Marc Hanewinkel Marc Hanewinkel Freiburg, Germany Freiburg, - - PowerPoint PPT Presentation

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Marc Hanewinkel

Freiburg, Germany

Marc Hanewinkel

Freiburg, Germany

Baden-Württemberg Forest Research Institute Baden-Württemberg Forest Research Institute

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Baden-Württemberg Forest Research Institute

Natural risks and long term forest management

Marc Hanewinkel Forest Research Institute of Baden-Württemberg

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Baden-Württemberg Forest Research Institute

Natural risks and long term forest management

• 1. Introduction
• 2. Lessons learnt from „Lothar“
• 3. „Lothar“ and the aftermath
• insect calamities
• carbon sequestration
• timber industry
• 4. What comes next ?

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Baden-Württemberg Forest Research Institute

Introduction

26.12.1999 ‘Lothar‘

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Baden-Württemberg Forest Research Institute

Introduction

Recent large storm disturbances in Europe 1990 – „Vivien/Wiebke“ >100 million m3 1999 – „Lothar/Martin“ >180 million m3 2005 – „Gudrun/Sweden“ > 75 million m3

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Baden-Württemberg Forest Research Institute

• Vulnerability of different tree species
• Influence of tree height and height / diameter ratio (h/d)
• Influence of exposure (TOPEX)
• Influence of geographic position
• Goal: Regionalization – mapping of potential risk
• Database: National Forest Inventory in Germany (2002)

Lessons learnt – a risk model

Lessons learnt

4 B D A C

150 m

(M.Schmidt, J.Bayer, G.Kändler)

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Baden-Württemberg Forest Research Institute

Lessons learnt

Comparing tree height and species

Spruce Fir Beech

P (Storm damage) Tree height (m) Spruce Fir Beech Spruce Fir Beech

Schmidt et al. (2006)

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Baden-Württemberg Forest Research Institute

################################################################################################################################################################################################################################################################################################################################################################################################################################

3450000 3455000 3460000 3465000 3470000

• 400
• 200

R echtswert

• 1*Topex-Index

3450000 3455000 3460000 3465000 3470000 200 400 600 800

R echtswert Seehöhe ü. NN [m]

Topex: topographic exposure

The Windthrow Research Group, University of British Columbia

Height a.s.l Easting Easting

Schmidt et al. (2006)

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Baden-Württemberg Forest Research Institute

Lessons learnt

• Influence of tree height and geographic position (large-scale

airflow - conditions)

# # # # # # #

# # # # # # #

S U MA HD KA FR RV

10 20 30 40 50 0.0 0.2 0.4 0.6 0.8 1.0

Baumhöhe [m] P (Sturmschaden)

P (Storm damage) Tree height

10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230 240 250 260 270 280 290 300 310 320 330 340 350

N S O W

Schmidt et al. (2006)

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Baden-Württemberg Forest Research Institute

Lessons learnt

Spatial autocorrelation

3400000 3450000 3500000 3550000 3600000 5300000 5400000 5500000

Rechtswert Hochwert

Sturmschadenswahrscheinlichkeit Thin Plate Regression Spline

Stuttgart Ulm Karlsruhe Freiburg Ravensburg Bad Mergentheim Oberkirch

Probability of storm damage

g(πi) = Xi β + f (north; easti) + Zib + εi

2-dimensional function to assess spatial influence

Northing Easting

Schmidt et al. (2006)

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Baden-Württemberg Forest Research Institute

Lessons learnt

Spatial autocorrelation

RW HW P (Sturmschaden)

Sturmschadenswahrscheinlichkeit Thin Plate Regression Spline

g(πi) = Xi β + f (north; easti) + Zib + εi

2-dimensional function to assess spatial influence

E a s t i n g N

• r

t h i n g

Probability of storm damage

Probability of storm damage

Schmidt et al. (2006)

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Baden-Württemberg Forest Research Institute

Lessons learnt

Regionalization – map of potential risk

Northern Black Forest

1 . . . . . 6

• .

