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Abstract/Summary
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<jats:p>In this article the authors share their experiences, results, and lessons learned during the creation of a coastal biodiversity participatory monitoring initiative. Throughout 2019, we delivered five training workshops to 51 citizen scientists. Data collected by the citizens scientists were validated by checking its similarities against that gathered by specialists. High similarity values were found, indicating that, if proper training is provided, there is a great potential for citizen scientists to contribute biodiversity data with high value. During this process a certain level of variation in data produced by specialists was found, drawing attention to the need for prior alignment among specialists who may offer training for citizens. In addition, despite overall similar results between specialists and participants, some differences emerged in particular parts of the habitat; for example, the bivalve zones presented higher complexity and hence greater challenge. Identifying key challenges for participants is key to developing appropriate citizen science protocols. Here it is provided preliminary evidence that supports the use of the monitoring protocol to obtain biodiversity data gathered by citizen scientists, assuring its scientific quality. Enhancing participation by the community and specialists is key to further validate the approach and to effectively expand such protocols, enhancing the level of biodiversity data collection. In order to promote participation, and maintain citizen scientist engagement in the initiative, it is recommended the development of new investigations that assess the interests and motivations of the public to take part. It is also fundamentally important to have an effective strategy to communicate the results of participants’ monitoring and their applicability to local and global issues, thus maximizing the continuity of engagement of citizen scientists.</jats:p>
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Hinweis
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DeepGreen-ID: e89d403227784c30adc0797ca8dbfceb ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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