Statistical analyses
We first compared total density and rarefied species diversity,
separately for beetles and spiders, between the six predefined flooding
categories (wet-wet, wet-dry, wet-wet/dry, dry-dry, dry-wet,
dry-wet/dry) using a GLM with negative binomial error distribution for
density and with an ANOVA for species diversity. We then modelled total
density and diversity in the same way as a function of the local
inundation frequency (within the 2x2 m2 pixel) and the
proportion of dry pixels at the different scales (6x6
m2 … 26x26 m2) as explanatory
variables. For models at each scale, we thereafter calculated
pseudo-R2 (density) and R2(diversity) and related these to the scale. The spatial scale with the
highest R2 was thereafter selected for further
analyses. In the third step, we again modelled total density and
rarefied species diversity as a function of the proportion of dry pixels
at the optimal scale but in these models, we also included the
inundation heterogeneity (at the optimal spatial scale) and
environmental factors (vegetation height and soil carbon content) as
explanatory variables. These models were simplified by excluding
non-significant variables. Finally, we used manyglm from the mvabund
(Wang, et al. 2012) to examine community responses (at a family level)
as a function of environmental variables and the optimal flooding scale.
These analyses were performed separately for beetles and spiders, and we
excluded families with few (<20) specimens. Finally, we repeated
the analyses using habitat preferences and species traits respectively
as response variables. All analyses were performed in R 4.2.2 (R Core
Team 2023).