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Monitoring and Analysis","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  dev = \"ragg_png\",\n  dpi = 100\n)\n\nset.seed(1)\n```\n\n# BirdFlowR \u003ca href=\"https://birdflow-science.github.io/BirdFlowR/\"\u003e\u003cimg src=\"man/figures/logo.png\" align=\"right\" height=\"139\" /\u003e\u003c/a\u003e\n\n\u003c!-- badges: start --\u003e\n  [![R-CMD-check](https://github.com/birdflow-science/BirdFlowR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/birdflow-science/BirdFlowR/actions/workflows/R-CMD-check.yaml)\n[![Codecov test coverage](https://codecov.io/gh/birdflow-science/BirdFlowR/branch/main/graph/badge.svg)](https://app.codecov.io/gh/birdflow-science/BirdFlowR?branch=main)\n\u003c!-- badges: end --\u003e\n\n\n\nAn R package to predict changes in bird distributions and generate synthetic \nmigration routes based on BirdFlow models.\n\n\n## Installation\n\nInstall just the package:\n```{r install, eval = FALSE}\nif (!require(\"remotes\"))\n  install.packages(\"remotes\")\nremotes::install_github(\"birdflow-science/BirdFlowR\")\n```\nOr to install with example data and vignette:\n\n```{r install everything, eval = FALSE}\ninstalled \u003c- rownames(installed.packages())\nif (!\"remotes\" %in% installed)\n  install.packages(\"remotes\")\nif (!\"rnaturalearthdata\" %in% installed)\n  install.packages(\"rnaturalearthdata\")\nremotes::install_github(\"birdflow-science/BirdFlowModels\")\nremotes::install_github(\"birdflow-science/BirdFlowR\", build_vignettes = TRUE, dependencies = TRUE)\n```\nSee the \n[Installation vignette](https://birdflow-science.github.io/BirdFlowR/articles/Installation.html) \nfor more information and help troubleshooting.\n\n## Usage \n\nThe two primary functions are `predict()` to project distributions and \n`route()` to generate synthetic routes.  \n\n`route_migration()` is a wrapper to `route()` which automates sampling\nlocations from a distribution for the start of the migration and setting \nthe start and end dates to route for the migration window. We can use it to \ncreate synthetic routes for a species.\n```{r examples}\nlibrary(BirdFlowR)\nlibrary(BirdFlowModels)\n\nbf \u003c- amewoo \n\nspecies(bf)\n\n# Generate routes for the prebreeding migration \nrts \u003c- route(bf, n = 10, season = \"prebreeding\")\n\n# Plot routes\nplot_routes(rts, bf)\n\n```\n\nVisualize the movement in the BirdFlow model for a timestep.\n\n```{r movement_vectors}\n\nplot_movement_vectors(bf, start = 12)\n\n```\n\n\n## Learn more\n\n- `vignette(\"BirdFlowR\")` has a longer introduction to the package, and how to\n  use `predict()` and `route()` to project bird distributions and movement. \n- `vignette(\"Installation\")` for detailed installation instructions.\n- `vignette(\"Preprocess\")` covers downloading and formatting data for model \n  fitting with `preprocess_species()`, importing fitted models with \n  `import_birdflow()`, and reducing model size with `sparsify()`.   \n- Read the paper:\n  - [BirdFlow: Learning Seasonal Bird Movements from Citizen Science Data](https://www.biorxiv.org/content/10.1101/2022.04.12.488057v1) Miguel Fuentes, Benjamin M. Van Doren, Daniel Fink, Daniel Sheldon bioRxiv 2022.04.12.488057; doi: https://doi.org/10.1101/2022.04.12.488057\n\n\n","funding_links":[],"readme_doi_urls":["https://doi.org/10.1101/2022.04.12.488057"],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["movement-ecology","aeroecology","enram","eumetnet-opera","nexrad","radar","weather-radar","wsr-88d"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/147948","html_url":"https://ost.ecosyste.ms/projects/147948"}