DEB_abj {cvasi} | R Documentation |
DEB_abj
Description
Creates a DEB abj scenario. The abj model with type M acceleration is
like model std, but acceleration occurs between birth and metamorphosis (V1-morph).
Isomorphy is assumed before and after acceleration. Metamorphosis is before
puberty and occurs at maturity E_Hj
, which might or might not correspond with
changes in morphology. The abj model is a one-parameter extension of model std
(DEB Wiki).
Usage
DEB_abj()
Details
State variables
The following list describes the default names and standard units of the model's state variables:
-
L
, structural length (cm) -
E
, energy reserve (J) -
H
, energy invested in maturity (J) -
R
, reproduction buffer (J) -
cV
, internal concentration (C) -
Lmax
, maximum structural length (cm)
All state variables are initialized with zero. See set_init()
on how to set
the initial state.
Parameters
The following model parameters are required:
-
p_M
, vol-spec somatic maintenance (J/d.cm^3) -
v
, energy conductance (cm/d) -
k_J
, maturity maint rate coefficient (1/d) -
p_Am
, surface-area specific maximum assimilation rate (J/d.cm^2) -
kap
, allocation fraction to soma (-) -
E_G
, spec cost for structure (J/cm^3) -
f
, scaled functional response (-) -
E_Hj
, maturity at metamorphosis (J) -
E_Hp
, maturity at puberty (J) -
kap_R
, reproduction efficiency (-) -
L_b
, structural length at birth (cm) -
L_j
, structural length at metamorphosis (cm) -
ke
, elimination rate constant (d-1) -
c0
, no-effect concentration sub-lethal (C) -
cT
, tolerance concentration (C) -
MoA
, mode of action switch (-)
Mode of Actions
Any combination of the following mode of actions (MoA) can be considered by the model:
-
MoA = 1
: effect on feeding -
MoA = 2
: effect on maintenance costs -
MoA = 4
: effect on overhead costs for making an egg -
MoA = 8
: hazard during oogenesis -
MoA = 16
: energy conductance
To activate more than one MoA, simply add up the corresponding
codes. To disable all MoAs, set the parameter to zero.
See also set_mode_of_action()
.
Effects
The state variables L (structural length) and R (reproduction buffer) are
set as effect endpoints by default. All state variables are available as
potential endpoints. The list of considered endpoints can be modified
by using set_endpoints()
.
To calculate effects, each DEB scenario is simulated twice: One simulation
which considers exposure to a toxicant and one simulation without exposure, i.e.
a control. See also effect()
.
Value
an S4 object of type DebAbj
Simulation output
Simulation results will contain the state variables.
It is possible to amend the output of simulate()
with additional model
quantities that are not state variables, for e.g. debugging purposes or to
analyze model behavior. To enable or disable additional outputs, use the
optional argument nout
of simulate()
. As an example, set nout=2
to
enable reporting of the acceleration factor (MV
) and the mobilization flux
(pC
). Set nout=0
to disable additional outputs (default).
The available output levels are as follows:
-
nout
>= 1:MV
acceleration factor (-) -
nout
>= 2:pC
mobilization flux (J/d) -
nout
>= 3:pA
assimilation flux (J/d) -
nout
>= 4:pJ
energy invested in maturity flux (J/d)
Solver settings
The arguments to ODE solver deSolve::ode()
control how model equations
are numerically integrated. The settings influence stability of the numerical
integration scheme as well as numerical precision of model outputs. Generally, the
default settings as defined by deSolve are used, but all deSolve settings
can be modified in cvasi workflows by the user, if needed. Please refer
to e.g. simulate()
on how to pass arguments to deSolve in cvasi
workflows.
See Also
Other DEB models:
DEB-models
,
DEBtox()
Examples
# Create an abj scenario from scratch and simulate it
DEB_abj() %>%
set_init(c(L=0.02,E=0.1,H=0.01)) %>%
set_param(c(p_M=3000,v=0.02,k_J=0.6,p_Am=300,kap=0.9,E_G=4000,f=1,
E_Hj=0.05,E_Hp=0.3,kap_R=0.9,ke=1,c0=0,cT=1,L_b=0.02,
L_j=0.04,MoA=0)) %>%
set_exposure(no_exposure()) %>%
set_times(0:10) %>%
simulate()
# Print information about sample scenario 'americamysis'
americamysis
# Simulate 'americamysis' scenario
americamysis %>% simulate()