Description Usage Format Details References See Also Examples
This is the semi-empirical growth model of Daphnia galeata according to Rinke and Petzoldt (2003).
1 |
S4 object according to the timedepModel
specification.
The object contains the following slots:
mainThe empirical equations for length and egg number.
body length of individuals (mm),
potential number of eggs.
parmsa List with parameters of the model:
parameter of the empirical growth model (mm),
parameter of the empirical growth model (mg C / L),
parameter of the empirical growth model (mm),
parameter of the empirical growth model (d),
parameter of the empirical growth model (1/d),
parameter of the empirical growth model (1/Celsius),
parameter of the clutch size model (number of eggs),
parameter of the clutch size model (mg C /L),
parameter of the clutch size model (number of eggs),
parameter of the clutch size model (1/mg C),
minimum individual body length of Hall's data (mm),
minimum individual body length of our data (mm), may also be adapted to other populations.
timessimulation time and time steps.
inputsenvironmental conditions, temperature (T
,
degrees Celsius), and food (F
, mg C/L).
solvercharacter or function string with the integration method (default: 'iteration'.
init, initfuncinit
is initialized automatically according to the
parameter values.
To see all details, please have a look into the implementation and the original publications.
Rinke, K. and Petzoldt, T. (2003). Modelling the effects of temperature and food on individual growth and reproduction of Daphnia and their consequences on the population level. Limnologica 33(4), 293–304.
Hall, D.J. (1964): An experimental approach to the dynamics of a natural population of Daphnia galeata mendotae. Ecology 45, 94–112.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ## create model object
m <- daphnia_tefi()
## inspect parameters, start values, time steps
parms(m)
init(m)
times(m)
## simulate the model
m <- sim(m)
o <- out(m)
plot(m)
parms(m)$L0 <- 0.5
#m <- initialize(m) # not more necessary, done automatically by sim()
plot(sim(m))
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