# Data analysis and figure generation for a gradient design to account for biases in plant removal experiments
## Overview
Code and data underlying "[Controlling biases in targeted plant removal experiments](https://doi.to-do)" by Sylvain Monteux, Gesche Blume-Werry, Konstantin Gavazov, Leah K. Kirchhoff, Eveline J. Krab, Signe Lett, Emily Pickering Pedersen, Maria Vaisanen, New Phytologist, 2023. This repository stores the entire analysis pipeline: statistical analyses and figure generation.
The experimental design consists in 5 spatially-replicated blocks containing each one of the following treatments: undisturbed control (CTL), targeted removal of ericoid- (-ERM), ecto- (-ECM) or both ericoid- and ecto-mycorrhizal plants (-ECM/-ERM) in a subarctic tundra heath at the forest-tundra ecotone in northern Sweden. A gradient of indiscriminate biomass removal based on area was implemented alongside the targeted removal treatments to account for biases induced by the removal of plant biomass. The repository describes how the data was analysed based on results observed in the gradient, and depending on that whether the response variables in the treatment plots were adjusted for potential confounding effects.
We show how non-specific biomass removal can result in false discoveries or false negatives based on data obtained within this experiment.
In short, the scripts in this repository:
- Create the conceptual Figure 1
- Assess the significance of relationships between response variables and biomass removed in the gradient (gradient regression)
- When these gradient regressions are significant:
- Adjust response variables to account for the confounding effect of removed biomass
- Simulate variation to assess how variability in the gradient regression
- Analyze the treatment effects on the observed, adjusted or simulated data
- Create Figure 4 to illustrate the procedure and its effect on three response variables
- Create Supplementary Figures S1 and S2
## Prerequisites
R scripts were tested on R4.1.3 on Windows 10 and R4.3.1 on Linux Mint 21.2.
No intensive resource use.
## Language
R.
## File description
- Files not contained in `code` or `data` are not necessary to initiate the analysis and are provided for record. Such files will be created and/or overwritten as the scripts are executed.
-`data/`
-`harmonized_data.csv` - Contains sample information, biomass removed and response variables
-`Manuscript_figures.Rmd` and `Manuscript_figures.html` - R-markdown and HTML output of the figure-generation script
-`sessionInfo.txt` - R environment file
-`LICENCE` - Licence file
-`./README.md` - This document
## Citation
Monteux S (2023) Data analysis for adjusting effects of biomass removal in a mycorrhizal association-based plant removal experiment. Software version 1.0.0. Bolin Centre Code Repository. <https://doi.org/10.57669/monteux-2023-plant-removal-1.0.0>
## References
Monteux S., Blume-Werry G., Gavazov K., Kirchhoff L.K., Krab E.J., Lett S., Pickering Pedersen E. and Vaisanen M., Controlling for biases in targeted plant removal experiments, journaljournaljournal, vol nr pp. nr. <https://doi.org/placeholder>
## Comments
### Acknowledgements
We thank the Swedish Polar Research Secretariat and SITES for the logistical support of the work done at the Abisko Scientific Research Station.
This study was financially supported by the Bolin Centre for Climate Research, Helge Ax:son Johnsons stiftelse and Arcum (SM); Swiss Polar Institute Exploratory Grant (SPIEG-2020-001) and Swiss National Science Foundation (grant PZ00P2_174047) (KG); Waldemar von Frenckells stiftelse, Oskar Oflunds stiftelse, the Osk. Huttunen Foundation and The University of Oulu & The Academy of Finland PROFI4 (Grant 318930) (MV).
We thank James T. Weedon for critical input on statistical data processing, Anika Mayr for obtaining and processing data on Betula nana growth and isotopic nitrogen content, and Sonia Meller for lending us the SEAR scanner. We also thank Anna Miettinen, Elisa Jung, Henrike Lange, Janne Welling, Lorenzo Masini, Luca Dettmers, Margaux Chadanson, Paul Schulz and Yannick Bernard for their help in the maintenance of the experiment and data collection.
## Creators
Sylvain Monteux
## Contact information
Sylvain Monteux
Department of Environmental Science, Stockholm University, SE-106 91 Stockholm, Sweden
sylvain.monteux [at] aces.su.se
UiT The Arctic University Museum of Norway, NO-9013 Tromsø, Norway
sylvain.monteux [at] uit.no
## Publisher
Bolin Centre Code Repository
## Version
1.0.0
## Project URL
<https://abisko-lter.weebly.com/>
## DOI
to-do
## License
Distributed under the GNU General Public License v3.0. See LICENSE text for more information.
