Preprints
https://doi.org/10.5194/bg-2016-550
https://doi.org/10.5194/bg-2016-550
18 Jan 2017
 | 18 Jan 2017
Status: this discussion paper is a preprint. It has been under review for the journal Biogeosciences (BG). The manuscript was not accepted for further review after discussion.

R-Package BIOdry: DendroClimatic Modeling from Multilevel Ecological Data Series

Wilson Lara, Stella Bogino, and Felipe Bravo

Abstract. R-package BIOdry is developed to consider ecological factors in dendroclimatic modeling of forest ecosystems. The package processes Multilevel ecological data series (MEDS) with two functions: modelFrame and muleMan. These integrate techniques for modeling Tree-rings in wood (TRW) chronologies and climatic series at specific ecological-factor levels (one-level modeling), developing multilevel analysis (mixed-effects detrending), and implementing multivariate comparison of MEDS. Several one-level functions for serial synchronization, drought modeling and allometric scaling are implemented to model tree-diameter growth and drought of Iberian pine forests (Pinus pinaster Ait.). Trends in the dendroclimatic MEDS are subtracted with in-package detrending methods. Extracted fluctuations are normalized with lme methods. Finally, enhancements in dendroclimatic modeling by accounting for ecological factors are tested. We conclude that BIOdry package is an useful tool for studying complex ecological time-space relationships.

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Wilson Lara, Stella Bogino, and Felipe Bravo
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Wilson Lara, Stella Bogino, and Felipe Bravo
Wilson Lara, Stella Bogino, and Felipe Bravo

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Short summary
BIOdry package was developed for dendroclimatic modeling. The package integrates one-level modeling, multilevel analysis, and multivariate comparison of Multilevel Ecological Data Series. We tested the package by studying dendroclimatic relationships of pine forests (P. pinaster Ait.) of north and east-central Spain. Dendroclimatic inferences were affected by within-sample variabilities. BIOdry package proved to be a valuable tool to study complex dendroclimatic time-space relationships.
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