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

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176 Chapter 7 year 2100 (Houghton et al. 1990, 1992). Hence these results do not mean that future climatic change will not affect these forests drastically, but that they are buffered better against climatic change than forests that are subject to environmental stress already under current climate (Bugmann & Fischlin 1994). The comparison of the behaviour of five forest gap models under one scenario of climatic change shows that the models disagree most sharply at sites close to the alpine timberline. Thus, under these conditions the models are sensitive to climatic parameters as well as to the formulation of ecological factors. Although there is less divergence at the other sites and it is felt that FORCLIM-E/P and FORCLIM-E/P/S are the most trustworthy of all the five models studied, it is daunting to see the differences the five models produce. Moreover, there is no clue that future versions of FORCLIM will be robust in their projections. For example, ongoing research (Perruchoud 1994) is aimed at providing an improved version of FORCLIM-S, which again may lead to projections about future forests differing strongly from the present ones. Thus, there is a serious problem concerning the number of factors to be included in forest ecosystem models and their exact formulation (cf. Bonan 1993). Even if the best scenario of climatic change could be unequivocally identified, there would remain some uncertainty in it. The investigation of the propagation of the uncertainties inherent in a state-of-the-art scenario obtained from large-scale GCM data (Gyalistras et al. 1994) showed that, again mainly at sites close to the timberline, a bewildering array of possible future forest compositions is obtained. Thus also such a climate scenario does not currently match the precision requirements of forest ecosystem models, corroborating the findings by Fischlin et al. (1994), which were based on a different climate scenario. FORCLIM was developed to include reliable formulations of the influence of temperature and precipitation on ecological processes. Thus it may be hypothesized that the model is trustworthy enough to assess the possible impact of climatic change on forest ecosystems in the European Alps. However, as discussed above little confidence can be placed in its projections both for climatological and ecological reasons. Yet, even if we are not able to give precise information on the potential future species composition at a given location, this does not mean that no statements could be made at all: The strength of the application of forest gap models in impact assessments of climatic change lies in determining the sensitivity of the simulated species composition to changes of climatic parameters. In this sense and under the assumption of a constant climate corresponding to the climate at the
Discussion 177 end of the 21st century, we may conjecture that mid altitudes in the European Alps are likely to undergo minor changes only, whereas subalpine areas and those close to the dry timberline are likely to undergo drastic changes of species composition, including forest dieback phenomena. These results suggest that the prediction of the species composition of near-natural forests under a changed climate is quite difficult. Hence it would be even more difficult to predict the transient dynamics of forest ecosystems in response to a transient climatic change (Schneider & Thompson 1981). The comparison of step, ramp, and sigmoid climatic changes during 100 years show that the choice of the transient scenario is not of paramount importance at this temporal scale because the anticipated climatic change proceeds much faster than the successional dynamics. Hence, the step and ramp scenarios used in previous studies (e.g. Solomon 1986, Pastor & Post 1988, Kienast 1991, Fischlin et al. 1994, Bugmann & Fischlin 1994) constitute a sufficient approximation of more detailed scenarios of transient climatic change on the timescale of 100 years. 7.6 Tools for modelling and simulation The RAMSES software for modelling and simulation (Fischlin et al. 1990, Fischlin 1991) proved to be very helpful for becoming familiar with forest gap models in the first, explorative phase of the project. The flexibility it offers for interactively changing parameters, monitoring any desired variable, and adding or removing single submodels without having to change the code was especially useful in that phase. Throughout the thesis, working interactively with the user interface of ModelWorks (Fischlin et al. 1990) was important. Moreover, the ModelWorks experiment mechanism made it possible to program large simulation experiments as well and to run them in a batch-oriented mode on up to four remote simulation servers at a time. This turned out to be indispensable and became ever more important towards the end of this study, especially for performing the analyses presented in chapter 5. The access to the high-level programming language Modula-2 (Wirth 1985) allowed to split the implementation of FORCLIM into several modules with well-defined interfaces. This made it easy to change single features of FORCLIM without the risk of producing side effects on other features. Moreover, the Dialog Machine (Fischlin 1986, Fischlin & Ulrich 1987) and Modula-2 made it possible to program a number of additional features, which provided even more flexibility from both the modeller's and the user's perspective.
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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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Parameter sensitivity & model valid
Page 119 and 120: 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: Discussion 175 comparably small imp
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 and 196: Appendix 201 II. Derivation of para
Page 197 and 198: Appendix 203 Tab. A-4: Tree species
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
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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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