Open Journal of Forestry
2012. Vol.2, No.1, 23-32
Published Online January 2012 in SciRes (http://www.SciRP.org/journal/ojf) http://dx.doi.org/10.4236/ojf.2012.21004
Copyright © 2012 SciRes. 23
Simulating Site-Specific Effects of a Changing Climate on Jack
Pine Productivity Using a Modified Variant of
the CROPLANNER Model
Peter F. Newton
Canadian Wood Fibre Centre, Canadian Forest Service, Natural Resources Canada, Ontario, Canada
Email: peter.newton@nrcan.gc.ca
Received September 17th, 2011; revised October 29th, 2011; accepted November 8th, 2011
This study evaluated the site-specific effects of projected future climate conditions on the productivity of
jack pine (Pinus banksiana Lamb.) plantations over the next 50 years (2011-2061). Climatic parameters
as predicted by the Canadian Global Climate Model in association with a regional spatial climatic model,
under 3 emissions scenarios (no change (NC), B1 and A2), were used as input values to a biophysical-
based site-specific height-age model that was integrated into the CROPLANNER model and associated
algorithm. Plantations managed under a basic silvicultural intensity on two site qualities at each of two
geographically separated sites (northeastern and northwestern Ontario, Canada) were assessed. The results
indicated that the stands situated on low-to-medium quality sites at both locations were largely unaffected
by the predicted increase in temperature and precipitation rates. Conversely, however, stands situated on
good-to-excellent quality sites grown under the B1 and A2 scenarios experienced consequential declines
in stand development rates resulting in decreases in rotational mean sizes, biomass yields, recoverable
end-product volumes, and economic worth. In addition to providing a plausible range of site-specific cli-
mate change outcomes on jack pine productivity within the central portion of the species range, these re-
sults suggest that future predictions that do not account for potential climate changes effects may overes-
timate merchantable productivity on the higher site qualities by approximately 15%. As demonstrated, in-
corporating biophysical-based site index functions within existing forest productivity models may repre-
sent a feasible approach when accounting for climate change effects on yield outcomes of boreal species.
Keywords: B1 and A2 Emission Scenarios; Low-to-Medium and Good-to-Excellent Site Qualities;
Basic Silvicultural Intensity Regimes
Introduction
Jack pine (Pinus banksiana Lamb.) occupies a wide range of
sites throughout the northern temperate forest region of North
America (Rudolph & Yeatman, 1982). Ecologically, jack pine
exhibits an ability to: 1) tolerate environment constraints (e.g.,
moisture and nutrient limitations); 2) temporarily exploit environ-
ments following severe disturbance (e.g., rapidly colonization
of recently-disturbed wildfire-burned sites due to its early matu-
rity (cone-bearing at 3 - 5 years of age), cone serotiny and asso-
ciated seed-dispersal habit (aerial dispersal of abundant viable
seeds following heat-induced opening of serotinous cones), and
favorable germination and seedling establishment conditions fol-
lowing wildfire (e.g., exposed mineral soil and temporary lack
of competing species)); and 3) intensely compete for environmen-
tal resources and/or physical space, as evident by its asymmetric
size-distributions and rapid rates of self-thinning as observed
within monospecific density-stressed populations. Jack pine is
one of the most economically important and intensely managed
species within the Canadian Boreal Forest Region (Rowe, 1972).
Specifically, in Canada’s largest province, Ontario, jack pine re-
presents 33% of the annual softwood volume harvested (OMNR,
2008). The principal products derived from this harvest are nor-
thern bleached softwood kraft pulp used to produce paperboard,
tissue products and newsprint, dimensional lumber (studs, struc-
tural joists and planks), and composite wood products that are
used in wood-frame residential house construction (Zhang &
Koubaa, 2008).
The effects of a changing climate on boreal ecosystems have
been estimated using a variety of different modeling approaches
(e.g., Myneni et al. (1997), Shaw et al. (2006), Girardin et al.
(2008), Kurz et al. (2009), Ise and Moorcroft (2010)). Although
contradictory tendencies have been reported, results from these
analyses have been useful in delineating a range of plausible out-
comes. At the regional level, recognition that the jack pine re-
source will be impacted by rapid changes in climate is well ap-
preciated throughout the forest management and scientific com-
munities (e.g., Parker et al., 2000; Colombo et al., 2007). Al-
though climate change projections vary by the type of model used,
emissions scenario considered, and locality assessed, the con-
sensus is that the climate within northeastern and northwestern
Ontario will undergo a consequential change over the next cen-
tury (Colombo et al., 2007). Given that jack pine exhibits a large
degree of phenotypic plasticity and has the ability to tolerate a
wide range of climatic and site conditions, it is important to es-
timate how this valuable resource will fair under a changed cli-
mate. Consequently, the objectives of this study were to simulate
climate change effects on the productivity of jack pine planta-
tions across a range of site qualities and locations. The approach
employed the CROPLANNER decision-support model (Newton,
2009) which was modified through the incorporation of a bio-
P. F. NEWTON
physical-based site-specific height-age function. This enabled
an empirical assessment of the effects of localized changes in
climate on jack pine productivity.
Briefly, CROPLANNER is an algorithmic analogue of the
structural stand density management model (SSDMM) which
was developed by expanding the stand density management dia-
gram modelling framework through the incorporation of distri-
bution recovery modules for diameter, height, biomass, carbon,
end-products, value and wood quality attributes (Newton, 2009).
