Qin-Long Dai, Jian-Wei Li, Yi Yang, Min Li, Kan Zhang, Liu-Yang He, Jun Zhang, Bo Tang, Hui-Ping Liu, Yu-Xia Li, Li-Feng Zhu, Zhi-Song Yang, Qiang Dai
{"title":"Genetic Diversity and Prediction Analysis of Small Isolated Giant Panda Populations After Release of Individuals.","authors":"Qin-Long Dai, Jian-Wei Li, Yi Yang, Min Li, Kan Zhang, Liu-Yang He, Jun Zhang, Bo Tang, Hui-Ping Liu, Yu-Xia Li, Li-Feng Zhu, Zhi-Song Yang, Qiang Dai","doi":"10.1177/1176934320939945","DOIUrl":null,"url":null,"abstract":"<p><p>Release of individuals is an effective conservation approach to protect endangered species. To save this small isolated giant panda population in Liziping Nature Reserve, a few giant pandas have been released to this population. Here we assess genetic diversity and future changes in the population using noninvasive genetic sampling after releasing giant pandas. In this study, a total of 28 giant pandas (including 4 released individuals) were identified in the Liziping, China. Compared with other giant panda populations, this population has medium-level genetic diversity; however, a Bayesian-coalescent method clearly detected, quantified, and dated a recent decrease in population size. The predictions for genetic diversity and survival of the population in the next 100 years indicate that this population has a high risk of extinction. We show that released giant pandas can preserve genetic diversity and improve the probability of survival in this small isolated giant panda population. To promote the recovery of this population, we suggest that panda release should be continued and this population will need to release 10 males and 20 females in the future.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"16 ","pages":"1176934320939945"},"PeriodicalIF":1.7000,"publicationDate":"2020-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1176934320939945","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Evolutionary Bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1177/1176934320939945","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/1/1 0:00:00","PubModel":"eCollection","JCR":"Q4","JCRName":"EVOLUTIONARY BIOLOGY","Score":null,"Total":0}
引用次数: 5
Abstract
Release of individuals is an effective conservation approach to protect endangered species. To save this small isolated giant panda population in Liziping Nature Reserve, a few giant pandas have been released to this population. Here we assess genetic diversity and future changes in the population using noninvasive genetic sampling after releasing giant pandas. In this study, a total of 28 giant pandas (including 4 released individuals) were identified in the Liziping, China. Compared with other giant panda populations, this population has medium-level genetic diversity; however, a Bayesian-coalescent method clearly detected, quantified, and dated a recent decrease in population size. The predictions for genetic diversity and survival of the population in the next 100 years indicate that this population has a high risk of extinction. We show that released giant pandas can preserve genetic diversity and improve the probability of survival in this small isolated giant panda population. To promote the recovery of this population, we suggest that panda release should be continued and this population will need to release 10 males and 20 females in the future.
期刊介绍:
Evolutionary Bioinformatics is an open access, peer reviewed international journal focusing on evolutionary bioinformatics. The journal aims to support understanding of organismal form and function through use of molecular, genetic, genomic and proteomic data by giving due consideration to its evolutionary context.