Unstructured citizen science reduces the perception of butterfly local extinctions: the interplay between species traits and user effort

Abstract

Abstract The detection of local extinctions is often hindered by the lack of long-term monitoring schemes, and thus relies on time series of presence data. Recently, citizen science has repeatedly shown its value in documenting species occurrences. We investigated the effectiveness of unstructured citizen science records in reducing the perception of local extinctions in butterfly populations across Italian National Parks. We addressed three research questions: (i) the ability of citizen science data to supplement existing knowledge to complete time series of occurrences, (ii) the impact on data collection of three species features (species size, distribution and length of flight period) determining their appearance, and (iii) the interplay between participant effort and species appearance in the amount of diversity recorded on the iNaturalist platform. Our analysis of 98,922 records of Italian butterflies (39,929 from literature and 58,993 from iNaturalist of which 7427 from National Parks) showed that the addition of iNaturalist data filled many recent gaps in time series, thus reducing the perception of potential local extinctions. Records from more engaged users encompassed a higher fraction of local biodiversity and were more likely to reduce the perception of local extinctions. User effort strongly interacted with species features in determining the frequency of records for individual species. In particular, more engaged users were less affected by species size. We provided updated butterfly checklists for Italian National Parks and a R package to calculate potential extinction upon time series. These results offer guidance for protected areas, conservationists, policymakers, and citizen scientists to optimize monitoring of local populations.