Functional and phylogenetic relationships link predators to plant diversity via trophic and non-trophic pathways.

Human-induced biodiversity loss negatively affects ecosystem function, but the interactive effects of biodiversity change across trophic levels remain insufficiently understood. We sampled arboreal spiders and lepidopteran larvae across seasons in 2 years in a subtropical tree diversity experiment, and then disentangled the links between tree diversity and arthropod predator diversity by deconstructing the pathways among multiple components of diversity (taxonomic, phylogenetic and functional) with structural equation models. We found that herbivores were major mediators of plant species richness effects on abundance, species richness, functional and phylogenetic diversity of predators, while phylogenetic, functional and structural diversity of trees were also important mediators of this process. However, the strength and direction differed between functional, structural and phylogenetic diversity effects, indicating different underlying mechanisms for predator community assembly. Abundance and multiple diversity components of predators were consistently affected by tree functional diversity, indicating that the variation in structure and environment caused by plant functional composition might play key roles in predator community assembly. Our study highlights the importance of an integrated approach based on multiple biodiversity components in understanding the consequences of biodiversity loss in multitrophic communities.

Tree dissimilarity determines multi-dimensional beta-diversity of herbivores and carnivores via bottom-up effects.

Global biodiversity decline and its cascading effects through trophic interactions pose a severe threat to human society. Establishing the impacts of biodiversity decline requires a more thorough understanding of multi-trophic interactions and, more specifically, the effects that loss of diversity in primary producers has on multi-trophic community assembly. Within a synthetic conceptual framework for multi-trophic beta-diversity, we tested a series of hypotheses on neutral and niche-based bottom-up processes in assembling herbivore and carnivore communities in a subtropical forest using linear models, hieratical variance partitioning based on linear mixed-effects models (LMMs) and simulation. We found that the observed taxonomic, phylogenetic and functional beta-diversity of both herbivorous caterpillars and carnivorous spiders were significantly and positively related to tree dissimilarity. Linear models and variance partitioning for LMMs jointly suggested that as a result of bottom-up effects, producer dissimilarities were predominant in structuring consumer dissimilarity, the strength of which highly depended on the trophic dependencies on producers, the diversity facet examined, and data quality. Importantly, linear models for standardized beta-diversities against producer dissimilarities implied a transition between niche-based processes such as environmental filtering and competitive exclusion, which supports the role of bottom-up effect in determining consumer community assembly. These findings enrich our mechanistic understanding of the 'Diversity Begets Diversity' hypothesis and the complexity of higher-trophic community assembly, which is fundamental for sustainable biodiversity conservation and ecosystem management.

Tree communities and functional traits determine herbivore compositional turnover.

There are many factors known to drive species turnover, although the mechanisms by which these operate are less clear. Based on comprehensive datasets from the largest tree diversity experiment worldwide (BEF-China), we used shared herbivore species (zeta diversity) and multi-site generalized dissimilarity modelling to investigate the patterns and determinants of species turnover of Lepidoptera herbivores among study plots across a gradient in tree species richness. We found that zeta diversity declined sharply with an increasing number of study plots, with complete changes in caterpillar species composition observed even at the fine spatial scale of our study. Plant community characteristics rather than abiotic factors were found to play key roles in driving caterpillar compositional turnover, although these effects varied with an increasing number of study plots considered, due to the varying contributions of rare and common species to compositional turnover. Our study reveals details of the impact of phylogeny- and trait-mediated processes of trees on herbivore compositional turnover, which has implications for forest management and conservation and shows potential avenues for maintenance of heterogeneity in herbivore communities.

Host functional and phylogenetic composition rather than host diversity structure plant-herbivore networks.

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.

Construction of a Species-Level Tree of Life for the Insects and Utility in Taxonomic Profiling.

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. [Data integration; data mining; insects; phylogenomics; phyloinformatics; tree of life.].

Resolving the phylogeny of a speciose spider group, the family Linyphiidae (Araneae).