Structurally, the model consists of a number of functional and
empirical quantitative relationships, which collectively represent
the cumulative effect of various underlying competition processes
on tree and stand yield parameters. The temporal dependency of
these processes is governed by the intensity of competition and
site quality as expressed by relative density index and site index,
respectively. As with most tree and stand simulators, the site-spe-
cific mean dominant height—age function largely governs the
rate of stand development. Consequently, accounting for the cu-
mulative effect of climate change through the use of a biophysi-
cal-based site-specific height-age function was considered a pru-
dent approach and is in accord with similar approaches used with
other tree and stand simulators (e.g., O’Neill & Nigh, 2011).
CROPLANNER, for a given density management regime, site
quality, rotation length, cost profile and set of merchantability
specifications, enables the estimation of overall productivity (e.g.,
mean annual volume, biomass and carbon increments), volume-
tric yields (e.g., total and merchantable volumes per unit area),
log-product distributions (e.g., number of pulp and saw logs),
biomass production and carbon sequestration outcomes (e.g.,
oven-dried masses of above-ground components and associated
carbon equivalents), recoverable end-products and associated mo-
netary values (e.g., volume and economic value of recovered chip
and dimensional lumber products) by sawmill-type (stud and
randomized length processing protocols), economic efficiency
(e.g., land expectation value), duration of optimal site occupancy,
structural stability, and bre attributes (e.g., wood density and
branch diameter). For a complete analytical description of the
approach used in the development and calibration of the modu-
lar-based SSDMM, refer to Newton (2009).
The scope of this analysis includes the consideration of the
effects of B1 and A2 emission scenarios (Nakicenovic et al.,
2000) relative to the null case of no climate change (NC). These
scenarios cover the plausible range normally considered by
policy makers and forest planners within the Province of On-
tario (Colombo et al., 2007). Specifically, the NC scenario was
based on climatic norms observed during the 1970-2000 period.
As defined by Nakicenovic et al. (2000), the B1 emission sce-
nario arises from a convergent world that is characterized by
global-based collaborative approaches to solving economic,
social, and environmental problems (i.e., best-case scenario).
The transition from conventional oil and gas resources to alter-
native energy systems is expected to be uneventful. Globally, the
population is expected to increase to 8.7 billion by 2050 but then
decline to 7.0 billion by 2100. The global gross domestic prod-
uct (GDP) is expected to increase to 136 billion (1990 US$/yr)
by 2050 and then to 328 billion (1990 US$/yr) by 2100. Proac-
tive nation-based environmental measures and associated poli-
cies are expected to result in relatively low anthropogenic
GHGs and aerosols emissions, reaching a maximum concentra-
tion of approximately 600 ppm by 2100 (IPPC, 2007). Relative
to the 1980-2000 period, the mean global temperature is ex-
pected to increase 2.4˚C by 2100 (IPPC, 2007).
Conversely, the A2 emission scenario is based on a hetero- ge-
neous and regionally differentiated world in terms of econo- mic
development, productivity, social structures and income equa- lity,
where the self-reliance and preservation of local identities is para-
mount (i.e., worst-case scenario; Nakicenovic et al., 2000). Al-
though attempts to control local environmental degradation will
occur, international co-operation in mitigating the effects of climate
change will be limited. The global population is expected to in-
crease to 11.3 billion by 2050 and then to 15.1 billion by 2100.
Global GDP is projected to increase to 82 billion (1990 US$/yr) by
2050 and then to 243 billion (1990 US$/yr) by 2100. This increase
in population growth combined with concurrent changes in land
use, and consumption of natural resources including the rapid de-
pletion of fossil fuels, will substantially increase GHGs and aero-
sols emissions, reaching a maximum concentration of approxi-
mately 1250 ppm by 2100 (IPPC, 2007). Resultantly, the mean
global temperature is expected to increase by approximately 3.4˚C
by 2010, relative to the 1980-2000 period (IPPC, 2007).
Material and Methods
Firstly, the CROPLANNER decision-support model (New-
ton, 2009) was modified through the inclusion of a biophysical-
based height-age model developed for jack pine plantations in
Ontario (Sharma et al., 2012). Specifically, the original site-based
height-age function developed by Carmean et al. (2001; Equation
(23) in Newton, 2009) was replaced by Equation (1):


1
ˆ
00
ˆˆ
1.31 1250.5
Ibh
HSA

  (1)
where
0
ˆ196.47 0.32090.376214.27790.0014,
wd g
PP TP
 aa
T
g
T
1
ˆ1.3757 0.00580.01140.2153,
wd
PP

H (m) is mean dominant height, SI is site index (mean domi-
nant height at a breast-height age of 25 yr), Abh is mean breast
height age (yr), Pw and Pd are total precipitation (mm) during
the wettest and driest period, respectively, Tg is the mean tem-
perature (˚C) during the growing season, Pa is the total precipi-
tation (mm) during the entire year, and Ta is the mean annual
temperature (˚C) during the entire year.
