Global arthropod decline demands effective biodiversity monitoring strategies. However, most current monitoring approaches do not provide an exhaustive picture of arthropod community structure. In particular, biotic interactions and temporal patterns of biodiversity change are still poorly understood due to a lack of suitable monitoring approaches. Here we explore the possibility of addressing these two shortfalls using spiders, one of the most important predators of terrestrial arthropods, as natural samplers for arthropod community DNA. We conducted several experiments comparing the recovered community composition between spider gut contents and traditional monitoring methods. Additionally, we used archived spiders that were over a decade old to assess the preservation of prey DNA in spiders over time. Spiders proved to be highly efficient natural DNA samplers with gut content metabarcoding revealing similar community composition and α- and β-diversity compared to metabarcoding results of traditional methods. Unique arthropod taxa were detected by spider gut contents and traditional methods respectively, indicating that spider gut contents are not replacements but valuable complements to traditional sampling. Besides providing an overview of local diversity patterns, comparing gut contents across spider species simultaneously generates an overview of trophic interactions and dietary ecology in arthropod communities. Furthermore, well-preserved archived spiders can effectively reconstruct historical diets, making them valuable for studying past dietary diversity. Historical collections of spiders thus constitute time capsules of spider dietary diversity. Spider natural samplers can overcome critical shortfalls in biodiversity monitoring and contribute to our future understanding of community assembly across space and time.

Flower-derived eDNA holds great promise as a rapid and non-invasive tool for monitoring pollinators and their plant-associations. However, pollinators often only briefly interact with a plant and leave little eDNA, making them particularly challenging to detect. In addition, taxonomic biases in eDNA deposition and PCR amplification prevent quantitative analysis of pollinator diversity. These limitations have so far precluded the widespread use of eDNA in pollinator monitoring. Comparing flower-derived eDNA with conventional monitoring in flower strips, we here explore the utility of eDNA to detect community diversity, species abundances and ecological specificity of plant-associated arthropods. We show that read abundances are a bad predictor of true abundances at the community level. Instead, the occupancy of individual species in replicated flower eDNA samples provides reliable quantitative estimates of pollinator biodiversity and detects their ecological specificity very well. Also, we find that pollinator eDNA can be collected non-invasively, by washing off from flowers in the field. Our work highlights eDNA analysis as a powerful tool for the rapid future monitoring of plant-arthropod interactions and plant-pollinator networks.

Spiders are a hyper-diverse taxon and among the most abundant predators in nearly all terrestrial habitats. Their success is often attributed to key developments in their evolution such as silk and venom production and major apomorphies such as a whole-genome duplication. Resolving deep relationships within the spider tree of life has been historically challenging, making it difficult to measure the relative importance of these novelties. Whole-genome data offer an essential resource in these efforts, but also for functional genomic studies. Here, we present de novo assemblies for three spider species: Ryuthela nishihirai (Heptathelidae), a representative of the ancient Mesothelae, the suborder which is sister to all other extant spiders; Uloborus plumipes (Uloboridae), a cribellate orbweaver whose phylogenetic placement is especially challenging; and Cheiracanthium punctorium (Cheiracanthiidae), which represents only the second family to be sequenced in the hyper-diverse Dionycha clade. These genomes fill critical gaps in the spider tree of life. Using these novel genomes along with 25 previously published ones, we examine two proposed drivers of diversification: spidroin gene and structural hox cluster diversity. Our analyses show that spidroin diversification as well as hox cluster duplication and restructuring mirror spider diversification, hence suggesting a key role in the evolutionary success of the group. Our assemblies provide critical genomic resources to facilitate deeper investigations into spider evolution. The near chromosome-level genome of the “living fossil” R. nishihirai represents an especially important step forward, offering new insights into the origins of spider traits.

The Special Issue brought together papers that highlighted the power of high-throughput sequencing (HTS) data to address classic questions in ecology and evolution, and/or use models/theory to infer key ecological and evolutionary processes, and make predictions, particularly focused on metabarcoding (amplicon) datasets in conjunction with complementary -omics data types. We highlight key papers that show the power of the new technology to address questions related to: (1) community assembly, and the interplay between competition, environmental filtering, and neutral processes, that can be inferred from the data, and how these change according to environmental conditions, and across successional and extended evolutionary time. (2) Interaction networks, and how these can show predictable changes over similar spatial and temporal gradients, providing insights into questions of biotic resilience. Studies also examined (3) cross scale interactions and those involving hosts and their microbiomes, with the critical development being the ease of comparison and integration across scales of organismic complexity, allowing insights at one scale to inform the other. The approach is also amenable to (4) studies of invasive species and biotic homogenization, providing insights of shifts in alpha and beta diversity across a wide range of spatial scales.

