The Scaled Subspaces Method: A new trait-based approach to model communities of populations with largely inhomogeneous density
Authored by Marco Castellani, Jarl Giske, Espen Strand, Selina Vage, T Frede Thingstad
Date Published: 2013
DOI: 10.1016/j.ecolmodel.2012.12.006
Sponsors:
European Union
Norwegian Research Council (NRF)
Platforms:
C++
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Abstract
We present a new individual-based approach to model populations of
largely inhomogeneous densities. By monitoring different populations at
a spatial scale which is inversely proportional to the maximum expected
concentration, the Scaled Subspaces Method solves the problem of
demographic explosion of the most numerous species. It is intuitively
similar to the experimental practice of changing the magnification of a
microscope depending on the size-class of organisms inspected, and
retains the possibility for uniform biological descriptions across
scales. We use this method to simulate a pelagic microbial mixotrophic
food web, where the most abundant species has population densities up to
five orders of magnitude higher than the rarest species. The model
generates biologically plausible and highly consistent predictions of
biomass distribution across this density spectrum. Individual-based
community models are affected by the possibility of artificial
extinctions. We discuss theoretically and confirm experimentally this
possibility, and show that this problem can be overcome through the use
of large populations, genetic mutations, and periodical random
reintroduction of lost species or traits. We also show that the proposed
individual-based model produces the same solutions as a state-variable
model of the same ecological scenario. This indicates that the
predictions of the two models are independent of implementation issues, and allows using them interchangeably according to convenience. Overall, the study proves the viability of the Scaled Subspaces Method, and
provides useful insights on its functioning and parameterization. (C)
2013 Elsevier B.V. All rights reserved.
Tags
Individual-based model
Dynamics
Phytoplankton
plankton
growth
Fish
Ocean
North-atlantic
Lagrangian ensemble model
Mixotrophs