A metamodeling framework for extending the application domain of process-based ecological models

Process-based ecological models used to assess organisms' responses to environmental conditions often need input data at a high temporal resolution, e.g., hourly or daily weather data. Such input data may not be available at a high spatial resolution for large areas, limiting opportunities to u...

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Main Authors: Sparks, Adam, Forbes, Greg A, Hijmans, Robert, Garrett, Karen A
Format: Journal Article
Published: Wiley-Blackwell 2011
Online Access:http://hdl.handle.net/20.500.11937/95229
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author Sparks, Adam
Forbes, Greg A
Hijmans, Robert
Garrett, Karen A
author_facet Sparks, Adam
Forbes, Greg A
Hijmans, Robert
Garrett, Karen A
author_sort Sparks, Adam
building Curtin Institutional Repository
collection Online Access
description Process-based ecological models used to assess organisms' responses to environmental conditions often need input data at a high temporal resolution, e.g., hourly or daily weather data. Such input data may not be available at a high spatial resolution for large areas, limiting opportunities to use such models. Here we present a metamodeling framework to develop reduced form ecological models that use lower resolution input data than the original process models. We used generalized additive models to create metamodels for an existing model that uses hourly data to predict risk of potato late blight, caused by the plant pathogen Phytophthora infestans. The metamodels used daily or monthly weather data, and their predictions maintained the key features of the original model. This approach can be applied to other complex models, allowing them to be used more widely.
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format Journal Article
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institution Curtin University Malaysia
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last_indexed 2025-11-14T11:44:01Z
publishDate 2011
publisher Wiley-Blackwell
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spelling curtin-20.500.11937-952292024-07-04T03:44:49Z A metamodeling framework for extending the application domain of process-based ecological models Sparks, Adam Forbes, Greg A Hijmans, Robert Garrett, Karen A Process-based ecological models used to assess organisms' responses to environmental conditions often need input data at a high temporal resolution, e.g., hourly or daily weather data. Such input data may not be available at a high spatial resolution for large areas, limiting opportunities to use such models. Here we present a metamodeling framework to develop reduced form ecological models that use lower resolution input data than the original process models. We used generalized additive models to create metamodels for an existing model that uses hourly data to predict risk of potato late blight, caused by the plant pathogen Phytophthora infestans. The metamodels used daily or monthly weather data, and their predictions maintained the key features of the original model. This approach can be applied to other complex models, allowing them to be used more widely. 2011 Journal Article http://hdl.handle.net/20.500.11937/95229 10.1890/ES11-00128.1 http://creativecommons.org/licenses/by/3.0/ Wiley-Blackwell fulltext
spellingShingle Sparks, Adam
Forbes, Greg A
Hijmans, Robert
Garrett, Karen A
A metamodeling framework for extending the application domain of process-based ecological models
title A metamodeling framework for extending the application domain of process-based ecological models
title_full A metamodeling framework for extending the application domain of process-based ecological models
title_fullStr A metamodeling framework for extending the application domain of process-based ecological models
title_full_unstemmed A metamodeling framework for extending the application domain of process-based ecological models
title_short A metamodeling framework for extending the application domain of process-based ecological models
title_sort metamodeling framework for extending the application domain of process-based ecological models
url http://hdl.handle.net/20.500.11937/95229