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Research program funded by
NSERC Alliance Grants Research Program
Led by
Alexis Achim, ing.f., PhD, Université Laval
Nicholas Coops, PhD, University of British Columbia
Silva21 aims to provide data, tools and practical solutions to improve the resilience of Canadian forests
to various disturbances and sources of stress, thereby contributing to the health of these ecosystems and
the well-being of the communities that depend on them
Published November 2022 by
Amy Wotherspoon, PhD, University of British Columbia
With the help of
Michael Burnett, M.Sc., University of British Columbia
Suggested citation:
Wotherspoon, A.R1*., Burnett, M1., Bernard, A2., Achim, A2., Coops, N.C1. 2022. Climate Scenarios for
Canadian Forests. Silva21, University of British Columbia, Vancouver, Canada.
1Department of Forest Resources Management, Faculty of Forestry, University of British Columbia, 2424
Main Mall, Vancouver, British Columbia, V6T 1Z4, Canada
2Renewabe Materials Research Centre, Faculté de foresterie, de géographie et de géomatique,
Université Laval, 2405 rue de la Terrasse, Québec, Québec, G1V 0A6, Canada
*Corresponding author: amy.wotherspoon@ubc.ca
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Research and writing for this publication took place at the University of British Columbia Vancouver
campus, on the traditional, ancestral and unceded territory of the Musqueam people. The authors would
like to thank the Musqueam people who, for millennia have taken care of the land on which we live,
work and play and have passed their culture, history and traditions from one generation to the next.
The authors would also like to thank C. Mahony (British Columbia Ministry of Forests, Lands, Natural
Resource Operations and Rural Development) for providing open-source code for the CMIP6-NA
application, from which our web application and model ensemble was based.
Lastly, the authors would like to thank all of the collaborators involved in the Silva21 project who come
from academia, government and industry with the combined goal to improve the resilience of Canadian
forests.
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Contents
1.0 Introduction ....................................................................................................................................... i
Report Objectives and Deliverables ........................................................................................................... i
How to use this report .............................................................................................................................. ii
2.0 Climate-Growth Relationships ......................................................................................................... iv
Temperature ............................................................................................................................................ iv
Precipitation ............................................................................................................................................. iv
Natural Disturbances ................................................................................................................................ v
Fire ........................................................................................................................................................ v
Invasive pests ........................................................................................................................................ v
Windthrow ........................................................................................................................................... vi
Carbon Sequestration .............................................................................................................................. vi
3.0 Climate Science ............................................................................................................................. viii
Generating Climate Data .................................................................................................................... viii
Future Climate Scenarios ..................................................................................................................... ix
-- DRY INLAND & COSTAL FOREST SITES-- ..................................................................................................... 0
4.0 QUESNEL RESEARCH FOREST ........................................................................................................... 1
5.0 MALCOLM KNAPP RESEARCH FOREST ............................................................................................. 9
--BOREAL FOREST SITES-- ............................................................................................................................ 18
6.0 LAC ST-JEAN RESEARCH FOREST .................................................................................................... 19
7.0 ROMEO MALETTE FOREST ............................................................................................................. 27
8.0 NEWFOUNDLAND FORESTS ........................................................................................................... 35
9.0 MONTMORENCY RESEARCH FOREST ............................................................................................. 43
--TEMPERATE HARDWOOD FOREST SITES-- ................................................................................................ 52
10.0 ESTRIE FORESTS ............................................................................................................................... 53
11.0 PETAWAWA RESEARCH FOREST ..................................................................................................... 61
12.0 HALIBURTON FOREST ..................................................................................................................... 69
--ACADIAN FOREST SITES-- .......................................................................................................................... 78
13.0 BLACK BROOK RESEARCH FOREST .................................................................................................. 79
14.0 ACADIA FOREST DISTRICT ............................................................................................................... 87
15.0 NOVA SCOTIA FORESTS ................................................................................................................... 95
16.0 LITERATURE CITED ........................................................................................................................ 105
--ANNEX I-- ................................................................................................................................................ 111
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ANNEX I: Supplementary Material ............................................................................................................ 112
--ANNEX II-- ............................................................................................................................................... 115
ANNEX 2: Supplementary Data ................................................................................................................. 116
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1.0 INTRODUCTION
CLIMATE CHANGE WILL CONTINUE TO IMPACT CANADIAN FORESTS IN MANY COMPLEX WAYS. HOW
REGIONAL CLIMATE IS PROJECTED TO EVOLVE FROM HISTORICAL NORMALS IS THE FIRST STEP IN
PLANNING FOR ADAPTIVE SILVICULTURE.
Silva21 is a 5-year research program across five Canadian universities, with 50 collaborators
across academia, government research and industry. The goal of Silva21 is to provide data, tools and
practical solutions to improve the resilience of Canadian forests to various disturbances and sources of
stress. In doing so, Silva21 aims to contribute to the long-term health of these ecosystems and the well-
being of the communities that depend on them.
Historically, silviculture and forest management have been developed on the basis of historical
empirical data. This means the effects of future silvicultural scenarios of composition, growth and
disturbance risk have been inferred based on past growing conditions and previous yields. Such
retrospective models do not account for the rapidly evolving climate and future changes that are
projected for the remainder of the century and beyond. For this reason, we should no longer be relying
on past growth to act as an indicator of future forest production (Achim et al., 2021).
To account for potential changes to future forest production, we must first identify how
Canadian climate is likely to change over the next century. Using knowledge from climate-growth
relationships established from dendrochronology, we can use historical growth patterns and their links
to extreme climate events to predict how a changing climate may impact future stand development.
Climate projections under different scenarios can then be applied to process-based physiological models
to allow forest growth projections under future climate scenarios.
Climate projections and their implications for future forest growth modelling are vital to ensure
forest management and silviculture can adapt to future environmental conditions, mitigate negative
effects of climate on tree growth, while also considering new combinations of species mixtures, stand
structures and sites (Landsberg et al., 2003; Novick, 2016).
