Figure 1: Schematic sketch of ant observation sites in each study
location. Each of the three transects contained six sampling plots at
increasing distance to the adjacent old grassland (semi-natural habitat
remnant; grey area on top). Hatched squares (OG ) = first
sampling plot of each transect in old grassland (reference plots); black
squares (NG ) = sampling plots within newly established
grassland; grey squares (CN ) = sampling plots in adjacent
cereal field near to NG; white squares (CF ) = sampling plots in
control cereal field far from NG.
The new grasslands had been established in August 2016 in five winter
cereal fields directly adjacent to selected areas of old grassland. In
order to mimic the native plant community of the old grasslands, the new
grasslands were sown with a variety of seeds from 54 different plant
species native to the region (30% grasses, 55% herbaceous plants and
15% legumes). The new grasslands were mowed once every year in late
summer and the old grasslands in late June. The use of tillage in the
cereal field transects was avoided by the farmers during the sampling
period between April and June, but otherwise field management (such as
the use of pesticides) continued here.
2.2 Data recording/sampling
Recording of ant activity and species diversity was done by hand
collecting of worker ants with fine tweezers. Hand collection has been
discussed as the most efficient method for sampling ants
(Gotelli
et al. 2011). It generates results comparable to those from pitfall
traps
(Andersen,
1991; Sanders, Barton, & Gordon, 2001), and is not biased in favour of
behaviourally dominant species that monopolize food-resources
(Andersen,
1997), which may occur when using bait traps. Over the sampling period a
total of three consecutive survey runs on each of the 90 sampling plots
was performed, with 14 to 21 days between each run. For statistical
evaluation, the results of all three runs were aggregated for each
transect/habitat. On each sampling plot two 1x1 m sized quadrants around
the center were searched for foraging worker ants for four minutes each
per run. Worker ants active around nests were also sampled and the total
aboveground nest activity (in ants per four minutes) estimated. Prior to
the hand sampling also the vegetation cover (0-100 % of soil covered)
was estimated in a radius of 2 m around the plot center. All collected
individuals were preserved in 70 % ethanol and later identified to
species level according to
Seifert
(2018) using a stereo-microscope at 10-fold magnification.
Measuring of biocontrol potential was done with sticky-card experiments,
using adult Drosophila melanogaster (Meigen) flies as baits
(Lys,
1995). Over the sampling period a total of four consecutive survey runs
on each sampling plot was performed. For statistical evaluation, the
results of all four runs were aggregated for each sampling plot/habitat.
For each sticky-card, thirty flies were glued to the upper side of a 6x8
cm cardboard, which had a plastic underlay (to protect the card from
soil moisture), and fixed to the ground with a long nail. Flies were
glued to the cardboard with well-diluted fish-glue enabling
ground-dwelling predatory arthropods to remove the prey which guarantees
successful predation
(Lys,
1995). Each cardboard was covered by an enclosure with an appropriate
mesh size (1x1 cm) preventing the access of rodents and birds, thus
enabling effectively to measure predation on flies by arthropods
(Hulme,
1996). Two cardboards were placed on each sampling plot per survey and
exposed to predatory arthropods for two and a half to 3 hours.
Afterwards, predation rates (number of destroyed/killed flies) and the
estimated vegetation cover of the sampling plots (0-100 % of surface
covered) were recorded directly in the field.
2.3 Ant traits
Life history traits of all ant species encountered were taken from
Seifert
(2017) and (2018) and
Arnan
et al. (2017). All trait data and a detailed description of trait
categories are provided in the appendix: see Tables S1 and S2. The
subsequent statistical analysis determined the overall functional trait
space covered by the ant communities and examined in detail a selection
of traits which are closely linked to biocontrol services.
2.4 Statistical Analyses
All statistical analyses were conducted in the statistical programming
environment R (Version 3.6.2,
R
Core Team 2019). Cumulated ant species richness (ant species in
transects pooled per habitat type) was compared across habitat types
according to a Monte-Carlo randomization test procedure
(Manly,
2006) using the “rich”-package
(Rossi,
2011). To investigate how species replacement (turnover) and species
loss (nestedness) account for the variation in species composition (beta
diversity), the total dissimilarity expressed as Sørensen index (βSOR)
across the four habitats, as well as its respective turnover (βSIM) and
nestedness (βSNE) components, were calculated using the package
“betapart”
(Baselga
& Orme, 2012).
