pipeline.md

\newpage

% Description of the traits and tree growth data formatting for workshop on traits and competitive interactions

Introduction

This document describes the data structure and the main R functions available so far for the data formatting for the working group on traits and competition.

Structure of data for analysis

For the analysis we need for each ecoregion country (or big tropical plot) a list with three elements.

First element is a data.frame for individual tree data with columns

---

var numeric units description

---

obs.id 0 a unique identifier of observqtion (if multiple observation for a same tree)

tree.id 0 a unique identifier of each tree

sp 0 the species code

sp.name 0

cluster 0

plot 0 the plot code

ecocode 0 the ecoregion code (trying to merge similar
ecoregion to have ecoregion with enough
observation per ecoregion)

D 1 cm diameter growth

G 1 mm/yr the diameter growth rate

dead 1 a dummy variable 0 alive 1 dead

year 1 yr the number of year for the growth measurement

htot 1 m the height of the individual for the data base
for which it is availble to compute max height
per species

Lon 1 deg Longitude of the plot in WGS84

Lat 1 deg Latitude of teh plots in WGS84

perc.dead 1 the percentage of dead computed on each plot to exlude plot with perturbation (equal 1 for plot with known perturbation)

weights 1 /mm2 the weigths of the tree to have an estimation of basal area per m^2

census 1 0 the name of the year of the census 1

Second element is a data.frame competition index with columns

- $tree.id$ a unique identifier of each tree
- $ecocode$ the species code
- one column per species with the name as in the species code $sp$ in the previous the plot code
- $BATOT.COMPET$ the sum of the basal area of all species

Third element is a data.frame for the species traits data with columns

---

var numeric units description

---

sp 0 the species code used in other tables

Latin_name 0 the latin name of the species

Leaf.N.mean 1 mg/g Leaf Nitrogen per mass

Seed.mass.mean 1 mg seed mass

SLA.mean 1 mm2/mg specific leaf area

Wood.density.mean 1 mg/mm3 wood density

Max.height.mean 1 from NFI data I compute the 99% quantile in m and the same columns with ,sd, instead of ,mean, with either the mean sd within species if species mean or the mean sd with genus if genus mean because
no species data a dummy variable with true or
false if genus mean

Leaf.N.sd 1

Seed.mass.sd 1

SLA.sd 1

Wood.density.sd 1

Max.height.sd 1

Leaf.N.exp 1

Seed.mass.exp 1

SLA.exp 1

Wood.density.exp 1

Leaf.N.genus 1

Seed.mass.genus 1

SLA.genus 1

Wood.density.genus 1

Leaf.N.nobs 1

Seed.mass.nobs 1

SLA.nobs 1

Wood.density.nobs 1

and the same columns with $sd$ instead of $mean$ with either the mean sd within species if species mean or the mean sd with genus if genus mean because no species data a dummy variable with true or false if genus mean

Competition index

National forest inventory type data

We computes the sum of basal area (BA) per plot (including the weight of each tree to have a basal area in $m^2/ha$) total and per species without the BA of the target tree (see the R function BA.SP.FUN in the file format.function.R).

Large plot data

Need to compute the basal area (m^2/ha) per species in the neighborhood of each individuals in given radius R. The function BA.SP.FUN.XY in the file format.function.R should do that but not tested.

Traits data

The objective is to have a table with the species mean of the traits or the genus mean for the traits if no data available.

TRY data

• The TRY data is provided with one row for each variables measured on a single individuals (traits variable and non traits variables). The function fun.extract.try (in FUN.TRY.R) extract the traits variables and the non traits variables that we want to create a table with one row per individual (Observation.ID) and one column per traits or non traits variables.

• Then we compute for each species (and all its potential synonyms) the mean observation of each traits (in log10) without experimental data if possible or with experimental data if no data. If no data is available for a given species we compute the genus mean (and a dummy variable indicating that this is genus mean). The function also compute the traits sd. See function fun.species.traits . This function also exclude outlier based on the method used by Kattge et al 2011 (GCB) (see function fun.out.TF2).

• Then I have computed the mean sd within species (assuming that the within species sd is constant over all species).

• So far on the French data I have only list species potential synonyms self build but it would be great to either creates a list of potential synonyms from existing list or alternatively to match the TRY species and the forest inventory species on the same list to have teh same species.

Other data provided for each data

• Need to write a function to compute mean per species for each traits and decide if we use the same species sd for these data sets.

Ecoregions

For the NFI data we will divide the data set by regions with similar ecological conditions. This will allow to estimate the link between competitive interactions and traits within regions of similar conditions and see how the results vary (for instance in the US there is a large variability between the north and the south). This will allow to make comparison with large tropical plot more easy. Then this will help to have smaller data set to speed up the estimation. Please could you either provides a source of ecoregion with a GIS layer that we can use or better directly includes this variable in the data (at the plot level). Similarly in term of climatic variables I was planning to use the best variables available for each data rather than a global data base of lower quality. Could you either give the link of such a data set or better directly do get the variables for each plot. I think that we do not have any ecoregion information that was directly measured in the SFI data. However, we have joint each SFI plot with Olson ecoregions.

Progress

---

Data.name Demographic.data

---

BCI Large 50ha plot with semi
spatial localisation of tree
with multiple census

Fushan Large plot with spatial
localisation of tree with
multiple census

Luquillo Large plot with spatial
localisation of tree with
multiple census

La Chonta Large plot with spatial
localisation of tree with
multiple census

Paracou Large plot with spatial
localisation of tree with
multiple census

Mbaiki Large plot with spatial
localisation of tree with
multiple census

FIA Forest inventory plots in the US Formatting M. Vanderwel to be done

Canada Forest inventory plots in
Canada Formatting John
Caspersen to be done

France Forest inventory plots

Spain Forest inventory plots check
with M Zaval formatting
probably done

Sweden Forest inventory plots.
Formatting to be discuss

Switzerland Forest inventory plots.
Formatting to be discuss

New Zealand Forest inventory plots.
Formatting to be discuss
(Coomes sub sample)

Autralia NSW Kooyman plots Several medium size plots.
Formatting in progress

CSIRO plots Several medium size plots.
Formatting in progress

---

Table: Table continues below (continued below)

---

Demo.data.availability Traits.data

---

ok Available with data

ok Available with data

Need to contact Zimmerman Available with data

no Available with data

ok Available with data

Waite Available with data

ok TRY

ok TRY

ok TRY

ok TRY

ok TRY

ok TRY

ok Available with data

ok Available with data

Waite Available with data

Table: Table continues below

---

Traits.data.vailability Abiotic.variables

---

ok topography and/or soil

ok topography and/or soil

Need to contact Swenson topography and/or soil

ok topography and/or soil

ok topography and/or soil

Waite topography and/or soil

ok climate

ok climate

ok climate

ok climate

ok climate

ok climate

ok climate

ok climate

Waite climate

---

Progress.in.formatting.the.data TODO

---

demo data ok compute CI adn process traits

demo data ok compute CI adn process traits

NO send email

NO

demo and competition index ok Traits ask Ghislain to do

Waite ghislain

Done Need to add max height from
FIA MISSING CENSUS VARIABLE

Need to pupdate with new code waite new data with Quebec
per ecoregion MISSING CENSUS VARIABLE

Done rewrite to format per
ecoregion

Demo done Competition index and TRY

demo ok missing TreeID and mortality

demo ok missing mortality, ecoregion

demo ok

demo and compeitition index Traits ask Ghislain to do
ok

Waite daniel send email with traits