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Biodiversity and Conservation

, Volume 26, Issue 14, pp 3343–3361 | Cite as

Habitat selection by Canada lynx: making do in heavily fragmented landscapes

  • Carmen VanbianchiEmail author
  • William L. Gaines
  • Melanie A. Murphy
  • Jason Pither
  • Karen E. HodgesEmail author
Original Paper

Abstract

Habitat loss and fragmentation result in landscapes where high quality habitat patches are surrounded by matrix habitats of low and variable quality. For mobile species to persist in such landscapes, individual animals often rely on the high quality habitats but also use matrix habitats for supplemental resources or while moving between higher quality patches. Determining what habitat features animals select when in these matrix areas is important, as retaining desirable features in lower quality habitats may enable species persistence. We examine a population of US federally threatened Canada lynx (Lynx canadensis) in northcentral Washington, near the southwestern range limit, where lynx habitat is fragmented by topography, wildfires, and human impacts. We used Global Positioning System radio-collar data from 17 lynx in the North Cascade Mountains during 2007–2013 to explore lynx habitat use. We used Random Forest models to analyze core hunting, resting, and denning habitat, and the habitats lynx select while between patches of core habitat. While selecting core habitat, lynx used spruce (Picea engelmannii)-fir (Abies lasiocarpa), lodgepole pine (Pinus contorta), and mixed sub-boreal-Douglas fir (Pseudotsuga menziesii) forests, and avoided dry forests and forest openings including new burns. When not in core habitat, lynx used a wider range of habitats, including new burns where fire skips and residual trees offered cover. Our results show clearly that Canada lynx tolerate a wider range of habitats where they occupy fragmented landscapes. Consequently, maintaining animals in fragmented landscapes requires that we identify and conserve not only the core habitats a particular species selects, but also the habitat features animals use while in less suitable environments.

Keywords

Habitat fragmentation Habitat selection Lynx canadensis Predators Random Forest models Wildfire 

Notes

Acknowledgements

Funding was provided by the University of British Columbia and a Natural Sciences and Engineering Research Council grant (312222) to KEH. Lynx trapping and collaring were funded as a joint project of the Washington Department of Fish and Wildlife, Washington Department of Natural Resources, U.S. Forest Service, U.S. Bureau of Land Management, and the U.S. Fish and Wildlife Service. Data are archived with the Washington Department of Fish and Wildlife and at the University of British Columbia. The paper was strengthened by feedback from J. Squires. C. Vanbianchi developed the idea, analysed data, and was the primary author. M. Murphy advised on Random Forest models. J. Pither assisted with GIS and R work, advised on Random Forest and sampling methods, and provided editorial feedback. W. Gaines advised on the GIS layers and habitat variables to include. K.E. Hodges developed the idea, advised on all analyses, obtained funding, and helped revise the paper. All authors contributed to the final version of the paper.