In order to study the influence of habitat type on ant species
composition of the transects, a constrained ordination analysis was
performed. A dummy species with an abundance of one in all samples was
added to the presence/absence data, to deal with low numbers of species
per transect
(Clarke,
Somerfield, & Chapman, 2006). Based on this dataset a Sørensen
dissimilarity matrix was created using the package “vegan”
(Oksanen
et al., 2018). Subsequently, a canonical analysis of principal
coordinates with two axes on the Sørensen dissimilarity matrix was
performed, with habitat type as a constraint variable. Differences
between the habitat types were tested for significance with a PERMANOVA
using “adonis” function, where the habitat type served as fixed factor
and the study region (Elsbach, Ollern) as random factor.
A principal component analysis of the species-trait data was performed
using the package “FactoMineR”
(Lê,
Josse, & Husson, 2008) and the first two principal coordinates of each
species plotted in a two-dimensional diagram. In order to display the
functional trait space covered by ants in the different study habitats,
a convex hull (polygon) was drawn around the respective species
communities. Differences between the habitat types were tested for
significance with a PERMANOVA based on an Euclidean distance matrix of
the species trait data.
Community weighted mean (CWM) values of selected ant species traits were
calculated using the “FD”-package
(Laliberté
& Legendre, 2010; Laliberté, Legendre, & Shipley, 2014). The
calculated CWM values refer to the average of species trait values at
each sampling transect weighed by the relative species abundance
(Lavorel
et al., 2008; Ricotta & Moretti, 2011). As the observed abundance of
foraging workers showed high fluctuations caused by e.g. life cycle
stage of ant colonies
(Seifert,
2018), the analysis was based on a pseudo-abundance matrix, which refers
to the presence of the respective species on the number of runs (0-3) on
each plot pooled per transect. Cereal field habitats were excluded from
the analysis, as a reliable calculation of CWM requires at least three
species, which was not given for the majority of transects of these
habitats. The analysis focussed on three distinct traits:proportion of animal-based resources in ant diet (Zoopha ;
food resources acquired via predation or scavenging, see Table S1),recruitment behaviour of workers (FS ; foraging strategy)
and colony size (CS ; number of individuals). In order to
increase the suitability of the CWM values for linear models and to
attain normal distribution, logit transformation was applied for the CWM
values of the traits Zoopha and FS and log transformation
for the trait CS . Using the CWM values of the selected traits as
response variable, the habitat type (OG, NG) as predictor variable and
study region as random factor three generalized linear mixed models
(GLMM) were created using the package “lmerTest”
(Kuznetsova,
Brockhoff, Christensen, & Jensen, 2019), which computes p-values via
the Satterthwaite approximation. To access p-values for the comparison
among fixed factor levels, Tukey’s post-hoc tests were conducted using
the package “multcomp”
(Hothorn,
Bretz, & Westfall, 2008). The same approach was applied for the
subsequent models.
To investigate the effect of habitat type and mean vegetation cover
(0-100 % of sampling plot surface covered) on predation intensity on
sticky cards, a predation rate (0-1) was calculated based on the number
of eaten flies per sampling plot summed across all four survey runs (n
per 240 flies in total; 30 flies x 2 cards per plot x 4 runs).
Subsequently, a GLMM was created, with the predation rate per sampling
plot as response variable, habitat type and logit transformed mean
vegetation cover of the sampling plot as fixed factors and study region
as random factor. Furthermore, the same GLMM approach was used to test
whether logit transformed mean vegetation cover showed significant
differences between habitat types. Fixed effect structures and GLMMs
were compared using the packages “multcomp” and “MuMIn”
(Bartoń,
2019).
To study the effect of habitat type on aboveground ant activity, the
number of observed worker ants per sampling plot was summed across all
three survey runs and transformed with Tukey’s Ladder of Powers, in
order to attain normally distributed values, using the package
“rcompanion”
(Magnificio
2019). Subsequently, a GLMM was created with Tukey transformed number of
observed workers per sampling plot as response variable, habitat type
and logit transformed mean vegetation cover of the sampling plot as
predictor variables and study region as random factor. Further, the
correlation of predation rate on sticky cards and Tukey transformed
aboveground ant activity was tested with a GLMM with study region as
random factor, again. Marginal and conditional R² values (R²m/R²c) of
the GLMM were calculated using the package “MuMIn”.