. . . . . 3 4 5 6 5 2 0 0

• 0. -

1 0 2 0 3 0 4 0. 7

P (storm damage): Schmidt et al. (2006)

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Baden-Württemberg Forest Research Institute

• Regionalization of risk based on digital

terrain model (DTM) and inventory data and original meteorological conditions

" 0,000106 - 0,050000 " 0,050001 - 0,100000 " 0,100001 - 0,150000 " 0,150001 - 0,200000 " 0,200001 - 0,250000 " 0,250001 - 0,300000 " 0,300001 - 0,350000 " 0,350001 - 0,400000 " 0,400001 - 0,450000 " 0,450001 - 0,500000 " 0,500001 - 0,550000 " 0,550001 - 0,600000

Risk-classes

Schmidt et al. (2006)

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Baden-Württemberg Forest Research Institute

• Regionalization of risk based on digital

terrain model (DTM) and inventory data and meteorological conditions type: centre of „Lothar“ - damage

" 0,000106 - 0,050000 " 0,050001 - 0,100000 " 0,100001 - 0,150000 " 0,150001 - 0,200000 " 0,200001 - 0,250000 " 0,250001 - 0,300000 " 0,300001 - 0,350000 " 0,350001 - 0,400000 " 0,400001 - 0,450000 " 0,450001 - 0,500000 " 0,500001 - 0,550000 " 0,550001 - 0,600000

Risk classes

Schmidt et al. (2006)

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Baden-Württemberg Forest Research Institute

Lessons learnt

Forest management implications

• Use large disturbances to build risk models (learn lessons !)
• Use topex (northing/easting) to map and regionalize the risk (exposure, wind

direction)

• Reduce height ! Decrease h/d (e.g. reach diameters earlier !)
• Choose adequate species

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Baden-Württemberg Forest Research Institute

Natural risks and long term forest management

• 1. Introduction
• 2. Lessons learnt from „Lothar“
• 3. „Lothar“ and the aftermath
• insect calamities
• carbon sequestration
• timber industry
• 4. What comes next ?

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Baden-Württemberg Forest Research Institute

The aftermath Insect calamities

• Bark beetle attacks in the follow-up of „Lothar“

Biberach Staat U lm Wangen B ü h l H

• rb

Vellberg Leutkirch Ehingen Künzelsau Vaihingen L a h r Pfullendorf Z e l l Eppingen Schöntal Engen H eilbronn Bretten C railsheim Schrozberg Sulz R adolfzell Aalen Backnang Mengen Ellwangen Sinsheim Langenau Überlingen Meßkirch G öppingen Weinheim BadWaldsee Buchen Bopfingen Bruchsal O b e r k i r c h T ettnang Adelsheim Stuttgart Blaustein Karlsruhe St aufen O chsenhausen Lörrach Stockach Albstadt Wertheim Walldürn R astatt R avensburg R

• ttw

eil Breisach Kirchheim Nürtingen N agold B a li n g e n Riedlingen Triberg Münsingen H errenberg G aildorf Jestetten G iengen Steinheim Rottenburg N euenstadt Wolf ach Kenzingen Hechingen O f f e n b u r g Leonberg G eislingen Mössingen Mosbach G undelsheim R eutlingen Donaueschingen E l z a c h K e h l i n R h e i n a u O berndorf Schorndorf Biberach-Staat H eidenheim Schramberg Lichtenstein Bad Urach H a u s a c h C alw Blaubeuren Schwetzingen W e h i n g e n Kandern Welzheim Stühlingen Z wiefalten Karlsbad N e u e n b ü r g Bonndorf Lorch T uttlingen Ette n h e i m T i tisee-N eustadt BadSchussenried Esslingen Spaichingen T auberbischofsheim Bad Mergentheim S t . M ä r g e n Immendingen R

