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Environmental Biology of Fishes

, Volume 101, Issue 5, pp 799–811 | Cite as

Genetic characteristics of coastal cutthroat trout inhabiting an urban watershed

  • Justin H. Bohling
  • Timothy A. Whitesel
  • Melissa Brown
Article

Abstract

Watersheds in urban areas are often heavily degraded due to human activity, which can have negative impacts on freshwater fishes. Monitoring the genetic characteristics of urban populations can provide insights into the impact of development on aquatic ecosystems. We performed a genetic analysis of coastal cutthroat trout (Oncorhynchus clarkii clarkii) inhabiting urban tributaries in Portland, OR. By analyzing nuclear microsatellite genotypes, we were able to assess population structure, genetic diversity, and effective population size for six locations across two tributaries on opposite sides of the Willamette River. Genetic diversity was generally equivalent across all sampling locations, although populations from smaller tributaries higher in the stream network had lower levels. Levels of effective population size were low but within expected ranges for small salmonid populations. As anticipated, smaller populations had higher levels of inter-individual relatedness. The primary genetic structure divided populations on opposite sides of the Willamette River, although there was evidence of dispersal between the two groups. Our results suggest that cutthroat trout inhabiting metropolitan areas are not necessarily genetically impoverished and may exhibit characteristics typical of populations in more ‘natural’ environments. Understanding how fish, especially anadromous species, respond to urban environments is essential to evaluating the value of these areas for conservation planning.

Keywords

Oncorhynchus clarkia Dispersal Urban ecology Metapopulation Population genetics 

Notes

Acknowledgements

We thank J. Von Bargen and M. Brinkmeyer (USFWS) for processing samples in the lab. Personnel from the Columbia River Fish and Wildlife Conservation Office collected tissue samples in the field. We thank R. Twibell (USFWS) and personnel from the Columbia River Fish and Wildlife Conservation Office for comments that improved the manuscript. We declare no conflict of interest in the publication of this study. We thank editor David Noakes and two peer-reviewers for their constructive comments. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the US Fish and Wildlife Service.

Funding

Funding was provided by the City of Portland’s Bureau of Environmental Services and the U.S. Fish and Wildlife Service’s Columbia River Fish and Wildlife Conservation Office. Collection of trout for this study was conducted with permits and animal use approval required by the US Fish and Wildlife Service and City of Portland Bureau of Environmental Services.

Supplementary material

10641_2018_739_MOESM1_ESM.docx (238 kb)
ESM 1 (DOCX 238 kb)

