An Integrated Platform for Agro-ecosystems Study
Ronan Tr
epos, H
ene Raynal and Gauthier Quesnel
INRA, UR875 Biom
etrie et Intelligence Artificielle, F-31326 Castanet-Tolosan, France
Agro-ecosystems, Modeling and Simulation Platform.
The complexity of models developped in order to improve the agricultural systems and the need to have
efficient tools to build them, simulate and analyse them have motivated the conception and the development of
the new modelling and simulating platform RECORD. This paper describes how this initiative of the French
National Institute for Agricultural Research has been conducted. A pragmatic strategy consisting in integrating
heterogeneous tools into a same framework has been used. The example of the integration of the 3 different
tools: VLE, R, Python illustrates how the users’ requirements have been fullfilled. The platform is currently
used in various projects, and on the basis of the first experiences, we conclude on the interest of this strategy.
We underline that this strategy must be accompanied by efforts on developping user’s training and coaching on
these powerful tools. Finally software design should facilitate collaborative developments, which will motivate
our future works.
Agriculture is currently driven by continuously evolv-
ing challenges (e.g. climate change, environmental
concerns, market globalisation, food safety and qual-
ity) and requires the development of innovative sus-
tainable production systems. Modelling and simu-
lation approaches are usefull in identifying the agri-
cultural systems that respond to current social, eco-
nomic, political and environmental concerns. How-
ever, building, testing, evaluating and using models
(i.e. simulating different combinations of manage-
ment, soil and climate conditions and policy and envi-
ronmental constraints) is far from being a straightfor-
ward task. Numerous models that can address ques-
tions about agro-ecosystem functioning already ex-
ist. The major issue now is how to combine or cou-
ple these models and use them at different spatial
and temporal scales rather than develop new models.
To overcome the problems which arise when build-
ing, simulating and reusing models, generic com-
puting platforms have been created. Most of these
platforms capitalise on advances in computer sci-
ence (e.g. object-oriented, modular and generic pro-
gramming) and propose model repositories to facili-
tate their use and re-use (e.g. CropSyst (Van Evert
and Campbell, 1994) or ICASA (Bouma and Jones,
To take advantage of these developments the
French cropping-system research community tries to
define a strategy to developp an integrated modelling
platform, named RECORD (REnovation and COOR-
Dination of agro-ecosystems modelling), to gather,
link and build models and companion tools to answer
new agricultural questions (Bergez et al., 2012). We
present in this paper the pragmatic approach we have
used to developp the platform. It is essentially based
on dedicated software development and reuse of ex-
isting tools. The first section gives an overview of
the functional requirements of the platform. Section
2 explains how the RECORD platform was designed
in order to fulfill the initial requirements.
The functional requirements for the platform were de-
fined following a survey targeting modellers from the
Environment and Agronomy department of INRA and
seminar in 2007.
Scope and Users. The platform must be able to
simulate cropping systems and interactions with the
surrounding territory. Four types of users were identi-
fied: i) researchers working on and designing crop-
Trépos R., Raynal H. and Quesnel G..
RECORD - An Integrated Platform for Agro-ecosystems Study.
DOI: 10.5220/0004058801860189
In Proceedings of the 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH-2012),
pages 186-189
ISBN: 978-989-8565-20-4
2012 SCITEPRESS (Science and Technology Publications, Lda.)
Figure 1: The coupling of a decision model, an assessment model called Bilan, and the corn crop model 2CV designed into
VLE. Up right, the hierarchical structure of the model is given into a tree structure. The model embeds coupled models (e.g.
2CV, CropFull) and atomic models (e.g. Decision, SoilSWCB).
ping systems ii) researchers using cropping system
models iii) extension service personnel who wants to
test new cropping-systems proposals and iv) graduate
students being trained in modelling.
Accepting Various Time and Spatial Scales.
Hourly simulations up to several decades for sustain-
ability studies have to be permitted. Spatial aggrega-
tions include a plot or a set of plots representing one
or more farms, including, if necessary, interstitial ar-
eas and larger areas such as a territory when dealing
with natural resources (e.g. a catchment). Transfers
between different spatial units must also be modelled
(e.g. water exchange, pests, genes, spores).
