Collective and harmonized high throughput barcoding of insular arthropod biodiversity: Toward a Genomic Observatories Network for islands

Abstract

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, and as such can provide key insights into processes governing biodiversity. Novel high throughput sequencing (HTS) approaches are now emerging as powerful tools to overcome limitations in the availability of arthropod biodiversity data, and hence provide insights into these processes. Here, we explored how these tools might be most effectively exploited for comprehensive and comparable inventory and monitoring of insular arthropod biodiversity. We first reviewed the strengths, limitations and potential synergies among existing approaches of high throughput barcode sequencing. We considered how this could be complemented with deep learning approaches applied to image analysis to study arthropod biodiversity. We then explored how these approaches could 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 identified seven island biology themes at the interface of ecology, evolution and conservation biology, within which collective and harmonized efforts in HTS arthropod inventory could yield significant advances in island biodiversity research.

Towards understanding insect species introduction and establishment: A community‐level barcoding approach using island beetles

“…The approximately 95% increase in the number of introduced species within Canary laurel forest through barcode sequence matching highlights an underappreciated shortfall in arthropod biodiversity data—knowledge of species native or introduced status. In addition to previously recognized shortfalls and challenges (Cardoso et al, 2011; Emerson et al, 2022; Hortal et al, 2015), a lack of reliable data on whether species are native or introduced will also constrain efforts to effectively monitor, understand, manage and ultimately conserve biodiversity. It is unlikely that our results are an idiosyncrasy, or unique to our focal taxonomic group and habitat.…”

“…The extent to which this problem manifests itself across different taxonomic domains and geographic areas will be determined by the completeness of relevant barcode reference libraries. In this context, globally coordinated efforts to generate taxonomically assigned barcode and metabarcode sequence data for arthropods (Arribas et al, 2020; Emerson et al, 2022) are needed.…”

Insights into Ecological & Evolutionary Processes via community metabarcoding

“…Moving beyond descriptive statistics and simple statistical correlations to understand biodiversity processes, using such massive datasets will require adopting more powerful modelling approaches and machine learning inference methods, such as many of the manuscripts in this Special Issue have exemplified. For example, machine learning visual processing approaches may be effectively applied to image recognition analysis to study arthropod biodiversity as in Emerson et al (2022). Another supervised learning method was used to make predictions of sediment sample proximity to shipwrecks based on frequency of microbial taxa (Hampel et al, 2022).…”

“…For example, machine learning visual processing approaches may be effectively applied to image recognition analysis to study arthropod biodiversity as in Emerson et al. (2022). Another supervised learning method was used to make predictions of sediment sample proximity to shipwrecks based on frequency of microbial taxa (Hampel et al., 2022).…”

“…The overall promise of whole community metabarcoding is presented in Emerson et al. (2022) who highlight the potential to complement such high throughput barcode sequencing with deep learning image recognition workflows to advance the way we study terrestrial arthropod biodiversity as a whole.…”