Ecological niche modelling of Culicoides imicola and future range shifts under climate change scenarios in Italy

Culicoides imicola is the main vector of viral diseases of livestock in Europe such as bluetongue (BT), African horse sickness and epizootic haemorrhagic disease. Climatic factors are the main drivers of C. imicola occurrence and its distribution might be subject to rapid shifts due to climate change. Entomological data, collected during BT surveillance, and climatic/environmental variables were used to analyse ecological niche and to model C. imicola distribution and possible future range shifts in Italy. An ensemble technique was used to weigh the performance of machine learning, linear and profile methods. Updated future climate projections from the latest phase of the Climate Model Intercomparison Project were used to generate future distributions for the next three 20‐year periods, according to combinations of general circulation models and shared socioeconomic pathways and considering different climate change scenarios. Results indicated the minimum temperature of the coldest month (BIO 6) and precipitation of the driest‐warmest months (BIO 14) as the main limiting climatic factors. Indeed, BIO 6 and BIO 14 reported the two highest values of variable importance, respectively, 9.16% (confidence interval [CI] = 7.99%–10.32%), and 2.01% (CI = 1.57%–2.44%). Under the worst‐case scenario of climate change, C. imicola range is expected to expand northward and shift away from the coasts of central Italy, while in some areas of southern Italy, environmental suitability will decrease. Our results provide predictions of C. imicola distribution according to the most up‐to‐date future climate projections and should be of great use to surveillance management at regional and national scales. Data from bluetongue surveillance and satellite imagery were used in a species distribution model framework to predict the suitable habitat of Culicoides imicola (1). A fine‐scale C. imicola distribution map was produced for central Italy (2), highlighting the most relevant biotic and abiotic variables to predict species occurrence (3). The relevant climatic variables were used to predict the Italian distribution of C. imicola along with its future range shifts, according to different climate change scenarios (4).