## Allometries: Tree species growth, biomass and crown data for detailed allometries

#### Usage Rights

This data is Private.

Brezzi Matteo, Schmid Bernhard, Baruffol Martin

#### Dataset Abstract

In order to get tree growth curves we estabilshed an allometry campaign during which we carefully measured, subsampled, dried and then re-constructed the biomass of 154 trees belonging to 8 species. The sampling is done to allows estimation of biomasses for different compartments in order to see if the different tree species have different growth pattern. The neighbours are as well measured to look at a possible influence of competition on tree growth and tree biomass compartimentation

#### Dataset Design

Trees were randomly chosen with the condition to look healthy and to have a particular DBH: because trees evenly located along the size range are needed to produce accurate growth curve estimate.General point:Every biomass or leaf area estimation come from an independent estimation and then has is own Standard Deviation. All the biomasses have been estimated SEPARATELY for each species in order to preserve specific differences (no pooling toward the grand mean). In all the models, the individual trees were considered as a random factor.The estimates and their standard deviation come from the posteriori distribution drawn out of the Markov chain Monte Carlo (three chains here). Each model was set up with 500'000 iterations from which the first 300'000 were discarded. Among the 200'000 valid iterations, one over twenty was kept in order to avoid the correlation between two consecutive estimates. So, each biomass estimate is the MEAN of the results given by the MCMC. The following variable is the SD of this mean (= "_sd").The model fit a value for each segment or each branch considered. The sum of them is done within the model: the final estimate gets a standard deviation that is right in confront with error propagation.The errors we provide are MODEL ERRORS. Thus they come from the variability around the estimates. Small trees for which every branch was measured in the lab have NO model error: the sd = 0.Bayesian estimation allows to include prior knowledge into the model: the priors. Here, we never used any informative priors, which means that our estimates come only from our own data.Branch biomass estimates:

Branches are "branches" in our definition when their diameter is equal or below 3 cm of diameter. Estimates coming from the sampled branches are the total branch biomass, the branch wood biomass and the branch leaf biomass. . For each branch, the total fresh wood weight ant the total fresh leaf weight were measured, subsamples were dried. From the dry mass of the subsamples the total dry mass of the leaves, wood and total branch were gathered.Usually, we have 6 branches / tree which have the real data measured (real branch number can be seen in the "branch_nb" variable). As descriptor variable we have their diameter and their position in the crown.

We use those predictors to predict the biomass of all the branches measured in vivo on the tree.For the branch biomass estimates, the model has this form:biomass estimate[i] ~ dnorm(yhat[i],tau[i])

yhat[i] they are the random factors.

b1[ind[i]] ~ dnorm(b1_mu, b1_tau) --> b1_mu is the average b1 estimated by the model with a precision b1_tau

b2[ind[i]] ~ dnorm(b2_mu, b2_tau) --> b2_mu is the average b2 estimated by the model with a precision b2_tauA graphical inspection showed an increase of variability with increasing branch diameter, that's why here the sd is modelized as a linear function of the diameter.An idea of the amount of material really measured versus how much is predicted can be seen with the following variables:

"field_bra_tot_weig" gives the real fresh weight of the branches, then "br_kg" is the wheight of the branches brought back to the lab. "p.branch.samp" is the precentage of branches that were brought back to the lab; as espected, the bigger the tree the smaller this percentage. "branch_nb" is the number of branches brought back to the lab.Branch leaf area estimates:

The leaf area estimates are based on the same branches than the branch biomass estimates.To get the leaf area estimates, two models were run simultaneously; one to estimate the branch leaf biomass and one to estimate the leaf area/ gr of leaf for this particular branch. Then, these two estimates are multiplied within the model (right error at the branch level) and the resulting leaf area summed for each tree (right error at the tree level).The leaf biomass estimates are done exactly as above, so we don't show it here again. A subset of leaves were scanned and dried for each branch. From this we obtain a mean area/weight at the branch level that can be modeled.We did not find any pattern for the leaf area / gr of leave with the branch diameter, so this variable does not appear in our model.

In contrast, leaves tend to have a lower surface / gr when being situated higher in the crown, so "thrd" is in our model. As before, the individuals are the random factor.area[i]~dnorm(yhatar[i],tauar)

yhatar[i]

#### Spatial Extent

According to Google Map, the site is N 29.113494, E 118.008817. The forest is an exploited plantation with about 80% of the trees being Cunninghamia lanceolata. The 20% remaining is naturally present there and comes from the surrounding natural forest. The site is situated at the end of a small valley with relatively strong slope

#### Temporal Extent

Time needed to sample the 154 trees

#### Taxonomic Extent

154 trees belonging to 8 different species (n, DBH size range in cm): 2 coniferous: Pinus massoniana (19, 2.9 – 23.2) and Cunninghamia lanceolata (17, 1 – 17.7), 3 deciduous: Liquidambar formosana (15, 2.6 – 37.5), Sassafras tzumu (20, 5.1 – 27.7) and Alniphyllum fortunei (21, 2.4 – 18.7), 3 evergreens: Castanopsis fargesi (25, 2.5 – 27.3), Castanopsis sclerophylla (16, 2.7 – 16.5) and Schima superba (21, 1.2 – 23.1).

