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Extending the use of ecological models without sacrificing details: a generic and parsimonious meta‐modelling approach
Author(s) -
Marie Guillaume,
Simioni Guillaume
Publication year - 2014
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12250
Subject(s) - computer science , metamodeling , ecology , scope (computer science) , scale (ratio) , field (mathematics) , parameterized complexity , range (aeronautics) , engineering , geography , mathematics , cartography , algorithm , aerospace engineering , pure mathematics , biology , programming language
Summary Difficulties in accounting for the fine scale nature of ecological processes in large‐scale simulations constitute an important issue in ecology. Among existing methods, meta‐modelling, that is creating a statistical emulator of a model, has seen very few applications in ecology. Yet, meta‐modelling methods are well advanced in the field of engineering. We adapted and applied a meta‐modelling approach to a case study typical of the complexity found in ecosystems. It involved a highly detailed, individual‐based and spatially explicit biophysical model (noTG). The model was parameterized for a multi‐specific, spatially heterogeneous forest. Our goal was to increase its temporal domain of applicability by obtaining a meta‐model of its light interception module many times faster. The meta‐model was constructed from a series of simulations with noTG, following a latin hypercube design. Several meta‐modelling techniques were compared, with neural networks providing the best results. The meta‐model accurately reproduced the behaviour of noTG across a range of variables and organization levels. It was also 62 times faster. These result show that meta‐modelling can be a practical tool in ecology and represents a highly powerful way to change the scope of a model while still accounting for fine details.