Data from: Null model analyses of temporal patterns of bird assemblages and their foraging guilds revealed the predominance of positive and random associations

Patterns of species associations have been commonly used to infer
interactions among species. If species positively co-occur they may form
predominantly neutral assemblages and such patterns suggest a relatively
weak role for compensatory dynamics. The main objective of this study was
to test this prediction on temporal samples of bird assemblages (n = 19,
10−57 years) by presence/absence and quantitative null models on
assemblage and guild levels. These null model outcomes were further
analysed to evaluate the effects of various dataset characteristics on the
outcomes of the null models. The analysis of two binary null models in
combination with three association indices revealed 20 % with significant
aggregations, 61 % with random associations and only 19 % with significant
segregations (n = 95 simulations). The results of the quantitative null
model simulations detected more none-random associations: 61 %
aggregations, 6 % random associations and 33 % segregations (n = 114
simulations). Similarly, quantitative analyses on guild levels showed 58 %
aggregations, 20 % segregations and 22 % random associations (n = 450
simulations). Bayesian GLMs detected that the outcomes of the binary and
quantitative null models applied to the assemblage analyses were
significantly related to census plot size, whereas the outcomes of the
quantitative analyses were also related to the mean population densities
of species in the data matrices. In guild level analyses, only 9 % of the
GLMs showed a significant influence of matrix properties (plot size,
matrix size, species richness, and mean species population densities) on
the null model outcomes. The results did not show the prevalence of
negative associations that would have supported compensatory dynamics.
Instead, we assume that a similar response of the majority of species to
climate-driven and stochastic factors may be responsible for the revealed
predominance of positive associations.