Landscape Ecology

, Volume 19, Issue 5, pp 491–499 | Cite as

Spatial analysis of roadside Acacia populations on a road network using the network K-function

  • Peter G. Spooner
  • Ian D. Lunt
  • Atsuyuki Okabe
  • Shino Shiode


Spatial patterning of plant distributions has long been recognised as being important in understanding underlying ecological processes. Ripley’s K-function is a frequently used method for studying the spatial pattern of mapped point data in ecology. However, application of this method to point patterns on road networks is inappropriate, as the K-function assumes an infinite homogenous environment in calculating Euclidean distances. A new technique for analysing the distribution of points on a network has been developed, called the network K-function (for univariate analysis) and network cross K-function (for bivariate analysis). To investigate its applicability for ecological data-sets, this method was applied to point location data for roadside populations of three Acacia species in a fragmented agricultural landscape of south-eastern Australia. Kernel estimations of the observed density of spatial point patterns for each species showed strong spatial heterogeneity. Combined univariate and bivariate network K-function analyses confirmed significant clustering of populations at various scales, and spatial patterns of Acacia decora suggests that roadworks activities may have a stronger controlling influence than environmental determinants on population dynamics. The network K-function method will become a useful statistical tool for the analyses of ecological data along roads, field margins, streams and other networks.