References

  1. Agee JK (2000) Disturbance ecology of North American boreal forests and associated northern mixed/subalpine forest. In: Ruggiero LF, Aubry KB, Buskirk SW, Koehler GM, Krebs CJ, McKelvey KS, Squires JR (eds) Ecology and conservation of lynx in the United States. University of Colorado Press, Boulder, pp 39–82Google Scholar
  2. Baddeley A, Rubak E, Turner R. (2015) Spatial point patterns: methodology and applications with R. London: Chapman and Hall/CRC Press. http://www.crcpress.com/Spatioal-Point-Patterns-Methodology-and-Applications-with-R/Baddeley-Rubak-Turner/9781482210200/
  3. Balshi MS, McGuire AD, Duffy P, Flannigan M, Walsh J, Melillo J (2009) Assessing the response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach. Glob Change Biol 15:578–600CrossRefGoogle Scholar
  4. Barbet-Massin M, Jiguet F, Albert CH, Thuiller W (2012) Selecting pseudo-absences for species distribution models: how, where and how many? Methods Ecol Evol 3:327–338CrossRefGoogle Scholar
  5. Belant JL (2009) Effects of antenna orientation and vegetation on Global Positioning System telemetry collar performance. Northeast Nat 16:577–584CrossRefGoogle Scholar
  6. Bivand RS, Pebesma E, Gomez-Rubio V (2013) Applied spatial data analysis with R, 2nd edn. Springer, NY. http://www.asdar-book.org/
  7. Breiman L (2001) Random Forests. Mach Learn 45:5–32CrossRefGoogle Scholar
  8. Buskirk ST, Ruggiero LR, Aubry KB, Pearson DE, Squires JR, McKelvey KS (2000) Comparative ecology of lynx in North America. In: Ruggiero LF, Aubry KB, Buskirk SW, Koehler GM, Krebs CJ, McKelvey KS, Squires JR (eds) Ecology and conservation of lynx in the United States. University of Colorado Press, Boulder, pp 397–418Google Scholar
  9. Chetkiewicz C-LB, St. Clair CC, Boyce MS (2006) Corridors for conservation: integrating pattern and process. Annu Rev Ecol Evol Syst 37:317–342CrossRefGoogle Scholar
  10. Cushman SA (2010) Animal movement data: GPS telemetry, autocorrelation and the need for path-level analysis. In: Cushman SA, Huettmann F (eds) Spatial complexity, informatics, and wildlife conservation. Springer, Tokyo, pp 131–149CrossRefGoogle Scholar
  11. Cutler DR, Edwards TC, Beard KH, Cutler A, Hess KT, Gibson J, Lawler JJ (2007) Random Forest for classification in ecology. Ecology 88:2783–2792CrossRefPubMedGoogle Scholar
  12. Elliot NB, Cushman SA, Loveridge AJ, Mtare G, Macdonald DW (2014) Movements vary according to dispersal stage, group size, and rainfall: the case of the African lion. Ecology 95:2860–2869CrossRefGoogle Scholar
  13. ESRI (2012) ArcGIS 10.1. ESRI, RedlandsGoogle Scholar
  14. Evans, J.S. (2015) spatialEco. R package version 2.0-0. http://CRAN.R-project.org/package=spatialEco
  15. Evans JS, Cushman SA (2009) Gradient modeling of conifer species using random forests. Landsc Ecol 24:673–683CrossRefGoogle Scholar
  16. Evans JS, Murphy MA (2014) rfUtilities. R package version 1.0-0. http://CRAN.R-project.org/package=rfUtilities
  17. Evans JS, Murphy MA, Holden ZA, Cushman SA (2011) Modeling species distribution and change using Random Forest. In: Drew AD, Wiersma YF, Huettmann F (eds) Predictive species and habitat modeling in landscape ecology: concepts and applications. Springer, New York, pp 139–159CrossRefGoogle Scholar
  18. Fauria MM, Johnson EA (2007) Climate and wildfires in the North American boreal forest. Philos Trans R Soc B Biol Sci 363:2317–2329Google Scholar
  19. Fisichelli NA, Frelich LE, Reich PB (2014) Temperate tree expansion into adjacent boreal forest patches facilitated by warmer temperatures. Ecography 37:152–161CrossRefGoogle Scholar
  20. Fox JF (1978) Forest fires and the snowshoe hare-Canada lynx cycle. Oecologia 31:349–374CrossRefPubMedGoogle Scholar
  21. Franklin JF, Dyrness CT (1973) Natural vegetation of Oregon and Washington. U.S. Forest Service, General Technical Report PNW-GTR-008:1-427Google Scholar
  22. Fuller AK, Harrison DJ, Vashon JH (2007) Winter habitat selection by Canada lynx in Maine: prey abundance or accessibility? J Wildl Manag 71:1980–1986CrossRefGoogle Scholar
  23. Gessler PE, Moore ID, McKenzie NJ, Ryan PJ (1995) Soil-landscape modeling and spatial prediction of soil attributes. Int J GIS 9:421–432Google Scholar
  24. Haddad NM, Tewksbury JJ (2005) Low-quality habitat corridors as movement conduits for two butterfly species. Ecol Appl 15:250–257CrossRefGoogle Scholar
