R/calc_intact_deadwood.R
calc_intact_deadwood.RdIn Core Areas, some lying deadwood is marked as 'complete tree' by giving
variable intact_fragm value 10 (intact) instead of 20 (fragment) to save
time (while in general all fragments are measured separately).
This function calculates the total volume (sum of bole and crown volume) for
this intact deadwood and keeps the initial volume in case of fragments.
calc_intact_deadwood(data_deadwood)dataframe on logs with variables plot_id, plottype,
date_dendro, species, decaystage, intact_fragm, calc_volume_m3,
period and year (output of function load_data_deadwood()), in which
calc_volume_m3 should be replaced by a more precise calculation
A similar dataframe (data_deadwood) in which the volume of intact
deadwood is replaced by a volume calculated based on tariffs.
Intermediate results vol_crown_m3 and vol_bole_m3 are added as columns
(which are NA in case of deadwood fragments).
library(forrescalc)
# (add path to your own fieldmap database here)
path_to_fieldmapdb <-
system.file("example/database/mdb_bosres.sqlite", package = "forrescalc")
data_deadwood <- load_data_deadwood(path_to_fieldmapdb)
calc_intact_deadwood(data_deadwood)
#> forest_reserve plot_id plottype period year date_dendro totalplotarea_ha
#> 1 Everzwijnbad 101 CP 1 2002 2002-12-01 0.1017876
#> 2 Everzwijnbad 101 CP 1 2002 2002-12-01 0.1017876
#> 3 Everzwijnbad 101 CP 1 2002 2002-12-01 0.1017876
#> 4 Everzwijnbad 101 CP 1 2002 2002-12-01 0.1017876
#> 5 Withoefse heide 204 CP 1 2000 2000-07-01 0.1257000
#> 6 Withoefse heide 204 CP 1 2000 2000-07-01 0.1257000
#> 7 Withoefse heide 204 CP 1 2000 2000-07-01 0.1257000
#> 8 Liedekerke 1005 CP 1 2006 2007-01-01 0.0706858
#> 9 Harras 21000 CA 1 2008 2009-03-01 0.9800008
#> 10 Harras 21000 CA 1 2008 2009-03-01 0.9800008
#> 11 Harras 21000 CA 1 2008 2009-03-01 0.9800008
#> 12 Harras 21000 CA 1 2008 2009-03-01 0.9800008
#> 13 Harras 21000 CA 1 2008 2009-03-01 0.9800008
#> 14 Harras 21000 CA 1 2008 2009-03-01 0.9800008
#> 15 Sevendonck A 141100 CA 1 2007 2007-10-01 0.4989261
#> 16 Sevendonck A 141100 CA 1 2007 2007-10-01 0.4989261
#> 17 Sevendonck A 141100 CA 1 2007 2007-10-01 0.4989261
#> 18 Everzwijnbad 101 CP 2 2012 2013-01-10 0.1017876
#> 19 Everzwijnbad 101 CP 2 2012 2013-01-10 0.1017876
#> 20 Everzwijnbad 101 CP 2 2012 2013-01-10 0.1017876
#> 21 Everzwijnbad 101 CP 2 2012 2013-01-10 0.1017876