Secondly, climatic parameters (Pw, Pd, Tg, Pa and Ta) were
predicted by the Canadian Global Climate Model (V. 3.1; En-
vironment Canada, 2011) in association with a regional spatial
climatic model (McKenney et al., 2007). Two emissions sce-
narios (B1 and A2; Nakicenovic et al., 2000) for the 2011-2040
and 2041-2070 periods at two geographic locations (Kirkland
Lake, ON (Forest Section B7 Missinaibi-Cabonga (Rowe, 1972))
and Thunder Bay, ON (B.9 Superior (Rowe, 1972))) were speci-
fied. For the no change scenario (NC), corresponding climatic va-
riables for the 1970-2000 period were obtained from the regio-
nal spatial climatic model (McKenney et al., 2007) for the same
locations. The 2011-2040 and 2041-2070 values were com-
bined and means obtained for the entire 2011-2070 period in or-
der to avoid abrupt changes at the 2040-2041 transition point.
Table 1 lists the derived parameters for each location by scena-
rio and time period.
Thirdly, the simulations consisted of inputting the resultant
climatic values into the modified CROPLANNER model and
implementing density management regimes consistent with a
basic silvicultural intensity (Bell et al., 2008) on poor-to-medium
2
4 Copyright © 2012 SciRes.
P. F. NEWTON
Copyright © 2012 SciRes. 25
Table 1.
Climatic input parameters for the modified CROPLANNER model: climatic variables corresponding to the NC, B1 and A2 emission scenarios by
period and location.
Input Location (Forest Section)a
Parameter Kirkland Lake, ON (B.7 Missinaibi-Cabonga) Thunder Bay, ON (B.9 Superior)
[Denotation] NC B1 A2 NC B1 A2
1971
-
2000
2011
-
2040
2041
-
2070
2011
-
2070
2011
-
2040
2041
-
2070
2011
-
2070
1971
-
2000
2011
-
2040
2041
-
2070
2011
-
2070
2011
-
2040
2041
-
2070
2011
-
2070
Total precipitation during wettest
period (mm) [Pw] 98 99 98 99 107100104 87 91 91 91 97 87 92
Total precipitation during driest
period (mm) [Pd] 47 49 59 54 61 59 60 28 32 38 35 38 36 37
Mean temperature during growing
season (˚C) [Tg] 11.2 12.5 13.6 13.1 12.913.8 13.411.3 12.713.6 13.2 13.1 14.013.6
Annual precipitation (mm) [Pa] 865 885 951 918 951964 958720 765 816 791 811 811 811
Annual mean temperature (˚C) [Ta] 1.54 2.71 4.01 3.36 3.334.85 4.092.74 3.985.25 4.62 4.50 6.145.32
All forecasted values of the climatic parameters were derived from the Canadian Global Climate Model (Version 3.1; Environment Canada, 2011). Specific estimates for
the 2 locations were derived from the web-based customized spatial climatic model as described by McKenney et al. (2007). aLongitude and latitude in decimal degrees for
Kirkland Lake, ON and Thunder Bay, ON: –80.0333 and 48.1500, –89.2500 and 48.3833, respectively. Forest Section after Rowe (1972).
and good-to-excellent sites within each of the two locales. The
underlying objective of the basic silvicultural intensity is to shorten
the rotation length and increase product value. The actual crop
plan consisted of site preparation and vegetation management
treatments preceding the planting of 2000 seedlings per hectare
and allowing 500 seedlings per hectare to establish naturally as
ingress. Table 2 lists the input variables and model parameters
that were used.
Results
During the 2011-2070 period, both precipitation and temperatures
are predicted to increase at both the eastern and western Ontario
locations with the greatest increases occurring under the A2 emis-
sion scenario (Table 1). Specifically, relative to the 1971-2000
period (Table 1): 1) annual precipitation is forecasted to increase
6.1% and 10.8% and mean annual temperatures by +1.8˚C and
+2.6˚C under the B1 and A2 scenarios, respectively, at the north-
eastern locale; and 2) annual precipitation is forecasted to increase
9.9% and 12.6% and mean annual temperatures by +1.9˚C and
+2.6˚C under the B1 and A2 scenarios, respectively, at the north-
western locale. Simulating the effect of these increases on jack pine
plantations established at nominal initial spacing across a range of
site qualities using the CROPLANNER model (Table 2), enabled a
comparative analysis of 50 yr rotational productivity outcomes for
each emission scenario. Table 3(a) and Table 3(b) list the yield
estimates for the northeastern and northwestern locales, respec-
tively. Similarly, Tables 4(a) and (b) provide a set of relevant per-
formance metrics for the northeastern and northwestern locales,
respectively. Site-specific representations of the expected size-
density trajectories within the traditional stand density management
graphic for each scenario by site quality and geographic location
are shown in Figures 1 and 2: Figures 1(a) and (b) illustrate the
trajectories for the poor-to-medium and good-to-excellent site
qualities at the north-eastern locale, respectively, whereas Figures
2(a) and (b) illustrate the corresponding trajectories at the north-
western locale, respectively.
Table 2.
Density management input parameters for the modified CROPLAN-
NER model.
