DEB_abj | R Documentation |
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).
DEB_abj()
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.
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 (-)
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()
.
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()
.
an S4 object of type DebAbj
Other DEB models:
DEB-models
,
DEBtox()
# 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()
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