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).