Evolutionary Applications (Jun 2022)

Genomic insights into the genotype–environment mismatch and conservation units of a Qinghai–Tibet Plateau endemic cypress under climate change

  • Heng Yang,
  • Jialiang Li,
  • Richard Ian Milne,
  • Wenjing Tao,
  • Yi Wang,
  • Jibin Miao,
  • Wentao Wang,
  • Tsam Ju,
  • Sonam Tso,
  • Jian Luo,
  • Kangshan Mao

DOI
https://doi.org/10.1111/eva.13377
Journal volume & issue
Vol. 15, no. 6
pp. 919 – 933

Abstract

Read online

Abstract Habitat loss induced by climate warming is a major threat to biodiversity, particularly to threatened species. Understanding the genetic diversity and distributional responses to climate change of threatened species is critical to facilitate their conservation and management. Cupressus gigantea, a rare conifer found in the eastern Qinghai–Tibet Plateau (QTP) at 3000–3600 m.a.s.l., is famous for its largest specimen, the King Cypress, which is >55 m tall. Here, we obtained transcriptome data from 96 samples of 10 populations covering its whole distribution and used these data to characterize genetic diversity, identify conservation units, and elucidate genomic vulnerability to future climate change. After filtering, we identified 145,336, 26,103, and 2833 single nucleotide polymorphisms in the whole, putatively neutral, and putatively adaptive datasets, respectively. Based on the whole and putatively neutral datasets, we found that populations from the Yalu Tsangpo River (YTR) and Nyang River (NR) catchments could be defined as separate management units (MUs), due to distinct genetic clusters and demographic histories. Results of gradient forest models suggest that all populations of C. gigantea may be at risk due to the high expected rate of climate change, and the NR MU had a higher risk than the YTR MU. This study deepens our understanding of the complex evolutionary history and population structure of threatened tree species in extreme environments, such as dry river valleys above 3000 m.a.s.l. in the QTP, and provides insights into their susceptibility to global climate change and potential for adaptive responses.

Keywords