• senfeld

F urtwangen H eidelberg Mühlacker Scho p f h e i m B a d S ä c k i n g e n Pforzheim Maulbronn Emm e n d i n g e n Rosenberg Murrhardt W a l d k i r c h T

• d

t m

• s

Eberbach G schw end Schwäbisch Gmünd Alpirsbach K i r c h z a r t e n S t . B l a s i e n Philippsburg Lauda- Königshofen Schwäbisch Hall Abtsgmünd S c h l u chsee S c h w a rz a c h Müllheim/Baden Löwenstein Altensteig G ammertingen W a l d shut-Tiengen Burladingen F reudenst adt F reiburg-S t a d t R

• tenfels

G ernsbach Neckargmünd T

• d

t n a u H ardt Baiersbronn Weil im Schönbuch Bad Liebenzell G e n g e n b a c h O berkochen B aden-BadenStadt Villingen-Schwenningen Stadt S c h ö n a u S c h w a r z w a l d Pf alz- grafenweiler T übingen Bebenhausen Bad Wildbad Enzklösterle Biberach-Stadt B a d Peterstal

• G

riesbach F

• rbach

Klosterreichenbach Bad H errenalb Villingen- Schwenningen St aat Bad Rippoldsau

• Schapbach

Murgschifferschaft in Forbach H

• spitalw

ald Dinkelsbühl

K äferh

• l

z f m

• 5

5 1

• 2

5 2 5 1

• 5

5 1

• 7

5 7 5 1

• 1

1 1

• 1

5 1 1 5 1

• 2

2 1

• 3

ü b e r 3

K ä f e r b e f a l l

n

a c h

F o

r s t b e z i r k e n

G e s a m t w a l d B a d e n

• W

ü r t t e m b e r g

ZSLF V S z

S t a n d 3 1 . 1 . 2 2

Bark beetles after „Lothar“ 2002 Storm damage due to „Lothar“

Weigerstorfer (2006)

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Baden-Württemberg Forest Research Institute

The aftermath Insect calamities

Bib era ch Sta at U lm Wangen B ü h l H

• rb

Vellberg L eutkirch Eh ingen Kü nzelsau Vaihingen L a h r Pfulle ndo rf Z ell Ep pingen Schöntal En gen H eilbro nn Bretten C railsheim Schrozberg Su lz R adolfzell Aalen Backnang Me n gen Ellwa ng en Sinsh eim La ngenau Ü berlinge n Meßkirch G öppin ge n Weinh eim Bad Waldsee Bu chen Bo pfinge n Bru chsal O berkirch T et tnang Ade lsh eim Stuttga rt Bla ustein Ka rlsruhe S t a u f e n O chse nh ausen Lörra ch Stockach Alb stad t Wertheim Walld ürn R a stat t R a vensburg R

• ttw

eil Bre isach Kirchheim N ürt in gen N agold B a li n g e n R iedlingen T riberg Mü nsingen H e rre nbe rg G aildorf Je ste tten G ieng en Steinh eim R

• ttenburg

N e ue nstadt Wolfach Ke nzi n g e n H echingen O f f e n b u r g L eon be rg G eislinge n Mössingen Mosbach G un delshe im R eutling en D

• na

ue schingen E l z a ch K e h l i n R h e i n a u O be rnd

• rf

Schorndorf Bibera ch

• Sta

at H eidenheim Schramb erg Lichte nstein BadUra ch H a usach C alw Blaubeuren Sch wetzing en W e h i n g e n Kandern We lzhe im Stüh lingen Z wiefalten Karlsbad N e u e n b ü r g Bo nndorf L

• rch

T uttlin ge n E t t e n h e i m T itisee-N eu stad t Bad Schu ssenried Esslinge n Sp aichinge n T aube rbischofsheim BadMerg en th eim S t . M ä rge n Immendingen R

