Optimization of Forest Regeneration Under Climate Change In Ontario

Where to Source and Replant Forests Under Climate Change?
A case study of black spruce and white pine in Ontario
Jing
a
a
Yang ,
Dan
b
McKenney ,John
b
Pedlar
and Alfons
c
Weersink
Graduate Student at Dept. of Food, Agricultural and Resource Economics, University of Guelph, b Canadian Forest Service, Natural Resources Canada, Sault Ste. Marie,
c Professor at Dept. of Food, Agricultural and Resource Economics, University of Guelph
Why the research is important
§  In productive forest zones of Ontario, the average annual
temperature could increase by 4.20C and annual
precipitation could increase by 30% at the end of this
century1.
§  Rapid climate change may outpace the rate of forest
adaption. In the short term, locally adapted populations are
likely to experience climates to which they are not well
adapted2,3.
§  Given millions of seedlings need to replant in Ontario,
there is concern about the appropriate means for
successfully regenerating Ontario’s forests.
What we found
Take-home message
Yield Response to Climate
§  Forest investors could benefit from
alternative seed strategies
§  Temperature at planting site is the most important climatic factor
Ø  Best yield at site temperature of 4-60C for black spruce and 120C for
white pine
Note: MAT is short for mean annual temperature
What motivated us
§  Given forest is sensitive to climate, how will climate
change affect black spruce and white pine growth in
Ontario?
§  Given the prospect of climate change and long-term
nature of forest, what is the MOST economically
efficient seed strategy (i.e., seed procurement and
deployment) under rapid changing climate?
What we did
§  Estimated tree response to climate using universal response
function (URF)3
Height of seed source from population j at planting site i =
f(climate variables at planting site, climate variables at seed
source site)
§  Applied the URF into Faustmann model4 in assessing the
net present value of regeneration selections under climate
change
Net present value (NPV)= discounted revernue from stumpage
price and harvested volume - discounted regeneration cost
To know more
Jing Yang
(519) 362-8629
[email protected]
Species
Seed Strategy
Local
Seed
Seed
Replantation Procurement Deployment
White
Pine
Site
Location
Black
Spruce
Rotation
Age (year)
Volume
(m3/ha)
Net Present
Value ($/ha)
Site
Location
Rotation
Age (year)
Volume
(m3/ha)
Net Present
Value ($/ha)
North Bay
( 46.30N,
-79.450W)
50
42.290N,
-83.200W
44.040N,
-83.790W
50
45
421
465
366
887
1009
951
Hearst
(49.70N,
-83.670W)
55
45.380N,
-93.200W
51.130N,
-74.200W
55
55
104
111
105
-60
-43
-58
Note: NPV ($/ha) Diversity for White Pine for Seed
Procurement (red circle:North Bay)
Note: NPV ($/ha) Diversity for White Pine for
Seed Deployment (red circle:North Bay)
Ø  They could gain additional $17/ha for
black spruce and $122/ha for white
pine from sourcing seed from a
specific location (i.e., seed
procurement).
Ø  Replanting black spruce and white
pine at a alternative planting site (i.e.,
seed deployment) could achieve a
NPV that is $2/ha higher for black
spruce and $64/ha higher for white
pine than local replantation.
§  Under climate change, local seed is no
longer ideal
Ø  Most suitable seed source for both
species is from a relative southern
region.
Ø  Highest yield for black spruce
occurs at a region with mean annual
temperature of 4-60C.
Ø  White pine grows best at a location
with mean annual temperature of
120C.
References
1) McKenney, D.W., J. Pedlar and G. O’Neill. 2009. Climate change and
forest seed zones: past trends, future prospects and challenges to ponder.
Forestry Chronicle 85(2): 258-266.
2) Morgenstern, E. K. 1996. Geographic variation in forest trees: genetic
basis and application of knowledge in silviculture. Vancouver, BC:
University of British Colombia press.
3) Wang, T., A. Hamann, A. Yanchuk, G.A. O’Neill and S.N. Aitken.
2006. Use of response functions in selecting lodgepole pine populations for
future climate. Global Change Biology 12(12): 2404-2416.
4) Chang, S.J. 1984. Determination of the optimal rotation age: a theoretical
analysis. Forest Ecology and Management 8(2): 137-147.