Building tables of abundance and basal area
Mauro Lepore
2018-06-13
Code
I developed these functions (based on notes in section Task below):
pick_plotname()to make it clear and easy to pick thePlotNameyou want from a ViewFullTable that may have multiple plots. It defaults to use the fist census in alphabetical order.pick_dbh_min()to make it clear and easy to pick trees of or over a specific DBH value.byyr_abundance()andbyyr_basal_area()to calculate abundance and basal area per (mean) year. In addition to their primary calculation, both of these functions do the following:- Check for inconsistent statuses.
- Fix wrong status automatically or die trying.
- Determine the status of each tree based on the status of its (multiple) stem(s).
- Drop “dead” status (includes “alive”, “missing”, “gone”, etc.).
- Drop rows where
DBH = NA: Some alive trees may have missing DBH. I exclude all rows whereDBH = NAbecause missing values can’t be used for calculating basal area; and although those rows can be used to count abundance, they are better excluded from abundance tables for consistency with basal area tables. - Drop rows where
ExactDate == NAif any. - Calculate year as a round average of
ExactDatebyPlotCensusNumber.
Comparing reference tables with code output
Reference tables
Aundance
Downloaded from https://dash.ucdavis.edu/stash/dataset/doi:10.15146/R3MM4V.
#> [1] "bciAbundTable.tab"
#> # A tibble: 328 x 11
#> Latin Family Authority `1982` `1985` `1990` `1995` `2000` `2005` `2010`
#> <chr> <chr> <chr> <int> <int> <int> <int> <int> <int> <int>
#> 1 Abar~ Fabac~ (Pittier~ 10 10 11 12 12 16 32
#> 2 Acal~ Eupho~ Jacq. 1562 1200 817 523 488 741 1019
#> 3 Acal~ Eupho~ Jacq. 79 66 44 42 43 52 52
#> 4 Adel~ Eupho~ (Müll.Ar~ 346 315 280 219 163 143 143
#> 5 Aegi~ Lamia~ Moldenke 136 126 92 77 62 44 40
#> 6 Alch~ Eupho~ Pax & K.~ 385 314 266 228 229 229 319
#> 7 Alch~ Eupho~ Sw. 2 2 3 2 1 1 1
#> 8 Alib~ Rubia~ Delprete~ 1 1 1 1 1 1 1
#> 9 Alib~ Rubia~ (Rich.) ~ 304 342 378 379 357 372 417
#> 10 Allo~ Sapin~ Radlk. 175 171 153 123 112 103 112
#> # ... with 318 more rows, and 1 more variable: `2015` <int>#> [1] "cocoliAbundTable.tab"
#> # A tibble: 176 x 6
#> Latin Family Authority `1994` `1997` `1998`
#> <chr> <chr> <chr> <int> <int> <int>
#> 1 Acacia melanoceras Fabaceae Beurl. 23 19 19
#> 2 Acalypha diversifolia Euphorbiaceae Jacq. 14 18 22
#> 3 Acalypha macrostachya Euphorbiaceae Jacq. 1 2 2
#> 4 Adelia triloba Euphorbiaceae (Müll.Arg.)~ 5 6 6
#> 5 Aegiphila panamensis Lamiaceae Moldenke 2 1 1
#> 6 Albizia adinocephala Fabaceae (Donn. Sm.)~ 55 53 57
#> 7 Albizia procera Fabaceae (Roxb.) Ben~ 2 2 2
#> 8 Alchornea costaricensis Euphorbiaceae Pax & K. Ho~ 2 1 1
#> 9 Alibertia edulis Rubiaceae (Rich.) A. ~ 253 228 224
#> 10 Alseis blackiana Rubiaceae Hemsl. 4 4 4
#> # ... with 166 more rows#> [1] "shermanAbundTable.tab"
#> # A tibble: 270 x 7
#> Latin Family Authority `1996` `1997` `1999` `2009`
#> <chr> <chr> <chr> <int> <int> <int> <int>
#> 1 Abarema barbouriana Fabaceae (Standl.) B~ 10 12 12 10
#> 2 Acacia melanoceras Fabaceae Beurl. 1 1 0 0
#> 3 Acacia sp.1 Fabaceae <NA> 0 0 0 4
#> 4 Acalypha diversifolia Euphorb~ Jacq. 9 7 5 20