Parameter (units) Value
Simulation Year 2011
Site Index (SI) 8 & 12
Rotation Age (yr) 50
Initial Density (stems/ha) 2500
Ingress Density (stems/ha) 500
Pulp Log Length (m) 2.59
Pulp Log Diameter (cm) 10
Saw Log Length (m) 5.03
Saw Log Diameter (cm) 14
Merchantable Top Diameter (cm) 4
Inflation Rate (%) 2
Discount Rate (%) 4
Operability Target for SI = 8:
Quadratic Mean Diameter (cm) 14
Operability Target for SI = 12:
Quadratic Mean Diameter (cm) 18
Site Preparation (CAN$/ha) 300
Planting (CAN$/seedling) 0.6
Operational Adjustment Factor (%) 1
Product Degrade Factor (%) 15
Harvesting + Stumpage + Renewal +
Transportation + Manufacturing Costs (CAN$/m3) 75
P. F. NEWTON
Lower Site Qualities
The stands established on the poor-to-medium site qualities
differed only slight in terms of their dynamics over the 50 yr ro-
tations (Figures 1(a) and 2(a)). However, for the northeastern
stands, these slight differences in the size-density trajectories
translated into greater rotational mean sizes (quadratic mean
diameter and mean volume) and per unit area yields (total and
merchantable volumes, and component-specific biomass and car-
bon yields), and end-product volumes (volume of recoverable chip
and lumber volumes), for stands grown under the NC and B1 sce-
narios, relative to the stand grown under the A2 scenario (Table
3(a)). Conversely, however, the trajectories for the northwestern
stands grown under the B1 and A2 scenarios actually attained a
slightly greater size-density condition at rotation than that ob-
tained within the stand grown under the NC scenario. These dif-
ferences translated into greater rotational mean sizes and per
unit area yields, and preferred end-product volumes, relative to
the NC scenario (Table 3(b)). In terms of the performance indi-
ces, merchantable volume, biomass productivity and carbon yields,
and the proportion of preferred end-products (number of saw-
logs and volume of recoverable dimension lumber), were slightly
greater for northeastern stands growing under the NC and B1
scenarios relative to the stand grown under the A2 scenario (Ta-
ble 4(a)). Apart from a decline in economic worth under the A2
scenario, differences in the duration of optimal site occupancy,
stand structure, wood quality metrics, and time to operability,
were largely inconsequential (Table 4(a)). The corresponding va-
lues for the northwestern stands established on a poor-to-medium
site quality, indicated that productivity and the percentage of pre-
ferred end-products increased slightly under the B1 and A2 sce-
narios, resulting in a consequential increase in economic worth
relative to the NC scenario (Tabl e 4(b)). Similar to the northeas-
tern stands, differences in the duration of optimal site occupancy,
stand structure, wood quality metrics, and time to operability,
were minimal. Although, the stand grown under the NC sce-
nario exhibited a slight increase in its rate of development as evi-
dent by a 3 yr differential (reduction) in the time to operability
status (Table 4(b)).
Table 3.
(a) Rotational yield estimates for jack pine plantations managed under a basic silvicultural intensity in northeastern Ontario by emission scenario and
site quality. (b) Rotational yield estimates for jack pine plantations managed under a basic silvicultural intensity in northwestern Ontario by emission
scenario and site quality.
(a)
Attributea Site qualityb
(Unit) Poor-to-medium Good-to-excellent
Emission scenarioc Emission scenarioc
NC B1 vs NCA2 vs NCNC B1 vs NC A2 vs NC
(% ) (% ) (% ) (% )
Mean dominant height (m) 16.2 0.0 –2.5 21.7 –7.8 –13.4
Quadratic mean diameter (cm) 15.9 0.0 –4.4 23.1 –10.4 –16.9
Total basal area per stand (m2/ha) 29 0.0 –6.9 35 –5.7 –11.4
Mean volume per tree (dm3) 140 0.0 –11.4 393 –26.0 –39.7
Total volume per stand (m3/ha) 202 0.5 –7.9 326 –13.2 –22.1
Total merchantable volume per stand (m3/ha) 190 0.5 –8.9 313 –13.4 –22.7
Total density per stand (stems/ha) 1445 0.8 3.8 829 17.2 29.3
Relative stand density (%/100) 0.64 1.6 –6.3 0.86 –8.1 –15.1
Total number of pulp logs per stand (logs/ha) 2313 0.7 –6.4 1550 35.7 47.5
Total number of saw logs per stand (logs/ha) 172 0.6 –31.4 1323 –32.9 –53.0
Total residual tip volume per stand (m3/ha) 49.9 0.8 –6.8 21.3 24.9 57.3
Total bark oven-dried biomass per stand (t/ha) 10.9 0.9 –5.5 12.1 0.0 –1.7
Total stem oven-dried biomass per stand (t/ha) 119.8 0.8 –8.7 180.3 –12.4 –19.9
Total branch oven-dried biomass per stand (t/ha) 10.2 0.0 –8.8 18.3 –15.3 –24.0
Total foliage oven-dried biomass per stand (t/ha) 6.1 0.0 –8.2 9.4 –11.7 –18.1
Total above-ground oven-dried biomass per stand (t/ha) 147.0 0.6 –8.4 220.0 –11.8 –19.1
Total bark carbon per stand (t/ha) 5.5 0.0 –7.3 6.0 1.7 0.0
Total stem carbon per stand (t/ha) 59.9 0.7 –8.7 90.2 –12.4 –20.0
Total branch carbon per stand (t/ha) 5.1 0.0 –9.8 9.1 –14.3 –24.2
Total foliage carbon per stand (t/ha) 3.0 0.0 –6.7 4.7 –10.6 –19.1
Total above-ground carbon per stand (t/ha) 73.5 0.5 –8.4 110.0 –11.8 –19.2
Total chip volume per stand—stud mill (m3/ha) 74.2 0.8 –8.6 106.8 –11.7 –19.0
Total lumber volume per stand—stud mill (m3/ha) 83.9 0.8 –12.9 189.8 –23.4 –35.8
Total chip volume per stand—randomized length mill (m3/ha) 46.1 0.9 –8.9 69.5 –12.8 –20.6
Total lumber volume per stand—randomized length mill (m3/ha) 112.6 0.8 –11.5 227.2 –21.1 –32.4
aPredicted values; bPoor-to-medium and good-to-excellent site qualities correspond to site indices of 8 and 12 m at a breast-height age of 25 yrs, respectively (Sharma et al.,
2012); cAs defined in the text.
