Statistical analysis
All statistical analyses were performed using R version 4.0.5 with the
packages: vegan v.2.5-7 (Oksanen et al., 2020), ade4 v. 1.7-18 (Dray et
al., 2007), lme4 v.1.1-27.1 (Bates et al., 2015), glmmADMB v.0.8.3.3.
(Bolker et al., 2012), MuMIn v.1.43.17 (Barton, 2016) statMatch 1.4.0
(D’Orazio) and ape v.5.5 (Paradis et al., 2021). Kettle holes were
classified into two hydroperiod-types based on the timespan of water
containment, i.e., permanent (kettle holes which contained water during
more than half of the sampling campaigns) and ephemeral (kettle holes
which contained water during half or less of the sampling campaigns).
Temporal stability of the species composition of a kettle hole was
assessed over two subsequent years (2019 and 2020), by comparing data
from water samples collected in the same month across both years (n=60
from 15 kettle holes) using diversity indices (Species richness S,
Shannon Index H’, and Simpson Index D1). A non-metric
multidimensional scaling (NMDS) approach based on Bray-Curtis
dissimilarities in combination with a Permanova was used to assess the
difference in community species compositions within kettle holes across
years. As these analyses did not reveal significant differences among
2019 and 2020, further analyses focused on the more densely sampled year
2019.
Seasonality in species numbers and composition of the open water
zooplankton communities within a year was assessed across the eight
sampling campaigns in 2019 (n= 91 metabarcoded samples from 24 kettle
holes). Species richness (S) and Shannon Index (H’) were related to
environmental parameters (pH, water temperature, surrounding field
crops, kettle hole size, kettle hole location, numbers of neighbouring
kettle holes in a 500 m radius, average wind direction/wind speed) with
a generalized linear mixed effects model (Gelman & Hill, 2006; Zuur et
al., 2009), using the lme4 package for Species richness (S) and glmmADMB
package for Shannon Index (H’). Kettle hole ID, referring to repeated
observations from the same kettle hole, was used as a random effect. The
diversity as response variable (H’) and predictor variables (pH, water
temperature, kettle hole size etc.) were Tukey-transformed to obtain a
distribution approximate to normal. To identify the model that explains
most of the variance, model selection was conducted based on the Akaike
information criterion (AIC), using the dedgre function in the R package
MuMIn (Barton, 2016). A NMDS approach based on Bray-Curtis
dissimilarities in combination with Permanovas and environmental
parameter correlation fitting (package vegan, function: envfit) was used
to assess the difference in species composition and putative drivers of
community assembly. To evaluate the influence of the individual kettle
hole within a season on community composition, a Permanova based on the
Bray-Curtis dissimilarities was conducted. To assess the impact of
geographic/environmental proximity/distance based on km and Gower’s
distance (Gower, 1971), a Mantel test was performed to correlate
community dissimilarities with geographic/environmental distances among
all pairs of kettle holes. To assess potential for dispersal from the
resting stages located in the sediment (“vertical dispersal”), we
compared soil and water samples from the same year (2019), using the
same diversity indices and the NMDS approach described above.