BlueCarbon
Facilitate the estimation of organic carbon stocks and fluxes from soil/sediment cores from blue carbon ecosystems.
https://github.com/ecologyr/bluecarbon
Category: Emissions
Sub Category: Emission Observation and Modeling
Keywords from Contributors
ecology bluecarbon marine-data seagrass geos control routing virtual transform crop
Last synced: about 23 hours ago
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Repository metadata
Estimation of organic carbon stocks and sequestration rates from soil/sediment cores from blue carbon ecosystems
- Host: GitHub
- URL: https://github.com/ecologyr/bluecarbon
- Owner: EcologyR
- License: gpl-3.0
- Created: 2023-03-22T18:42:24.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2025-03-06T12:14:33.000Z (about 2 months ago)
- Last Synced: 2025-04-12T18:31:08.972Z (15 days ago)
- Language: R
- Homepage: https://ecologyr.github.io/BlueCarbon/
- Size: 3.55 MB
- Stars: 7
- Watchers: 6
- Forks: 1
- Open Issues: 2
- Releases: 1
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE.md
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
README.Rmd
--- output: github_document editor_options: markdown: wrap: sentence --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" ) ``` # BlueCarbon`r badger::badge_cran_release()`  [](https://github.com/EcologyR/BlueCarbon/actions/workflows/R-CMD-check.yaml) [](https://app.codecov.io/gh/EcologyR/BlueCarbon) `r badger::badge_lifecycle("stable")` `r badger::badge_repostatus("Active")` [](https://cran.r-project.org/package=BlueCarbon) The goal of BlueCarbon is to facilitate the estimation of organic carbon stocks and sequestration rates from soil/sediment cores from blue carbon ecosystems. It includes seven main [functions](https://ecologyr.github.io/BlueCarbon/reference/index.html) to (1) estimate core compaction, (2) correct core compaction, (3) estimate sample thickness, (4) estimate organic carbon content from organic matter content, (5) estimate organic carbon stocks and (6) sequestration rates, and (7) visualize the error in stock extrapolation. {width="569"} #### ***estimate_compaction*** **- Estimate Core Compaction** Sampling soil cores by manual percussion often results in the compaction of the material retrieved. This function (`estimate_compaction()`) estimates the percentage of compaction using measurements taken before and after inserting the corer tube (Fig. 2): the length of the corer tube (sampler_length), distance between the surface of the soil and the top of the tube in the outside (external_distance) and distance between the surface of the soil and the top of the tube in the inside of the tube (internal_distance). {width="364"} #### ***decompact*** **- Calculate sediment properties after decompaction** Core compaction derived from field extraction can be mathematically corrected to estimate the original depth of the samples. This function (`decompact()`) applies a linear correction (assuming uniform compaction of the core material) to adjust the sample depth accurately. If dry bulk density data is provided, the function also corrects it accordingly. #### ***estimate_oc*** **- Organic carbon content estimation from organic carbon data** There is a linear correlation between organic carbon and organic matter content. This correlation can vary across ecosystems and sampling sites. This function (`estimate_oc()`) fits a linear regression model between organic matter and organic carbon content of the samples and predicts organic carbon values for samples where the latter information is missing. Estimation of organic carbon is performed using a linear regression between the logarithm of the organic carbon content and the logarithm of the organic matter content (log(organic carbon) \\\~ log(organic matter)), providing an organic carbon value for each organic matter value. It fits a model for each sampling station, dominant species, and ecosystem. If an organic carbon value is already available for a sample, the function returns it. Otherwise, it applies the model for the corresponding sampling station. If a model cannot be fitted for that station (e.g. because of limited sample size) or if the model fit is poor, the function instead applies the model for the dominant species. If no suitable species-level