R/calculate_dendrometry.R
calculate_dendrometry.RdThis function calculates additional variables and makes aggregations of individual tree measures on the levels of
plot and year
plot, tree species and year
diameter class, plot and year
diameter class, plot, tree species and year
and it makes aggregations of volume data on logs on the levels of
decay stage, plot and year
decay stage, plot, tree species and year
calculate_dendrometry(
data_dendro,
data_deadwood,
data_shoots,
height_model,
plotinfo
)dataframe on tree measures with variables plot_id,
plottype, tree_measure_id, date_dendro, dbh_mm, height_m,
species, alive_dead, decaystage, period, old_id, year,
subcircle, plotarea_ha,...
(output of function load_data_dendrometry())
dataframe on logs with variables plot_id, plottype,
date_dendro, species, decaystage, calc_volume_m3, period and year
(output of function load_data_deadwood())
dataframe on shoots as given from the function
load_data_shoots()
dataframe with model containing 'exp' or 'ln',
coefficients P1 and P2 to calculate height model for each combination of
species, forest_reserve, period and plottype. Height models in .xlsx
generated by Fieldmap can be grouped in a dataframe using function
load_height_models()
dataframe on surveyed plots with variables plot_id,
plottype, forest_reserve, survey_trees, survey_deadw, period and
year_dendro
(output of function load_plotinfo())
List of dataframes that are mentioned in the above description
library(forrescalc)
# (add path to your own fieldmap database here)
path_to_fieldmapdb <-
system.file("example/database/mdb_bosres.sqlite", package = "forrescalc")
data_dendro <- load_data_dendrometry(path_to_fieldmapdb)
data_deadwood <- load_data_deadwood(path_to_fieldmapdb)
data_shoots <- load_data_shoots(path_to_fieldmapdb)
# omit argument 'example_dataset = TRUE' below to use all height models
height_model <- load_height_models(example_dataset = TRUE)
plotinfo <- load_plotinfo(path_to_fieldmapdb)
#> Joining with `by = join_by(forest_reserve, plot_id, plottype, survey_trees)`
calculate_dendrometry(
data_dendro, data_deadwood, data_shoots, height_model, plotinfo)
#> $dendro_by_plot
#> # A tibble: 17 × 16
#> plottype plot_id year period number_of_tree_species number_of_trees_ha
#> <chr> <int> <int> <dbl> <int> <dbl>
#> 1 CA 11000 1986 0 2 0.558
#> 2 CA 11000 2000 1 3 0.651
#> 3 CA 11000 2010 2 3 0.558
#> 4 CA 11000 2020 3 3 0.558
#> 5 CA 21000 2008 1 4 28.6
#> 6 CA 21000 2018 2 3 26.5
#> 7 CA 141100 2007 1 2 8
#> 8 CA 141100 2016 2 2 4
#> 9 CP 101 2002 1 3 364.
#> 10 CP 101 2012 2 2 206.
#> 11 CP 204 2000 1 1 23.9
#> 12 CP 204 2011 2 1 23.9
#> 13 CP 1005 2006 1 1 42.4
#> 14 CP 1005 2016 2 1 42.4
#> 15 CP 2006 2000 1 1 10.6
#> 16 CP 2006 2010 2 1 10.6
#> 17 CP 2006 2020 3 1 10.6
#> # ℹ 10 more variables: stem_number_ha <dbl>, basal_area_alive_m2_ha <dbl>,
