Scanning the horizon for invasive plant threats using a data-driven approach

By

Kendig, Amy
Canavan, Susan
Anderson, Patti
Flory, S. Luke
Gettys, Lyn A.
Gordon, Doria
Iannone, Basil V., III
Kunzer, John M
Petri, Tabitha
Pfingsten, Ian
Lieurance, Deah

Type

Article

Date of Publication

2022

Original Publication

NeoBiota : advancing research on alien species and biological invasions

Volume

74

Pages

129--154

Subjects

certainty , consensus building , Florida , horizon scan , invasion , Prevention , rapid risk assessment

Contributed by

Pensoft Publishers

Language

English

Published by

Sophia, Bulgaria Pensoft Publishers

Identifiers

DOI: https://doi.org/10.3897/neobiota.74.83312

 

Abstract

Early detection and eradication of invasive plants are more cost-effective than managing well-established invasive plant populations and their impacts. However, there is high uncertainty around which taxa are likely to become invasive in a given area. Horizon scanning that combines a data-driven approach with rapid risk assessment and consensus building among experts can help identify invasion threats. We performed a horizon scan of potential invasive plant threats to Florida, USA—a state with a high influx of introduced species, conditions that are generally favorable for plant establishment, and a history of negative impacts from invasive plants. We began with an initial list of 2128 non-native plant taxa that are known invaders or crop pests. We built on previous invasive species horizon scans by developing data-based criteria to prioritize 100 taxa for rapid risk assessment. The semi-automated prioritization process included selecting taxa “on the horizon” (i.e., not yet in the target location and not on a noxious weed list) with climate matching, naturalization history, “weediness” record, and global commonness. We derived overall invasion risk scores with rapid risk assessment by evaluating the likelihood of each of the taxa arriving, establishing, and having an impact in Florida. Then, following a consensus-building discussion, we identified six plant taxa as high risk, with overall risk scores ranging from 75 to 100 out of a possible 125. The six taxa are globally distributed, easily transported to new areas, found in regions with climates similar to Florida’s, and can impact native plant communities, human health, or agriculture. Finally, we evaluated our initial and final lists for potential biases. Assessors tended to assign higher risk scores to taxa that had more available information. In addition, we identified biases towards four plant families and certain geographical regions of origin. Our horizon scan approach identified taxa conforming to metrics of high invasion risk and used a methodology refined for plants that can be applied to other locations.