• se

nfeld F urtw a ngen H e id elbe rg Mühlacke r S c h

• p

f h e i m B a d S ä c k i n g e n Pforzheim Maulbronn E m m e n d i n g e n R

• sen

berg Murrhardt W a l d k i r c h T

• d

t m

• s

Ebe rba ch G schw end Schwä bisch Gmün d Alpirsba ch K i r c h z a r t e n S t . B l asien Philippsburg La ud a- Kö nigsho fen Sch wä bisch Hall Abtsg mün d Schluchse e S c h w a rz a c h Müllh eim/Bad en Löwenstein Altensteig G amm ertin gen Wa ld shut-Tie ng en Burladin gen F reu denstadt F r e i b u r g

• S

t a d t R

• tenfels

G ern sbach N ecka rgmü nd T

• d

t n a u H ard t Baiersbronn Weil im Schönbu ch Ba d Lieb enzell G e n g e n bach O berkochen Ba den

• Baden Stadt

Villing en-Schw enn in ge n Stad t S c h ö n a u S c h w a r z w a l d Pfalz- g ra fenwe iler T übin gen Bebenhausen Bad Wildb ad En zklösterle Biberach-Sta dt Bad Peterstal

• Grie

sbach F

• rbach

Klost erreich en ba ch Bad H erre nalb Villingen- Sch wen ningen St aat Bad Rippo ld sau

• Sch

apbach Mu rgschifferscha ftin Fo rba ch H

• spitalw

ald Dinke lsbüh l

Käfer h

• l

z f m

• 5

5 1

• 2

5 2 5 1

• 5

5 1

• 7

5 7 5 1

• 1

1 1

• 1

5 1 1 5 1

• 2

2 1

• 3

ü b e r 3

K ä f e r b e f a l l

n

a c h

F

• r s

t b e z i r k e n

G e s a m t w a l d B a d e n

• W

ü r t t e m b e r g

Z SLF V S z

S t a n d 3 1 . 1 2 . 2 4

Bark beetles after „Lothar“ 2004 Storm damage due to „Lothar“

Weigerstorfer (2006)

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Baden-Württemberg Forest Research Institute

The aftermath Insect calamities Storm damage due to „Lothar“

C alw B iberach O r t e n a u k r e i s R av ensbu rg O stalbkreis H eilbronn Ras tatt Waldshut K arlsruhe R eu tlinge n Rottw eil S igm aring en K

• nstanz

L

• errac

h S chw aebisc hH all A lb-D

• nau-Kreis

T uttlingen M ain-Ta uber-Kreis E nzkreis Freudens tadt E ss ling en Z

• llernalbkreis

B

• eblingen

R he in-Ne ckar-Kreis L udwigs burg G

• eppingen

H eidenheim R em s-M urr-Kre is B r e i s g a u

• H
• c

h schwarzw ald Hoh enlohek reis Tuebingen N eckar-Odenw ald-K reis E m m e n d i n g e n B

• dense

ekreis S chw arzwald-Baar-Kreis U lm S tuttgart M annheim K arlsruhe-Stadt B aden-Baden H eidelbe rg P forz heim F reiburg i m B r e i s g a u Heilbronn-Stadt Käferholz fm 0 - 200 2001 - 5 5001 - 1 10001

• 3

30001

• 5

50001

• 8

80001

• 1

100001

• 1

5 über 1 5

I n s e k t e n s c h ä d e n

N

a d e l h

• l z

e i n s c h l a g n a c h F

• r s

t b e z i r k e n

G e s a m t w a l d

B

a d e n

• W ü

r t t e m b e r g

S t a n d 3 1 . 1 . 2 5

Z SLF V S z

Bark beetles after „Lothar“ 2005

Weigerstorfer (2006)

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Baden-Württemberg Forest Research Institute

Cross-correlation Storm-Insects

The aftermath Insect calamities

• 2nd peaks:

10-11yrs (storm) and 15yrs (snow)

• Cross-

correlation Storm/Insects:

• up to 6 years

Hanewinkel et al. (2006)

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Baden-Württemberg Forest Research Institute

The aftermath Carbon sequestration

C-removal due to „Lothar“ 1999

• Living biomass (above

ground)

