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Different facets of the same niche: Integrating citizen science and scientific survey data to predict biological invasion risk under multiple global change drivers
Authors:Mirko Di Febbraro  Luciano Bosso  Mauro Fasola  Francesca Santicchia  Gaetano Aloise  Simone Lioy  Elena Tricarico  Luciano Ruggieri  Stefano Bovero  Emiliano Mori  Sandro Bertolino
Institution:1. Environmetrics Lab, Department of Biosciences and Territory, University of Molise, Pesche, Isernia, Italy;2. Department of Research Infrastructures for Marine Biological Resources, Stazione Zoologica Anton Dohrn, Naples, Italy;3. Dipartimento Scienze della Terra e dell'Ambiente, Università di Pavia, Pavia, Italy;4. Environment Analysis and Management Unit, Guido Tosi Research Group, Department of Theoretical and Applied Sciences, Università degli Studi dell'Insubria, Varese, Italy;5. Museo di Storia Naturale e Orto Botanico, Università della Calabria, Rende, Cosenza, Italy;6. Department of Agricultural, Forest and Food Sciences, University of Turin, Turin, Italy;7. Department of Biology, University of Florence, Sesto Fiorentino, Italy;8. EBN Italia at Pro Natura, Turin, Italy;9. “Zirichiltaggi” Sardinia Wildlife Conservation NGO, Sassari, Italy;10. National Biodiversity Future Center (NBFC), Palermo, Italy;11. Department of Life Sciences and Systems Biology, University of Turin, Turin, Italy
Abstract:Citizen science initiatives have been increasingly used by researchers as a source of occurrence data to model the distribution of alien species. Since citizen science presence-only data suffer from some fundamental issues, efforts have been made to combine these data with those provided by scientifically structured surveys. Surprisingly, only a few studies proposing data integration evaluated the contribution of this process to the effective sampling of species' environmental niches and, consequently, its effect on model predictions on new time intervals. We relied on niche overlap analyses, machine learning classification algorithms and ecological niche models to compare the ability of data from citizen science and scientific surveys, along with their integration, in capturing the realized niche of 13 invasive alien species in Italy. Moreover, we assessed differences in current and future invasion risk predicted by each data set under multiple global change scenarios. We showed that data from citizen science and scientific surveys captured similar species niches though highlighting exclusive portions associated with clearly identifiable environmental conditions. In terrestrial species, citizen science data granted the highest gain in environmental space to the pooled niches, determining an increased future biological invasion risk. A few aquatic species modelled at the regional scale reported a net loss in the pooled niches compared to their scientific survey niches, suggesting that citizen science data may also lead to contraction in pooled niches. For these species, models predicted a lower future biological invasion risk. These findings indicate that citizen science data may represent a valuable contribution to predicting future spread of invasive alien species, especially within national-scale programmes. At the same time, citizen science data collected on species poorly known to citizen scientists, or in strictly local contexts, may strongly affect the niche quantification of these taxa and the prediction of their future biological invasion risk.
Keywords:alien species  biological invasions  citizen science  data science  ecological niche models  global change
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