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Fractal geometry predicts varying body size scaling relationships for mammal and bird home ranges

Author

Listed:
  • John P. Haskell

    (Utah State University)

  • Mark E. Ritchie

    (Syracuse University)

  • Han Olff

    (Wageningen University)

Abstract

Scaling laws that describe complex interactions between organisms and their environment as a function of body size offer exciting potential for synthesis in biology1,2,3,4. Home range size, or the area used by individual organisms, is a critical ecological variable that integrates behaviour, physiology and population density and strongly depends on organism size5,6,7. Here we present a new model of home range–body size scaling based on fractal resource distributions, in which resource encounter rates are a function of body size. The model predicts no universally constant scaling exponent for home range, but defines a possible range of values set by geometric limits to resource density and distribution. The model unifies apparently conflicting earlier results and explains differences in scaling exponents among herbivorous and carnivorous mammals and birds5,6,7,8,9,10,11,12,13,14,15,16,17,18. We apply the model to predict that home range increases with habitat fragmentation, and that the home ranges of larger species should be much more sensitive to habitat fragmentation than those of smaller species.

Suggested Citation

  • John P. Haskell & Mark E. Ritchie & Han Olff, 2002. "Fractal geometry predicts varying body size scaling relationships for mammal and bird home ranges," Nature, Nature, vol. 418(6897), pages 527-530, August.
    • Handle: RePEc:nat:nature:v:418:y:2002:i:6897:d:10.1038_nature00840
    DOI: 10.1038/nature00840
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    Cited by:

    1. Aurélie Lalanne & Shana Sundstrom & Ahjond Garmestani, 2023. "Discontinuous structure of regional and subregional urban systems: Nouvelle-Aquitaine, France (1800–2015)," Urban Studies, Urban Studies Journal Limited, vol. 60(5), pages 869-884, April.
    2. Pierpaolo Andriani & Bill McKelvey, 2007. "Beyond Gaussian averages: redirecting international business and management research toward extreme events and power laws," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 38(7), pages 1212-1230, December.
    3. He, Ji-Huan, 2006. "Cell size and cell number as links between noncoding DNA and metabolic rate scaling," Chaos, Solitons & Fractals, Elsevier, vol. 28(4), pages 1026-1028.
    4. Hendriks, A. Jan, 2007. "The power of size: A meta-analysis reveals consistency of allometric regressions," Ecological Modelling, Elsevier, vol. 205(1), pages 196-208.
    5. Yang Yang & Baibai Fu, 2023. "Spatial Heterogeneity of Urban Road Network Fractal Characteristics and Influencing Factors," Sustainability, MDPI, vol. 15(16), pages 1-16, August.
    6. Alemanno, Sara & Mancinelli, Giorgio & Basset, Alberto, 2007. "Effects of invertebrate patch use behaviour and detritus quality on reed leaf decomposition in aquatic systems: A modelling approach," Ecological Modelling, Elsevier, vol. 205(3), pages 492-506.
    7. Andrew Crompton, 2005. "Scaling in a Suburban Street," Environment and Planning B, , vol. 32(2), pages 191-197, April.
    8. Scherer, Cédric & Jeltsch, Florian & Grimm, Volker & Blaum, Niels, 2016. "Merging trait-based and individual-based modelling: An animal functional type approach to explore the responses of birds to climatic and land use changes in semi-arid African savannas," Ecological Modelling, Elsevier, vol. 326(C), pages 75-89.
    9. He, Ji-Huan, 2006. "Application of E-infinity theory to biology," Chaos, Solitons & Fractals, Elsevier, vol. 28(2), pages 285-289.
    10. Bill McKelvey & Benyamin B. Lichtenstein & Pierpaolo Andriani, 2012. "When organisations and ecosystems interact: toward a law of requisite fractality in firms," International Journal of Complexity in Leadership and Management, Inderscience Enterprises Ltd, vol. 2(1/2), pages 104-136.
    11. Pierpaolo Andriani & Bill McKelvey, 2006. "Beyond Gaussian Averages: Redirecting Management Research Toward Extreme Events and Power Laws," Department of Economics Working Papers 2006_03, Durham University, Department of Economics.

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