{Reference Type}: Journal Article
{Title}: Spatiotemporal dynamics of Ixodes ricinus abundance in northern Spain.
{Author}: Peralbo-Moreno A;Espí A;Barandika JF;García-Pérez AL;Acevedo P;Ruiz-Fons F;
{Journal}: Ticks Tick Borne Dis
{Volume}: 15
{Issue}: 6
{Year}: 2024 Jul 2
{Factor}: 3.817
{DOI}: 10.1016/j.ttbdis.2024.102373
{Abstract}: Ixodes ricinus is the most medically relevant tick species in Europe because it transmits the pathogens that cause Lyme borreliosis and tick-borne encephalitis. Northern Spain represents the southernmost margin of its main European range and has the highest rate of Lyme borreliosis hospitalisations in the country. Currently, the environmental determinants of the spatiotemporal patterns of I. ricinus abundance remain unknown in this region and these may differ from drivers in highly favourable areas for the species in Europe. Therefore, our study aimed to understand the main factors modulating questing I. ricinus population dynamics to map abundance patterns in northern Spain. From 2012 to 2014, monthly/fortnightly samplings were conducted at 13 sites in two regions of northern Spain to estimate spatiotemporal variation in I. ricinus questing abundance. Local abundance of I. ricinus was modelled in relation to variation in local biotic and abiotic environmental conditions by constructing generalised linear mixed models with a zero-inflated negative binomial distribution for overdispersed data. The different developmental stages of I. ricinus were most active at different times of the year. Adults and nymphs showed a peak of abundance in spring, while questing larvae were more frequent in summer. The main determinants affecting the spatiotemporal abundance of the different stages were related to humidity and temperature. For adults and larvae, summer seemed to be the most influential period for their abundance, while for nymphs, winter conditions and those of the preceding months seemed to be determining factors. The highest abundances of nymphs and adults were predicted for the regions of northern Spain with the highest rate of Lyme borreliosis hospitalisations. Our models could be the basis on which to build more accurate predictive models to identify the spatiotemporal windows of greatest potential interaction between animals/humans and I. ricinus that may lead to the transmission of I. ricinus-borne pathogens.