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Life and Fishery","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"---\noutput: github_document\n---\n\n\u003c!-- README.md is generated from README.Rmd. Please edit that file --\u003e\n\n```{r, include = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/README-\",\n  out.width = \"100%\"\n)\n```\n\n# planktonr \u003ca href=\"https://github.com/PlanktonTeam/planktonr\"\u003e\u003cimg src=\"man/figures/planktonr.png\" align=\"right\" width=\"139px\" /\u003e\u003c/a\u003e\n\n\u003c!-- badges: start --\u003e\n[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)\n[![Windows](https://github.com/PlanktonTeam/planktonr/actions/workflows/Windows.yaml/badge.svg)](https://github.com/PlanktonTeam/planktonr/actions/workflows/Windows.yaml)\n[![Ubuntu](https://github.com/PlanktonTeam/planktonr/actions/workflows/Ubuntu.yaml/badge.svg)](https://github.com/PlanktonTeam/planktonr/actions/workflows/Ubuntu.yaml)\n[![MacOS](https://github.com/PlanktonTeam/planktonr/actions/workflows/MacOS.yaml/badge.svg)](https://github.com/PlanktonTeam/planktonr/actions/workflows/MacOS.yaml)\n[![Codecov test coverage](https://codecov.io/gh/PlanktonTeam/planktonr/branch/main/graph/badge.svg)](https://app.codecov.io/gh/PlanktonTeam/planktonr?branch=main)\n[![issues - planktonr](https://img.shields.io/github/issues/PlanktonTeam/planktonr)](https://github.com/PlanktonTeam/planktonr/issues)\n\u003c!-- badges: end --\u003e\n\n`planktonr` is an R package that facilitates the download, analysis, and visualisation of phytoplankton and zooplankton data. The package primarily focuses on plankton data from the Australian Ocean Data Network ([AODN](https://portal.aodn.org.au)) collected by the Integrated Marine Observing System ([IMOS](https://www.imos.org.au)), including:\n\n* **National Reference Stations (NRS)** - Coastal monitoring stations with monthly sampling\n* **Continuous Plankton Recorder (CPR)** - Ship-based transect sampling across ocean basins  \n* **Southern Ocean Time Series (SOTS)** - Deep ocean mooring south of Tasmania\n\nThe package provides access to phytoplankton, zooplankton, larval fish, and biogeochemical data, along with tools for trend analysis, biodiversity assessment, and data visualisation.\n\n## Installation\n\nThe package is under active development. You can install the development version from [GitHub](https://github.com/) with:\n\n``` r\n# install.packages(\"devtools\")\ndevtools::install_github(\"PlanktonTeam/planktonr\")\n```\n\nSome optional features require additional packages:\n``` r\n# For satellite data access\ninstall.packages(\"thredds\")\n\n# For parallel processing (speeds up large data downloads)\ninstall.packages(c(\"future\", \"furrr\"))\n\n# For community analysis functions\ninstall.packages(\"vegan\")\n```\n\n## Quick Start\n\n```{r, eval=FALSE}\nlibrary(planktonr)\nlibrary(dplyr)\nlibrary(ggplot2)\n\n# Get zooplankton biomass from NRS stations\ndf \u003c- pr_get_Indices(\"NRS\", \"Zooplankton\") %\u003e%\n  filter(Parameters == \"Biomass_mgm3\", \n         StationCode %in% c(\"MAI\", \"PHB\"))\n\n# Plot time series\npr_plot_TimeSeries(df, trans = \"log10\")\n\n# Examine long-term trends\npr_plot_Trends(df, Trend = \"Raw\", method = \"lm\", trans = \"log10\")\n\n# Look at seasonal patterns\npr_plot_Trends(df, Trend = \"Month\", method = \"loess\", trans = \"log10\")\n```\n\n## Key Features\n\n### Data Access\n* **`pr_get_NRSData()`** - Raw taxonomic data from NRS stations\n* **`pr_get_CPRData()`** - Raw taxonomic data from CPR surveys\n* **`pr_get_Indices()`** - Pre-calculated ecological indices (biomass, diversity, abundance)\n* **`pr_get_FuncGroups()`** - Functional group abundance (diatoms, copepods, etc.)\n* **`pr_get_NRSChemistry()`** - Nutrient and carbon chemistry data\n* **`pr_get_NRSPigments()`** - Photosynthetic pigment concentrations\n\n### Visualisation\n* **`pr_plot_TimeSeries()`** - Basic time series plots\n* **`pr_plot_Trends()`** - Time series with fitted trend lines\n* **`pr_plot_Climatology()`** - Seasonal and annual climatologies\n* **`pr_plot_tsfg()`** - Functional group composition over time\n* **`pr_plot_EOVs()`** - Essential Ocean Variable plots for reporting\n\n### Analysis\n* **`pr_remove_outliers()`** - Statistical outlier detection and removal\n* **`pr_add_Bioregions()`** - Assign samples to Australian marine bioregions\n* **`pr_filter_data()`** - Helper for filtering datasets for analysis\n\n## Learn More\n\nSee the package vignettes for detailed examples:\n* `vignette(\"planktonr\")` - Overview and sampling frequency maps\n* `vignette(\"EssentialOceanVariables\")` - EOV analysis and reporting\n* `vignette(\"Phytoplankton\")` - Phytoplankton data analysis examples\n* `vignette(\"Zooplankton\")` - Zooplankton data analysis examples\n* `vignette(\"Biogeochemistry\")` - Nutrient and pigment data\n* `vignette(\"LarvalFish\")` - Larval fish distribution data\n\n## Acknowledgements\n\nThis package accesses data from the Integrated Marine Observing System (IMOS). IMOS is enabled by the National Collaborative Research Infrastructure Strategy (NCRIS) and is supported by the Australian Government.\n\nThanks to the Integration and Application Network ([ian.umces.edu/media-library](https://ian.umces.edu/media-library)) for the plankton symbols used in the planktonr hex sticker.\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":[],"project_url":"https://ost.ecosyste.ms/api/v1/projects/152767","html_url":"https://ost.ecosyste.ms/projects/152767"}