The 2006 Marcus Wallenberg Prize Symposium -...

Marc HanewinkelFreiburg, GermanyMarc HanewinkelFreiburg, GermanyBaden-Württemberg Forest Research InstituteBaden-Württemberg Forest Research Institute

Baden-Württemberg Forest Research Institute

Natural risks and long term forest management

Marc Hanewinkel

Forest Research Institute of Baden-Württemberg



1. Introduction2. Lessons learnt from „Lothar“3. „Lothar“ and the aftermath

• insect calamities• carbon sequestration• timber industry

4. What comes next ?


Introduction

26.12.1999 ‘Lothar‘


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


• 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

DA

C

150 m

(M.Schmidt, J.Bayer, G.Kändler)


Lessons learnt

Comparing tree height and species

SpruceFirBeech

P (S

torm

dam

age)

Tree height (m)

Spruce Fir Beech

Spruce Fir Beech

Schmidt et al. (2006)


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

3450000 3455000 3460000 3465000 3470000-400

-200

0

R echtswert

-1*T

opex

-Inde

x

3 450000 3455000 3460000 3465000 3470000200

400

600

800

R echtswert

Seeh

öhe

ü. N

N [m

]Topex: topographic

exposure The Windthrow Research Group, University of British ColumbiaH

eigh

t a.s

.l

Easting

Easting



Lessons learnt

• Influence of tree height and geographic position (large-scaleairflow - conditions)

#

#

#

#

#

#

#

#

#

#

#

#

#

#

S

U

MA

HD

KA

FR

RV0 10 20 30 40 50

0.0

0.2

0.4

0.6

0.8

1.0

Baumhöhe [m]

P (S

turm

scha

den)

P (S

torm

dam

age)

Tree height

0

010 20

3040

5060

70

80

90

100

110

120130

140150

160170180

190200210

220230

240

250

260

270

280

290

300310

320330

340 350

N

S

OW



Lessons learnt

Spatial autocorrelation

3400000 3450000 3500000 3550000 3600000

5300

000

5400

000

5500

000

Rechtswert

Hoc

hwer

t

SturmschadenswahrscheinlichkeitThin 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

Nor

thin

g

Easting



Lessons learnt

Spatial autocorrelation

RWHW

P (S

turmschaden)

SturmschadenswahrscheinlichkeitThin Plate Regression Spline

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

2-dimensional function to assess spatial influence

EastingNorthing

Probability of storm damage

Probability of storm dam

age



Lessons learnt Regionalization – map of potential risk

Northern Black Forest

0

1

.

.

...

6

-.....

.3456

5

2

0 00 -0 -0 -0 -0 -0. -

10 20 30 40.0

7

P (storm damage):



• 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



• 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



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, winddirection)