Acacia Anthropogenic disturbance Field margins Kernel estimation Road verge Stream ecology 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Andrews A. 1990. Fragmentation of habitat by roads and utility corridors: a review. Australian Zoologist 26: 130–141.Google Scholar
  2. Bailey T.C. and Gatrell A.C. 1995. Interactive Spatial Data Analysis. Longman Scientific and Technical, Essex, UK.Google Scholar
  3. Bennett A.F. 1991. Roads, roadsides and wildlife conservation: a review.. In: Saunders D.A. and Hobbs R.J. (eds), Nature Conservation 2: The Role of Corridors, pp. 99–118. Surrey Beatty and Sons, Chipping North, New South Wales, Australia.Google Scholar
  4. Bull L. 1997. Lockhart Shire Roadside Vegetation Survey and Recommendations. Lockhart Shire Council, Lockhart, New South Wales, Australia.Google Scholar
  5. Cale P. 1990. The value of road reserves to the avifauna of the central wheat-belt of Western Australia. Proceedings of the Ecological Society of Australia 16: 359–367.Google Scholar
  6. Carr L.W., Fahrig L. and Pope S.E. 2002. Impacts of landscape transformation by roads.. In: Gutzwiller K.J. (ed.), Applying Landscape Ecology in Biological Conservation. Springer-Verlag, New York, New York, USA, pp. 225–243.Google Scholar
  7. Clarke J.S. 1991. Disturbance and tree life history on the shifting mosaic. Ecology 72: 1102–1118.Google Scholar
  8. Cooper S.D., Barmuta L., Sarnelle O., Kratz K., Diehl S. 1997. Quantifying spatial heterogeneity in streams. Journal of the North American Benthological Society 16: 174–188.Google Scholar
  9. Dale M.R.T. 1999. Spatial Pattern Analysis in Plant Ecology. Cambridge University Press, Cambridge, UK.Google Scholar
  10. de Blois S., Domon G. and Bouchard A. 2002. Landscape issues in plant ecology: a review. Ecography 25: 244–256.CrossRefGoogle Scholar
  11. Debski I., Burslem D.F.R.P. and Lamb D. 2000. Ecological processes maintaining differential tree species distributions in an Australian rain forest: implications for models of species coexistence. Journal of Tropical Ecology 16: 387–415.CrossRefGoogle Scholar
  12. Diggle P.J. 1983. Statistical Analysis of Spatial Point Patterns. Academic Press, London, UK.Google Scholar
  13. Forman R.T.T. 1998. Road ecology: a solution for the giant embracing us. Landscape Ecology 13: iii–v.CrossRefGoogle Scholar
  14. Forman R.T.T. and Alexander L.E. 1998. Roads and their major ecological effects. Annual Review of Ecology and Systematics 29: 207–231.CrossRefGoogle Scholar
  15. Forman R.T.T. 1999. Spatial models as an emerging foundation of road system ecology, and a handle for transportation planning and policy.. In: Evink G.L., Garrett P. and Zeigler D. (eds), Proceedings of the 3rd International Conference on Wildlife Ecology and Transportation. Florida Department of Transportation, Tallahassee, Florida, USA, pp. 118–123.Google Scholar
  16. Getis A. and Franklin J. 1987. Second-order neighbourhood analysis of mapped point patterns. Ecology 68: 473–477.Google Scholar
  17. Haase P. 1995. Spatial pattern analysis in ecology based on Ripley’s K-function: introduction and methods of edge correction. Journal of Vegetation Science 6: 575–582.Google Scholar
  18. Hobbs R.J. and Saunders D.A. 1994. Effects of landscape fragmentation in agricultural areas.. In: Moritz C. and Kikkawa J. (eds), Conservation Biology in Australia and Oceania. Surrey Beatty and Sons, Chipping Norton, New South Wales, Australia, pp. 77–95.Google Scholar
  19. Hooge P.N. 2002. Animal movement analysis Arcview extension. USGS-BRD, Alaska Biological Science Center, Alaska, Canada. Accessed 07 November 2002. Scholar
  20. Kenkel N.C. 1988. Pattern of self-thinning in jack pine: testing the random mortality hypothesis. Ecology 69: 1017–1024.Google Scholar
  21. Le Coeur D., Baudry J., Burel F. and Thenail C. 2002. Why and how we should study field boundary biodiversity in an agrarian landscape context. Agriculture Ecosystems and Environment 89: 23–40.CrossRefGoogle Scholar
  22. Little L.S., Edwards D., Porter D.E. 1997. Kriging in estuaries: as the crow flies, or as the fish swims? Journal of Experimental Marine Biology and Ecology 213: 1–11.CrossRefGoogle Scholar
  23. McIntyre S., Lavorel S. and Tremont R.M. 1995. Plant life-history attributes: their relationship to disturbance response in herbaceous vegetation. Journal of Ecology 83: 31–44.Google Scholar
  24. Miller H.J. 1994. Market area delimination within networks using Geographical Information Systems. Geographical Systems 1: 157–173.Google Scholar
  25. Miller H.J. 1999. Measuring space-time accessibility benefits within transportation networks: basic theory and computational methods. Geographical Analysis 31: 187–212.Google Scholar
  26. Moloney K.A. and Levin S.A. 1996. The effects of disturbance architecture on landscape-level population dynamics. Ecology 77: 375–394.Google Scholar
  27. Motzkin G., Foster D., Allen A., Harrod J. and Boone R. 1996. Controlling site to evaluate history: vegetation patterns of a New England sand plain. Ecological. Monographs 66: 345–365.Google Scholar
  28. Okabe A. and Kitamura M. 1996. A computational method for market area analysis on a network. Geographical Analysis 28: 330–349.Google Scholar
  29. Okabe A., Okunuki K. and Funamoto S. 2002b. SANET: A Toolbox for Spatial Analysis on a Network-Version 1.0-0211125. Centre for Spatial Information Science, University of Tokyo, Tokyo, Japan. URL: sanet/sanet-index.html.Google Scholar
  30. Okabe A., Okunuki K., Funamoto S. and Ishitomi T. 2002a. A Toolbox for Spatial Analysis on a Network and its Software. Proceedings of the 2nd International Conference on Geographical Information Science, Boulder, Colorado, USA.Google Scholar
  31. Okabe A. and Yamada I. 2001. The K-function method on a network and its computational implementation. Geographical Analysis 33: 271–290.Google Scholar
  32. Podani J. and Czaran T. 1997. Individual-centred analysis of mapped point patterns representing multi-species assemblages. Journal of Vegetation Science 8: 259–270.Google Scholar
  33. Rathbun S.L. 1998. Spatial modelling in irregular shaped regions: kriging estuaries. Environmetrics 9: 109–129.CrossRefGoogle Scholar
  34. Ripley B.D. 1976. The second-order analysis of stationary point processes. Journal of Applied Probability 13: 255–266.Google Scholar
  35. Ripley B.D. 1981. Spatial Statistics. John Wiley, Chichester, UK.Google Scholar
  36. Spooner P.G., Lunt I.D., Briggs S.V. and Freudenberger D. 2004. Effects of soil disturbance from roadworks on roadside shrubs in a fragmented agricultural landscape. Biological Conservation (in press).Google Scholar
  37. Szwagrzyk J. and Czerwczak M. 1993. Spatial patterns of trees in natural forests of east-central Europe. Journal of Vegetation Science 4: 469–476.Google Scholar
  38. Tame T. 1992. Acacias of South-east Australia. Kangaroo Press, Kenthurst, New South Wales, Australia.Google Scholar
  39. Turner M.G. and Dale V.H. 1990. Modelling landscape disturbance.. In: Turner M.G. and Gardner R.H. (eds), Quantitative Methods in Landscape Ecology. Springer-Verlag, New York, New York, USA, pp. 323–351.Google Scholar
  40. Vermeulen H.J.W. and Opdam P.F.M. 1995. Effectiveness of roadside verges as dispersal corridors for small ground-dwelling animals: a simulation study. Landscape and Urban Planning 31: 233–248.CrossRefGoogle Scholar
  41. Way J.M. 1977. Roadside verges and conservation in Britain: a review. Biological Conservation 12: 65–74.CrossRefGoogle Scholar
  42. West P.W. 1984. Inter-tree competition and small-scale pattern in monoculture of Eucalyptus obliqua (L’Herit). Australian Journal of Ecology 9: 405–411.Google Scholar
  43. Yamada I and Thill J. 2003. Empirical comparisons of planar and network K-functions in Traffic Accident Analysis.. In: Proceedings of the 82nd Transportation Research Board Annual Meeting, Washington, DC, USA.Google Scholar
  44. Yates C.J. and Hobbs R.J. 1997. Temperate eucalypt woodlands: a review of their status, processes threatening their persistence and techniques for restoration. Australian Journal of Botany 45: 949–973.CrossRefGoogle Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Peter G. Spooner
    • 1
  • Ian D. Lunt
    • 1
  • Atsuyuki Okabe
    • 2
  • Shino Shiode
    • 2
  1. 1.The Johnstone CentreCharles Sturt UniversityAlburyAustralia
  2. 2.Centre for Spatial Information ScienceUniversity of TokyoBunkyo-ku, TokyoJapan

Personalised recommendations