Assessing the impact of climate change on the spatial distribution of multiple

ecosystem goods and services in mountain forests.

Ché Elkin Harald Bugmann

che.elkin@env.ethz.ch

Forest dynamics….. … and climate change impacts

EGS • Biodiversity • Protection (gravitational hazards) • Forest harvest

•Biodiversity • Protection Spatial correlations? (gravitational hazards) Changes through time? • Forest harvest

EGS

Forest dynamics….. … and climate change impacts

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

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

Case study: Valais, Switzerland

Climate scenario IPCC 4: a1b

future climate

(2100)

current climate

Visp

Forest biomass 2000 2050 2100

Forest state: Forest biomass (tons /625m2)

Visp

Forest state Changes in species composition through time (2000 – 2200)

Bio

mas

s B

iom

ass

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?

Biodiversity

Protection against gravitational hazards

Structural Shannon’s index

Rock fall

EGS changes

2000 2050 2100

Shannon’s Structural Index

2000 State

2010 2020 2030 2040 2050

2060 2070 2080 2090 2100

2010 2050 2100

State 2000

Rock fall protection

2010 2020 2030 2040 2050

2060 2070 2080 2090 2100

2010 2050 2100

EGS correlations: transition

2100 2100

Transition correlation • Changes in EGS through time • Assessment of drivers of EGS change

Biodiversity Rock fall

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

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

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

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

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

che.elkin@env.ethz.ch