Population connectivity and genetic offset in the spawning coral Acropora digitifera in Western Australia.

Arne A S Adam, Luke Thomas, Jim Underwood, James Gilmour, Zoe T Richards
Author Information
  1. Arne A S Adam: Coral Conservation and Research Group, Trace and Environmental DNA Laboratory, School of Molecular and Life Sciences, Curtin University, Bentley, Western Australia. ORCID
  2. Luke Thomas: Australian Institute of Marine Science, IOMRC, The University of Western Australia, Crawley, Western Australia.
  3. Jim Underwood: Australian Institute of Marine Science, IOMRC, The University of Western Australia, Crawley, Western Australia. ORCID
  4. James Gilmour: Australian Institute of Marine Science, IOMRC, The University of Western Australia, Crawley, Western Australia. ORCID
  5. Zoe T Richards: Coral Conservation and Research Group, Trace and Environmental DNA Laboratory, School of Molecular and Life Sciences, Curtin University, Bentley, Western Australia. ORCID

Abstract

Anthropogenic climate change has caused widespread loss of species biodiversity and ecosystem productivity across the globe, particularly on tropical coral reefs. Predicting the future vulnerability of reef-building corals, the foundation species of coral reef ecosystems, is crucial for cost-effective conservation planning in the Anthropocene. In this study, we combine regional population genetic connectivity and seascape analyses to explore patterns of genetic offset (the mismatch of gene-environmental associations under future climate conditions) in Acropora digitifera across 12 degrees of latitude in Western Australia. Our data revealed a pattern of restricted gene flow and limited genetic connectivity among geographically distant reef systems. Environmental association analyses identified a suite of loci strongly associated with the regional temperature variation. These loci helped forecast future genetic offset in gradient forest and generalized dissimilarity models. These analyses predicted pronounced differences in the response of different reef systems in Western Australia to rising temperatures. Under the most optimistic future warming scenario (RCP 2.6), we predicted a general pattern of increasing genetic offset with latitude. Under the extreme climate scenario (RCP 8.5 in 2090-2100), coral populations at the Ningaloo World Heritage Area were predicted to experience a higher mismatch between current allele frequencies and those required to cope with local environmental change, compared to populations in the inshore Kimberley region. The study suggests complex and spatially heterogeneous patterns of climate-change vulnerability in coral populations across Western Australia, reinforcing the notion that regionally tailored conservation efforts will be most effective at managing coral reef resilience into the future.

