Miscellaneous software
On this page, I will collect
links to freely-available software packages provided by
other parties to perform calculations on GUTS and DEB(tox).
I have not been involved in the production of these packages
(apart from openGUTS), so I cannot provide any assistance or
support for them. I am responsible for the Matlab
implementations of GUTS, DEBtox and DEBkiss as part of the BYOM
platform. Several more implementations for GUTS are known to
exist, of which a number is planned to be offered for free
download by their developers in the near future. When more
information is available I will update the list below.
Web-based GUTS calculations
A web-based and user-friendly way
to perform GUTS calculations (reduced SD and IT models only)
is available in the MOSAIC facility at https://mosaic.univ-lyon1.fr/guts.
See also the papers of Baudrot et al
(2018) and Charles
et al (2022). Under the hood, it applies Bayesian
inference with the MORSE R-package. This is a very elegant
implementation, but the user needs to realise that the
software applies weakly informative prior distributions
(i.e., the output is more than just the information from the
data set). The priors are based on test design, which I
believe is somewhat awkward (see my
comment in ES&T and the author's
response to that). In general, these priors will not
affect the results. However, in specific cases (when a
parameter runs away to zero or infinity, e.g., 'slow
kinetics'), they will influence the results (to some
extent). In the current version, these cases are flagged
with a warning, so the user is aware that the priors are
affecting the results.
This touches upon a general issue for Bayesian inference
(and MCMC) when the posterior is insufficiently constrained
by the data (and becomes 'improper'). For more information I
suggest the excellent and readable paper from Raue et
al. (2013). At this moment, it is unclear to me how
other Bayesian GUTS applications address this issue.
Standalone GUTS software
In December 2019, the first
version of the openGUTS standalone software was released.
This is an easy-to-use and robust software that runs under
Windows. It can be freely downloaded from the dedicated
website http://openguts.info/.
There is also a Matlab version of openGUTS, available from
the same website.
In June 2018, the Fraunhofer Institute has launched the
first version of their standalone GUTS-3S. More information. A test
version of this software was included in the ring test
(which is part of the GUTS e-book).
I have not looked at this version yet, so I cannot provide
you with my opinion just yet.
A user interface for the GUTS-R (see below) package is
currently being developed by RIFCON, turning it into a
standalone software under the name EasyGUTS (presented in
SETAC posters in 2017 and 2018). This version is planned to
become available for free download, but is not available yet
(only on request). This version should be able to do the
reduced GUTS models (also SD and IT combined). Mentioned on
the Rifcon downloads
site under 'download software'.
R-packages for GUTS
Two R-packages are available to
make the GUTS calculations in a Bayesian framework. The
first package was developed by Carlo Albert & Sören
Vogel, is currently maintained by RIFCON, and can be found
at https://cran.r-project.org/package=GUTS.
I am not sure if and how they deal with the issue of
'improper posteriors' noted above for the web-based MOSAIC
software.
The second is the MORSE R-package, as developed and
maintained by the University of Lyon. It contains the
reduced SD and IT models. This package can be found at https://cran.r-project.org/package=morse.
There is a web-based interface around it as well (see
previous item above).
Python-package for GUTS
A Python toolbox is available for
GUTS calculations. The toolbox is developed and maintained
by Raymond Nepstad (SINTEF, Trondheim), and can be
downloaded from GitHub: https://github.com/nepstad/epytox
Web-based DEBtox predictions
Take a look at the DeEP tool for
EPx predictions with DEBtox2019.
Note that this tool does not perform calibrations or
validations on data sets, but rather makes EPx predictions
for exposure profiles, such as those from FOCUS. As input,
it requires model parameters to be entered as well as an
exposure profile (in simple text format). As of version 6.4,
BYOM contains
functionality to translate DEBtox2019 calibration output to
a DeEP input file.
DEB-IBM in NETlogo
The individual-based modelling
implementation of DEB in NetLogo of
Martin et al. (2012) can be found CREAM
website or on Ben
Martin's personal pages. This is a flexible model for
population dynamics using DEB individuals, and quite user
friendly. The associated publication is:
Martin B, Zimmer EI, Grimm V and Jager T (2012). Dynamic
Energy Budget theory meets individual-based modelling: a
generic and accessible implementation. Methods in Ecology
and Evolution 3:445-449. http://dx.doi.org/10.1111/j.2041-210X.2011.00168.x
DEBtool in Matlab
DEBtool is an extensive library of
code in Matlab to perform a wide range of DEB calculations.
Originally developed by Bas Kooijman, but now maintained and
developed by a larger group of experts. DEBtool (and various
extensions) can be found in the DEB portal, and that is the
best place to get more information about it.
User-friendliness is limited as there is no GUI (just as
with BYOM), so experience with Matlab coding and DEB theory
is indispensable. The DEBtool software is used in the DEB course,
so the course is the best place to get started with it.
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