References

  1. Botkin DB, Beveridge CE (1997) Cities as environments. Urban Ecosyst 1:3–19.  https://doi.org/10.1023/A:1014354923367 CrossRefGoogle Scholar
  2. Campana MG, Hunt HV, Jones H, White J (2011) CorrSieve: software for summarizing and evaluating structure output. Mol Ecol Resour 11:349–352.  https://doi.org/10.1111/j.1755-0998.2010.02917.x CrossRefPubMedGoogle Scholar
  3. Campton DE, Utter FM (1987) Genetic structure of anadromous cutthroat trout (Salmo clarki clarki) populations in the Puget sound area: evidence for restricted gene flow. Can J Fish Aquat Sci 7:573–582CrossRefGoogle Scholar
  4. Delaney KS, Riley SPD, Fisher RN (2010) A rapid, strong, and convergent genetic response to urban habitat fragmentation in four divergent and widespread vertebrates. PLoS One 5:e12767.  https://doi.org/10.1371/journal.pone.0012767 CrossRefPubMedPubMedCentralGoogle Scholar
  5. Do C, Waples RS, Peel D et al (2014) NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne) from genetic data. Mol Ecol Resour 14:209–214.  https://doi.org/10.1111/1755-0998.12157 CrossRefPubMedGoogle Scholar
  6. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620.  https://doi.org/10.1111/j.1365-294X.2005.02553.x CrossRefPubMedGoogle Scholar
  7. Everard M, Moggridge HL (2012) Rediscovering the value of urban rivers. Urban Ecosyst 15:293–314.  https://doi.org/10.1007/s11252-011-0174-7 CrossRefGoogle Scholar
  8. Excoffier L, Lischer H (2010) Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour 10:564–567.  https://doi.org/10.1111/j.1755-0998.2010.02847.x CrossRefPubMedGoogle Scholar
  9. Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes. Genetics 131:479–491.  https://doi.org/10.1007/s00424-009-0730-7 PubMedPubMedCentralGoogle Scholar
  10. Falush D, Stephens M, Pritchard JK (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–1587PubMedPubMedCentralGoogle Scholar
  11. Gouskov A, Reyes M, Bitterlin L, Vorburger C (2016) Fish population genetic structure shaped by hydroelectric power plants in the upper Rhine catchment. Evol Appl 9:394–408.  https://doi.org/10.1111/eva.12339 CrossRefPubMedPubMedCentralGoogle Scholar
  12. Hansen MM, Jensen LF (2005) Sibship within samples of brown trout (Salmo trutta) and implications for supportive breeding. Conserv Genet 6:297–305.  https://doi.org/10.1007/s10592-004-7827-5 CrossRefGoogle Scholar
  13. Hansen MM, Limborg MT, Ferchaud A-L, Pujolar J-M (2014) The effects of medieval dams on genetic divergence and demographic history in brown trout populations. BMC Evol Biol 14:122.  https://doi.org/10.1186/1471-2148-14-122 CrossRefPubMedPubMedCentralGoogle Scholar
  14. Helms BS, Feminella JW, Pan S (2005) Detection of biotic responses to urbanization using fish assemblages from small streams of western Georgia, USA. Urban Ecosyst 8:39–57.  https://doi.org/10.1007/s11252-005-1418-1 CrossRefGoogle Scholar
  15. ICF International (2010) Status & Trends of Salmonid Potential in Johnson Creek: 2000 to 2009. April. (ICF 97.09.) Portland, OR. Prepared for City of Portland, Bureau of Environmental Services, ORGoogle Scholar
  16. Jakobsson M, Rosenberg NA (2007) CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23:1801–1806.  https://doi.org/10.1093/bioinformatics/btm233 CrossRefPubMedGoogle Scholar
  17. Johnson JR, Baumsteiger J, Zydlewski J, Hudson JM, Ardren W (2010) Evidence of panmixia between sympatric life history forms of coastal cutthroat trout in two lower Columbia River tributaries. N Am J Fish Manag 30:691–701.  https://doi.org/10.1577/M09-055.1 CrossRefGoogle Scholar
  18. Jombart T, Devillard S, Balloux F (2010) Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet 11:94.  https://doi.org/10.1186/1471-2156-11-94 CrossRefPubMedPubMedCentralGoogle Scholar
  19. Kanno Y, Vokoun JC, Letcher BH (2011a) Sibship reconstruction for inferring mating systems, dispersal and effective population size in headwater brook trout (Salvelinus fontinalis) populations. Conserv Genet 12:619–628.  https://doi.org/10.1007/s10592-010-0166-9 CrossRefGoogle Scholar