Keywords

Associated Data

Dryad | 10.5061/dryad.t1g1jwt4g

References

  1. Nat Commun. 2015 Oct 23;6:8562 [PMID: 26493738]
  2. Curr Biol. 2013 Aug 5;23(15):1399-408 [PMID: 23850284]
  3. Mol Ecol Resour. 2012 Nov;12(6):1158-60 [PMID: 22883857]
  4. Glob Chang Biol. 2019 Dec 27;: [PMID: 31883173]
  5. PLoS One. 2011;6(8):e23064 [PMID: 21860667]
  6. Glob Chang Biol. 2014 Jan;20(1):103-12 [PMID: 24151155]
  7. Genetics. 2014 Jun;197(2):573-89 [PMID: 24700103]
  8. Nature. 2011 Feb 24;470(7335):479-85 [PMID: 21350480]
  9. Glob Chang Biol. 2020 Oct;26(10):5646-5660 [PMID: 32713061]
  10. Proc Biol Sci. 2015 Aug 7;282(1812):20151217 [PMID: 26224707]
  11. Nature. 2019 Apr;568(7752):387-390 [PMID: 30944475]
  12. Proc Natl Acad Sci U S A. 2021 May 25;118(21): [PMID: 33972407]
  13. Glob Chang Biol. 2021 Sep;27(18):4307-4321 [PMID: 34106494]
  14. PLoS One. 2012;7(12):e51807 [PMID: 23284773]
  15. Philos Trans R Soc Lond B Biol Sci. 2020 Mar 16;375(1794):20190104 [PMID: 31983329]
  16. BMC Genomics. 2018 Jun 14;19(1):458 [PMID: 29898658]
  17. Proc Natl Acad Sci U S A. 1973 Dec;70(12):3321-3 [PMID: 4519626]
  18. Science. 2011 Nov 4;334(6056):652-5 [PMID: 22053045]
  19. Glob Chang Biol. 2020 Jun;26(6):3473-3481 [PMID: 32285562]
  20. Evol Appl. 2020 Mar 19;13(8):1923-1938 [PMID: 32908595]
  21. Sci Rep. 2016 Dec 21;6:39666 [PMID: 28000782]
  22. Nature. 2011 Jul 24;476(7360):320-3 [PMID: 21785439]
  23. Glob Chang Biol. 2016 Nov;22(11):3539-3549 [PMID: 27154763]
  24. Glob Chang Biol. 2017 Jun;23(6):2197-2205 [PMID: 28132420]
  25. Mol Ecol. 2007 Feb;16(4):771-84 [PMID: 17284210]
  26. PLoS One. 2015 Feb 25;10(2):e0117791 [PMID: 25714443]
  27. Glob Chang Biol. 2020 Jan;26(1):68-79 [PMID: 31618499]
  28. Ecol Lett. 2015 Jan;18(1):1-16 [PMID: 25270536]
  29. Proc Biol Sci. 2016 Apr 27;283(1829): [PMID: 27122569]
  30. Glob Chang Biol. 2021 Jan;27(1):108-120 [PMID: 33118308]
  31. Nature. 2019 May;569(7754):108-111 [PMID: 31019302]
  32. PeerJ. 2014 Mar 04;2:e281 [PMID: 24688859]
  33. Glob Chang Biol. 2021 Feb;27(3):475-488 [PMID: 32979891]
  34. Ecol Appl. 2009 Jan;19(1):18-29 [PMID: 19323171]
  35. Science. 2015 Nov 6;350(6261):691-4 [PMID: 26542574]
  36. Proc Biol Sci. 2013 Aug 07;280(1768):20131201 [PMID: 23926147]
  37. Mol Ecol Resour. 2017 Sep;17(5):1072-1089 [PMID: 27801969]
  38. PLoS One. 2013 Jul 29;8(7):e69863 [PMID: 23922829]
  39. Glob Chang Biol. 2018 Feb;24(2):e474-e484 [PMID: 29044761]
  40. Mol Ecol. 2022 Jul;31(13):3533-3547 [PMID: 35567512]
  41. Sci Rep. 2016 Dec 22;6:39734 [PMID: 28004835]
  42. Science. 2013 Apr 5;340(6128):69-71 [PMID: 23559247]
  43. Evol Appl. 2009 May;2(2):222-33 [PMID: 25567863]
  44. Ecol Appl. 2022 Apr;32(3):e2509 [PMID: 34870357]
  45. Nature. 2017 Mar 15;543(7645):373-377 [PMID: 28300113]
  46. Ecology. 2012 Jan;93(1):156-68 [PMID: 22486096]
  47. Science. 2018 Jan 05;359(6371):83-86 [PMID: 29302012]
  48. Mol Ecol. 2015 Sep;24(17):4348-70 [PMID: 26184487]
  49. Glob Chang Biol. 2021 May;27(10):2200-2212 [PMID: 33511779]
  50. Glob Chang Biol. 2021 Oct;27(19):4825-4838 [PMID: 34390297]
  51. Bioinformatics. 2008 Jun 1;24(11):1403-5 [PMID: 18397895]
  52. Mol Ecol. 2018 Apr;27(7):1586-1602 [PMID: 29575282]
  53. Integr Comp Biol. 2012 Oct;52(4):525-37 [PMID: 22821585]
  54. Commun Biol. 2018 Jul 17;1:95 [PMID: 30271976]
  55. Mol Ecol. 2013 Feb;22(4):925-46 [PMID: 23279006]
  56. Curr Zool. 2016 Dec;62(6):581-601 [PMID: 29491947]
  57. Science. 2013 Sep 13;341(6151):1239-42 [PMID: 24031017]
  58. PLoS One. 2013;8(2):e55648 [PMID: 23409015]
  59. Evol Appl. 2020 Jun 22;13(9):2404-2421 [PMID: 33005230]
  60. Science. 2018 Aug 3;361(6401): [PMID: 30072513]
  61. Genetics. 2008 Oct;180(2):977-93 [PMID: 18780740]
  62. PLoS One. 2017 Feb 28;12(2):e0172977 [PMID: 28245232]
  63. Sci Adv. 2017 Nov 01;3(11):e1701413 [PMID: 29109975]
  64. Nat Ecol Evol. 2020 Jul;4(7):919-926 [PMID: 32424279]
  65. Mol Ecol Resour. 2019 Sep;19(5):1355-1365 [PMID: 31136078]

MeSH Term

Animals
Anthozoa
Climate Change
Coral Reefs
Ecosystem
Gene Flow
Western Australia

Word Cloud

Created with Highcharts 10.0.0coralgeneticfutureAustraliaclimatereefoffsetWesternchangeacrossconnectivityanalysespredictedpopulationsspeciesvulnerabilitycoralsconservationstudyregionalpopulationpatternsmismatchgene-environmentalassociationsAcroporadigitiferalatitudepatternsystemslociscenarioRCPAnthropogeniccausedwidespreadlossbiodiversityecosystemproductivityglobeparticularlytropicalreefsPredictingreef-buildingfoundationecosystemscrucialcost-effectiveplanningAnthropocenecombineseascapeexploreconditions12degreesdatarevealedrestrictedgeneflowlimitedamonggeographicallydistantEnvironmentalassociationidentifiedsuitestronglyassociatedtemperaturevariationhelpedforecastgradientforestgeneralizeddissimilaritymodelspronounceddifferencesresponsedifferentrisingtemperaturesoptimisticwarming26generalincreasingextreme852090-2100NingalooWorldHeritageAreaexperiencehighercurrentallelefrequenciesrequiredcopelocalenvironmentalcomparedinshoreKimberleyregionsuggestscomplexspatiallyheterogeneousclimate-changereinforcingnotionregionallytailoredeffortswilleffectivemanagingresiliencePopulationspawningNorth-westbroadcastgenetics

Similar Articles

Cited By