Skip to main content

Riverscape genetic structure of a threatened and dispersal limited freshwater species, the Rocky Mountain Sculpin (Cottus sp.)

Abstract

Understanding the movement ability and the spatial scale(s) of population genetic structure of species can together better ‘tune’ management objectives to prevent potential range contraction and population declines. We studied the Rocky Mountain Sculpin (Cottus sp.), a threatened species in Canada, to demonstrate the utility of using two complementary approaches to assess connectivity of a species. To do so, we used Passive Integrated Transponder (PIT) tags with a stationary tracking array (n = 223) to track movement and genetic data (n = 1,015) from nine microsatellite loci to assess genetic population structure. The PIT tag results indicated that Rocky Mountain Sculpin are sedentary; approximately 50% of individuals only moved a maximum distance of 10 meters (upstream or downstream) over a 5-month period. Genetic analyses indicated that at the spatial scale of our study area (5500 km2), watershed structure (river basins) is the main geographic feature influencing population genetic structure. We used the Bayesian clustering tool STRUCTURE, which suggested four distinct sub-populations of Rocky Mountain Sculpin in Canada. Genetic structure at finer spatial scales (within basins and sub-basins) appears to be influenced by fluvial distance (i.e., geographic distance along a river) and elevation change between sample locations (i.e., isolation-by-distance and isolation-by-environment). Combining movement and genetic analyses provides complimentary evidence of limited dispersal in Rocky Mountain Sculpin and highlights that both approaches together can provide broader insight into connectivity between populations that may ultimately help to aid future management decisions.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

References

  • AEP (2015) Alberta’s River Basins: River Flows and Levels. Alberta Environment and Parks GoAUhweacabDaDAF, Edmonton

    Google Scholar 

  • Bailey JE (1952) Life history and ecology of the sculpin Cottus biardi punctulatus in southwestern Montana. Copeia 4:243–255

    Google Scholar 

  • Balloux F, Lugon-Moulin N (2002) The estimation of population differentiation with microsatellite markers. Mol Ecol 11:155–165

    Article  PubMed  Google Scholar 

  • Broquet T, Petit EJ (2009) Molecular estimation of dispersal for ecology and population genetics. Annu Rev Ecol Evol Syst 40:193–216

    Article  Google Scholar 

  • Canada (2015) Historical Hydrometric Data Search. Government of Canada UhwegcssehshoAoF, 2016.).

  • Canada WSo (2013) HYDAT Database, Environment Canada. Available from https://www.ec.gc.ca/rhc-wsc/default.asp?lang=En&n=9018B5EC-1. Accessed 27 May 2015

  • COSEWIC (2010) COSEWIC assessment and status report on the Rocky Mountain Sculpin Cottus sp., Westslope populations, in Canada. Committee on the Status of Endangered Wildlife in Canada. Ottawa. x + 30 pp. (http://www.sararegistry.gc.ca/status/status_e.cfm).

  • Csardi G, Nepusz T (2006) igraph: The igraph software package for complex network research, InterJournal, Complex Systems. URL: http://igraph.org.

  • Dennenmoser S, Nolte AW, Vamosi SM, Rogers SM (2013) Conservation genetics of prickly sculpin (Cottus asper) at the periphery of its distribution range in Peace River, Canada. Conserv Genet 14:735–739

    Article  Google Scholar 

  • DFO (2013) Recovery potential assessment of Rocky Mountain Sculpin (Cottus sp.) eastslope populations in Alberta. Department of Fisheries and Oceans Canadian Science Advisory Secretariat SAR, Canada

    Google Scholar 

  • Dudgeon D, Arthington AH, Gessner MO, Kawabata ZI, Knowler DJ, Leveque C, Naiman RJ, Prieur-Richard AH, Soto D, Stiassny MLJ, Sullivan CA (2006) Freshwater biodiversity: importance, threats, status and conservation challenges. Biol Rev 81:163–182

    Article  PubMed  Google Scholar 

  • Engelke DR, Krikos A, Bruck ME, Ginsburg D (1990) Purification of thermus-aquaticus DNA-Polymerase expressed in Escherichia coli. Anal Biochem 191:396–400