2
6 Copyright © 2012 SciRes.
P. F. NEWTON
(b)
Attributea Site qualityb
(Unit) Poor-to-medium Good-to-excellent
Emission scenarioc Emission scenarioc
NC B1 vs NCA2 vs NCNC B1 vs NC A2 vs NC
(% ) (% ) (% ) (% )
Mean dominant height (m) 15.5 3.2 1.9 20.9 –5.3 –7.2
Quadratic mean diameter (cm) 15.0 4.0 2.7 22.0 –6.8 –9.1
Total basal area per stand (m2/ha) 27 3.7 3.7 33 –3.0 –3.0
Mean volume per tree (dm3) 119 11.8 7.6 342 –17.5 –22.8
Total volume per stand (m3/ha) 179 8.9 5.6 302 –8.3 –11.3
Total merchantable volume per stand (m3/ha) 166 10.2 6.6 290 –8.6 –11.7
Total density per stand (stems/ha) 1498 –1.8 –0.9 883 11.4 14.9
Relative stand density (%/100) 0.58 6.9 5.2 0.82 –4.9 –7.3
Total number of pulp logs per stand (logs/ha) 2087 8.0 5.4 1791 7.5 20.6
Total number of saw logs per stand (logs/ha) 103 42.7 25.2 1116 –24.6 –32.3
Total residual tip volume per stand (m3/ha) 44.6 8.7 6.1 26.1 23.4 33.0
Total bark oven-dried biomass per stand (t/ha) 9.9 8.1 5.1 12.4 –3.2 –1.6
Total stem oven-dried biomass per stand (t/ha) 104.8 10.2 6.7 172.3 –10.4 –10.9
Total branch oven-dried biomass per stand (t/ha) 9.0 8.9 5.6 17.8 –14.6 –15.2
Total foliage oven-dried biomass per stand (t/ha) 5.5 7.3 3.6 9.3 –11.8 –11.8
Total above-ground oven-dried biomass per stand (t/ha) 129.2 9.8 6.3 211.8 –10.4 –10.8
Total bark carbon per stand (t/ha) 5.0 6.0 4.0 6.2 –3.2 –1.6
Total stem carbon per stand (t/ha) 52.4 10.1 6.7 86.1 –10.3 –10.8
Total branch carbon per stand (t/ha) 4.5 8.9 4.4 8.9 –14.6 –15.7
Total foliage carbon per stand (t/ha) 2.8 3.6 3.6 4.6 –10.9 –10.9
Total above-ground carbon per stand (t/ha) 64.6 9.8 6.3 105.9 –10.4 –10.8
Total chip volume per stand—stud mill (m3/ha) 65.0 10.0 6.5 101.3 –9.2 –9.6
Total lumber volume per stand—stud mill (m3/ha) 69.0 14.9 9.4 170.9 –18.3 –20.5
Total chip volume per stand—randomized length mill (m3/ha) 40.1 10.7 7.0 65.8 –10.2 –10.8
Total lumber volume per stand—randomized length mill (m3/ha) 94.3 13.5 8.7 206.7 –16.4 –18.2
a,b,cAs defined in T able 3(a).
Table 4.
(a) Stand-level performance indices for jack pine plantations managed under a basic silvicultural intensity in northeastern Ontario by emission sce-
nario and site quality. (b) Stand-level performance indices for jack pine plantations managed under a basic silvicultural intensity in northwestern
Ontario by emission scenario and site quality.
(a)
Indexa Site qualityb
(Unit) Poor-to-medium Good-to-excellent
Emission scenarioc Emission scenarioc
NC B1 vs NCA2 vs NCNC B1 vs NC A2 vs NC
(% ) (% ) (% ) (% )
Mean annual merchantable volume increment (m3/ha/yr) 3.8 0.0 –7.9 6.3 –14.3 –23.8
Mean annual biomass increment (t/ha/yr) 2.9 3.4 –6.9 4.4 –11.4 –18.2
Mean annual carbon increment (t/ha/yr) 1.5 0.0 –13.3 2.2 –13.6 –18.2
Percentage of sawlogs produced 6.9 0.0 –24.6 46 –35.4 –53.5
Lumber volume recovered—stud mill (%) 53.1 0.0 –2.3 64 –5.2 –8.6
Lumber volume recovered—randomized length mill (%) 70.9 0.0 –0.8 76.6 –2.5 –3.9
Land expectation value—stud mill (CAN$K/ha) 1.0 2.3 –51.2 7.7 –42.4 –61.3
Land expectation value—randomized length mill (CAN$K/ha) 3.1 1.2 –21.5 10.1 –33 –48
Duration of optimal site occupancy (% of rotation) 28 –14.3 0.0 16 –25.0 0.0
Mean height/diameter ratio (m/m) 88.9 0.6 0.8 86.4 1.9 1.3
Mean wood density (g/cm3) 0.4556 –0.2 0.2 0.4461 –0.7 –0.6
Mean maximum branch diameter (cm) 2.86 –0.7 –0.3 2.80 –1.1 –1.8
Time to operability status (yr) 44 0.0 2.3 38 5.3 15.8
Time of initial crown closure (yr) 13 23.1 23.1 9 22.2 11.1
aPredicted values; bPoor-to-medium and good-to-excellent site qualities correspond to site indices of 8 and 12 m at a breast-height age of 25 yrs, respectively (Sharma et al.,
2012). cAs defined in the text.