#> 22 Everzwijnbad 101 CP 2 2012 2013-01-10 0.1017876
#> 23 Withoefse heide 204 CP 2 2011 2012-03-01 0.1257000
#> 24 Withoefse heide 204 CP 2 2011 2012-03-01 0.1257000
#> 25 Withoefse heide 204 CP 2 2011 2012-03-01 0.1257000
#> 26 Kersselaerspleyn 2006 CP 2 2010 2010-06-17 0.2827000
#> 27 Kersselaerspleyn 2006 CP 2 2010 2010-06-17 0.2827000
#> 28 Kersselaerspleyn 2006 CP 2 2010 2010-06-17 0.2827000
#> 29 Kersselaerspleyn 2006 CP 2 2010 2010-06-17 0.2827000
#> 30 Kersselaerspleyn 2006 CP 2 2010 2010-06-17 0.2827000
#> 31 Kersselaerspleyn 2006 CP 2 2010 2010-06-17 0.2827000
#> 32 Kersselaerspleyn 11000 CA 2 2010 2010-06-01 10.7485378
#> 33 Kersselaerspleyn 11000 CA 2 2010 2010-06-01 10.7485378
#> 34 Kersselaerspleyn 11000 CA 2 2010 2010-06-01 10.7485378
#> 35 Kersselaerspleyn 11000 CA 2 2010 2010-06-01 10.7485378
#> 36 Harras 21000 CA 2 2018 2018-09-03 0.9800008
#> 37 Harras 21000 CA 2 2018 2018-09-03 0.9800008
#> 38 Harras 21000 CA 2 2018 2018-09-03 0.9800008
#> 39 Harras 21000 CA 2 2018 2018-09-03 0.9800008
#> 40 Harras 21000 CA 2 2018 2018-09-03 0.9800008
#> 41 Harras 21000 CA 2 2018 2018-09-03 0.9800008
#> 42 Sevendonck A 141100 CA 2 2016 2017-02-06 0.4989261
#> 43 Sevendonck A 141100 CA 2 2016 2017-02-06 0.4989261
#> 44 Sevendonck A 141100 CA 2 2016 2017-02-06 0.4989261
#> 45 Sevendonck A 141100 CA 2 2016 2017-02-06 0.4989261
#> 46 Kersselaerspleyn 2006 CP 3 2020 2020-12-03 0.2827000
#> 47 Kersselaerspleyn 2006 CP 3 2020 2020-12-03 0.2827000
#> 48 Kersselaerspleyn 2006 CP 3 2020 2020-12-03 0.2827000
#> 49 Kersselaerspleyn 2006 CP 3 2020 2020-12-03 0.2827000
#> 50 Kersselaerspleyn 2006 CP 3 2020 2020-12-03 0.2827000
#> 51 Kersselaerspleyn 2006 CP 3 2020 2020-12-03 0.2827000
#> 52 Kersselaerspleyn 11000 CA 3 2020 2020-09-11 10.7485378
#> 53 Kersselaerspleyn 11000 CA 3 2020 2020-09-11 10.7485378
#> 54 Kersselaerspleyn 11000 CA 3 2020 2020-09-11 10.7485378
#> 55 Kersselaerspleyn 11000 CA 3 2020 2020-09-11 10.7485378
#> 56 Kersselaerspleyn 11000 CA 2 2010 2010-06-01 10.7485378
#> 57 Kersselaerspleyn 11000 CA 2 2010 2010-06-01 10.7485378
#> 58 Kersselaerspleyn 11000 CA 3 2020 2020-09-11 10.7485378
#> 59 Kersselaerspleyn 11000 CA 3 2020 2020-09-11 10.7485378
#> plotarea_ha lying_deadw_id species decaystage intact_fragm calc_volume_m3
#> 1 0.10178760 11587 87 12 20 0.010111
#> 2 0.10178760 11626 87 13 20 0.051150
