Institute of Silviculture I Michael Maroschek 1

University of Natural Resources and

Life Sciences, Vienna

Department of Forest and Soil Sciences

Value-based trade-offs between ecosystem

services from European mountain forests

Mountain Forest Management in a Changing World

7-9 July 2015 – High Tatra Mountains

Alexandra Langner, Florian Irauschek, Susana Perez,

Marta Pardos, Tzvetan Zlatanov, Manfred J. Lexer

Institute of Silviculture I Alexandra Langner 2 2

Contents

Introduction – ES framework

– ES multi-functionality

Methods – Forest simulation modeling & MCDA

Results – Ranking of management alternatives

– Trade-offs

Conclusions

Institute of Silviculture I Alexandra Langner 3 3

Ecosystem services & trade-offs

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Aim of the study

To explore how preferable alternative forest management systems are for ecosystem service provisioning

– in three European mountain forest regions

– depending on different ecosystem service preferences

To identify value based trade-offs between these ecosystem services

management preferences climate

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Case Study Areas

Valsain de Montes, Spain

Iberian Central Mountains

Montafon, Austria

Eastern Alps

Rhodope Mountains, Bulgaria

Western Rhodopes

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Ecosystem service indicators

Timber production (TP) Total volume harvested [m3/ha]

Volume increment [m3/ha]

Stocking volume [m3/ha]

Carbon sequestration (CS) [t/ha]

Biodiversity and nature conservation (BDNC) Tree species diversity [Index]

Tree size diversity [Index]

Standing dead wood volume [m3/ha]

Bird habitat quality [Index]

Protection against gravitational hazards (PGH) Rockfall protection index [Index]

Avalanche protection index [Index]

Landslide protection index [Index]

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Model-simulations of ES indicators

Baseline climate (c0 ) and

five climate change scenarios (c1 to c5)

Management alternatives MCDA and trade-offs

ES indicators Forest models

Time period 2000 – 2100 divided into three periods

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MCDA – additive weighting

Overall utility = a1 x TP + b1 x CS + c1 x BDNC + d1 x PGH

TP = a1 x TVH + a2 x VI + a3 x V

CS = C_total

BDNC = a1 x D + a2 x H + a3 x SDWV + a4 x BHQ

PGH = a1 x RPI + a2 x LPI + a3 x API

TVH, VI, V

C_total preference

D, H, SDWV, BHQ functions

RPI, LPI, API

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Generic preference functions

Case study specific

Preference scale [0-1]

Linear functions

(with the exception of stocking volume)

Thresholds based on scientific literature,

inherent minima and maxima of the data

set or expert knowledge

Regional maxima

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Weighting of ecosystem services

Increasing importance

0 0,2 0,4 0,6 0,8 1,0

0,4 x TP + 0,2 x CS + 0,2 x BDNC + 0,2 x PGH

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Quantification of trade-offs

Trade-off calculation: root mean square deviation

A

B

C

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Results - ranking of mgmt alternatives…

Kendall‘s Tau Rank Correlation Coefficient c0-c5:

– Spain: 0,6 - 1,0

– Austria: 0,78 – 1,0

– Bulgaria: 1

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…considering multi-functionality

Kendall‘s Tau Rank Correlation Coefficient c0-c5:

– Spain: 0,4 - 1,0

– Austria: 0,81 – 1,0

– Bulgaria: 1

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Results - trade-offs

no management

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Trade-offs considering multi-functionality

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Conclusions

CS, BDNC and PGH are balanced contrary to TP

Minor effect of climate change on the management ranking order

and trade-offs

Trade-offs are high only for no management and TP-related ES pairs

ES indicators are no sustainability indicators

Institute of Silviculture I Michael Maroschek 17

University of Natural Resources and

Life Sciences, Vienna

Department of Forest and Soil Sciences

Contact:

Alexandra Langner

Institute of Silviculture, Department of Forest and Soil Sciences

Universitäty of Natural Resources and Life Sciences, Vienna

Peter Jordan-Straße 82, 1190 Wien

Tel.: +01 - 47654 4079

alexandra.langner@boku.ac.at

www.wabo.boku.ac.at/waldbau.html

Thank you!

This study has been supported by the EU through the Marie Curie Initial Training Networks (ITN)

action CASTLE, grant agreement no. 316020