Copyright © 2012 SciRes. 27
P. F. NEWTON
28 Copyright © 2012 SciRes.
(b)
Indexa Site qualityb
(Unit) Poor-to-medium Good-to-excellent
Emission scenarioc Emission scenarioc
NC B1 vs NC
(% )
A2 vs NC
(% ) NC B1 vs NC
(% )
A2 vs NC
(% )
Mean annual merchantable volume increment (m3/ha/yr) 3.3 12.1 6.1 5.8 –8.6 –12.1
Mean annual biomass increment (t/ha/yr) 2.6 7.7 3.8 4.2 –9.5 –9.5
Mean annual carbon increment (t/ha/yr) 1.3 7.7 7.7 2.1 –9.5 –9.5
Percentage of sawlogs produced 4.7 29.8 17.0 38.4 –20.8 –32.6
Lumber volume recovered—stud mill (%) 51.5 2.1 1.4 62.8 –4.0 –4.9
Lumber volume recovered—randomized length mill (%) 70.2 0.7 0.4 75.9 –1.8 –2.2
Land expectation value—stud mill (CAN$K/ha) 0.3 137.1 84.3 6.4 –37.1 –38.8
Land expectation value—randomized length mill (CAN$K/ha) 2.2 28.6 18.2 8.8 –28.1 –28.9
Duration of optimal site occupancy (% of rotation) 32 –12.5 –12.5 16 –25.0 0.0
Mean height/diameter ratio (m/m) 89.1 –1.0 –0.4 86.9 0.2 0.5
Mean wood density (g/cm3) 0.4577 –0.4 –0.3 0.4460 –0.7 –0.6
Mean maximum branch diameter (cm) 2.87 –1.0 –0.7 2.80 –1.4 –1.4
Time to operability status (yr) 46 –4.3 –4.3 39 5.1 7.7
Time of initial crown closure (yr) 12 25.0 25.0 8 25.0 25.0
a,b,cAs defined in T able 4(a).
Higher Site Qualities
The effects of climate change were clearly evident for the
stands managed on the good-to-excellent site qualities irrespec-
tive of locale. The size-density trajectories of the stands grown
under the NC scenario incurred greater mortality during the mid-
dle of the rotation whereas the stands grown under the B1 and
A2 exhibited greater rates of mortality later in the rotation
(Figures 1(b) and 2(b)). The stands grown under the B1 and A2
scenarios illustrated a continuous decline in the rate of their
stand development as measured by their size-density trajecto-
ries and dominant height status during the later stages of the
rotation (Figures 1(b) and 2(b)). Relative to the NC scenario,
rotational mean volumes were approximately 33% smaller
within the northeastern stands grown under the B1 and A2 sce-
narios (Table 3(a)). Similarly, for the northwestern stands,
mean volumes were on average 20% smaller relative to the NC
scenario (Table 3(b)). In terms of development, the dominant
height of the northeastern stands grown under the B1 and A2
scenarios were on average 11% smaller at rotation than that
obtained within the stand grown under the NC scenario (Table
3(a)). Likewise, for the northwestern stands, the dominant
heights at rotation were on average 13% smaller within the
stands grown under the B1 and A2 scenarios, relative to the
stand grown under the NC scenario (Table 3(b)).
Volumetric productivity declined by 14% and 24% within the
northeastern stands grown under the B1 and A2 scenarios, re-
spectively, compared to the stand grown under the NC scenario
(Table 4(a)). The corresponding values for the northwestern
stands were 9% and 12% for the B1 and A2 scenarios, respect-
tively (Table 4(b)). Biomass production and carbon yields ex-
hibited similar levels of decline for both the B1 and A2 scenar-
ios, in both regions (Tables 4(a) and (b)). Relative to the stands
grown under the NC scenario, the proportion of preferred end-
products (number of sawlogs and volume of dimensional lum-
ber) and associated economic values at the time of harvest (land
expectation value), declined within the stands grown under the
B1 and A2 scenarios, irrespective of locale (Tables 4(a) and (b)).
Similar to the results from the low quality sites, differences in
the duration of optimal site occupancy, structural stability (height/-
diameter ratio), wood quality metrics, and time to crown clo-
sure, were minimal among all three scenarios (Tables 4(a) and
(b)). In terms of operability, however, the northeastern stands
grown under the B1 and A2 scenarios required an additional 2
and 6 years, respectively, to attain operability status. Correspond-
ing values for the northwestern stands were 2 and 3 years, re-
spectively.
