Can indicator species guide conservation investments to restore connectivity in Great Lakes tributaries?

Abstract

In many applications, conservation organizations depend on one species to indicate the presence of another. While extensive research has gone into methods for selecting these indicator species, few studies have directly measured the performance of indicator species in guiding conservation actions. Here, we evaluated whether a small number of indicator species could be used to efficiently select barrier removal projects to restore breeding habitat access for many other Great Lakes migratory fishes in the highly fragmented tributaries of the North American Great Lakes. First, we used a dataset of the historical distributions of 35 species of native migratory fishes to identify four clusters of co-occurring species, and then selected an indicator species for each cluster based on within-group co-occurrence or range width. We evaluated the utility of these indicator species by using upstream habitat and removal costs for 103,894 dams and road culverts across 1800 tributaries of the Great Lakes. We compared the potential increase in accessible tributary habitat for each species when barrier removals were prioritized to maximize benefits for (1) each species itself, versus (2) possible indicator species. We found that for 80% of the species, habitat gains from indicator-based project selection were at least 75% of the maximum gains possible under species-specific planning. However, a small subset of species would receive few habitat gains under indicator-directed project selection. Overall, our findings suggest that a suite of indicator species could be an efficient basis for planning restoration efforts for a majority of native migratory fishes in the Great Lakes.

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Data availability

The datasets generated during and/or analyzed during the current study are available on reasonable request. For more information see Khoury et al. (2018) and Neeson et al. (2015).

Code availability

Available from corresponding author upon reasonable request.

References

  1. Allan JD, Smith SDP, McIntyre PB, Joseph CA, Dickinson CE, Marino AL, Biel RG, Olson JC, Doran PJ, Rutherford ES, Adkins JE, Adeyemo AO (2015) Using cultural ecosystem services to inform restoration priorities in the Laurentian Great Lakes. Front Ecol Environ 13(8):418–424. https://doi.org/10.1890/140328

    Article  Google Scholar 

  2. Azeria ET, Fortin D, Hebert C, Peres-Neto P, Pothier D, Ruel J (2009) Using null model analysis of species co-occurrences to deconstruct biodiversity patterns and select indicator species. Divers Distrib 15:958–971. https://doi.org/10.1111/j.1472-4642.2009.00613.x

    Article  Google Scholar 

  3. Bal P, Tulloch AIT, Addison PFE, McDonald-Madden E, Rhodes JR (2018) Selecting indicator species for biodiversity management. Front Ecol Environ 16(10):589–598. https://doi.org/10.1002/fee.1972

    Article  Google Scholar 

  4. Bednarek AT (2001) Undamming rivers: a review of the ecological impacts of dam removal. Environ Manage 27(6):803–814. https://doi.org/10.1007/s002670010189

    CAS  Article  PubMed  Google Scholar 

  5. Bini LM, Diniz-Filho JAF, Rangel TFLVB, Bastos RP, Pinto MP (2006) Challenging Wallacean and Linnean shortfalls: knowledge gradients and conservation planning in a biodiversity hotspot. Divers Distrib 12:475–482. https://doi.org/10.1111/j.1366-9516.2006.00286.x

    Article  Google Scholar 

  6. Block WM, Brennan LA, Gutierrez RJ (1987) Evaluation of guild-indicator species for use in resource management. Environ Manage 11(2):265–269. https://doi.org/10.1007/BF01867205

    Article  Google Scholar 

  7. Caro TM (2010) Conservation by proxy: indicator, umbrella, keystone, flagship, and other surrogate species. Island Press, Washington

    Google Scholar 

  8. Caro TM, O’Doherty G (1999) On the use of surrogate species in conservation biology. Conserv Biol 13(4):805–814. https://doi.org/10.1046/j.1523-1739.1999.98338.x

    Article  Google Scholar 

  9. Childress ES, Allan JD, McIntyre PB (2014) Nutrient subsidies from iteroparous fish migrations can enhance stream productivity. Ecosystems 17:522–534. https://doi.org/10.1007/s10021-013-9739-z

