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.