Discussion
The results of this study suggest that the predicted warmer
temperatures and wetter growing seasons arising from increases
in the emission of greenhouse gases and aerosols will negati-
vely affect jack pine productivity on good-to-excellent site qua-
lities over the next 50 years (2011-2061). Specifically, stands
managed employing a basic silvicultural intensity (Bell et al.,
2008) and grown on such sites under either a B1 or A2 scenario
will experience declines in their rate of development. By the
end of the rotation, these declines will result in reductions in
rotational mean sizes (11% for quadratic mean diameter and 27%
for mean volume) and per unit area yields (14% for total vol-
ume and merchantable volumetric yields, and 13% for biomass
production and carbon outcomes), recoverable end-product vol-
umes (13% for the volume of recoverable chip and 23% for
lumber volumes), economic worth (40% for land expectation
value), and operability status (8% longer to attain the threshold
operability targets), relative to comparable stands grown under
the NC scenario. Contrary to expectation, these results suggest
that the warmer temperatures combined with increases in pre-
cipitation forecasted under the B1 and A2 scenarios may actu-
ally degrade the productivity of jack pine plantations. Although
speculative, one plausible explanation is that this additional mois-
ture will not be made available due to the low moisture retention
P. F. NEWTON
(a)
(b)
Figure 1.
(a) Temporal size-density trajectories by scenario for jack pine plantations managed under a basic sil-
vicultural intensity as presented within the traditional stand density management diagram (SDMD)
graphic for a low-to-medium quality site (SI = 8) situated in northeastern Ontario. Graphically illustrat-
ing: 1) isolines for mean dominant height (Hd; 4 - 22 m by 2 m intervals proceeding vertically up-
wards), quadratic mean diameter (Dq; 4 - 26 cm by 2 cm intervals proceeding vertically upwards),
mean live crown ratio (Lr; 35%, 40%, 50%,···, 80% proceeding from left-to-right horizontally), relative
density index (Pr; 0.1 - 1.0 by 0.1 intervals proceeding left-to-right horizontally); 2) crown closure line
(lower diagonal solid line) and self-thinning rule at a Pr = 1.0 (upper diagonal solid line); 3) lower and
upper Pr values delineating the optimal density management window (Dm; 0.32 Pr 0.45); and 4)
expected 50 year size-density trajectories with 1 year intervals denoted for each scenario. (b) Temporal
size-density trajectories by scenario for jack pine plantations managed under a basic silvicultural inten-
sity as presented within the SDMD graphic for a good-to-excellent quality site (SI = 12) situated within
northeastern Ontario. Graphical denotations as defined in Figure 1(a).
Copyright © 2012 SciRes. 29
P. F. NEWTON
(a)
(b)
Figure 2.
(a) Temporal size-density trajectories by scenario for jack pine plantations managed under a basic silvicultural
intensity as presented within the SDMD graphic for a low-to-medium quality site (SI = 8) situated within north-
western Ontario. Graphical denotations as defined in Figure 1(a); (b) Temporal size-density trajectories by sce-
nario for jack pine plantations managed under a basic silvicultural intensity as presented within the SDMD
graphic for a good-to-excellent quality site (SI = 12) situated within northwestern Ontario. Graphical denotations
as defined in Figure 1(a).
3
0 Copyright © 2012 SciRes.
P. F. NEWTON
ability of the sites that jack pine traditionally occupies. Addi-
tionally, temperature-induced increases in the rates of evapotrans-
piration and tree respiration (Boisvenue & Running, 2006) dur-
ing the growing season may divert some of the photosynthate
resources away from the production of new plant tissue.
Conversely, the productivity of jack pine plantations estab-
lished on poor-to-medium site qualities may be somewhat in-
variant to the forecasted changes in climate, depending on a
stand’s specific geographical location. Mensurational-based yield
and performance metrics for the northeastern stands grown under
the NC and B1 scenarios were approximately equivalent to that
of the stand grown under the A2 scenario. The northwestern
stands grown under the B1 and A2 scenarios actually benefitted
from the increase in temperature and precipitation as evident by
the slightly improved mean tree size and per unit area yield out-
comes. Ecologically, this may indicate that jack pine plantations
situated on poor-to-medium quality sites at the northwestern lo-
cale may be moisture deficient. Thus these stands may be able
to gain from a more maritime-like climate in the future. Notably,
across both site quality classes assessed and irrespective of lo-
cale, effects arising from either the B1 or A2 scenario did not
appreciatively affect the duration of optimal site occupancy,
stand stability or wood quality metrics.
The site-specific patterns observed in this study suggest that
jack pine productivity will be affected to a much greater degree
on the higher site qualities than on the lower site qualities.
Similar general trends were reported by Loustau et al. (2005)
who found that climate change effects on the productivity of
forests in western Europe were greatest on high fertility sites.
The importance of scaling global climate change effects to
the local level is increasingly being acknowledged within the
climate change literature (e.g., Malone & Engle, 2011). Com-
bining site-specific future estimates of climatic variables under
various emission scenarios with a forest productivity model, as
shown in this study, readily facilitates the evaluation of climate
change effects at the local level. The two regions selected for as-
sessment in this study reflected representative examples within
two of the most important areas for jack pine management in
Ontario. These areas were geographically separated and inher-
ently different in terms of their biophysical characteristics. Con-
sequently, the results reported in this study represent a plausible
range of outcomes for this particular species within the central
portion of its range.
Modeling App roach and Associa ted Limi t ations
The objective of this study was to evaluate the potential ef-
fect of projected future climate conditions on the productivity
of jack pine plantations over the next 50 years (2011-2061).