  20. Kanno Y, Vokoun JC, Letcher BH (2011b) Fine-scale population structure and riverscape genetics of brook trout (Salvelinus fontinalis) distributed continuously along headwater channel networks. Mol Ecol 20:3711–3729.  https://doi.org/10.1111/j.1365-294X.2011.05210.x CrossRefPubMedGoogle Scholar
  21. Keenan K, McGinnity P, Cross TF et al (2013) diveRsity: an R package for the estimation and exploration of population genetics parameters and their associated errors. Methods Ecol Evol 4:782–788.  https://doi.org/10.1111/2041-210X.12067 CrossRefGoogle Scholar
  22. Lee JS, Ruell EW, Boydston EE et al (2012) Gene flow and pathogen transmission among bobcats (Lynx rufus) in a fragmented urban landscape. Mol Ecol 21:1617–1631.  https://doi.org/10.1111/j.1365-294X.2012.05493.x CrossRefPubMedGoogle Scholar
  23. May CW, Horner RR, Karr JR et al (1997) Effects of urbanization on small streams in the Puget sound ecoregion. Watershed Prot Tech 2:483–494Google Scholar
  24. Munshi-South J, Zolnik CP, Harris SE (2016) Population genomics of the Anthropocene: urbanization is negatively associated with genome-wide variation in white-footed mouse populations. Evol Appl 9:546–564.  https://doi.org/10.1111/eva.12357 CrossRefPubMedPubMedCentralGoogle Scholar
  25. Noël S, Lapointe F-J (2010) Urban conservation genetics: study of a terrestrial salamander in the city. Biol Conserv 143:2823–2831.  https://doi.org/10.1016/j.biocon.2010.07.033 CrossRefGoogle Scholar
  26. Ozerov M, Jürgenstein T, Aykanat T, Vasemägi A (2015) Use of sibling relationship reconstruction to complement traditional monitoring in fisheries management and conservation of brown trout. Conserv Biol 29:1164–1175.  https://doi.org/10.1111/cobi.12480 CrossRefPubMedGoogle Scholar
  27. Paradis E (2010) Pegas: an R package for population genetics with an integrated-modular approach. Bioinformatics 26:419–420.  https://doi.org/10.1093/bioinformatics/btp696 CrossRefPubMedGoogle Scholar
  28. Paul MJ, Meyer JL (2001) Streams in the urban landscape. Annu Rev Ecol Syst 32:333–365.  https://doi.org/10.1146/annurev.ecolsys.32.081501.114040 CrossRefGoogle Scholar
  29. Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research--an update. Bioinformatics 28:2537–2539.  https://doi.org/10.1093/bioinformatics/bts460 CrossRefPubMedPubMedCentralGoogle Scholar
  30. Pew J, Muir PH, Wang J, Frasier TR (2015) Related: an R package for analysing pairwise relatedness from codominant molecular markers. Mol Ecol Resour 15:557–561.  https://doi.org/10.1111/1755-0998.12323 CrossRefPubMedGoogle Scholar
  31. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedPubMedCentralGoogle Scholar
  32. R Core Team (2015). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.
  33. Rios-Touma B, Prescott C, Axtell S, Kondolf GM (2015) Habitat restoration in the context of watershed prioritization: the ecological performance of urban stream restoration projects in portland, oregon. River Res Appl 31:755–766.  https://doi.org/10.1002/rra.2769 CrossRefGoogle Scholar
  34. Rosenfeld J, Porter M, Parkinson E (2000) Habitat factors affecting the abundace and distribution of juvenile cutthroat trout (Oncorhynchus clarki) and coho salmon (Oncorhynchus kisutch). Can J Fish Aquat Sci 57:766–7740.  https://doi.org/10.1139/f00-010 CrossRefGoogle Scholar
  35. Rosenfeld JS, Macdonald S, Foster D et al (2002) Importance of small streams as rearing habitat for coastal cutthroat trout. North Am J Fish Manag 22:177–187.  https://doi.org/10.1577/1548-8675(2002)022<0177:IOSSAR>2.0.CO;2 CrossRefGoogle Scholar
  36. Ruzzante D, Hansen M, Meldrup D (2001) Distribution of individual inbreeding coefficients, relatedness and influence of stocking on native anadromous brown trout (Salmo trutta) population structure. Mol Ecol 10:2107–2128.  https://doi.org/10.1046/j.1365-294X.2001.01352.x CrossRefPubMedGoogle Scholar
