PCI Zoology

126

Title *

Improving species conservation plans under IUCN's One Plan Approach using quantitative genetic methodsuse asterix (*) to get italics

Authors *

Drew Sauve, Jane Hudecki, Jessica Steiner, Hazel Wheeler, Colleen Lynch, Amy A. ChabotPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"

Year *

2022

Picture *

Abstract *

<p>Human activities are resulting in altered environmental conditions that are impacting the demography and evolution of species globally. If we wish to prevent anthropogenic extinction and extirpation, we need to improve our ability to restore wild populations. Ex situ populations can be an important tool for species conservation. However, it is difficult to prevent deviations from an optimal breeding design and altered environments in captivity seem likely to lead to evolutionary or plasticity-induced phenotypic change that could make reintroduction more difficult. Quantitative genetic analysis can help disentangle the causes of phenotypic change in ex situ populations. Consequently, quantitative genetics can improve the management of these populations and the success of in situ population management actions that they support. In this review we outline methods that could be used to improve the management of in situ and ex situ populations in a One Plan Approach. We discuss how quantitative genetic models can help measure genetic variation, phenotypic plasticity, and social effects on phenotypes. Finally, we discuss how phenotypic change can be predicted using measurements of additive genetic variance and selection. While previous work has highlighted the value of ex situ populations for the field of quantitative genetics, we argue that quantitative genetics can, in turn, offer opportunities to improve management and consequently conservation of populations of species at risk. We show that quantitative genetic analyses are a tool that could be incorporated into and improve ex situ management practices.</p>

Indicate the full web address (DOI or URL) giving public access to these data (if you have any problems with the deposit of your data, please contact contact@zool.peercommunityin.org). In case all raw data are included in the preprint, indicate the DOI or URL of the preprint. *

You should fill this box only if you chose 'All or part of the results presented in this preprint are based on data'. URL must start with http:// or https://

Indicate the full web address (DOI or URL) giving public access to these scripts (if you have any problems with the deposit of your scripts, please contact contact@zool.peercommunityin.org). In case all raw scripts are included in the preprint, indicate the DOI or URL of the preprint. *

You should fill this box only if you chose 'Scripts were used to obtain or analyze the results'. URL must start with http:// or https://

Indicate the full web address (DOI, SWHID or URL) giving public access to these codes (if you have any problems with the deposit of your codes, please contact contact@zool.peercommunityin.org). In case all raw codes are included in the preprint, indicate the DOI or URL of the preprint. *

You should fill this box only if you chose 'Codes have been used in this study'. URL must start with http:// or https://

Keywords (optional)

Adaptive potential, ex situ, ecological genetics, gene flow, genetic groups, phenotypic plasticity, translocation, zoos, One Plan Approach, WCC 2020 Resolution 079

Methods that require specific expertise (optional)

NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).

Thematic fields *

Conservation biology, Ecology, Evolution, Genetics/Genomics

Suggested reviewers - Suggest up to 10 reviewers (provide names and Email addresses). (Optional)

e.g. John Doe john@doe.com

No need for them to be recommenders of PCI Zool. Please do not suggest reviewers for whom there might be a conflict of interest. Reviewers are not allowed to review preprints written by close colleagues (with whom they have published in the last four years, with whom they have received joint funding in the last four years, or with whom they are currently writing a manuscript, or submitting a grant proposal), or by family members, friends, or anyone for whom bias might affect the nature of the review - see the code of conduct

Opposed reviewers - Suggest up to 5 people not to invite as reviewers. (Optional)

e.g. John Doe john@doe.com

Submission date

2022-02-21 10:45:22

Recommender

Peter Galbusera

Reviewers

or Register
Submit a preprint