Analytically, climatic parameters as predicted by a global climate
model in association with a regional spatial climatic model,
under 3 plausible emissions scenarios, were used as input val-
ues to a biophysical-based site-specific height-age function. The
resultant function when integrated within the CROPLANNER
simulation model enabled the estimation of climate change ef-
fects on a broad array of stand-level productivity measures. A
similar approach was used to predict the effects of climate change
on lodgepole pine (Pinus contorta Douglas ex Louden) in Brit-
ish Columbia (O’Neill & Nigh, 2011). In this case, the site-hei-
ght equation within the Tree and Stand Simulator (TASS) was
modified in order to account for changing climatic conditions
for specific genotypes and locales. Ninety-year simulations for
three disparate provenances growing under three emission sce-
narios suggested that volumetric yields would decline by 7% -
13%. Although acknowledging differences in species, scenarios,
locale, site qualities and models between the studies, the trend
of decrease productivity with future climate change is projected
for both of these pine species. However, similar to most attempts
to model the effects of climate change, the validity of future
longterm forecasts is unknown and hence caution must be ex-
ercised when interpreting the projected consequences, irrespec-
tive of the modeling approach utilized.
The approach utilized in this study reinforces the utility of
modifying existing empirical-based model structures in order to
account for climate change effects on yield outcomes. However,
the approach assumes that the wide array of biological changes
arising from climate change can be expressed through the site-
based height-age equation. Although height growth is the uni- ver-
sally accepted driver of forest productivity (O’Neill & Nigh, 2011),
this is nevertheless a simplifying assumption which requires further
verification. For example, a warmer and wetter climate may in-
crease growth losses due to biotic (insect and disease) and abiotic
(wind) agents (e.g., Fleming, 2000). The effects of increased de-
composition rates and the CO2 fertilization effect will also affect
productivity (e.g., Girardin et al., 2011). Consequently, the effects
on the insect and disease vectors and changes in the hydrological
and biochemical cycles are not directly addressed using this ap-
proach. Hence until these effects of climate change are better un-
derstood, the results of this study should be considered tentative.
Nevertheless, the initial projections and associated inferences sug-
gest that jack pine may respond in site specific manner with higher
site qualities experiencing the largest declines. Therefore, current
yield projections derived from models that do not account for cli-
mate change effects are likely over-estimating future productivity
on the better site qualities.
The scenarios evaluated in this study consisted of a static
scenario which was composed of climatic variables not chang-
ing from their historical norms, the conceptual B1 emission sce-
nario based on convergent greener world characterized by col-
lective approaches to solving economic, social, and environmen-
tal problems, and the A2 scenario which arises from a decentra-
lized and heterogeneous organized world where collective ini-
tiatives for addressing global environmental problems are mini-
mal. However, the consequences of these scenarios were only
assessed for the 2011-2061 period and thus included only 2 of
the 3 projection periods normally considered under long-term
climate change modeling (i.e., 2011-2040, 2041-2070 and 2071-
2100). Consequently, the scope of the simulations did not in-
clude the most severe period of predicted climate change and
hence the results do not reflect the full potential of the negative
ramifications arising from extreme changes in climate on jack
pine productivity. Forest managers and policy makers will need
to account for these more severe climate change effects when
forecasting the future development of plantations managed
under a 50 yr rotation that are established after 2020.
Conclusion
The simulation results from the CROPLANNER model indi-
cated that future yields for stands situated on low-to-medium qual-
ity sites were largely unaffected by the predicted increased tem-
perature and precipitation rates during the 2011-2061 period. Con-
versely, however, stands situated on good-to-excellent quality sites
grown under the B1 and A2 scenarios experienced consequential
declines in stand development: reductions of 6.6% and 12.0% in
mean dominant height at rotation for the B1 and A2 scenarios,
Copyright © 2012 SciRes. 31
P. F. NEWTON
respectively, relative to the NC scenario. These declines translated
into decreases in merchantable volume productivity (mean annual
merchantable volume increment) in the order of 19% for the
northeastern stands and 10% for the northwestern stands grown
under the B1 and A2 scenarios. Similar declining trends were evi-
dent for rotational mean sizes (quadratic mean diameter and mean
stem volume), biomass yields (component-specific biomass pro-
duction and carbon outcomes), recoverable end-product volumes
(volume of recoverable chip and lumber volumes), and economic
worth (land expectation value). In addition to providing plausible
site-specific climate change outcomes on jack pine productivity
within the central portion of the species range, the results suggest
that future predictions made under the no change emission scenario
may overestimate merchantable volume productivity on the higher
site qualities by as much as 15%. Consequently, forest managers
should exercise caution when interpreting future long-term yield
forecasts derived from models that have yet to account for climate
change effects.
Acknowledgements
The author expresses his appreciation to: 1) Dr. Sharma, Re-
search Scientist, Ontario Forest Research Institute, Ontario Mi-
nistry of Natural Resources, Sault Ste. Marie, Ontario, Canada,
for providing assess to the biophysical height-age function; 2)
John Parton, Provincial Growth and Yield Modeler, Ontario Mi-
nistry of Natural Resources, South Porcupine, Ontario, Canada,
for provision of constructive input during the early phase of this
study; and 3) to the anonymous reviewers for their constructive
comments and suggestions.
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