Measuring boundary convexity at multiple spatial scales using a linear “moving window” analysis: an application to coastal river otter habitat selection

Landscape Ecology volume 25, pages1575–1587(2010)Cite this article

Abstract

Landscape metrics have been used to quantify ecological patterns and to evaluate relationships between animal presence/abundance and habitat at multiple spatial scales. However, many ecological flows occur in linear systems such as streams, or across patch/landscape boundaries (ecotones). Some organisms and flows may depend on the boundary shape, but metrics for defining linear boundary characteristics are scarce. While sinuosity and fractal dimension address some elements of shape, they fail to specify the dominate shape direction (convexity/concavity). We propose a method for measuring boundary convexity and assess its utility, along with sinuosity and fractal dimension, for predicting site selection by coastal river otters. First, we evaluate the characteristics of boundary convexity using a hypothetical boundary. Second, to compare convexity with other linear metrics boundary convexity, sinuosity and fractal dimension were calculated for the coastline of a set of islands in Prince William Sound, AK. Finally, we use logistic regression in an information-theoretic framework to assess site selection of river otters as a function of these linear metrics. Boundary convexity, fractal dimension and sinuosity are relatively uncorrelated at all scales. Otter latrine sites occurred at significantly more convex locations on the coastline than random sites. Using logistic regression and convexity values at the 100 m window-size, 69.5% of the latrine sites were correctly classified. Coastal terrestrial convexity appears to be a promising landscape-scale metric for predicting otter latrine sites. We suggest that boundary convexity may be an important landscape metric for describing species use or ecological flows at ecotones.

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References

  1. Albeke SE, Nibbelink NP, Mu L, Ellsworth DJ (2009) Boundary convexity tool. University of Georgia, Athens. http://arcscripts.esri.com/details.asp?dbid=16165. Accessed 14 Apr 2009

  2. Allen TFH, Hoekstra TW (1992) Toward a unified ecology. Columbia University Press, New York, NY

    Google Scholar 

  3. Anderson DR, Burnham KP, Thompson WL (2000) Null hypothesis testing: problems, prevalence, and an alternative. J Wildl Manag 64:912–923

    Article  Google Scholar 

  4. Ben-David M, Bowyer RT, Duffy LK, Roby DD, Schell DM (1998) Social behavior and ecosystem processes: river otter latrines and nutrient dynamics of terrestrial vegetation. Ecology 79:2567–2571

    Article  Google Scholar 

  5. Ben-David M, Blundell GM, Kern JW, Maier JAK, Brown ED, Jewett SC (2005) Communication in coastal river otters: creation of variable resource sheds for terrestrial communities. Ecology 86:1331–1345

    Article  Google Scholar 

  6. Bowyer RT, Blundell GM, Ben-David M, Jewett SC, Dean TA (2003) Effects of the Exxon Valdez oil spill on river otters: injury and recovery of a sentinel species. Wildl Monogr 153:1–53

    Google Scholar 

  7. Burnham KP, Anderson DR (2001) Kullback–Leibler information as a basis for strong inference in ecological studies. Wildl Res 28:111–119

    Article  Google Scholar 

  8. ESRI (2006) ArcGIS: Release 9.2 [software]. Environmental Systems Research Institute, Redlands, CA

    Google Scholar 

  9. Ewers RM, Didham RK (2007) The effect of fragment shape and species’ sensitivity to habitat edge on animal population size. Conserv Biol 21:926–936

    Article  Google Scholar 

  10. Forester JD, Ives AR, Turner MG, Anderson DP, Fortin D, Beyer HL, Smith DW, Boyce MS (2007) State-space models link elk movement patterns to landscape characteristics in Yellowstone National Park. Ecol Monogr 77:285–299

    Article  Google Scholar 

  11. Grober-Dunsmore R, Frazer TK, Beets JP, Lindberg WJ, Zwick P, Funicelli NA (2008) Influence of landscape structure, on reef fish assemblages. Landscape Ecol 23:37–53

    Article  Google Scholar 

  12. Hamer TL, Flather CH, Noon BR (2006) Factors associated with grassland bird species richness: the relative roles of grassland area, landscape structure, and prey. Landscape Ecol 21:569–583

