Alexandre, M., Ferreira, E., Hipólito, D., Fonseca, C. & Rosalino, L.M. (2020) Humans do matter: determinants of red fox (Vulpes vulpes) presence in a western Mediterranean landscape.Mammal Research, 65, 203-214. DOI:10.1007/s13364-019-00449-y (IF2020 1,722; Q4 Zoology)
Habitat loss, due to landscape changes induced by human activities, is considered one of the main drivers of biodiversity decline. Thus, understanding how these changes affect top trophic-level species is essential to develop effective conservation strategy measures to overcome this problem. Mesocarnivores, as higher trophic-level species with crucial roles in ecosystem functioning, are a pivotal functional group in such strategies. Generalist mesocarnivores, such as the red fox (Vulpes vulpes), are excellent models to study species ecological adaption to landscapes moulded by humans. Using generalised linear mixed model (GLMM), we aim to understand how the landscape context affects the presence of this generalist species, in a Mediterranean ecosystem (northeastern Portugal) characterised by a combination of natural areas and traditional agricultural land uses. Based on scats’ distribution, we generated distribution models to test different ecological hypotheses—anthropic disturbance factors, altitude and land-cover patterns. According to our results, red foxes seem to have two distinct strategies: in forest-dominated areas, human activities have a negative effect (disturbance); in areas with a low percentage of forests, agriculture patches and the proximity to urban areas are the main drivers determining its presence, with a positive influence (food availability). Our results confirm the opportunistic character of this species and its high degree of adaptation. Further, the outcome also reveals that landscape context influences the detected pattern. Consequently, considering that populations of the same species are constrained by the same factors, independently of the landscape composition, will affect the effectiveness of management measures that will not account for landscape context effects.