Résumé
Monitoring biodiversity is seldom comprehensive, as the spatio-temporal resolution needed to accurately reflect dynamic changes of these communities in diverse environments is often lacking. Citizen science offers a promising tool to help fill these gaps, engaging a wider audience in monitoring efforts and thus enhancing our understanding of earthworm ecology. However, a significant challenge arises as earthworms are difficult to identify to the species level in the field by non-experts, necessitating the use of morphotypes as taxonomic proxies. This study evaluates the reliability of earthworm classification into four earthworm morphotypes within the '500 ENI' (Non-intended Effects) Monitoring Network in France. The network relies on annual sampling conducted in agricultural lands by non-specialist participants with subsequent identification verification by earthworm taxonomists. Analyzing >48,000 individual earthworms collected over 950 plots, we calculated two indices: the misclassification rate (MR) and the undetected rate (UR) to assess the reliability of classification into earthworm morphotypes. The results indicated an average MR of 28 % and an average UR of 32 %, which both varied according to morphotypes. Endogeics had lower error rates compared to epigeics, anecics with a red anterior, and anecics with a black anterior. Our findings underscored the significant impact of sampler experience and earthworm community composition on the reliability of classification of individuals into morphotypes by citizens. The results highlight the critical need for enhanced support and guidance for participants with limited experience. Furthermore, we recommend providing additional training or resources to aid in morphotype classification, especially for earthworm communities exhibiting low abundance, low adult proportion, or low morphotype diversity. Encouraging participants to sample during periods favorable for detecting reliable total and adult abundances would also help optimize morphotype detection