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Cendrine Mony (*), Marc Garbey (**), Malek Smaoui (**) and Marie-Lise Benot (*)
(**) Department
of Computer
Science,
The goal of this
project
is to study the fundamental mechanisms involved in the dynamic of a
prairie in
response to disturbance (recurrent mowing, grazing…). Such
model has several
applications such as the design of prairies with high agronomical
values or the
preservation of ecological systems with high biodiversity. New insights
are
also developed recently on new ecological uses of such systems (see for
instance the recent study sponsored by NSF “Mixed Prairie
Grasses are better
source of biofuel than corn ethanol and soybean biodiesel”, http://www.nsf.gov/news/news_summ.jsp?cntn_id=108206).
Through the ViP project,
the effects of management
practices on plant competition and genetic structure of the prairie
will be
forecast.
In our project,
experimental data from both statistical measurements in prairie and
controlled
experiments on individual clonal plant growth under various
environmental
conditions provide the basis for modeling. An individual agent based
model
simulates individual plants as a growing network of ramets (i.e. new
clonal
individuals) and connexions (structures linking the ramets and
promoting plant
propagation in space).
Phase one
of the
project is to study and classify the behavior of individual clonal
plants and
their strategy to survive in challenging environments: clonal traits
and their
plasticity are at the core of this question. The main target is the
identification
of the objective function that corresponds to the optimal growing
strategy.
Phase two
of the
project is to study the dynamic of clonal species mixtures in prairies.
Rules
linked with plant interaction will be added.
Both phases require very large scale simulations with
embarrassing parallelism that can be friendly achieved with BOINC.
