Amaro A., Reed D., Soares P. (editors) Modelling Forest Systems
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Amaro Forests Index 1/8/03 11:54 am Page 396
396 Index
Complex system 390–391
Cone production 131, 132–133, 137, 138
Conifer 42
Cork oak 259
productive system see Montado
CORKFITS 2.1 260, 261
Corsican pine 146
Cost-plus-loss analysis 296, 303, 361,
364
economic loss
297, 299–302
net present value (NPV) 297–298
total costs 296
Data
aquisition
1, 4
classification
growth 238, 241
mortality
238, 242
recruitment 238, 242
correlation 230
economic
309, 310
inventory 296
multilevel 226
quality 2, 4, 199, 361
quality vs. quantity 1
quantity 314, 317
satellite see Landsat 7
splitting 284–286, 288
structure 199
Data warehouse 370
Decision 363, 364
complexity
360
management 359
Defoliation 163
Dioryctria mendacella 133
Douglas fir
250, 254
ECOCRAFT project 147
E-GROW ARCEL 64, 65, 66, 67, 68, 71
Encapsulation 367
End-users 315
End-users researchers 86
Error
Type I 360
Type II 360
Estonia
170
Eucalyptus 78, 214, 221
globulus 65, 97, 98
grandis 63, 64
nitens 65
r
egnans 27
Euclidean distance 239
see also Cluster analysis
Extensible markup language see
XML
Extrapolation 283
Fagus sylvatica 145
FBMIS
371, 375–377
Field’s thinning ratio function 81
Flexural properties 327
FMA 393
Foliage biomass 158, 163, 165
Forest Biometry, Modelling and
Information Sciences see
FBMIS
Forest information system
ABIES 349
FOGIS–INTEND Kassel 349
FORCITE 349
TRAGIC 349, 351, 354
TRAGIC++ 351, 354
VIWA 349, 350, 353
VIWA 2 350, 353
Forest Model Archive see
FMA
Forest modelling platform see
CAPSIS
Forest simulator see CAPSIS
FORTRAN-90 210
France 112, 119
French Guiana
Paracou 238, 240
Fuzzy
maths
381
system 384
GAYA-JLP 296
GIS 349, 350, 351
GLOBTREE 97–109
Gnutella 371
GORCAM 144, 147
Gradient vector 204
Graphical analysis 273–275
Graphical user interface see GUI
Greenwich Initiative 372
GUI 349, 350, 351, 356
Guyana 309, 310, 313
HABPLAN 362
Harvest scheduling 363, 364
Metr
opolis algorithm 362
see also
HABPLAN
Amaro Forests Index 1/8/03 11:54 am Page 397
Index 397
Height increment 250, 252
Hessian matrix 215
Heuristic system 86
Index
cork pr
oduction 260, 262, 263, 264
dissimilarity 239; see also Cluster
analysis
quality
260, 262, 263
suppression 82
Indonesia 309, 310, 313
Information technology
52, 53–57, 60
Integration 391
Interaction 53–57
Interface
visualization 53, 57, 58, 59, 60
Italy
Acquapendente
42
IUFRO 379
GFIS Taskforce 370, 372
Jack pine 123
budworm 123, 124
Johnson’s SB
171–173, 175, 176, 178
JTRAGIC see Interface
Kernel 319, 320
Knowledge
database
380, 381, 382
Kyoto protocol 144
Landsat 7 43–44
Land use
308
Litter
accumulation 34
decay 34
Loblolly pine
4
Lodgepole pine 11–14
Logging
impact 28
Logic r
epresentation 380
Logistic regression 225, 226–228
binary variable 225, 226
multilevel 227–228, 228
Loss function
361
Lumber 326, 327, 332
stress-graded dimension 329, 331
Mapping 47–49, 348
isoclines
16
non-parametric classifier
fuzzy discrimination 45, 46–47
K-nearest neighbour 45–46
pr
obability map 139, 140
remote sensing see Landsat 7
technology see
ANUSPLIN,
ArcView
Markov Chain
124–126, 127, 129
Mean annual increment (MAI) see 3-
PG
Metadata 372
Mixed forest 144
Model 369, 381, 390
accuracy 3–6
aggr
egation complex 85
binomial 128
basal area 81, 82, 214, 220–222; see
also
ALBA
bias 5
bioclimatic 191, 195
biological analysis 392
biomass 148, 150, 151
Chapman–Richards 75, 79, 80, 339,
340, 343, 375
Clutter–Jones
80
complexity 6
complexity vs. accuracy 4
cone production 133
Cunia 184
density 80
development 85
diameter class see
MYRLIN
diameter distribution 171, 174, 178,