  25. Hebblewhite M, Percy M, Merrill EH (2007) Are all global positioning system collars created equal? Correcting habitat-induced bias using three brands in the central Canadian Rockies. J Wildl Manag 71:2026–2033CrossRefGoogle Scholar
  26. Hodges KE (2000) Ecology of snowshoe hares in southern boreal and montane forest. In: Ruggiero LF, Aubry KB, Buskirk SW, Koehler GM, Krebs CJ, McKelvey KS, Squires JR (eds) Ecology and conservation of lynx in the United States. University of Colorado Press, Boulder, pp 163–206Google Scholar
  27. Hornseth ML, Walpole AA, Walton LR, Bowman J, Ray JC, Fortin M, Murray DL (2014) Habitat loss, not fragmentation, drives occurrence patterns of Canada lynx at the southern range periphery. PLoS ONE 9:1–11CrossRefGoogle Scholar
  28. Hoving CL, Harrison DJ, Krohn WB, Jakubas WJ, McCollough MA (2004) Canada lynx Lynx canadensis habitat and forest succession in northern Maine, USA. Wildl Biol 10:285–294Google Scholar
  29. Imre I, Derbowka D (2011) Major threats facing terrestrial mammals in Canada. Can Field Nat 125:213–219CrossRefGoogle Scholar
  30. Keinath D, Doak D, Hodges KE, Prugh L, Fagan W, Sekercioglu C, Buchart S, Kauffman M (2016) A global analysis of species sensitivity to habitat disturbance. Glob Ecol Biogeogr. doi: 10.1111/geb.12509 Google Scholar
  31. Koehler GM (1990) Population and habitat characteristics of lynx and snowshoe hares in north central Washington. Can J Zool 68:845–851CrossRefGoogle Scholar
  32. Koehler GM, Maletzke BT, von Kienast JA, Aubry KB, Wielgus RB, Naney RH (2008) Habitat fragmentation and the persistence of lynx populations in Washington State. J Wildl Manag 72:1518–1524Google Scholar
  33. Kosterman MK (2014) Correlates of Canada lynx reproductive success in Northwestern Montana. M. S. Thesis, University of Montana, Missoula, USAGoogle Scholar
  34. Laliberte AS, Ripple WJ (2004) Range contractions of North American carnivores and ungulates. Bioscience 54:123–138CrossRefGoogle Scholar
  35. Lewis JC (2016) Draft periodic status review for the Lynx in Washington. Washington Department of Fish and Wildlife, OlympiaGoogle Scholar
  36. Lewis CW, Hodges KE, Koehler GM, Mills LS (2011) Influence of stand and landscape features on snowshoe hare abundance in fragmented forests. J Mamm 93:561–567CrossRefGoogle Scholar
  37. Liaw A, Wiener M (2002) Classification and regression by random forest. R News 2:18–22Google Scholar
  38. Lillybridge TR, Kovalchik BL, Williams CK, Smith BG (1995) Field guide for forested plant associations of the Wenatchee National Forest. US Forest Service, General Technical Report, PNW-GTR-359:1-335Google Scholar
  39. Littell JS, Oneil EE, McKenzie D, Hicke JA, Lutz JA, Norheim RA, Elsner MM (2010) Forest ecosystems, disturbance, and climate change in Washington State, USA. Clim Change 102:129–158CrossRefGoogle Scholar
  40. Maletzke BT, Koehler GM, Wielgus RB, Aubry KB, Evans MA (2008) Habitat conditions associated with lynx hunting behavior during winter in northern Washington. J Wildl Manag 72:1473–1478Google Scholar
  41. McCann NP, Moen RA (2011) Mapping potential core areas for lynx (Lynx canadensis) using pellet counts from snowshoe hares (Lepus americanus) and satellite imagery. Can J Zool 89:509–516CrossRefGoogle Scholar
  42. McCune B, Keon D (2002) Equations for potential annual direct incident radiation and heat load index. J Veg Sci 13:603–606CrossRefGoogle Scholar
  43. McKelvey KS, Buskirk SW, Krebs CJ (2000a) Theoretical insights into the population viability of lynx. In: Ruggiero LF, Aubry KB, Buskirk SW, Koehler GM, Krebs CJ, McKelvey KS, Squires JR (eds) Ecology and conservation of lynx in the United States. University of Colorado Press, Boulder, pp 21–38Google Scholar
  44. McKelvey KS, Ortega YK, Koehler GM, Aubry KB, Brittell JD (2000b) Canada lynx habitat and topography use patterns in north central Washington: a reanalysis. In: Ruggiero LF, Aubry KB, Buskirk SW, Koehler GM, Krebs CJ, McKelvey KS, Squires JR (eds) Ecology and conservation of lynx in the United States. University of Colorado Press, Boulder, pp 307–336Google Scholar
  45. Mech LD (1973) Canadian lynx invasion of Minnesota. Biol Cons 5:151–152CrossRefGoogle Scholar
  46. Moen R, Burdett CL, Niemi GJ (2008) Movement and habitat use of Canada lynx denning in Minnesota. J Wildl Manag 72:1507–1513CrossRefGoogle Scholar
  47. Moore ID, Gessler PE, Nielsen GA, Petersen GA (1993) Terrain attributes: estimation methods and scale effects. In: Jakeman AJ, Beck MB, McAleer M (eds) Modeling change in environmental systems. Wiley, London, pp 189–214Google Scholar
