Algae_TKTD | R Documentation |
The model is a mechanistic combined toxicokinetic-toxicodynamic (TK/TD) and
growth model for algae. The model simulates the development of algal biomass
under laboratory and environmental conditions. The growth of the algae
population is simulated on the basis of growth rates, which are dependent on
environmental conditions (radiation, temperature and phosphorus).
The model is a variant of the Algae_Weber()
model (Weber 2012) as cited
in EFSA TKTD opinion (2018). This Algae model, Algae_TKTD()
, provides an
additional possibility (probit) to simulate the dose-response curve and
considers a scaled internal damage instead of the external concentration.
Algae_TKTD()
an S4 object of type AlgaeTKTDScenario
The model has four state variables:
A
, Biomass (ug fresh wt/mL, cells/mL *10^4)
Q
, Mass of phosphorous internal (ug P/ug fresh wt)
P
, Mass of phosphorous external (ug P/L)
Dw
, Damage concentration (ug/L)
Growth model
mu_max
, Maximum growth rate (d-1)
Q_min
, Minimum intracellular P (ug P/ug fresh wt)
Q_max
, Maximum intracellular P (ug P/ug fresh wt)
v_max
, Maximum P-uptake rate at non-limited growth (ug P/ug fresh wt/d)
k_s
, Half-saturation constant for extracellular P (mg P/L)
m_max
, Natural mortality rate (1/d)
I_opt
, Optimum light intensity for growth (uE/m²/s)
T_opt
, Optimum temperature for growth (°C)
T_max
, Maximum temperature for growth (°C)
T_min
, Minimum temperature for growth (°C)
Concentration response (Toxicodynamics)
EC_50
, Effect concentration of 50% inhibition of growth rate (ug L-1)
b
, slope of concentration effect curve at EC_50 (-)
dose_resp
, shape of the dose response curve (0 = logit, 1 = probit)
External concentration (Toxicokinetics)
kD
, dominant rate constant (d-1)
Besides exposure events (Cw), the Algae model requires two environmental
properties as time-series input: Irradiance (I
, uE/m²/s) and
temperature (T_act
, deg C).
Forcings time-series are represented by data.frame
objects
consisting of two columns. The first for time and the second for the
environmental factor in question. The input format for all forcings is a
list of the data frames.
Simulation results will contain the state variables Biomass (A
), mass of
internal phosphorous (Q
), mass of external phosphorous (P
) and the damage
concentration (Dw
). The derivatives are also available as additional output.
nout >= 4
dA
, biomass derivative (µg)
dQ
, internal phosphorous derivative (mg P/ug fresh wt)
dP
, external phosphorous derivative (mg P L-1)
dDw
, damage concentration derivative (ug L-1)
Weber D, Schaeffer D, Dorgerloh M, Bruns E, Goerlitz G, Hammel K, Preuss TG and Ratte HT, 2012. Combination of a higher-tier flow-through system and population modeling to assess the effects of time-variable exposure of isoproturon on the green algae Desmodesmus subspictatus and Pseudokirchneriella subcapitata. Environmental Toxicology and Chemistry, 31, 899-908. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/etc.1765")}
Scenarios, Transferable
Other algae models:
Algae-models
,
Algae_Simple()
,
Algae_Weber()
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