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

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48 Chapter 3 photosynthesis (gALGF, Fig. 3.2). Gap models are geometrically explicit in the vertical dimension, but most of them use a very simple approach to model crown geometry: All the leaves are assumed to be concentrated at the top of the stem (Botkin et al. 1972a,b). This assumption is not as unrealistic as it may appear; for example, Schulze et al. (1977) found that in a Picea excelsa forest more than 70% of the annual CO 2 uptake was attributable to the needles exposed to direct sunlight at the top of the crown. Leemans and Prentice (1989) argued that sun angles in the boreal zone often are so low that most direct sunlight incides from the side and not from above, making an explicit consideration of true crown geometry necessary. For the present study, which deals with forests at temperate latitudes where sun angles are much higher, the simple crown geometry of conventional forest gap models (Shugart 1984) seems appropriate. The following climate dependent constraints are used in FORCLIM: The direct effects of temperature are modelled as the annual sum of degree-days (uDD). Woodward (1988) showed that this index correlates well with the distribution of plant species (gDDGF), although it may lack a physiological basis (Bonan & Sirois 1992). The water content of the rooting zone is used to model the effect of drought stress (uDrStr) on growth (gSMGF, Cramer & Prentice 1988), assuming that it is indicative of the water availability for plants. In their classic fertilizer trials, Mitchell & Chandler (1939) found that tree growth increases in a well predictable manner with increasing soil nitrogen concentrations (uAvN). Aber et al. (1979, 1982) and Pastor & Post (1985) incorporated these findings in forest gap models, and the same approach is used in FORCLIM (gSNGF). The possible direct effects of atmospheric CO 2 on tree growth (“CO 2 fertilization”) are still hotly debated in the literature (e.g. Eamus & Jarvis 1989, Overdieck & Forstreuter 1991, Körner 1993). While the short-term effects of enhanced CO 2 concentrations on photosynthesis and water-use efficiency of tree seedlings and saplings seem to be well established (e.g. Strain & Cure 1985), the long-term effects on older trees and whole ecosystems remain undetermined and can not be extrapolated simply from the findings at smaller scales (Eamus & Jarvis 1989). These authors also noted that at the ecosystem scale “recourse must be made … to modelling” (p. 8). Simulation studies dealing with this problem typically found that the response at the ecosystem scale is much smaller than the increase in the growth rate of the single trees (e.g. Shugart & Emanuel 1985) or even that there is no response at the ecosystem scale at all (e.g. Luxmoore et al. 1990). Based on these studies and in view of the large uncertainties concerning this issue, the hypothesized direct effects of atmospheric CO 2 on tree growth are neglected in FORCLIM.
The forest model FORCLIM 49 gBFlag ForClim-P: Plant submodel ForClim-E: Environment submodel uWiT uDD gWFlag gDFlag gDDGF ESTABLISHMENT gLFlag cumulative LAI uDrStr gSMGF D GROWTH gALGF ForClim-S: Soil submodel uAvN Plant litter gSNGF intrinsic mortality disturbances MORTALITY slow growth S G r Fig. 3.2: Structure of the plant submodel FORCLIM-P. Square boxes denote state variables; boxes with rounded edges are auxiliary variables. Arrows from x to y indicate that y = ƒ(x), and broken lines denote the calculation of input/output variables. The identifiers are explained in the text. The final problem for calculating the annual diameter increment of trees is: How shall the several growth factors be combined to arrive at one single, composite index of environmental conditions? In the JABOWA model (Botkin et al. 1972a,b) all the growth factors were combined in a multiplicative manner to reduce the maximum diameter increment. This approach is based on the assumption that all the factors are mutually dependent and that any favourable factor can compensate for any other unfavourable factor, which may
Page 1: Diss. ETH No. 10638 On the Ecology
Page 4 and 5: ii Table of contents A BSTRACT.....
Page 6 and 7: iv APPENDIX .......................
Page 8 and 9: vi Harald BUGMANN, 1994: On the eco
Page 10 and 11: viii Harald BUGMANN, 1994: Aspekte
Page 13 and 14: 1 1 . Introduction 1.1 Climatic cha
Page 15 and 16: Introduction 3 1.2 Methods for the
Page 17 and 18: Introduction 5 in a changing climat
Page 19 and 20: Introduction 7 Their integrative ca
Page 21 and 22: Introduction 9 (1984) provides a mo
Page 23 and 24: Introduction 11 The main advantage
Page 25 and 26: 13 2 . Analysis of existing forest
Page 27 and 28: Analysis of existing forest gap mod
Page 39 and 40: The forest model FORCLIM 45 carbon
Page 41: The forest model FORCLIM 47 TREE GR
Page 45 and 46: 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 91 and 92: Behaviour of FORCLIM along a transe
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Behaviour of FORCLIM along a transe
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Parameter sensitivity & model valid
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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
Page 181 and 182:
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
Page 189 and 190:
References 195 Rudloff, W., 1981. W
Page 191 and 192:
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
Page 251 and 252:
Appendix 257 Tab. A-22 (continued)
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