Last data update: 2014.03.03
R: Population Dynamic Models
Population Dynamic Models
Description
Functions to simulate population dynamic models.
Usage
popExp(N0, lamb, tmax, intt)
estEnv(N0, lamb, tmax, varr, npop, ext)
BDM(tmax, b, d, migr, N0)
estDem(N0, tmax, b, d, migr, nsim, ciclo)
popLog(N0, tmax, r, K, ext)
popStr(tmax, p.sj, p.jj, p.ja, p.aa, fec, ns, nj, na, rw, cl)
logDiscr(N0, tmax, rd, K)
bifAttr(N0, K, tmax, nrd, maxrd=3, minrd=1)
Arguments
N0
number of individuals at start time.
lamb
finite rate of population growth.
tmax
maximum simulation time.
intt
interval time size.
varr
variance.
npop
number of simulated populations.
ext
extinction.
b
birth rate.
d
death rate.
migr
migration. logical.
nsim
number of simulated populations.
ciclo
number of cycles in simulation.
r
intrinsic growth rate.
K
carrying capacity.
p.sj
probability of seed survival.
p.jj
probability of juvenile survival.
p.ja
probability of transition from juvenile to adult phase.
p.aa
probability of adult survival.
fec
mean number of propagules per adult each cycle.
ns
number of seeds at initial time.
nj
number of juveniles at initial time.
na
number of adults at initial time.
rw
number of rows for the simulated scene.
cl
number of columns for the simulated scene.
rd
discrete growth rate.
nrd
number of discrete population growth rate to simulate.
maxrd
maximum discrete population growth rate.
minrd
minimum discrete population growth rate.
Details
popExp simulates discrete and continuous exponential population growth.
estEnv simulates a geometric population growth with environmental stochasticity.
BDM simulates simple stochastic birth death and immigration dynamics of a population (Renshaw 1991).
estDem creates a graphic output based on BDM simulations.
Stochastic models uses lambda values taken from a normal distribution with mean lambda and variance varr.
popLog simulates a logistic growth for continuous and discrete models.
popStr simulates a structured population dynamics, with Lefkovitch matrices.
In popStr the number of patches in the simulated scene is defined by rw*cl.
logDiscr simulates a discrete logistic growth model.
bifAttr creates a bifurcation graphic for logistic discrete models.
Value
The functions return graphics with the simulation results, and a matrix with the population size for deterministic and stochastic models.
Author(s)
Alexandre Adalardo de Oliveira and Paulo Inacio Prado ecovirtualpackage@gmail.com
References
Gotelli, N.J. 2008. A primer of Ecology. 4th ed. Sinauer Associates, 291pp.
Renshaw, E. 1991. Modelling biological populations in space and time Cambridge University Press.
Stevens, M.H.H. 2009. A primer in ecology with R. New York, Springer.
See Also
metaComp
,
http://ecovirtual.ib.usp.br
Examples
## Not run:
popStr(p.sj=0.4, p.jj=0.6, p.ja=0.2, p.aa=0.9, fec=0.8, ns=100,nj=40,na=20, rw=30, cl=30, tmax=20)
## End(Not run)
Results