Code and data underlying "[Controlling biases in targeted plant removal experiments]" by Sylvain Monteux, Gesche Blume-Werry, Konstantin Gavazov, Leah Kirchhoff, Eveline J. Krab, Signe Lett, Emily P. Pedersen, Maria Vaisanen, New Phytologist, 2023. This repository stores the entire analysis pipeline: statistical analyses and figure generation.
Code and data underlying "[Controlling biases in targeted plant removal experiments](https://doi.org/10.1111/nph.19386)" by Sylvain Monteux, Gesche Blume-Werry, Konstantin Gavazov, Leah Kirchhoff, Eveline J. Krab, Signe Lett, Emily P. 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.
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.
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Monteux, S., Blume-Werry, G., Gavazov, K., Kirchhoff, L., Krab, E.J., Lett, S., Pedersen, E.P., and Väisänen, M. (2023). Controlling for biases in targeted plant removal experiments. bioRxiv, 2023.08.22.554120. https://doi.org/10.1101/2023.08.22.554120
Monteux, S., Blume-Werry, G., Gavazov, K., Kirchhoff, L., Krab, E.J., Lett, S., Pedersen, E.P., and Väisänen, M. (2023). Controlling for biases in targeted plant removal experiments. bioRxiv, 2023.08.22.554120. https://doi.org/10.1101/2023.08.22.554120
Monteux, S., Blume-Werry, G., Gavazov, K., Kirchhoff, L., Krab, E.J., Lett, S., Pedersen, E.P., and Väisänen, M. (2023). Controlling for biases in targeted plant removal experiments. New Phytologist, Manuscript accepted for publication.
Monteux, S., Blume-Werry, G., Gavazov, K., Kirchhoff, L., Krab, E.J., Lett, S., Pedersen, E.P., and Väisänen, M. (2023). Controlling for biases in targeted plant removal experiments. New Phytologist. http://doi.org/10.1111/nph.19386
