https://github.com/doi-usgs/streammetabolizer

streamMetabolizer uses inverse modeling to estimate aquatic metabolism (photosynthesis and respiration) from time series data on dissolved oxygen, water temperature, depth, and light.

https://github.com/doi-usgs/streammetabolizer

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streamMetabolizer uses inverse modeling to estimate aquatic metabolism (photosynthesis and respiration) from time series data on dissolved oxygen, water temperature, depth, and light.

README.Rmd

---
title: "README"
output:
  md_document:
    variant: markdown_github
editor_options: 
  chunk_output_type: console
---

```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "##",
  fig.path = "man/figures/README-"
)
```

# streamMetabolizer: Models for Estimating Aquatic Photosynthesis and Respiration

```diff
! 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](https://doi.org/10.1002/2017JG004140). An application to 356
streams across the U.S. is described in [Appling et al. 2018b](https://doi.org/10.1038/sdata.2018.292).

> 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.
```{r eval=TRUE}
citation('streamMetabolizer')
```

## Installation

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)](https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens). There are [several methods](https://usethis.r-lib.org/articles/git-credentials.html) 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:
```{r, eval=FALSE}
remotes::install_github('appling/unitted')
```

You can then install the most cutting edge version of `streamMetabolizer` with this command:
```{r, eval=FALSE}
remotes::install_github(
  "USGS-R/streamMetabolizer", # soon to be "DOI-USGS/streamMetabolizer"
  build_vignettes = TRUE)
```

### Software dependencies for Bayesian models

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](https://github.com/stan-dev/rstan/wiki) for the most up-to-date installation instructions, which differ by operating system.


## Getting started

After installing and loading `streamMetabolizer`, run `vignette()` in R to see tutorials on getting started and customizing your metabolism models.
```{r eval=FALSE}
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](https://github.com/USGS-R/streamMetabolizer/blob/main/inst/doc/get_started.html), which you can download and then open in a browser.


## Development and Maintenance Status

`streamMetabolizer` is a USGS Archive Research Package:
[![USGS Status](https://img.shields.io/badge/USGS-Research-blue.svg)](https://owi.usgs.gov/R/packages.html#research)

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](https://github.com/USGS-R/streamMetabolizer/issues).


## Contributing

We want to encourage a warm, welcoming, and safe environment for contributing to this project. See [CODE_OF_CONDUCT.md](https://github.com/USGS-R/streamMetabolizer/blob/main/CODE_OF_CONDUCT.md) for more information.

For technical details on how to contribute, see [CONTRIBUTING.md](https://github.com/USGS-R/streamMetabolizer/blob/main/CONTRIBUTING.md)


### Development History

`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.


## Model Archive

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.


```{r eval=FALSE}
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
```

```{r disclaimer, child="DISCLAIMER.md", eval=TRUE}
```

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