REPORT OBJECTIVES AND DELIVERABLES
The objective of this report is to produce consistent, spatially explicit climate layers at a fine
spatial resolution for the 12 Silva21 key managed forested areas across Canada. Generated layers intend
to provide historical trends and future projections for Canadian climate. This report can be used to
explore how regional changes in climate are likely to impact tree growth, stand dynamics, forest
composition, competition, invasive species and climate extremes. The use of future climate projects also
informs implications for future adaptive silviculture. As a result, we anticipate the report could be useful
for academics, researchers and industry alike.
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HOW TO USE THIS REPORT
This report is intended to guide the reader through identifying and understanding overall changes to
climatic conditions that are likely to occur within a specific Silva21 research hub or forest type.
Interactions amongst climate, tree growth and future stand development are briefly presented, as well
as discussion topics for forest managers at the regional level for future adaptive silviculture.
Here we present trends of fundamental climatic variables (temperature and precipitation), whereas
derived (calculated) climate variables, such as climate moisture index, precipitation falling as snow,
growing degree days and number of frost-free days will be discussed in a later report.
When reading this report, it is important to consider the uncertainties associated with climate data
projections and the greater variation that is associated with projections occurring further in the future.
This guide is not intended to be used to evaluate the affinity of each model or to identify specific
extreme climate events.
The reader should also note the use of Shared Socioeconomic Pathways (SSP), which are the latest
addition of future climate scenarios, designed to be complementary to the commonly known
Representative Concentration Pathways (RCPs). Under these new scenarios, SSP3-7.0 is the most
commonly applicable ‘high-end’ emission scenario that is best used for impact and adaptation research.
This is discussed in greater detail in Section 3.0.
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SILVA21 FOREST RESEARCH HUBS
Climate projection data was generated for 12 Canadian research forests (hereafter referred to
as ‘hubs’) across Canada (Table 1.1 ). The 12 hubs cover five forest types including dry inland (N=1),
coastal (N=1), boreal (N=4), temperate hardwood (N=3) and Acadian (N=3). Each hub will be reviewed
individually with further evaluation of Canada-wide climate projections to be reported in a later
publication.
Table 1.1 Silva21’s 12 Canadian research forests research hubs by map code, forest type and location
Forest Type
Code
Location
Coastal
Forest
MK
Malcolm Knapp, British
Columbia
Dry Inland
Forest
QN
Quesnel, British Columbia
Boreal
Forest
LSJ
Lac St-Jean, Québec
RM
Romeo Malette, Ontario
NFL
Harry’s River Newfoundland
Temperate
Hardwood
HA
Haliburton, Ontario
PW
Petawawa, Ontario
MM
Montmorency, Québec
ES
Estrie, Québec
Acadian
Forest
BB
Black Brook, New Brunswick
AC
Acadia, New Brunswick
NS
Annapolis Valley, Nova
Scotia
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2.0 CLIMATE-GROWTH RELATIONSHIPS
TEMPERATURE
Temperature is a climate variable most often associated with projected changes in future
climate scenarios. This is because temperature has a direct influence on a variety of biological processes
including photosynthesis, physiology, phenology and therefore growth, distribution and migration.
In boreal regions, where trees commonly grow below their optimum temperature, temperature
is often positively correlated to tree growth (Babst et al., 2019; Way & Oren, 2010). This has been well
documented in eastern Canadian boreal forest for black spruce (Picea mariana (Mill.) B.S.P.) and Jack
pine (Pinus banksiana Lamb) which have positive growth response to current year winter (January),
spring (March and April) and whole growing season temperatures (Huang et al., 2010). Warmer
temperatures are not only capable of accelerating tree growth, but can also alter physiological wood
properties. For example, trees growing in warmer temperatures have been found to be taller and
thinner with more foliage and fewer roots. This was also found more commonly in deciduous species
than in evergreen species, as was the overall growth-response to temperature (Way & Oren, 2010).
By comparison, when growing in a warmer, or moisture-limited environment, temperature can
be negatively correlated to tree growth. Mean response of boreal tree species have been found to have
a negative growth response to greater previous summer temperatures when associated with southern
relatively moisture-stress environments compared to their cooler northern locations (Chagnon et al.,
2022; Huang et al., 2010).
Climate niche projections, which suggest that species are the most sensitive to climate at the
margins of their distribution (Iverson et al., 2008), could imply that boreal species are likely to benefit
from future warming at northern latitudes (Chagnon et al., 2022; Huang et al., 2010). Similarly, research
suggests that boreal species are likely to shift to northeastern North America in search of a relatively
wetter and cooler refugium for migrating tree species (D’Orangeville et al., 2016). By comparison, trees
at southern latitudes are likely to see an increase in competition for water availability and see a growing
abundance of drought-tolerant species (Searle & Chen, 2017).
PRECIPITATION
Total precipitation is a common climate variable used for climate-growth relationships, as it has
direct influence on tree growth and distribution. The amount of precipitation, falling as either snow or
rain and the time of year it falls highly influence these relationships.
In regions with relatively warm temperatures, precipitation falling during the winter months
(December through February) is often negatively correlated to tree growth. This is due to a greater
volume of rain precipitation accumulating in the soil, making it more susceptible to freezing. This can
increase the risk of damage to tree roots, especially with reduced snow cover or compressed snow and
ice encasement (Kreuzwieser & Rennenberg, 2014). Such factors can greatly increase tree stress and risk
frost desiccation and damage to root systems, particularly in young seedlings (Domisch et al., 2018).
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Winter precipitation falling as rain also increases the number of rain-on-snow events which generate
greater runoff and increase risk of flood events, landslides and debris flow (Marks et al., 1998).