    CAS  Article  PubMed  Google Scholar 

  • Englbrecht CC, Largiader CR, Hanfling B, Tautz D (1999) Isolation and characterization of polymorphic microsatellite loci in the European bullhead Cottus gobio L-(Osteichthyes) and their applicability to related taxa. Mol Ecol 8:1966–1969

    CAS  Article  PubMed  Google Scholar 

  • 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

    CAS  Article  PubMed  Google Scholar 

  • Fall A, Fortin M-J, Manseau M, O’Brien D (2007) Spatial graphs: Principles and applications for habitat connectivity. Ecosystems 10:448–461

    Article  Google Scholar 

  • Falush D, Stephens M, Pritchard JK (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–1587

    CAS  PubMed  PubMed Central  Google Scholar 

  • Fiumera AC, Porter BA, Grossman GD, Avise JC (2002) Intensive genetic assessment of the mating system and reproductive success in a semi-closed population of the mottled sculpin, Cottus bairdi. Mol Ecol 11:2367–2377

    CAS  Article  PubMed  Google Scholar 

  • Fraser DF, Gilliam JF, Daley MJ, Le AN, Skalski GT (2001) Explaining leptokurtic movement distributions: Intrapopulation variation in boldness and exploration. Am Nat 158:124–135

    CAS  Article  PubMed  Google Scholar 

  • Fujishin LM, Barker FK, Huff DD, Miller LM (2009) Isolation of 13 polymorphic microsatellite loci for slimy sculpin (Cottus cognatus). Conserv Genet Resour 1:429–432

    Article  Google Scholar 

  • Fullerton DS, Colton RB, Bush CA, Straub AW (2004) Map showing spatial and temporal relations of mountain and continental glaciations of the northern plains, primarily in northern Montana and northwestern North Dakota. U.S. Department of the Interior, U.S. Geological Survey, Scientific Investigations Map 2843: 4 p. Available through http://pubs.usgs.gov/sim/2004/2843/. Accessed 10 Feb 2016

  • Galpern P, Rayfield B, Fall A, Manseau M (2014) grainscape: Grains of connectivity and minimum planar graph modelling of landscape connectivity (Windows only). R package version 0.3/r29. https://R-Forge.R-project.org/projects/grainscape/.

  • Goslee SC, Urban DL (2007) The ecodist package for dissimilarity-based analysis of ecological data. J Stat Softw 22:1–19

    Article  Google Scholar 

  • Goudet J (1995) FSTAT (Version 1.2): A computer program to calculate F-statistics. J Hered 86:485–486

    Article  Google Scholar 

  • Goudet J, Jombart T (2015) hierfstat: Estimation and Tests of Hierarchical F-Statistics. R package version 0.04–22. https://CRAN.R-project.org/package=hierfstat.

  • Grant EHC, Lowe WH, Fagan WF (2007) Living in the branches: population dynamics and ecological processes in dendritic networks. Ecol Lett 10:165–175

    Article  Google Scholar 

  • Hanski I (1998) Metapopulation dynamics. Nature 396:41–49

    CAS  Article  Google Scholar 

  • Heim KC, Wipfli MS, Whitman MS, Arp CD, Adams J, Falke JA (2015) Seasonal cues of Arctic grayling movement in a small Arctic stream: the importance of surface water connectivity. Environ Biol Fish 99:49–65

    Article  Google Scholar 

  • Hughes JM, Schmidt DJ, Finn DS (2009) Genes in streams: using DNA to understand the movement of freshwater fauna and their riverine habitat. Bioscience 59:573–583

    Article  Google Scholar 

  • Hughes JM, Huey JA, Schmidt DJ (2013) Is realised connectivity among populations of aquatic fauna predictable from potential connectivity? Freshw Biol 58:951–966

    Article  Google Scholar 

  • Jakober MJ, McMahon TE, Thurow RF, Clancy CG (1998) Role of stream ice on fall and winter movements and habitat use by bull trout and cutthroat trout in Montana headwater streams. Trans Am Fish Soc 127:223–235

