Spatio-temporal partitioning facilitates mesocarnivore sympatry in the Stara Planina Mountains, Bulgaria

2020 
Abstract The top trophic level in many terrestrial food webs is typically occupied by mammalian carnivores (Order Carnivora) that broadly affect and shape ecosystems through trophic cascades. Their inter-specific interactions can further complicate effects on community dynamics as a consequence of intra-guild competition. The capacity for competitive mammalian carnivores to segregate their hunting and activity regimes is in major part a function of their similarity, in terms of body-size and dietary niche; termed the ‘niche variation hypothesis’. In this study, we used camera-trapping to investigate intra-guild interactions and spatio-temporal partitioning among five mesocarnivores, the golden jackal (Canis aureus), European badger (Meles meles), red fox (Vulpes vulpes), European wildcat (Felis sylvestris) and stone marten (Martes foina), in the Stara Planina Mountains, Bulgaria. We collected a total of 444 images of golden jackals, 236 images of European badgers, 200 images of red foxes, 171 images of stone martens, and 145 images of European wildcats, from 6612 camera-days across fifteen camera-trapping stations. With respect to body size, the three smaller species (fox, wildcat and marten) were active in different time periods than the two larger competitors (jackal and badger) through both the warm and cold season. The more similar the trophic niche between species pairs (particularly relating to rodent consumption), the greater the spatio-temporal partitioning we observed within the pair; however, this adapted to seasonal dietary shifts. In conclusion, spatial and temporal (fine-scale and seasonal) niche partitioning appeared to reduce encounter probabilities and competition and may act to facilitate sympatric coexistence among this regional mesocarnivore guild.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    71
    References
    4
    Citations
    NaN
    KQI
    []