Global Ecology and Conservation (Dec 2020)
In the black: Information harmonisation and educational potential amongst international databases for invasive alien species designated as of Union Concern
Abstract
Since 2016, the European Union (EU) has required Member States to prevent, control and eradicate selected invasive alien species (IAS) designated as Species of Union Concern. To improve these conservation efforts, online information systems are used to convey IAS information to the wider public, often as a means to bolster community-based environmental monitoring. Despite this, both the conformity and quality of information presented amongst online databases remain poorly understood. Here, we assess the harmonisation and educational potential of four major IAS databases (i.e., conformity of information and information quality, respectively): CABI, EASIN, GISD and NOBANIS. All databases were interrogated for information concerning 49 IAS of Union Concern. For each species, information presented within the evaluated databases was scored in relation to several key topics: morphological identification; EU distribution; detrimental impacts; control options; and the use of source material citations. Overall, scores differed significantly among databases and thus lacked harmonisation, whereby CABI ranked significantly highest based on the combined scores for all topics. In addition, CABI ranked highest for the individual topics of species identification, impacts, control options, and for the use of citations. EASIN ranked highest for species distribution data. NOBANIS consistently ranked as the lowest scoring database across all topics. For each topic, the highest scoring databases achieved scores indicative of detailed or highly detailed information, which suggests a high educational potential for the information portrayed. Nevertheless, the extent of harmonisation and quality of information presented amongst online databases should be improved. This is especially pertinent if online databases are to contribute to public participatory monitoring initiatives for IAS detection.
