Published March 3, 2021 | Version v1
Dataset Open

Genome, annotations and SNPs for the green peafowl and associated scripts

  • 1. Kunming Institute of Zoology
  • 2. Biodiversity Research Center, Academia Sinica
  • 3. Sun Yat-sen University
  • 4. Beijing Normal University

Description

Both anthropogenic impacts and historical climate change could contribute to population decline and species extinction, but their relative importance has yet to be determined. Emerging approaches based on genomic, climatic and anthropogenic data provide a promising analytical framework to address this question. This study applied such an integrative approach to examine potential drivers for endangerment of the green peafowl (Pavo muticus). Several demographic reconstructions based on population genomes congruently retrieved a drastic population declination since the mid-Holocene. Furthermore, comparison between historical and modern genomes suggested genetic diversity decrease during the last 50 years. However, climate-based ecological niche models predicted general range stationarity during these periods and imply little impact of climate change. Further analyses suggested that human activity intensities were negatively correlated with the green peafowl's effective population sizes and significantly associated with its survival statuses (extirpation or persistence). Archaeological and historical records corroborate the critical role of humans, leaving the footprint of low genomic diversity and high inbreeding in the surviving populations. This study sheds light on the potential deep-time effects of human disturbance on species endangerment and on the whole, offers immediately a multi-evidential approach in examining underlying forces for population declines.

Notes

Funding provided by: National Natural Science Foundation of China
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100001809
Award Number: 31872255

Funding provided by: National Natural Science Foundation of China
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100001809
Award Number: 31772437

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historical-modern_occurrences_dataset.csv

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