Parasites & Vectors (Sep 2020)
Incompletely observed: niche estimation for six frequent European horsefly species (Diptera, Tabanoidea, Tabanidae)
Abstract
Abstract Background More than 170 species of tabanids are known in Europe, with many occurring only in limited areas or having become very rare in the last decades. They continue to spread various diseases in animals and are responsible for livestock losses in developing countries. The current monitoring and recording of horseflies is mainly conducted throughout central Europe, with varying degrees of frequency depending on the country. To the detriment of tabanid research, little cooperation exists between western European and Eurasian countries. Methods For these reasons, we have compiled available sources in order to generate as complete a dataset as possible of six horsefly species common in Europe. We chose Haematopota pluvialis, Chrysops relictus, C. caecutiens, Tabanus bromius, T. bovinus and T. sudeticus as ubiquitous and abundant species within Europe. The aim of this study is to estimate the distribution, land cover usage and niches of these species. We used a surface-range envelope (SRE) model in accordance with our hypothesis of an underestimated distribution based on Eurocentric monitoring regimes. Results Our results show that all six species have a wide range in Eurasia, have a broad climatic niche and can therefore be considered as widespread generalists. Areas with modelled habitat suitability cover the observed distribution and go far beyond these. This supports our assumption that the current state of tabanid monitoring and the recorded distribution significantly underestimates the actual distribution. Our results show that the species can withstand extreme weather and climatic conditions and can be found in areas with only a few frost-free months per year. Additionally, our results reveal that species prefer certain land-cover environments and avoid other land-cover types. Conclusions The SRE model is an effective tool to calculate the distribution of species that are well monitored in some areas but poorly in others. Our results support the hypothesis that the available distribution data underestimate the actual distribution of the surveyed species.
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