Transcript Modelling Climate Change Impacts on Woodlands James Morison

Modelling Climate Change
Impacts on Woodlands
James Morison
Centre for Forestry & Climate Change
Duncan Ray
Centre for Human & Ecological Sciences
Climate Impacts Modelling Conference,
19-20 March, Gregynog
FR Climate Change programmes
Introduction
Adaptation:
assist and encourage forest planners, managers, and
owners in adapting forests and woodlands to the changing climate,
and using those woodlands to help society adapt.
Managing Forest C and GHG balances: understand and
quantify C stocks, and processes determining changes, and how
management influences GHG balance.
Protecting Soil and Water Resources: evaluate the impact
of forests and woodlands on soil and water resources to support the
development and implementation of sustainable forest management.
Land Use and Ecosystem Services: the role of trees,
woodlands and forest in delivering ecosystem services, and the role
of biodiversity in provisioning ecosystem services; landscape scale.
All using climate change information, models and data
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Outline
Examples of recent research on climate change
impacts by FR:
• Expert system tree species suitability models
with CC projections
• Linking ESC to forestry ‘yield models’ for
energy forestry projections
• Using process models for forest growth and
for short rotation coppice
• Forest & woodland planning
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Recent climate trends in Wales
Growing season temperature change
Average of Aberporth, Ross and Valley
800
600
+10%
ATemperature Anomaly
400
200
0
-200
1942
1947
-400
1952
1957
1962
1967
1972
1977
1982
1987
1992
1997
2002
2007
-10%
-600
-800
Year
(accumulated temperature anomaly relative to 1961-1990 year mean)
4
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Modelling tree species suitability
Using climate projections
for adaptation recommendations
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Analysing key climatic drivers
Accumulated Temperature > 5oC (day.°C), 2080
Moisture Deficit (mm), 2080
(Using UKCIP02)
See: www.ukcip.org.uk, www.forestry.gov.uk/climatechange/wales
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Frequency of dry summers
Projected frequency of Moisture Deficit ≤ 200 mm
(2091-2100)
Community Climate Change Consortium for Ireland, C4I, http://www.c4i.ie/
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Calculating probability
Projected change in frequency of SMD (High emissions)
Suitable
Unsuitable
100
Cumulative frequency
90
80
2020s
70
2040s
60
50
2060s
40
30
2080s
20
Baseline
10
0
40
70
100
130
160
190
220
260
Moisture
deficit (mm)
annual
Moisture
Deficit - MD [mm]
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ESC-DSS
The Ecological Site Classification Decision
Support System (ESC-DSS)
‘Expert system’ that focuses on key factors of sites that
influence tree growth of different species
• Accumulated temperature
• Soil moisture deficit
• Windiness
•Continentality, climatic zones
• Soil moisture regime
• Soil nutrient regime
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ESC-DSS
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Response curves ESC-DSS
Potential
Yield Class
(Spp.)
Moisture deficit
Windiness
Continentality
Soil moisture
regime
Soil nutrient
regime
Yield Class = PYC x min(MDf, Df, Cf, SMf, SNf)
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ESC projections
Sitka spruce
2050, High
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2080, High
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Species diversity guidance 2010
•
East and south Wales are most at risk of
drought and provide the best opportunities for
change. Review planting proposals for
vulnerable sites – shallow soils, south facing
and, or, dry sites
•
In west Wales, target plantings at lower
elevations on better soils for opportunities
to diversify tree species
•
For conifer blocks, presume Douglas fir and
other redwoods will be the preferred where site
and exposure allow
•
Limited opportunities in the exposed peaty gley
dominated uplands. Presume ALL
opportunities will be taken to utilise site
variations to increase species diversity
•
Improve and expand existing habitat
networks (for example ancient woodland,
native woodland and riparian zones) will be the
focus of expansion of native species
•
Advice supporting policy on adaptation measures
Create stands of mixed conifer and broadleaf
where it will meet strategic and local objectives
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Sycamore SRF yield
Combining ESC suitability with
forestry Yield Models
Change in % sycamore yield,
2050/baseline
(assumed 20 year rotation)
-100%
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0
+100%
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Eric Casella & colleagues, FR,
project for UKERC
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Modelling SRC willow
Process-based model, ForestGrowth-SRC
Matt Tallis, Southampton Univ.,
Eric Casella, FR, project for
UKERC
•Soil input data: Harmonised World Soils Data (HWSD v1.1)
•Meteorological input data : 25km2 monthly variables
•Future climate scenarios: UKCP09 SCP (2020 to 2050) low, med, high emissions
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Modelling SRC willow
1 km2 resolution
HWSD
1990-2000 climate
Matt Tallis, Southampton Univ.,
Eric Casella, FR, project for
UKERC
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Straits Inclosure CO2 flux site, Alice Holt
(Matt Wilkinson, Mark Broadmeadow, Ed Eaton et al. , FR)
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SPA modelling of woodland CO2 fluxes
2007
2008
2009
Not capturing early
canopy development
Mat Williams, Univ. Edinburgh, Eric Casella, FR
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2009
Climate & phenology
Spring leafing variability
4th May
2010
2011
(Toshie Mizunuma, Univ. Edinburgh,
Matt Wilkinson, FR)
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Modelling phenology and CO2 flux
Using camera images to derive
vegetation indices to use in light
interception models of GPP
Implications also for other woodland biodiversity
Toshie Mizunuma, Univ. Edinburgh, Matt Wilkinson, FR
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Forest planning case studies
MOTIVE case study in Clocaenog forest :
• effects of climate change on tree growth,
species suitability and wind risk
• effect of adaptation through species
diversification on sustainability indicators
•predict and optimise forest design plans.
•measure impacts on various sustainability
indicators (GVA, biodiversity, C stock,
recreation, jobs etc…)
Forest Design assessed under two scenarios:
• Traditional conservative, ‘private forest company’, replacing like with like
• Adaptive, forward thinking, more mixed species and age stands
(Bruce Nicoll & colleagues, FR, with European partners)
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Impacts of diversification
‘BAU’
Stakeholders
(planners) consulted
about changes to tree
species and forest
management system
‘Adaptation’
CC projections link to multi-disciplinary adaptation research
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Other areas of climate change impacts research
• Abiotic risks
• wind, fire, flood
• Biotic risks:
• pests and pathogens: types, species, incidence, severity, timing
• invasive species
• Socio-economic impacts
• Valuation, jobs, financial risk,
• Operational consequences
• timing of operations,
• altered infrastructure requirements
• Planning and policy
• Peatland restoration
• Woodfuel demand; re-introducing management
• Urban greenspace development
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Summary
• Multiple aspects of FR’s research are on climate
change
• Impacts, Adaptation, Mitigation
• Mixture of CC impacts modelling
•
•
•
•
•
•
‘expert knowledge’ model on species suitability
Semi-empirical yield models
Process models for energy crops, woodland C
Spatial modelling critical
Socio-economic modelling
Strong link to evidence and experiments
• Abiotic risk: wind, fire
• Biotic risk: pest & pathogen
• Key elements of multi-disciplinary assessment of
future woodland and forest management
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Thank you !
[email protected]
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