Climatic variables drive temporal patterns of α and β diversities of dung beetles.

Understanding the mechanisms underpinning spatiotemporal diversity patterns of biological communities is a major goal of ecology. We aimed to test two ecological hypotheses: (i) temporal patterns of β-diversity will mostly be driven by nestedness, with a loss of species from summer to winter, and (ii) nestedness values will correlate with climatic variables instead of turnover values, indicating either a loss of species during winter or a gain of species during summer. We sampled dung beetles using standardized sampling protocols along a year in four Atlantic forest sites: two at the northwest and two at the central region of Rio Grande do Sul state, southern Brazil. We partitioned temporal patterns of β-diversity into turnover and nestedness in order to investigate if community changes are driven by species substitution or gain/loss across time. Our results highlighted five main findings: (i) dung beetle composition varied more with sites than site geographic position; (ii) there was almost one and a half 'true' dung beetle assemblages regarding the spatial distribution of species weighed by abundance; (iii) we found a positive influence of mean temperature and a negative influence of relative humidity on both species richness and abundance; (iv) both spatial and temporal dissimilarity among sites were dominated by species replacement, while the relative importance of nestedness was higher in temporal than spatial patterns; (v) there was an effect of precipitation and relative humidity on temporal patterns of β-diversity components, but these effects were site-dependent. Contrary to our expectations, the β-diversity component of turnover dominated both spatial and temporal patterns in dung beetle dissimilarity among sites and months. Distinct climatic variables affected differently the α-diversity and β-diversity components of dung beetle assemblages. Partitioning β-diversity into temporal components is a promising approach to unveil patterns of the community dynamics and to produce insights on mechanisms underlying such patterns.