    Article  Google Scholar 

  • 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

    CAS  Article  PubMed  Google Scholar 

  • James PMA, Cooke B, Brunet BMT, Lumley LM, Sperling FAH, Fortin MJ, Quinn VS, Sturtevant BR (2015) Life-stage differences in spatial genetic structure in an irruptive forest insect: implications for dispersal and spatial synchrony. Mol Ecol 24:296–309

    Article  PubMed  Google Scholar 

  • Kalinowski ST, Taper ML (2006) Maximum likelihood estimation of the frequency of null alleles at microsatellite loci. Conserv Genet 7:991–995

    CAS  Article  Google Scholar 

  • Krejsa RJ (1967) The systematics of the prickly sculpin, Cottus asper Richardson, a polytypic species: part II. Studies on the life history, with especial reference to migration. Pacific Sci 21:414–422

    Google Scholar 

  • Labbe TR, Fausch KD (2000) Dynamics of intermittent stream habitat regulate persistence of a threatened fish at multiple scales. Ecol Appl 10:1774–1791

    Article  Google Scholar 

  • Lamphere BA, Blum MJ (2012) Genetic estimates of population structure and dispersal in a benthic stream fish. Ecol Freshw Fish 21:75–86

    Article  Google Scholar 

  • Landguth EL, Bearlin A, Day CC, Dunham J (2016) CDMetaPOP: an individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics. Methods Ecol Evol. doi:10.1111/2041-210X.12608

    Google Scholar 

  • Legendre P (2005) Code for t-test for independent samples with permutation test. http://adn.biol.umontreal.ca/~numericalecology/Rcode/

  • Legendre P, Legendre L (1998) Numerical Ecology, 2nd English Edn. Elsevier, Amsterdam

    Google Scholar 

  • Lichstein JW (2007) Multiple regression on distance matrices: a multivariate spatial analysis tool. Plant Ecol 188:117–131

    Article  Google Scholar 

  • Lowe WH, Allendorf FW (2010) What can genetics tell us about population connectivity? Mol Ecol 19:3038–3051

    Article  PubMed  Google Scholar 

  • McCauley DJ, Pinsky ML, Palumbi SR, Estes JA, Joyce FH, Warner RR (2015) Marine defaunation: animal loss in the global ocean. Science 347:8

    Article  Google Scholar 

  • McCleave JD (1964) Movement and population of the mottled sculpin (Cottus bairdi Girard) in a small Montana stream. Copeia 1964:506–513

    Article  Google Scholar 

  • McLachlan JS, Hellmann JJ, Schwartz MW (2007) A framework for debate of assisted migration in an era of climate change. Conserv Biol 21:297–302

    Article  PubMed  Google Scholar 

  • McRae BH, Dickson BG, Keitt TH, Shah VB (2008) Using circuit theory to model connectivity in ecology, evolution, and conservation. Ecology 89:2712–2724

    Article  PubMed  Google Scholar 

  • Meffe GK, Vrijenhoek RC (1988) Conservation genetics in the management of desert fishes. Conserv Biol 2:157–169

    Article  Google Scholar 

  • Murphy AL, Pavlova A, Thompson R, Davis J, Sunnucks P (2015) Swimming through sand: connectivity of aquatic fauna in deserts. Ecol Evol 5:5252–5264

    Article  Google Scholar 

  • Nei M (1973) Analysis of gene diversity in subdivided populations. Proc Natl Acad Sci USA 70:3321–3323

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Nolte AW, Stemshorn KC, Tautz D (2005) Direct cloning of microsatellite loci from Cottus gobio through a simplified enrichment procedure. Mol Ecol Notes 5:628–636

    CAS  Article  Google Scholar 

  • NRC (2012) Canadian Digital Elevation Model (CDEM). (ed. Government of Canada NRC, Earth Sciences Sector. http://geogratis.gc.ca/api/en/nrcan-rncan/ess-sst/C40ACFBA-C722-4BE1-862E-146B80BE738E.html. Accessed 20 Jun 2016)

  • Oksanen J, F. Guillaume Blanchet, R. Kindt, P. Legendre, P. R. Minchin, R. B. O’Hara, G. L. Simpson, P. Solymos, M. H. H. Stevens, Wagner H (2015) vegan: Community Ecology Package. In: R package version version 22–1 http://CRAN.R-project.org/package=vegan.

