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

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104 Chapter 4 such as Davos agrees with descriptions of other near-natural forests of the area (e.g. Melico-Piceetum Ellenberg & Klötzli 1972; cf. also Ellenberg 1986). Similar to the site Bever, the stronger occurrence of summer drought causes shifts of the species composition at the site Bern (Fig. 4.9): Spruce (P. excelsa) loses importance. On the other hand, the biomass of A. alba increases considerably, and that of Quercus robur increases slightly. Abies clearly is overrepresented now, which is due to its large maximum height and the formulation of asymmetric competition, as discussed already by Kienast & Kuhn (1989b). The rest of the community remains virtually unchanged. At the site Sion, radical changes are observed when the abiotic environment is stochastic (Fig. 4.9): Total biomass decreases to about one third, Tilia and Taxus disappear, and Castanea is reduced to very low biomass. The forest simulated by FORCLIM-E/P is an oak-pine forest close to the arid timberline, which corresponds better to phytosociological expectations (Ellenberg & Klötzli 1972, Burnand 1976). It should be noted that small changes of the drought tolerance parameters (kDrT) of P. silvestris, Q. robur, and Q. pubescens can lead to strong changes in the relative proportions of these species at the site Sion; the simulated species composition therefore should be interpreted with caution. The simulation time required to simulate 1200 years of successional dynamics on one patch with FORCLIM-E/P is 40 seconds (Macintosh Quadra 700); for the same run on the same machine, the FORTRAN version of the FORECE model requires 226 seconds. In other words, simulation time with FORCLIM-E/P is less than one fifth of FORECE (19.4%). Most of the increased efficiency is attributable to the model simplifications (section 2.3) and not to the different programming and simulation environment. Hence large-scale simulation experiments can be performed more efficiently with FORCLIM than with FORECE (cf. chapter 5). 4.3.3 FORCLIM-E/P/S In this model version, neither the weather nor the availability of nitrogen are kept constant, and it is also possible to evaluate the amount of belowground organic matter. Fig. 4.10 & 4.11 show the results obtained from FORCLIM-E/P/S at the four sites. A common pattern is visible at all sites: the accumulation of biomass is slower in the E/P/S than in the E/P model because nitrogen availability limits tree growth markedly as long as soil organic matter is accumulating (cf. section 4.2). Moreover, even if the average nitro-
Behaviour of FORCLIM along a transect in the European Alps 105 gen availability in the steady state of FORCLIM-E/P/S is higher than the 100 kg/ha assumed in the previous sections, there are prolonged periods where N availability drops to low values, e.g. when a large fallen log immobilizes large amounts of nitrogen. During such phases, species which are tolerant of these conditions (i.e. those which have a low kNTol parameter) have a competitive advantage. Hence, these species may be expected to increase their abundance in the FORCLIM-E/P/S model as compared to the variant E/P. 600 Bever (south, P) 500 Biomass (t/ha) 400 300 200 Populus nigra Pinus silvestris Larix decidua Pinus cembra Picea excelsa 100 0 0 400 Year 800 1200 600 Davos (P) 500 Biomass (t/ha) 400 300 200 Populus nigra Pinus silvestris Larix decidua Pinus cembra Picea excelsa 100 0 0 400 Year 800 1200 Fig. 4.6: Average species composition from 200 forest patches simulated by the FORCLIM-P model in isolation, assuming a nutrient-rich soil and a constant abiotic environment (i.e. no yearto-year variability in the weather). Top: A south-facing slope at the site Bever; bottom: Davos. The graphs show cumulative species-specific biomass values.
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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
Page 47 and 48: The forest model FORCLIM 53 decay o
Page 49 and 50: The forest model FORCLIM 55 the est
Page 51 and 52: The forest model FORCLIM 57 3.3 Mod
Page 53 and 54: The forest model FORCLIM 59 Light a
Page 55 and 56: The forest model FORCLIM 61 Overall
Page 57 and 58: The forest model FORCLIM 63 D (cm)
Page 59 and 60: The forest model FORCLIM 65 a) b) c
Page 61 and 62: The forest model FORCLIM 67 Growth
Page 63 and 64: The forest model FORCLIM 69 Stress-
Page 65 and 66: The forest model FORCLIM 71 Tab. 3.
Page 67 and 68: The forest model FORCLIM 73 3.3.2 F
Page 69 and 70: The forest model FORCLIM 75 where k
Page 71 and 72: The forest model FORCLIM 77 NITROGE
Page 73 and 74: The forest model FORCLIM 79 peratur
Page 75 and 76: The forest model FORCLIM 81 of degr
Page 77 and 78: The forest model FORCLIM 83 microcl
Page 79 and 80: The forest model FORCLIM 85 Tab. 3.
Page 81 and 82: The forest model FORCLIM 87 3.4.3 F
Page 83 and 84: The forest model FORCLIM 89 All the
Page 85 and 86: The forest model FORCLIM 91 The mas
Page 87 and 88: The forest model FORCLIM 93 FORCLIM
Page 89 and 90: Behaviour of FORCLIM along a transe
Page 97: Behaviour of FORCLIM along a transe
Page 115 and 116: Parameter sensitivity & model valid
Page 147 and 148: 153 6 . Model applications Climatic
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Model applications 155 The simulate
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Model applications 157 6.2 Possible
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Model applications 159 simulation s
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Model applications 161 Simulation e
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Model applications 163 At the site
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Model applications 165 Bever Biomas
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Model applications 167 tainty inher
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Model applications 169 scenario cho
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Discussion 171 Finally, the analysi
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Discussion 173 bitrarily chosen par
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Discussion 175 comparably small imp
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Discussion 177 end of the 21st cent
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Conclusions 179 Ecological factors
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Conclusions 181 species composition
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References 183 Begon, M., Harper, J
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References 185 Burger, H., 1951. Ho
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References 187 Faber, P.J., 1991. A
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References 189 Huntley, B. & Birks,
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References 191 Leemans, R. & Prenti
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References 193 Olson, J.S., 1963. E
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References 195 Rudloff, W., 1981. W
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References 197 Smith, T.M., Leemans
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References 199 Whittaker, R.H., 195
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Appendix 201 II. Derivation of para
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Appendix 203 Tab. A-4: Tree species
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Appendix 205 Tab. A-7: Values for m
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Appendix 207 The minimum winter tem
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Appendix 209 Tab. A-11: Shade toler
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Appendix 211 Tab. A-14: Climatic pa
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Appendix 213 IV. Source code of the
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Appendix 215 FROM SimBase IMPORT De
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Appendix 217 END; (* IF *) prevDay
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Appendix 219 PROCEDURE InitializeFW
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Appendix 221 InstallSeparator( fMen
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Appendix 223 FROM FCPFileIO IMPORT
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Appendix 225 modelSp^.p.kHm := sens
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Appendix 227 DeclMV( meanLitt[leafS
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Appendix 229 Swiss Federal Institut
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Appendix 231 (*********************
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Appendix 233 BEGIN WITH sp^ DO d :=
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Appendix 235 Definition module FCPB
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Appendix 237 Purpose Simulation mod
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Appendix 239 END Immobilization; PR
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Appendix 241 CONST lem = 3; VAR ef:
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Appendix 243 Purpose Provides the b
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Appendix 245 Example of a text file
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Appendix 247 Tab. A-15: Lower end o
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Appendix 249 Tab. A-17: Percentage
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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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