Advertisement

Vegetatio

, Volume 83, Issue 1–2, pp 81–95 | Cite as

Ecological Field Theory: the concept and field tests

  • J. Walker
  • P. J. H. Sharpe
  • L. K. Penridge
  • H. Wu
Article

Abstract

Ecological field theory (EFT) quantifies plant spatial influences as pulsating geometric zones about individual plants. It provides the basis for a methodology to include spatial interactions between plants of different size, function and growth-form in models of plant community dynamics. The key components of EFT are: 1. the influence domain of individuals (D), 2. the field intensity within the domains (I), 3. the influence surface (ID) and 4. the intensity of interactions (II). The means to calculate these key components are outlined and several tests of the methodology as applied to a semi-arid eucalypt woodland are presented. The tests include a comparison of measured shrub growth with a computer implementation of EFT (the RESCOMP model) and spatial growth data from the eucalypt woodland to support the postulates included in EFT. Practical uses expected for the method are in agroforestry, landscape rehabilitation, simulations of disturbance effects and in determining invasibility of plant communities.

Keywords

Competition Field intensity Influence domain Interaction intensity Spatial interaction 

Abbreviations

ARGR =

Actual Relative Growth Rate

EFT =

Ecological Field Theory

IRM =

Integrated Rate Method

PRGR =

Potential Relative Growth Rate

RESCOMP=

RESource COMPetition model

SMRGR =

Spatially Modified Relative Growth Rate

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. BeestonG. R., WalkerP. J., PurdieR. & PickardJ. 1980. Plant communities of the poplar box (Eucalyptus populnea) lands of Eastern Australia. Aust. Rangel. J. 2: 1–16.Google Scholar
  2. BeggJ. E. & CunninghamR. B., 1974. Penetration of radiation into a eucalypt woodland. J. Aust. Inst. Agric. Sci. 40: 160–164.Google Scholar
  3. BraunackM. V. & WalkerJ. 1985. Recovery of some surface soil properties following sheep grazing regimes on a semi-arid woodland. Aust. J. Ecol. 10: 451–460.Google Scholar
  4. BurchG. & NichollsA. O. 1981. Effects of vegetation communities on the simulated soil water balance in Eucalyptus populnea lands. Aust. Rangel. J. 3: 24–32.Google Scholar
  5. CharleyJ. L. & WestN. E. 1975. Plant-induced soil chemical patterns in some shrub-dominated semi-desert ecosystems of Utah. J. Ecol. 63: 945–964.Google Scholar
  6. CrawleyM. J. 1986. Plant ecology. Blackwell Scientific Publications, Oxford.Google Scholar
  7. FordE. D. 1975. Competition and stand structure in some even-aged plant monocultures. J. Ecol. 63: 311–33.Google Scholar
  8. FordE. D. & DiggleP. J. 1981. Competition for light in a plant monoculture modelled as a spatial stochastic process. Ann. Bot. (Lond.) 48 (4): 481–500.Google Scholar
  9. GatesD. J. 1982. Competition and skewness in plantations. J. theor. Biol. 94: 909–922.Google Scholar
  10. GatesD. J. & WestcottM. 1981. Negative skewness and negative correlations in spatial competition models. J. Math. Biol. 13: 159–171.Google Scholar
  11. GrimeJ. P. 1979. Plant strategies and vegetation processes. Wiley & Sons, chichester.Google Scholar
  12. HarperJ. L. 1977. Population biology of plants. Academic Press, London.Google Scholar
  13. JuppD. L. B., WalkerJ. & PenridgeL. K. 1986. Interpretation of vegetation structure in Landsat MSS imagery: a case study in disturbed semi-arid eucalypt woodlands. Part 2. Model-based analysis. J. Environ. Managem. 23: 35–57.Google Scholar
  14. KuuluvainenT. & PukkalaT. 1987. Effect of crown shape and tree distribution on the spatial distribution of shade. Agric. Forest Meteorol. 40: 215–231.Google Scholar
  15. NixH. A. 1982. Environmental determinats of biogeography, and evolution in Terra Australis. In: BarkerW. R. & GreensladeP. J. M. (eds), Evolution of the flora and fauna of arid Australia, pp. 47–66. Peacock Publications, Adelaide.Google Scholar