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

• Choose adequate species


The aftermath Insect calamities

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

BiberachStaat

Ulm

Wangen

B ü h l

Horb

Vellberg

Leutkirch

Ehingen

Künzelsau

Vaihingen

L a h r

Pfullendorf

Z e l l

Eppingen

Schöntal

Engen

Hei lbronnBretten

Crailsheim

Schrozberg

Sulz

Radolfzell

Aalen

Backnang

Mengen

Ellwangen

Sinsheim

Langenau

Überlingen

Meßkirch

Göppingen

Weinheim

BadWaldsee

Buchen

Bopfingen

Bruchsal

O b e r k i r c h

Tettnang

Adelsheim

Stuttgart

Blaustein

Karlsruhe

Staufen

Ochsenhausen

Lörrach

Stockach

Albstadt

Wertheim

Walldürn

Rastatt

Ravensburg

Rottweil

Breisach

KirchheimNürtingen

Nagold

BalingenRiedlingen

Triberg

Münsingen

Herrenberg

Gaildor f

Jestetten

Giengen

Steinheim

Rottenburg

Neuenstadt

Wolfach

Kenzingen

Hechingen

O f f e n b u r g

Leonberg

Geislingen

Mössingen

Mosbach

Gundelsheim

Reutlingen

Donaueschingen

E l z a c h

K e h l i n R h e i n a u

Oberndorf

Schorndorf

Biberach-Staat

Heidenheim

Schramberg

Lichtenstein

Bad Urach

H a u s a c h

Calw

Blaubeuren

Schwetzingen

Wehingen

Kandern

Welzheim

Stühlingen

Zwiefalten

KarlsbadNeuenbürg

Bonndorf

Lorch

Tuttlingen

Ette n h e i m

T i tisee-Neustadt

BadSchussenried

Esslingen

Spaichingen

Tauberbischofsheim

Bad Mergentheim

S t . M ä r g e n Immendingen

Rosenfeld

Furtwangen

Heidelberg

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 o d t m o o s

Eberbach

Gschwend

Schwäbisch Gmünd

Alpirsbach

K i r c h z a r t e n

S t . B l a s i e n

Phil ippsburg

Lauda-Königshofen

Schwäbisch Hall

Abtsgmünd

S c h l u chsee

Schwarzach

Müllheim/Baden

Löwenstein

Altensteig

Gammertingen

W a l d shut-Tiengen

Burladingen

Freudenstadt

Freiburg-S t a d t

Rotenfels

Gernsbach

Neckargmünd

T o d t n a u

Hardt

Baiersbronn

Weil imSchönbuch

Bad Liebenzell

G e n g e n b a c h

OberkochenB aden-BadenStadt

Villingen-SchwenningenStadt

S c h ö n a u S c h w a r z w a l d

Pfalz-grafenweiler

TübingenBebenhausen

BadWildbad

Enzklösterle

Biberach-Stadt

B a d Peterstal- G riesbach

Forbach

Klosterreichenbach

BadHerrenalb

Villingen-Schwenningen

Staat

BadRippoldsau-Schapbach

Murgschifferschaft in Forbach

Hospitalwald Dinkelsbühl

Käferh o l z f m 0 - 5 0 0 5 0 1 - 2 5 0 0 2 5 0 1 - 5 0 0 0 5 0 0 1 - 7 5 0 0 7 5 0 1 - 1 0 0 0 0 1 0 0 0 1 - 1 5 0 0 1 1 5 0 0 1 - 2 0 0 0 0 2 0 0 0 1 - 3 0 0 0 0 ü b e r 3 0 0 0 0

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

ZSL FV Sz

S t a n d 3 1 . 0 1 . 2 0 0 2

Bark beetles after „Lothar“2002

Storm damage due to „Lothar“

Weigerstorfer (2006)



