Landscape Ecology

, Volume 25, Issue 10, pp 1547–1560 | Cite as

Maintaining or restoring connectivity of modified landscapes: evaluating the least-cost path model with multiple sources of ecological information

Research Article

Abstract

Habitat connectivity is an important element of functioning landscapes for mobile organisms. Maintenance or creation of movement corridors is one conservation strategy for reducing the negative effects of habitat fragmentation. Numerous spatial models exist to predict the location of movement corridors. Few studies, however, have investigated the effectiveness of these methods for predicting actual movement paths. We used an expert-based model and a resource selection function (RSF) to predict least-cost paths of woodland caribou. Using independent data for model evaluation, we found that the expert-based model was a poor predictor of long-distance animal movements; in comparison, the RSF model was effective at predicting habitat selection by caribou. We used the Path Deviation Index (PDI), cumulative path cost, and sinuosity to quantitatively compare the spatial differences between inferred caribou movement paths and predicted least-cost paths, and quasi-random null models of directional movement. Predicted movement paths were on average straighter than inferred movement paths for collared caribou. The PDI indicated that the least-cost paths were no better at predicting the inferred paths than either of two null models—straight line paths and randomly generated paths. We found statistically significant differences in cumulative cost scores for the main effects of model and path type; however, post-hoc comparisons were non-significant suggesting no difference among inferred, random, and predicted least cost paths. Paths generated from an expert based cost surface were more sinuous than those premised on the RSF model, but neither differed from the inferred path. Although our results are specific to one species, they highlight the importance of model evaluation when planning for habitat connectivity. We recommend that conservation planners adopt similar techniques when validating the effectiveness of movement corridors for other populations and species.

Keywords

Animal movement Corridor Expert-based model Fragmentation Least-cost path Path deviation index Resource selection function 

Notes

Acknowledgments

We thank M. Gillingham and J. Kirkpatrick for insightful comments during the development of this paper. P. Beier and two anonymous reviewers provided a thorough review of the manuscript. Following submission, the Coordinating Editor, H. Wagner, skilfully navigated the paper through the review process and was instrumental in improving the final version. S. McNay kindly donated unpublished caribou locations that allowed us to evaluate the predictions of the RSF and expert-based models.

Supplementary material

10980_2010_9526_MOESM1_ESM.jpg (10.7 mb)
Supplementary material 1 (JPEG 10941 kb)
10980_2010_9526_MOESM2_ESM.jpg (11 mb)
Supplementary material 2 (JPEG 11240 kb)
10980_2010_9526_MOESM3_ESM.jpg (11 mb)
Supplementary material 3 (JPEG 11216 kb)
10980_2010_9526_MOESM4_ESM.jpg (11.1 mb)
Supplementary material 4 (JPEG 11321 kb)

