The fortedata R package: open-science datasets from a manipulative experiment testing forest resilience
Environmental sciences
0106 biological sciences
QE1-996.5
13. Climate action
GE1-350
Geology
15. Life on land
01 natural sciences
DOI:
10.5194/essd-13-943-2021
Publication Date:
2021-03-09T13:22:50Z
AUTHORS (19)
ABSTRACT
Abstract. The fortedata R package is an open data notebook from the Forest Resilience Threshold
Experiment (FoRTE) – a modeling and manipulative field experiment that tests
the effects of disturbance severity and disturbance type on carbon cycling
dynamics in a temperate forest. Package data consist of measurements of
carbon pools and fluxes and ancillary measurements to help analyze and
interpret carbon cycling over time. Currently the package includes data and
metadata from the first three FoRTE field seasons, serves as a central,
updatable resource for the FoRTE project team, and is intended as a resource
for external users over the course of the experiment and in perpetuity.
Further, it supports all associated FoRTE publications, analyses, and
modeling efforts. This increases efficiency, consistency, compatibility, and productivity while minimizing duplicated effort and error propagation that
can arise as a function of a large, distributed and collaborative effort.
More broadly, fortedata represents an innovative, collaborative way of approaching
science that unites and expedites the delivery of complementary datasets to
the broader scientific community, increasing transparency and
reproducibility of taxpayer-funded science. The fortedata package is available via GitHub:
https://github.com/FoRTExperiment/fortedata (last access: 19 February 2021), and detailed
documentation on the access, used, and applications of fortedata are available at
https://fortexperiment.github.io/fortedata/ (last access: 19 February 2021). The first public
release, version 1.0.1 is also archived at
https://doi.org/10.5281/zenodo.4399601 (Atkins et al., 2020b).
All data products are also available outside of the
package as .csv files: https://doi.org/10.6084/m9.figshare.13499148.v1 (Atkins et al., 2020c).
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