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.