Spatio-temporal ecological niche modelling of multigenerational insect migrations

Modelling ecological niches of migratory animals requires incorporating a temporal dimension, in addition to space. Here, we introduce an approach to model multigenerational migratory insects using time-partitioned environmental variables (by months and years) and time- and behaviour-partitioned records (breeding records to model reproductive habitat). We apply this methodology to modelling the Palearctic-African migratory cycle of the Painted Lady butterfly (Vanessa cardui), based on data encompassing 36 years (646 breeding sites from 30 countries). Each breeding record is linked to a particular time (month and year), and the associated values of the bioclimatic variables are used for an ensemble modelling strategy, to finally obtain monthly projections. The results show obligated movements, mostly latitudinal, for the species' successive generations across the overall range, and only scattered locations show high probabilities of reproduction year-round. The southernmost reproductive areas estimated for the Palearctic-African migratory pool reach equatorial latitudes from December to February. We thus propose a potential distribution for the winter ‘missing generations' that would expand the V. cardui migration cycle to encompass about 15 000 km in latitude, from northernmost Europe to equatorial Africa. In summer, Europe represents the major temporary resource for V. cardui, while January and February show the lowest overall suitability values, and they are potentially the most vulnerable period for the species to suffer yearly bottlenecks. In summary, we demonstrate the potential of the proposed niche modelling strategy to investigate migratory movements of insects.This work was funded by the Committee for Research and Exploration of the National Geographic Society (grant no. WW1-300R-18), the British Ecological Society (grant no. LRB16/1015), the PRIC grants of the Fundació Barcelona Zoo, and by project CGL2016-76322 (AEI/FEDER, UE) to G.T. G.T. is supported by the MINECO programme Juan de la Cierva Incorporación (IJCI-2016-29083), the Marie Curie Actions FP7-People-2013 IOF (project 622716) and ‘La Caixa' Foundation (grant LCF/BQ/PR19/11700004).Peer reviewe