Large scale parameter study of an individual-based model of clonal plant with volunteer computing
Authored by M Garbey, C Mony, M Smaoui, M -L Benot
Date Published: 2011
DOI: 10.1016/j.ecolmodel.2010.10.014
Sponsors:
French National Research Agency (ANR)
Platforms:
BOINC (Berkeley Open Infrastructure for Network Computing)
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
Understanding clonal strategies (i.e. the ability of plants to reproduce
vegetatively) is particularly important to explain species persistence.
A clonal individual may be considered as a network of interconnected
ramets that colonizes space. Resources in this network can be shared
and/or stored. We developed an individual-based model (IBM) to simulate
the growth of an individual clonal plant. Typically a realistic IBM
requires a large set of parameters to adequately represent the
complexity of the clonal plant growth. Simulations in the literature are
often limited to small subsets of the parameter space and are guided by
the a priori knowledge and with heuristic aims of the researcher. The
aim of this paper was to demonstrate the benefit of volunteer computing
in computational ecology to systematically browse the parameter space
and analyze the simulation results in order to draw rigorous
conclusions. To be specific, we simulated clonal plant growth using nine
growth rules related to the metabolic process, plant architecture, resource sharing and storage and nineteen input parameters. We chose 2-4
values per input parameter which corresponded to 20 millions of
combinations tested through volunteer computing. We used three criteria
to evaluate plant performance: plant total resource, ramet production
and maximum length of one branch. The 1\% top-performing plants were
sorted according to these criteria. Plant total resource and ramet
production were correlated while considering the top-performing plants.
The maximum length of one branch was independent from the other two
performance traits. We detected two processes promoting at least one of
the plant performance traits: (i) a relatively high metabolic gain (high
photosynthetic activity and low production cost for new growth units), a
low resource storage and long integration distance for resource sharing;
(ii) short spacer lengths and the predominance of elongation of existing
branches over branching. Interactive effects between parameter values
were demonstrated for more than half of the input parameters. Best
performance was reached for plants with slightly different combinations
of values for these parameters (i.e. different strategies) rather than a
single one (i.e. unique strategy). This modeling approach with volunteer
computing enabled us to proceed to large-scale virtual experiments which
provided a new quality of insight into ecological processes linked with
clonal plant growth. (C) 2010 Elsevier BM. All rights reserved.
Tags
Competition
Simulation
fitness
Grassland
perennials
Physiological integration
Trifolium-repens l.
White clover
Stoloniferous herb
Glechoma-hederacea
Growth rules