challenge in accounting for uncertainty. I present new methods for quantifying and visualizing sources of uncertainty in the I-Rank scores and provide conceptual risk assessment and management contexts for these methods. Results indicate that the predicted invasion risk often depends on the scale at which the I-Rank questions are evaluated. Ten of the species evaluated are noxious in neighboring states, but not likely to become invasive in Nebraska. The study identified numerous species likely to be invasive in Nebraska, including seven plants not recognized as noxious weeds or “watch list” species in Nebraska. I-Rank results for many species indicated high levels of uncertainty and require additional interpretation or research to make conclusions. I make suggestions for interpreting I-Rank results using available information to prioritize species for management decisions in Nebraska. I discuss relative strengths/weaknesses of the I-Rank method, offer conclusions/recommendations based on my results for Nebraska, and identify opportunities for future research. A similar approach could be used to adapt this method for other states or geographic areas of interest. I conclude that the I-Rank assessment provides a straightforward method for synthesizing information from numerous sources to evaluate invasive species threats at an appropriate scale to meet research needs and inform management decisions.

Adviser: Craig R. Allen