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inline\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  cache = TRUE,\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/README-\"\n)\n\nset.seed(1)\n```\n\n# \u003cimg src=\"https://i.imgur.com/vTLlhbp.png\" align=\"right\" height=88 /\u003e Calculate biomass\n\n[![lifecycle](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)\n[![Travis build status](https://travis-ci.org/forestgeo/fgeo.biomass.svg?branch=master)](https://travis-ci.org/forestgeo/fgeo.biomass)\n[![Coverage status](https://coveralls.io/repos/github/forestgeo/fgeo.biomass/badge.svg)](https://coveralls.io/r/forestgeo/fgeo.biomass?branch=master)\n[![CRAN status](https://www.r-pkg.org/badges/version/fgeo.biomass)](https://cran.r-project.org/package=fgeo.biomass)\n\nThe goal of fgeo.biomass is to calculate biomass using [ForestGEO](https://forestgeo.si.edu/) data and equations from either the [BIOMASS package](https://CRAN.R-project.org/package=BIOMASS) or the [allodb package](https://forestgeo.github.io/allodb/). \n\n* The BIOMASS package is applicable to tropical forests. It was first [published on CRAN in 2016](https://cran.r-project.org/) and on [Methods on Ecology and Evolution in 2017](https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.12753). fgeo.biomass provides the main features of BIOMASS with a simpler interface, consistent with all [fgeo packages](https://forestgeo.github.io/fgeo/).\n\n* The allodb package is work in progress, and aims to provide expert-selected allometric equations, both for tropical and temperate forests. fgeo.biomass provides a simple interface to automate the process of finding the right equation(s) for each stem and computing biomass. \n\n## Installation\n\nInstall the development version of **fgeo.biomass** with:\n\n```\n# install.packages(\"devtools\")\ndevtools::install_github(\"forestgeo/fgeo.biomass\")\n```\n\n## Setup\n\nIn addition to the fgeo.biomass package we will use dplyr and ggplot2 for data wrangling and plotting.\n\n```{r, message=FALSE}\nlibrary(ggplot2)\nlibrary(dplyr)\nlibrary(fgeo.biomass)\n```\n\n## fgeo.biomass wrapping BIOMASS\n\nWe'll use data from the [Barro Colorado Island, Panama](https://forestgeo.si.edu/sites/neotropics/barro-colorado-island) (BCI). We first pick alive trees and drop missing `dbh` values as we can't calculate biomass for them.\n\n```{r}\nif (!requireNamespace(\"bciex\", quietly = TRUE)) {\n  stop(\n    \"For this example, you must first install the bciex package with:\\n\",\n    \"devtools::install_github('forestgeo/bciex')\"\n  )\n}\n\nbci_tree \u003c- as_tibble(bciex::bci12t7mini) %\u003e% \n  filter(status == \"A\", !is.na(dbh))\nbci_tree\n```\n\nWe also need species data.\n\n```{r}\nbci_species \u003c- as_tibble(bciex::bci_species)\nbci_species\n```\n\n`add_tropical_biomass()` adds biomass to your census data.\n\n```{r}\nbiomass \u003c- add_tropical_biomass(bci_tree, bci_species)\nbiomass\n```\n\nYou may also provide a specific `region` or `latitude` and `longitude`.\n\n```{r}\nbiomass \u003c- add_tropical_biomass(\n  bci_tree, \n  bci_species,\n  latitude = 9.154965, \n  longitude = -79.845884\n)\n\nbiomass %\u003e% \n  select(biomass, everything())\n```\n\n`propagate_errors()` allows you to propagate errors.\n\n```{r}\nstr(\n  propagate_errors(biomass)\n)\n```\n\n`model_height()` allows you to create a height model, which you can use to propagate height errors. This is what the entire pipeline looks like:\n\n```{r}\nmodel \u003c- model_height(bci_tree)\n\nerrors \u003c- bci_tree %\u003e% \n  add_tropical_biomass(bci_species) %\u003e% \n  propagate_errors(height_model = model)\n\nstr(errors)\n```\n\nIf you pass `latitude` and `longitude` to `add_tropical_biomass(), and then you pass a `height_model` to `propagate_errors()`, then you will need to ignore the coordinates. On an interactive session, you should see something like this:\n\n![](https://i.imgur.com/dhHCYJN.png)\n\n```{r}\nif (interactive()) {\n  errors \u003c- bci_tree %\u003e% \n    add_tropical_biomass(\n      bci_species, \n      latitude = 9.154965, \n      longitude = -79.845884\n    ) %\u003e% \n    propagate_errors(height_model = model)\n  \n  str(errors)\n}\n```\n\n`add_wood_density()` adds wood density to your census data. It is not limited to tropical forests, and has support for all of these regions: `r glue::glue_collapse(fgeo.biomass:::wd_regions(), sep = \", \", last = \", and \")`.\n\n```{r}\nwood_density \u003c- add_wood_density(bci_tree, bci_species)\n\nwood_density %\u003e% \n  select(starts_with(\"wd_\"), everything())\n```\n\nThe BIOMASS package provides a tool to correct taxonomic names. fgeo.biomass does not include that feature. You may use BIOMASS directly or the more focused [taxize package](https://cran.r-project.org/web/packages/taxize/taxize.pdf).\n\n##  fgeo.biomass wrapping allodb\n\n## Warning\n\nThese features are not ready for research. We are now building a [Minimum Viable Product](https://en.wikipedia.org/wiki/Minimum_viable_product), with just enough features to collect feedback from alpha users and redirect our effort. The resulting biomass is still meaningless.