Multilevel analysis of dendroclimatic series with the R-package BIOdry.

The R-package BIOdry allows to model and compare fluctuations of Tree-ring Width (TRW) and climate, or dendroclimatic fluctuations, while accounting for source variability. The package eases multilevel modeling and multivariate comparison in dendroclimatic analysis using the nlme and ecodist package...

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Main Authors: Wilson Lara, Stella Bogino, Felipe Bravo
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5957401?pdf=render
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spelling doaj-ea005eaf35004e8097fe85e59ee2e4b32020-11-25T01:07:19ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01135e019692310.1371/journal.pone.0196923Multilevel analysis of dendroclimatic series with the R-package BIOdry.Wilson LaraStella BoginoFelipe BravoThe R-package BIOdry allows to model and compare fluctuations of Tree-ring Width (TRW) and climate, or dendroclimatic fluctuations, while accounting for source variability. The package eases multilevel modeling and multivariate comparison in dendroclimatic analysis using the nlme and ecodist packages, respectively. For implementing such libraries, the in-package algorithms transform the dendroclimatic fluctuations into Multilevel Dendroclimatic Data Series and maintain categorical variables and time units in the outputs. The dendroclimatic modeling is developed with two functions: modelFrame and muleMan. The first function binds core-level cumulative TRWs to the processed data sets and subtracts trends in TRWs by fitting multilevel log-linear growth formulas or multilevel linear formulas. modelFrame can also model within-group fluctuations in dendroclimatic variables other than tree-radial increments such as aridity indices or allometric components of tree growth: e.g. diameters at breast height over bark, tree basal areas, total tree biomass, among other. The second function compares fluctuations in modelFrame objects that share outermost categorical variable and annual records. Here, we use BIOdry to model dendroclimatic relationships in northern and east-central Spain to illustrate future users in the implementation of the package for modeling ecological relationships in space and time.http://europepmc.org/articles/PMC5957401?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Wilson Lara
Stella Bogino
Felipe Bravo
spellingShingle Wilson Lara
Stella Bogino
Felipe Bravo
Multilevel analysis of dendroclimatic series with the R-package BIOdry.
PLoS ONE
author_facet Wilson Lara
Stella Bogino
Felipe Bravo
author_sort Wilson Lara
title Multilevel analysis of dendroclimatic series with the R-package BIOdry.
title_short Multilevel analysis of dendroclimatic series with the R-package BIOdry.
title_full Multilevel analysis of dendroclimatic series with the R-package BIOdry.
title_fullStr Multilevel analysis of dendroclimatic series with the R-package BIOdry.
title_full_unstemmed Multilevel analysis of dendroclimatic series with the R-package BIOdry.
title_sort multilevel analysis of dendroclimatic series with the r-package biodry.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2018-01-01
description The R-package BIOdry allows to model and compare fluctuations of Tree-ring Width (TRW) and climate, or dendroclimatic fluctuations, while accounting for source variability. The package eases multilevel modeling and multivariate comparison in dendroclimatic analysis using the nlme and ecodist packages, respectively. For implementing such libraries, the in-package algorithms transform the dendroclimatic fluctuations into Multilevel Dendroclimatic Data Series and maintain categorical variables and time units in the outputs. The dendroclimatic modeling is developed with two functions: modelFrame and muleMan. The first function binds core-level cumulative TRWs to the processed data sets and subtracts trends in TRWs by fitting multilevel log-linear growth formulas or multilevel linear formulas. modelFrame can also model within-group fluctuations in dendroclimatic variables other than tree-radial increments such as aridity indices or allometric components of tree growth: e.g. diameters at breast height over bark, tree basal areas, total tree biomass, among other. The second function compares fluctuations in modelFrame objects that share outermost categorical variable and annual records. Here, we use BIOdry to model dendroclimatic relationships in northern and east-central Spain to illustrate future users in the implementation of the package for modeling ecological relationships in space and time.
url http://europepmc.org/articles/PMC5957401?pdf=render
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