Statistical analyses
All statistical analyses were conducted with R version 4.1.0
(2021-05-18) ”Camp Pontanezen”. To account for different isotopic
baselines among different land-use types, bulk isotope values
(δ13C and δ15N) of canopy arthropod
orders were normalized to trees or oil palms representing primary
producers by subtracting the isotopic signatures of leaves from the
respective plots. These leaf-calibrated isotope data are denoted as
Δ13C and Δ15N. To calculate mean,
minimum and maximum of Δ13C and Δ15N
for each land-use system in the two landscapes, Δ13C
and Δ15N values of canopy arthropod orders were
weighted by biomass and scaled between 0 and 1 for each community in a
plot (Cucherousset & Villéger 2015). To estimate biomass distribution
among trophic levels, we assigned ‘Δ15N classes’ from
the highest to the lowest Δ15N values, each with a
span of 3 ‰ (equivalent to approximately one trophic level) and summed
the biomass of taxa in each class for each plot. To test for differences
in abundance, biomass and isotopic composition between canopy arthropod
orders, land-use systems, landscapes and seasons, and for differences in
biomass distribution among trophic levels and land-use systems,
landscapes and seasons, we constructed linear mixed effects models in R
using the packages ‘lme4’ (Bates et al. 2015) and ‘lmerTest’ (Kuznetsova
et al. 2017). ‘Plot’ was included in the models as random effect.
Non-significant effects were eliminated from full models using the
‘step’ function, but without reducing random effects. To test for
differences among mean, minimum and maximum of Δ13C
and Δ15N, we used the R packages ‘nlme’ (Pinheiroet al. 2021) and ‘mass’ (Ripley et al. 2019) to construct
linear models with landscape, land-use and season as fixed factors.
For the reconstruction of the trophic structure of the studied taxa and
the calculation of energy fluxes among them see Box 1. We additionally
ran a sensitivity analysis to test if assumptions used for energy flux
calculations will influence the conclusions of our study (Supplementary
Text S1 and Fig. S2). To inspect differences between ecological
functions depending on land-use, region and season, we again constructed
linear mixed effects models with plot as random term (see above).