These functions allow you to get or set the species parameters stored in a MizerParams object.
species_params(params)species_params(params) <- value
A MizerParams object
A data frame with the species parameters
The species_params
data frame holds species-specific parameters that Mizer
can use, together with allometric assumptions, to set its various
size-dependent parameters. The data frame has one row for each species and
one column for each species parameter. There are a lot of species parameters
as we will now discuss, but most of them have sensible default values.
gamma
and q
are used to set the search volume, see setSearchVolume()
.
h
and n
are used to set the maximum intake rate, see setMaxIntakeRate()
.
k
, ks
and p
are used to set activity and basic metabolic rate,
see setMetabolicRate()
.
z0
is used to set the external mortality rate, see setExtMort()
.
w_mat
, w_mat25
, w_inf
and m
are used to set the allocation to
reproduction, see setReproduction()
.
w_min
is the egg size.
beta
and sigma
are parameters of the lognormal predation kernel, see
lognormal_pred_kernel()
. There will be other parameters if you are
using other predation kernel functions, see the "Setting predation kernel"
section in the help for setPredKernel()
.
Not all of these parameters have to be specified by the user. If they are missing, mizer will give them default values, sometimes by using other species parameters.
k_vb
and t0
are the von Bertalanffy growth parameters and are used
together with the length-weight relationship exponent b
and the egg
size w_min
to
get a default value for the coefficient of the maximum intake rate h
,
see get_h_default()
.
f0
is the feeding level and is used to get a default value for the
coefficient of the search volume gamma
, see get_gamma_default()
.
fc
is the critical feeding level below which the species can not
maintain itself. This is used to get a default value for the coefficient
of the metabolic rate ks
, see get_ks_default()
.
Note that these parameters are ignored if the parameters for which they allow defaults to be calculated have instead been set explicitly.
There are also some species parameters that are used directly in the model rather than being used for setting up size-dependent parameters:
alpha
is the assimilation efficiency, the proportion of the consumed
biomass that can be used for growth, metabolism and reproduction, see
the help for getEReproAndGrowth()
.
interaction_resource
sets the interaction strength with the resource,
see "Predation encounter" section in the help for getEncounter()
.
erepro
is the reproductive efficiency, the proportion of the energy
invested into reproduction that is converted to egg biomass, see
getRDI()
.
Rmax
is the parameter in the Beverton-Holt density dependence added to
the reproduction, see setBevertonHolt()
. There will be other such
parameters if you use other density dependence functions, see the
"Density dependence" section in the help for setReproduction()
.
Finally there are two species parameters that control the way the species are represented in plots:
linecolour
specifies the colour and can be any valid R colour value.
linetype
specifies the line type ("solid", "dashed", "dotted", "dotdash",
"longdash", "twodash" or "blank")
When you set up a MizerParams object with newMultispeciesParams()
you
need to specify a species parameter data frame, but you do not need to
give values for all of the species parameters described above. The only
required columns are species
for the species name and w_inf
for its
asymptotic size. Mizer will choose default values for all others, see
newMultispeciesParams()
.
When you change a species parameter in an already existing MizerParams
object, then this will be used to update the corresponding size-dependent
rates by automatically calling setParams()
.
Other functions for setting parameters:
gear_params()
,
resource_params()
,
setExtMort()
,
setFishing()
,
setInitialValues()
,
setInteraction()
,
setMaxIntakeRate()
,
setMetabolicRate()
,
setParams()
,
setPredKernel()
,
setReproduction()
,
setResource()
,
setSearchVolume()