plantphys / gsti Goto Github PK

We need to replace the install instructions/pointers to the new location of the spectratrait pacakge i n the PlantPhys organization

Ask dataset to [email protected]

(Qian, X., Zhang, Y., Liu, L., & Du, S. (2019). Exploring the potential of leaf reflectance spectra for retrieving the leaf maximum carboxylation rate. International Journal of Remote Sensing, 40(14), 5411-5428.)

Global Vcmax isnt very descriptive, doesnt really convey what this is, and doesnt contain spec.

Better describe the data curation (how to do the QAQC of the A-Ci curves)
Add the dependencies (package here, readxl, spectratrait, ..)
Add a how-to-start section with emails to contact
Take the example of the spectratrait package.

0_Import_transform_original_ACi_data

Some ideas for providing objective definitions:
https://www.nature.com/articles/sdata2018214

https://www.nature.com/articles/sdata2018214/figures/1

Biome defs by Olsson: https://github.com/TESTgroup-BNL/Global_Vcmax/blob/main/Vignettes/Biomes.csv

Köppen: https://en.wikipedia.org/wiki/K%C3%B6ppen_climate_classification

Right now the site description is in the dataset description. It would be better to separate the two and have only the citations, acknowledgments, authors, DOI, and article info ... in the dataset description. All the site information should move into a site info csv with a shortname. The plant description should include the site and also the type of species and the type of environment (pot, glasshouse, natural or managed).

I am considering making this repository independent from the package LeafGasExchange. Basically, we just need a few functions from the package, we don't need the leaf energy budget functions, the canopy scaling functions etc.. which are quite heavy and depend on other packages. What do you think @serbinsh Shawn? I can also ask Gilles Le Moguédec to make the fitting procedure more "professional".

Should we convert the HOWTOs to a wiki instead of a vignette? They arent a traditional code execution vignette and more instructional

Data curated and processed

I took this dataset from ecosis: https://ecosis.org/package/hyperspectral-leaf-reflectance--biochemistry--and-physiology-of-droughted-and-watered-crops

@serbinsh or @regnans could you check if the units given for "Elemental_N" are correct? In the "readme_data_descriptions.txt" it is written that it is g.m-2 so this would be the nitrogen content per surface area, but given the column name this could be the Nmass (per dry weight). Maybe I am overinterpreting here.

Long term goal

0_Import_transform_original_ACi_data

The link to the PLSR example (first section, just above References) returns 404 error.

0_Import_transform_original_ACi_data

Here is some text for the README. Edit as required. (links not formatted)

The project utilizes the data and metadata formatting recommendations presented in the "Leaf-level gas exchange data and metadata reporting format" (Ely et al, 2021). Data contributors are welcome to submit metadata that describes data collection protocols using the methods metadata template (https://github.com/ess-dive-community/essdive-leaf-gas-exchange/blob/master/templates/methodsMetadataTemplate.xlsx).

Ely KS, Rogers A, Agarwal DA, Ainsworth EA, Albert LP, Ali A, et al. A reporting format for leaf-level gas exchange data and metadata. Ecol Inform. 2021;61: 101232. doi:10.1016/j.ecoinf.2021.101232

Put data on ecosis

For a start, I used FATES photosynthesis model and parameters. Given the more mechanistic nature of the Johnson Field and Berry C3 model, we could decide to implement it as well so our results are more future proof.

Johnson, J.E., Field, C.B. & Berry, J.A. The limiting factors and regulatory processes that control the environmental responses of C3, C3–C4 intermediate, and C4 photosynthesis. Oecologia (2021). https://doi.org/10.1007/s00442-021-05062-y

Need a list of R dependencies and instructions for working through the steps of the data curation workflow. Perhaps create a small example dataset to use to demonstrate the steps?

A template for this: https://github.com/bpbond/cosore

@serbinsh DO you have the raw data for this one? https://ecosis.org/package/uw-bnl-nasa-hyspiri-airborne-campaign-leaf-and-canopy-spectra-and-trait-data

We should be using file.path() NOT paste and assuming / or \ in file paths

@serbinsh Can you check if the data are the good ones? I found the raw data in an old slack conversation, I have put them on the dataset folder Serbin_et_al_2012.