#### Data Analysis

Exponential curves according to species and other covariates; This data are not "raw", to get the biomasses from the raw data one needs to many steps, so here we provide the processed data and the methods required to get them

### Data columns available in the raw data part of this dataset

*Data group: Tree identifier for harvested trees*

*Keywords: tree, object*

Values |
---|

101 |

105 |

107 |

104 |

103 |

*Baruffol, M.*also contributed to this column.

*Data group: Helper*

Values |
---|

alf |

cas |

caf |

cul |

lif |

*Data group: Scientific plant species name*

*Keywords: species, taxon, allometries*

Values |
---|

Cunninghamia lanceolata |

Castanopsis fargesii |

Alniphyllum fortunei |

Castanopsis sclerophylla |

Liquidambar formosana |

*Unit: Degree*

*Data group: Inclination*

*Keywords: inclination, slope*

Values |
---|

10 |

16 |

12 |

13 |

14 |

*Baruffol, M.*also contributed to this column.

*Unit: Degree*

*Data group: Aspect*

*Keywords: exposition, aspect*

Values |
---|

0 |

190 |

10 |

20 |

197 |

*Baruffol, M.*also contributed to this column.

*Unit: none*

*Data group: Curvature*

*Keywords: curvature*

Values |
---|

convex |

slope |

concave |

*Baruffol, M.*also contributed to this column.

*Unit: Centimeters*

*Data group: Diameter at breast height*

*Keywords: dbh, size*

Values |
---|

1 |

10.1 |

10.3 |

10.2 |

10.4 |

*Unit: Meters*

*Data group: Plant height*

*Keywords: height, size*

Values |
---|

10.3 |

10.7 |

10.4 |

10.6 |

10.5 |

*Baruffol, M.*also contributed to this column.

*Unit: Meters*

*Data group: Crown architecture*

*Keywords: crown*

Values |
---|

0.8 |

1 |

0.9 |

0.4 |

0.1 |

*Baruffol, M.*also contributed to this column.

*Unit: Centimeters*

*Data group: Basal diameter*

*Keywords: basal diameter*

Values |
---|

10 |

10.9 |

10.7 |

10.3 |

11 |

*Baruffol, M.*also contributed to this column.

*Unit: Centimeters*

*Data group: Basal diameter*

*Keywords: basal diameter*

Values |
---|

10.7 |

10.4 |

11 |

10.1 |

10.9 |

*Baruffol, M.*also contributed to this column.

*Unit: none*

*Data group: Tree social status*

*Keywords: social status*

Values |
---|

5 |

2 |

3 |

4 |

*Baruffol, M.*also contributed to this column.

*Unit: Meters*

*Data group: Crown architecture*

*Keywords: crown*

Values |
---|

0.2 |

0 |

0.3 |

-0.3 |

0.4 |

*Baruffol, M.*also contributed to this column.

*Unit: Meters*

*Data group: Crown architecture*

*Keywords: crown*

Values |
---|

0.4 |

0.5 |

-0.5 |

0.6 |

0.2 |

*Baruffol, M.*also contributed to this column.

*Unit: Meters*

*Data group: Crown architecture*

*Keywords: crown*

Values |
---|

0.1 |

0.2 |

0.05 |

-0.1 |

0.15 |

*Baruffol, M.*also contributed to this column.

*Unit: Meters*

*Data group: Crown architecture*

*Keywords: crown*

Values |
---|

0.8 |

0.7 |

0.6 |

0 |

0.4 |

*Baruffol, M.*also contributed to this column.

*Unit: Kilograms*

*Data group: Above and below ground biomass measurement*

*Keywords: response variable, biomass*

Values |
---|

0.513031193333333 |

0.365365278333333 |

0.183229019666667 |

1.02266464333333 |

1.00702335333333 |

*Baruffol, M.*also contributed to this column.

*Unit: Kilograms*

*Data group: Above and below ground biomass measurement*

*Keywords: biomass*

Values |
---|

0.0561967243493172 |

0.0233461183333973 |

0.0381755880348408 |

0.0548726710659948 |

0.0365129535044636 |

*Baruffol, M.*also contributed to this column.