model exists, it then applies the ecosystem-level model. If no models are available at any of these levels, the function defaults to published models: [Fourqurean et al. (2012)](https://doi.org/10.1038/ngeo1477) for seagrasses, [Maxwell et al. (2023)](https://doi.org/10.1038/s41597-023-02633-x) for salt marshes, and Piñeiro-Juncal et al. for mangroves. It is unlikely, but possible, that the model predicts higher organic carbon than organic matter content. If this occurs, the function issues a warning, and it is recommended to discard that model. #### ***estimate_h*** **- Sample thickness estimation** For cores where only selected samples were measured, it is necessary to assign a carbon density to the unmeasured sections before estimating the total stock. This function (`estimate_h()`) identifies gaps between samples and, if any are present, divides the space between the previous and next sample, ensuring continuous samples without gaps in the core (Fig. 3). The midpoint between two consecutive samples is estimated from the bottom of the previous sample to the top of the next sample, preventing the uneven distribution of gaps between samples with different thickness. The stock and sequestration rate estimation functions (`estimate_oc_stock()` and `estimate_seq_rate()`) already incorporate this function, so there is no need to run it separately. {width="365"} #### ***estimate_oc_stock*** **- Organic carbon stock estimation** Estimates carbon stocks from soil core data down to a specified depth, with 100 as the default. If the core does not reach the desired depth, the function extrapolates the stock using a linear model based on the relationship between accumulated organic carbon mass and depth. In this model, accumulated organic carbon mass (stock) is the target variable and depth the explanatory variable (lm(accumulated organic carbon mass \~ depth)). {width="380"} #### ***test_extrapolation*** **- Visualize the error of stock extrapolation** This function subset the cores that reach the desired depth, estimates the observed stock, and estimates the stock using the linear model on the relationship between accumulated organic carbon mass and depth. Extrapolations are performed using the top 90, 75, 50 and 25% length of the specified depth. The function then compares the observed stock with the extrapolated stock estimates. Note that this function requires that at least some cores reach the desired depth. #### ***estimate_seq_rate*** **- Organic carbon sequestration rates estimation** Estimates the average organic carbon sequestration rate in the soil over a specified time frame (by default 100). The average sequestration rate is calculated by dividing the stock at the depth corresponding to the target time frame by the length of the time frame itself. ## Installation BlueCarbon can be installed directly from [CRAN](https://cran.r-project.org/package=BlueCarbon): ``` r install.packages("BlueCarbon") ``` or from [R-universe](https://ecologyr.r-universe.dev/BlueCarbon): ``` r install.packages("BlueCarbon", repos = c("https://ecologyr.r-universe.dev", "https://cloud.r-project.org")) ``` Or from [GitHub](https://github.com/EcologyR/BlueCarbon): ``` r # install.packages("remotes") remotes::install_github("EcologyR/BlueCarbon") ``` ## Citation If using this package, please cite it: ```{r comment=NA} citation("BlueCarbon") ``` ## Code of Conduct Please note that the BlueCarbon project is released with a [Contributor Code of Conduct](https://ecologyr.github.io/BlueCarbon/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms. ## Funding The development of this software has been funded by Fondo Europeo de Desarrollo Regional (FEDER) and Consejería de Transformación Económica, Industria, Conocimiento y Universidades of Junta de Andalucía (project US-1381388 led by Francisco Rodríguez Sánchez, Universidad de Sevilla). NPJ was supported by a Juan de la Cierva fellowship (JDC2022-048342-I, MCIN/AEI/10.13039/501100011033, European Union “NextGenerationEU”/PRTR”). JA acknowledges funding from the CLIMB-FOREST Horizon Europe Project (No 101059888) funded by the European Union. FRS was supported by VI PPIT-US from Universidad de Sevilla. MM was supported by a FCT PhD grant (https://doi.org/10.54499/2020.06996.BD). 
