THE ENSEMBLE KALMAN FILTER FOR MULTIDIMENSIONAL BIOECONOMIC MODELS
Abstract To integrate economic considerations into management decisions in ecosystem frameworks, we need to build models that capture observed system dynamics and incorporate existing knowledge of ecosystems, while at the same time accommodating economic analysis. The main constraint for models to s...
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Online Access: | http://dx.doi.org/10.1111/nrm.12070 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fnrm.12070 https://onlinelibrary.wiley.com/doi/pdf/10.1111/nrm.12070 |
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crwiley:10.1111/nrm.12070 2023-12-03T10:20:07+01:00 THE ENSEMBLE KALMAN FILTER FOR MULTIDIMENSIONAL BIOECONOMIC MODELS KVAMSDAL, STURLA F. SANDAL, LEIF K. Norges Forskningsråd 2015 http://dx.doi.org/10.1111/nrm.12070 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fnrm.12070 https://onlinelibrary.wiley.com/doi/pdf/10.1111/nrm.12070 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Natural Resource Modeling volume 28, issue 3, page 321-347 ISSN 0890-8575 1939-7445 Environmental Science (miscellaneous) Modeling and Simulation journal-article 2015 crwiley https://doi.org/10.1111/nrm.12070 2023-11-09T14:36:52Z Abstract To integrate economic considerations into management decisions in ecosystem frameworks, we need to build models that capture observed system dynamics and incorporate existing knowledge of ecosystems, while at the same time accommodating economic analysis. The main constraint for models to serve in economic analysis is dimensionality. In addition, to apply in long‐term management analysis, models should be stable in terms of adjustments to new observations. We use the ensemble Kalman filter to fit relatively simple models to ecosystem or foodweb data and estimate parameters that are stable over the observed variability in the data. The filter also provides a lower bound on the noise terms that a stochastic analysis requires. In this paper, we apply the filter to model the main interactions in the Barents Sea ecosystem. In a comparison, our method outperforms a regression‐based approach. Article in Journal/Newspaper Barents Sea Wiley Online Library (via Crossref) Barents Sea Natural Resource Modeling 28 3 321 347 |
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Open Polar |
collection |
Wiley Online Library (via Crossref) |
op_collection_id |
crwiley |
language |
English |
topic |
Environmental Science (miscellaneous) Modeling and Simulation |
spellingShingle |
Environmental Science (miscellaneous) Modeling and Simulation KVAMSDAL, STURLA F. SANDAL, LEIF K. THE ENSEMBLE KALMAN FILTER FOR MULTIDIMENSIONAL BIOECONOMIC MODELS |
topic_facet |
Environmental Science (miscellaneous) Modeling and Simulation |
description |
Abstract To integrate economic considerations into management decisions in ecosystem frameworks, we need to build models that capture observed system dynamics and incorporate existing knowledge of ecosystems, while at the same time accommodating economic analysis. The main constraint for models to serve in economic analysis is dimensionality. In addition, to apply in long‐term management analysis, models should be stable in terms of adjustments to new observations. We use the ensemble Kalman filter to fit relatively simple models to ecosystem or foodweb data and estimate parameters that are stable over the observed variability in the data. The filter also provides a lower bound on the noise terms that a stochastic analysis requires. In this paper, we apply the filter to model the main interactions in the Barents Sea ecosystem. In a comparison, our method outperforms a regression‐based approach. |
author2 |
Norges Forskningsråd |
format |
Article in Journal/Newspaper |
author |
KVAMSDAL, STURLA F. SANDAL, LEIF K. |
author_facet |
KVAMSDAL, STURLA F. SANDAL, LEIF K. |
author_sort |
KVAMSDAL, STURLA F. |
title |
THE ENSEMBLE KALMAN FILTER FOR MULTIDIMENSIONAL BIOECONOMIC MODELS |
title_short |
THE ENSEMBLE KALMAN FILTER FOR MULTIDIMENSIONAL BIOECONOMIC MODELS |
title_full |
THE ENSEMBLE KALMAN FILTER FOR MULTIDIMENSIONAL BIOECONOMIC MODELS |
title_fullStr |
THE ENSEMBLE KALMAN FILTER FOR MULTIDIMENSIONAL BIOECONOMIC MODELS |
title_full_unstemmed |
THE ENSEMBLE KALMAN FILTER FOR MULTIDIMENSIONAL BIOECONOMIC MODELS |
title_sort |
ensemble kalman filter for multidimensional bioeconomic models |
publisher |
Wiley |
publishDate |
2015 |
url |
http://dx.doi.org/10.1111/nrm.12070 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fnrm.12070 https://onlinelibrary.wiley.com/doi/pdf/10.1111/nrm.12070 |
geographic |
Barents Sea |
geographic_facet |
Barents Sea |
genre |
Barents Sea |
genre_facet |
Barents Sea |
op_source |
Natural Resource Modeling volume 28, issue 3, page 321-347 ISSN 0890-8575 1939-7445 |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1111/nrm.12070 |
container_title |
Natural Resource Modeling |
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28 |
container_issue |
3 |
container_start_page |
321 |
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347 |
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1784267543866769408 |