In addition, on ecosis there are two datasets : https://ecosis.org/package/2008-university-of-wisconsin-biotron-fresh-leaf-spectra-and-gas-exchange-leaf-traits

and

https://ecosis.org/package/leaf-spectral-reflectance-and-vcmax-measurements-for-tree-and-crop-species-collected-in-wisconsin

Can you tell me if the two datasets are distinct? If you have the raw data I ll do something with it

Added by Peng

I think we want to simplify the landing page model stats and info to include a more concise summary. We can add a new page to link to with more detailed info but at the moment the layout is a little messy plus the long species table stretches the page and is only going to get longer. Suggest maybe we do something like a genus table or higher level summary on the main landing page, with a map a spectra figure and a current model stats/fit figure layed out a bit more cleanly below the info

0_Import_transform_original_ACi_data

I stopped at step 3, file: 3_Import_transform_reflectance.R

I successfully imported the reflectance but this is the raw data, not interpolated and with an overlap at some wavelengths. The Reflectance needs to be interpolated and jump corrected.

If @serbinsh or @DavidsonKen if you feel inspired and want to do it, be my guest!

Lets not dump our auto fitting outputs to the main github folder, instead lets have the auto code put the outputs in an ./Outputs folder

haozhu233/kableExtra#186

@JulienLamour I am trying to fix the LFS issues and the repo but there are some strange issues in some files. eg. .

library(LeafGasExchange)
library(spectratrait)
library(here)
path=here()
setwd(paste(path,'/Datasets/Albert_et_al_2018',sep=''))
spectra=read.csv('Copy of Wu et al. 2019 spectra brazil.csv')
load('2_Result_ACi_fitting.Rdata',verbose=TRUE)

in Albert et al. 2018 which seems like an error and I also dont see that data, unless its Wu et al. 2019 spectra panama in Wu et al?

Also we should not have spaces in any filenames

Can you let me know if things are missing? I am trying to get the repo back into working shape so we can share it.

Here is how I was doing this for my ngee paper: https://github.com/serbinsh/SSerbin_NGEEArctic_Spectra_Trait/blob/main/R_scripts/Curate_datasets/Curate_leaf_gasex_datasets.R

But this is using the data fitted for the studies, I think you may want to fit again with the raw data

Hey Shawn @serbinsh ,

As you know, to start I used the Rdata format as intermediate outputs of the pipeline for each dataset. Before starting to curate everything in a hopefully final and stable state, maybe we should consider using .csv instead. What do you think?

0_Import_transform_original_ACi_data

Ask for data (Alpine forest in Japan) : Jin, J., Arief Pratama, B., & Wang, Q. (2020). Tracing Leaf Photosynthetic Parameters Using Hyperspectral Indices in an Alpine Deciduous Forest. Remote Sensing, 12(7), 1124. [email protected], [email protected]

@JulienLamour FYI - some of the new datasets have issues with their spectra that stem from the use of ASD spectrometers and/or those that dont provide "jump corrected" spectra. You can see below the spectral edges/discontinuities that need to be fixed or removed from our database otherwise they will artificially impact the accuracy of our fits and throw off our model. These spectral issues are not something we should embed in our models and are things that should be corrected by the data provider and / or using R packages that process spectral data

For example in my most recent look at the data we now have specta issues

The easiest thing to do right now is drop any new data with these issues and later on figure out how to automate the detection of issues like this or others like erroneous Vcmax values

0_Ask his dataset

https://github.com/TESTgroup-BNL/Global_Vcmax/blob/main/Contacts%20and%20datasets.docx

We need to make this a TODO list etc or a issue where we can add to it and easily read. OR we could covert it to another document that can be edited / viewed here in git like a .txt

For example rgeos is no longer availible but a dependency in Datasets_Map_and_resume.R

From our meeting, I agree that we should add the ability to include dark-adapted Rdark datasets.
However, when reading Burnett et al. 2019 and De Kauwe et al. 2016 I see that the one-point method was tested using a Rday (estimated from A_Ci curve in both method). From what I remember, Rday estimated from A-Ci curve is very different from Rdark. So I am not sure how relevant it is to add a Rdark option in the one point method and if that could bias Vcmax estimates. Any thought? In all cases I will include a Rdark description for people who want to include dark respiration measurement independently from the one point method.

Another agriculture dataset but still useful to compile

However we need either the Tleaf data per sample OR better yet the raw A-Ci data to refit and harmonize

Need to fill the spectrometer info as well as the leaf clip in file 3_Import_transform_Reflectance.R

@JulienLamour we should not be blanket saving all .csv files as LFS, as this then also includes small files like "Description.csv" files. This is creating extra overhead issues that make code management harder

I suggest two options: 1) a separate data repo specific to this effort that is used to store the datasets or 2) change the Description files from csv to txt so they arent included in the LFS. Or alternatively, we have to manually curate each required LFS file

We could use the Kumarathunge et al. 2019 dependence. That would necessitate to store the mean air temperature during the growth season for each dataset.

Ask the dataset