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Mosquito alert: leveraging citizen science to create a GBIF mosquito occurrence dataset
Título : | Mosquito alert: leveraging citizen science to create a GBIF mosquito occurrence dataset |
Autor : | Juznic Zonta, Zivko Sanpera Calbet, Isis Eritja, Roger Palmer, John R. B. Escobar, Agustí Garriga, Joan Alarcón Elbal, Pedro María |
Materias: | Culícidos; Mosquitoes; Ciencia abierta; Open science; Biodiversidad; Biodiversity; Ecología; Ecology; Taxonomía animal; Animal taxonomy |
Editorial : | GigaScience |
Citación : | Južnič-Zonta, Z., Sanpera-Calbet, I., Eritja, R., Palmer, J.R.B., Escobar, A., Garriga, J., Oltra, A., Richter-Boix, A., Schaffner, F., Torre, A. della, Miranda, M.A., Koopmans, M., Barzon, L., Ferre, F.B., Mosquito Alert Digital Entomology Network & Mosquito Alert Community. (2022). Mosquito alert: leveraging citizen science to create a GBIF mosquito occurrence dataset. Gigabyte. DOI: https://doi.org/10.46471/gigabyte.54 |
Resumen : | The Mosquito Alert dataset includes occurrence records of adult mosquitoes collected worldwide in 2014–2020 through Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes. Records are linked to citizen science-submitted photographs and validated by entomologists to determine the presence of five targeted European mosquito vectors: Aedes albopictus, Ae. aegypti, Ae. japonicus, Ae. koreicus, and Culex pipiens. Most records are from Spain, reflecting Spanish national and regional funding, but since autumn 2020 substantial records from other European countries are included, thanks to volunteer entomologists coordinated by the AIM-COST Action, and to technological developments to increase scalability. Among other applications, the Mosquito Alert dataset will help develop citizen science-based early warning systems for mosquito-borne disease risk. It can also be reused for modelling vector exposure risk, or to train machine-learning detection and classification routines on the linked images, to assist with data validation and establishing automated alert systems. |
URI : | http://hdl.handle.net/10637/15466 |
Derechos: | http://creativecommons.org/licenses/by/4.0/deed.es Open Access |
ISSN : | 2709-4715 (Electrónico) |
Fecha de publicación : | 30-may-2022 |
Centro : | Universidad Cardenal Herrera-CEU |
Aparece en las colecciones: | Dpto. Producción y Sanidad Animal, Salud Pública Veterinaria y Ciencia y Tecnología de los Alimentos |
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