#> # basal_area_dead_m2_ha <dbl>, vol_alive_m3_ha <dbl>,
#> # vol_dead_standing_m3_ha <dbl>, vol_bole_alive_m3_ha <dbl>,
#> # vol_bole_dead_m3_ha <dbl>, vol_log_m3_ha <dbl>, vol_deadw_m3_ha <dbl>,
#> # stems_per_tree <dbl>
#>
#> $dendro_by_plot_species
#> # A tibble: 39 × 16
#> plottype plot_id year period species number_of_trees_ha stem_number_ha
#> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 CA 11000 1986 0 7 0.279 0.279
#> 2 CA 11000 1986 0 87 0.279 0.279
#> 3 CA 11000 2000 1 7 0.279 0.279
#> 4 CA 11000 2000 1 16 0.0930 0.0930
#> 5 CA 11000 2000 1 87 0.279 0.279
#> 6 CA 11000 2010 2 7 0.279 0.279
#> 7 CA 11000 2010 2 16 0.0930 0.0930
#> 8 CA 11000 2010 2 87 0.186 0.186
#> 9 CA 11000 2020 3 7 0.279 0.279
#> 10 CA 11000 2020 3 16 0.0930 0.0930
#> # ℹ 29 more rows
#> # ℹ 9 more variables: basal_area_alive_m2_ha <dbl>,
#> # basal_area_dead_m2_ha <dbl>, vol_alive_m3_ha <dbl>,
#> # vol_dead_standing_m3_ha <dbl>, vol_bole_alive_m3_ha <dbl>,
#> # vol_bole_dead_m3_ha <dbl>, vol_log_m3_ha <dbl>, vol_deadw_m3_ha <dbl>,
#> # stems_per_tree <dbl>
#>
#> $dendro_by_diam_plot
#> # A tibble: 125 × 14
#> plottype plot_id year period dbh_class_5cm stem_number_alive_ha
#> <chr> <int> <int> <dbl> <fct> <dbl>
#> 1 CA 11000 1986 0 50 - 55 cm 0.0930
#> 2 CA 11000 1986 0 60 - 65 cm 0.0930
#> 3 CA 11000 1986 0 65 - 70 cm 0.0930
#> 4 CA 11000 1986 0 75 - 80 cm 0.0930
#> 5 CA 11000 1986 0 80 - 85 cm 0.0930
#> 6 CA 11000 1986 0 85 - 90 cm 0.0930
#> 7 CA 11000 2000 1 30 - 35 cm 0.0930
#> 8 CA 11000 2000 1 55 - 60 cm 0.0930
#> 9 CA 11000 2000 1 70 - 75 cm 0.0930
#> 10 CA 11000 2000 1 75 - 80 cm 0.0930
#> # ℹ 115 more rows
#> # ℹ 8 more variables: stem_number_dead_ha <dbl>, basal_area_alive_m2_ha <dbl>,
#> # basal_area_dead_m2_ha <dbl>, vol_alive_m3_ha <dbl>,
#> # vol_dead_standing_m3_ha <dbl>, vol_bole_alive_m3_ha <dbl>,
#> # vol_bole_dead_m3_ha <dbl>, vol_log_m3_ha <dbl>
#>
#> $dendro_by_diam_plot_species
#> # A tibble: 158 × 15
#> plottype plot_id year period species dbh_class_5cm stem_number_alive_ha
#> <chr> <int> <int> <dbl> <dbl> <fct> <dbl>
#> 1 CA 11000 1986 0 7 65 - 70 cm 0.0930
#> 2 CA 11000 1986 0 7 80 - 85 cm 0.0930
#> 3 CA 11000 1986 0 7 85 - 90 cm 0.0930
#> 4 CA 11000 1986 0 87 50 - 55 cm 0.0930
#> 5 CA 11000 1986 0 87 60 - 65 cm 0.0930
#> 6 CA 11000 1986 0 87 75 - 80 cm 0.0930
#> 7 CA 11000 2000 1 7 75 - 80 cm 0.0930
#> 8 CA 11000 2000 1 7 85 - 90 cm 0.0930
#> 9 CA 11000 2000 1 7 95 - 100 cm 0.0930
#> 10 CA 11000 2000 1 16 30 - 35 cm 0.0930
#> # ℹ 148 more rows
#> # ℹ 8 more variables: stem_number_dead_ha <dbl>, basal_area_alive_m2_ha <dbl>,
#> # basal_area_dead_m2_ha <dbl>, vol_alive_m3_ha <dbl>,
#> # vol_dead_standing_m3_ha <dbl>, vol_bole_alive_m3_ha <dbl>,
#> # vol_bole_dead_m3_ha <dbl>, vol_log_m3_ha <dbl>
#>
#> $deadw_by_decay_plot
#> plottype plot_id year period decaystage vol_dead_standing_m3_ha
