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

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 explore how these tools might be most effectively exploited 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.


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Authors: Emerson, Brent C., Borges, Paulo A.V., Cardoso, Pedro, Convey, Peter ORCIDORCID record for Peter Convey, deWaard, Jeremy R., Economo, Evan P., Gillespie, Rosie, Kennedy, Susan, Krehenwinkel, Henrik, Meier, Rudolf, Roderick, George, Strasberg, Dominique, Thébaud, Christophe, Traveset, Anna, Creedy, Thomas J., Meramveliotakis, Emmanouil, Noguerales, Víctor, Overcast, Isaac, Morlon, Hélène, Papadopoulou, Anna, Vogler, Alfried P., Arribas, Paula, Andújar, Carmelo

On this site: Peter Convey
1 December, 2023
Molecular Ecology / 32
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