untb {untb} | R Documentation |
Simulates ecological drift under the UNTB. Function untb()
carries out the simulation; function select()
carries out a single generational step.
untb(start, prob=0, D=1, gens=150, keep=FALSE, meta=NULL) select(a, D=length(a), prob=0, meta=NULL) select.mutate(a, D=length(a), prob.of.mutate=0) select.immigrate(a, D=length(a), prob.of.immigrate=0, meta)
a, start |
Starting ecosystem; coerced to class census. Usually,
pass an object of class count; see examples. To start
with a monoculture of size 10, use start=rep(1,10) and to
use start=1:10 . |
prob, prob.of.immigrate, prob.of.mutate |
Probability of “new” organism not being a descendent of an existing individual |
D |
Number of organisms that die in each timestep |
gens |
Number of generations to simulate |
keep |
In function untb() Boolean with default
FALSE meaning to return the system at the end of the
simulation and TRUE meaning to return a matrix whose rows are
the ecosystem at successive times |
meta |
In function untb() , the metacommunity; coerced to a
count object. Default of NULL means to use a
“greedy” system in which every mutation gives rise to a new,
previously unencountered species. This would correspond to an
infinitely large, infinitely diverse, Hubbellian ecosystem (which is
not too ridiculous an assumption for a small island near a large
diverse mainland).
In function select.immigrate() , a simplified representation
of a metacommunity.
|
Functions select.immigrate()
and select.mutate()
are not
really intended for the end user; they use computationally efficient
(and opaque) integer arithmetic.
Robin K. S. Hankin
S. P. Hubbell 2001. “The Unified Neutral Theory of Biodiversity”. Princeton University Press.
data(butterflies) untb(start=butterflies, prob=0, gens=100) a <- untb(start=1:10,prob=0.005, gens=1000,keep=TRUE) plot(species.count(a),type="b") matplot(species.table(a),type="l",lty=1)