    CAS  Article  Google Scholar 

  10. Cooper AR, Infante DM, Wehrly KE, Wang L, Brenden TO (2016) Identifying indicators and quantifying large-scale effects of dams on fishes. Ecol Indic 61(2):646–657. https://doi.org/10.1016/j.ecolind.2015.10.016

    Article  Google Scholar 

  11. Cushman SA, McKelvey KS, Noon BR, McGarigal K (2010) Use of abundance of one species as a surrogate for abundance of others. Conserv Biol 24(3):830–840. https://doi.org/10.1111/j.1523-1739.2009.01396.x

    Article  PubMed  Google Scholar 

  12. De Cáceres MD, Legendre P (2009) Associations between species and groups of sites: indices and statistical inference. Ecology 90(12):3566–3574. https://doi.org/10.1890/08-1823.1

    Article  PubMed  Google Scholar 

  13. Dufrene M, Legendre P (1997) Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecol Monogr 67(3):345–366

    Google Scholar 

  14. Favreau JM, Drew CA, Hess GR, Rubino MJ, Koch FH, Eschelback KA (2006) Recommendations for assessing the effectiveness of surrogate species approaches. Biodivers Conserv 15:3949–3969. https://doi.org/10.1007/s10531-005-2631-1

    Article  Google Scholar 

  15. Ferguson RG (1958) The preferred temperature of fish and their midsummer distribution in temperate lakes in temperate lakes and streams. J Fish Res Bd Canada 15(4):607–624. https://doi.org/10.1139/f58-032

    Article  Google Scholar 

  16. Ferris R, Humphrey JW (1999) A review of potential biodiversity indicators for application in British forests. Forestry 72(4):313–328. https://doi.org/10.1093/forestry/72.4.313

    Article  Google Scholar 

  17. Fox CA, Magilligan FJ, Sneddon CS (2016) “You kill the dam, you are killing a part of me”: dam removal and the environmental politics of river restoration. Geoforum 70:93–104. https://doi.org/10.1016/j.geoforum.2016.02.013

    Article  Google Scholar 

  18. Gillenwater D, Granata T, Zika U (2006) GIS-based modeling of spawning habitat suitability for walleye in the Sandusky River, Ohio, and implications for dam removal and river restoration. Ecol Eng 28(3):311–323. https://doi.org/10.1016/j.ecoleng.2006.08.003

    Article  Google Scholar 

  19. Graf WL (2006) Downstream hydrologic and geomorphic effects of large dams on American rivers. Geomorphology 79:336–360. https://doi.org/10.1016/j.geomorph.2006.06.022

    Article  Google Scholar 

  20. Grossman E (2002) Watershed: the undamming of America. Counterpoint, New York

    Google Scholar 

  21. Haxton T, Whelan G, Bruch R (2014) Historical biomass and sustainable harvest of Great Lakes lake sturgeon (Acipenser fulvescens Rafinesque, 1817). J Appl Ichthyol 30:1371–1378. https://doi.org/10.1111/jai.12569

    Article  Google Scholar 

  22. Hayden TA, Holbrook CM, Fielder DG, Vandergoot CS, Bergstedt RA, Dettmers JM, Krueger CC, Cooke SJ (2014) Acoustic telemetry reveals large-scale migration patterns of walleye in Lake Huron. PLoS ONE 9(12):e114833. https://doi.org/10.1371/journal.pone.0114833

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  23. Januchowski-Hartley SR, McIntyre PB, Diebel M, Doran PJ, Infante DM, Joseph C, Allan JD (2013) Restoring aquatic ecosystem connectivity requires expanding inventories of both dams and road crossings. Front Ecol Environ 11:211–217. https://doi.org/10.1890/120168

    Article  Google Scholar 

  24. Jones ML, Netto JK, Stockwell JD, Mion JB (2003) Does the value of newly accessible spawning habitat for walleye (Stizostedion vitreum) depend on its location relative to nursery habitat? Can J Fish Aquat Sci 60:1527–1538. https://doi.org/10.1139/f03-130

