iNaturalist is a widely-utilized platform for data collection and sharing among non-professional volunteers and is widely employed in citizen science. This platform's data are also used in scientific studies for a wide range of purposes, including tracking changes in species distribution, monitoring the spread of alien-invasive species, and assessing the impacts of urbanization and land-use change on biodiversity. Lichens, due to their year-round presence on trees, soil and rocks, and their diverse shapes and colours, have captured the attention of iNaturalist users, and lichen records are widely represented on the platform. However, due to the complexity of lichen identification, the use of data collected by untrained, or poorly trained volunteers in scientific investigation poses concerns among lichenologists. To address these concerns, this study assessed the reliability of lichen identification by iNaturalist users by comparing records on the platform with identifications carried out by experts (experienced lichenologists) in three cities where citizen science projects were developed. Results of this study caution against the use of unchecked data obtained from the platform in lichenology, demonstrating substantial inconsistency between results gathered by iNaturalist users and experts.

Can we trust iNaturalist in lichenology? Evaluating the effectiveness and reliability of artificial intelligence in lichen identification

Isocrono, Deborah
Co-first
;
2023-01-01

Abstract

iNaturalist is a widely-utilized platform for data collection and sharing among non-professional volunteers and is widely employed in citizen science. This platform's data are also used in scientific studies for a wide range of purposes, including tracking changes in species distribution, monitoring the spread of alien-invasive species, and assessing the impacts of urbanization and land-use change on biodiversity. Lichens, due to their year-round presence on trees, soil and rocks, and their diverse shapes and colours, have captured the attention of iNaturalist users, and lichen records are widely represented on the platform. However, due to the complexity of lichen identification, the use of data collected by untrained, or poorly trained volunteers in scientific investigation poses concerns among lichenologists. To address these concerns, this study assessed the reliability of lichen identification by iNaturalist users by comparing records on the platform with identifications carried out by experts (experienced lichenologists) in three cities where citizen science projects were developed. Results of this study caution against the use of unchecked data obtained from the platform in lichenology, demonstrating substantial inconsistency between results gathered by iNaturalist users and experts.
2023
Inglese
Esperti anonimi
55
5
193
201
9
https://www.cambridge.org/core/journals/lichenologist/article/can-we-trust-inaturalist-in-lichenology-evaluating-the-effectiveness-and-reliability-of-artificial-intelligence-in-lichen-identification/B3FF5A93621A4684B5E6A114F7C89FFB
algorithm biodiversity citizen science plant blindness species identification taxonomy
PORTOGALLO
1 – prodotto con file in versione Open Access (allegherò il file al passo 6 - Carica)
262
3
Munzi, Silvana; Isocrono, Deborah; Ravera, Sonia
info:eu-repo/semantics/article
open
03-CONTRIBUTO IN RIVISTA::03A-Articolo su Rivista
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1935991
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