Output details
11 - Computer Science and Informatics
University of Southampton
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Output 0 of 0 in the submission
Article title
Connecting dynamic vegetation models to data - an inverse perspective
Type
D - Journal article
Title of journal
Journal of Biogeography
Article number
-
Volume number
39
Issue number
12
First page of article
2240
ISSN of journal
0305-0270
Year of publication
2012
Number of additional authors
6
Additional information
Significance of output:
<27>This article, in a top Journal for Physical Geography, shows for the first time how Bayesian statistical methods can be used to improve the performance of process-based ecological models. The techniques developed have since been applied in the context of lake ecosystems and the analysis of limnological data. This has involved researchers from UK and China. Approach validated with mathematical analysis and computer simulations. We detail how other scientists can apply our approach to a wide range of process-based models.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
12
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
