Data from: Varyingly hungry caterpillars: predictive models and foliar chemistry suggest how to eat a rainforest

A long-term goal in evolutionary ecology is to explain the incredible
diversity of insect herbivores and patterns of plant host use in speciose
groups like tropical Lepidoptera. Here we used standardised food-web data,
multigene phylogenies of both trophic levels and plant chemistry data to
model interactions between Lepidoptera larvae (caterpillars) from two
lineages (Geometridae and Pyraloidea) and plants in species-rich lowland
rainforest in New Guinea. Model parameters were used to make and test
blind predictions for two hectares of exhaustively sampled forest. For
pyraloids we relied on phylogeny alone and predicted 54% of species level
interactions, translating to 79% of all trophic links for individual
insects, by sampling insects from only 15% of local woody plant diversity.
The phylogenetic distribution of host plant associations in polyphagous
geometrids was less conserved, reducing accuracy. In a truly quantitative
food-web only 40% of pair-wise interactions were described correctly in
geometrids. Polyphenol oxidative activity (but not protein precipitation
capacity), was important for understanding the occurrence of geometrids
(but not pyraloids) across their hosts. When both foliar chemistry and
plant phylogeny were included, we predicted geometrid-plant occurrence
with 89% concordance. Such models help to test macroevolutionary
hypotheses at the community level.