For high-level molecular phylogenies, a comprehensive sampling design is a key factor for not only improving inferential accuracy, but also for maximizing the explanatory power of the resulting phylogeny. Two standing problems in molecular phylogenies are the unstable placements of some deep and long branches, and the phylogenetic relationships shown by robust supported clades conflict with recognized knowledge. Empirical and theoretical studies suggest that increasing taxon sampling is expected to ameliorate, if not resolve, both problems; however, sometimes neither the current taxonomic system nor the established phylogeny can provide sufficient information to guide additional sampling design. We examined the phylogeny of the spider family Linyphiidae, and selected ingroup species based on epigynal morphology, which can be reconstructed in a phylogenetic context. Our analyses resulted in seven robustly supported clades within linyphiids. The placements of four deep and long branches are sensitive to variations in both outgroup and ingroup sampling, suggesting the possibility of long branch attraction artifacts. Results of ancestral state reconstruction indicate that successive state transformations of the epigynal plate are associated with early cladogenetic events in linyphiid diversification. Representatives of different subfamilies were mixed together within well supported clades and examination revealed that their defining characters, as per traditional taxonomy, are homoplastic. Furthermore, our results demonstrated that increasing taxon sampling produced a more informative framework, which in turn helps to study character evolution and interpret the relationships among linyphiid lineages. Additional defining characters are needed to revise the linyphiid taxonomic system based on our phylogenetic hypothesis.

A protocol for species delineation of public DNA databases, applied to the Insecta.

Public DNA databases are composed of data from many different taxa, although the taxonomic annotation on sequences is not always complete, which impedes the utilization of mined data for species-level applications. There is much ongoing work on species identification and delineation based on the molecular data itself, although applying species clustering to whole databases requires consolidation of results from numerous undefined gene regions, and introduces significant obstacles in data organization and computational load. In the current paper, we demonstrate an approach for species delineation of a sequence database. All DNA sequences for the insects were obtained and processed. After filtration of duplicated data, delineation of the database into species or molecular operational taxonomic units (MOTUs) followed a three-step process in which (i) the genetic loci L are partitioned, (ii) the species S are delineated within each locus, then (iii) species units are matched across loci to form the matrix L × S, a set of global (multilocus) species units. Partitioning the database into a set of homologous gene fragments was achieved by Markov clustering using edge weights calculated from the amount of overlap between pairs of sequences, then delineation of species units and assignment of species names were performed for the set of genes necessary to capture most of the species diversity. The complexity of computing pairwise similarities for species clustering was substantial at the cytochrome oxidase subunit I locus in particular, but made feasible through the development of software that performs pairwise alignments within the taxonomic framework, while accounting for the different ranks at which sequences are labeled with taxonomic information. Over 24 different homologs, the unidentified sequences numbered approximately 194,000, containing 41,525 species IDs (98.7% of all found in the insect database), and were grouped into 59,173 single-locus MOTUs by hierarchical clustering under parameters optimized independently for each locus. Species units from different loci were matched using a multipartite matching algorithm to form multilocus species units with minimal incongruence between loci. After matching, the insect database as represented by these 24 loci was found to be composed of 78,091 species units in total. 38,574 of these units contained only species labeled data, 34,891 contained only unlabeled data, leaving 4,626 units composed both of labeled and unlabeled sequences. In addition to giving estimates of species diversity of sequence repositories, the protocol developed here will facilitate species-level applications of modern-day sequence data sets. In particular, the L × S matrix represents a post-taxonomic framework that can be used for species-level organization of metagenomic data, and incorporation of these methods into phylogenetic pipelines will yield matrices more representative of species diversity.

Resolving ambiguity of species limits and concatenation in multilocus sequence data for the construction of phylogenetic supermatrices.