207, 208; see also Johnson’s SB
171
171
Gram–Charlie 171
log-normal 171
normal 171
Weibull 171
dimensionality 8, 9
distribution
205; see also
BALANCE,
Weibull
diameter 171, 174, 178, 207, 208;
see also Johnson’s SB
size-biased
201, 210, 211
weighted 201, 210, 211
documentation 392–393
dominant height
80, 113, 214,
218–220; see also
ALDO
Amaro Forests Index 1/8/03 11:54 am Page 398
398 Index
Model continued
ecological individual tree see
SYMFOR
empirical 56, 63, 64, 199, 249, 308;
see also
ALBA, ALDO, CORKFITS 2.1,
E-GROW ARCEL, GLOBTREE, SOP
EUCALYPT
322
individual tree 65
MOUNTAIN 321
NITGRO 65
PNN 321
PP3 322
PTAEDA 2 65
SELVA 321
size class 65
stand level 7, 8, 64, 65, 75, 79, 370
VENTOUX 322
evaluation 89, 106, 268–270, 271,
272–284, 287–289, 392–393; see
also Graphical analysis,
Sensitivity analysis, Threshold
biological meaning 280, 289
independent data 295, 300
statistical test 275–276, 295
foliage biomass 157, 158, 159
forest management 309
integration 314
large-scale 312
growth and yield 7
Gypsy Moth Life System 335
hybrid 199
E-GROW ARCEL 3-PG 66, 71
PROMOD NITGRO 65
PTAEDA MAESTRO 89
PTAEDA2 MAESTRO 65
individual tree 7, 8, 370
interactive 85
large-scale forestry scenario
296
see also Cost-plus-loss analysis
linkage
growth and yield financial
analysis 311, 312, 315, 317
growth and yield management
314, 317
Lundqvist-Korf 214, 215
matrix 238, 240, 242, 243, 244, 245,
246
transition probability 240
mechanistic see Model, process-
based
multi-level mortality 200
NetW
eaver 380, 381, 384
non-linear 215, 339, 370
parsimony 3–6, 9
performance 267
practical idealistic 267
precision 5
process-based 56, 64, 199, 249, 370
BIOMASS 65
CENTURY 65
FOREST-BGC 65
G’DAY 65
JABOWA 65
MAESTRO 65
PROMOD 65
see also 3-
PG; SECRETS
projection length 8
regeneration simulator see
STRUGEN
Richards 183–184, 214, 215, 339,
340, 343
Schumacher 79, 81
spatial stand simulator see
CAPSIS,
STRUGEN
BIOMECHANICS
library 322
SPATIAL library 322
WINDSTORM 322
Stand Damage (SDM) 335, 336
stand height 193
state 85
tree crown ratio 99
tree diameter 335
tree diameter increment 99, 102,
105–106, 335
tree height 335
tree height–diameter 99, 173,
176–177, 178, 184, 186
tree mortality 99, 103–104, 108, 200,
225, 233, 235, 239, 243, 244
tree volume 99
updating 199–200
use 391–392
users 390, 392
verification 199
von Bertalanfy 339, 340
Weibull 339, 340, 343
Weibull – allometric 161, 163, 164,
165
wood stocking 193
see also
GORCAM; MYRLIN; SYMFOR
Modelling 1, 2, 3, 75, 88–92, 133, 136,
380, 382, 389, 390–391
competition 370
Amaro Forests Index 1/8/03 11:54 am Page 399
Index 399
forest attributes 41–42
geostatistics 132, 133, 134, 140
kriging 133, 135, 138
spatial correlation 138
spatial prediction 135–136
structural analysis 134, 137
variogram 134, 135, 137
growth 79, 370
level 7–9, 79
Monte Carlo technique 363
mortality 370
platform see
CAPSIS
spatial 41–42
Montado 259, 264
Montreal process 384
MSE 5–6, 273
MYRLIN 310, 312, 313–314
National Forest Inventory see
NFI
NBP 35, 36
Net biome productivity see NBP
NFI 170
Non-wood forest products 309
Norway 296
Norway spruce 52, 57
Oak
northern r
ed 338
southern red 338
white 338
Optimism principle 271, 272–273
Parameter estimation 29, 199, 240, 246
four per
centile – 4PR 172, 174
Gauss–Newton algorithm 162
KB 172, 174
Levenberg–Marquardt 215, 253
likelihood function 126
linear regression 172, 174
log-likelihood 239, 240
marginal quasi-likelihood 227, 229,
231, 232, 234, 235
Marquardt 184, 339, 340–341
maximum likelihood 126, 172, 174,
204–205, 226, 229, 231, 234
moments 172, 174, 203
N2SLS 215, 219, 222
N3SLS 216, 219, 222
neural networks 91, 251, 252–254
NOLS
216, 217, 218
