The Relationship between
Light Availability and
Understory Spruce Growth
Complex Stand Conference, February 20 2007
Rasmus Astrup, Scientist
BV Research Centre
Complex stands
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Trees grow for
extended periods in
shaded conditions
Complex stand management
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Complex stand
management require
focus on understory
trees
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To forecast stand
dynamics and
growth we need to
understand predict
understory tree
growth
Light availability as predictor of
understory tree growth
‡
Light is the main driver of photosynthesis and affect tree
growth
‡
Understory light availability is relatively simple to quantify
and predict
‡
Understory light availability is often correlated to belowground resource availability
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Understory light availability is the resource that we directly
control through silvicultural treatments in complex stands
What does the relationship between light
and understory spruce growth look like?
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Compile existing regression models of juvenile
spruce growth as a function of light
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Transform the predicted values for height increment
to cm/year
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Transform the predicted values for radial increment
to mm/year
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Plot the relationships in one graph
Existing regression models of spruce height
increment as a function of light availability
Existing regression models of spruce height
increment as a function of light availability
Reasons for the differences in the
light-growth relationships
Methodology:
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Different tree sizes
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Different functional forms for the regression models
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Different sampling methodologies (e.g. methods of light measurement
and site types)
Other Explanations:
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Different Picea species (white spruce, Engelmann spruce, black spruce,
and interior spruce)
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Different regional macro-climatic conditions
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Different canopy-types (aspen-dominated versus conifer-dominated)
Growth as a Function of Light in different regions of
western boreal and sub-boreal Canada
Sampling Methodology
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All sampling was performed on
mesic sites with average nutrient
availability
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Sampled between 80 – 120
individual trees/ region
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Measured height and radial
increment
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Estimated light availability for
each tree with a hemispherical
photo
Analysis
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A large set of regression models of height and
diameter increment as a function of light and tree size
were fitted the data
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The best approximating model was selected with the
model selection criterion AICC
‡
Tested for regional differences in the light-growth
relationship
Results
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The best approximating model was found to be a logistic
function where the asymptote increase linearly with tree size:
a + b × Diameter
Increment =
1 + e ( c − d × Light )
(
)
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Strong evidence was found for regional variation in the lightgrowth relationship
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To represent the regional variation, regional estimates for
parameters b and c were utilized, while global parameters
were estimated for parameters a and d
Spruce Regional Height Increment
Models
Each line represent a regression model for an individual geographic region
Spruce Regional Radial Increment
Models
Each line represent a regression model for an individual geographic region
Linear and Asymptotic light-growth
relationships
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Approximately linear relationships were found in the
conifer-dominated forest of western British Columbia
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Asymptotic relationships were found in aspendominated stands in the boreal mixedwood region
(Alberta, Saskatchewan, and Fort Nelson (BC))
Two types of regional variation in the
light-growth relationship
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Differences in growth rates at full light availability
(maximum growth rates)
‡
Differences in the shape of the light-growth
relationship (asymptotic versus approximately linear)
‡
How do we explain these two types of variation?
Three Possible Explanations
1.
Different Picea species (white spruce,
Engelmann spruce, black spruce, and interior
spruce)
2.
Different regional macro-climatic conditions
3.
Different canopy-types (aspen-dominated
versus conifer-dominated)
Tested the explanations in a framework
of multiple working hypotheses
‡
Each explanation is
represented by
several mathematical
models
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The level of support
for each model is
determined with AICC
Explaining Regional Variation in growth at
full light
Explaining Regional Variation in the shape of
the Light-Growth Relationship
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Shape of each individual regression model was represented
by the fraction of full light growth that was obtained at 50%
light.
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A number close to 1 represents a asymptotic relationship
while a number close to 0.5 represents an approximately
linear relationship
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Data consisted of all the published regression models and the
developed models developed for this study
%Increment obtained at 50% light
The Effect of Canopy Type
Conceptual Effect of Canopy Type
Conclusion
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Spruce does not have one general shape of the light-growth
relationship
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There is regional variability in the shape of the light-growth
relationship
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The variation in growth a full light to be best explained by
climatic variables
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For understory spruce, the variation in the shape of the lightgrowth relationship is best explained by differences between
aspen- and conifer-dominated canopies
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Under aspen-dominated canopies generally asymptotic while it
is approximately linear in conifer-dominated
Thank You
Acknowledgements
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For help and advise:
„
„
‡
Dave Coates
Bruce Larson
Funding
„
„
„
FIA-FSP
MWMA
BC Ministry of Forests
Why do we have to understand this regional
variation in the light-growth relationship
‡ Can
we transfer experience/knowledge
between regions?
‡ Are
growth models portable between regions?
Management implications of a linear versus
an asymptotic light-growth relationship
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Linear relationship: approximately 50% of potential
increment obtained at 50% light
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Asymptotic relationship: approximately 70% of the
potential height increment is obtained at the 50%
light availability
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In a management context, this has quite large
impact on targets for understory light availability
and optimal gap sizes in partial cutting strtegies