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Assessing the impact of climate change on the spatial distribution of multiple
ecosystem goods and services in mountain forests.
Ché Elkin Harald Bugmann
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Forest dynamics….. … and climate change impacts
EGS • Biodiversity • Protection (gravitational hazards) • Forest harvest
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•Biodiversity • Protection Spatial correlations? (gravitational hazards) Changes through time? • Forest harvest
EGS
Forest dynamics….. … and climate change impacts
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Wind throw
Fire
Disease
Harvest
Landclim: forest simulation model
• Spatially explicit (25 x 25 m cells)
• Dynamic, process based
• Modeling of succession
• Cohort based
• Dynamics of tree cohorts:
establishment, growth, mortality
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Assessing the current and future state of forest ecosystem goods
Species Cohort Biomass (tones/ha)
Stem #
Picea abies 1960 3.474 4
Picea abies 1995 0.011 12
Pinus cembra 1994 0.010 11
Abies alba 1982 0.020 2
Abies alba 1983 0.018 1
EGS •Biodiversity • Protection • Forest Harvest
25 m Visp
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Case study: Valais, Switzerland
Climate scenario IPCC 4: a1b
future climate
(2100)
current climate
Visp
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Forest biomass 2000 2050 2100
Forest state: Forest biomass (tons /625m2)
Visp
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Forest state Changes in species composition through time (2000 – 2200)
Bio
mas
s B
iom
ass
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EGS Dynamics
• Biodiversity
• Protection from gravitational hazards
• How do EGS response through time to climate drivers ?
• How do EGS respond spatial to climate drivers ?
• Where are EGS correlated?
• When are EGS correlated?
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Biodiversity
Protection against gravitational hazards
Structural Shannon’s index
Rock fall
EGS changes
2000 2050 2100
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Shannon’s Structural Index
2000 State
2010 2020 2030 2040 2050
2060 2070 2080 2090 2100
2010 2050 2100
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State 2000
Rock fall protection
2010 2020 2030 2040 2050
2060 2070 2080 2090 2100
2010 2050 2100
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EGS correlations: transition
2100 2100
Transition correlation • Changes in EGS through time • Assessment of drivers of EGS change
Biodiversity Rock fall
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EGS correlations
Correlations in EGS transitions • Value normalized based on year 2000 maximum (landscape)
∆x = Xfuture – X2000 ∆x > 0.15 2 Strong gain 0.05 < ∆x < 0.15 1 Weak gain -0.05 < ∆x < 0.05 0 No change -0.15 < ∆x < -0.05 -1 Weak loss ∆x < -0.15 -2 Strong loss
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EGS Correlations: Transition
2001 2050 2100
- 4 Negative correlation + 4 Positive correlation
Positive correlations only
- 4 both EGS weaken + 4 both EGS strengthen
EGS correlation
2100
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EGS Correlations: Transition
2001 2050 2100
Negative correlations only
+ 4 Rock fall strengthens, Biodiversity weakens - 4 Biodiversity strengthens, Rock fall weakens
- 4 Negative correlation + 4 Positive correlation
EGS correlation
2100
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Conclusions
Forest state • low elevations: decrease in biomass, shift towards drought
tolerant species • high elevations: increase biomass
Biodiversity • increase at landscape scale • decrease at low elevations, increase at middle/ high elevation
Rock fall • decrease at landscape scale (not monotonic) • decrease at low and intermediate elevations, but increase at
higher elevations
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Conclusions
EGS correlations Climate driven changes in rock fall and biodiversity are generally positively correlated (at the landscape scale) Positive correlations • Low elevations: both decrease • very High elevations: both increase
Negative correlations • Time dependent (less spatial consistency)
• 2050 : rock fall strengthens , biodiversity weakens • 2100: biodiversity strengthens, rock fall weakens