Uncertainty in invasive alien species listing
Lists of invasive alien species (IAS) are essential for preventing, controlling and reporting on the state of biological invasions. However, these lists suffer from a range of errors, with serious consequences for their use in science, policy and management. Errors and causes of uncertainty were collated and classified in IAS listing and consisted of: (i) human error (e.g. erroneous information in data entry), (ii) incomplete information searches, (iii) species misidentification, (iv) error on the information on the presence and extent of the species, (v) use of data and knowledge which are not documented or not readily or widely accessible, (vi) inadequate indigenous range information, (vii) limited data on biodiversity impacts, (viii) diverging definitions of “invasive”.
These errors have impacts on the number of IAS listed. Insufficient data on the identity, distribution and impacts of IAS is particularly problematic and may result in species being misidentified, alien species not being recognized, their impacts not being understood, or the level of risk being incorrectly categorized.
An important element for improving the reliability, transparency and credibility of expert contributions to the listing process is the use of models, systems, definitions and structured rules to improve the transparency and repeatability of listing decisions. Other important elements include training, awareness and deliberate consideration of potential biases and reasons underlying incorrect judgments and differences in opinion.
This study mentions that a distinction exists between “uncertainty due to a lack of knowledge” (epistemic) and “uncertainty due to variability inherent in the system under consideration” (ontogenic). Uncertainties in the IAS listing process are currently almost exclusively epistemic.
McGeoch M A, Spear D, Kleynhans E J ; Marais E (2012) Uncertainty in invasive alien species listing. Ecological applications 22(3), 959-971.