TEASIng apart alien species risk assessments: a framework for best practices

Abstract

Some alien species cause substantial impacts, yet most are innocuous. Given limited resources, forecasting risks from alien species will help prioritise management. Given that risk assessment (RA) approaches vary widely, a synthesis is timely to highlight best practices. We reviewed quantitative and scoring RAs, integrating > 300 publications into arguably the most rigorous quantitative RA framework currently existing, and mapping each study onto our framework, which combines Transport, Establishment, Abundance, Spread and Impact (TEASI). Quantitative models generally measured single risk components (78% of studies), often focusing on Establishment alone (79%). Although dominant in academia, quantitative RAs are underused in policy, and should be made more accessible. Accommodating heterogeneous limited data, combining across risk components, and developing generalised RAs across species, space and time without requiring new models for each species may increase attractiveness for policy applications. Comparatively, scoring approaches covered more risk components (50% examined > 3 components), with Impact being the most common component (87%), and have been widely applied in policy (> 57%), but primarily employed expert opinion. Our framework provides guidance for questions asked, combining scores and other improvements. Our risk framework need not be completely parameterised to be informative, but instead identifies opportunities for improvement in alien species RA.

Comparing the ecological impacts of native and invasive crayfish: could native species’ translocation do more harm than good?

“…Leung et al (2012) recently proposed a unified quantitative invasive species assessment framework which considers transport, establishment, abundance, spread and impact (TEASI), and meta-analyses like that presented here offer a promising approach for quantifying risk. For most existing and future invasive species, there will not be sufficient species and community-specific empirical data to inform case-specific decision-making.…”

The generic impact scoring system (GISS): a standardized tool to quantify the impacts of alien species

“…While all measure environmental impact, only 14 measure socio-economic impact. List derived from assessments reviewed by Essl et al (2011) and/or listed in Appendix S1 in Leung et al (2012) with recent additions…”

“…Three confidence levels are distinguished: low, medium, and high. There are multiple possibilities to define confidence and its quantification (Leung et al 2012). For the GISS, we Sandvik et al (2013) suggest the approach given by Blackburn et al (2014) who restrict uncertainty to data quality.…”

“…However, the diversity of metrics for variables of impacts usually considered makes it impossible to directly compare impacts across taxa (Vilà et al 2010; but see Blackburn et al 2014;Kumschick et al 2015b). Therefore, various impact scoring systems have been developed to integrate the variability of the empirical evidence on impacts in a comparable way (e.g., Leung et al 2012 and references mentioned therein).…”

Metaphors in Invasion Biology: Implications for Risk Assessment and Management of Non-Native Species

“…the assuring and definite tone of risk classifications sharply contrasts with the many uncertainties and complexities in the risk assessment processes (Liu, Sheppard, Kriticos, & Cook, 2011;Mcgeoch, Spear, Kleynhans, & Marais, 2012) and with the variability in risk classifications between countries (Verbrugge, Van der Velde, Hendriks, Verreycken, & Leuven, 2012). Risk protocols in force are of qualitative or semi-quantitative nature, translating qualitative data into numbers (Leung et al, 2012). Lack of data is a common problem and risk assessments often rely on expert judgments and anecdotal knowledge (Bayliss, Wilcox, Stewart, & Randall, 2012).…”