Public DNA databases are becoming too large and too complex for manual methods to generate phylogenetic supermatrices from multiple gene sequences. Delineating the terminals based on taxonomic labels is no longer practical because species identifications are frequently incomplete and gene trees are incongruent with Linnaean binomials, which results in uncertainty about how to combine species units among unlinked loci. We developed a procedure that minimizes the problem of forming multilocus species units in a large phylogenetic data set using algorithms from graph theory. An initial step established sequence clusters for each locus that broadly correspond to the species level. These clusters frequently include sequences labeled with various binomials and specimen identifiers that create multiple alternatives for concatenation. To choose among these possibilities, we minimize taxonomic conflict among the species units globally in the data set using a multipartite heuristic algorithm. The procedure was applied to all available GenBank data for Coleoptera (beetles) including > 10 500 taxon labels and > 23 500 sequences of 4 loci, which were grouped into 11 241 clusters or divergent singletons by the BlastClust software. Within each cluster, unidentified sequences could be assigned to a species name through the association with fully identified sequences, resulting in 510 new identifications (13.9% of total unidentified sequences) of which nearly half were "trans-locus" identifications by clustering of sequences at a secondary locus. The limits of DNA-based clusters were inconsistent with the Linnaean binomials for 1518 clusters (13.5%) that contained more than one binomial or split a single binomial among multiple clusters. By applying a scoring scheme for full and partial name matches in pairs of clusters, a maximum weight set of 7366 global species units was produced. Varying the match weights for partial matches had little effect on the number of units, although if partial matches were disallowed, the number increased greatly. Trees from the resulting supermatrices generally produced tree topologies in good agreement with the higher taxonomy of Coleoptera, with fewer terminals compared with trees generated according to standard filtering of sequences using species labels. The study illustrates a strategy for assembling the tree-of-life from an ever more complex primary database.

Plant diversity enhances ecosystem multifunctionality via multitrophic diversity.

Ecosystem functioning depends on biodiversity at multiple trophic levels, yet relationships between multitrophic diversity and ecosystem multifunctionality have been poorly explored, with studies often focusing on individual trophic levels and functions and on specific ecosystem types. Here, we show that plant diversity can affect ecosystem functioning both directly and by affecting other trophic levels. Using data on 13 trophic groups and 13 ecosystem functions from two large biodiversity experiments-one representing temperate grasslands and the other subtropical forests-we found that plant diversity increases multifunctionality through elevated multitrophic diversity. Across both experiments, the association between multitrophic diversity and multifunctionality was stronger than the relationship between the diversity of individual trophic groups and multifunctionality. Our results also suggest that the role of multitrophic diversity is greater in forests than in grasslands. These findings imply that, to promote sustained ecosystem multifunctionality, conservation planning must consider the diversity of both plants and higher trophic levels.

An integrative bioinformatics pipeline shows that honeybee-associated microbiomes are driven primarily by pollen composition.

The microbiomes associated with bee nests influence colony health through various mechanisms, although it is not yet clear how honeybee congeners differ in microbiome assembly processes, in particular the degrees to which floral visitations and the environment contribute to different aspects of diversity. We used DNA metabarcoding to sequence bacterial 16S rRNA from honey and stored pollen from nests of 4 honeybee species (Apis cerana, A. dorsata, A. florea, and A. laboriosa) sampled throughout Yunnan, China, a global biodiversity hotspot. We developed a computational pipeline integrating multiple databases for quantifying key facets of diversity, including compositional, taxonomic, phylogenetic, and functional ones. Further, we assessed candidate drivers of observed microbiome dissimilarity, particularly differences in floral visitations, habitat disturbance, and other key environmental variables. Analyses revealed that microbiome alpha diversity was broadly equivalent across the study sites and between bee species, apart from functional diversity which was very low in nests of the reclusive A. laboriosa. Turnover in microbiome composition across Yunnan was driven predominantly by pollen composition. Human disturbance negatively impacted both compositional and phylogenetic alpha diversity of nest microbiomes, but did not correlate with microbial turnover. We herein make progress in understanding microbiome diversity associated with key pollinators in a biodiversity hotspot, and provide a model for the use of a comprehensive informatics framework in assessing pattern and drivers of diversity, which enables the inclusion of explanatory variables both subtly and fundamentally different and enables elucidation of emergent or unexpected drivers.