*Unit: Kilograms*

*Data group: Above and below ground biomass measurement*

*Keywords: biomass*

Values |
---|

0.183229019666667 |

0.513031193333333 |

100.941464333333 |

0.98988923 |

0.365365278333333 |

*Baruffol, M.*also contributed to this column.

*Unit: Kilograms*

*Data group: Above and below ground biomass measurement*

*Keywords: biomass*

Values |
---|

0.0548726710659948 |

0.0435399993116495 |

0.036764732970587 |

0.0527099073814094 |

0.0233461183333973 |

*Baruffol, M.*also contributed to this column.

*Unit: Kilograms*

*Data group: Above and below ground biomass measurement*

*Keywords: wood, dry weight, biomass*

Values |
---|

0.131414159833333 |

0.392902148333333 |

0.933126776666667 |

0.244039089016667 |

0.835006626666667 |

*Baruffol, M.*also contributed to this column.

*Unit: Kilograms*

*Data group: Above and below ground biomass measurement*

*Keywords: dry weight, biomass*

Values |
---|

0.0382163692981812 |

0.043074155425042 |

0.0401769113665396 |

0.0370585212769948 |

0.0146875639726168 |

*Baruffol, M.*also contributed to this column.

*Unit: Kilograms*

*Data group: Above and below ground biomass measurement*

*Keywords: dry weight, leaf, biomass*

Values |
---|

0.0790891907558767 |

0.0488727315133333 |

0.0213221541079407 |

0.0625853693033333 |

0.0247012378983333 |

*Baruffol, M.*also contributed to this column.

*Unit: Kilograms*

*Data group: Above and below ground biomass measurement*

*Keywords: leaf, biomass*

Values |
---|

0.0141229249980643 |

0.0171096660056617 |

0 |

0.0207986236502255 |

0.00948064263379279 |

*Baruffol, M.*also contributed to this column.

*Unit: CentimetersSquared*

*Data group: Leaf area*

*Keywords: leaf*

Values |
---|

1040183.77 |

105339.231666667 |

113791.455 |

101954.043333333 |

106295.3635 |

*Baruffol, M.*also contributed to this column.

*Unit: CentimetersSquared*

*Data group: Leaf area*

*Keywords: leaf*

Values |
---|

0 |

10139.1876292698 |

10056.9839574142 |

10024.2631107316 |

102552.884454243 |

*Baruffol, M.*also contributed to this column.

*Unit: Kilograms*

*Data group: Above and below ground biomass measurement*

*Keywords: biomass*

Values |
---|

0.0017140617 |

0.0018272328 |

0 |

0.002139311 |

0.00190497996666667 |

*Baruffol, M.*also contributed to this column.

*Unit: Kilograms*

*Data group: Above and below ground biomass measurement*

*Keywords: biomass*

Values |
---|

0.000195800381588775 |

0.000291719474569235 |

0 |

0.00013547046553382 |

0.00013009448584222 |

*Baruffol, M.*also contributed to this column.

*Unit: Kilograms*

*Data group: Above and below ground biomass measurement*

*Keywords: biomass*

Values |
---|

0.02116 |

0 |

0.02097 |

0.00349 |

0.00856 |

*Baruffol, M.*also contributed to this column.

*Unit: dimentionless*

*Data group: Sample size*

Values |
---|

12 |

10 |

11 |

0 |

13 |

*Baruffol, M.*also contributed to this column.

*Unit: dimentionless*

*Data group: Helper*

Values |
---|

0.731975089051266 |

0.9590675863808 |

0.674124248139835 |

1.0494343391189 |

0.827611823934838 |

*Baruffol, M.*also contributed to this column.

*Unit: Kilograms*

*Data group: Above and below ground biomass measurement*

*Keywords: biomass, branch*

Values |
---|

0.62 |

0.53 |

0.385 |

0.35 |

0.69 |

*Baruffol, M.*also contributed to this column.

*Unit: Kilograms*

*Data group: Above and below ground biomass measurement*

*Keywords: biomass, branch*

Values |
---|

0.38696 |

0.22789 |

0.34703 |

0.28111 |

0.32038 |

*Baruffol, M.*also contributed to this column.

*Unit: dimentionless*

*Data group: Sample size*

Values |
---|

1 |

5 |

4 |

2 |

3 |

*Baruffol, M.*also contributed to this column.

*Unit: dimentionless*

*Data group: Helper*

Values |
---|

10.0240708812261 |

11.9072774717309 |

10.7740208408193 |

11.9609736842105 |

100 |

*Baruffol, M.*also contributed to this column.

### Keywords

aboveground biomass, allometries, aspect, basal diameter, biomass, branch, crown, crown diameter, curvature, dbh, dry weight, exposition, height, inclination, leaf, leaf area, object, response variable, size, slope, social status, species, taxon, tree, tree height, wood### Last update

2017-01-26 11:01