| Title: | Reconstructing Tree Growth and Carbon Accumulation with Stem Analysis Data |
|---|---|
| Description: | Use stem analysis data to reconstructing tree growth and carbon accumulation. Users can independently or in combination perform a number of standard tasks for any tree species. (i) Age class determination. (ii) The cumulative growth, mean annual increment, and current annual increment of diameter at breast height (DBH) with bark, tree height, and stem volume with bark are estimated. (iii) Tree biomass and carbon storage estimation from volume and allometric models are calculated. (iv) Height-diameter relationship is fitted with nonlinear models, if diameter at breast height (DBH) or tree height are available, which can be used to retrieve tree height and diameter at breast height (DBH). <https://github.com/forestscientist/StemAnalysis>. |
| Authors: | Huili Wu [aut, cre], Wenhua Xiang [aut] |
| Maintainer: | Huili Wu <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 0.1.0 |
| Built: | 2025-03-04 03:47:16 UTC |
| Source: | https://github.com/forestscientist/stemanalysis |
A dataframe containing the list of output variables and their description.
allomCarbonallomCarbon
A data frame with 7 variables:
The growth ring number of the disc at ground
The age class of a tree growths, year
The aboveground biomass of a sampled tree, kg
The belowground biomass of a sampled tree, kg
The total tree biomass of a sampled tree, kg
The aboveground carbon storage of a sampled tree, kg
The belowground carbon storage of a sampled tree, kg
The total tree carbon storage of a sampled tree, kg
head(allomCarbon)head(allomCarbon)
A dataset containing the list of input variables and their description. Note: If a user uses the StemAnalysis package to estimate a sampled tree carbon by allometric models, a parameters dataset should be provided. Owing the allometric model varies among tree species, the users should input the parameter data of the allometric models for the correspondingly tree species.
allomPardataallomPardata
A data frame with 3 rows and 7 variables:
The line number
The tree diameter of breast height, cm
The tree tissues including aboveground and belowground
The parameter a in the allometric model ln(B)=ln(a)+b×ln(DBH)+c×ln(H)
The parameter b in the allometric model ln(B)=ln(a)+b×ln(DBH)+c×ln(H)
The parameter c in the allometric model ln(B)=ln(a)+b×ln(DBH)+c×ln(H)
The carbon concentration in each tree tissues, kg C kg-1
head(allomPardata)head(allomPardata)
Reconstructing Tree Growth and Carbon Accumulation with Stem Analysis Data
stemanalysism( xtree, stemgrowth = FALSE, treecarbon = FALSE, HDmodel = FALSE, stemdata, allompardata, volumepardata )stemanalysism( xtree, stemgrowth = FALSE, treecarbon = FALSE, HDmodel = FALSE, stemdata, allompardata, volumepardata )
xtree |
Xtree is the tree number (Treeno), which is used to choose a target tree to be analyzed |
stemgrowth |
If stemgrowth is 'TRUE', stem growth profile and growth trends in terms of diameter at breast height (DBH), tree height, and stem volume will be showed in a graph. A example graph is man/Figures/StemGrowth.png |
treecarbon |
If treecarbon is 'TRUE', total tree biomass and carbon storage will be estimated by general allometric models (National Forestry and Grassland Administration, 2014) and volume model (Fang et al., 2001). The example graphs are man/Figures/TreeCarbon_allometric.png and TreeCarbon_volume. In addition, although treecarbon is 'TRUE', the estimation of tree biomass and carbon storage by allometric models will skip if 'allompardata' is missing, and the same is true for the estimation by volume model if 'volumepardata' is missing. |
HDmodel |
If HDmodel is 'TRUE', height-diameter relationship will be fitted with nonlinear models (Mehtatalo, 2017) and showed the fitted results in a graph. A example graph is man/Figures/HDmodel.png |
stemdata |
table as described in |
allompardata |
table as described in |
volumepardata |
table as described in |
A list with class "output" containing three data.frame.