  • Paradis E (2010) pegas: an R package for population genetics with an integrated-modular approach. Bioinformatics 26:419–420

    CAS  Article  PubMed  Google Scholar 

  • 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

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Peres-Neto PR, Jackson DA (2001) How well do multivariate data sets match? The advantages of a Procrustean superimposition approach over the Mantel test. Oecologia 129:169–178

    Article  PubMed  Google Scholar 

  • Petty JT, Grossman GD (2004) Restricted movement by mottled sculpin (pisces : cottidae) in a southern Appalachian stream. Freshw Biol 49:631–645

    Article  Google Scholar 

  • Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959

    CAS  PubMed  PubMed Central  Google Scholar 

  • R Development Core Team (2016) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna

    Google Scholar 

  • Radinger J, Wolter C (2014) Patterns and predictors of fish dispersal in rivers. Fish Fish 15:456–473

    Article  Google Scholar 

  • Rousset F (1997) Genetic differentiation and estimation of gene flow from F-statistics under isolation by distance. Genetics 145:1219–1228

    CAS  PubMed  PubMed Central  Google Scholar 

  • Ruetz CR, Earl BM, Kohler SL (2006) Evaluating passive integrated transponder tags for marking mottled sculpins: effects on growth and mortality. Trans Am Fish Soc 135:1456–1461

    Article  Google Scholar 

  • Safner T, Miller MP, McRae BH, Fortin MJ, Manel S (2011) Comparison of bayesian clustering and edge detection methods for inferring boundaries in landscape genetics. Int J Mol Sci 12:865–889

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Schwalb AN, Poos MS, Ackerman JD (2011) Movement of logperch-the obligate host fish for endangered snuffbox mussels: implications for mussel dispersal. Aquat Sci 73:223–231

    Article  Google Scholar 

  • Selkoe KA, Srcribner KT, Galindo HM (2016) Waterscape genetics - applications of landscape genetics to rivers, lakes, and seas. In:Balknhol N, Cushman SA, Storfer AT, Waits LP (eds) Landscape genetics: Concepts, methods, applications, 1 edn. Wiley, Chichester, pp. 264

    Google Scholar 

  • Spear SF, Balkenhol N, Fortin MJ, McRae BH, Scribner K (2010) Use of resistance surfaces for landscape genetic studies: considerations for parameterization and analysis. Mol Ecol 19:3576–3591

    Article  PubMed  Google Scholar 

  • Wagner HH, Fortin MJ (2013) A conceptual framework for the spatial analysis of landscape genetic data. Conserv Genet 14:253–261

    Article  Google Scholar 

  • Wang IJ, Bradburd GS (2014) Isolation by environment. Mol Ecol 23:5649–5662

    Article  PubMed  Google Scholar 

  • Watkinson DA, Boguski DA (2013) Information in support of a recovery potential assessment of Rocky Mountain Sculpin (Cottus sp.), Eastslope populations, in Alberta. Canadian Science Advisory Secretariat, Ottawa

    Google Scholar 

  • Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evol Int J Org Evol 38:1358–1370

    CAS  Google Scholar 

Download references

Acknowledgements

The authors would like to acknowledge individuals part of the field sampling team, including: Wesley Donaldson, Elliot Macdonald, Kelly Mulligan, Caitlin Good, Christine Lacho, Troy Adams, Kenton Neufeld, Elashia Young, and Denyse Dawe. Thanks are also due to Fisheries and Oceans Canada Species at Risk group for funding to MP and DW.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jonathan L. W. Ruppert.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 726 KB)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ruppert, J.L.W., James, P.M.A., Taylor, E.B. et al. Riverscape genetic structure of a threatened and dispersal limited freshwater species, the Rocky Mountain Sculpin (Cottus sp.). Conserv Genet 18, 925–937 (2017). https://doi.org/10.1007/s10592-017-0938-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10592-017-0938-6

Keywords

  • Demographic connectivity
  • Genetic connectivity
  • Dendritic network
  • Isolation-by-distance
  • Isolation-by-environment
  • Stream hierarchy