On the Ecology of Mountainous Forests in a Changing Climate: A ...

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202 Appendix 80% of the foliage weight obtained for group 2 (Tab. A-3). The relationships between foliage weight and diameter as well as a comparison of the new parametrization with the one used by Kienast (1987) are plotted in Fig. A-1. Tab. A-3: Regressions of foliage wet weight (L) vs. diameter at breast height (D) for several species groups as derived from the data in Burger (1945-53), where L = kA 1·D kA 2. Linear regressions were calculated based on the transformation Ln(L) = Ln(kA 1 ) + kA 2·Ln(D). n denotes sample size. Species kA 1 kA 2 r 2 group no. n Abies alba, Picea excelsa, Pinus cembra, P. montana 0.23 1.56 0.93 5 130 P. silvestris 0.17 1.40 0.76 4 210 Fagus silvatica, Quercus spp. 0.06 1.70 0.93 3 144 Larix decidua 0.10 1.43 0.87 2 99 Betula sp., Salix sp. (no data) 0.08 1.43 – 1 – L (kg) Picea: foliage data gFolW (kg) 40.00 300 35.00 30.00 25.00 1 2 200 20.00 3 15.00 10.00 5.00 0.00 0 20 40 60 80 D (cm) 4 5 100 0 0 20 40 60 80 Kienast’s formula regression, group 5 measurement 100 120 D (cm) Fig. A-1: Left: Relationship between foliage dry weight (gFolW) and diameter at breast height (D) of the species groups defined in Tab. A-3. Right: Measured foliage fresh weight of Picea excelsa (dots), the FORECE parametrization (Kienast 1987) and the parametrization for group 5 derived from the original Burger data (Tab. A-3). Grouping of the species To assign every species to one of the five groups defined above (Tab. A-3), the ranking of the species with respect to their capability of casting shade from Ellenberg (1986) and the values of the parameters A1 and A2 used by Kienast (1987) were consulted (Tab. A- 4). These data sources allowed to rank the 30 tree species with respect to the sType parameter. kDm, kHm & kAm parameters Probably the best way to determine these three parameters would be based on diameter, height, and age distributions of trees in old-growth forests that are not subject to strong environmental stress. A theoretical distribution could be fitted to such data, e.g. an exponential distribution in the case of maximum age (cf. Eq. 3.29f. in section 3.3.1), and the parameters could be estimated from these distributions. However, data from old-growth European forests is scarce (e.g. Leibundgut 1993). Moreover, it would be difficult to obtain these data for many tree species, let alone for all the 30 species used under European conditions in FORCLIM. Therefore, a simpler and necessarily less accurate approach had to be adopted to derive an estimate of these parameters.
Appendix 203 Tab. A-4: Tree species, Ellenberg's (1986) ranking of their capability to cast shade as pure stands (1 = low, 5 = high), the parameters kA 1 and kA 2 as used in FORECE (Kienast 1987) and the sType parameters derived from these sources and the regressions in Tab. A-3. For species in bold face, the data is from Burger (1945-53). Species name Ellenberg FORECE kA 1 FORECE kA 2 sType Abies alba 5 0.08 1.96 C5 Larix decidua 1 0.04 1.64 D2 Picea excelsa 4 0.08 1.90 C5 Pinus cembra 4 0.08 1.90 C5 Pinus montana 1 0.08 1.90 C5 Pinus silvestris 1 0.10 1.58 C4 Taxus baccata 5 0.08 1.96 C5 Acer campestre 3 0.05 1.75 D2 Acer platanoides 4 0.05 1.75 D3 Acer pseudoplatanus 4 0.05 1.75 D3 Alnus glutinosa 3 0.05 1.75 D2 Alnus incana 3 0.05 1.75 D2 Alnus viridis – 0.05 1.75 D2 Betula pendula 1 0.05 1.58 D1 Carpinus betulus 5 0.05 1.80 D3 Castanea sativa 3 0.05 1.80 D3 Corylus avellana – 0.05 1.80 D3 Fagus silvatica 5 0.05 1.79 D3 Fraxinus excelsior 3 0.06 1.70 D2 Populus nigra 2 0.05 1.70 D2 Populus tremula 2 0.05 1.70 D2 Quercus petraea 3 0.04 1.78 D3 Quercus pubescens 2 0.04 1.78 D3 Quercus robur 2 0.04 1.78 D3 Salix alba 2 0.05 1.70 D1 Sorbus aria 4 0.05 1.70 D2 Sorbus aucuparia 2 0.05 1.70 D1 Tilia cordata 4 0.05 1.75 D3 Tilia platyphyllos 4 0.05 1.75 D3 Ulmus scabra 4 0.05 1.75 D3 To this end, a large data base was compiled for deriving the three parameters from the silvics descriptions in Amann (1954), Fenaroli & Gambi (1976), Brosse (1977), Polunin (1977), Phillips (1978), Bernatzky (1978), Krüssmann (1979), Mitchell (1979), Hess et