#> 3 0.10178760 11629 16 13 20 0.028642
#> 4 0.10178760 21595 87 10 20 0.026293
#> 5 0.12566371 4652 26 13 20 0.031397
#> 6 0.12566371 4654 26 13 20 0.132376
#> 7 0.12566371 4656 26 13 20 0.065287
#> 8 0.07068583 256 87 13 20 0.125215
#> 9 0.98000000 1 87 13 20 0.070122
#> 10 0.98000000 2 87 13 20 0.091488
#> 11 0.98000000 3 87 13 20 0.044860
#> 12 0.98000000 4 16 13 20 0.096259
#> 13 0.98000000 37 16 14 20 2.239566
#> 14 0.98000000 38 16 13 20 0.028375
#> 15 0.50000000 48 87 13 20 0.046782
#> 16 0.50000000 50 87 12 20 0.157460
#> 17 0.50000000 51 87 13 20 0.037550
#> 18 0.10178760 1 87 13 20 0.025009
#> 19 0.10178760 2 16 12 20 0.072072
#> 20 0.10178760 3 16 12 20 0.125457
#> 21 0.10178760 4 87 11 20 0.022424
#> 22 0.10178760 5 87 13 20 0.039200
#> 23 0.12566371 1 26 14 20 0.024953
#> 24 0.12566371 2 26 13 20 0.075955
#> 25 0.12566371 3 26 13 20 0.229073
#> 26 0.28274334 1 7 14 20 0.054496
#> 27 0.28274334 2 7 14 20 0.017654
#> 28 0.28274334 3 87 13 20 0.023561
#> 29 0.28274334 4 87 13 20 0.067066
#> 30 0.28274334 5 87 13 20 0.793940
#> 31 0.28274334 6 7 15 20 0.012059
#> 32 10.74850000 496 7 14 20 2.168861
#> 33 10.74850000 497 7 14 20 5.337756
#> 34 10.74850000 498 7 14 20 6.451706
#> 35 10.74850000 699 87 13 20 2.452648
#> 36 0.98000000 1 87 10 20 0.248578
#> 37 0.98000000 2 87 10 20 0.012389
#> 38 0.98000000 3 87 10 20 0.016299
#> 39 0.98000000 18 16 10 20 0.269896
#> 40 0.98000000 26 16 14 20 0.028582
#> 41 0.98000000 1002 16 12 20 0.038932
#> 42 0.50000000 7 6 14 20 0.006062
#> 43 0.50000000 9 87 13 20 0.005201
#> 44 0.50000000 20 87 13 20 0.061579
#> 45 0.50000000 26 87 13 20 0.198267
#> 46 0.28274334 1 7 14 20 0.014511
#> 47 0.28274334 2 87 13 20 0.636307
#> 48 0.28274334 3 7 12 20 0.016680
#> 49 0.28274334 4 87 14 20 0.034024
#> 50 0.28274334 5 7 12 20 0.022437
#> 51 0.28274334 8 87 13 20 0.554639
#> 52 10.74850000 496 7 14 20 0.974255
#> 53 10.74850000 497 7 14 20 3.472722
#> 54 10.74850000 498 7 14 20 4.596163
#> 55 10.74850000 699 87 13 20 2.452139
#> 56 10.74850000 687 87 13 10 3.861142
#> 57 10.74850000 701 87 11 10 9.976843
#> 58 10.74850000 687 87 13 10 3.861142
#> 59 10.74850000 701 87 13 10 8.212920
#> calc_length_m total_length_m min_diam_mm max_diam_mm dbh_class_5cm r_A1
#> 1 1.287 3.283 10 10 <NA> 2.25
#> 2 5.368 5.368 100 120 10 - 15 cm 2.25
#> 3 8.226 8.255 10 110 10 - 15 cm 2.25