Our limited knowledge about the ecological drivers of global arthropod decline highlights the urgent need for more effective biodiversity monitoring approaches. Monitoring of arthropods is commonly performed using passive trapping devices, which reliably recover diverse communities, but provide little ecological information on the sampled taxa. Especially the manifold interactions of arthropods with plants are barely understood. A promising strategy to overcome this shortfall is environmental DNA (eDNA) metabarcoding of arthropods from plant material they have interacted with. However, the accuracy of this approach has not been sufficiently tested. In four experiments, we exhaustively test the comparative performance of plant-derived eDNA from surface washes of plants and homogenized plant material against traditional monitoring approaches. We show that the recovered communities of plant-derived eDNA and traditional approaches only partly overlap, with eDNA recovering various additional cryptic taxa. This suggests eDNA as a useful complementary tool to traditional monitoring. Despite the differences in recovered taxa, estimates of community α- and β-diversity between both approaches are well correlated, highlighting the utility of eDNA as a broad scale tool for community monitoring. Last, eDNA outperforms traditional approaches in the recovery of plant-specific arthropod communities. Unlike traditional monitoring, eDNA revealed fine-scaled community differentiation between individual plants and even within plant compartments. Especially specialized herbivores are better recovered with eDNA. Our results highlight the value of plant derived eDNA analysis for large-scale biodiversity assessments that include information about community level interactions.

The term ‘habitat fragmentation’ is frequently associated with the biologically-destructive activities of human development, but an important evolutionary hypothesis posits that much of the biodiversity we see today was generated by episodic, natural habitat fragmentation. This hypothesis suggests that fragmentation can serve as a ‘crucible of evolution’ through the amplifying feedbacks of colonization, extinction, adaptation, and speciation. Interrogating the generality of this hypothesis requires measuring the repercussions of fragmentation at intra- and interspecific levels across entire communities. We use DNA metabarcoding to capture these repercussions from the scales of intraspecific differentiation to community composition in a megadiverse, ecologically foundational group, arthropods, using a natural habitat fragmentation experiment on patches of wet forest isolated by contemporary Hawaiian lava flows (kīpuka). We find a pronounced effect of area in kīpuka cores, where the taxonomic richness supported by a kīpuka scales with its size. Kīpuka cores exhibit higher intra- and interspecific turnover over space than continuous forest. Additionally, open lava, kīpuka edges, and the cores of small kīpuka (which are essentially entirely “edge”) host lower richness, are more biologically homogeneous, and have higher proportions of non-native taxa than kīpuka cores. Our work shows how habitat fragmentation isolates entire communities of habitat specialists, paving the way for genetic differentiation. Parsing the extent to which differentiation in kīpuka is driven by local adaptation versus drift provides a promising future avenue for understanding how fragmentation, and the different isolated communities created through this process, may lead to speciation in this system.

Our current understanding of ecological and evolutionary processes underlying island biodiversity is heavily shaped by empirical data from plants and birds, although arthropods comprise the overwhelming majority of known animal species. This is due to inherent problems with obtaining high-quality arthropod data. Novel high throughput sequencing approaches are now emerging as powerful tools to overcome such limitations, and thus comprehensively address existing shortfalls in arthropod biodiversity data. Here we explore how, as a community, we might most effectively exploit these tools for comprehensive and comparable inventory and monitoring of insular arthropod biodiversity. We first review the strengths, limitations and potential synergies among existing approaches of high throughput barcode sequencing. We consider how this can be complemented with deep learning approaches applied to image analysis to study arthropod biodiversity. We then explore how these approaches can be implemented within the framework of an island Genomic Observatories Network (iGON) for the advancement of fundamental and applied understanding of island biodiversity. To this end, we identify seven island biology themes at the interface of ecology, evolution and conservation biology, within which collective and harmonised efforts in HTS arthropod inventory could yield significant advances in island biodiversity research.