    Article  Google Scholar 

  13. Hargis CD, Bissonette JA, David JL (1998) The behavior of landscape metrics commonly used in the study of habitat fragmentation. Landscape Ecol 13:167–186

    Article  Google Scholar 

  14. Haynes KJ, Cronin JT (2006) Interpatch movement and edge effects: the role of behavioral responses to the landscape matrix. Oikos 113:43–54

    Article  Google Scholar 

  15. Heegaard E, Okland RH, Bratli H, Dramstad WE, Engan G, Pedersen O, Solstad H (2007) Regularity of species richness relationships to patch size and shape. Ecography 30:589–597

    Article  Google Scholar 

  16. Hopkins RL (2009) Use of landscape pattern metrics and multiscale data in aquatic species distribution models: a case study of a freshwater mussel. Landscape Ecol 24:943–955

    Article  Google Scholar 

  17. Hosmer DW, Lemeshow S (2000) Applied logistic regression. Wiley, New York

    Google Scholar 

  18. Howell CA, Dijak WD, Thompson FR III (2007) Landscape context and selection for forest edge by breeding brown-headed cowbirds. Landscape Ecol 22:273–284

    Article  Google Scholar 

  19. Kearns FR, Kelly NM, Carter JL, Resh VH (2005) A method for the use of landscape metrics in freshwater research and management. Landscape Ecol 20:113–125

    Article  Google Scholar 

  20. Kie JG, Ager AA, Bowyer RT (2005) Landscape-level movements of North American elk (Cervus elaphus): effects of habitat patch structure and topography. Landscape Ecol 20:289–300

    Article  Google Scholar 

  21. King G, Tanner MA, Rosen O (2004) Ecological inference: new methodological strategies. Cambridge University Press, Cambridge, UK

    Google Scholar 

  22. Larsen DN (1983) Habitats, movements, and foods of river otters in coastal southeastern Alaska, University of Alaska, Fairbanks, Alaska, 169 pp

  23. Li BL (2000) Fractal geometry applications in description and analysis of patch patterns and patch dynamics. Ecol Model 132:33–50

    Article  Google Scholar 

  24. Li H, Wu J (2004) Use and misuse of landscape indices. Landscape Ecol 19:389–399

    Article  Google Scholar 

  25. Mandelbrot BB (1982) The fractal geometry of nature. W. H. Freeman, San Francisco

    Google Scholar 

  26. McGarigal K, Cushman SA, Neel MC, Ene E (2002) FRAGSTATS: spatial pattern analysis program for categorical maps. University of Massachusetts, Amherst. http://www.umass.edu/landeco/research/fragstats/fragstats.html. Accessed Jan 2007

  27. McGrath MT, DeStefano S, Riggs RA, Irwin LL, Roloff GJ (2003) Spatially explicit influences on northern goshawk nesting habitat in the interior Pacific northwest. Wildl Monogr 154:1–63

    Google Scholar 

  28. Mitchell MS, Lancia RA, Gerwin JA (2001) Using landscape-level data to predict the distribution of birds on a managed forest: effects of scale. Ecol Appl 11:1692–1708

    Article  Google Scholar 

  29. Nams VO, Mowat G, Panian MA (2006) Determining the spatial scale for conservation purposes—an example with grizzly bears. Biol Conserv 128:109–119

    Article  Google Scholar 

  30. Polis GA, Hurd SD (1996) Linking marine and terrestrial food webs: allochthonous input from the ocean supports high secondary productivity on small islands and coastal land communities. Am Nat 147:396–423

    Article  Google Scholar 

  31. Rempel R (2008) Patch analyst 4. Centre for Northern Forest Ecosystem Research (Ontario Ministry of Natural Resources), Lakehead University. http://flash.lakeheadu.ca/~rrempel/patch/index.html. Accessed Jan 2008

  32. Ritters KH, O’Neill RV, Hunsaker CT, Wickham JD, Yankee DH, Timmins SP, Jones KB, Jackson BL (1995) A factor analysis of landscape pattern and structure metrics. Landscape Ecol 10:23–39