Citation (CITATION.cff)
# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "BlueCarbon" in publications use:' type: software license: GPL-3.0-or-later title: 'BlueCarbon: Estimation of Organic Carbon Stocks and Sequestration Rates from Soil Core Data' version: 0.1.0 abstract: Tools to estimate soil organic carbon stocks and sequestration rates in blue carbon ecosystems. 'BlueCarbon' contains functions to estimate and correct for core compaction, estimate sample thickness, estimate organic carbon content from organic matter content, estimate organic carbon stocks and sequestration rates, and visualize the error of carbon stock extrapolation. authors: - family-names: Piñeiro-Juncal given-names: Nerea email: [email protected] orcid: https://orcid.org/0000-0003-3767-1812 - family-names: Astigarraga given-names: Julen orcid: https://orcid.org/0000-0001-9520-3713 - family-names: Costa given-names: Valentina orcid: https://orcid.org/0000-0002-1513-0284 - family-names: Martins given-names: Marcio orcid: https://orcid.org/0000-0002-6969-2215 - family-names: Rodriguez-Sanchez given-names: Francisco orcid: https://orcid.org/0000-0002-7981-1599 preferred-citation: type: manual title: 'BlueCarbon: Estimation of Organic Carbon Stocks and Sequestration Rates From Soil Core Data' authors: - family-names: Piñeiro-Juncal given-names: Nerea email: [email protected] orcid: https://orcid.org/0000-0003-3767-1812 - family-names: Astigarraga given-names: Julen orcid: https://orcid.org/0000-0001-9520-3713 - family-names: Costa given-names: Valentina orcid: https://orcid.org/0000-0002-1513-0284 - family-names: Martins given-names: Marcio orcid: https://orcid.org/0000-0002-6969-2215 - family-names: Rodriguez-Sanchez given-names: Francisco orcid: https://orcid.org/0000-0002-7981-1599 year: '2025' url: https://github.com/EcologyR/BlueCarbon notes: R package version 0.1.0, https://EcologyR.github.io/BlueCarbon/ repository-code: https://github.com/EcologyR/BlueCarbon url: https://ecologyr.github.io/BlueCarbon/ contact: - family-names: Piñeiro-Juncal given-names: Nerea email: [email protected] orcid: https://orcid.org/0000-0003-3767-1812 references: - type: software title: 'R: A Language and Environment for Statistical Computing' notes: Depends url: https://www.R-project.org/ authors: - name: R Core Team institution: name: R Foundation for Statistical Computing address: Vienna, Austria year: '2025' version: '>= 4.1' - type: software title: covr abstract: 'covr: Test Coverage for Packages' notes: Suggests url: https://covr.r-lib.org repository: https://CRAN.R-project.org/package=covr authors: - family-names: Hester given-names: Jim email: [email protected] year: '2025' doi: 10.32614/CRAN.package.covr - type: software title: testthat abstract: 'testthat: Unit Testing for R' notes: Suggests url: https://testthat.r-lib.org repository: https://CRAN.R-project.org/package=testthat authors: - family-names: Wickham given-names: Hadley email: [email protected] year: '2025' doi: 10.32614/CRAN.package.testthat version: '>= 3.0.0' - type: software title: dplyr abstract: 'dplyr: A Grammar of Data Manipulation' notes: Imports url: https://dplyr.tidyverse.org repository: https://CRAN.R-project.org/package=dplyr authors: - family-names: Wickham given-names: Hadley email: [email protected] orcid: https://orcid.org/0000-0003-4757-117X - family-names: François given-names: Romain orcid: https://orcid.org/0000-0002-2444-4226 - family-names: Henry given-names: Lionel - family-names: Müller given-names: Kirill orcid: https://orcid.org/0000-0002-1416-3412 - family-names: Vaughan given-names: Davis email: [email protected] orcid: https://orcid.org/0000-0003-4777-038X year: '2025' doi: 10.32614/CRAN.package.dplyr - type: software title: ggplot2 abstract: 'ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics' notes: Imports url: https://ggplot2.tidyverse.org repository: https://CRAN.R-project.org/package=ggplot2 authors: - family-names: Wickham given-names: Hadley email: [email protected] orcid: