Assessing the spatial and spatio-temporal distribution of forest species via bayesian hierarchical modeling
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Published version
Author(s)
Rodríguez de Rivera, Oscar
López-Quílez, Antonio
Blangiardo, MAG
Type
Journal Article
Abstract
Climatic change is expected to affect forest development in the short term, as well as the spatial distribution of species in the long term. Species distribution models are potentially useful tools for guiding species choices in reforestation and forest management prescriptions to address climate change. The aim of this study is to build spatial and spatio-temporal models to predict the distribution of four different species present in the Spanish Forest Inventory. We have compared the different models and showed how accounting for dependencies in space and time affect the relationship between species and environmental variables.
Date Issued
2018-09-16
Date Acceptance
2018-09-11
Citation
Forests, 2018, 9 (9)
ISSN
1999-4907
Publisher
MDPI AG
Journal / Book Title
Forests
Volume
9
Issue
9
Copyright Statement
©
2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/)
2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/)
Subjects
Science & Technology
Life Sciences & Biomedicine
Forestry
hierarchical Bayesian models
stochastic partial differential equation
integrated nested laplace approximation
species distribution
spatial model
spatio-temporal model
NESTED LAPLACE APPROXIMATION
CLIMATE-CHANGE IMPACTS
POINT PROCESS MODELS
CROSS-VALIDATION
VULNERABILITY
EUROPE
EQUIVALENCE
UNCERTAINTY
PREDICTION
INFERENCE
Article Number
ARTN 573