DEBtox {cvasi}R Documentation

DEBtox model

Description

Creates a DEBtox scenario as described by Jager (2020). It represents a simplified DEBtox model based on DEBkiss. In the BYOM application [link], this model is referred to as DEBtox 2019, version 4.7. It supports an optional feature of the ERA special model variant, which can consider a reference Lm parameter to compare results of multiple datasets.

Usage

DEBtox()

DEB_Daphnia()

Details

State variables

The following list describes the names and units of the model's state variables:

State variables D, L, and R are initialized with zero. Variable S is initialized with one (1.0). See set_init() on how to set the initial state manually.

Parameters

The following parameters are required:

A reference Lm_ref is needed to properly compare different data sets, or when calibrating on more than one data set. If Lm differs, one would not want to have different rate constants at the same length.

Mode of Action

Any combination of the following mode of actions (MoA) can be considered by the model:

To activate more than one mode of action, simply add up the corresponding codes and set parameter MoA to the desired value. To disable all mode of actions, set parameter MoA to zero. See also set_moa().

As an example, to consider effects on feeding and maintenance, set the mode of action to three (3):

DEBtox() %>% set_param(c(MoA=3))

Feedbacks

Any combination of the following damage feedbacks can be considered by the model:

To activate more than one feedback, simply add up the corresponding codes. To disable all feedbacks, set the parameter to zero.

Effects

The state variables L (body length), R (cumulative reproduction), and S (survival probability) 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 DEBtox scenario is simulated twice: One simulation which considers exposure to a toxicant and one simulation without exposure, i.e. a control. See also effect().

Simulation output

The following intermediary model variables can be added to the model output on demand. Simply set the optional parameter nout to the required output level and pass it to simulate().

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.

Some default settings of deSolve were adapted for this model by expert judgement to enable precise, but also computationally efficient, simulations for most model parameters. These settings can be modified by the user, if needed:

Model history and changes

Value

an S4 object of type DebTox

Functions

References

Jager T, 2020: Revisiting simplified DEBtox models for analysing ecotoxicity data. Ecol Model 416. doi:10.1016/j.ecolmodel.2019.108904

Romoli et al., 2024: Environmental risk assessment with energy budget models: a comparison between two models of different complexity. Environ Toxicol Chem 43(2):440-449. doi:10.1002/etc.5795

See Also

Other DEB models: DEB-models, DEB_abj()


[Package cvasi version 1.4.0 Index]