Overcoming Biases in Opportunistic Citizen Science for Studying Life History Traits of an Invasive Leaf-Mining Tree Insect Pest

The aim of this study was to determine whether opportunistic citizen science can support the detection of life history traits in invasive insects. Using the invasive leaf-mining micromoth <i>Macrosaccus robiniella</i> (Clemens 1859) (Lepidoptera: Gracillariidae) as a model species, we analyzed data from iNaturalist submitted by citizen scientists to assess the variability in its leaf mines on its native host, <i>Robinia pseudoacacia</i> L., 1753 (Fabaceae), across both the moth's invaded (Europe, North America-Eastern United States) and native range (North America-Southern and Western Unites States, Eastern Canada). We examined 86,489 photographs collected over the past 20 years to compare the occurrence and proportions of different <i>M. robiniella</i> leaf mine types between invaded and native ranges using three search variants: (I) <i>M. robiniella</i>, (II) all endophagous invasive insects associated with <i>R. pseudoacacia</i>, and (III) the host plant itself. The first two datasets revealed differences in the ratio of leaf mine types between Europe and North America (when analyzed separately for native and invaded areas), whereas the third dataset showed no significant differences in either the presence or proportion of mine types between invaded and native ranges. Leaf mine types atypical of <i>M. robiniella</i>, which resemble damage caused by other invasive insects such as <i>Parectopa robiniella</i> Clemens, 1863 (Lepidoptera: Gracillariidae) and <i>Obolodiplosis robiniae</i> (Haldeman, 1847) (Diptera: Cecidomyiidae)-also associated with <i>R. pseudoacacia</i>-have been observed in Europe for at least a decade. Our main conclusion is that, when investigating the life history traits of invasive herbivorous insects, focusing data collection on the host plant rather than on the insect species alone can reduce biases associated with opportunistic citizen science and help reveal true ecological patterns.