#> 1 CP 101 2002 1 16 0.0000000
#> 2 CP 101 2002 1 10 0.0000000
#> 3 CP 101 2002 1 12 0.0000000
#> 4 CP 101 2002 1 13 0.0000000
#> 5 CP 204 2000 1 16 0.0000000
#> 6 CP 204 2000 1 13 0.0000000
#> 7 CP 1005 2006 1 16 0.0000000
#> 8 CP 1005 2006 1 13 0.0000000
#> 9 CP 2006 2000 1 12 3.6801507
#> 10 CP 2006 2000 1 16 0.0000000
#> 11 CA 11000 2000 1 16 0.0000000
#> 12 CA 21000 2008 1 12 7.2705860
#> 13 CA 21000 2008 1 16 0.0000000
#> 14 CA 21000 2008 1 13 0.0000000
#> 15 CA 21000 2008 1 14 0.0000000
#> 16 CA 141100 2007 1 16 0.0000000
#> 17 CA 141100 2007 1 12 0.0000000
#> 18 CA 141100 2007 1 13 0.0000000
#> 19 CP 101 2012 2 12 1.0195947
#> 20 CP 101 2012 2 13 0.5865537
#> 21 CP 101 2012 2 16 0.0000000
#> 22 CP 101 2012 2 11 0.0000000
#> 23 CP 204 2011 2 16 0.0000000
#> 24 CP 204 2011 2 13 0.0000000
#> 25 CP 204 2011 2 14 0.0000000
#> 26 CP 1005 2016 2 16 0.0000000
#> 27 CP 2006 2010 2 16 0.0000000
#> 28 CP 2006 2010 2 13 0.0000000
#> 29 CP 2006 2010 2 14 0.0000000
#> 30 CP 2006 2010 2 15 0.0000000
#> 31 CA 11000 2010 2 12 0.6169605
#> 32 CA 11000 2010 2 16 0.0000000
#> 33 CA 11000 2010 2 11 0.0000000
#> 34 CA 11000 2010 2 13 0.0000000
#> 35 CA 11000 2010 2 14 0.0000000
#> 36 CA 21000 2018 2 11 0.0805941
#> 37 CA 21000 2018 2 12 2.4328335
#> 38 CA 21000 2018 2 16 0.0000000
#> 39 CA 21000 2018 2 10 0.0000000
#> 40 CA 21000 2018 2 14 0.0000000
#> 41 CA 141100 2016 2 16 0.0000000
#> 42 CA 141100 2016 2 13 0.0000000
#> 43 CA 141100 2016 2 14 0.0000000
#> 44 CP 2006 2020 3 16 0.0000000
#> 45 CP 2006 2020 3 12 0.0000000
#> 46 CP 2006 2020 3 13 0.0000000
#> 47 CP 2006 2020 3 14 0.0000000
#> 48 CA 11000 2020 3 12 0.6849400
#> 49 CA 11000 2020 3 16 0.0000000
#> 50 CA 11000 2020 3 13 0.0000000
#> 51 CA 11000 2020 3 14 0.0000000
#> 52 CA 11000 1986 0 16 0.0000000
#> vol_bole_dead_m3_ha vol_log_m3_ha
#> 1 0.00000000 0.00000000
#> 2 0.00000000 0.25831240
#> 3 0.00000000 0.09933430
#> 4 0.00000000 0.78390687
#> 5 0.00000000 0.00000000
#> 6 0.00000000 1.82280156
#> 7 0.00000000 0.00000000
#> 8 0.00000000 1.77142988
#> 9 3.34711960 0.00000000
#> 10 0.00000000 0.00000000
#> 11 0.00000000 0.00000000
#> 12 6.06076149 0.00000000
#> 13 0.00000000 0.00000000
#> 14 0.00000000 0.33786122
#> 15 0.00000000 2.28527143
#> 16 0.00000000 0.00000000
#> 17 0.00000000 0.31492000
#> 18 0.00000000 0.16866400
#> 19 1.01959467 1.94059980
#> 20 0.57843873 0.63081356
#> 21 0.00000000 0.00000000
#> 22 0.00000000 0.22030188
#> 23 0.00000000 0.00000000
#> 24 0.00000000 2.42733570
#> 25 0.00000000 0.19856966
#> 26 0.00000000 0.00000000
#> 27 0.00000000 0.00000000
#> 28 0.00000000 3.12851579
#> 29 0.00000000 0.25517843
#> 30 0.00000000 0.04264999
#> 31 0.54898100 0.00000000
#> 32 0.00000000 0.00000000
#> 33 0.00000000 0.92820795
#> 34 0.00000000 0.58741129
#> 35 0.00000000 1.29862986
#> 36 0.05250379 0.00000000
