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@article{1812519,
author = {Marceno', Corrado and Padulles Cubino, Josep and Chytrý, Milan and Genduso, Emanuele and Salemi, Dario and La Rosa, Alfonso and Gristina, Alessandro Silvestre and Agrillo, Emiliano and Bonari, Gianmaria and del Galdo, Gianpietro Giusso. and Ilardi, Vincenzo and Landucci, Flavia and Guarino, Riccardo},
article_location = {Hoboken},
article_number = {10},
doi = {http://dx.doi.org/10.1111/1365-2664.13896},
keywords = {databases; European Vegetation Archive (EVA); Facebook; flora; Mediterranean; plant traits; Sicily; social network},
language = {eng},
issn = {0021-8901},
journal = {Journal of Applied Ecology},
title = {Facebook groups as citizen science tools for plant species monitoring},
url = {https://doi.org/10.1111/1365-2664.13896},
volume = {58},
year = {2021}
}
TY - JOUR
ID - 1812519
AU - Marceno', Corrado - Padulles Cubino, Josep - Chytrý, Milan - Genduso, Emanuele - Salemi, Dario - La Rosa, Alfonso - Gristina, Alessandro Silvestre - Agrillo, Emiliano - Bonari, Gianmaria - del Galdo, Gianpietro Giusso. - Ilardi, Vincenzo - Landucci, Flavia - Guarino, Riccardo
PY - 2021
TI - Facebook groups as citizen science tools for plant species monitoring
JF - Journal of Applied Ecology
VL - 58
IS - 10
SP - 2018-2028
EP - 2018-2028
PB - Wiley
SN - 00218901
KW - databases
KW - European Vegetation Archive (EVA)
KW - Facebook
KW - flora
KW - Mediterranean
KW - plant traits
KW - Sicily
KW - social network
UR - https://doi.org/10.1111/1365-2664.13896
N2 - Social networks offer communication channels through which people share huge amounts of primary data that can be used for scientific analyses, including biodiversity research. To understand to what extent data extracted from social networks could complement data collected for scientific purposes, it is necessary to quantify the bias of such data. We analysed which plant traits increased the probability of a wild-growing plant species to be photographed and posted to a social network based on the data from an unstructured citizen science tool; a Facebook group focused on the vascular flora of Sicily (Italy). Then, we compared botanical data collected by this Facebook group members with data collected by scientists in 6,366 vegetation plots sampled across Sicily, stored in the EVA database. Our results suggested that data proceeding from the analysed Facebook group were affected by various sampling biases, which differed from the biases inherent to other types of biodiversity data such as those from vegetation plots. Facebook users recorded a higher proportion of red-listed and alien species than vegetation scientists. Therefore, social networks can provide a valuable complement to the data collected by scientists for research purposes. Synthesis and applications. Despite Facebook does not support geotagging and interface for data access and analysis, it is an invaluable source of biodiversity data that could complement those collected by professional researchers. The main advantage of data from social networks is their high dynamism, as they report large amounts of species occurrences in almost real time. Therefore, citizen science data from a Facebook group where the records are curated by expert volunteers can be used (a) for monitoring population dynamics of threatened and alien species; (b) as a source of additional data on rare species occurrences, particularly for plants that are attractive for amateur botanists, such as orchids; (c) for early warning systems of potential new invasions; and (4) for phenological studies, especially at the beginning of the flowering season.
ER -
MARCENO', Corrado, Josep PADULLES CUBINO, Milan CHYTRÝ, Emanuele GENDUSO, Dario SALEMI, Alfonso LA ROSA, Alessandro Silvestre GRISTINA, Emiliano AGRILLO, Gianmaria BONARI, Gianpietro Giusso. DEL GALDO, Vincenzo ILARDI, Flavia LANDUCCI and Riccardo GUARINO. Facebook groups as citizen science tools for plant species monitoring. \textit{Journal of Applied Ecology}. Hoboken: Wiley, 2021, vol.~58, No~10, p.~2018-2028. ISSN~0021-8901. Available from: https://dx.doi.org/10.1111/1365-2664.13896.
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