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Sentinel surveillance plays a critical role in monitoring pathogen circulation, assessing potential threats for species conservation, and evaluating the risk of spillover to human populations. This study provides a comprehensive exploration of helminth parasites in the Mediterranean-distributed hedgehog species Atelerix algirus in Mallorca, Balearic Islands. Using an integrated approach that combines necropsies and morphological and molecular identifications using the COI gene, we identified 11 helminth taxa in 135 hedgehogs, representing half of those that died at the local wildlife hospital in Mallorca between 2019 and 2022. We report an overall A. cantonensis prevalence of 11.5% and confirm the first case of a subclinical neuroangiostrongyliasis infection in a wildlife host. Infection prevalences over the year revealed that only two species, the nematode A. cantonensis and the cestode Mathevotaenia sp., had a seasonal pattern, with most A. cantonensis cases occurring in autumn and, to a lesser extent, Mathevotaenia sp. cases in winter. This pattern is probably due to the higher abundance and greater activity of snails and slugs (intermediate hosts) during these seasons, with important implications for public health and strategies for prevention of neuroangiostrongyliasis. Other key findings include a high prevalence (88.1%) of the lungworm Crenosoma striatum and detection of the acanthocephalan Moniliformis saudi for the first time in A. algirus. We anticipate that our study will facilitate surveillance efforts and clarify species identities in future studies. Given the lethal effects of A. cantonensis infection in hedgehogs, further studies are needed to evaluate the threat this parasite represents to European wildlife.

Citizen Science is a powerful tool for biodiversity research, as it facilitates data recording at large scales that would otherwise be impossible to cover by standard academic research. Despite its benefits, the accuracy of citizen science data remains a subject of concern among scientists, with varying results reported so far. Neither citizen science data nor academic records are immune to biases, which can significantly impact the quality and reliability of observations. Here, using insects in the Iberian Peninsula as a case study, we compare data collected by participatory platforms to those obtained through academic research projects, and assess their taxonomic, spatial, temporal, and environmental biases. Results show a prominent taxonomic bias in both academic and citizen science data, with certain insect orders receiving more attention than others. These taxonomic biases are conserved between different participatory platforms, as well as between groups of users with different levels of contribution performance. The biases captured by leading contributors in participatory platforms mirrored those of sporadic users and academic data. Citizen science data had higher spatial coverage and less spatial clustering than academic data, showing also clearer trends in temporal seasonality. Environmental coverage over time was more stable in citizen science than in academic records. User behaviour, preference, taxonomical expertise, data collection methodologies and external factors may contribute to these biases. This study shows the multifaceted nature of biases present in academic records and citizen science platforms. The insights gained from this analysis emphasize the need for careful consideration of these biases when making use of biodiversity data from different sources. Combining academic and citizen science data enhances our understanding of biodiversity, as their integration offers a more comprehensive perspective than relying solely on either dataset alone, especially since biases in these two types of data are not always the same. [ABSTRACT FROM AUTHOR]

Photographic identification methods are of highly importance when it comes to reduce the animal's stress, pain and possible injuries during or after marking techniques and thus to increase the reliability of demographic parameter estimates. There is plenty of software available for photo-identification, allowing individual identification in capture-mark-recapture (CMR) methods using body patterns, spots and marks unique to each individual. However, these non-invasive methods have hardly ever been used with arthropods. In this study, APHIS (Automated PHoto Identification Suite) has been assessed as a software capable of identifying individuals in different samplings during catch-and-release sessions with dead specimens under laboratory conditions. For this individual identification, SPM (Spot Pattern Matching) and ITM (Image Template Matching) procedures were tested; achieving a success of 100% and 95.35%, respectively. In SPM, the software itself matched the specimens almost automatically in half of the cases. However, it resulted more time-consuming than ITM during the pre-processing of images. On the other hand, ITM saves time during this step and still is able to detect recaptures accurately, yet more time may be needed when selecting the recaptures from the candidate list. Thus, it can be attested that APHIS is a competent and efficient software regarding photo-identification of Rhynchophorus ferrugineus and species with similar and unique individual colour patterns in their pronotum. [ABSTRACT FROM AUTHOR]