  16. NobleI. R. & SlatyerR. O. 1980. The use of vital attributes to predict successional changes in plant communities subject to recurrent disturbances. Vegetatio 43: 5–21.Google Scholar
  17. OlsenR. L., SharpeP. J. H. & WuH. 1985. Whole plant modelling: A continuous-time Markov (CTM) approach. Ecol. Modell. 29: 171–188.Google Scholar
  18. PenridgeL. K. & WalkerJ. 1986. The effect of neighbouring trees on eucalypt growth in a semi-arid woodland in Australia, J. Ecol. 74: 925–936.Google Scholar
  19. Penridge, L. K., Walker, J., Sharpe, P. J. H., Spence, R. D., Wu, H. & Zou, G. 1987. RESCOMP: A resource competition model to simulate the dynamics of vegetation cover. CSIRO Div. of Water and Land Resources Technical Memorandum 87/5, Canberra.Google Scholar
  20. PielouL. 1977. Mathematical ecology. John Wiley & Sons, New York.Google Scholar
  21. ReeceP. H. & CampbellB. L. 1986. The use of 137Cs for determining soil erosion differences in a disturbed and non-disturbed semi-arid ecosystem. In: Rangelands: A resource under siege. Proc. of the Second International Rangeland Congress. Australian Academy of Science, Canberra, 1986.Google Scholar
  22. SharpeP. J. H., WalkerJ., PenridgeL. K. & WuH. 1985. A physiologically-based continuous-time Markov approach to plant growth modelling in semi-arid woodlands. Ecol. Modell. 29: 189–214.Google Scholar
  23. SharpeP. J. H., WalkerJ., PenridgeL. K., WuH. & RykielE. J. 1986. Spatial considerations in physiological models of tree growth. Tree Physiol. 2: 403–421.Google Scholar
  24. ShugartH. H. 1984. A theory of forest dynamics. Springer-Verlag, New York.Google Scholar
  25. SmithT. M. & GoodmanP. S. 1986. The effect of competition on the structure and dynamics of Acacia savannas in southern Africa. J. Ecol. 74: 1031–1044.Google Scholar
  26. TilmanD. 1988. Dynamics and structure of plant communities. Princeton Univ. Press. Princeton.Google Scholar
  27. TunstallB. R. & WalkerJ. 1975. The effect of woodland disturbance on soil water, Proc. Ecol. Soc. Aust. 9: 49–58.Google Scholar
  28. vanTongerenO. & PrenticeI. C. 1986. A spatial simulation model for vegetation dynamics. Vegetatio 65: 163–173.Google Scholar
  29. WalkerJ., MooreR. M. & RobertsonJ. A. 1972. Herbage response to tree, and shrub thinning in E. populnea woodlands. Aust. J. Agric. Res. 23: 405–410.Google Scholar
  30. WalkerJ., thompsonC. H., FergusI. F. & TunstallB. R. 1981. Plant succession and soil development in coastal sand dunes of sub-tropical eastern Australia. In: WestD., ShugartH. H. & BotkinD. (eds), Forest succession — concepts and applications, pp. 107–126. Springer-Verlag, New York.Google Scholar
  31. WalkerJ., robertsonJ. A., PenridgeL. K. & SharpeP. J. H. 1986. Herbage response to tree thinning in a Eucalyptus crebra woodland. Aust. J. Ecol. 11: 135–140.Google Scholar
  32. WeinerJ. 1984. Neighbourhood interference amongst Pinus rigida individuals. J. Ecol. 72: 183–195.Google Scholar
  33. WoodwardF. I. 1987. Climate and plant distribution. Cambridge Univ. Press, Cambridge.Google Scholar
  34. WuH., SharpeP. J. H., WalkerJ. & PenridgeL. K. 1985. Ecological field theory (EFT): A spatial analysis of resource interference among plants. Ecol. Modell. 29: 215–243.Google Scholar
  35. ZinkeP. J., 1962. The pattern of individual forest trees on soil properties. Ecology 43: 130–133.Google Scholar

Copyright information

© Kluwer Academic Publishers 1989

Authors and Affiliations

  • J. Walker
    • 1
  • P. J. H. Sharpe
    • 2
  • L. K. Penridge
    • 1
    • 2
  • H. Wu
    • 1
    • 2
  1. 1.CSIRO Division of Water ResourcesCanberra LaboratoryCanberraAustralia
  2. 2.Biosystems Research Group, Department of Industrial EngineeringTexas A & M UniversityCollege StationUSA

Personalised recommendations