    Article  Google Scholar 

  25. Jorgensen D, Renofalt BM (2012) Damned if you do, dammed if you don’t: debates on dam removal in the Swedish media. Ecol Soc 18(1):18. https://doi.org/10.5751/ES-05364-180118

    Article  Google Scholar 

  26. Kemp PS, O’Hanley JR (2010) Procedures for evaluating and prioritising the removal of fish passage barriers: a synthesis. Fisheries Manag Ecol 17:297–322. https://doi.org/10.1111/j.1365-2400.2010.00751.x

    Article  Google Scholar 

  27. Khoury ML, Herbert ME, Yacobson E, Ross J (2018) Development of tributary conservation priorities for Great Lakes migratory fishes. Lansing, MI. https://www.conservationgateway.org/ConservationByGeography/NorthAmerica/wholesystems/greatlakes/watersheds/Documents/Dev_trib_conspriorities_GL_migfish.pdf

  28. Lambeck RJ (1997) Focal species: a multi-species umbrella for nature conservation. Conserv Biol 11(4):849–856. https://doi.org/10.1046/j.1523-1739.1997.96319.x

    Article  Google Scholar 

  29. Landres PB, Verner J, Thomas JW (1988) Ecological uses of vertebrate indicator species: a critique. Conserv Biol 2(4):316–328. https://doi.org/10.1111/j.1523-1739.1988.tb00195.x

    Article  Google Scholar 

  30. Lawler JJ, White D (2008) Assessing the mechanisms behind successful surrogates for biodiversity in conservation planning. Anim Conserv 11:270–280. https://doi.org/10.1111/j.1469-1795.2008.00176.x

    Article  Google Scholar 

  31. Lawler JJ, White D, Sifneos JC, Master LL (2003) Rare species and the use of indicator groups for conservation planning. Conserv Biol 17:875–882. https://doi.org/10.1046/j.1523-1739.2003.01638.x

    Article  Google Scholar 

  32. Lyons J, Zorn T, Stewart J, Seelbach P, Wehrly K, Wang L (2009) Defining and characterizing coolwater streams and their fish assemblages in Michigan and Wisconsin, USA. N Am J Fish Manage 29:1130–1151. https://doi.org/10.1577/M08-118.1

    Article  Google Scholar 

  33. Magnuson JJ, Crowder LB, Medvick PA (1979) Temperature as an ecological resource. Am Zool 19(1):331–343. https://doi.org/10.1093/icb/19.1.331

    Article  Google Scholar 

  34. Mansfield PJ (1984) Reproduction by Lake Michigan fishes in a tributary stream. Tam Fish Soc 113(2):231–237

    Article  Google Scholar 

  35. McCarthy DP, Donald PF, Scharlemann JPW, Buchanan GM, Balmford A, Green JMH, Bennum LA, Burgess ND, Fishpool LDC, Garnett ST, Leonard DL, Maloney RF, Morling P, Schaefer HM, Symes A, Wiedenfeld DA, Butchart STM (2012) Financial costs of meeting global biodiversity conservation targets: current spending and unmet needs. Science 338:946–949. https://doi.org/10.1126/science.1229803

    CAS  Article  PubMed  Google Scholar 

  36. McLaughlin RL, Smyth ERB, Castro-Santos T, Jones ML, Koops MA, Pratt TC, Velez-Espino L (2013) Unintended consequences and trade-offs of fish passage. Fish Fish 14:580–604. https://doi.org/10.1111/faf.12003

    Article  Google Scholar 

  37. Menezes S, Baird DJ, Soares AM (2010) Beyond taxonomy: a review of macroinvertebrate trait-based community descriptors as tools for freshwater biomonitoring. J Appl Ecol 47(4):711–719. https://doi.org/10.1111/j.1365-2664.2010.01819.x

    Article  Google Scholar 

  38. Meurant M, Gonzalez A, Doxa A, Albert CH (2018) Selecting surrogate species for connectivity conservation. Biol Conserv 227:326–334. https://doi.org/10.1016/j.biocon.2018.09.028

