knitr::opts_chunk$set( collapse = TRUE, comment = "##", fig.path = "man/figures/README-" )
! In summer or fall 2023, this package will move from ! https://github.com/USGS-R/streamMetabolizer to ! https://github.com/DOI-USGS/streamMetabolizer. ! Please update your links accordingly.
The streamMetabolizer
R package uses inverse modeling to estimate aquatic
photosynthesis and respiration (collectively, metabolism) from time series
data on dissolved oxygen, water temperature, depth, and light. The package
assists with data preparation, handles data gaps during modeling, and
provides tabular and graphical reports of model outputs. Several
time-honored methods are implemented along with many promising new variants
that produce more accurate and precise metabolism estimates.
This package has been described, with special focus on the Bayesian model options, by Appling et al. 2018a. An application to 356 streams across the U.S. is described in Appling et al. 2018b.
Appling, A. P., Hall, R. O., Yackulic, C. B., & Arroita, M. (2018a). Overcoming equifinality: Leveraging long time series for stream metabolism estimation. Journal of Geophysical Research: Biogeosciences, 123(2), 624–645. https://doi.org/10.1002/2017JG004140
Appling, A. P., Read, J. S., Winslow, L. A., Arroita, M., Bernhardt, E. S., Griffiths, N. A., Hall, R. O., Harvey, J. W., Heffernan, J. B., Stanley, E. H., Stets, E. G., & Yackulic, C. B. (2018b). The metabolic regimes of 356 rivers in the United States. Scientific Data, 5(1), 180292. https://doi.org/10.1038/sdata.2018.292
To see the recommended citation for this package, please run citation('streamMetabolizer')
at the R prompt.
citation('streamMetabolizer')
To install the streamMetabolizer
package, use the remotes
package (running install.packages('remotes')
first if needed). To use remotes::install_github()
it is convenient to set a GitHub Personal Access Token (PAT). There are several methods for setting your PATs within R; the simplest is to call `Sys.setenv(GITHUB_PAT="yyyy"),
replacing yyyy with the PAT you established on the GitHub website.
You may first need to install the unitted
dependency:
remotes::install_github('appling/unitted')
You can then install the most cutting edge version of streamMetabolizer
with this command:
remotes::install_github( "USGS-R/streamMetabolizer", # soon to be "DOI-USGS/streamMetabolizer" build_vignettes = TRUE)
The major dependency for Bayesian models is the rstan
package, and installation of that package is rarely as simple as a call to install.packages()
. Start at the rstan wiki page for the most up-to-date installation instructions, which differ by operating system.
After installing and loading streamMetabolizer
, run vignette()
in R to see tutorials on getting started and customizing your metabolism models.
vignette(package='streamMetabolizer') ## displays a list of available vignettes vignette('get_started', package='streamMetabolizer') ## displays an html or pdf rendering of the 'get_started' vignette
You can also view pre-built html versions of these vignettes in the "inst/doc" folder in the source code, e.g., inst/doc/get_started.html, which you can download and then open in a browser.
streamMetabolizer
is a USGS Archive Research Package:
Project funding has ended and our maintenance time is limited, but we do attempt to provide bug fixes and lightweight support as we are able. Submit questions or suggestions to https://github.com/USGS-R/streamMetabolizer/issues.
We want to encourage a warm, welcoming, and safe environment for contributing to this project. See CODE_OF_CONDUCT.md for more information.
For technical details on how to contribute, see CONTRIBUTING.md
streamMetabolizer
was developed 2015-2018 with support from the USGS Powell Center (through a working group on Continental Patterns of Stream Metabolism), the USGS National Water Quality Program, and the USGS Office of Water Information.
The following version of R and package dependencies were used most recently to pass the embedded tests within this package. There is no guarantee of reproducible results using future versions of R or updated versions of package dependencies; however, we aim to test and update future modeling environments.
sessioninfo::session_info() ## ─ Session info ─────────────────────────────────────────────────────────────────────────────────── ## setting value ## version R version 4.2.3 (2023-03-15) ## os macOS Ventura 13.4.1 ## system x86_64, darwin17.0 ## ui RStudio ## language (EN) ## collate en_US.UTF-8 ## ctype en_US.UTF-8 ## tz America/New_York ## date 2023-07-02 ## rstudio 2023.06.0+421 Mountain Hydrangea (desktop) ## pandoc 3.1.1 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown) ## ## ─ Packages ─────────────────────────────────────────────────────────────────────────────────────── ## package * version date (UTC) lib source ## cli 3.6.1 2023-03-23 [1] CRAN (R 4.2.0) ## deSolve 1.35 2023-03-12 [1] CRAN (R 4.2.0) ## digest 0.6.32 2023-06-26 [1] CRAN (R 4.2.0) ## dplyr 1.1.2 2023-04-20 [1] CRAN (R 4.2.0) ## evaluate 0.21 2023-05-05 [1] CRAN (R 4.2.0) ## fansi 1.0.4 2023-01-22 [1] CRAN (R 4.2.0) ## fastmap 1.1.1 2023-02-24 [1] CRAN (R 4.2.0) ## generics 0.1.3 2022-07-05 [1] CRAN (R 4.2.0) ## glue 1.6.2 2022-02-24 [1] CRAN (R 4.2.0) ## htmltools 0.5.5 2023-03-23 [1] CRAN (R 4.2.0) ## knitr 1.43 2023-05-25 [1] CRAN (R 4.2.0) ## LakeMetabolizer 1.5.5 2022-11-15 [1] CRAN (R 4.2.0) ## lazyeval 0.2.2 2019-03-15 [1] CRAN (R 4.2.0) ## lifecycle 1.0.3 2022-10-07 [1] CRAN (R 4.2.0) ## lubridate 1.9.2 2023-02-10 [1] CRAN (R 4.2.0) ## magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.2.0) ## pillar 1.9.0 2023-03-22 [1] CRAN (R 4.2.0) ## pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.2.0) ## plyr 1.8.8 2022-11-11 [1] CRAN (R 4.2.0) ## purrr 1.0.1 2023-01-10 [1] CRAN (R 4.2.0) ## R6 2.5.1 2021-08-19 [1] CRAN (R 4.2.0) ## Rcpp 1.0.10 2023-01-22 [1] CRAN (R 4.2.0) ## rLakeAnalyzer 1.11.4.1 2019-06-09 [1] CRAN (R 4.2.0) ## rlang 1.1.1 2023-04-28 [1] CRAN (R 4.2.0) ## rmarkdown 2.22 2023-06-01 [1] CRAN (R 4.2.0) ## rstudioapi 0.14 2022-08-22 [1] CRAN (R 4.2.0) ## sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.2.0) ## streamMetabolizer * 0.12.1 2023-07-02 [1] local ## tibble 3.2.1 2023-03-20 [1] CRAN (R 4.2.0) ## tidyr 1.3.0 2023-01-24 [1] CRAN (R 4.2.0) ## tidyselect 1.2.0 2022-10-10 [1] CRAN (R 4.2.0) ## timechange 0.2.0 2023-01-11 [1] CRAN (R 4.2.0) ## unitted 0.2.9 2023-06-05 [1] Github (appling/unitted@d1f1172) ## utf8 1.2.3 2023-01-31 [1] CRAN (R 4.2.0) ## vctrs 0.6.3 2023-06-14 [1] CRAN (R 4.2.0) ## xfun 0.39 2023-04-20 [1] CRAN (R 4.2.0) ## yaml 2.3.7 2023-01-23 [1] CRAN (R 4.2.0) ## ## [1] /Library/Frameworks/R.framework/Versions/4.2/Resources/library
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