## Publication date
placeholder
# Data analysis and figure generation for a gradient design to account for biases in plant removal experiments
## Overview
Code and data underlying "[Controlling biases in targeted plant removal experiments](https://doi.to-do)" by Sylvain Monteux, Gesche Blume-Werry, Konstantin Gavazov, Leah K. Kirchhoff, Eveline J. Krab, Signe Lett, Emily Pickering Pedersen, Maria Vaisanen, New Phytologist, 2023. This repository stores the entire analysis pipeline: statistical analyses and figure generation.
The experimental design consists in 5 spatially-replicated blocks containing each one of the following treatments: undisturbed control (CTL), targeted removal of ericoid- (-ERM), ecto- (-ECM) or both ericoid- and ecto-mycorrhizal plants (-ECM/-ERM) in a subarctic tundra heath at the forest-tundra ecotone in northern Sweden. A gradient of indiscriminate biomass removal based on area was implemented alongside the targeted removal treatments to account for biases induced by the removal of plant biomass. The repository describes how the data was analysed based on results observed in the gradient, and depending on that whether the response variables in the treatment plots were adjusted for potential confounding effects.
We show how non-specific biomass removal can result in false discoveries or false negatives based on data obtained within this experiment.
In short, the scripts in this repository:
- Create the conceptual Figure 1
- Assess the significance of relationships between response variables and biomass removed in the gradient (gradient regression)
- When these gradient regressions are significant:
- Adjust response variables to account for the confounding effect of removed biomass
- Simulate variation to assess how variability in the gradient regression
- Analyze the treatment effects on the observed, adjusted or simulated data
- Create Figure 4 to illustrate the procedure and its effect on three response variables
- Create Supplementary Figures S1 and S2
## Prerequisites
R scripts were tested on R4.2.3 on Windows 10 and R4.3.1 on Linux Mint 21.2.
No intensive resource use.
## Language
R.
## File description
- Files not contained in `code` or `data` are not necessary to initiate the analysis and are provided for record. Such files will be created and/or overwritten as the scripts are executed.
-`code/`
-`Manuscript_figures.Rmd` and `Manuscript_figures.html` - R-markdown and HTML output of the figure-generation script
-`data/`
-`harmonized_data.csv` - Contains sample information, biomass removed and response variables
Monteux S (2023) Data analysis for adjusting effects of biomass removal in a mycorrhizal association-based plant removal experiment. Software version 1.0.0. Bolin Centre Code Repository. <https://doi.org/10.57669/monteux-2023-plant-removal-1.0.0>
## References
Monteux S., Blume-Werry G., Gavazov K., Kirchhoff L.K., Krab E.J., Lett S., Pickering Pedersen E. and Vaisanen M., Controlling for biases in targeted plant removal experiments, bioRxiv [preprint], 2023.08.22.554120. <https://doi.org/10.1101/2023.08.22.554120>
Monteux S., Blume-Werry G., Gavazov K., Kirchhoff L.K., Krab E.J., Lett S., Pickering Pedersen E. and Vaisanen M., Controlling for biases in targeted plant removal experiments, New Phytologist, vol nr pp. nr. <https://doi.org/placeholder>
## Comments
### Acknowledgements
We thank the Swedish Polar Research Secretariat and SITES for the logistical support of the work done at the Abisko Scientific Research Station.
This study was financially supported by the Bolin Centre for Climate Research, Helge Ax:son Johnsons stiftelse and Arcum (SM); Swiss Polar Institute Exploratory Grant (SPIEG-2020-001) and Swiss National Science Foundation (grant PZ00P2_174047) (KG); Waldemar von Frenckells stiftelse, Oskar Oflunds stiftelse, the Osk. Huttunen Foundation and The University of Oulu & The Academy of Finland PROFI4 (Grant 318930) (MV).
We thank James T. Weedon for critical input on statistical data processing, Anika Mayr for obtaining and processing data on Betula nana growth and isotopic nitrogen content, and Sonia Meller for lending us the SEAR scanner. We also thank Anna Miettinen, Elisa Jung, Henrike Lange, Janne Welling, Lorenzo Masini, Luca Dettmers, Margaux Chadanson, Paul Schulz and Yannick Bernard for their help in the maintenance of the experiment and data collection.
## Creators
Sylvain Monteux
## Contact information
Sylvain Monteux
Department of Environmental Science, Stockholm University, SE-106 91 Stockholm, Sweden
sylvain.monteux [at] aces.su.se
UiT The Arctic University Museum of Norway, NO-9013 Tromsø, Norway
sylvain.monteux [at] uit.no
## Publisher
Bolin Centre Code Repository
## Version
1.0.0
## Project URL
<https://abisko-lter.weebly.com/>
## DOI
to-do
## License
Distributed under the GNU General Public License v3.0. See LICENSE text for more information.