Accepting Various Formalisms. Most current
models are dynamic with discrete time steps. How-
ever, the platform also should be able to incorpo-
rate static and stochastic models and different for-
malisms (e.g. difference equations, differential equa-
tions, Markov chains, state charts, cellular automata).
Focusing on Management. It is particularly im-
portant that the platform be able to handle manage-
ment models for cropping systems. Modelling fac-
tors such as technical operations sequences, compe-
tition among agricultural tasks, spatial distribution of
agricultural practices and choice of crop rotations in a
field must be possible.
Using Existing Codes. Existing crop models cover
a wide variety of crops, crop management options
and spatial and temporal scales. The architecture of
the platform should enable integration of these dif-
ferent types of models, either by recoding or by en-
capsulating existing code. The design of the platform
should also allow model developpers to share easily
their models and generic developments through a col-
laborative development strategy.
Using Models. The platform should facilitate i) im-
plementation of optimisation methods by simulation,
ii) implementation of methods of multicriteria choice,
iii) comparison of cropping-systems models and iv)
use of data-mining techniques to exploit simulation
results. Deployment of models on web sites should
be facilitated by generic web development.
Applications in agriculture or environment requires
frequently the integration of several models, the pos-
sibility to share them and to explore them with nu-
merical methods. For modelisation and simulation,
the platform relies on DEVS theory and VLE soft-
ware. The use of R software is favoured for statisti-
cals works on models (parameterization, evaluation).
Finally, python language and its libraries offer a good
solution for web development.
DEVS Theory. DEVS (Discrete Event System
Specification) is a theoretical formalism for mod-
elling and simulating dynamic systems with discrete
events. It provides a robust solution for the coupling
and integration of heterogeneous models and the im-
plementation of complex hierarchical systems as it
was proved by formal mathematical proofs (Zeigler
et al., 2000). There are two types of models in DEVS,
atomic and coupled models, which exchange infor-
mation in the form of events. Based on DEVS theory,
the abstract simulator DSDE (Barros, 1998), is able
to modify model structure during a simulation with
an atomic model called executive.
VLE Software. VLE (Quesnel et al., 2009) is a
free and open-source software developed in C++
which provides simulators, modelling tools, libraries,
an IDE (Integrated Development Environment) and
a SDK (Software Development Kit). It is a
generic modelling, simulation and analysis environ-
ment based on the DEVS formalism, and implements
a DSDE simulator. VLE offers a library of extensions
which correspond to commonly-used mathematical
formalisms: cellular automata, statecharts, ordinary
differential equations (including classical numerical
integration schemes such as Runge Kutta and QSS
(Cellier et al., 2008)), difference equations and a de-
cision making extension based on planification of ac-
tivities. We identified the three last cited extensions
as a basis for modeling agro-ecosystems. Solutions
for complex models that involve large territories are
provided. For example modelling hundreds of plots
is achieved by using “executive” models that gener-
ate the plots and their connections from GIS (Geo-
graphical Information System) data. A GUI (Graphi-
cal User Interface) is used to edit models, to set initial
conditions and to perfom simple simulations (Figure
1). For multi-simulation, one can express experiment
plans as combinations of initial conditions and par-
allelisation of simulations on different cores can be
Statistical and Mathematical Works with Models.
Statistical methods for parameter estimation, valida-
tion and sensitivity analysis are necessary for imple-
menting and analysing agro-ecosystem models (Wal-
lach et al., 2006). Platform RECORD relies on a
package rvle that links VLE to the statistical language
R (R Development Core Team, 2011) in order to per-
form models calibration and exploration. For exam-
ple, Table 1 gives indices resulting from a sensitivity
analysis performed with fast99 (Saltelli et al., 1999)
on the crop model 2CV. It concerns 5 decision vari-
ables for irrigation and targets a net margin output.