  37. Ruzzante DE, McCracken GR, Parmelee S et al (2016) Effective number of breeders, effective population size and their relationship with census size in an iteroparous species, Salvelinus Fontinalis. Proc R Soc B 283:20152601.  https://doi.org/10.1098/rspb.2015.2601 CrossRefPubMedPubMedCentralGoogle Scholar
  38. Silver BP, Hudson JM, Lujan K, Brown M, Whitesel T (2017) An urban stream can support a healthy population of coastal cutthroat trout. Urban Ecosyst.  https://doi.org/10.1007/s11252-017-0711-0 Google Scholar
  39. Smith CT, Von Bargen J, Whitesel T (2015) Population structure of coastal cutthroat trout from Tryon Creek, OR. US Fish & Wildlife Service, AFTC Final Report: 287Google Scholar
  40. Stranko SA, Hilderbrand RH, Palmer MA (2011) Comparing the fish and benthic macroinvertebrate diversity of restored urban streams to reference streams. Restor Ecol 20:747–755.  https://doi.org/10.1111/j.1526-100X.2011.00824.x CrossRefGoogle Scholar
  41. Walsh CJ, Roy AH, Feminella JW et al (2005) The urban stream syndrome: current knowledge and the search for a cure. J North Am Benthol Soc 24:706–723.  https://doi.org/10.1899/04-028.1 CrossRefGoogle Scholar
  42. Wang J (2007) Triadic IBD coefficients and applications to estimating pairwise relatedness. Genet Res 89:135–153.  https://doi.org/10.1017/S0016672307008798 CrossRefPubMedGoogle Scholar
  43. Wang J (2016) A comparison of single-sample estimators of effective population sizes from genetic marker data. Mol Ecol 25:4692–4711.  https://doi.org/10.1111/mec.13725 CrossRefPubMedGoogle Scholar
  44. Wang LZ, Lyons J, Kanehl P, Bannerman R (2001) Impacts on stream habitat and fish across multiple spatial scales. Environ Manag 28:255–266.  https://doi.org/10.1007/s0026702409 CrossRefGoogle Scholar
  45. Waples RS, Do C (2010) Linkage disequilibrium estimates of contemporary Ne using highly variable genetic markers: a largely untapped resource for applied conservation and evolution. Evol Appl 3:244–262.  https://doi.org/10.1111/j.1752-4571.2009.00104.x CrossRefPubMedGoogle Scholar
  46. Waples RS, Teel DJ (1990) Conservation genetics of Pacific salmon I. Temporal changes in allele frequency. Conserv Biol 4:144–156.  https://doi.org/10.1111/j.1523-1739.1990.tb00103.x CrossRefGoogle Scholar
  47. Weir B, Cockerham C (1984) Estimating F-statistics for the analysis of population structure. Evolution 38:1358–1370.  https://doi.org/10.1111/j.1558-5646.1984.tb05657.x PubMedGoogle Scholar
  48. Wenburg JK, Bentzen P, Foote CJ (1998) Microsatellite analysis of genetic population structure in an endangered salmonid: the coastal cutthroat trout (Oncorhynchus clarki clarki). Mol Ecol 7:733–749.  https://doi.org/10.1046/j.1365-294x.1998.00386.x CrossRefGoogle Scholar
  49. Whiteley AR, Hastings K, Wenburg JK et al (2010) Genetic variation and effective population size in isolated populations of coastal cutthroat trout. Conserv Genet 11:1929–1943.  https://doi.org/10.1007/s10592-010-0083-y CrossRefGoogle Scholar
  50. Whiteley AR, Coombs JA, Hudy M, Robinson Z, Nislow KH, Letcher BH (2012) Sampling strategies for estimating brook trout effective population size. Conserv Genet 13:623–637CrossRefGoogle Scholar
  51. Zydlewski GB, Zydleowski J, Johnson J (2009) Patterns of migration and residency in coastal cutthroat trout Oncorhynchus clarkii clarkii from two tributaries of the lower Columbia River. Journal of Fish Biology 75: 203–222Google Scholar

Copyright information

© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2018

Authors and Affiliations

  1. 1.Abernathy Fish Technology CenterUS Fish and Wildlife ServiceLongviewUSA
  2. 2.Columbia River Fish and Wildlife Conservation OfficeUS Fish and Wildlife ServiceVancouverUSA
  3. 3.City of Portland Bureau of Environmental ServicesPortlandUSA

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