DOI: 10.5061/dryad.n2z34tn32
title: Phytochemical diversity impacts herbivory in a tropical rainforest tree community

description: Metabolomics provides an unprecedented window into diverse plant
 secondary metabolites that represent a potentially critical niche
 dimension in tropical forests underlying species co-existence.
 Here, we used untargeted metabolomics to evaluate chemical
 composition of 358 tree species and its relationship with phylogeny
 and variation in light environment, soil nutrients, and
 insect-herbivore leaf damage in a tropical rain forest plot. We
 report no phylogenetic signal in most compound
 classes, indicating rapid diversification in tree metabolomes. We
 found that locally co-occurring species were more chemically dissimilar
 than random, and that local chemical dispersion and metabolite
 diversity was associated with lower herbivory, especially that of
 specialist insect herbivores. Our results highlight the role of
 secondary metabolites in mediating plant-herbivore interactions
 and their potential to facilitate niche differentiation in a
 manner that contributes to species coexistence. Furthermore, our
 findings suggest that specialist herbivore pressure is an important
 mechanism promoting phytochemical diversity in tropical forests.
description: Plant secondary metabolites
 were extracted and analyzed from leaves using ultra-high performance
 liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), following
 Sedio et al. (2021) with slight modifications. Three branches were taken
 from different directions, and 10 leaves per branch were sequentially
 selected from top to bottom on each branch to avoid overestimating the
 percent herbivory and
 ignoring certain types of herbivores (Woodman & Fernandes, 1991).
 All collected leaves were scanned, and the leaf area was calculated using
 ImageJ software (Abramoff et al., 2004). The percent herbivory for each
 leaf was calculated as the ratio of damaged area to estimated undamaged
 area, with higher percentages indicating greater herbivore damage
 (Kurokawa & Nakashizuka, 2008). We classified herbivore damage
 into broad categories (e.g., hole feeding, margin feeding) according to
 Labandeira et al. (2007) and further divided them into three diet-breadth
 categories: generalized, intermediate, or specialized (Labandeira et al.,
 2007; Wang et al., 2022). We used published data from our laboratory for 9
 soil nutrient variables in the plot (Hu et al., 2012, Yang et al., 2014),
 including pH, total N, total P, total K, available N, extractable P,
 extractable K, total C and bulk density. Light availability was measured
 using hemispherical photographs taken with a digital camera and analyzed
 using the Gap Light Analyzer Version 2.0 software to calculate the canopy
 gap fraction, representing the non-vegetated portion of the image (Frazer
 et al., 2000). To quantify variation in percent herbivory and chemical
 diversity in different habitats, the plot was divided into slope, ridge
 and valley habitats from Yang et al.
description: # Phytochemical diversity impacts herbivory in a tropical rainforest tree
 community
 [https://doi.org/10.5061/dryad.n2z34tn32](https://doi.org/10.5061/dryad.n2z34tn32) ## Description of the data and file structure 1\. In the El\_submitted file\, qua was plot name; species richness is the species richness in each plot; scale\_herbivory\.ratio is herbivory ratio data which was scaled; scale\(generalized\.ratio\) was scaled generalized ratio; scale\(specialized\.ratio\) was scaled specialized ratio; soil\.pc1\, soil\.pc2 and soil\.pc3 were the first three axes after the principal component analysis of soil nutrient indicators; scale\_PSMshannon was Shannon index of plant secondary metabolites which was scaled; all\.classified\.nri was the net\-relatedness index of all classified compounds; all\.chemical\.diversity was diversity of all chemical compounds; Alkaloids\.diversity\, Amino\.diversity\, Carbohydrates\.diversity\, Fattyacids\.diversity\, Polyketides\.diversity\, Shikimates\.diversity\, Terpenoids\.diversity was diversity of Alkaloids\, Amino\, Carbohydrates\, Fattyacids\, Polyketides\, Shikimates\, Terpenoids\. 2\. In pathway\_percent file\, pathway was different classified chemical compound; number was the number of compounds in different classes; percent was the percentage of different classes of compounds in the total compounds\.   3\. In 7type\_boxplot file\, adj\.nri was the net\-relatedness index after removing the spatial autocorrelation; in the type\, aap means amino acids and peptides\, alkaloids mean alkaloids\, carbohy means carbohydrates\, fa means fatty acids\, poly means polyketides\, sp means shikimates and phenylpropanoids\, terp means terpenoids\. ## Sharing/Access information Data was derived from the following sources: [https://datadryad.org/stash/share/TdkGT62wy0UECZQu2Rw08UvtQIIktNmS8jBu7fd7Kuo](https://datadryad.org/stash/share/TdkGT62wy0UECZQu2Rw08UvtQIIktNmS8jBu7fd7Kuo)