BiberachStaat

Ulm

Wangen

B ü hl

Horb

Vellberg

Leutkirch

Ehingen

Künzelsau

Vaihingen

L a h r

Pfullendorf

Z ell

Eppingen

Schöntal

Engen

HeilbronnBretten

Crailsheim

Schrozberg

Sulz

Radolfzell

Aalen

Backnang

Mengen

Ellwangen

Sinsheim

Langenau

Überlingen

Meßkirch

Göppingen

Weinheim

Bad Waldsee

Buchen

Bopfingen

Bruchsal

O berkirch

Tettnang

Adelsheim

Stuttgart

Blaustein

Karlsruhe

S t a u f e n

Ochsenhausen

Lörrach

Stockach

Albstadt

Wertheim

Walldürn

Rastatt

Ravensburg

Rottweil

Breisach

KirchheimNür tingen

Nagold

BalingenRiedlingen

Triberg

Münsingen

Herrenberg

Gaildorf

Jestetten

Giengen

Steinheim

Rottenburg

Neuenstadt

Wolfach

Kenzi n g e n

Hechingen

O f f e n b u r g

Leonberg

Geislingen

Mössingen

Mosbach

Gundelsheim

Reutlingen

Donaueschingen

E l z ach

K e h l i n R h e i n a u

Oberndorf

Schorndorf

Biberach-Staat

Heidenheim

Schramberg

Lichtenstein

BadUrach

Hausach

Calw

Blaubeuren

Schwetzingen

Wehingen

Kandern

Welzheim

Stühlingen

Zwiefalten

KarlsbadNeuenbürg

Bonndorf

Lorch

Tuttlingen

E t t e n h e i m

Titisee-Neustadt

Bad Schussenried

Esslingen

Spaichingen

Tauberbischofsheim

BadMergentheim

S t . M ä rgen

Immendingen

Rosenfeld

Furtwangen

Heidelberg

Mühlacker

S c h o 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

Rosenberg

Murrhardt

W a l d k i r c h

T o d t m o o s

Eberbach

Gschwend

Schwäbisch Gmünd

Alpirsbach

K i r c h z a r t e n

S t . B l asien

Philippsburg

Lauda-Königshofen

Schwäbisch Hall

Abtsgmünd

Schluchsee

Schwarzach

Müllheim/Baden

Löwenstein

Altensteig

Gammertingen

Waldshut-Tiengen

Burladingen

Freudenstadt

Fr e i b u r g - S t a d t

Rotenfels

Gernsbach

Neckargmünd

T o d t n a u

Hardt

Baiersbronn

Weil imSchönbuch

Bad Liebenzell

G e n g e n bach

OberkochenBaden-Baden Stadt

Villingen-SchwenningenStadt

S c h ö n a u S c h w a r z w a l d

Pfalz-grafenweiler

TübingenBebenhausen

BadWildbad

Enzklösterle

Biberach-Stadt

Bad Peterstal-Griesbach

Forbach

Klosterreichenbach

BadHerrenalb

Villingen-Schwenningen

Staat

BadRippoldsau-Schapbach

Murgschifferschaft in Forbach

Hospitalwald Dinkelsbühl

Käfer h o l z f m 0 - 5 0 0 5 0 1 - 2 5 0 0 2 5 0 1 - 5 0 0 0 5 0 0 1 - 7 5 0 0 7 5 0 1 - 1 0 0 0 0 1 0 0 0 1 - 1 5 0 0 11 5 0 0 1 - 2 0 0 0 02 0 0 0 1 - 3 0 0 0 0 ü b e r 3 0 0 0 0

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


ZSLFV Sz

S t a n d 3 1 . 1 2 . 2 0 0 4







Calw

Biberach

O r t e n a u k r e i s

Ravensburg

Ostalbkreis

Heilbronn

Rastatt

Waldshut

Karlsruhe

Reutlingen

Rottweil

Sigmaringen

Konstanz

Loerrac h

Schwaebisch Hall

Alb-Donau-Kreis

Tuttlingen

Main-Tauber-Kreis

Enzkreis

Freudenstadt

Esslingen

Zollernalbkreis

Boeblingen

Rhein-Neckar-Kreis

Ludwigsburg

Goeppingen Heidenheim

Rems-Murr-Kreis

B r e i s g a u - H o c hschwarzwald

Hohenlohekreis

Tuebingen

Neckar-Odenwald-Kreis

E m m e n d i n g e n

Bodenseekreis

Schwarzwald-Baar-Kreis

Ulm

Stuttgart

Mannheim

Karlsruhe-Stadt

Baden-Baden

Heidelberg

Pforzheim

Freiburg i m B r e i s g a u

Heilbronn-Stadt

Käferholz fm 0 - 200 0 2001 - 5 0 0 0 5001 - 1 0 0 0 0 10001 - 3 0 0 0 0 30001 - 5 0 0 0 0 50001 - 8 0 0 0 0 80001 - 1 0 0 0 0 0 100001 - 1 5 0 0 0 0 über 1 5 0 0 0 0

I n s e k t e n s c h ä d e n N a d e l h o l z e i n s c h l a g

n a c h F o r s t b e z i r k e n


S t a n d 3 1 . 1 0 . 2 0 0 5

ZSLFV Sz




Cross-correlation Storm-Insects


• 2nd peaks: 10-11yrs (storm) and 15yrs (snow)

• Cross-correlation Storm/Insects:

• up to 6 years

Hanewinkel et al. (2006)


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 tostorm :

6.9 Million t C

Zell et al. (2006)


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)


The aftermath The timber industry

0

5

10

15

20bis 10

10-20

20-30

30-40

40-50

50-60

60-70 >70

BHD-Stufen [cm mR]

Vorr

at [M

io. m

³ V m

R]

BWI IWW 99BWI II

19871999

2002DBH- classes (cm)

Stan

din g

vol

ume

(mi ll

ion

m3 )

<

Norway spruce (SW-Germany, State Forest )

Kändler (2006)



• 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


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)


What comes next?

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

0

500

1.000

1.500

2.000

1953 1958 1963 1968 1980 1985 1990 1995 2000 2005

1000

m3

"Wiebke" 1990 "Lothar" 1999



What comes next?

Storm damage probabilities• Storm damage

probability increases– at higher elevations,– with higher timber

volume,– …,– across the century.



What comes next?

Periodicity of storm-damage

• Power spectrum estimation

• Harmonic analysis • Maxima for

harmonics at frequency 11 yrs for storm




• 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


Thank you for your attention !!

The 2006 Marcus Wallenberg Prize Symposium -...

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