A new algorithm for reconstructing tree height growth with stem analysis data
Cite this dataset
Salas-Eljatib, Christian (2021). A new algorithm for reconstructing tree height growth with stem analysis data [Dataset]. Dryad. https://doi.org/10.5061/dryad.qnk98sfgc
Abstract
I offer here both dataset and computing code related to a stem analysis algorithm to reconstruct height growth of trees. First, the dataset has time series records of tree height for Nothofagus alpina ("rauli"), N. dombeyi ("coigue"), N. obliqua ("roble"), and Pseudotsuga menziesii ("Douglas-fir"). The data come from stem analysis sample trees in both southern Chile and the Inland Northwest, USA. These trees are part of the ones used in an article about a new algorithm for reconstructing tree height growth. The article is published in Methods in Ecology and Evolution (https://doi.org/10.1111/2041-210x.13616). Second, I provide an R code implementing the proposed algorithm for a given dataset as example.
Methods
See methods and accompanying paper in the following article for more details.
Salas-Eljatib C. 2021. A new algorithm for reconstructing tree height growth with stem analysis data. Methods in Ecology and Evolution 12: 2008-2016.
Usage notes
The datafile "dataHgSpp.dat" has the following columns:
1. tree.code: tree code
2. tree.id: tree correlative number within the species
3. spp: species common name
4. age : age, in yrs.
5. height: total height, in m.
The R code "stemAnaAlgo.R" can be run without the need to install any further package. Therefore, It is pretty straightforward.
See methods and accompanying paper in Methods in Ecology and Evolution for more details.
If you want to read this datafile in R, simply type the following syntax at the console:
df <- read.table(file="dataHgSpp.dat", header = T, skip=22)
head(df)
str(df)
For any questions, or if you want to collaborate, please refer to:
Christian Salas-Eljatib
Email: cseljatib AT gmail DOT com
Web: www.eljatib.com
Funding
Agencia Nacional de Investigación y Desarrollo, Award: ID19|10421
Fondo Nacional de Desarrollo Científico y Tecnológico, Award: 1191816