This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.3897/neobiota.71.69422. This is version 1 of this Preprint.
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Abstract
Blacklists of invasive alien species are a popular tool to manage and prevent biological invasions. Furthermore, by providing accessible examples of invasive alien species and by having a certain media resonance, they can in principle raise the awareness and make laypeople curious towards this topic. However, no study ever tested for this side-effect of blacklists. We tested if the implementation of the first blacklist of invasive alien species of the European concern, by the European Union in August 2016, increased visits to Wikipedia pages about invasive alien mammals in Italy. We adopted Bayesian Structural Time Series, using native mammals as a synthetic control, and we considered both invasive alien mammals that appeared on the list and those which were not included.
Following the publication of the first European blacklist of invasive alien species, there was no increase in the amount of weekly visits to the Wikipedia pages about invasive mammals. This was true both for species that were included in the list and those which were not. Rather increased search volumes were syncronous to other events that had media resonance. Our results indicate that important policymaking initiatives, do not necessarily raise public awareness about biological invasions, even when these policies, such as blacklists, are easy to understand and have a certain media coverage. We emphasize the importance of coupling them with adequate communication campaigns and also to develop communication guidelines for the media.
DOI
https://doi.org/10.32942/osf.io/t4hm9
Subjects
Environmental Studies, Social and Behavioral Sciences
Keywords
Bayesian structural time series, blacklist, causal impact analysis, Europe, invasive alien mammal, Italy, Wikipedia
Dates
Published: 2020-09-16 22:12
License
CC-By Attribution-NonCommercial-NoDerivatives 4.0 International
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Data and Code Availability Statement:
Data can be downloaded from Wikipedia, using the reproducible software code.
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