al. (1980), Edlin & Nimmo (1983), Marcet & Gohl (1985), Godet (1986), Leibundgut (1991), and Prentice & Helmisaari (1991). From every reference, the maximum diameter, height and age were recorded for every species listed. The following rationale, which undoubtedly is ad hoc, was used to derive species parameters from this data base: The arithmetic mean of all values does not reflect true maximum dimensions since some authors probably were not aware of very large specimen. On the other hand, using the maximum of all the values would introduce a strong bias towards exaggerated large dimensions. Thus, it was decided to calculate the species parameters as the average of the mean and the maximum values found (Tab. A-5 – A-7). Maximum tree diameter (Tab. A-5) is covered rather well in the literature; for most species, at least 3 values could be compiled. For some species that not usually dominate forests (i.e. Pinus montana, Corylus avellana, Quercus pubescens) only one value could be found. No parameter for Alnus viridis could be derived at all; since this species is a bush rather than a tree (cf. Tab. A-6), its kDm is small and thus was estimated as 20 cm. Maximum tree height (Tab. A-6) is covered well in the literature (seven or more values for all species except Pinus montana and Alnus viridis). The same species as for maximum diameter and height have a low coverage concerning maximum age (Tab. A-7): Pinus montana and Alnus viridis. It is known that the latter species is not very long-lived, thus its maximum age was arbitrarily set to 100 years. A similar procedure had to be adapted when estimating kAm for Quercus pubescens: Oaks can grow quite old, but Q. pubescens does not attain the high age of the other two native oak species (860 and 1060 years); thus, its maximum age was set to 500 years.
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Diss. ETH No. 10638 On the Ecology
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ii Table of contents A BSTRACT.....
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iv APPENDIX .......................
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vi Harald BUGMANN, 1994: On the eco
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viii Harald BUGMANN, 1994: Aspekte
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1 1 . Introduction 1.1 Climatic cha
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Introduction 3 1.2 Methods for the
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Introduction 5 in a changing climat
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Introduction 7 Their integrative ca
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Introduction 9 (1984) provides a mo
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Introduction 11 The main advantage
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13 2 . Analysis of existing forest
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Analysis of existing forest gap mod
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The forest model FORCLIM 45 carbon
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The forest model FORCLIM 47 TREE GR
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The forest model FORCLIM 49 gBFlag
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The forest model FORCLIM 51 Disturb
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The forest model FORCLIM 53 decay o
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The forest model FORCLIM 55 the est
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The forest model FORCLIM 57 3.3 Mod
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The forest model FORCLIM 59 Light a
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The forest model FORCLIM 61 Overall
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The forest model FORCLIM 63 D (cm)
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The forest model FORCLIM 65 a) b) c
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The forest model FORCLIM 67 Growth
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The forest model FORCLIM 69 Stress-
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The forest model FORCLIM 71 Tab. 3.
