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

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156 Chapter 6 500 Ulmus scabra Quercus robur Biomass (t/ha) 400 300 200 100 0 500 700 900 1100 1300 1500 Quercus petraea Populus tremula Populus nigra Fraxinus excelsior Fagus silvatica Castanea sativa Betula pendula Alnus incana Alnus glutinosa Acer pseudoplatanus Acer platanoides Abies alba Year Fig. 6.2: Simulation results at the site “CLIMINDEX” for the years 525-1525 AD when sampling the weather stochastically from the long-term statistics (Tab. 6.1). The simulation starts with a bare plot in the year 525. 500 Ulmus scabra Quercus robur Biomass (t/ha) 400 300 200 100 0 1500 1600 1700 1800 1900 Quercus petraea Populus tremula Populus nigra Fraxinus excelsior Fagus silvatica Castanea sativa Betula pendula Alnus incana Alnus glutinosa Acer pseudoplatanus Acer platanoides Abies alba Year Fig. 6.3: Simulation results at the site “CLIMINDEX” for the years 1525 to 1979 AD when using the reconstructed weather data from Pfister (1988) to drive the FORCLIM-E model. The initial state of the forest is taken from the results presented in Fig. 6.2.
Model applications 157 6.2 Possible effects of future climatic change on forest ecosystems in the European Alps Any assessment of the possible effects of future climatic change on forest ecosystems is faced with a twofold problem: First, there is a considerable uncertainty inherent in the predictions of future climate, both on the global and even more pronounced on the regional scale (Houghton et al. 1990, 1992, Wigely & Raper 1992). Second, every forest model incorporates different and highly simplified parametrizations of ecological processes; these certainly contain errors both on the quantitative and maybe even on the conceptual level (Solomon 1986, Shugart & Prentice 1992). Thus, it appears to be more promising to analyse the behaviour of several ecological models under several scenarios of climatic change instead of focusing on just one model and one scenario. This approach also emphasizes that such studies are tests of the sensitivity of forests ecosystems to climatic changes, and not predictions of their future structure and functioning. In this section, scenarios of climatic change will be used that refer to the year 2100, and it will be assumed that the climatic parameters reached by then can be used to define a new, constant climate. It is undisputed that this assumption is unrealistic because there is no evidence that climatic change would come to a halt by the end of the next century (Houghton et al. 1990, 1992). Again, it should be noted that the simulation results obtained like this do not constitute predictions of the future state of forests in the European Alps, but simple sensitivity tests. First, let us assume that there was one forest model that we could favour over all the others. How does this model behave when it is exposed to several climate scenarios? How sensitive are the projections obtained from the forest model to the differences between these climate scenarios? Second, given that there was no uncertainty in the prediction of future climate, i.e. that one climate scenario could be identified unequivocally as the “best estimate”, how does the behaviour of several forest models compare under this climate scenario? Are the projections on future forest ecosystem structure sensitive to the assumptions incorporated in the various forest models? Third, even if we could favour one climate scenario over the others, there is some uncertainty inherent in this scenario. How sensitive are the projections obtained from a forest model to these uncertainties?
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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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Page 99 and 100: Behaviour of FORCLIM along a transe
Page 115 and 116: Parameter sensitivity & model valid
Page 147 and 148: 153 6 . Model applications Climatic
Page 149: Model applications 155 The simulate
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 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
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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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