non-linear regression 162, 172, 174,
184
OLS 215, 272–273
penalized quasi-likelihood 227,
229, 231, 232
quadratic regression 190
restricted maximum likelihood
227
size-based likelihood 208
variance–covariance 239, 240
Pattern generation 61
PCA 65
Percentage of explained variance see
PEV
Permanent Sample Plot see PSP
PEV 242
3-
PG 64, 65, 66–67, 68, 69–70, 71
Phytomass 194
Picea abies 52, 57
Pinus 78, 119
banksiana 123
contorta 11–14
nigra 112, 113, 114, 119
pinea 131, 132, 133, 140
radiata 65
sibirica 189
sylvestris 146, 161, 162, 163, 226,
230
taeda 326, 327, 329, 331
Pissodes validirostris 133
Pollen cones 124
Poplar 181, 182
Populus tremuloides 362
Populus euroamericana 181, 182
Portugal 97
Potential modifier 260
Probability density function 202, 203
Productivity
index 182, 185
region 214, 219
frost risk 215, 222
water availability 215, 222
Pseudo-species 238, 239, 241
Pseudotsuga menziessi 250, 254
PSP see
SINKA
Quadratic mean DBH 296, 298, 299
Quaking aspen 362
Amaro Forests Index 1/8/03 11:54 am Page 400
400 Index
Quercus
alba 338
cerris 42
falcata 338
petraea 146
robur 145
rubra 338
suber 259
R
2
5–6, 230, 234
Rate of return on investment 330, 331,
332
Register of Ecological Models see
REM
Register of Forest Models see RFM
REM 373
RFM 373
Risk 360, 361, 364
Sample
err
or 362
size 361
Sampling
cluster 43, 44
probability proportional to size
(PPS) design 201
SAS 339, 344
Scale 2, 85, 145, 348, 390
landscape 27, 349, 350, 356
spatial 88
temporal 88
Scenario 383
Scots pine 226, 230
SECRETS 146–147
Sensitivity analysis 282–283
Sequential Gaussian simulation
136
Serbia 250, 251
SFM 380, 381, 384
Siberia 189
Siberian cedar 189, 192
Siberian fir 189, 192
SINKA 230
Site index 14–15
isoclines 16
SOP 214, 221
Soporcel 214, 222
South Africa 75
Komatiland forest 75, 76
Spacing
trial
4, 78
correlated curve trend (CCT)
78–79
Nelder 78
Triple-S CCT 78
Spain 131, 181, 182, 183
Huesca 181, 182, 183
Valladolid 134, 140
SPSS 215
Stakeholder 308, 315, 317
Stand 117–119
density 45, 47–49, 296, 298, 299
density effect
dominant height 117
density index
basal area 114
crown competition factor 114
Hart and Becking 114, 117, 118,
119, 120
Reineke 114
dynamics 99–100, 104
even-aged 261, 263, 264
patch 145, 146, 151
uneven-aged 190, 261, 263, 264
volume 45, 47–49
Stand simulator
FVS, LS 362
STATISTICA 215
Statistical test 125, 360
bias 164, 233, 234
2
276, 278–279
classification tables 230
correlation 165
F 163, 277, 278
Hosmer–Lemeshow 227, 229, 233,
235
Kolmogorov–Smirnov 129, 173,
174, 175, 178, 277, 278, 280
likelihood ratio 127, 217, 221
Mann Whitney 163, 164
MSE 340, 344, 276, 278, 279
Pearson
2
229
sensitivity 230, 233; see also Logistic
regression
specificity 230, 233; see also Logistic
regression
t 163, 165, 276, 278, 279
Wilcoxon 340
Wilcoxon signed-rank 277, 278,
280
see also Model evaluation
Amaro Forests Index 1/8/03 11:54 am Page 401
Index 401
Stem Training 316, 317
biomass 34 Tropical forest 308
carbon 36
volume 32 UML 380
Stone pine 131, 132, 133, 140 Uncertainty 381
STRUGEN 260 Universal Modelling Language see
Sustainability 380, 381 UML
Sustainable Forest Management see USA
SFM Minnesota 362
Sweden 163 Ohio 337, 342
Jädraas 163
SYMFOR 311, 312 Virtual Reality Modelling Language see
SYSTAT 29 VRML
Visualization 347, 356
AMAP 350, 351
Taper curve 29, 31, 32, 33
ENVISION 350, 353
Test statistics see
Statistical test GROGRA 349
Thinning
JTRAGIC 351, 354
trial 57, 59 VRML 33
Thin-plate smothing spline see
Mapping Weibull
Threshold 286–287 distribution 202–205, 206, 208, 209
Time series see
Markov Chain World Wide Web see WWW
Total expected loss 361 WWW 371
Trafalgar group 372
TRAGIC++ 58 XML 349