  48. Mowat G, Slough B (2003) Habitat preference of Canada lynx through a cycle in snowshoe hare abundance. Can J Zool 81:1736–1745CrossRefGoogle Scholar
  49. Murphy MA, Evans JS, Storfer A (2010) Quantifying Bufo boreas connectivity in Yellowstone National Park with landscape genetics. Ecology 91:252–261CrossRefPubMedGoogle Scholar
  50. Pebesma EJ, Bivand RS (2005) Classes and methods for spatial data in R. R News 5 (2). http://cran.r-project.org/doc/Rnews/
  51. Prugh LR, Hodges KE, Sinclair ARE, Brashares JS (2008) Effect of habitat area and isolation on fragmented animal populations. Proc Natl Acad Sci 105:20770–20775CrossRefPubMedPubMedCentralGoogle Scholar
  52. Pulliam HR (1988) Sources, sinks, and population regulation. Am Nat 132:652–661CrossRefGoogle Scholar
  53. Purvis A, Gittleman JL, Cowlishaw G, Mace GM (2000) Predicting extinction risk in declining species. Proc R Soc Lond Ser B 267:1947–1952CrossRefGoogle Scholar
  54. Ruediger B, Claar J, Gniadek S, Holt B, Lewis L, Mighton S, Naney B, Patton G, Rinaldi T, Trick J, Vandehey A, Wahl F, Warren N, Wenger D, Williamson A (2000) Canada lynx conservation assessment and strategy USDA Forest Service, USDI Fish and Wildlife Service, USDI Bureau of Land Management, and USDI National Park Service. Forest Service Publication #R1-00-53, Missoula, MontanaGoogle Scholar
  55. Simons-Legaard EM, Harrison DJ, Krohn WB, Vashon JH (2013) Canada lynx occurrence and forest management in the Acadian Forest. J Wildl Manag 77:567–578CrossRefGoogle Scholar
  56. Soja AJ, Tchebakova NM, French NHF, Flannigan MD, Shugart HH, Stocks BJ, Sukhinin AI, Parfenova EI, Chapin SF III, Stackhouse PW Jr (2007) Climate-induced boreal forest change: predictions versus current observations. Glob Planet Change 56:247–296CrossRefGoogle Scholar
  57. Squires JR, Laurion T (2000) Lynx home range and movements in Montana and Wyoming: preliminary results. In: Ruggiero LF, Aubry KB, Buskirk SW, Koehler GM, Krebs CJ, McKelvey KS, Squires JR (eds) Ecology and conservation of lynx in the United States. University of Colorado Press, Boulder, pp 337–350Google Scholar
  58. Squires JR, Decesare NJ, Kolbe JA, Ruggiero LF (2010) Seasonal resource selection of Canada lynx in managed forests of the Northern Rocky Mountains. J Wildl Manag 74:1648–1660CrossRefGoogle Scholar
  59. Stinson DW (2001) Washington state recovery plan for the lynx. Washington Department of Fish and Wildlife, OlympiaGoogle Scholar
  60. U.S. Fish and Wildlife Service (2000) Determination of threatened status for the contiguous U.S. distinct population segment of the Canada lynx and related rule; final rule. Fed Reg 65:16052–16086Google Scholar
  61. Vanbianchi C (2015) Habitat use and connectivity for Canada lynx in the North Cascade Mountains, Washington. M.S. thesis, University of British Columbia Okanagan. Kelowna, British Columbia, CanadaGoogle Scholar
  62. Vanbianchi C, Murphy MA, Hodges KE (2017) Hotter summers and larger fires: implications for protecting threatened Canada lynx. Ecol Evol. doi: 10.1002/ece3.2824 PubMedPubMedCentralGoogle Scholar
  63. Vashon JH, Meehan AL, Organ JF, Jakubas WJ, McLaughlin CR, Vashon AD, Crowley SM (2008) Diurnal habitat relationships of Canada lynx in an intensively managed private forest landscape in northern Maine. J Wildl Manag 72:1488–1496CrossRefGoogle Scholar
  64. von Kienast J (2003) Winter habitat selection and food habits of lynx on the Okanogan Plateau, Washington. M.S. Thesis, University of Washington. Seattle, Washington, USAGoogle Scholar
  65. Walker CJ (2005) Influences of landscape structure on snowshoe hare populations in fragmented forests. M. S. Thesis, University of Montana. Missoula, Montana, USAGoogle Scholar
  66. Wiens JA (2006) Introduction: connectivity research-what are the issues? In: Crooks KR, Sanjayan M (eds) Connectivity conservation. Cambridge University Press, United Kingdom, pp 24–27Google Scholar
  67. Wilcove DS, Rothstein D, Dubow J, Philliph A, Losos E (1998) Quantifying threats to imperiled species in the United States. Bioscience 48:607–615CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Biology DepartmentUniversity of British Columbia OkanaganKelownaCanada
  2. 2.Washington Conservation Science InstituteLeavenworthUSA
  3. 3.Department of Ecosystem Science and Management, Program in EcologyUniversity of WyomingLaramieUSA

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