- 'StemGrowth': the estimated stem growth trends data for a target tree, including the tree age class and the corresponding growth data of diameter at breast height (DBH), stem height, and stem volume. More details on the output is StemGrowth
- 'allomCarbon': the estimated tree biomass and carbon storage data by using allometric models for a target tree, including tree biomass and carbon storage for aboveground, belowground, and total tree. More details on the output is allomCarbon
- 'volumeCarbon': the estimated tree biomass and carbon storage data by using volume model for a target tree, including tree biomass and carbon storage for aboveground, belowground, and total tree. More details on the output is volumeCarbon
The stemanalysis was performed on individual trees
Fang, J., Chen, A., Peng, C., et al. (2001) Changes in forest biomass carbon storage in China between 1949 and 1998. Science 292, 2320-2322. doi:10.1126/science.1058629
Mehtatalo, L. (2017) Lmfor: Functions for forest biometrics. https://CRAN.R-project.org/package=lmfor
National Forestry and Grassland Administration. (2014) Tree biomass models and related parameters to carbon accounting for Cunninghamria lanceolata. Forestry industry standards of the People's Republic of China Beijing, LY/T 2264—2014
library(StemAnalysis) # Load the data sets data(stemdata) data(volumePardata) data(allomPardata) # To calculating stem growth trends for an individual tree is needed stemanalysism(xtree = 8, stemgrowth = TRUE, stemdata = stemdata) # To calculating tree carbon storage by allometric models is needed stemanalysism(xtree = 8, treecarbon = TRUE, stemdata = stemdata, allompardata = allomPardata) # To calculating tree carbon storage by volume model is needed stemanalysism(xtree = 8, treecarbon = TRUE, stemdata = stemdata, volumepardata = volumePardata) # To fitting the height-diameter relationships stemanalysism(xtree = 8, HDmodel = TRUE, stemdata = stemdata)library(StemAnalysis) # Load the data sets data(stemdata) data(volumePardata) data(allomPardata) # To calculating stem growth trends for an individual tree is needed stemanalysism(xtree = 8, stemgrowth = TRUE, stemdata = stemdata) # To calculating tree carbon storage by allometric models is needed stemanalysism(xtree = 8, treecarbon = TRUE, stemdata = stemdata, allompardata = allomPardata) # To calculating tree carbon storage by volume model is needed stemanalysism(xtree = 8, treecarbon = TRUE, stemdata = stemdata, volumepardata = volumePardata) # To fitting the height-diameter relationships stemanalysism(xtree = 8, HDmodel = TRUE, stemdata = stemdata)
A dataset containing the list of input variables and their description. Note: If a user uses the StemAnalysis package to analysis a very big tree, the number of inner growth rings that diameter measured for some cross-sectional discs may be more than 11, the Dnobark12, Dnobark13, and much more variables can be added, which also could successfully run.
stemdatastemdata
A data frame with 98 rows and 18 variables:
The line number
The tree number for the sampled tree, the same number represents the same tree
Tree total height, m
The stem height that the cross-sectional discs were obtained, m
The age namely the number of growth rings of the cross-sectional disc, year
The maximum diameter of the cross-sectional disc with bark, cm
The maximum diameter of the cross-sectional disc without bark, cm
The diameter for the 1th age class inner growth ring of the cross-sectional disc, cm
The diameter for the 2th age class inner growth ring of the cross-sectional disc, cm
The diameter for the 3th age class inner growth ring of the cross-sectional disc, cm
The diameter for the 4th age class inner growth ring of the cross-sectional disc, cm
The diameter for the 5th age class inner growth ring of the cross-sectional disc, cm
The diameter for the 6th age class inner growth ring of the cross-sectional disc, cm
The diameter for the 7th age class inner growth ring of the cross-sectional disc, cm
The diameter for the 8th age class inner growth ring of the cross-sectional disc, cm
The diameter for the 9th age class inner growth ring of the cross-sectional disc, cm
The diameter for the 10th age class inner growth ring of the cross-sectional disc, cm
The diameter for the 11th age class inner growth ring of the cross-sectional disc, cm
head(stemdata)head(stemdata)
A dataframe containing the list of output variables and their description.
StemGrowthStemGrowth
A data frame with 10 variables:
The growth ring number of the disc at ground
The age class of a tree growths, year
The tree diameter at breast height, cm
The tree height, m
The tree stem volume, m3
The mean annual increment of diameter at breast height, cm
The mean annual increment of tree height, m
The mean annual increment of tree stem volume, m3
The current annual increment of diameter at breast height, cm
The current annual increment of tree height, m
The current annual increment of tree stem volume, m3
head(StemGrowth)head(StemGrowth)
A dataframe containing the list of output variables and their description.
volumeCarbonvolumeCarbon
A data frame with 9 variables:
The growth ring number of the disc at ground
The age class of a tree growths, year
The biomass conversion factor along age classes of a sampled tree, kg
The root-to-shoot ratio along age classes of a sampled tree, kg
The aboveground biomass of a sampled tree, kg
The belowground biomass of a sampled tree, kg
The total tree biomass of a sampled tree, kg
The aboveground carbon storage of a sampled tree, kg
The belowground carbon storage of a sampled tree, kg
The total tree carbon storage of a sampled tree, kg
head(volumeCarbon)head(volumeCarbon)
A dataset containing the list of input variables and their description. Note: If a user uses the StemAnalysis package to estimate a sampled tree carbon by volume model, a parameters dataset for the factors (BCF and RSR) should be provided. Owing the parameters of BCF and RSR vary among tree species, the users should input the parameters data for the correspondingly tree species
volumePardatavolumePardata
A data frame with 5 rows and 7 variables:
The line number
The tree diameter of breast height, cm
The tree biomass estimation factors including BCF and RSR
The parameter a in the estimation model of BCF (ln(BCF)=ln(a)+b×ln(DBH)+c×ln(H)) and RSR (ln(RSR)=ln(a)+b×ln(DBH)+c×ln(H))
The parameter b in the estimation model of BCF and RSR
The parameter c in the estimation model of BCF and RSR
The total tree carbon concentration, kg C kg-1
head(volumePardata)head(volumePardata)