ranlogist | R Documentation |
Random population growth with logistic expectation.
ranlogist(N0, b, d, K, bcontr=0.5) ## S3 method for class 'ranlogist' plot(x, ...) ## S3 method for class 'ranlogist' lines(x, ...) ## S3 method for class 'ranlogist' traj(x, ...)
N0 |
Initial population size |
b |
Birth rate. |
d |
Death rate. |
K |
Carrying capacity. |
bcontr |
The proportion of decrease of growth rate due to decrease in the birth rate. |
x |
|
... |
Other parameters passed to graphical functions. |
The stochastic population growth rate is based on logistic expectation following Pielou (1969). The instantaneous growth rate is the difference of birth and death rates r = b - d. The birth and death rates are dependent on current population size and at carrying capacity K they are equal (r = b). The sum of death and birth rates at given population size gives the current event rate which is used to simulate the time to the next event from exponential distribution. The next event is either (1) a birth that increases population size by one or (2) a death that reduces population size by one individual. Consequently, the population size is discrete (integer) but time is continuous, unlike in many other stochastic models which treat time as discrete, but population size as continuous. Further, Pielou's model has real temporal autocorrelation of population size, unlike many other models which vary expected population growth with no autocorrelation.
Krebs (2009, p. 155) discusses Pielou (1969) briefly, but ignores the advanced features of her model.
Function ranlogist
perform the simulation, traj
extracts the simulation results, and plot
and lines
can be used for graphics. The plot
is based on
plot.traj
.
Function ranlogist
returns the model parameters, r,
targeted end time of simulation (timend
) and the simulation
results in vectors time
and N
, and the function
call
.
Jari Oksanen
Krebs, C. J. (2009) Ecology. Benjamin Cummings. 6 ed., 655 pp.
Pielou, E.C. (1969) An Introduction to Mathematical Ecology. Wiley-Interscience, 286 pp.
par(mfrow=c(2,2)) replicate(4, plot(ranlogist(5, 1.2, 0.8, 50))) par(mfrow=c(1,1))
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.