    Article  Google Scholar 

  39. Milt AW, Diebel MW, Doran PJ, Ferris MC, Herbert M, Khoury ML, Moody AT, Neeson TM, Ross J, Treska T, O’Hanley JR, Walter L, Wangen SR, Yacobson E, McIntyre PB (2018) Minimizing opportunity costs to aquatic connectivity restoration while controlling an invasive species. Conserv Biol. https://doi.org/10.1111/cobi.13105

    Article  PubMed  Google Scholar 

  40. Mion JB, Stein RA, Marschall EA (1998) River discharge drive survival of larval walleye. Ecol Appl 8(1):88–103

    Article  Google Scholar 

  41. Moody AT, Neeson TM, Wangen S, Dischler J, Diebel MW, Milt A, Herbert M, Khoury M, Yacobson E, Doran PJ, Ferris MC, O’Hanley JR, McIntyre PB (2017) Pet project or best project? Online decision support tools for prioritizing barrier removals in the Great Lakes and beyond. Fisheries 42(1):57–65. https://doi.org/10.1080/03632415.2016.1263195

    Article  Google Scholar 

  42. Morais GF, Santos Ribas LG, Goncalves Ortega JC, Heino J, Bini LM (2018) Biological surrogates: a word of caution. Ecol Indic 88:214–218. https://doi.org/10.1016/j.ecolind.2018.01.027

    Article  Google Scholar 

  43. Neeson TM, Mandelik Y (2014) Pairwise measures of species co-occurrence for choosing indicator species and quantifying overlap. Ecol Indic 45:721–727. https://doi.org/10.1016/j.ecolind.2014.06.006

    Article  Google Scholar 

  44. Neeson TM, Ferris MC, Diebel MW, Doran PJ, O’Hanley JR, McIntyre PB (2015) Enhancing ecosystem restoration efficiency through spatial and temporal coordination. Proc Natl Acad Sci 112(19):6236–6241. https://doi.org/10.1073/pnas.1423812112

    CAS  Article  PubMed  Google Scholar 

  45. Neeson TM, Doran PJ, Ferris MC, Fitzpatrick KB, Herbert M, Khoury M, Moody AT, Ross J, Yacobson E, McIntyre PB (2018) Conserving rare species can have high opportunity costs for common species. Glob Change Biol 24(8):3826–3872. https://doi.org/10.1111/gcb.14162

    Article  Google Scholar 

  46. Niemi GJ, Hanowski JM, Lima AR, Nicholls T, Weiland N (1997) A critical analysis on the use of indicator species in management. J Wildlife Manage 61(4):1240–1252. https://doi.org/10.2307/3802123

    Article  Google Scholar 

  47. Norden B, Paltto H, Gotmark F, Wallin K (2007) Indicators of biodiversity, what do they indicate? Lessons for conservation of cryptogams in oak-rich forest. Biol Conserv 135:369–379. https://doi.org/10.1016/j.biocon.2006.10.007

    Article  Google Scholar 

  48. Poff NL, Hart DD (2002) How dams vary and why it matters for the emerging science of dam removal. Bioscience 52(8):659–668

    Article  Google Scholar 

  49. R Core Team (2018) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.

  50. Reid SM, Mandrak NE, Carl LM, Wilson CC (2008) Influence of dams and habitat condition on the distribution of redhorse (Moxostoma) species in the Grand River watershed, Ontario. Environ Biol Fish 81(1):111–125. https://doi.org/10.1007/s10641-006-9179-0

    Article  Google Scholar 

  51. Rice JC, Rochet MJ (2005) A framework for selecting a suite of indicators for fisheries management. ICES J Mar Sci 62:516–527. https://doi.org/10.1016/j.icesjms.2005.01.003

    Article  Google Scholar 

  52. Rodrigues ACL, Brooks TM (2007) Shortcuts for biodiversity conservation planning: the effectiveness of surrogates. Annu Rev Ecol Evol S 38:713–737. https://doi.org/10.1146/annurev.ecolsys.38.091206.095737

