https://github.com/trevorkeenan/gpp-co2
Code to reproduce the analysis and figures in 'A constraint on historic growth in global photosynthesis due to increasing CO2' Keenan et al. 2021. Nature https://www.nature.com/articles/s41586-021-04096-9
https://github.com/trevorkeenan/gpp-co2
co2 fertilization gpp land-sink photosynthesis
Last synced: 5 months ago
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Code to reproduce the analysis and figures in 'A constraint on historic growth in global photosynthesis due to increasing CO2' Keenan et al. 2021. Nature https://www.nature.com/articles/s41586-021-04096-9
- Host: GitHub
- URL: https://github.com/trevorkeenan/gpp-co2
- Owner: trevorkeenan
- Created: 2021-06-15T20:47:35.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2023-10-17T16:38:42.000Z (over 2 years ago)
- Last Synced: 2024-01-27T23:38:33.537Z (over 2 years ago)
- Topics: co2, fertilization, gpp, land-sink, photosynthesis
- Homepage:
- Size: 134 KB
- Stars: 6
- Watchers: 2
- Forks: 8
- Open Issues: 0
-
Metadata Files:
- Readme: ReadME.md
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README
# GPP-CO2
## Overview
This repository contains analysis and plotting scripts to reproduce the emergent constraint results presented in:
Keenan et al. 2021: A constraint on historic growth in global photosynthesis due to increasing CO2.
Nature - https://www.nature.com/articles/s41586-021-04096-9
This paper was retracted in early 2022 due to an issue that affect the results presented in Figure 1. See the retraction notice here:
https://www.nature.com/articles/s41586-022-04869-w
We have removed the underlying code from the repository to avoid proliferation of the error in other analyses, but leave the description below for anyone wishing to dig deeper.
## depreciated text:
Full information on the methods used in this study are attached to this paper and are available
online at the link provided above; this includes information about datasets used, as well as the motivation and reasoning
behind the analysis.
The scripts, written in Matlab, are:
## A. varianceNormalization.m
This script derives the relationship between Sland and Beta^{GPP}, and performs variance normalization
to extract the partial response.
## B. calc_EC_andPlot.m
This code, called by 'varianceNormalization.m' uses the emergent constraint between
the partial response of Sland to Beta^{GPP} across models to derive the constrained Beta^{GPP}
## Running the code
Running A_varianceNormalization.m will produce the following figures reported in Keenan et al. 2021: \
*Figure 1a-d \
*ED Figure 1 \
*ED Figure 2 \
*ED Figure 3 \
*ED Figure 6
A_varianceNormalization.m calls B_calc_EC_andPlot.m
## Folder structure and contents
./figures/emergent contains the figures produced
if the save_figures flag is set to 1.
./TRENDYv6_derived contains derived output from the TRENDY model simulations.
TRENDY model simulations are not publically available but can be obtained through request to Prof. Sitch (S.A.Sitch@exeter.ac.uk)
./dataIntermediates contains output from the scripts included here,
extracted from the data contained in ./TRENDYv6_derived
./functions contains plotting code and the prediction error code.