Open AccessA metamodeling framework for extending the application domain of process‐based ecological models
Author(s) -
Sparks A. H.,
Forbes G. A.,
Hijmans R. J.,
Garrett K. A.
Publication year - 2011
Publication title -
ecosphere
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.255
H-Index - 57
ISSN - 2150-8925
DOI - 10.1890/es11-00128.1
Subject(s) - metamodeling , process (computing) , phytophthora infestans , computer science , process modeling , domain (mathematical analysis) , key (lock) , data mining , ecology , blight , work in process , engineering , mathematics , mathematical analysis , operations management , computer security , horticulture , biology , programming language , operating system
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.