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Northward range extension for Durvillaea poha bull kelp: Response to tectonic disturbance?

Felix VauxDave CrawCeridwen I FraserJonathan M Waters
Published in: Journal of phycology (2021)
Understanding the forces that shape species distributions is increasingly important in a fast-changing world. Although major disturbance events can adversely affect natural populations, they can also present new opportunities, for example by opening up habitat for colonization by other lineages. Following extensive geographic sampling, we use genomic data to infer a range extension following disturbance for an ecologically important intertidal macroalgal species. Specifically, we genotyped 288 southern bull kelp (Durvillaea) plants from 28 localities across central New Zealand. All specimens from the North Island were expected to be D. antarctica, but unexpectedly 10 samples from four sites were identified as D. poha. Extensive sampling from the northern South Island (105 samples at five locations) confirmed the absence of D. poha north of the Kaikōura Peninsula. The North Island specimens of D. poha therefore reveal a biogeographic disjunction, some 150 km northeast of the nearest (South Island) population of this species. Based on strong geographic correspondence between these North Island samples and historic disturbance, we infer that tectonic upheaval, particularly earthquake-generated landslides, likely extirpated local D. antarctica and created an opportunity for a northward range expansion event by D. poha. Close phylogenomic relationships between this new North Island population and South Island samples support a geologically recent northward expansion, rather than a deeper evolutionary origin. These findings indicate the potential of large-scale disturbances to facilitate sudden biogeographic range expansions, and they emphasize the ability of genomic analyses with fine-scale sampling to reveal long-lasting signatures of past disturbance, dispersal, and colonization.
Keyphrases
  • tertiary care
  • genome wide
  • air pollution
  • single cell
  • machine learning
  • copy number
  • fine needle aspiration
  • ultrasound guided