Precipitation falling during the summer is often more crucial to tree growth. In temperate
climates where trees grow below their optimum temperature, or in regions with relatively short growing
seasons, sufficient precipitation over summer months has a positive effect on tree growth (Chagnon et
al., 2022). However, rising temperatures and the lengthening of the growing season risk reducing the
amount of water availability for these sites (Babst et al., 2019), and increase moisture stress particularly
near the end of the growing season. This has been clearly identified in forests that were already
moisture-limited either due to warm growing seasons or relatively low growing season precipitation and
have seen reduced tree growth in recent years due to climate warming (Tei et al., 2017).
NATURAL DISTURBANCES
FIRE
Temperature is often the best predictor for forest fire risk assessment and is incorporated into
indicators such as annual area burned. However, the influence of temperature on forest fire is complex
and often interacts with precipitation and fuel availability. Both variables are used when assessing fire
risk, length and frequency. Given the heterogeneous moisture gradient across Canada, there are
contrasts between forest fire risk across the country. Historical changes in the climate of Québec have
shown that simultaneous increases in temperature and precipitation have decreased fire frequency in
the last 150 years (Bergeron et al., 2001; Flannigan et al., 2005), whereas the opposite has been found in
western and central Canada (Wang et al., 2015).
Rising temperatures, particularly warmer spring and fall seasons, have resulted in the
lengthening of the fire season. Between 1979 and 2015, the fire season length has already increased
from 191 to 205 days over North America (Hanes et al., 2019). Fuel moisture sensitivities indicate that
for every one degree of warming, precipitation must increase by more than 15% to compensate for fine
fuel moisture (Flannigan et al., 2016). Not only does this have large implications for tree health, as well
as wood quality, but also implies large risks to old growth forests, late successional species, habitat
fragmentation and carbon emissions.
INVASIVE PESTS
Climate has, and will likely continue to, impact the frequency and intensity of insect outbreak
across Canada. Warmer winters have increased the ability of pests to survive over winter which have
previously prevented larvae from surviving from one year to the next (Hamann & Wang, 2006). Rising
temperatures, particularly warmer winters, are likely to intensify the impact of pests at all life stages,
including pests’ abilities to cross geographic barriers and spread into new areas (Pureswaran et al.,
2018).
Currently, the spruce budworm (Choristoneura fumiferana) is the most damaging insect causing
tree mortality in eastern Canada and is increasing tree mortality to northern spruce and fir forests
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(Zhang et al., 2014). Similarly, the mountain pine beetle (Dendroctonus ponderosae) is largely
responsible for logging losses in British Columbia and has contributed to 270 megatonnes of carbon due
to the conversion of a small net carbon sink to a large net carbon source between 2000 and 2020 (Kurz
et al., 2008). These insects, along with others like the Asian Long-horned Beetle (Anoplophora
glabripennis), are likely to continue to expand northward altering ecosystem structure and function
through tree mortality, changes to the fire cycles and residence times of carbon sinks (Pyke et al., 2008).
This is likely to result in a positive feedback loop where climate change will continue to open new
habitats for invasive pests and invasive pests will continue to damage ecosystems, making them more
susceptible to climate change (McNeely, 2000).
Climate change is also likely to impact the spread of native and invasive terrestrial plants. Similar
to insects, the spread of invasive plant species is predicted to follow a northward shift towards a more
suitable climate (Wang et al., 2022). Species such as the Tree of Heaven (Ailanthus altissima) found in
British Columbia, Ontario and Québec is one of the species that is predicted to show the fastest change
in distribution of suitable habitat (Wang et al., 2022). Such shifts have large implications for changes to
forest stand composition, resource competition, loss of biodiversity and carbon dynamics. Other
examples of invasive terrestrial plants include Himalayan Blackberry (Rubus armeniacus), dwarf
mistletoe (Arceuthobium pusillum) and Kudzu (Pueraria montana var lobata). Such plants may become
resistant to existing herbicides under increasing CO2 levels associated with climate change (Hellmann et
al., 2008) and increase risk of tree mortality.
WINDTHROW
Windthrow is a major disturbance for Canadian forests, particularly in eastern Canada and for
shallow-rooted tree species such as balsam fir (Abies balsamea (L.) Mill). Windthrow events, sometimes
entirely stand replacing, therefore play an important role in forest dynamics which will possibly be
affected by climate change and are expected to become more intense across Canada in the future
(Cheng et al., 2014; Colle et al., 2015). While predicting wind patterns and windthrow risks come with a
high degree of uncertainty and is beyond the scope of this report, it is likely that the combination of
warmer winter temperatures, reduced soil freezing and snowpack have can further limit tree anchorage,
making trees more susceptible to uprooting during later and stronger wind events (Gregow et al., 2014).
CARBON SEQUESTRATION
Overall, there is consensus that future climate conditions will strongly influence optimum
species growing conditions and therefore influence carbon dynamics (Dymond et al., 2016). However,
positive growth-response of temperature, greater forest productivity and migration would indicate a
greater global gain in carbon sequestration (Kurz et al., 2008), particularly in colder and wetter
ecoregions (Dymond et al., 2016). It has been suggested that this sink will outweigh carbon sources,
such as loss of biomass and fire disturbance (Gonsamo et al., 2017). On the other hand, other research
shows future projections with greater carbon storage in vegetation compared to soil, which can increase
fuel loads and greater susceptibility to forest fire and insect disturbance. Overall, finer details to
determine carbon sink or source potential of Canadian forests are highly influenced by species, site
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conditions and their interactions, disturbance type and competition, as well as mitigation activities and
adaptive management.