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The forest model FORCLIM 73 3.3.2 F
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The forest model FORCLIM 75 where k
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The forest model FORCLIM 77 NITROGE
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The forest model FORCLIM 79 peratur
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The forest model FORCLIM 81 of degr
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The forest model FORCLIM 83 microcl
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The forest model FORCLIM 85 Tab. 3.
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The forest model FORCLIM 87 3.4.3 F
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The forest model FORCLIM 89 All the
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The forest model FORCLIM 91 The mas
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The forest model FORCLIM 93 FORCLIM
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Behaviour of FORCLIM along a transe
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Parameter sensitivity & model valid
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Page 145 and 146: Parameter sensitivity & model valid
Page 147 and 148: 153 6 . Model applications Climatic
Page 149 and 150: Model applications 155 The simulate
Page 151 and 152: Model applications 157 6.2 Possible
Page 153 and 154: Model applications 159 simulation s
Page 155 and 156: Model applications 161 Simulation e
Page 157 and 158: Model applications 163 At the site
Page 159 and 160: Model applications 165 Bever Biomas
Page 161 and 162: Model applications 167 tainty inher
Page 163 and 164: Model applications 169 scenario cho
Page 165 and 166: Discussion 171 Finally, the analysi
Page 167 and 168: Discussion 173 bitrarily chosen par
Page 169 and 170: Discussion 175 comparably small imp
Page 171 and 172: Discussion 177 end of the 21st cent
Page 173 and 174: Conclusions 179 Ecological factors
Page 175 and 176: Conclusions 181 species composition
Page 177 and 178: References 183 Begon, M., Harper, J
Page 179 and 180: References 185 Burger, H., 1951. Ho
Page 181 and 182: References 187 Faber, P.J., 1991. A
Page 183 and 184: References 189 Huntley, B. & Birks,
Page 185 and 186: References 191 Leemans, R. & Prenti
Page 187 and 188: References 193 Olson, J.S., 1963. E
Page 189 and 190: References 195 Rudloff, W., 1981. W
Page 191 and 192: References 197 Smith, T.M., Leemans
Page 193 and 194: References 199 Whittaker, R.H., 195
Page 195: Appendix 201 II. Derivation of para
Page 199 and 200: Appendix 205 Tab. A-7: Values for m
Page 201 and 202: Appendix 207 The minimum winter tem
Page 203 and 204: Appendix 209 Tab. A-11: Shade toler
Page 205 and 206: Appendix 211 Tab. A-14: Climatic pa
Page 207 and 208: Appendix 213 IV. Source code of the
Page 209 and 210: Appendix 215 FROM SimBase IMPORT De
Page 211 and 212: Appendix 217 END; (* IF *) prevDay
Page 213 and 214: Appendix 219 PROCEDURE InitializeFW
Page 215 and 216: Appendix 221 InstallSeparator( fMen
Page 217 and 218: Appendix 223 FROM FCPFileIO IMPORT
Page 219 and 220: Appendix 225 modelSp^.p.kHm := sens
Page 221 and 222: Appendix 227 DeclMV( meanLitt[leafS
Page 223 and 224: Appendix 229 Swiss Federal Institut
Page 225 and 226: Appendix 231 (*********************
Page 227 and 228: Appendix 233 BEGIN WITH sp^ DO d :=
Page 229 and 230: Appendix 235 Definition module FCPB
Page 231 and 232: Appendix 237 Purpose Simulation mod
Page 233 and 234: Appendix 239 END Immobilization; PR
Page 235 and 236: Appendix 241 CONST lem = 3; VAR ef:
Page 237 and 238: Appendix 243 Purpose Provides the b
Page 239 and 240: Appendix 245 Example of a text file
Page 241 and 242: Appendix 247 Tab. A-15: Lower end o
Page 243 and 244: Appendix 249 Tab. A-17: Percentage
Page 245 and 246: Appendix 251 Tab. A-19: Significant
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Appendix 253 VI. Derivation of para
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Appendix 255 Tab. A-21: Species-spe
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Appendix 257 Tab. A-22 (continued)
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