    Article  Google Scholar 

  33. Robinson WS (1950) Ecological correlations and the behavior of individuals. Am Sociol Rev 15:351–357

    Article  Google Scholar 

  34. Roe AM, Meyer CB, Nibbelink NP, Ben-David M (2010) Differential production of trees and shrubs in response to fertilization and disturbance by coastal river otters in Alaska. Ecology. doi:10.1890/09-1216.1

    Article  Google Scholar 

  35. Rostain RR, Ben-David M, Groves P, Randall JA (2004) Why do river otters scent-mark? An experimental test of several hypotheses. Anim Behav 68:703–711

    Article  Google Scholar 

  36. Ruiz D, Escribano C, Fernandez-Quintanilla C (2006) Identifying associations among sterile oat (Avena sterilis) infestation level, landscape characteristics, and crop yields. Weed Sci 54:1113–1121

    CAS  Article  Google Scholar 

  37. Selonen V, Hanski IK (2004) Young flying squirrels (Pteromys volans) dispersing in fragmented forests. Behav Ecol 15:564–571

    Article  Google Scholar 

  38. Steyerberg EW, Frank E, Harrell J, Borsboom GJJM, Eijkemans MJC, Vergouwe Y, Habbema JDF (2001) Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol 54:774–781

    CAS  Article  Google Scholar 

  39. Swets JA (1988) Measuring the accuracy of diagnostic systems. Science 240:1285–1293

    CAS  Article  Google Scholar 

  40. Taylor RS, Oldland JM, Clarke MF (2008) Edge geometry influences patch-level habitat use by an edge specialist in south-eastern Australia. Landscape Ecol 23:377–389

    Article  Google Scholar 

  41. Trani MK, Giles RH (1999) An analysis of deforestation: metrics used to describe pattern change. For Ecol Manag 114:459–470

    Article  Google Scholar 

  42. Turchin P (1996) Fractal analyses of animal movement: a critique. Ecology 77:2086–2090

    Article  Google Scholar 

  43. Turner MG (1989) Landscape ecology—the effect of pattern on process. Annu Rev Ecol Syst 20:171–197

    Article  Google Scholar 

  44. Wu J (2004) Effects of changing scale on landscape pattern analysis: scaling relations. Landscape Ecol 19:125–138

    Article  Google Scholar 

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Acknowledgments

We thank K. Ott, J. Herreman, B. Myers, K. Pope, T. Whitaker and M. Wood for valuable assistance in the field. Additional logistical support was provided by the Alaska Department of Fish and Game and Babkin Charters Inc. Additionally, we would like to thank the editors for their insightful review of earlier versions of this manuscript. Funding for this project was provided by the University of Georgia, Warnell School of Forestry and Natural Resources and a grant from the National Science Foundation (NSF #0454474) to M. Ben-David, N. Nibbelink, and C. Meyer.

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Author notes

  1. Shannon E. Albeke

    Present address: Wyoming Geographic Information Science Center, University of Wyoming, Dept. 4008, 1000 E. University Ave., Laramie, WY, 82071, USA

Affiliations

  1. Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA, 30602, USA

    Shannon E. Albeke & Nathan P. Nibbelink

  2. Department of Geography, University of Georgia, Athens, GA, 30602, USA

    Lan Mu

  3. College of Natural Sciences, University of Texas Austin, Austin, TX, 78712, USA

    Daniel J. Ellsworth

Authors
  1. Shannon E. Albeke
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  2. Nathan P. Nibbelink
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  3. Lan Mu
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  4. Daniel J. Ellsworth
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Correspondence to Shannon E. Albeke.

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Albeke, S.E., Nibbelink, N.P., Mu, L. et al. Measuring boundary convexity at multiple spatial scales using a linear “moving window” analysis: an application to coastal river otter habitat selection. Landscape Ecol 25, 1575–1587 (2010). https://doi.org/10.1007/s10980-010-9528-4

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Keywords

  • Ecotone
  • Sinuosity
  • Fractal dimension
  • Boundary shape
  • Lontra canadensis
  • Landscape and patch metrics