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3.0 CLIMATE SCIENCE
CLIMATE MODELS ARE THE PRIMARY MEANS TO INFORM FOREST MANAGERS HOW THE CLIMATE MAY
CHANGE OVER THE NEXT CENTURY. THEREFORE, GLOBAL CIRCULATION MODELS AND CLIMATE CHANGE
SCENARIOS ARE IMPORTANT TOOLS TO IDENTIFY SPATIALLY EXPLICIT PATTERNS TO BE USED IN
REGIONAL ASSESSMENTS AND ADAPTATION PLANNING
GENERATING CLIMATE DATA
The International Panel on Climate Change (IPCC) is currently in its Sixth Assessment Report
(AR6), which provides an overview on the current knowledge on climate change science and new results
since the previous publication in 2014. This includes the release of the 6th Coupled Model
Intercomparison Project (CMIP6; Eyring et al., 2016) which presents the new design and organisation of
climate models that generate simulations for future climate projections.
The CMIP6 includes multiple General
Circulation Models (GCMs) which are often reduced
to smaller subsets that are more appropriate for
regional climate projections. A 13 GCM ensemble
has recently been developed for use over North
America (Mahony et al., 2022; full detailed list of
models in Annex I, Table S1.1). This list was adapted
from a continental to a regional scale for the most
appropriate collection of GCMs for spatially-explicit
use with each of Silva21’s 12 specific hub sites. This
application, as well as its corresponding climate data
projections are available online
(https://silva21.shinyapps.io/cmip6_app/; Figure
3.1).
ClimateNA (www.climatena.ca; Wang et al.,
2016), a standalone Microsoft Windows application
that downscales PRISM (Daly et al., 2008) 1971 – 2000 gridded monthly climate data to scale-free point
locations was used to generate data for Silva21’s hub sites for this report. ClimateNA uses scale-free
data as a baseline for historical and future climate variables for individual years and periods between
1901 and 2100.
Climate normals, defined as the mean climate state over a 30-year period, were calculated for
the period of 1981 – 2010 for each hub at 250 m resolution. Mean and sum monthly data was used to
calculate seasonal and annual values for temperature and precipitation, respectively. Observed climate
normals provide a reference period from which we can compare changes in future climate projected by
GCMs.
Future climate projections were generated for basic climate variables including precipitation
(mm) as well as minimum and maximum temperature (°C). Data was generated on a monthly basis and
then an average or sum value (for temperature and precipitation, respectively) were calculated for a
Figure 3.1. A screenshot of Silva21’s web-based application to
select GCM models based on spatially explicit ranking. The
projections in the image are an example of projections for the
Acadia Forests.
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seasonal basis for winter (previous year December, current year January and February), spring (March,
April, May), summer (June, July, August) and autumn (September, October, November). Future data is
then presented as the projected values or the change in climate variables relative the historical
reference period.
FUTURE CLIMATE SCENARIOS
Future climate data was generated for each hub using Mahony et al. (2022)’s 13 GCM ensemble
under four Shared Socioeconomic Pathway (SSP) scenarios (Annex I; Table S1.2) at 250 m resolution.
SSPs are a new development of the AR6’s CMIP6, which are complementary with the more commonly
known Representative Concentration Pathway (RCPs). RCPs set pathways for greenhouse gas
concentrations, and therefore the associated warming, while SSPs
explore how the reductions in emissions will (or will not) be
achieved. SSPs are used to ultimately determine emission scenarios,
both with and without climate policies (termed mitigation and
baseline scenarios, respectively) which are then used to derive
projections of future climate change (Riahi et al., 2017) (Figure 3.1).
Current research suggests that while the original projections
associated with RCP8.5 assume high future emissions and expansion
of coal energy, SSP5-8.5 recognizes this as a world without future
climate policy and not “business as usual” as it has sometimes been
referred to (van Vuuren et al., 2011). Therefore, given the extremely
unlikely case of coal-energy dependence (Ritchie & Dowlatabadi,
2017) it is reasonable to exclude SSP5-8.5 from projections when
using this climate data for impacts and adaptation research. In light
of this, it remains important to include as a practice of scientific
endeavours, even when the likelihood of their outcome is still
debated. If readers choose to emit SSP5-8.5 projections, SSP3-7.0 becomes the more likely choice for
“high-end” emission scenarios.
Future climate data was generated on a monthly, seasonal and annual basis for five 20-year
horizons. These are presented as means for the 2010 (2001 – 2020), 2030 (2021 – 2040), 2050 (2041 –
2060), 2070 (2061 – 2080) and 2090 (2081 – 2100). This report focuses on climate projections for winter
and summer during 2050 and 2090, though supplementary data for all SSPs and seasons are available in
ANNEX 2: Supplementary Data.
Changes in projected temperature were subtracted from corresponding values of historical
climate normals and presented in °C. Changes in precipitation were calculated the same way (in mm)
and also as change as percentage compared to historical climate normals.
List of Abbreviations
IPCC – International Panel on
Climate Change
GCM – General Circulation
Model
CMIP – Coupled Model
Intercomparison Project
AR6 – 6th Assessment Report
SSP – Shared Socioeconomic
Pathway
RCP – Represented
Concentration Pathways
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-- DRY INLAND & COSTAL FOREST SITES--
Dry Inland &
Costal Forest
Sites
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4.0 QUESNEL RESEARCH FOREST
EXECUTIVE SUMMARY
There is general agreement across all global circulation models that the Quesnel Forest District will see an
increase in precipitation and general warming by the end of the century. Of the three climate variables, precipitation
showed the most variation in future projections across the region, given the two distinct climate types to the west
and east of the Fraser River.
By 2100, precipitation is likely to increase during the winter months (an average increase of 42%, the
equivalent of 58 mm), with the majority falling to the east of the Fraser River (up to 2,813 mm) compared to the
west (up to 750 mm). Summer precipitation is likely to remain constant during summer months and all changes in
precipitation are likely to be more extreme in the next 30 years compared to the following 50.
Few seasonal trends were observed between summer and winter temperatures, all indicating a general
warming with maximum temperature during summer months projected to see the greatest increase (a warming of
5.0°C). Changes in both minimum and maximum temperatures are likely to be more extreme in the next 30 years
compared to the following 50.
