Ecological Niche Overlap in Sympatric Species (Zoological Archives: An International Journal, 2026)
Ecological niche theory predicts that co-existing species partition available resources along environmental and bioticaxes to reduce competitive overlap, yet the dimensionality of niche partitioning and the relative importance of differentniche axes in structuring co-existence remain contested. This study quantified ecological niche overlap among 28sympatric mammal species across 42 sites in temperate European forests (Central European mixed forest andPannonian broadleaf forest biomes) using hypervolume-based niche analysis (Hypervolume R package) on asix-dimensional trait space (body mass, dietary guild, activity period, stratum use, home range size, litter size) combinedwith species distribution modelling (MaxEnt; 12 environmental predictors) and camera trap activity data (12,840trap-nights; 2020-2024). Mean pairwise niche overlap (Bhattacharyya coefficient, BC) across 378 species pairs was0.184 +/- 0.084 -- significantly lower than a null model expectation of 0.284 +/- 0.042 (p < 0.001), confirming non-randomniche partitioning. Niche overlap was lowest between species from different dietary guilds (BC = 0.084 +/- 0.028) andhighest among congeners within the same guild (BC = 0.484 +/- 0.084). Environmental niche overlap (MaxEntdistribution overlap) was higher than trait-based niche overlap (BC = 0.384 +/- 0.064 vs. 0.184 +/- 0.084), indicating thatspecies sharing similar habitat requirements differ more strongly in functional traits -- consistent with habitat-mediatedcoexistence through functional complementarity. Camera trap temporal analysis confirmed that species pairs with hightrait overlap showed significantly less temporal co-occurrence (P24 co-occurrence index = 0.284 +/- 0.048) thanlow-overlap pairs (P24 = 0.684 +/- 0.064), consistent with temporal partitioning as an additional axis of nichedifferentiation. These results demonstrate multidimensional niche partitioning across European forest mammalcommunities and identify temporal activity patterns as an underappreciated coexistence mechanism.