#> 4 4.760 4.760 10 140 10 - 15 cm 2.25
#> 5 5.312 5.312 10 145 10 - 15 cm 20.00
#> 6 9.713 9.712 10 223 20 - 25 cm 20.00
#> 7 9.593 9.593 10 156 15 - 20 cm 20.00
#> 8 5.171 5.171 150 200 20 - 25 cm 2.25
#> 9 5.368 8.754 70 250 25 - 30 cm NA
#> 10 6.436 6.435 70 190 15 - 20 cm NA
#> 11 3.825 3.825 80 160 15 - 20 cm NA
#> 12 5.415 5.415 130 170 15 - 20 cm NA
#> 13 17.631 17.632 220 560 55 - 60 cm NA
#> 14 3.406 3.406 85 120 10 - 15 cm NA
#> 15 5.271 5.654 90 120 10 - 15 cm NA
#> 16 4.882 19.084 10 230 20 - 25 cm NA
#> 17 0.948 19.089 10 230 20 - 25 cm NA
#> 18 2.044 3.278 90 140 10 - 15 cm 2.25
#> 19 9.406 11.548 60 150 15 - 20 cm 2.25
#> 20 12.979 15.052 40 190 15 - 20 cm 2.25
#> 21 3.399 3.399 60 120 10 - 15 cm 2.25
#> 22 2.843 2.843 65 190 15 - 20 cm 2.25
#> 23 2.597 2.597 90 130 10 - 15 cm 20.00
#> 24 7.655 7.655 70 150 15 - 20 cm 20.00
#> 25 9.220 9.220 120 230 20 - 25 cm 20.00
#> 26 3.540 3.540 140 140 10 - 15 cm 3.00
#> 27 1.561 1.561 120 120 10 - 15 cm 3.00
#> 28 3.249 3.249 70 120 10 - 15 cm 3.00
#> 29 2.245 2.245 190 200 20 - 25 cm 3.00
#> 30 18.749 24.985 110 300 30 - 35 cm 3.00
#> 31 3.278 12.089 22 330 30 - 35 cm 3.00
#> 32 18.459 18.450 150 490 45 - 50 cm NA
#> 33 15.984 15.984 560 740 70 - 75 cm NA
#> 34 33.763 33.763 180 750 75 - 80 cm NA
#> 35 20.599 28.867 130 520 50 - 55 cm NA
#> 36 8.624 8.624 40 310 30 - 35 cm NA
#> 37 4.263 4.263 10 100 10 - 15 cm NA
#> 38 4.681 4.681 10 110 10 - 15 cm NA
#> 39 16.184 16.184 70 210 20 - 25 cm NA
#> 40 1.615 1.615 140 160 15 - 20 cm NA
#> 41 7.868 7.868 30 120 10 - 15 cm NA
#> 42 0.242 7.725 70 180 15 - 20 cm NA
#> 43 0.340 4.882 120 140 10 - 15 cm NA
#> 44 6.858 6.858 70 140 10 - 15 cm NA
#> 45 9.926 9.926 90 220 20 - 25 cm NA
#> 46 2.531 2.531 70 100 10 - 15 cm 3.00
#> 47 18.455 24.593 80 280 25 - 30 cm 3.00
#> 48 2.351 2.351 90 100 10 - 15 cm 3.00
#> 49 2.206 2.206 130 150 15 - 20 cm 3.00
#> 50 2.847 2.847 90 110 10 - 15 cm 3.00
#> 51 19.844 23.716 40 280 25 - 30 cm 3.00
#> 52 7.027 7.027 400 440 40 - 45 cm NA
#> 53 15.984 15.984 330 700 70 - 75 cm NA
#> 54 31.056 31.056 230 610 60 - 65 cm NA
#> 55 20.595 28.886 130 520 50 - 55 cm NA
#> 56 30.563 30.563 130 550 55 - 60 cm NA
#> 57 34.048 34.048 80 820 80 - 85 cm NA
#> 58 30.563 30.563 130 550 55 - 60 cm NA
#> 59 34.048 34.048 80 750 75 - 80 cm NA
#> r_A2 r_A3 r_A4 length_core_area_m width_core_area_m core_area_ha
