Duncan Ray and Louise Sing, Forest Research, UK

email: duncan.ray@forestry.gov.uk

Climate Matching in T4F WP8 Spatial research to promote more resilient

European forests to support the emerging green bio-economy

Presentation overview • WP8 output • Climate Matching – what is it? • Conceptual diagram and methods • Model development and testing • Some Results – Some uncertainty • Potential outcomes • Some questions to stakeholders

1. Develop infrastructure for the

spatial description of species and provenance site suitability models.

2. Make available climate matching tools for species and provenance selection in Europe.

3. Tools will help identify material suitable for adapting forestry to reduce the impacts of climate change.

WP8 – Spatial modelling work package - overview

• Task 8.1 – Climate Matching tool • Task 8.2 – Database development for Douglas fir, ash and European beech • Task 8.3 – Provenance breeding zone models • Task 8.4 – Final report

• Main partners –

o Forest Research, Roslin, UK o INRA, Orleans and Nancy, France o Alterra, Wageningen, The Netherlands o Thunen Institute, Germany o ICAS, Romania o CRA, Italy

What does the climate matching algorithm do?

• For any site in Europe identified by a latitude and longitude the application looks up baseline and future climate projections for the site, and calculates the closest matches of either the current climate or, the projected future climate, to contemporary climates from around the world

• Being developed as a web application tool for the Trees4Future website

Concept diagram

Web application method

Climate matching methods • Tested the method published by Broadmeadow et al 2005

– Uses three climate parameters • Monthly mean temperature, total monthly rainfall, monthly diurnal

temperature range – Calculates climatic difference (CD) scores (low CD = good match)

• Tested some variations on this method • Tested a standardised model

– the 3 parameters are standardised to apply equal weighting in low CD score – a transformation is included to prevent compensation giving a low CD score – all parameters must contribute to a low CD score

• Testing each of these models with 12 month data and growing season data

Broadmeadow M, Ray D, Samuel C (2005) Forestry 78 (2):145-167

Graphical user interface testing

• Different GCMs • Baseline or future

projection • SRES scenarios -

A1B only available • Different climate

matching models • Periods over which

the climate is matched – all year or just growing season

Parameter distribution for Forêt d’Orléans

0

50

100

150

200

250

300

Tmea

n1

tmea

n2

tmea

n3

tmea

n4

tmea

n5

tmea

n6

tmea

n7

tmea

n8

tmea

n9

tmea

n10

tmea

n11

tmea

n12

Degr

ees C

*10

Mean monthly temperature

WorldClim 1971-2000

ECHAM5 2050s

ECHAM5 2080s

HadCM3 2050s

HadCM3 2080s

0

20

40

60

80

100

120

140

160

dtr1

dt

r2

dtr3

dt

r4

dtr5

dt

r6

dtr7

dt

r8

dtr9

dt

r10

dtr1

1 dt

r12

Degr

ees C

*10

Daily temperature range

WorldClim 1971-2000

ECHAM5 2050s

ECHAM5 2080s

HadCM3 2050s

HadCM3 2080s

0 10 20 30 40 50 60 70 80 90

100

prec

1 pr

ec2

prec

3 pr

ec4

prec

5 pr

ec6

prec

7 pr

ec8

prec

9 pr

ec10

pr

ec11

pr

ec12

Mea

n m

onth

ly p

reci

pita

tion

(mm

)

Precipitation

WorldClim 1971-2000

ECHAM5 2050s

ECHAM5 2080s

HadCM3 2050s

HadCM3 2080s

Baseline climate matching results for Forêt d’Orléans • Baseline analysis –

Broadmeadow model 12 month period

• Baseline analysis – Broadmeadow model Growing season

• Baseline analysis – Standardised model 12 month period

• Baseline analysis – Standardised model Growing season

Future climate matching results for Forêt d’Orléans

• GCM ECHAM5 Standardised model – 12 month period

• GCM ECHAM5 Broadmeadow model – 12 month period

• GCM ECHAM5 Standardised model – Growing period

• GCM HadCM3 Standardised model – 12 month period

• GCM HadCM3 Broadmeadow model – 12 month period

• GCM HadCM3 Standardised model – Growing period

Expected outcomes • Green bio-economy in Europe

– Greater use of renewable resources in society, including wood products – Transition from a fossil fuel economy to a renewable and resource

efficient society – Forestry and wood industry in Europe

269 billion € 3 million people

• Climate matching – tool to provide information, knowledge, and a societal

understanding of changes in the suitability of tree species and provenance across Europe – Help adaptation thinking – Develop resilient forest ecosystems and forestry business – Increase the supply of biomass and timber for society – Help maintain progress in the transition from fossil fuels to renewables

Some questions to stakeholders 1. Our initial thoughts were that this tool (and the additional modelling tasks

of WP8) will be of interest to tree breeders, nurseries, and researchers. Is this the case?

2. Uncertainty - in GCMs – in matching methods – in SRES, will a user guide and recommendations discussing the best use of the tool suffice ?

3. Are the tools of interest to forest managers and planners? E.g. where do we look for novel species and forest management systems that are suited to the projected climate of 2080?

4. With the additional provenance suitability modelling framework in WP8, will the new information to add to adaptation knowledge?

5. Is the web application implementation plan useful?

Thank you for your attention