Last data update: 2014.03.03
|
R: A Sediment Model of Oxygen Consumption
A Sediment Model of Oxygen Consumption
Description
A model that describes oxygen consumption in a marine sediment.
One state variable:
Organic carbon settles on the sediment surface (forcing function Flux)
and decays at a constant rate.
The equation is simple:
frac{dC}{dt} = Flux - k C
This model is written in FORTRAN .
Usage
SCOC(times, y = NULL, parms, Flux, ...)
Arguments
times |
time sequence for which output is wanted; the first value
of times must be the initial time,
|
y |
the initial value of the state variable; if NULL it
will be estimated based on Flux and parms ,
|
parms |
the model parameter, k ,
|
Flux |
a data set with the organic carbon deposition rates,
|
... |
any other parameters passed to the integrator ode
(which solves the model).
|
Details
The model is implemented primarily to demonstrate the linking of
FORTRAN with R-code.
The source can be found in the ‘doc/examples/dynload’
subdirectory of the package.
Author(s)
Karline Soetaert <karline.soetaert@nioz.nl>
References
Soetaert, K. and P.M.J. Herman, 2009. A Practical Guide to Ecological
Modelling. Using R as a Simulation Platform. Springer, 372 pp.
See Also
ccl4model , the CCl4 inhalation model.
aquaphy , the algal growth model.
Examples
## Forcing function data
Flux <- matrix(ncol = 2, byrow = TRUE, data = c(
1, 0.654, 11, 0.167, 21, 0.060, 41, 0.070, 73,0.277, 83,0.186,
93,0.140,103, 0.255, 113, 0.231,123, 0.309,133,1.127,143,1.923,
153,1.091,163,1.001, 173, 1.691,183, 1.404,194,1.226,204,0.767,
214, 0.893,224,0.737, 234,0.772,244, 0.726,254,0.624,264,0.439,
274,0.168,284 ,0.280, 294,0.202,304, 0.193,315,0.286,325,0.599,
335, 1.889,345, 0.996,355,0.681,365,1.135))
parms <- c(k = 0.01)
times <- 1:365
out <- SCOC(times, parms = parms, Flux = Flux)
plot(out[,"time"], out[,"Depo"], type = "l", col = "red")
lines(out[,"time"], out[,"Mineralisation"], col = "blue")
## Constant interpolation of forcing function - left side of interval
fcontrol <- list(method = "constant")
out2 <- SCOC(times, parms = parms, Flux = Flux, fcontrol = fcontrol)
plot(out2[,"time"], out2[,"Depo"], type = "l",col = "red")
lines(out2[,"time"], out2[,"Mineralisation"], col = "blue")
Results
|