Literature DB >> 32635865

Precipitation and vegetation shape patterns of genomic and craniometric variation in the central African rodent Praomys misonnei.

Katy Morgan1, Jean-François Mboumba2, Stephan Ntie2, Patrick Mickala2, Courtney A Miller1, Ying Zhen3, Ryan J Harrigan3, Vinh Le Underwood3, Kristen Ruegg3, Eric B Fokam4, Geraud C Tasse Taboue4, Paul R Sesink Clee5, Trevon Fuller3, Thomas B Smith3, Nicola M Anthony1.   

Abstract

Predicting species' capacity to respond to climate change is an essential first step in developing effective conservation strategies. However, conservation prioritization schemes rarely take evolutionary potential into account. Ecotones provide important opportunities for diversifying selection and may thus constitute reservoirs of standing variation, increasing the capacity for future adaptation. Here, we map patterns of environmentally associated genomic and craniometric variation in the central African rodent Praomys misonnei to identify areas with the greatest turnover in genomic composition. We also project patterns of environmentally associated genomic variation under future climate change scenarios to determine where populations may be under the greatest pressure to adapt. While precipitation gradients influence both genomic and craniometric variation, vegetation structure is also an important determinant of craniometric variation. Areas of elevated environmentally associated genomic and craniometric variation overlap with zones of rapid ecological transition underlining their importance as reservoirs of evolutionary potential. We also find that populations in the Sanaga river basin, central Cameroon and coastal Gabon are likely to be under the greatest pressure from climate change. Lastly, we make specific conservation recommendations on how to protect zones of high evolutionary potential and identify areas where populations may be the most susceptible to climate change.

Entities:  

Keywords:  climate change; ecotones; generalized dissimilarity modelling; gradient forest; landscape genomics; population genomics

Mesh:

Year:  2020        PMID: 32635865      PMCID: PMC7423474          DOI: 10.1098/rspb.2020.0449

Source DB:  PubMed          Journal:  Proc Biol Sci        ISSN: 0962-8452            Impact factor:   5.349


  39 in total

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Review 3.  A practical guide to environmental association analysis in landscape genomics.

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Journal:  Syst Biol       Date:  2005-08       Impact factor: 15.683

6.  Building evolutionary resilience for conserving biodiversity under climate change.

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Journal:  Proc Natl Acad Sci U S A       Date:  2019-01-18       Impact factor: 11.205

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Authors:  Yuan-Xiang Tao; Gavin Rumbaugh; Guo-Du Wang; Ronald S Petralia; Chengshui Zhao; Frederick W Kauer; Feng Tao; Min Zhuo; Robert J Wenthold; Srinivasa N Raja; Richard L Huganir; David S Bredt; Roger A Johns
Journal:  J Neurosci       Date:  2003-07-30       Impact factor: 6.167

9.  The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes.

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10.  Landscape genomics provides evidence of climate-associated genetic variation in Mexican populations of Quercus rugosa.

Authors:  Karina Martins; Paul F Gugger; Jesus Llanderal-Mendoza; Antonio González-Rodríguez; Sorel T Fitz-Gibbon; Jian-Li Zhao; Hernando Rodríguez-Correa; Ken Oyama; Victoria L Sork
Journal:  Evol Appl       Date:  2018-08-31       Impact factor: 5.183

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1.  Challenging ecogeographical rules: Phenotypic variation in the Mountain Treeshrew (Tupaia montana) along tropical elevational gradients.

Authors:  Arlo Hinckley; Ines Sanchez-Donoso; Mar Comas; Miguel Camacho-Sanchez; Melissa T R Hawkins; Noor Haliza Hasan; Jennifer A Leonard
Journal:  PLoS One       Date:  2022-06-17       Impact factor: 3.752

2.  Genotype-environment associations across spatial scales reveal the importance of putative adaptive genetic variation in divergence.

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Journal:  Evol Appl       Date:  2022-08-24       Impact factor: 4.929

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