• Total C affected:

8.2 Million t C

• Enrichment in snags

(deadwood): 1.3 Million t C Removal due to storm :

6.9 Million t C

Zell et al. (2006)

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Baden-Württemberg Forest Research Institute

The aftermath Carbon sequestration

Change in C-pools

• Important pool :

– Coarse woody debris – (= large pieces of dead down wood )

• Increase in this pool from

– 2,93 t C / ha (average) to – 8,93 t C / ha (storm affected)

Zell et al. (2006)

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Baden-Württemberg Forest Research Institute

The aftermath The timber industry

5 10 15 20 bis 10 10-20 20-30 30-40 40-50 50-60 60-70 >70

BHD-Stufen [cm mR] Vorrat [Mio. m³ V mR]

BWI I WW 99 BWI II

1987 1999 2002 DBH- classes (cm) Standing volume (million m3) <

Norway spruce (SW-Germany, State Forest )

Kändler (2006)

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Baden-Württemberg Forest Research Institute

Forest management implications

• Extent of insect outbreaks after disturbances often underestimated
• Pest management as integrated part of risk management
• Accumulating standing volume might not always be a wise strategy for

C-sequestration

• Adapt your risk-management strategy to the needs of the timber

industry

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Baden-Württemberg Forest Research Institute

Natural risks and long term forest management

• 1. Introduction
• 2. Lessons learnt from „Lothar“
• 3. „Lothar“ and the aftermath
• insect calamities
• carbon sequestration
• timber industry
• 4. What comes next ?

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Baden-Württemberg Forest Research Institute

What comes next?

Climate scenario for Climate scenario for SW Germany (KLIWA) SW Germany (KLIWA)

• sum of yearly precipitations

+ 250 mm

• N days with heavy rain

Ø + 11

• change in distribution of rain

(wet winters)

• average yearly temperature

+ 1,5°C

• N summer days

Ø + 20

• N heat days

+ 50 %

• N frost-/ice-days

– X

• sum of yearly precipitations

+ 250 mm

• N days with heavy rain

Ø + 11

• change in distribution of rain

(wet winters)

• average yearly temperature

+ 1,5°C

• N summer days

Ø + 20

• N heat days

+ 50 %

• N frost-/ice-days

– X

storm flooding heat drought insects

?

Weigerstorfer (2006)

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Baden-Württemberg Forest Research Institute

What comes next?

Salvage cuttings SW-Germany public forest (1953-1970 / 1979-2005)

500 1.000 1.500 2.000 1953 1958 1963 1968 1980 1985 1990 1995 2000 2005 1000 m 3

"Wiebke" 1990 "Lothar" 1999

Weigerstorfer (2006)

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Baden-Württemberg Forest Research Institute

What comes next?

Salvage cuttings SW-Germany public forest (1953-1970 / 1979-2005)

500 1.000 1.500 2.000 1953 1958 1963 1968 1980 1985 1990 1995 2000 2005 1000 m 3

"Wiebke" 1990 "Lothar" 1999

Weigerstorfer (2006)

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Baden-Württemberg Forest Research Institute

What comes next?

Storm damage probabilities

• Storm damage

probability increases

– at higher elevations, – with higher timber volume, – …, – across the century.

Hanewinkel et al. (2006)

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Baden-Württemberg Forest Research Institute

What comes next?

Periodicity of storm-damage

• Power spectrum

estimation

• Harmonic analysis
• Maxima for

harmonics at frequency 11 yrs for storm

Hanewinkel et al. (2006)

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Baden-Württemberg Forest Research Institute

Forest management implications

• Scientific analysis instead of fatalism
• Realistic scenarios instead of „worst-case scenarios“
• Probabilities, amount of damage and periodicity of disturbances are

needed (long term time series !!)

• Use information to build insurance models for storm damage
• Use new technologies to conserve timber after large disturbances

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Baden-Württemberg Forest Research Institute

Thank you for your attention !!