Different temperature response of
broadleaf and conifer species alters
productivity predictions of boreal
forests under climate change
Tapio Linkosalo1), Pasi Kolari2), Raisa Mäkipää1),
Jukka Pumpanen2), Annikki Mäkelä2)
1) Finnish Forest Research Institute, Vantaa research unit, Finland,
2) Dept. of Forest Ecology, University of Helsinki, Finland.
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The CC-TAME (Climate Change: Terrestrial Adaptation & Mitigation in
Europe) project concentrates on assessing the impacts of agricultural,
climate, energy, forestry and other associated land-use policies considering
the resulting feed-backs on the climate system in the European Union.
CC-TAME’s international consortium is composed of 16 highly recognized
multi-disciplinary science partners who will carry out the project during 2008 2011.
A technologically explicit bottom-up approach on the farm/forest management
practice level to full fledged sector analysis allows the CC-TAME consortium
to assess "The efficiency of current and future land-use adaptation and
mitigation processes" on various levels:
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Land-use practice (fertilization, tillage, thinning etc…)
Land-use change (e.g. bioenergy potential)
Economic efficiency (cost minimization) - economic potential and competitive
economic potential
Efficiency of policy instruments (e.g. subsidies, auctioning of environmental
services, taxes)
Effectiveness with respect to political implementability and acceptability
Gross Primary Production (GPP) -model
Potential GPP calculated with PreLuEd model(*) (also used
in PipeQual):
P = fAPAR·[β · f(I)] · f(T) · f(H2O) · f(CO2), where
β max. potential photosynthetic rate
f(I) irradiance modifier
fAPAR absorbed fraction of radiation [varies for species and sites]
f(T) temperature/phenology modifier
f(H2O) VPD/soil water modifier
f(CO2) CO2 modifier
(*) Model from: A. Makela et al., 2008. Developing an empirical model of stand GPP with the LUE
approach: analysis of eddy covariance data at five contrasting conifer sites in Europe. Global
Change Biology 14:92-108
Vegetation subzones follow nicely the
temperature sum areas -> datapoints
can be classified to subzones based
on TS!
•Hemiboreal, TS >1250 DD
•South boreal, 1100 < TS < 1250
•Mid-boreal, 900 < TS < 1100
•North boreal, TS < 900 DD
Change in productivity (GPP) over 100 years relative to "no
change" -scenario
Temperature / phenology the major difference in
productivity between conifers and broadleaf species
Therefore, lets take a closer look where the difference
comes from!
Temperature modifier combines the effect of :
– Photosynthetic rate depending on air temperature
– Phenology
For conifers, a rate function following air temperature
with delay (for frost resistance)
For broadleaves, a rate function following immediate air
temperature,
In addition, a temperature sum model to predict timing of
leaf bud burst
F(T) –function for (both) conifers and broadleaf species:
xk =
TMean − Tmin
Tmax − Tmin
∆S =
xk − S k
τ
 0, S < 0

f (T ) = S ,0 ≤ S ≤ 1
 1, S > 1

Variable: TMean = daily mean air temperature (°C)
Parameters:
Conifer:
Broadleaf:
Tmax = 13.2 (°C), Tmin = -3.9 (°C), τ = 6.4 (days)
Tmax = 17.0 (°C), Tmin = 0 (°C), τ = 1 (days)
Current climate:
Annual development of
f(T) averaged over years,
for a site in Southern
Finland (Hyytiälä)
Changed climate:
Conclusion:
– Temperature function is the main difference between conifers
and broadleaf species
– The difference comes from the different value for saturating
temperature:
Parameters:
Conifer:
Tmax = 13.2 (°C), Tmin = -3.9 (°C), τ = 6.4 (days)
Broadleaf:
Tmax = 17.0 (°C), Tmin = 0 (°C), τ = 1 (days)
Are the parameter values valid?
Momentarily values:
From Hyytiälä:
– 15+ °C for pine
– up to 25 °C for aspen
from literature:
• 18 °C for spruce (Bergh et al. 2003)
• 22 °C for cottonwood (Sigurdsson 2001)
• 24 °C beech (Freeman 1998)
Take-home message:
Broadleaf species show a larger potential for growth
increase with climatic warming, due to their higher
optimal temperature for photosynthesis
Thank you
Precipitation,
snow melt
Soil water -model
• Soil water model(*) is a simple "open bucket" -type
model,
• Soil water holding capacity is the (metric) difference
between wilting point and field capacity
• The difference translates to the maximum water layer
thickness that the soil can hold
• Soil water holding capacity depends on soil thickness,
soil type, texture etc.
• for modeling purposes volume of retended water is
sufficient!
(*) based loosely on Duursma, R. A. et al. 2006. Predicting the
decline in daily maximum transpiration rate of two pine stands
during drought based on constant minimum leaf water potential
and plant hydraulic conductance, Tree Physiology 28, 265–276.
Evapotranspiration
Runoff,
drainage
Soil water -model
• Precipitation comes from meteorological data
• Evapotranspiration calculated as:
Et = (E0 ⋅ f ( I ) ⋅ f (T ) ⋅ f ( D) + a1 ⋅ PAR + a2 ) ⋅ f (θ )
300
280
260
Soil moisture (mm)
•f(I) = PAR - does not
saturate!
•separate functions for VPD
and soil water
•constant and PAR-related
term for wintertime
evaporation
240
220
200
180
160
140
120
Observed
100
80
01-98
Predicted
01-99
01-00
01-01
01-02
01-03
Date
01-04
01-05
01-06
01-07