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Landscape Ecology

, Volume 24, Issue 1, pp 77–88 | Cite as

Modeling patch occupancy: Relative performance of ecologically scaled landscape indices

  • Carol E. Rizkalla
  • Jeffrey E. Moore
  • Robert K. Swihart
Research Article

Abstract

In fragmented landscapes, the likelihood that a species occupies a particular habitat patch is thought to be a function of both patch area and patch isolation. Ecologically scaled landscape indices (ESLIs) combine a species’ ecological profile, i.e., area requirements and dispersal ability, with indices of patch area and connectivity. Since their introduction, ESLIs for area have been modified to incorporate patch quality. ESLIs for connectivity have been modified to incorporate niche breadth, which may influence a species’ ease in crossing the non-habitat matrix between patches. We evaluated the ability of 4 ESLIs, the original and modified indices of area and connectivity, to explain patterns in patch occupancy of 5 forest rodents. Occupancy of eastern gray squirrels (Sciurus carolinensis), North American red squirrels (Tamiasciurus hudsconicus), fox squirrels (Sciurus niger), white-footed mice (Peromyscus leucopus), and eastern chipmunks (Tamias striatus) was modeled at 471 sites in 35 landscapes sampled from the upper Wabash River basin in Indiana. Models containing ESLIs received support for gray squirrels, red squirrels, and chipmunks. Modified ESLIs were important in models for red squirrels. However, none of the models demonstrated high predictive ability. Incorporating habitat quality and using surrogate measures of dispersal can have important effects on model results. Additionally, different responses of species to area, isolation, and habitat quality suggest that generalizing patterns of metapopulation dynamics was not justified, even across closely related species.

Keywords

Connectivity Forest rodent Metapopulation Niche breadth Patch area 

Notes

Acknowledgments

We are grateful to hundreds of private landowners who allowed access to their properties. Dozens of field technicians and crew chiefs collected data or digitized GIS layers. J. Crick, T. Preuss, L. Connolly, and N. Engbrecht coordinated field efforts, helped develop field protocols, and collected and managed data. J. Goheen provided data from tree squirrel mobility studies. M. Miller provided the script for ESLI calculation. P. Waser, T. Wiegand, and two anonymous reviewers provided useful comments on the manuscript. Our GIS data sources included the Center for Advanced Applications in GIS at Purdue University, National Land Cover Data, Indiana Unified Watershed Assessment, and the National Water Information System. Funding was provided by the John S. Wright Fund, Department of Forestry and Natural Resources, Purdue University, the U.S. Department of Education Graduate Assistance in Areas of National Need Award P200A030188, and the Cooperative State Research, Education, and Extension Service, U.S. Department of Agriculture, under Agreement No. 2000-04649.