https://orcid.org/0000-0003-4757-117X - family-names: Chang given-names: Winston orcid: https://orcid.org/0000-0002-1576-2126 - family-names: Henry given-names: Lionel - family-names: Pedersen given-names: Thomas Lin email: [email protected] orcid: https://orcid.org/0000-0002-5147-4711 - family-names: Takahashi given-names: Kohske - family-names: Wilke given-names: Claus orcid: https://orcid.org/0000-0002-7470-9261 - family-names: Woo given-names: Kara orcid: https://orcid.org/0000-0002-5125-4188 - family-names: Yutani given-names: Hiroaki orcid: https://orcid.org/0000-0002-3385-7233 - family-names: Dunnington given-names: Dewey orcid: https://orcid.org/0000-0002-9415-4582 - family-names: Brand given-names: Teun name-particle: van den orcid: https://orcid.org/0000-0002-9335-7468 year: '2025' doi: 10.32614/CRAN.package.ggplot2 - type: software title: gridExtra abstract: 'gridExtra: Miscellaneous Functions for "Grid" Graphics' notes: Imports repository: https://CRAN.R-project.org/package=gridExtra authors: - family-names: Auguie given-names: Baptiste email: [email protected] year: '2025' doi: 10.32614/CRAN.package.gridExtra - type: software title: reshape abstract: 'reshape: Flexibly Reshape Data' notes: Imports url: http://had.co.nz/reshape repository: https://CRAN.R-project.org/package=reshape authors: - family-names: Wickham given-names: Hadley email: [email protected] year: '2025' doi: 10.32614/CRAN.package.reshape
Owner metadata
- Name: EcologyR
- Login: EcologyR
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- Profile URL: https://github.com/EcologyR
GitHub Events
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- Release event: 1
- Issues event: 14
- Watch event: 5
- Delete event: 1
- Issue comment event: 7
- Push event: 48
- Fork event: 1
Last Year
- Create event: 2
- Release event: 1
- Issues event: 14
- Watch event: 5
- Delete event: 1
- Issue comment event: 7
- Push event: 48
- Fork event: 1
Committers metadata
Last synced: 7 days ago
Total Commits: 270
Total Committers: 7
Avg Commits per committer: 38.571
Development Distribution Score (DDS): 0.463
Commits in past year: 106
Committers in past year: 5
Avg Commits per committer in past year: 21.2
Development Distribution Score (DDS) in past year: 0.34
Name | Commits | |
---|---|---|
NPJuncal | n****l@g****m | 145 |
Francisco Rodriguez-Sanchez | f****c@g****m | 80 |
NPJuncal | n****l@g****m | 21 |
Julen Astigarraga | j****a@g****m | 14 |
MarcioFCMartins | m****d@g****m | 4 |
github-actions[bot] | 4****] | 3 |
costavale | v****a@h****m | 3 |
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Issue and Pull Request metadata
Last synced: 2 days ago
Total issues: 53
Total pull requests: 11
Average time to close issues: 5 months
Average time to close pull requests: 4 days
Total issue authors: 3
Total pull request authors: 3
Average comments per issue: 2.98
Average comments per pull request: 0.91
Merged pull request: 11
Bot issues: 0
Bot pull requests: 0
Past year issues: 4
Past year pull requests: 0
Past year average time to close issues: 14 days
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Past year average comments per issue: 1.5
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Package metadata
- Total packages: 1
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Total downloads:
- cran: 198 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 1
- Total maintainers: 1
cran.r-project.org: BlueCarbon
Estimation of Organic Carbon Stocks and Sequestration Rates from Soil Core Data
- Homepage: https://github.com/EcologyR/BlueCarbon
- Documentation: http://cran.r-project.org/web/packages/BlueCarbon/BlueCarbon.pdf
- Licenses: GPL (≥ 3)
- Latest release: 0.1.0 (published 2 months ago)
- Last Synced: 2025-04-26T04:01:29.585Z (2 days ago)
- Versions: 1
- Dependent Packages: 0
- Dependent Repositories: 0
- Downloads: 198 Last month
-
Rankings:
- Dependent packages count: 27.154%
- Dependent repos count: 33.449%
- Average: 49.215%
- Downloads: 87.043%
- Maintainers (1)
Score: 9.436439551116026