Exploring the mystery in the spatial distribution of organisms

Yamamura, K. 2000. Colony expansion model for describing the spatial distribution of populations.
Researches on Population Ecology 42, 161-169. [PDF (164KB)] (Copyright by the Society of Population Ecology and Springer-Verlag Tokyo) The original publication is available at http://www.springerlink.com


Two equations have been frequently used to describe the relation between the sample variance (s2) and sample mean (m) of the number of individuals per quadrat: Taylor's power law, s2=amb, and Iwao's m*-m regression, s2 = cm + dm2, where a, b, c, and d are constants. We can obtain biological information such as the colony size and the degree of aggregation of colonies from the parameters c and d of Iwao's m*-m regression. However, we cannot obtain such biological information from the parameters a and b of Taylor's power law since these parameters have not been described by simple functions. To mitigate such inconvenience, I propose a mechanistic model that produces Taylor's power law; it is called the colony expansion model. This model has the following two assumptions: (1) Population consists of a fixed number of colonies that lie across several quadrats. (2) The number of individuals per unit occupied area of colony becomes v times larger in an allometric manner when the occupied area of colony becomes h times larger (v >= 1, h >= 1). The parameter h indicates the dispersal rate of organisms. We then obtain Taylor's power law with b = {ln[E (h )] + ln[E (v2)]}/{ln[E(h ) + ln[E (v )]], where E indicates the expectation. We can use the inverse of exponent, 1/b, as an index of dispersal of individuals since it increases with increasing E (h ). This model also yields a relation, which is known as the Kono-Sugino relation, between the proportion of occupied quadrats and the mean density per quadrat: - ln(1 - p ) = fmg, where p is the proportion of occupied quadrats, f is a constant, and g = ln[E (h )]/{ln[E (h )] + ln[E (v )]}. We can use g as an index of dispersal since it increases with increasing E(h). The problem at low densities where Taylor's power law cannot be applicable is also discussed. (Copyright by the Society of Population Ecology and Springer-Verlag Tokyo)

Fitting the models to data

Figure 1.  Example of Taylor's power law. The variance-mean relation for the number of citrus red mite Panonychus citri per tree is shown. Estimated equations are as follows. Taylor's power law: s2 = 8.234m1.625, r2=0.982) Iwao's m*-m regression: s2 = 1.554m + 3.415m2(r2=0.965). (Copyright by the Society of Population Ecology and Springer-Verlag Tokyo)


Iwao's (1968) model

Iwao Model

Colony expansion model

Colony expansion model

Figure 2.  Schematic illustration of the assumptions of the model. Circles indicate colonies. Shade of the color indicates the density at that point. In Iwao's (1968) model, the population increase is described by the increase in the number of colonies while the colony size is fixed (upper). In the colony expansion mode, by contrast, the population increase is described by the development of each colony while the number of major colonies is fixed (lower). (Copyright by the Society of Population Ecology and Springer-Verlag Tokyo)




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