References

  1. Apps CD, McLellan BN (2006) Factors influencing the dispersion and fragmentation of endangered mountain caribou populations. Biol Conserv 130:84–97CrossRefGoogle Scholar
  2. Beier P, Majka DR, Spencer WD (2008) Forks in the road: choices in procedures for designing wildland linkages. Conserv Biol 22:836–851CrossRefPubMedGoogle Scholar
  3. Beyer HL (2004) Hawth’s analysis tools for ArcGIS. http://www.spatialecology.com/htools
  4. Boyce MS, Vernier PR, Nielsen SE, Schmiegelow FKA (2002) Evaluating resource selection functions. Ecol Model 157:281–300CrossRefGoogle Scholar
  5. Chetkiewicz CLB, Boyce MS (2009) Use of resource selection functions to identify conservation corridors. J Appl Ecol 46:1036–1047CrossRefGoogle Scholar
  6. Chetkiewicz CLB, St. Clair CC, Boyce MS (2006) Corridors for conservation: integrating pattern and process. Annu Rev Ecol Syst 37:317–342CrossRefGoogle Scholar
  7. Clevenger AP, Wierzchowski J, Chruszcz B, Gunson K (2002) GIS-generated expert based models for identifying wildlife habitat linkages and mitigation passage planning. Conserv Biol 16:503–514CrossRefGoogle Scholar
  8. Couvet D (2002) Deleterious effects of restricted gene flow in fragmented populations. Conserv Biol 16:369–376CrossRefGoogle Scholar
  9. Csuti B (1991) Conservation corridors: countering habitat fragmentation. In: Hudson WE (ed) Landscape linkages and biodiversity. Island Press, Washington, pp 81–90Google Scholar
  10. de Smith MJ (2004) Distance and path: the development, interpretation and application of distance measurement in mapping and spatial modelling. PhD thesis, University of London, University College, Department of Geography, LondonGoogle Scholar
  11. Eastman JR (2004) IDRISI Kilimanjaro, version 14.01. Clark University Laboratory, Clark University, WorcesterGoogle Scholar
  12. ESRI (2005) ArcGIS—ArcInfo, version 9.1. Environmental Systems Research Institute, Inc, RedlandsGoogle Scholar
  13. Fortin D, Beyer HL, Boyce MS, Smith DW, Duchesne T, Mao JS (2005) Wolves influence elk movements: behavior shapes a trophic cascade in Yellowstone National Park. Ecology 86:1320–1330CrossRefGoogle Scholar
  14. Goncalves AB (2010) An extension of GIS-based least cost path modelling to the location of wide paths. Int J Geogr Inf Sci 24:983–996CrossRefGoogle Scholar
  15. Harris LD (1984) The fragmented forest: island biogeography theory and the preservation of biotic diversity. The University of Chicago Press, ChicagoGoogle Scholar
  16. Hoekstra JM, Boucher TM, Ricketts TH, Roberts C (2005) Confronting a biome crisis: global disparities of habitat loss and protection. Ecol Lett 8:23–29CrossRefGoogle Scholar
  17. Hosmer DW, Lemeshow S (2000) Applied logistic regression, 2nd edn. Wiley, New YorkGoogle Scholar
  18. Hurley MV, Rapaport EK, Johnson CJ (2009) Utility of expert-based knowledge for predicting wildlife-vehicle collisions. J Wild Manag 73:278–286CrossRefGoogle Scholar
  19. Jan O, Horowitz AJ, Peng Z-R (1999) Using GPS data to understand variations in path choice. Paper presented at the 78th meeting of the Transportation Research Board, WashingtonGoogle Scholar
  20. Jenness J (2004) Alternate animal movement routes (altroutes.avx) extension for ArcView 3.x, v. 2.1. Jenness Enterprises. http://www.jennessent.com/arcview/alternate_routes.htm
  21. Johnson CJ, Gillingham MP (2004) Mapping uncertainty: sensitivity of wildlife habitat ratings to variation in expert opinion. J Appl Ecol 41:1032–1041CrossRefGoogle Scholar
  22. Johnson CJ, Gillingham MP (2005) An evaluation of mapped species distribution models used for conservation planning. Environ Conserv 32:117–128CrossRefGoogle Scholar
  23. Johnson CJ, Heard DC, Parker KL (2002a) Expectations and realities of GPS animal location collars: results of three years in the field. Wild Biol 8:153–159Google Scholar
  24. Johnson CJ, Parker KL, Heard DC, Gillingham MP (2002b) A multiscale behavioural approach to understanding the movements of woodland caribou. Ecol Appl 12:1840–1860CrossRefGoogle Scholar
  25. Johnson CJ, Parker KL, Heard DC, Gillingham MP (2002c) Movement parameters of ungulates and scale-specific responses to the environment. J Anim Ecol 71:225–235CrossRefGoogle Scholar
  26. Johnson CJ, Alexander ND, Wheate RD, Parker KL (2003) Characterizing woodland caribou habitat in sub-boreal and boreal forests. For Ecol Manag 180:241–248CrossRefGoogle Scholar
  27. Johnson CJ, Seip DR, Boyce MS (2004) A quantitative approach to conservation planning: using resource selection functions to identify important habitats for mountain caribou. J Appl Ecol 41:238–251CrossRefGoogle Scholar