#> 37 2.08903223 0.03972653
#> 38 0.00000000 0.00000000
#> 39 0.00000000 0.55832857
#> 40 0.00000000 0.02916531
#> 41 0.00000000 0.00000000
#> 42 0.00000000 0.53009400
#> 43 0.00000000 0.01212400
#> 44 0.00000000 0.00000000
#> 45 0.00000000 0.13834809
#> 46 0.00000000 4.21210984
#> 47 0.00000000 0.17165745
#> 48 0.54898100 0.00000000
#> 49 0.00000000 0.00000000
#> 50 0.00000000 1.35146314
#> 51 0.00000000 0.84133972
#> 52 0.00000000 0.00000000
#>
#> $deadw_by_decay_plot_species
#> plottype plot_id year period species decaystage vol_dead_standing_m3_ha
#> 1 CP 101 2002 1 16 16 0.00000000
#> 2 CP 101 2002 1 28 16 0.00000000
#> 3 CP 101 2002 1 87 16 0.00000000
#> 4 CP 101 2002 1 16 13 0.00000000
#> 5 CP 101 2002 1 87 10 0.00000000
#> 6 CP 101 2002 1 87 12 0.00000000
#> 7 CP 101 2002 1 87 13 0.00000000
#> 8 CP 204 2000 1 26 16 0.00000000
#> 9 CP 204 2000 1 26 13 0.00000000
#> 10 CP 1005 2006 1 87 16 0.00000000
#> 11 CP 1005 2006 1 87 13 0.00000000
#> 12 CP 2006 2000 1 7 16 0.00000000
#> 13 CP 2006 2000 1 87 12 3.68015070
#> 14 CA 11000 2000 1 7 16 0.00000000
#> 15 CA 11000 2000 1 16 16 0.00000000
#> 16 CA 11000 2000 1 87 16 0.00000000
#> 17 CA 21000 2008 1 6 16 0.00000000
#> 18 CA 21000 2008 1 7 16 0.00000000
#> 19 CA 21000 2008 1 16 12 0.04587028
#> 20 CA 21000 2008 1 16 16 0.00000000
#> 21 CA 21000 2008 1 87 12 7.22471567
#> 22 CA 21000 2008 1 87 16 0.00000000
#> 23 CA 21000 2008 1 16 13 0.00000000
#> 24 CA 21000 2008 1 16 14 0.00000000
#> 25 CA 21000 2008 1 87 13 0.00000000
#> 26 CA 141100 2007 1 28 16 0.00000000
#> 27 CA 141100 2007 1 87 16 0.00000000
#> 28 CA 141100 2007 1 87 12 0.00000000
#> 29 CA 141100 2007 1 87 13 0.00000000
#> 30 CP 101 2012 2 16 16 0.00000000
#> 31 CP 101 2012 2 28 12 1.01959467
#> 32 CP 101 2012 2 28 13 0.58655366
#> 33 CP 101 2012 2 87 16 0.00000000
#> 34 CP 101 2012 2 16 12 0.00000000
#> 35 CP 101 2012 2 87 11 0.00000000
#> 36 CP 101 2012 2 87 13 0.00000000
#> 37 CP 204 2011 2 26 16 0.00000000
#> 38 CP 204 2011 2 26 13 0.00000000
#> 39 CP 204 2011 2 26 14 0.00000000
#> 40 CP 1005 2016 2 87 16 0.00000000
#> 41 CP 2006 2010 2 7 16 0.00000000
#> 42 CP 2006 2010 2 7 14 0.00000000
#> 43 CP 2006 2010 2 7 15 0.00000000
#> 44 CP 2006 2010 2 87 13 0.00000000
#> 45 CA 11000 2010 2 7 16 0.00000000
#> 46 CA 11000 2010 2 16 16 0.00000000
#> 47 CA 11000 2010 2 87 12 0.61696050
#> 48 CA 11000 2010 2 87 16 0.00000000
#> 49 CA 11000 2010 2 7 14 0.00000000
#> 50 CA 11000 2010 2 87 11 0.00000000
#> 51 CA 11000 2010 2 87 13 0.00000000
#> 52 CA 21000 2018 2 7 11 0.08059410
#> 53 CA 21000 2018 2 7 16 0.00000000
#> 54 CA 21000 2018 2 16 12 0.01150031
#> 55 CA 21000 2018 2 16 16 0.00000000
#> 56 CA 21000 2018 2 87 12 2.42133316
#> 57 CA 21000 2018 2 87 16 0.00000000
#> 58 CA 21000 2018 2 16 10 0.00000000
#> 59 CA 21000 2018 2 16 14 0.00000000
#> 60 CA 21000 2018 2 87 10 0.00000000