References

  1. Akaike H (1973) Information theory as an extension of the maximum likelihood principle. In: Petrov BN, Csaki F (eds) Second international symposium on information theory. Akademiai Kiado, BudapestGoogle Scholar
  2. Bennett AF, Henein K, Merriam G (1994) Corridor use and the elements of corridor quality: chipmunks and fencerows in a farmland mosaic. Biol Conserv 68:155–165. doi: 10.1016/0006-3207(94)90347-6 CrossRefGoogle Scholar
  3. Burnham KP, Anderson DR (2002) Model selection and multi-model inference. Springer-Verlag, New YorkGoogle Scholar
  4. Cooch E, White G (2004) Program MARK: a gentle introduction. Available from http://www.phidot.org/software/mark/docs/book/
  5. Cummings JR, Vessey SH (1994) Agricultural influences on movement patterns of white-footed mice (Peromyscus leucopus). Am Midl Nat 132:209–218. doi: 10.2307/2426575 CrossRefGoogle Scholar
  6. Devictor V, Julliard R, Couvet D et al (2007) Functional homogenization effect of urbanization on bird communities. Conserv Biol 21:741–751. doi: 10.1111/j.1523-1739.2007.00671.x PubMedCrossRefGoogle Scholar
  7. Fahrig L (1997) Relative effects of habitat loss and fragmentation on population extinction. J Wildl Manage 61:603–610. doi: 10.2307/3802168 CrossRefGoogle Scholar
  8. Fahrig L (2003) Effects of habitat fragmentation on biodiversity. Annu Rev Ecol Evol Syst 34:487–515. doi: 10.1146/annurev.ecolsys.34.011802.132419 CrossRefGoogle Scholar
  9. Fielding AH, Bell JF (1997) A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ Conserv 24:38–49. doi: 10.1017/S0376892997000088 CrossRefGoogle Scholar
  10. Franken RJ, Hik DS (2004) Influence of habitat quality, patch size and connectivity on colonization and extinction dynamics of collared pikas Ochotona collaris. J Anim Ecol 73:889–896. doi: 10.1111/j.0021-8790.2004.00865.x CrossRefGoogle Scholar
  11. Goheen JR, Swihart RK (2005) Resource selection and predation of North American red squirrels in deciduous forest fragments. J Mammal 86:22–28. doi:10.1644/1545-1542(2005)086<0022:RSAPON>2.0.CO;2CrossRefGoogle Scholar
  12. Goheen JR, Swihart RK, Gehring TM et al (2003) Forces structuring tree squirrel communities in landscapes fragmented by agriculture: species differences in perceptions of forest connectivity and carrying capacity. Oikos 102:95–103. doi: 10.1034/j.1600-0706.2003.12336.x CrossRefGoogle Scholar
  13. Gu W, Swihart RK (2004) Absent or undetected? Effects of non-detection of species occurrence on wildlife-habitat models. Biol Conserv 116:195–203. doi: 10.1016/S0006-3207(03)00190-3 CrossRefGoogle Scholar
  14. Henein K, Wegner J, Merriam G (1998) Population effects of landscape model manipulation on two behaviourally different woodland small mammals. Oikos 81:168–186. doi: 10.2307/3546479 CrossRefGoogle Scholar
  15. Julliard R, Clavel J, Devictor V et al (2006) Spatial segregation of specialists and generalists in bird communities. Ecol Lett 9:1237–1244. doi: 10.1111/j.1461-0248.2006.00977.x PubMedCrossRefGoogle Scholar
  16. Koprowski JL (1994) Sciurus niger. Mamm Species 479:1–9Google Scholar
  17. Kozakiewicz M (1993) Habitat isolation and ecological barriers—the effect on small mammal populations and communities. Acta Theriol (Warsz) 38:1–30Google Scholar
  18. Lindenmayer DB, Fischer J (2007) Tackling the habitat fragmentation panchreston. Trends Ecol Evol 22:127–132. doi: 10.1016/j.tree.2006.11.006 PubMedCrossRefGoogle Scholar
  19. MacKenzie DI, Nichols JD, Lachman GB et al (2002) Estimating site occupancy rates when detection probabilities are less than one. Ecology 83:2248–2255Google Scholar
  20. Matter SF, Roslin T, Roland J (2005) Predicting immigration of two species in contrasting landscapes: effects of scale, patch size and isolation. Oikos 111:359–367. doi: 10.1111/j.0030-1299.2005.14127.x CrossRefGoogle Scholar
  21. Merriam G, Lanoue A (1990) Corridor use by small mammals: field measurement for three experimental types of Peromyscus leucopus. Landsc Ecol 4:123–131. doi: 10.1007/BF00132856 CrossRefGoogle Scholar
  22. Moilanen A, Hanski I (1998) Metapopulation dynamics: effects of habitat quality and landscape structure. Ecology 79:2503–2515CrossRefGoogle Scholar
  23. Moore JE, Swihart RK (2005) Modeling patch occupancy by forest rodents: incorporating detectability and spatial autocorrelation with hierarchically structured data. J Wildl Manage 69:933–949. doi: 10.2193/0022-541X(2005)069[0933:MPOBFR]2.0.CO;2 CrossRefGoogle Scholar