#> 5 Aegiphila panamensis Lamiace~ Moldenke 1 0 0 0
#> 6 Alchornea latifolia Euphorb~ Sw. 93 90 94 96
#> 7 Alchornea sp.3 Euphorb~ <NA> 33 24 22 12
#> 8 Alibertia edulis Rubiace~ (Rich.) A. ~ 2 2 2 0
#> 9 Amaioua corymbosa Rubiace~ Kunth 89 88 89 83
#> 10 Andira inermis Fabaceae (W. Wright)~ 41 38 38 37
#> # ... with 260 more rowsSee also: https://forestgeo.si.edu/bci-abundance-all-tree-species-50-ha-plot-1982-2005-saplings-and-trees
Example:
Basal Area
I found no tables of basal area at https://dash.ucdavis.edu/stash/dataset/doi:10.15146/R3MM4V. But here are some other references:
https://forestgeo.si.edu/bci-abundance-all-tree-species-50-ha-plot-1982-2005-saplings-and-trees
https://forestgeo.si.edu/bci-abundance-all-tree-species-50-ha-plot-1982-2005-trees
Example:
Code output
Abundance
#> [1] "bci_abundance_table.csv"
#> # A tibble: 325 x 10
#> species Family `1982` `1985` `1990` `1995` `2000` `2005` `2010` `2015`
#> <chr> <chr> <int> <dbl> <int> <int> <dbl> <int> <int> <int>
#> 1 Abarema~ Fabac~ 10 10 11 12 12 16 33 44
#> 2 Acacia ~ Fabac~ 6 7 14 14 11 24 54 51
#> 3 Acalyph~ Eupho~ 1894 1530 1159 746 762 1134 1615 2353
#> 4 Acalyph~ Eupho~ 115 95 77 64 71 107 91 107
#> 5 Adelia ~ Eupho~ 490 424 726 573 565 517 529 443
#> 6 Aegiphi~ Lamia~ 142 128 94 80 63 45 40 26
#> 7 Alchorn~ Eupho~ 411 351 407 345 316 325 427 391
#> 8 Alchorn~ Eupho~ 3 3 5 3 1 1 1 0
#> 9 Alibert~ Rubia~ 363 417 492 490 460 475 543 592
#> 10 Allophy~ Sapin~ 204 203 257 209 177 165 188 182
#> # ... with 315 more rows#> [1] "cocoli_abundance_table.csv"
#> # A tibble: 175 x 5
#> species Family `1994` `1997` `1998`
#> <chr> <chr> <int> <int> <int>
#> 1 Acacia melanoceras Fabaceae-mimosoideae 23 19 19
#> 2 Acalypha diversifolia Euphorbiaceae 24 32 30
#> 3 Acalypha macrostachya Euphorbiaceae 1 2 3
#> 4 Adelia triloba Euphorbiaceae 5 7 7
#> 5 Aegiphila panamensis Lamiaceae 2 1 1
#> 6 Albizia adinocephala Fabaceae-mimosoideae 56 53 57
#> 7 Albizia procera Fabaceae-mimosoideae 2 3 3
#> 8 Alchornea costaricensis Euphorbiaceae 2 1 1
#> 9 Alibertia edulis Rubiaceae 340 304 306
#> 10 Alseis blackiana Rubiaceae 4 4 4
#> # ... with 165 more rows#> [1] "sherman_abundance_table.csv"
#> # A tibble: 274 x 7
#> species Family `1996` `1997` `1999` `2009` `2016`
#> <chr> <chr> <int> <int> <int> <int> <int>
#> 1 Abarema barbouriana Fabaceae-mi~ 10 12 12 10 10
#> 2 Acacia melanoceras Fabaceae-mi~ 1 1 0 0 0
#> 3 Acalypha diversifolia Euphorbiace~ 12 10 10 34 34
#> 4 Aegiphila panamensis Lamiaceae 1 0 0 0 0
#> 5 Alchornea costaricensis Euphorbiace~ 1 1 1 1 1
#> 6 Alchornea latifolia Euphorbiace~ 140 120 123 118 102
#> 7 Alibertia edulis Rubiaceae 2 2 2 0 0
#> 8 Amaioua corymbosa Rubiaceae 93 90 92 87 92
#> 9 Andira inermis Fabaceae-pa~ 41 38 39 38 36
#> 10 Annona spraguei Annonaceae 15 9 7 13 13
#> # ... with 264 more rowsBasal area
The values here are orders of magnitude greater that those reported in Condit et al.. The issue is likely related to this comment:
To standardize a density per unit area, each count must be divided by the size of the plot: 50 ha at Barro Colorado, 4 ha at Cocoli, and 5.96 ha at Sherman.
But I don’t still understand what precise standardization I should do (TODO: Discuss with Suzanne).
