The Big Five: Species Distribution Models from Citizen Science Data as Tool for Preserving the Largest Protected Saproxylic Beetles in Italy

Abstract

Background. Volunteers’ participation in scientific research has increased in recent decades. Citizen science (CS) data have been used in quantitative ecology to analyse species ranges by means of species distribution models. We investigated the Italian distribution of five large saproxylic beetles (big five), to describe their niche space, paramount areas for their conservation, and conservation gaps. Methods. CS data from two projects, climate and environmental variables were used to produce Habitat suitability (HS) maps for each species and averaged HS maps. The big five’s conservation status was assessed interpolating HS maps with the distribution of protected areas, concomitantly identifying conservation gaps. Results. The pre-alpine and Apennines arcs, north-eastern Sicily and eastern Sardinia, were identified as conservation’s hotspots. Ranking HS levels from minimum to optimal, the extent of conservation gaps decreases as environmental suitability for the big five increases. Conclusions. For the first time in Italy, CS data have been used to investigate niche space of the largest protected saproxylic beetles and analyse the distribution of their suitable habitat. The resulting HS raster maps and vector layers, reporting HS value in all Italian protected areas (n° 3771), were provided and discussed, reporting an application example for conservation purposes.

Advantages and Drawbacks of Open-Ended, Use-Agnostic Citizen Science Data Collection: A Case Study

“…As we saw with our findings here, sightings tend to be biased to localities close to the observer's home, or to heavily used recreation areas (Di Cecco et al 2021; although see Geurts et al 2023). Thus, sampling may be too uneven to be useful for applications like species distribution modelling (Drew, Wiersma, and Huettmann 2011;although see Feng and Lougheed 2023;Redolfi De Zan et al 2023;and Serniak et al 2023 for examples of species distribution models developed with citizen science data). As well, the regional focus of NLNature proved in the end to be somewhat of a limitation.…”