| Literature DB >> 35603331 |
Veronica Nanni1, Stefano Mammola2,3, Nuria Macías-Hernández2,4, Alessia Castrogiovanni5, Ana L Salgado6, Enrico Lunghi7, Gentile Francesco Ficetola5, Corrado Modica8, Riccardo Alba9, Maria Michela Spiriti10,11, Susanne Holtze12, Érica Munhoz de Mello13, Barbara De Mori10, Pierfrancesco Biasetti12, Dan Chamberlain9, Raoul Manenti5,14.
Abstract
Most people lack direct experience with wildlife and form their risk perception primarily on information provided by the media. The way the media frames news may substantially shape public risk perception, promoting or discouraging public tolerance towards wildlife. At the onset of the COVID-19 pandemic, bats were suggested as the most plausible reservoir of the virus, and this became a recurrent topic in media reports, potentially strengthening a negative view of this ecologically important group. We investigated how media framed bats and bat-associated diseases before and during the COVID-19 pandemic by assessing the content of 2651 online reports published across 26 countries, to understand how and how quickly worldwide media may have affected the perception of bats. We show that the overabundance of poorly contextualized reports on bat-associated diseases likely increased the persecution towards bats immediately after the COVID-19 outbreak. However, the subsequent interventions of different conservation communication initiatives allowed pro-conservation messages to resonate across the global media, likely stemming an increase in bat persecution. Our results highlight the modus operandi of the global media regarding topical biodiversity issues, which has broad implications for species conservation. Knowing how the media acts is pivotal for anticipating the propagation of (mis)information and negative feelings towards wildlife. Working together with journalists by engaging in dialogue and exchanging experiences should be central in future conservation management.Entities:
Keywords: Bats; Communication; Conservation; Mass media; Risk perception; SARS-CoV-2
Year: 2022 PMID: 35603331 PMCID: PMC9110911 DOI: 10.1016/j.biocon.2022.109591
Source DB: PubMed Journal: Biol Conserv ISSN: 0006-3207 Impact factor: 7.497
Fig. 1Graphic overview of recommendations to improve conservation communication by conservationists.
Fig. 2(a) Yearly proportion of reports on bat-associated diseases by country. (b) Total number of media reports regarding each topic in 2018, 2019 and 2020. Reports regarding disease transmission by bats increased significantly in 2020 (p = 2.2 e−16). (c) Word cloud of media coverage of bats families and species as mentioned in the news (when only the genus was mentioned it was grouped into the corresponding family).
Fig. 3Comparison between the spread of both news reports on bat-associated diseases (grey) and the COVID-19 pandemic (purple) in each country in 2020. Namibia was excluded because no reports on bat-associated diseases were located. We considered the temporal trend of both news on bat-associated disease and emerging cases of COVID-19, every 15 days. The cumulative curves for the media news and COVID-19 cases were estimated with a kernel density estimation. In the majority of countries, the first peak of news on bat-associated diseases news coincided with the first peak of the epidemic in China, regardless of whether the epidemic had arrived (χ21 = 0.3, P = 0.6). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 4Comparison between the spread of news reports containing pro-conservation messages (grey), and the COVID-19 pandemic (purple) in each country in 2020. Namibia was excluded because no pro-conservation reports were located. We considered the temporal distribution of both pro-conservation media reports, and emerging cases of COVID-19, every 15 days. The cumulative curves for pro-conservation news and COVID-19 cases were estimated with a kernel density estimation. Pro-conservation reports were significantly more frequent after the first exponential growth of the epidemic curve in each country (χ21 = 10.2, P = 0.001). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)