\n\nWe'll use the `add_biomass()` with these inputs:\n\n1. A ForestGEO-like _stem_ or _tree_ table.\n2. A _species_ table (internally used to look up the Latin species names from the species codes in the `sp` column of the census table).\n\nWe'll use data from the [Smithsonian Conservation Biology Institute, USA](https://forestgeo.si.edu/sites/north-america/smithsonian-conservation-biology-institute) (SCBI). We first pick alive trees and drop missing `dbh` values as we can't calculate biomass for them.\n\n```{r}\ncensus \u003c- fgeo.biomass::scbi_tree1 %\u003e% \n  filter(status == \"A\", !is.na(dbh))\n\ncensus\n```\n\nWe now use `add_biomass()` to add biomass to our census dataset. \n\n```{r}\nspecies \u003c- fgeo.biomass::scbi_species\n\nwith_biomass \u003c- census %\u003e% \n  add_biomass(species, site = \"SCBI\")\n```\n\nWe are warned that we are using a tree-table (as opposed to a stem-table), and informed about how to interpret the resulting `biomass` values for trees and shrubs.\n\nSome equations couldn't be found. There may be two reasons:\n\n* Some stems in the data belong to species with no matching species in allodb.\n* Some stems in the data belong to species that do match species in allodb but the available equations were designed for a dbh range that doesn't include actual dbh values in the data.\n\nHere are the most interesting columns of the result:\n\n```{r}\nwith_biomass %\u003e% \n  select(treeID, species, biomass)\n```\n\nLet's now visualize the relationship between `dbh` and b`biomass` by `species` (black points), in comparison with `agb` (above ground biomass) values calculated with allometric equations for tropical trees (grey points). \n\n```{r, fig.height=14}\nwith_biomass %\u003e% \n  # Convert agb from [Mg] to [kg]\n  mutate(agb_kg = agb * 1e3) %\u003e% \n  ggplot(aes(x = dbh)) +\n  geom_point(aes(y = agb_kg), size = 1.5, color = \"grey\") +\n  geom_point(aes(y = biomass), size = 1, color = \"black\") +\n  facet_wrap(\"species\", ncol = 4) +\n  ylab(\"Reference `agb` (grey) and calculated `biomass` (black) in [kg]\") +\n  xlab(\"dbh [mm]\") +\n  theme_bw()\n```\n\nAbove, the species for which `biomass` couldn't be calculated show no black points, although they do show grey reference-points.\n\nTo better understand the distribution of `biomass` values for each species we can use a box-plot.\n\n```{r}\nwith_biomass %\u003e% \n  ggplot(aes(species, biomass)) +\n  geom_boxplot() +\n  ylab(\"biomass [kg]\") +\n  coord_flip()\n```\n\nFor some species the maximum `dbh` for which `biomass` was calculated is much lower than the maximum `dbh` value for which the reference `agb` was calculated. This is because most equations in __allodb__ are defined for a specific range of `dbh` values. Eventually __allodb__ might provide equations beyond the `dbh` limits currently available.\n\nTo explore this issue, here we use `add_component_biomass()` which allows us to see intermediary results that `add_biomass()` doesn't show.\n\n```{r}\ndetailed_biomass \u003c- suppressWarnings(suppressMessages(\n  add_component_biomass(census, species, site = \"SCBI\")\n))\n\n# Maximum `dbh` values by species\nmax_by_species \u003c- detailed_biomass %\u003e% \n  select(species, dbh_max_mm) %\u003e% \n  group_by(species) %\u003e% \n  arrange(desc(dbh_max_mm)) %\u003e% \n  filter(row_number() == 1L) %\u003e% \n  ungroup()\n\n# `dbh` is above the maximum limit, so `biomass` is missing (agb has a value)\ndetailed_biomass %\u003e% \n  filter(dbh \u003e 1000) %\u003e% \n  select(-dbh_max_mm) %\u003e% \n  left_join(max_by_species) %\u003e% \n  mutate(agb_kg = agb * 1e3) %\u003e%\n  select(species, biomass, agb, dbh, dbh_max_mm) %\u003e% \n  arrange(species) %\u003e%\n  print(n = Inf)\n```\n\n## Biomass via BIOMASS versus allodb\n\n```{r}\ntemperate_biomass \u003c- add_biomass(census, species, site = \"scbi\")\n\n# Warning: Aplying tropical equations to a temperate forest for comparison\ntropical_biomass \u003c- add_tropical_biomass(census, species)\n\ndbh_biomsss \u003c- tibble(\n  dbh = temperate_biomass$dbh,\n  species = temperate_biomass$species,\n  temperate_biomass = temperate_biomass$biomass, \n  tropical_biomass = tropical_biomass$biomass\n)\n```\n\n```{r, fig.height=14}\ndbh_biomsss %\u003e% \n  ggplot(aes(x = dbh)) +\n  geom_point(aes(y = tropical_biomass), size = 1.5, color = \"grey\") +\n  geom_point(aes(y = temperate_biomass), size = 1) +\n  facet_wrap(\"species\", ncol = 4) +\n  ylab(\"Biomass [kg] (via the BIOMASS (grey) and allodb (black) packages)\") +\n  xlab(\"dbh [mm]\") +\n  theme_bw()\n```\n\n## General information\n\n* [Getting help](SUPPORT.md).\n* [Contributing](CONTRIBUTING.md).\n* [Contributor Code of Conduct](CODE_OF_CONDUCT.md).\n\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":[],"project_url":"https://ost.ecosyste.ms/api/v1/projects/546","html_url":"https://ost.ecosyste.ms/projects/546"}