#> 61 CA 141100 2016 2 28 16 0.00000000
#> 62 CA 141100 2016 2 87 16 0.00000000
#> 63 CA 141100 2016 2 6 14 0.00000000
#> 64 CA 141100 2016 2 87 13 0.00000000
#> 65 CP 2006 2020 3 7 16 0.00000000
#> 66 CP 2006 2020 3 7 12 0.00000000
#> 67 CP 2006 2020 3 7 14 0.00000000
#> 68 CP 2006 2020 3 87 13 0.00000000
#> 69 CP 2006 2020 3 87 14 0.00000000
#> 70 CA 11000 2020 3 7 16 0.00000000
#> 71 CA 11000 2020 3 16 16 0.00000000
#> 72 CA 11000 2020 3 87 12 0.68493999
#> 73 CA 11000 2020 3 87 16 0.00000000
#> 74 CA 11000 2020 3 7 14 0.00000000
#> 75 CA 11000 2020 3 87 13 0.00000000
#> 76 CA 11000 1986 0 7 16 0.00000000
#> 77 CA 11000 1986 0 87 16 0.00000000
#> vol_bole_dead_m3_ha vol_log_m3_ha
#> 1 0.00000000 0.00000000
#> 2 0.00000000 0.00000000
#> 3 0.00000000 0.00000000
#> 4 0.00000000 0.28138987
#> 5 0.00000000 0.25831240
#> 6 0.00000000 0.09933430
#> 7 0.00000000 0.50251700
#> 8 0.00000000 0.00000000
#> 9 0.00000000 1.82280156
#> 10 0.00000000 0.00000000
#> 11 0.00000000 1.77142988
#> 12 0.00000000 0.00000000
#> 13 3.34711960 0.00000000
#> 14 0.00000000 0.00000000
#> 15 0.00000000 0.00000000
#> 16 0.00000000 0.00000000
#> 17 0.00000000 0.00000000
#> 18 0.00000000 0.00000000
#> 19 0.04587028 0.00000000
#> 20 0.00000000 0.00000000
#> 21 6.01489120 0.00000000
#> 22 0.00000000 0.00000000
#> 23 0.00000000 0.12717755
#> 24 0.00000000 2.28527143
#> 25 0.00000000 0.21068367
#> 26 0.00000000 0.00000000
#> 27 0.00000000 0.00000000
#> 28 0.00000000 0.31492000
#> 29 0.00000000 0.16866400
#> 30 0.00000000 0.00000000
#> 31 1.01959467 0.00000000
#> 32 0.57843873 0.00000000
#> 33 0.00000000 0.00000000
#> 34 0.00000000 1.94059980
#> 35 0.00000000 0.22030188
#> 36 0.00000000 0.63081356
#> 37 0.00000000 0.00000000
#> 38 0.00000000 2.42733570
#> 39 0.00000000 0.19856966
#> 40 0.00000000 0.00000000
#> 41 0.00000000 0.00000000
#> 42 0.00000000 0.25517843
#> 43 0.00000000 0.04264999
#> 44 0.00000000 3.12851579
#> 45 0.00000000 0.00000000
#> 46 0.00000000 0.00000000
#> 47 0.54898100 0.00000000
#> 48 0.00000000 0.00000000
#> 49 0.00000000 1.29862986
#> 50 0.00000000 0.92820795
#> 51 0.00000000 0.58741129
#> 52 0.05250379 0.00000000
#> 53 0.00000000 0.00000000
#> 54 0.01150031 0.03972653
#> 55 0.00000000 0.00000000
#> 56 2.07753192 0.00000000
#> 57 0.00000000 0.00000000
#> 58 0.00000000 0.27540408
#> 59 0.00000000 0.02916531
#> 60 0.00000000 0.28292449
#> 61 0.00000000 0.00000000
#> 62 0.00000000 0.00000000
#> 63 0.00000000 0.01212400
#> 64 0.00000000 0.53009400
#> 65 0.00000000 0.00000000
#> 66 0.00000000 0.13834809
#> 67 0.00000000 0.05132216
#> 68 0.00000000 4.21210984
#> 69 0.00000000 0.12033528
#> 70 0.00000000 0.00000000
#> 71 0.00000000 0.00000000
#> 72 0.54898100 0.00000000
#> 73 0.00000000 0.00000000
#> 74 0.00000000 0.84133972
#> 75 0.00000000 1.35146314
#> 76 0.00000000 0.00000000
#> 77 0.00000000 0.00000000
#>