Key forest implications for the Quesnel Forest District suggest heavy emphasis on forest management in
order to mitigate the negative effects of summer warming on tree growth and forest fire risk and severity.
Combinations of summer warming and greater winter precipitation could suggest an overall increase in forest
productivity which could be promising for the Quesnel Timber Supply Area. However, warmer and wetter winters
could also make the ongoing eradication of pests such as the mountain pine beetle and the spruce beetle
(Dendroctonus rufipennis) more difficult. Wetter winters could also pose potential risks of spring flooding at lower
elevations along the Fraser River.
STUDY AREA
The Quesnel Forest District, located in British
Columbia, Canada (52°58′N, 122°29′W; Figure 4.1) is
found in the Northern Cariboo Forest Region in the
Southern Interior. Covering over 2 million ha, the
Quesnel Forest is dominated by sub-boreal spruce and
sub-boreal pine—spruce biogeoclimatic zones but also
includes montane spruce, Engelmann spruce—
subalpine fir, interior Douglas fir, interior cedar-
hemlock and alpine tundra. Overall, the Quesnel
Forest is dominated by lodgepole pine (Pinus contorta
Douglas; 85%), spruce (Picea spp.; 10%) and Douglas-
fir (Pseudotsuga menziesii Mirbel; 3%) (Snetsinger,
2011) and includes hemlock (Tsuga spp.) and balsam
(Abies spp.) with minor components of deciduous
species (Pedersen, 2004). 80% of the forests are
Figure 4.1. The Quesnel Forest District (in relation to map of
Canada; top right), located in British Columbia, Canada (bottom).
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classified as a Timber Harvesting Land Base (THLB) (Wells & Haag, 2008), also referred to as a Timber
Supply Area (TSA) region of Canada that is partially managed by the BC Ministry of Forests, Lands and
Natural Resource Operations.
Figure 4.2. Biogeoclimatic Ecological Classification (BEC) zones associated with relatively dry region to the west (pictured on the left) and the
relatively wet region to the east (pictured on the right) of Fraser River in the Quesnel Forest District (Wells and Haag, 2007).
The Quesnel Forest District lies across the Fraser Basin and the Interior Plateau between the
Coast Mountains on the west and the Cariboo Mountains on the east. For this reason, it exhibits two
contrasting climate and forest types. To the west of the Fraser River, the region is classified as relatively
dry, dominated by lodgepole pine (Figure 4.2.). To the east of the Fraser River, the relatively wetter
region is dominated by spruce and balsam (Figure 4.2.) (Wells & Haag, 2008).
The Quesnel Forest includes two large provincial parks – Bowron Lake Park and Itcha Ilgachuz
Park. It also includes many small parks, 42 recreation sites (of which 28 are extensively managed) and 35
recreational trails. Popular recreational activities that occur in the Quesnel Forest include hiking,
canoeing, camping, guided horse tours, fishing, hunting, snowmobiling, dog-sledding and skiing.
Several First Nations communities are actively present on QF land including the Lhoosk’uz Dene
(Kluskus Band), Lhtako-Dene (Red Bluff Band), ?Esdilagh (Alexandria Band) and the Ndazkhot’en First
Nation (Nazko Band). Eight other First Nations are located outside the TSA area and assert to have
traditional territories inside Quesnel TSA. Many First Nations companies hold forest licences to harvest
timber and are involved in the forest industry.
HISTORICAL CLIMATE DATA
To the west of the Fraser River, Quesnel Forest has a relatively dry climate and receives between
380 and 750 mm of precipitation annually. To the east of the Fraser River, the relatively wetter region
3
receives between 750 and 2,470 mm of precipitation per year. Observed climate normal data for
Quesnel Forest for the reference period of 1981 – 2010 are shown in Table 4.1.
FUTURE PRECIPITATION
For the reference period of 1981 – 2010, the 30-year normal of annual precipitation was 606
mm per year. Normals for total precipitation by season are shown in Table 4.1. Projected changes using
the 13 GCM ensemble and four SSP scenarios showed an overall increase in precipitation over the next
century. By 2050, mean annual precipitation is likely to increase by 16%, the equivalent of 96 mm for an
average of 702 (+ 261) mm per year. More specifically, the region to the west of the Fraser River, will
receive annual precipitation between 336 and 960 mm whereas the region to the east will receive up to
2,680 mm per year. By 2090, mean annual precipitation is likely to increase by 20% (the equivalent of
123 mm) for a total of 729 (+ 273) mm per year by the end of the century. The west of the Fraser River
will receive between 460 and 750 mm, whereas to the east will receive up to 2,813 mm.
WINTER PRECIPITATION
Projected changes in winter precipitation show an overall increase, particularly to the east of
the Fraser River (Figure 4.3. ). By the year 2050, winter precipitation is projected to increase between 33
— 38%, the equivalent of 46 – 53 mm. By 2090, these projections are expected to reach an increase
between 35 and 49%, the equivalent of 58 – 68 mm. The mean across all four SSP scenarios of the 13
GCM ensemble suggests that by the end of the century Quesnel Forest will receive a total of 197 mm
precipitation during the winter months, an increase of 58 mm compared to 30-year historical average.
SUMMER PRECIPITATION
Projected changes to summer precipitation show minimal changes (Figure 4.3. ). By the year
2050, summer precipitation is projected to increase by up to 4%, the equivalent of 7 mm. By the year
2090, summer precipitation could decrease by 6% or increase by 4%, the equivalent of -12 – 8 mm. The
mean across all four SSP scenarios of the 13 GCM ensemble suggests that by the end of the century,
Table 4.1. Observed climate normal from 1981 – 2010 at the Quesnel Forest District generated by
ClimateNA at 250 m resolution. Total precipitation includes both rainfall and snowfall.
