The protozoans Giardia duodenalis and Cryptosporidium spp. are common causes of gastrointestinal disease in humans and animals. While both are commonly documented in domestic animals, few studies have analysed their presence in wildlife. To assess the prevalence of both parasites in wild boar (Sus scrofa) in the Valencian Community (eastern Spain), 498 wild boar faecal samples were collected from 2018 to 2022. Cryptosporidium spp. was detected by performing a nested PCR targeting a 578 bp sequence of the small subunit ribosomal RNA gene (SSU rRNA), followed by sequencing and phylogenetic analysis. For G. duodenalis, a qPCR amplifying a fragment of 62 bp from the SSU rRNA was employed. Positive samples were genotyped for glutamate dehydrogenase and β-giardin genes. Different epidemiological factors were considered potential modulating variables in the transmission of both parasites. G. duodenalis prevalence was 1.20%, while Cryptosporidium spp. prevalence reached 21.7%. Coinfection was observed in 0.2%. Genotyping of G. duodenalis isolates only detected genotype E. Two species of Cryptosporidium spp. were identified: Cryptosporidium scrofarum and Cryptosporidium suis. The results of this study demonstrate that the exposure to Cryptosporidium spp. in wild boars is high, particularly among young individuals belonging to the Typical Mediterranean climate. Moreover, the probability of infection is dependent on both the season and the density of wild boars. On the other side, exposure to G. duodenalis seems scarce and is influenced, in turn, by the climate. Both Cryptosporidium species detected in the present study have been reported in humans. Due to wild boar increasing in number and their colonisation of urban and peri-urban areas, this could represent an inherent health risk for the human population.

Urbanisation is reshaping ecosystems and increasing human–wildlife interactions. Wild boar (Sus scrofa), a highly adaptable species, is increasingly common in European cities, where it exploits natural and anthropogenic resources, often leading to conflict. Predicting when and where wild boars enter urban areas remains challenging, particularly using scalable tools such as remote sensing. Here, we show that temporal and spatial drivers of urban presence are decoupled in Barcelona over a 14-year period. Seasonal vegetation dynamics influenced the timing of urban incursions, with peaks in spring and late summer associated with changes in vegetation moisture and likely reinforced by increased energetic demands during reproduction and early lactation. However, remotely sensed vegetation indices captured these dynamics only partially, limiting their predictive power when used alone. Spatial variation in urban green area use was primarily explained by landscape structure, with proximity to streams and habitat fragmentation contributing similarly. Green areas near natural corridors were concentrated higher and had more variable presence, while heterogeneous landscapes likely facilitated repeated use by increasing access to foraging and refuge. Integrating remote sensing with landscape metrics can improve the anticipation and management of human–wildlife conflicts.

Urbanisation is reshaping ecosystems and increasing human–wildlife interactions. Wild boar (Sus scrofa), a highly adaptable species, is increasingly common in European cities, where it exploits natural and anthropogenic resources, often leading to conflict. Predicting when and where wild boar enters urban areas remains challenging, particularly using scalable tools such as remote sensing. Here we show that temporal and spatial drivers of urban presence are decoupled in Barcelona over a 14-year period. Seasonal vegetation dynamics influenced the timing of urban incursions, with peaks in spring and late summer associated with changes in vegetation moisture and likely reinforced by increased energetic demands during reproduction and early lactation. However, remotely sensed vegetation indices captured these dynamics only partially, limiting their predictive power when used alone. Spatial variation in urban green area use was primarily explained by landscape structure, with proximity to streams and habitat fragmentation contributing similarly. Green areas near natural corridors concentrated higher and more variable presence, while heterogeneous landscapes likely facilitated repeated use by increasing access to foraging and refuge. Integrating remote sensing with landscape metrics can improve anticipation and management of human–wildlife conflicts.