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.

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.

Earth systems are nearing a global tipping point, beyond which the dynamics of biological systems will become unstable. One major driver of instability is species invasion, especially by organisms that act as “ecosystem engineers” through their modification of abiotic and biotic factors. In a mosaic landscape of non-invaded and invaded habitat, ecosystems modified through invasion may serve as “sink” habitat. To understand how native organisms respond to habitat that is becoming increasingly modified, it is essential to examine biological communities within invaded and non-invaded habitat, identifying compositional shifts between native and non-native taxa as well as measuring how modification has affected interactions among community members. Using dietary metabarcoding, our study examines the response of a native Hawaiian generalist predator to habitat modification by comparing biotic interactions across metapopulations of spiders collected in native forest and sites invaded by kahili ginger. Our study shows that, although there are shared components of the dietary community, spiders in invaded habitat are eating a less consistent and more diverse diet consisting of more non-native arthropods which are rarely or entirely undetected in spiders collected from native forest. Additionally, the frequency of novel interactions with parasites was significantly higher in invaded sites, reflected by the frequency and diversity of non-native Hymenoptera parasites and entomopathogenic fungi. The study highlights the role of habitat modification driven by an invasive plant in altering community structure and biotic interactions, appearing to serve as a “sink” for native arthropods and thereby threatening the stability of the ecosystem.

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.

The relative influence of geography, oceanography and environment on gene flow within sessile marine species remains an open question. Detecting subtle genetic differentiation at small scales relevant to marine protected areas is challenging in benthic populations due to large effective population sizes, general lack of resolution in genetic markers, potential microbial associations, and because barriers to dispersal often remain elusive. We genotyped the sponge species Suberites diversicolor using double digest restriction-site associated DNA sequencing (4,826 Single Nucleotide Polymorphisms, SNPs), compared it to same individuals using single markers (COI and ITS), and used previously published data on the associated microbial communities from a subset of the same locations. Studying S. diversicolor from marine lakes at different spatial scales (1-1,400 km), along a gradient of connection to the surrounding sea, and with different environmental regimes, we did not detect strong effects of geographic distance, permeability of seascape barriers or local environments in shaping population genetic structure. All markers detected two major lineages and geographic clustering over a large spatial scale. However, with the SNP dataset we provide new evidence of strong population structure even at scales <10km (average FST = 0.56), where previously none was detected. A lack of congruence between host population structure and microbial community patterns of S. diversicolor from the same locations was observed, suggesting they are on different eco-evolutionary tracks. Our results call for a reassessment of poorly dispersing benthic organisms that were previously assumed to be highly connected based on low resolution markers.