Assessing the invasion risk of traded alien ferns using species distribution models

Abstract

Risk analysis plays a crucial role in regulating and managing alien and invasive species but can be time-consuming and costly. Alternatively, combining invasion and impact history with species distribution models offers a cost-effective and time-efficient approach to assess invasion risk and identify species for which a comprehensive risk analysis should take precedence. We conducted such an assessment for six traded alien fern species, determining their invasion risk in countries where they are traded. Four of the species (Dicksonia antarctica, Dryopteris erythrosora, Lygodium japonicum, and Phlebodium aureum) showed limited global distributions, while Adiantum raddianum and Sphaeropteris cooperi had broader distributions. A. raddianum, however, was the only species found to pose a high invasion risk in two known trade countries – the USA and Australia – and requires a complete risk analysis to determine the appropriate regulatory responses. Dicksonia antarctica, Phlebodium aureum (for New Zealand), and Dryopteris erythrosora (for the USA) posed a medium risk of invasion due to the lack of evidence of impacts, and a complete risk analysis is thus deemed less crucial for these species in these countries. For other species, suitable environments were not predicted in the countries where they are traded, thus the risk of invasion is low, and a complete risk analysis is not required. For species in countries where suitable environments are predicted but no trade information or presence data are available, risk assessments are recommended to better determine the risk posed. Despite the relatively limited potential global distribution of the studied ferns relative to other major plant invaders (e.g., Pinus spp. and Acacia spp.), their history of invasion, documented impacts in pristine environments, and high propagule pressure from trade warrants concern, possibly necessitating legislative and regulatory measures in environmentally suitable regions.