Plant diversity loss can alter higher trophic‐level communities via non‐random species interactions, which in turn may cascade to affect key ecosystem functions. These non‐random linkages might be best captured by patterns of phylogenetic diversity, which take into account co‐evolutionary dependencies. However, lack of adequate phylogenetic data of higher trophic levels hampers our mechanistic understanding of biodiversity relationships in species‐rich ecosystems. We used DNA barcoding to generate data on the phylogenetic diversity of lepidopteran caterpillars in a large‐scale forest biodiversity experiment in subtropical China. We analysed how different metrics of lepidopteran phylogenetic diversity (Faith's PD, MPD, MNTD) and taxonomic diversity were influenced by multiple components of tree diversity (taxonomic, functional, phylogenetic). Our data from six sampling periods represent 7,204 mitochondrial cytochrome c oxidase subunit I (COI) sequences of lepidopteran larvae, clustered into 461 molecular operational taxonomic units. Lepidopteran abundance, the effective number of species (irrespective of the focus on rare or common species) and Faith's PD and MPD (reflecting basal evolutionary splits), but not MNTD (reflecting recent evolutionary splits), significantly increased with experimentally manipulated tree species richness. Lepidopteran MNTD decreased with increasing tree MNTD. Path analyses showed that tree phylogenetic and functional diversity explained part, but not all of the effects of tree species richness on lepidopteran diversity. Importantly, tree diversity effects on lepidopteran diversity were to a large extent indirect, operating via changes in lepidopteran abundance. Synthesis. Our study shows that evolutionary dependencies determine the response of herbivore communities to changes in host plant diversity. Incorporating a wider range of diversity metrics both at the level of producers and consumers can thus help to develop a more comprehensive understanding of the functional consequences of biodiversity change across trophic levels. Moreover, the dependence of trophic linkages on herbivore abundances underlines the need to address the consequences of current declines in insect abundances for ecosystem structure and functioning.

Declining plant diversity alters ecological networks, such as plant–herbivore interactions. However, our knowledge of the potential mechanisms underlying effects of plant species loss on plant–herbivore network structure is still limited. We used DNA barcoding to identify herbivore–host plant associations along declining levels of tree diversity in a large‐scale, subtropical biodiversity experiment. We tested for effects of tree species richness, host functional and phylogenetic diversity, and host functional (leaf trait) and phylogenetic composition on species, phylogenetic and network composition of herbivore communities. We found that phylogenetic host composition and related palatability/defence traits but not tree species richness significantly affected herbivore communities and interaction network complexity at both the species and community levels. Our study indicates that evolutionary dependencies and functional traits of host plants determine the composition of higher trophic levels and corresponding interaction networks in species‐rich ecosystems. Our findings highlight that characteristics of the species lost have effects on ecosystem structure and functioning across trophic levels that cannot be predicted from mere reductions in species richness.

Although comprehensive phylogenies have proven an invaluable tool in ecology and evolution, their construction is made increasingly challenging both by the scale and structure of publically available sequences. The distinct partition between gene-rich (genomic) and species-rich (DNA barcode) data is a feature of data that has been largely overlooked, yet presents a key obstacle to scaling supermatrix analysis. I present a phyloinformatics framework for draft construction of a species-level phylogeny of insects (Class Insecta). Matrix-building requires separately optimized pipelines for nuclear transcriptomic, mitochondrial genomic, and species-rich markers, whereas tree-building requires hierarchical inference in order to capture species-breadth while retaining deep-level resolution. The phylogeny of insects contains 49,358 species, 13,865 genera, 760 families. Deep-level splits largely reflected previous findings for sections of the tree that are data rich or unambiguous, such as inter-ordinal Endopterygota and Dictyoptera, the recently evolved and relatively homogeneous Lepidoptera, Hymenoptera, Brachycera (Diptera), and Cucujiformia (Coleoptera). However, analysis of bias, matrix construction and gene-tree variation suggests confidence in some relationships (such as in Polyneoptera) is less than has been indicated by the matrix bootstrap method. To assess the utility of the insect tree as a tool in query profiling several tree-based taxonomic assignment methods are compared. Using test data sets with existing taxonomic annotations, a tendency is observed for greater accuracy of species-level assignments where using a fixed comprehensive tree of life in contrast to methods generating smaller de novo reference trees. Described herein is a solution to the discrepancy in the way data are fit into supermatrices. The resulting tree facilitates wider studies of insect diversification and application of advanced descriptions of diversity in community studies, among other presumed applications.