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Import and manipulate ForestGEO datafgeo.tool helps you to import and manipulate ForestGEO data.
Install the latest stable version of fgeo.tool from CRAN with:
Install the development version of fgeo.tool from GitHub with:
Or install all fgeo packages in one step.
library(fgeo.tool)
#>
#> Attaching package: 'fgeo.tool'
#> The following object is masked from 'package:stats':
#>
#> filter
# Helps access data for examples
library(fgeo.x)example_path() allows you to access datasets stored in your R libraries.
example_path()
#> [1] "csv" "mixed_files" "rdata" "rdata_one"
#> [5] "rds" "taxa.csv" "tsv" "vft_4quad.csv"
#> [9] "view" "weird" "xl"
(vft_file <- example_path("view/vft_4quad.csv"))
#> [1] "/usr/local/lib/R/site-library/fgeo.x/extdata/view/vft_4quad.csv"read_vft() and read_taxa() import a ViewFullTable and ViewTaxonomy from .tsv or .csv files.
read_vft(vft_file)
#> # A tibble: 500 × 32
#> DBHID PlotName PlotID Family Genus SpeciesName Mnemonic Subspecies SpeciesID
#> <int> <chr> <int> <chr> <chr> <chr> <chr> <chr> <int>
#> 1 385164 luquillo 1 Rubia… Psyc… brachiata PSYBRA <NA> 185
#> 2 385261 luquillo 1 Urtic… Cecr… schreberia… CECSCH <NA> 74
#> 3 384600 luquillo 1 Rubia… Psyc… brachiata PSYBRA <NA> 185
#> 4 608789 luquillo 1 Rubia… Psyc… berteroana PSYBER <NA> 184
#> 5 388579 luquillo 1 Areca… Pres… acuminata PREMON <NA> 182
#> 6 384626 luquillo 1 Arali… Sche… morototoni SCHMOR <NA> 196
#> 7 410958 luquillo 1 Rubia… Psyc… brachiata PSYBRA <NA> 185
#> 8 385102 luquillo 1 Piper… Piper glabrescens PIPGLA <NA> 174
#> 9 353163 luquillo 1 Areca… Pres… acuminata PREMON <NA> 182
#> 10 481018 luquillo 1 Salic… Case… arborea CASARB <NA> 70
#> # ℹ 490 more rows
#> # ℹ 23 more variables: SubspeciesID <chr>, QuadratName <chr>, QuadratID <int>,
#> # PX <dbl>, PY <dbl>, QX <dbl>, QY <dbl>, TreeID <int>, Tag <chr>,
#> # StemID <int>, StemNumber <int>, StemTag <int>, PrimaryStem <chr>,
#> # CensusID <int>, PlotCensusNumber <int>, DBH <dbl>, HOM <dbl>,
#> # ExactDate <date>, Date <int>, ListOfTSM <chr>, HighHOM <int>,
#> # LargeStem <chr>, Status <chr>pick_dbh_under(), drop_status() and friends pick and drop rows from a ForestGEO ViewFullTable or census table.
tree5 <- fgeo.x::tree5
tree5 %>%
pick_dbh_under(100)
#> # A tibble: 18 × 19
#> treeID stemID tag StemTag sp quadrat gx gy MeasureID CensusID
#> <int> <int> <chr> <chr> <chr> <chr> <dbl> <dbl> <int> <int>
#> 1 7624 160987 108958 175325 TRIPAL 722 139. 425. 486675 5
#> 2 19930 117849 123493 165576 CASARB 425 61.3 496. 471979 5
#> 3 31702 39793 22889 22889 SLOBER 304 53.8 73.8 447307 5
#> 4 35355 44026 27538 27538 SLOBER 1106 203. 110. 449169 5
#> 5 39705 48888 33371 33370 CASSYL 1010 184. 194. 451067 5
#> 6 57380 155867 66962 171649 SLOBER 1414 274. 279. 459427 5
#> 7 95656 129113 131519 131519 OCOLEU 402 79.7 22.8 474157 5
#> 8 96051 129565 132348 132348 HIRRUG 1403 278 40.6 474523 5
#> 9 96963 130553 134707 134707 TETBAL 610 114. 182. 475236 5
#> 10 115310 150789 165286 165286 MANBID 225 24.0 497. 483175 5
#> 11 121424 158579 170701 170701 CASSYL 811 146. 218. 484785 5
#> 12 121689 158871 171277 171277 INGLAU 515 84.2 285. 485077 5
#> 13 121953 159139 171809 171809 PSYBRA 1318 247. 354. 485345 5
#> 14 124522 162698 174224 174224 CASSYL 1411 279. 210. 488386 5
#> 15 125038 163236 175335 175335 CASSYL 822 153. 426. 488924 5
#> 16 126087 NA 177394 <NA> CASARB 521 89.8 408. NA NA
#> 17 126803 NA 178513 <NA> PSYBER 622 113. 426 NA NA
#> 18 126934 NA 178763 <NA> MICRAC 324 47 480. NA NA
#> # ℹ 9 more variables: dbh <dbl>, pom <chr>, hom <dbl>, ExactDate <date>,
#> # DFstatus <chr>, codes <chr>, nostems <dbl>, status <chr>, date <dbl>pick_main_stem() and pick_main_stemid() pick the main stem or main stemid(s) of each tree in each census.
stem <- download_data("luquillo_stem6_random")
dim(stem)
#> [1] 1320 19
dim(pick_main_stem(stem))
#> [1] 1000 19add_status_tree() adds the column status_tree based on the status of all stems of each tree.
stem %>%
select(CensusID, treeID, stemID, status) %>%
add_status_tree()
#> # A tibble: 1,320 × 5
#> CensusID treeID stemID status status_tree
#> <int> <int> <int> <chr> <chr>
#> 1 6 104 143 A A
#> 2 6 119 158 A A
#> 3 NA 180 222 G A
#> 4 NA 180 223 G A
#> 5 6 180 224 G A
#> 6 6 180 225 A A
#> 7 6 602 736 A A
#> 8 6 631 775 A A
#> 9 6 647 793 A A
#> 10 6 1086 1339 A A
#> # ℹ 1,310 more rowsadd_index() and friends add columns to a ForestGEO-like dataframe.
stem %>%
select(gx, gy) %>%
add_index()
#> Guessing: plotdim = c(320, 500)
#> * If guess is wrong, provide the correct argument `plotdim`
#> # A tibble: 1,320 × 3
#> gx gy index
#> <dbl> <dbl> <dbl>
#> 1 10.3 245. 13
#> 2 183. 410. 246
#> 3 165. 410. 221
#> 4 165. 410. 221
#> 5 165. 410. 221
#> 6 165. 410. 221
#> 7 149. 414. 196
#> 8 38.3 245. 38
#> 9 143. 411. 196
#> 10 68.9 253. 88
#> # ℹ 1,310 more rowsThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.