#> [1] "bci_basal_area_table.csv"
#> # A tibble: 325 x 10
#> species Family `1982` `1985` `1990` `1995` `2000` `2005` `2010` `2015`
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Abarema~ Fabac~ 1.25e5 2.04e5 3.13e5 4.22e5 5.41e5 6.44e5 7.64e5 9.29e5
#> 2 Acacia ~ Fabac~ 4.61e4 3.20e4 4.10e4 6.11e4 3.05e4 4.34e4 9.39e4 1.17e5
#> 3 Acalyph~ Eupho~ 1.03e6 1.07e6 9.15e5 5.88e5 5.20e5 6.14e5 8.89e5 1.23e6
#> 4 Acalyph~ Eupho~ 1.96e5 1.44e5 1.34e5 8.73e4 9.56e4 1.19e5 1.25e5 1.48e5
#> 5 Adelia ~ Eupho~ 3.46e6 3.47e6 3.50e6 3.08e6 2.94e6 2.52e6 2.52e6 2.27e6
#> 6 Aegiphi~ Lamia~ 5.40e5 5.19e5 5.22e5 5.07e5 4.71e5 3.79e5 3.05e5 2.63e5
#> 7 Alchorn~ Eupho~ 1.32e7 1.38e7 1.74e7 1.37e7 1.16e7 1.23e7 1.18e7 1.17e7
#> 8 Alchorn~ Eupho~ 4.41e4 4.69e4 4.98e4 2.35e4 3.37e4 4.01e4 4.83e4 0.
#> 9 Alibert~ Rubia~ 2.19e5 2.37e5 3.18e5 3.12e5 3.04e5 3.11e5 3.22e5 3.61e5
#> 10 Allophy~ Sapin~ 8.63e5 9.09e5 8.55e5 8.51e5 7.74e5 8.89e5 9.54e5 9.52e5
#> # ... with 315 more rows#> [1] "cocoli_basal_area_table.csv"
#> # A tibble: 175 x 5
#> species Family `1994` `1997` `1998`
#> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 Acacia melanoceras Fabaceae-mimosoideae 7996. 5018. 5177.
#> 2 Acalypha diversifolia Euphorbiaceae 14066. 17423. 18278.
#> 3 Acalypha macrostachya Euphorbiaceae 113. 306. 384.
#> 4 Adelia triloba Euphorbiaceae 30559. 33428. 34488.
#> 5 Aegiphila panamensis Lamiaceae 2684. 154. 154.
#> 6 Albizia adinocephala Fabaceae-mimosoideae 342662. 273660. 257362.
#> 7 Albizia procera Fabaceae-mimosoideae 911. 1792. 2088.
#> 8 Alchornea costaricensis Euphorbiaceae 9645. 11310. 11499.
#> 9 Alibertia edulis Rubiaceae 199436. 191955. 189378.
#> 10 Alseis blackiana Rubiaceae 93449. 99678. 102224.
#> # ... with 165 more rows#> [1] "sherman_basal_area_table.csv"
#> # A tibble: 274 x 7
#> species Family `1996` `1997` `1999` `2009` `2016`
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Abarema barbouriana Fabaceae-m~ 123042. 1.34e5 1.47e5 3.07e5 4.46e5
#> 2 Acacia melanoceras Fabaceae-m~ 254. 3.14e2 0. 0. 0.
#> 3 Acalypha diversifolia Euphorbiac~ 6577. 2.69e3 2.59e3 1.05e4 1.24e4
#> 4 Aegiphila panamensis Lamiaceae 1134. 0. 0. 0. 0.
#> 5 Alchornea costaricensis Euphorbiac~ 29255. 2.99e4 2.96e4 3.24e4 3.24e4
#> 6 Alchornea latifolia Euphorbiac~ 378432. 3.60e5 3.65e5 3.58e5 3.20e5
#> 7 Alibertia edulis Rubiaceae 827. 3.40e2 3.40e2 0. 0.
#> 8 Amaioua corymbosa Rubiaceae 194806. 1.97e5 1.99e5 1.88e5 2.05e5
#> 9 Andira inermis Fabaceae-p~ 360518. 3.73e5 3.81e5 3.16e5 1.95e5
#> 10 Annona spraguei Annonaceae 105990. 9.59e4 2.74e4 1.02e4 1.16e4
#> # ... with 264 more rowsTask
Cocoli should have the exact same number of censuses, but Sherman will have one more census.
– Suzanne
- Pick stems 1 cm and over (at 1.3 m)
All trees at least 1 cm diameter at breast height were censused in three sites in Panama.
- Determine year as average or median year by census/plotcensusnumber
In the datasets, you should look at the “plotcensusnumber” or “censusid” instead of the years. Some censuses may take more than one year …. The years in the publications refer to the average or the median year.
– Suzanne
Example from https://forestgeo.si.edu/bci-abundance-all-tree-species-50-ha-plot-1982-2005-saplings-and-trees:
- Pick alive trees.
The three accompanying tables give the population size of living individuals of all species in every census at the three sites.
Individuals with multiple stems from one root base were counted as single trees.
To standardize a density per unit area, each count must be divided by the size of the plot: 50 ha at Barro Colorado, 4 ha at Cocoli, and 5.96 ha at Sherman.