View source: R/setReproduction.R
setReproduction | R Documentation |
Sets the proportion of the total energy available for reproduction and growth that is invested into reproduction as a function of the size of the individual and sets additional density dependence.
setReproduction(
params,
maturity = NULL,
repro_prop = NULL,
reset = FALSE,
RDD = NULL,
...
)
getMaturityProportion(params)
maturity(params)
maturity(params) <- value
getReproductionProportion(params)
repro_prop(params)
repro_prop(params) <- value
setReproduction()
: A MizerParams object with updated reproduction
parameters.
getMaturityProportion()
or equivalently 'maturity():
An array (species x size) that holds the proportion
of individuals of each species at size that are mature.
getReproductionProportion()
or equivalently repro_prop()
:
An array (species x size) that holds the
proportion of consumed energy that a mature individual allocates to
reproduction for each species at size. For sizes where the maturity
proportion is zero, also the reproduction proportion is returned as zero.
For each species and at each size, the proportion \psi
of the
available energy
that is invested into reproduction is the product of two factors: the
proportion maturity
of individuals that are mature and the proportion
repro_prop
of the energy available to a mature individual that is
invested into reproduction. There is a size w_repro_max
at which all the
energy is invested into reproduction and therefore all growth stops. There
can be no fish larger than w_repro_max
. If you have not specified the
w_repro_max
column in the species parameter data frame, then the maximum size
w_max
is used instead.
If the the proportion of individuals that are mature is not supplied via
the maturity
argument, then it is set to a sigmoidal
maturity ogive that changes from 0 to 1 at around the maturity size:
{\tt maturity}(w) = \left[1+\left(\frac{w}{w_{mat}}\right)^{-U}\right]^{-1}.
(To avoid clutter, we are not showing the species index in the equations,
although each species has its own maturity ogive.)
The maturity weights are taken from the w_mat
column of the
species_params data frame. Any missing maturity weights are set to 1/4 of the
maximum weight in the w_max
column.
The exponent U
determines the steepness of the maturity ogive. By
default it is chosen as U = 10
, however this can be overridden by
including a column w_mat25
in the species parameter dataframe that
specifies the weight at which 25% of individuals are mature, which sets
U = \log(3) / \log(w_{mat} / w_{mat25}).
The sigmoidal function given above would strictly reach 1 only
asymptotically. Mizer instead sets the function equal to 1 already at a size
taken from the w_repro_max
column in the species parameter data frame, if it
exists, or otherwise from the w_max
column. Also, for computational
simplicity, any proportion smaller than 1e-8
is set to 0
.
If the the energy available to a mature individual that is
invested into reproduction is not supplied via the repro_prop
argument,
it is set to the allometric form
{\tt repro\_prop}(w) = \left(\frac{w}{w_{mat_max}}\right)^{m-n}.
Here n
is the scaling exponent of the energy income rate. Hence
the exponent m
determines the scaling of the investment into
reproduction for mature individuals. By default it is chosen to be
m = 1
so that the rate at which energy is invested into reproduction
scales linearly with the size. This default can be overridden by including a
column m
in the species parameter dataframe. The maximum sizes are taken
from the w_repro_max
column in the species parameter data frame, if it
exists, or otherwise from the w_max
column.
The total proportion of energy invested into reproduction of an individual
of size w
is then
\psi(w) = {\tt maturity}(w){\tt repro\_prop}(w)
The reproductive efficiency \epsilon
, i.e., the proportion of energy allocated to
reproduction that results in egg biomass, is set through the erepro
column in the species_params data frame. If that is not provided, the default
is set to 1 (which you will want to override). The offspring biomass divided
by the egg biomass gives the rate of egg production, returned by
getRDI()
:
R_{di} = \frac{\epsilon}{2 w_{min}} \int N(w) E_r(w) \psi(w) \, dw
The stock-recruitment relationship is an emergent phenomenon in mizer, with several sources of density dependence. Firstly, the amount of energy invested into reproduction depends on the energy income of the spawners, which is density-dependent due to competition for prey. Secondly, the proportion of larvae that grow up to recruitment size depends on the larval mortality, which depends on the density of predators, and on larval growth rate, which depends on density of prey.
Finally, to encode all the density dependence in the stock-recruitment
relationship that is not already included in the other two sources of density
dependence, mizer puts the the density-independent rate of egg production
through a density-dependence function. The result is returned by
getRDD()
. The name of the density-dependence function is
specified by the RDD
argument. The default is the Beverton-Holt
function BevertonHoltRDD()
, which requires an R_max
column
in the species_params data frame giving the maximum egg production rate. If
this column does not exist, it is initialised to Inf
, leading to no
density-dependence. Other functions provided by mizer are
RickerRDD()
and SheperdRDD()
and you can easily use
these as models for writing your own functions.
Other functions for setting parameters:
gear_params()
,
setExtEncounter()
,
setExtMort()
,
setFishing()
,
setInitialValues()
,
setInteraction()
,
setMaxIntakeRate()
,
setMetabolicRate()
,
setParams()
,
setPredKernel()
,
setSearchVolume()
,
species_params()
# Plot maturity and reproduction ogives for Cod in North Sea model
maturity <- getMaturityProportion(NS_params)["Cod", ]
repro_prop <- getReproductionProportion(NS_params)["Cod", ]
df <- data.frame(Size = w(NS_params),
Reproduction = repro_prop,
Maturity = maturity,
Total = maturity * repro_prop)
dff <- melt(df, id.vars = "Size",
variable.name = "Type",
value.name = "Proportion")
library(ggplot2)
ggplot(dff) + geom_line(aes(x = Size, y = Proportion, colour = Type))
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