Winter
(Dec – Feb)
Spring
(Mar – May)
Summer
(Jun – Aug)
Autumn
(Sep – Nov)
Annual
Minimum Temperature (°C)
-12.5
-3.9
5.7
-2.8
-3.4
Maximum temperature (°C)
-2.4
9.0
19.4
8.0
8.5
Average temperature (°C)
-7.5
2.6
12.5
2.6
2.5
Total precipitation (mm)
139
107
191
169
606
4
Quesnel Forest will receive a total of 190 mm precipitation during the summer months, 1 mm less than
the 30-year historical average.
FUTURE MINIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of minimum temperature was -
3.4°C. Normals for minimum temperature by season are shown in Table 4.1. Historically, areas along the
Fraser River have been the warmest of the Quesnel Forest District with coolest temperatures to the
east. Projected changes using the 13 GCMs showed an overall increase in annual minimum temperature
over the next century. Mean annual minimum temperature is likely to increase by 2.4°C and 4.1°C by
years 2050 and 2090, respectively, indicating that mean minimum temperature could be as high as 0.7°C
by the end of the century. These values represent the average change across all four SSP scenarios of a
13 GCM ensemble.
WINTER MINIMUM TEMPERATURE
Projected changes in winter minimum temperature for each SSP scenario are shown in Figure
4.4. By the year 2050, minimum temperature during winter months is projected to increase by 1.4 –
2.5°C. By 2090, minimum temperature is projected to increase by 1.8 – 5.7°C. The mean across all four
SSP scenarios of the 13 GCM ensemble suggests a winter minimum temperature of -8.8°C by the end of
the century, an increase of 3.7°C compared to the 30-year historical average.
SUMMER MINIMUM TEMPERATURE
Projected changes in summer minimum temperature for each SSP scenario are shown in Figure
4.4. By the year 2050, minimum temperature throughout the summer is projected to increase by 2.0 –
3.0°C. By 2090, minimum temperatures are projected to continue to increase by 2.2 – 6.2°C. The mean
across all four SSP scenarios of the 13 GCM ensemble suggests summer minimum temperature of 10.0°C
by the end of the century, an increase of 4.7°C compared to the reference period.
FUTURE MAXIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of maximum temperature was
8.5°C. Normals for maximum temperature by season are shown in Table 4.1. Projected changes using
the 13 GCMs showed an overall increase in annual maximum temperature over the next century. Across
all four SSP scenarios of the 13 GCM ensemble, mean annual maximum temperature is likely to increase
by 2.1°C and 3.7°C by years 2050 and 2090, respectively, indicating that mean maximum temperature
could reach as high as 12.2°C by the end of the century.
5
WINTER MAXIMUM TEMPERATURE
Projected changes of winter maximum temperature for each SSP are shown in Figure 4.5. By the
year 2050, maximum temperature throughout the winter months is projected to increase between 0.9 –
1.6°C. By 2090, maximum temperature is projected to continue to increase by 1.1 – 4.1°C. The mean
across all four SSP scenarios of the 13 GCM ensemble suggests winter maximum temperature of -0.1°C
by the end of the century, an increase of 2.0°C compared to the 30-year historical normal.
SUMMER MAXIMUM TEMPERATURE
Projected changes of summer maximum temperature for each SSP are shown in Figure 4.5.By
the year 2050, maximum temperature throughout the summer months is projected to increase between
2.4 – 3.6°C. By 2090, maximum temperature is projected to increase by 2.6 – 7.4°C. The mean across all
four SSP scenarios of the 13 GCM ensemble suggests summer maximum temperature of 24.4°C by the
end of the century, an increase of 5.0°C compared to the 30-year historical normal.
----
Means of seasonal and annual variables by SSP scenario and 20-year interval from 2001 – 2100 for each
climate variable can be found in ANNEX 2: Supplementary Data.
6
Figure 4.3. Projections for change in seasonal precipitation (mm; for both rain and snow) for the years 2050 and 2090 relative to the reference
period (1981 – 2010).
7
Figure 4.4. Projections for change in seasonal minimum temperature (°C) for the years 2050 and 2090 relative to the reference period (1981 –
2010).
8
Figure 4.5. Projections for change in seasonal maximum temperature (°C) for the years 2050 and 2090 relative to the reference period (1981 –
2010).
9
5.0 MALCOLM KNAPP RESEARCH FOREST
EXECUTIVE SUMMARY
There is a general agreement across all global circulation models that the Malcolm Knapp Research Forest
will see a slight increase in annual precipitation and general warming. Precipitation is likely to increase during the
winter months (a projected increase of 15%, the equivalent of an additional 125 mm), and decrease during the
summer months (a projected decrease of 24%, the equivalent of 75 mm less). Changes to both winter and summer
precipitations are likely to be more extreme in the next 30 years, compared to the subsequent 50.
Few seasonal trends were observed between summer and winter temperatures, all indicating a general
warming. However, maximum temperature during the summer months was projected to see the greatest change in
temperatures (warming of 5.1°C by the end of the century). Changes in minimum temperature are likely to be more
extreme in the next 30 years, whereas changes in maximum temperature are likely to be more extreme in the
following 50.
Key implications for forestry suggest that Malcolm Knapp will have some of the greatest relative drying
within the next century. However, given the highest rates of annual precipitation in the country, soil moisture
content will likely remain adequate in order to maintain productive forests. In fact, warmer summer temperatures
suggest potential increase in productivity during the beginning of the growing season. However, drier conditions
during months of July and August are expected to be more likely.
STUDY AREA
The Malcolm Knapp Research Forest
(MKRF), located in Maple Ridge, British
Columbia (Figure 5.1) covers 5,157 ha of
forested land and was granted by the Crown
to the University of British Columbia in 1949.
The MFKP is part of the coastal western
hemlock biogeoclimatic zone with the
southern portion of the forest at low
elevation dry maritime subzone and the
northern portion at high-elevations
maritime subzone. Some parts of the forest
are also included in the submontane and
montane altitudinal variants (Klinka et al.,
2005).