Based on this analysis, one can search for the couple
of values of water supply and stock (ie. the variables
that impact the most the output), that lead to a maxi-
mal expected net margin. The stochastic behavior of
the model comes from climatic data produced by a
a stochastic generator of climatic series available into
the platform. Results of a simulated annealing optimi-
sation, performed with R function optim, suggest the
couple (16 mm, 121 mm) which leads to an expected
output of 898 euros per hectare.
Concerning optimisation of agro-ecosystems
models, challenges such as multi-objective (e.g.
economic and ecologic criterion) and optimisation
under uncertainty (when e.g. models depend on
climatic data) arise rapidly; see e.g. (Crespo et al.,
2010). Current works also concern embedding opti-
misation into simulation. For example, optimising the
behavior of an agent that reacts to a system such as
a biophysical model, by mean of e.g. reinforcement
learning (Garcia, 1999) requires that the optimisation
is finely coupled to simulation.
Table 1: Indices (ordered by total effect) of 5 decision vari-
ables resulting from a sensitivity analysis.
interactions total
water stock 0.54 0.29 0.83
water supply 0.37 0.39 0.76
0.20 0.20 0.40
threshold on
0.002 0.042 0.044
soil water
threshold on
0.003 0.040 0.043
available water
Web Applications. The models in the RECORD plat-
form could be of real interest as educational tools to
improve understanding of agro-ecosystems or as tools
for decision makers to integrate agronomic, social,
economic and environmental issues. However, di-
rect use of these models by non-scientists or by users
with limited computed skills could be problematic be-
cause i) they often require significant parameterisa-
tion to adapt them to individual contexts, ii) model
validity is context-dependent and iii) working directly
on the platform requires a minimum level of train-
ing. Therefore, we proposed a web-oriented tool, de-
signed to develop web applications around the mod-
els implemented on the platform (Figure 2). This
tool is based on the development of a specific pack-
age: PyVLE that enables the use of VLE from Python
applications. This package provides a set of func-
tions that enable the management of VLE simulations
from Python scripts. Therefore, VLE simulators can
be parameterized, launched from Python and results
are available for further uses such as graphical repre-
sentations. A framework (such as Pylons, Django or
Zope) to help in developing the application is used.
The database holds the information used to specify
the various simulated contexts (e.g. climate, soil, va-
rietal characteristics, crop distributions). There is one
model per context, and several contexts are simulated
at the same time. The results are aggregated into in-
dicators and graphs which are easily understandable
by professionals. Some applications are already on-
line and used by scientists, students and agricultural
User browser
Service Web
Framework Pylon
User database
Figure 2: The main elements of the RECORD web archi-
Since 2007, choices have been made for the develop-
ment of the platform RECORD. First, it has been de-
cided that all features that were required should not be
part of one unique tool, in light of the large range of
disciplines that are involved. Nevertheless the techni-
cal solutions should not restrain the different commu-
nities to a confined set of methods and tools. Techni-
cal solutions for model development, model analysis
and web applications are the following:
The software VLE provides an IDE for designing
and coupling models. Coupling properties are en-
sured by the DEVS theory which is the basis of
VLE. This IDE can be used to perform the first
R and its libraries are used for analysing and ex-
ploring models. The platform relies on a specific
R package that links R to VLE.
Python and its libraries are the basis of web ap-
plications development for RECORD projects,
thanks to a link between Python and VLE.
A large set of methods and tools are thus possibly
carried out into the platform. Due to this integration
strategy, there are few assumptions that are made re-
garding the methods that are involved. For example,
parameter estimation of a model using R can be per-
formed in different ways. The challenge of RECORD
is to identify well suited methods with the help of ex-
perts and to build training courses which are provided
through an E-learning web site and 3-days practice
sessions (2 per year).
We finally argue that integrating tools is the best
solution to develop a collaborative platform. An-
other important task that the platform team addresses
is to facilitate the collaborative work. The solutions
proposed and which are currently under construction
comprise the package management system into VLE,
attachment of meta-data to packages and models for
documentation and configuration.
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