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Overcoming data sparseness and parametric constraints in modeling of tree mortality: a new nonparametric Bayesian model

Abstract:

Accurately describing patterns of tree mortality is central to understanding forest dynamics and is important for both management and ecological inference. However, for many tree species, annual survival of most individuals is high, so that mortality is rare and, therefore, difficult to estimate. Furthermore, tree mortality models have potentially complex suites of covariates. Here, we extend traditional and recent approaches to modeling tree mortality and propose a new non-parametric Bayesia...

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Publication status:
Published

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Publisher copy:
10.1139/X09-083

Authors


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Institution:
University of Oxford
Department:
Oxford, MPLS, Zoology
Role:
Author
Journal:
CANADIAN JOURNAL OF FOREST RESEARCH-REVUE CANADIENNE DE RECHERCHE FORESTIERE
Volume:
39
Issue:
9
Pages:
1677-1687
Publication date:
2009-09-05
DOI:
EISSN:
1208-6037
ISSN:
0045-5067
URN:
uuid:a5c1fb35-e34c-4949-a6ad-71d8bc0a9a93
Source identifiers:
314538
Local pid:
pubs:314538
Language:
English

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