    Article  Google Scholar 

  53. Rowland MM, Wisdom MJ, Suring LH, Meinke CW (2006) Greater sage-grouse as an umbrella species for sagebrush-associated vertebrates. Biol Conserv 126:323–335. https://doi.org/10.1016/j.biocon.2005.10.048

    Article  Google Scholar 

  54. Saetersdal M, Gjerde I (2011) Prioritising conservation areas using species surrogate measures: consistent with ecological theory? J Appl Ecol 48(5):1236–1240. https://doi.org/10.1111/j.1365-2664.2011.02027.x

    Article  Google Scholar 

  55. Schoener TW (1970) Nonsynchronous spatial overlap of lizards in patchy habitats. Ecology 51(3):408–418. https://doi.org/10.2307/1935376

    Article  Google Scholar 

  56. Simberloff D (1998) Flagships, umbrellas, and keystones: is single-species management passe in the landscape era? Biol Conserv 83(3):247–257. https://doi.org/10.1016/S0006-3207(97)00081-5

    Article  Google Scholar 

  57. Simberloff D (1999) The role of science in the preservation of forest biodiversity. Forest Ecol Manag 115:101–111. https://doi.org/10.1016/S0378-1127(98)00391-0

    Article  Google Scholar 

  58. Stanley EH, Doyle MW (2003) Trading off: the ecological effects of dam removal. Front Ecol Environ 1(1):15–22

    Article  Google Scholar 

  59. Tulloch A, Possingham HP, Wison K (2011) Wise selection of an indicator for monitoring the success of management actions. Biol Conserv 144:141–154. https://doi.org/10.1016/j.biocon.2010.08.009

    Article  Google Scholar 

  60. Wehrly KE, Wiley MJ, Seelbach PW (2003) Classifying regional variation in thermal regime based on stream fish community patterns. T Am Fish Soc 132(1):18–38

    Article  Google Scholar 

  61. Whittaker RJ, Araujo MB, Jepson P, Ladle RJ, Watson JEM, Willis KJ (2005) Conservation biogeography: assessment and prospect. Divers Distrib 11(1):3–23. https://doi.org/10.1111/j.1366-9516.2005.00143.x

    Article  Google Scholar 

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Acknowledgements

We are grateful for comments and suggestions from B. Hoagland, R. Loraamm, and LCLUC group at the University of Oklahoma on earlier drafts of this paper. Funding was provided by the Upper Mid-west and Great Lakes Landscape Conservation Cooperative, The Nature Conservancy’s Great Lakes Project, The University of Wisconsin, The Great Lakes Fishery Trust, The University of Michigan Water Center, and the Department of Interior Northeast Climate Science Center. Its contents are solely the responsibility of the authors and do not necessarily represent the views of the Northeast Climate Science Center or the USGS. This manuscript is submitted for publication with the understanding that the US Government is authorized to reproduce and distribute prints for Governmental purposes.

Funding

Funding was provided by the Upper Mid-west and Great Lakes Landscape Conservation Cooperative, The Nature Conservancy’s Great Lakes Project, The University of Wisconsin, The Great Lakes Fishery Trust, The University of Michigan Water Center, and the Department of Interior Northeast Climate Science Center.

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KBF and TMN contributed to the study concept. MEH, MK, EY, JAR, and PJD collected and prepared the data. KBF, ATM, AM, MCF, PBM, and TMN developed the models and analyzed the data. The first draft of the manuscript was written by KBF and TMN and all authors provided comments on previous versions of the manuscript.

Corresponding author

Correspondence to Kimberly B. Fitzpatrick.

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All authors declare that they have no conflict of interest.

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Communicated by Angus Jackson.

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Fitzpatrick, K.B., Moody, A.T., Milt, A. et al. Can indicator species guide conservation investments to restore connectivity in Great Lakes tributaries?. Biodivers Conserv (2020). https://doi.org/10.1007/s10531-020-02084-5

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Keywords

  • Surrogate species
  • Fragmentation
  • River restoration
  • Freshwater
  • Dams
  • Road culverts