#> 1 4.5 9 18 NA NA NA
#> 2 4.5 9 18 NA NA NA
#> 3 4.5 9 18 NA NA NA
#> 4 4.5 9 18 NA NA NA
#> 5 20.0 20 20 NA NA NA
#> 6 20.0 20 20 NA NA NA
#> 7 20.0 20 20 NA NA NA
#> 8 4.5 15 15 NA NA NA
#> 9 NA NA NA 140 70 0.9800
#> 10 NA NA NA 140 70 0.9800
#> 11 NA NA NA 140 70 0.9800
#> 12 NA NA NA 140 70 0.9800
#> 13 NA NA NA 140 70 0.9800
#> 14 NA NA NA 140 70 0.9800
#> 15 NA NA NA 100 50 0.5000
#> 16 NA NA NA 100 50 0.5000
#> 17 NA NA NA 100 50 0.5000
#> 18 4.5 9 18 NA NA NA
#> 19 4.5 9 18 NA NA NA
#> 20 4.5 9 18 NA NA NA
#> 21 4.5 9 18 NA NA NA
#> 22 4.5 9 18 NA NA NA
#> 23 20.0 20 20 NA NA NA
#> 24 20.0 20 20 NA NA NA
#> 25 20.0 20 20 NA NA NA
#> 26 6.0 12 30 NA NA NA
#> 27 6.0 12 30 NA NA NA
#> 28 6.0 12 30 NA NA NA
#> 29 6.0 12 30 NA NA NA
#> 30 6.0 12 30 NA NA NA
#> 31 6.0 12 30 NA NA NA
#> 32 NA NA NA NA NA 10.7485
#> 33 NA NA NA NA NA 10.7485
#> 34 NA NA NA NA NA 10.7485
#> 35 NA NA NA NA NA 10.7485
#> 36 NA NA NA 140 70 0.9800
#> 37 NA NA NA 140 70 0.9800
#> 38 NA NA NA 140 70 0.9800
#> 39 NA NA NA 140 70 0.9800
#> 40 NA NA NA 140 70 0.9800
#> 41 NA NA NA 140 70 0.9800
#> 42 NA NA NA 100 50 0.5000
#> 43 NA NA NA 100 50 0.5000
#> 44 NA NA NA 100 50 0.5000
#> 45 NA NA NA 100 50 0.5000
#> 46 6.0 12 30 NA NA NA
#> 47 6.0 12 30 NA NA NA
#> 48 6.0 12 30 NA NA NA
#> 49 6.0 12 30 NA NA NA
#> 50 6.0 12 30 NA NA NA
#> 51 6.0 12 30 NA NA NA
#> 52 NA NA NA NA NA 10.7485
#> 53 NA NA NA NA NA 10.7485
#> 54 NA NA NA NA NA 10.7485
#> 55 NA NA NA NA NA 10.7485
#> 56 NA NA NA NA NA 10.7485
#> 57 NA NA NA NA NA 10.7485
#> 58 NA NA NA NA NA 10.7485
#> 59 NA NA NA NA NA 10.7485
#> vol_crown_m3 vol_bole_m3
#> 1 NA NA
#> 2 NA NA
#> 3 NA NA
#> 4 NA NA
#> 5 NA NA
#> 6 NA NA
#> 7 NA NA
#> 8 NA NA
#> 9 NA NA
#> 10 NA NA
#> 11 NA NA
#> 12 NA NA
#> 13 NA NA
#> 14 NA NA
#> 15 NA NA
#> 16 NA NA
#> 17 NA NA
#> 18 NA NA
#> 19 NA NA
#> 20 NA NA
#> 21 NA NA
#> 22 NA NA
#> 23 NA NA
#> 24 NA NA
#> 25 NA NA
#> 26 NA NA
#> 27 NA NA
#> 28 NA NA
#> 29 NA NA
#> 30 NA NA
#> 31 NA NA
#> 32 NA NA
#> 33 NA NA
#> 34 NA NA
#> 35 NA NA
#> 36 NA NA
#> 37 NA NA
#> 38 NA NA
#> 39 NA NA
#> 40 NA NA
#> 41 NA NA
#> 42 NA NA
#> 43 NA NA
#> 44 NA NA
#> 45 NA NA
#> 46 NA NA
#> 47 NA NA
#> 48 NA NA
#> 49 NA NA
#> 50 NA NA
#> 51 NA NA
#> 52 NA NA
#> 53 NA NA
#> 54 NA NA
#> 55 NA NA
#> 56 0.6624929 3.198649
#> 57 2.3272250 7.649618
#> 58 0.6624929 3.198649
#> 59 1.7701569 6.442763