Soils at the MKRF are variable but
predominantly identified as podzols, with
brunisol, gleysol and organic orders also
commonly found. These soils produce coniferous stands with the most dominant tree species being
Douglas fir, western red cedar (Thuja plicata Donn ex D. Don) and western hemlock (Tsuga heterophylla
Figure 5.1. The Malcolm Knapp Research Forest in relation to
Vancouver (bottom left), located in British Columbia, Canada (right).
10
(Raf.) Sarg.). At the southern end of the forest, red alder (Alnus rubra Bong.) is a prominent part of the
species composition. Understory vegetation consists mostly of salal (Gaultheria shallon Pursh), red
huckleberry (Vaccinimum ovatum Pursh), Oregon grape (Mahonia aquifolium (Pursh) Nutt.), vine maple
(Acer circinatum Pursh), bracken fern (Blechnum spicant (L.) F.W. Weiss), sword fern (Polystichum
munitum (Kaulf.) C. Presl), Alaskan blueberry (Vaccinium ovalifolium Sm.), step moss (Hylocomium
splendens (Hedw.) Schimp), beaked moss (Kindbergia oregana (Sull.) Ochyra), lanky moss
(Rhytidiadelphus loreus (Hedw.) Warnst.) and wavy leaf cotton moss (Plagiothecium undulatum (Hedw.)
Schimp) (Green & Klinka, 1994). Historical wildfires and logging have developed a mosaic of even aged
stands.
Forest management of the MKRF remains the responsibility of UBC’s Faculty of Forestry. The
main objectives include research (primary mandates), demonstration and education, recreation (walking
and hiking), cultural heritage for First Nations, visual quality and carbon resources. The MKRF is divided
into four management units which include primary timber production (72%), scenic areas and secondary
timber production (14%), old growth and deferred areas (10%) and riparian buffers (4%). The harvest
planning is influenced by non-timber values, access road development, timber types, markets and
research or education objectives. Timber harvest is ecosystem-based and utilizes several silvicultural
systems including variable retention harvesting, clearcut, clearcut with reserves, patch cuts, salvage,
group selection and commercial thinning. Since 2004, Gallant Enterprises has offered a service of
sawmilling and timber manufacturing and fabricates custom wood products made of Douglas-fir,
western redcedar, yellow cedar and western hemlock timber grown and harvested for the MKRF.
The MKRF is part of the traditional, ancestral and unceded territory of many First Nations, but
particularly the Katzie people, the Sto:lo and the Tsawwassen. A protocol agreement between MKRF and
Katzie First Nation reflects mutual respect and recognition of the Katzie as original owner and ongoing
caretaker of the land. The MKRF and Katzie First Nation collaborate in forest management and
education to the local community.
HISTORICAL CLIMATE
The MKRF climate is characteristic of the coastal rainforest ecotype with a maritime climate with
a low continental influence from Coast Mountains in the northeast and a mean annual temperature of
8.7°C. Mean annual precipitation being approximately 2,500 mm, with slightly more falling in northern
regions at higher elevations. It is considered to have wet and mild winters, cool and relatively dry
summers. Observed climate normal data for the Malcolm Knapp Research Forest for the reference
period of 1981 – 2010 are shown in Table 5.1.
11
FUTURE PRECIPITATION
For the reference period of 1981 – 2010, the 30-year normal of annual precipitation was 2,522
mm per year. Normals for total precipitation by season are shown in Table 5.1. Projected changes using
the 13 GCMs showed an overall annual increase in precipitation over the next century. Precipitation is
likely to stay constant through 2050 (a slight increase of 13 mm) and increase by 2.4% by 2090 (the
equivalent of 60 mm) for a total of 2,582 mm per year. These values represent the average change
across all four SSP scenarios of a 13 GCM ensemble.
WINTER PRECIPITATION
Projected changes in winter precipitation for each SSP scenario are shown in Figure 5.2. Winter
precipitation is projected to increase between 10 to 13% (the equivalent of 89 – 114 mm) by 2050 and
by 12 and 18% (the equivalent of 102 – 149 mm) by 2090. The mean across all four SSP scenarios of the
13 GCM ensemble suggests that by the end of the century, MKRF will receive a total of 971 mm
precipitation during the winter months, a mean increase of 125 mm compared to the reference period.
SUMMER PRECIPITATION
Projected changes in summer (June, July, August) precipitation for each SSP scenario are shown
in Figure 5.2. Summer precipitation is projected to decrease by 15 – 20% (the equivalent of 46 – 65 mm)
by 2050, and by 13 – 32% (the equivalent of 40 – 100 mm) by 2090. The mean across all four SSP
scenarios of the 13 GCM ensemble suggests that by the end of the century, the Malcolm Knapp
Research Forest will receive a total of 239 mm precipitation during the summer months, a mean
decrease of 75 mm compared to the reference period.
Table 5.1. Observed climate normal from 1981 – 2010 at the Malcolm Knapp Research Forest generated
by ClimateNA at 250 m resolution. Total precipitation includes both rainfall and snowfall.
Winter
(Dec – Feb)
Spring
(Mar – May)
Summer
(Jun – Aug)
Autumn
(Sep – Nov)
Annual
Minimum Temperature (°C)
-0.4
3.6
11
5.5
5.0
Maximum temperature (°C)
4.9
12
21
13
13
Average temperature (°C)
22
7.9
16
9
8.7
Total precipitation (mm)
846
600
314
763
2,522
12
FUTURE MINIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of minimum temperature was
4.8°C. Normals for minimum temperature by season are shown in Table 5.1. Projected changes using the
13 GCMs showed an overall increase in minimum temperature over the next century. Minimum
temperature is likely to increase by 2.0°C and 3.6°C by years 2050 and 2090, respectively, indicating that
mean minimum temperature could be as high as 8.4°C by the end of the century. These values represent
the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER MINIMUM TEMPERATURE
Projected changes in winter minimum temperature for each SSP scenario are shown in Figure
5.3. By the year 2050, minimum temperature during winter months is projected to increase between -
0.4°C and 2.2°. By 2090, this range is expected to be closer to between 1.7°C and 4.9°C. The mean across
all four SSP scenarios of the 13 GCM ensemble suggests a winter minimum temperature of 2.9°C by the
end of the century, a mean increase of 3.3°C, compared to the reference period.