  28. Kautz R, Kawula R, Hoctor T, Comiskey J, Jansen D, Jennings D, Kasbohm J, Mazzotti F, McBride R, Richardson L, Root K (2006) How much is enough? Landscape-scale conservation for the Florida panther. Biol Conserv 130:118–133CrossRefGoogle Scholar
  29. Kehoe NM (1995) Grizzly bear distribution in the north fork of the Flathead River valley: a test of the linkage zone prediction model. MS thesis. University of Montana, MissoulaGoogle Scholar
  30. Kindall JL, Van Manen FT (2007) Identifying habitat linkages for American black bears in North Carolina, USA. J Wild Manag 71:487–495CrossRefGoogle Scholar
  31. Manly BFJ, McDonald LL, Thomas DL, McDonald TL, Erickson WP (2002) Resource selection by animals: statistical design and analysis for field studies. Kluwer, DordrechtGoogle Scholar
  32. Menard S (1995) Applied logistic regression analysis. Quantitative applications in the social sciences series no. 07-106. Sage University, Thousand Oaks, CAGoogle Scholar
  33. Merriam G (1991) Corridors and connectivity: animal populations in heterogeneous environments. In: Saunders DA, Hobbs RJ (eds) Nature conservation 2: the role of corridors. Surrey Beatty and Sons Pty Ltd, Chipping Norton, pp 133–142Google Scholar
  34. Murray JV, Goldizen AW, O’Leary RA, McAlpine CA, Possingham HP, Choy SL (2009) How useful is expert opinion for predicting the distribution of a species within and beyond the region of expertise? A case study using brush-tailed rock-wallabies Petrogale penicillata. J Appl Ecol 46:842–851CrossRefGoogle Scholar
  35. Noss RF (1991) Landscape connectivity: different functions at difference scales. In: Hudson W (ed) Landscape linkages and biodiversity. Island Press, Washington, pp 27–38Google Scholar
  36. Pace F (1991) The Klamath corridors: preserving biodiversity in the Klamath National Forest. In: Hudson W (ed) Landscape linkages and biodiversity. Island Press, Washington, pp 105–116Google Scholar
  37. Pearce J, Ferrier S (2000) Evaluating the predictive performance of habitat models developed using logistic regression. Ecol Model 133:225–245CrossRefGoogle Scholar
  38. Poole KG, Heard DC, Mowat G (2000) Habitat use by woodland caribou near Takla Lake in central British Columbia. Can J Zool 78:1552–1561CrossRefGoogle Scholar
  39. Ray N, Lehmann A, Joly P (2002) Modeling spatial distribution of amphibian populations: a GIS approach based on habitat matrix permeability. Biodivers Conserv 11:2143–2165CrossRefGoogle Scholar
  40. Richard Y, Armstrong DP (2010) Cost distance modelling of landscape connectivity and gap-crossing ability using radio-tracking data. J Appl Ecol 47:603–610CrossRefGoogle Scholar
  41. Ricketts TH (2002) The matrix matters: effective isolation in fragmented landscapes. Am Nat 158:87–99CrossRefGoogle Scholar
  42. Rouget M, Cowling RM, Lombard AT, Knight AT, Graham IHK (2006) Designing large-scale conservation corridors for pattern and process. Conserv Biol 20:549–561CrossRefPubMedGoogle Scholar
  43. Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15:234–281CrossRefGoogle Scholar
  44. Saher DJ, Schmiegelow FKA (2005) Movement pathways and habitat selection by woodland caribou during spring migration. Rangifer 16:143–154Google Scholar
  45. Simberloff DS, Cox J (1987) Consequences and costs of conservation corridors. Conserv Biol 1:63–71CrossRefGoogle Scholar
  46. Simberloff DS, Farr JA, Cox J, Mehiman DW (1992) Movement corridors: conservation bargains or poor investments? Conserv Biol 6:493–504CrossRefGoogle Scholar
  47. Singleton PH, Gaines WL, Lehmkuhl JF (2002) Landscape permeability for large carnivores in Washington: a geographic information system weighted-distance and least-cost corridor assessment. U.S. Department of Agriculture, Pacific Northwest Research Station, PortlandGoogle Scholar
  48. Soulé ME, Mackey BG, Recher HF, Williams JE, Woinarski JCZ, Driscoll D, Dennison WC, Jones ME (2004) The role of connectivity in Australian conservation. Pac Conserv Biol 10:266–279Google Scholar
  49. Walker R, Craighead L (1997) Least-cost-path corridor analysis: analyzing wildlife movement corridors in Montana using GIS. In: Proceedings of the ESRI user’s conference, San DiegoGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.School of Geography and Environmental StudiesUniversity of TasmaniaHobartAustralia
  2. 2.Ecosystem Science and Management ProgramUniversity of Northern British ColumbiaPrince GeorgeCanada

Personalised recommendations