Uncertainty quantification for ecological models with random parameters

Jody R. Reimer; Frederick R. Adler; Kenneth M. GoldenAkil Narayan

首页> 外文期刊>Ecology letters >Uncertainty quantification for ecological models with random parameters

【24h】

Uncertainty quantification for ecological models with random parameters

机译：Uncertainty quantification for ecological models with random parameters

获取原文

获取原文并翻译 | 示例

获取外文期刊封面封底 >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相关主题

摘要

Abstract There is often considerable uncertainty in parameters in ecological models. This uncertainty can be incorporated into models by treating parameters as random variables with distributions, rather than fixed quantities. Recent advances in uncertainty quantification methods, such as polynomial chaos approaches, allow for the analysis of models with random parameters. We introduce these methods with a motivating case study of sea ice algal blooms in heterogeneous environments. We compare Monte Carlo methods with polynomial chaos techniques to help understand the dynamics of an algal bloom model with random parameters. Modelling key parameters in the algal bloom model as random variables changes the timing, intensity and overall productivity of the modelled bloom. The computational efficiency of polynomial chaos methods provides a promising avenue for the broader inclusion of parametric uncertainty in ecological models, leading to improved model predictions and synthesis between models and data.

著录项

来源
《Ecology letters》 |2022年第10期|2232-2244|共13页
作者
Jody R. Reimer; Frederick R. Adler; Kenneth M. GoldenAkil Narayan;
展开▼
作者单位

University of Utah;

展开▼
收录信息
原文格式 PDF
正文语种英语
中图分类普通生物学;
关键词
aleatory uncertainty; bloom dynamics; epistemic uncertainty; global sensitivity; Jensen's inequality; polynomial chaos; random parameters; sea ice algae; uncertainty quantification;

Uncertainty quantification for ecological models with random parameters

摘要

著录项

相关主题

期刊订阅