Fig. 5 : Canopy energy flux (mean ± SE) within different feeding interaction types (algae-microbivory, herbivory, carnivory) and total energy flux in four land-use systems (rainforest, jungle rubber, rubber and oil palm) pooled for landscape and season.
Box 1: Trophic structure and calculation of energy fluxes
For reconstructing the trophic structure of the studied taxa and calculating energy fluxes among them, we generated predator-prey adjacency matrices for each plot in both the dry and rainy season based on (1) bulk stable isotope composition, (2) optimum predator-prey mass-ratios (PPMR) and (3) biomass-based preferences (Potapov 2022). Bulk isotope composition was used to calculate ‘optimum’ prey or food resource for each animal group by taking in account a trophic enrichment of 2.3 ‰ for δ15N and of 1 ‰ for δ13C between prey and predator (Tiunov 2007). Taxa with δ15N values below those of plant leaves were assumed to mainly feed on algae/microbes that have lower δ15N values than plants (Potapov et al . 2019). PPMR was used as a characteristic that reflects size-based predation (i.e., small predator feeds on small prey and large predator can also feed on larger prey) and optimum foraging strategy (i.e., balancing the energetic profit and handling efforts; Brose et al. 2008), commonly used in food-web ecology (Brose et al. 2019). The optimum PPMR was set to 100, implying that typical prey has 100 times less mass than the predator (Brose et al . 2008). Since this value is derived from laboratory experiments and modelling, we allowed for a very broad range for “optimum” prey (PPMR width), i.e. body mass range of the optimum prey was set to be triple the body mass range of the predator, representing a large niche. Parasitoids (parasitoid wasps/Braconidae and Diptera) and ants were ‘allowed’ to feed on larger prey and the range for potential prey was set two times wider than for other groups due to parasitic lifestyle/pack hunting (Potapov 2022). Biomass-based preferences were set up assuming that prey preference scaled with available prey biomass (Gauzens et al. 2019). The three optimum prey (adjacency) matrices above were multiplied to obtain a final food web matrix for each plot in each season representing feeding preferences among food web nodes (taxa). The food web matrices were subsequently used to calculate energy fluxes per square metre at plot-level using the R package ‘Fluxweb’ (Gauzens et al . 2019). When applying the ‘fluxing’ function, biomass preferences were set to ‘false’ as they were already accounted for in the food web matrices. Biomass losses were set to ‘true’, as metabolic losses of taxa were defined per unit of biomass. Per capita metabolic rates in W based on metabolic theory scaling (Brown 2004) were calculated assuming a constant temperature of 25.2 °C and using general coefficients for invertebrates (Jochum et al. 2021). The efficiency level was set to ‘predator’, i.e. the efficiencies with which the predator/consumer assimilates consumed prey were used. Temperature-corrected assimilation efficiencies of food for predators (0.915) and herbivores (0.573) were calculated using parameters from Lang et al. (2017) and the mean annual temperature measured by meteo-stations across all studied plots, i.e. 25.2 °C (Drescher et al. 2016). We assumed assimilation efficiencies of algae-microbivores to be similar to herbivores. To infer ecological functions, the fluxes to herbivores were summed up as herbivory, the fluxes to algae-microbivores were summed up as algae-microbivory and the fluxes to predators were summed up as predation.