  24. Mossman CA, Waser PM (2001) Effects of habitat fragmentation on population genetic structure in the white-footed mouse (Peromyscus leucopus). Can J Zool 79:285–295. doi: 10.1139/cjz-79-2-285 CrossRefGoogle Scholar
  25. Mumford RE, Whitaker JO Jr (1982) Mammals of Indiana. Indiana University Press, BloomingtonGoogle Scholar
  26. Nelson E, Polasky S, Lewis DJ et al (2008) Efficiency of incentives to jointly increase carbon sequestration and species conservation on a landscape. Proc Natl Acad Sci USA 105:9471–9476. doi: 10.1073/pnas.0706178105 PubMedCrossRefGoogle Scholar
  27. Nupp TE (1997) Population dynamics and community structure of granivorous forest rodents in a fragmented landscape. Dissertation, Purdue UniversityGoogle Scholar
  28. Parris KM (2004) Environmental and spatial variables influence the composition of frog assemblages in sub-tropical eastern Australia. Ecography 27:392–400. doi: 10.1111/j.0906-7590.2004.03711.x CrossRefGoogle Scholar
  29. Pellet J, Fleishman E, Dobkin DS et al (2007) An empirical evaluation of the area and isolation paradigm of metapopulation dynamics. Biol Conserv 136:483–495. doi: 10.1016/j.biocon.2006.12.020 CrossRefGoogle Scholar
  30. Rizkalla CE, Swihart RK (2007) Explaining movement decisions of forest rodents in fragmented landscapes. Biol Conserv 140:339–348. doi: 10.1016/j.biocon.2007.08.019 CrossRefGoogle Scholar
  31. Schmid-Holmes S, Drickamer LC (2001) Impact of forest patch characteristics on small mammal communities: a multivariate approach. Biol Conserv 99:293–305. doi: 10.1016/S0006-3207(00)00195-6 CrossRefGoogle Scholar
  32. Schumaker NH, Ernst T, White D et al (2004) Projecting wildlife responses to alternative future landscapes in Oregon’s Willamette Basin. Ecol Appl 14:381–400. doi: 10.1890/02-5010 CrossRefGoogle Scholar
  33. Sutherland GD, Harestad AS, Price K et al (2000) Scaling of natal dispersal distances in terrestrial birds and mammals. Conserv Ecol 4(1):16. http://www.consecol.org/ vol4/iss1/art16/ (online)Google Scholar
  34. Swihart RK, Slade NA (2004) Modeling interactions of private ownership and biological diversity: an architecture for landscapes with sharp edges. In: Swihart RK, Moore JE (eds) Conserving biodiversity in agricultural landscapes: model-based planning tools. Purdue University Press, West LafayetteGoogle Scholar
  35. Swihart RK, Verboom J (2004) Using ecologically scaled landscape indices to assess biodiversity consequences of land use-decisions. In: Swihart RK, Moore JE (eds) Conserving biodiversity in agricultural landscapes: model-based planning tools. Purdue University Press, West LafayetteGoogle Scholar
  36. Swihart RK, Atwood TC, Goheen JR et al (2003a) Patch occupancy of North American mammals: is patchiness in the eye of the beholder? J Biogeogr 30:1259–1279. doi: 10.1046/j.1365-2699.2003.00925.x CrossRefGoogle Scholar
  37. Swihart RK, Gehring TM, Kolozsvary MB et al (2003b) Responses of “resistant” vertebrates to habitat loss and fragmentation: the importance of niche breadth and range boundaries. Divers Distrib 9:1–18. doi: 10.1046/j.1472-4642.2003.00158.x CrossRefGoogle Scholar
  38. Swihart RK, Goheen JR, Schnelker SA et al (2007) Testing the generality of patch and landscape-level predictors of tree squirrel occurrence at a regional scale. J Mammal 88:564–572. doi: 10.1644/06-MAMM-A-275R.1 CrossRefGoogle Scholar
  39. Thomas JA, Bourn NAD, Clarke RT et al (2001) The quality and isolation of habitat patches both determine where butterflies persist in fragmented landscapes. Proc R Soc Lond B Biol Sci 268:1791–1796. doi: 10.1098/rspb.2001.1693 CrossRefGoogle Scholar
  40. Vanreusel W, Maes D, Van Dyck H (2007) Transferability of species distribution models: a functional habitat approach for two regionally threatened butterflies. Conserv Biol 21:201–212. doi: 10.1111/j.1523-1739.2006.00577.x PubMedCrossRefGoogle Scholar
  41. Vos CC, Verboom J, Opdam PFM et al (2001) Toward ecologically scaled landscape indices. Am Nat 157:24–41. doi: 10.1086/317004 PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Carol E. Rizkalla
    • 1
    • 2
  • Jeffrey E. Moore
    • 1
    • 3
  • Robert K. Swihart
    • 1
  1. 1.Department of Forestry and Natural ResourcesPurdue UniversityWest LafayetteUSA
  2. 2.Disney’s Animal KingdomLake Buena VistaUSA
  3. 3.Duke Center for Marine ConservationDuke University Marine LaboratoryBeaufortUSA

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