SUMMER MINIMUM TEMPERATURE
Projected changes in summer minimum temperature for each SSP scenario are shown in Figure
5.3. By the year 2050, minimum temperature throughout the summer is projected to increase between
1.8°C and 2.8°C. By 2090, this range is expected to increase to between 2.0°C and 5.9°C. The mean
across all four SSP scenarios of the 13 GCM ensemble suggests summer minimum temperature of 14.7°C
by the end of the century, a mean increase of 4.0°C.
FUTURE MAXIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of maximum temperature was
12.5°C. Normals for maximum temperature by season are shown in Table 5.1. Projected changes using
the 13 GCMs showed an overall increase in mean annual maximum temperature over the next century,
likely by 2.2°C and 3.8°C by years 2050 and 2090, respectively. This indicates an increase as high as
16.3°C by the end of the century. These values represent the average change across all four SSP
scenarios of a 13 GCM ensemble.
WINTER MAXIMUM TEMPERATURE
Projected changes of winter maximum temperature for each SSP are shown in Figure 5.4. By the
year 2050, maximum temperature throughout the winter months is projected to increase between 1.2°C
and 1.9°C and is projected to continue to increase by 1.4°C – 4.4°C by 2090. The mean across all four
SSP scenarios of the 13 GCM ensemble suggests winter maximum temperature of 6.5°C by the end of
the century, an increase of 1.5°C compared to the reference period.
13
SUMMER MAXIMUM TEMPERATURE
Projected changes of summer maximum temperature for each SSP are shown in Figure 5.4. By
the year 2050, maximum temperature throughout the summer months is projected to increase between
2.4°C and 3.7°C and stay relatively stable until 2090 (between 2.6°C and 3.7°C). The mean across all four
SSP scenarios of the 13 GCM ensemble suggests summer maximum temperature of 25.6°C by the end of
the century, an increase of 5.1°C relative to the reference period.
----
Means of seasonal and annual variables by SSP scenario and 20-year interval from 2001 – 2100 for each
climate variable can be found in ANNEX 2: Supplementary Data.
14
Figure 5.2. Projections for change in seasonal precipitation (mm) for the years 2050 and 2090 relative to the reference period (1981 – 2010).
15
Figure 5.3. Projections for change in seasonal minimum temperature (°C) for the years 2050 and 2090 relative to the reference period (1981 –
2010).
16
Figure 5.4. Projections for change in seasonal maximum temperature (°C) for the years 2050 and 2090 relative to the reference period (1981 –
2010).
17
18
--BOREAL FOREST SITES--
Boreal
Forest Sites
19
6.0 LAC ST-JEAN RESEARCH FOREST
EXECUTIVE SUMMARY
There is general agreement across all global circulation models that the Lac St-Jean Research Forest (LSJRF)
will see an increase in precipitation and general warming by the end of the century.
Over the next century, winter precipitation will increase up to 56% (the equivalent of 46 mm) falling by
2050 and an additional 22 mm by 2090. Summer precipitation will also increase in the next 30 years, with an increase
of up to 20% (the equivalent of 55 mm) by 2050, but only an additional 1mm is expected in the subsequent 50 years.
Both minimum and maximum temperatures are expected to increase over the next century, indicating an
overall warming. The largest increase in temperature is likely to occur during winter months, with both minimum
and maximum temperature expecting to double. This is the equivalent of an 8.6°C increase in minimum winter
temperature and an increase of 4.4°C of summer temperatures by 2090. Changes in to minimum and maximum
temperature are likely to be more extreme in the next 30, years compared to the following 50.
Key forest implications for the LSJRF suggest greater tree growth given warmer annual temperatures and a
continued supply of summer precipitation, as is expected for the boreal forest region. Because of this water
availability, the region is likely to see an increase in hardwood species that are likely to migrate northward. However,
warmer summers and winters increase risk of forest insect infestations. Therefore, forest management plans
prioritize pest management while they may see increase in forest productivity, even if only temporarily.
STUDY AREA
The Lac St-Jean Research Forest,
located in Québec, Canada (Figure 6.1.) is a
public Crown Land Forest managed by
Québec’s Ministère des Forêts, de la Faune
et des Parcs (MFFP). The majority of the
land (97.5%) is part of Québec’s
Saguenay—Lac-St-Jean administrative
region, while a small portion (2.5%) is in the
Côte-Nord administrative region.
The forest is situated within the
boreal zone, across two bioclimatic
domains; the balsam fir – yellow birch
domain to the south and the spruce-
feathermoss domain to the north. Soils
consist mostly of undifferentiated glacial
till, particularly on high slopes and
escarpments. At mid elevation and lower
slopes, peatlands can be found in areas with
Figure 6.1. The Lac St-Jean Research Forest, located in Québec, Canada
(bottom left) in the boreal region (right).
20
slow drainage. The forest is comprised mostly of black spruce, balsam fir, white birch (Betula papyrifera
Marshall) and occasionally Jack pine. Softwood and mixed wood stands cover the majority of the area at
75% and 11%, respectively. Hardwood stands cover only 2% of the area, while regenerating stands with
no defined cover type account for 12% of the land area.
Forests in and around the LSJRF are managed by MFFP who’s aim is to manage and enhance the
land and its forests, wildlife, mining and energy resources (Ministère des Forêts, 2018). Forest
management in the region is based on principles of the Sustainable Forest Development Act (SFDA) and
is planned according to the concept of Ecosystem-Based Forest Management (Grenon et al., 2011).
Silvicultural practices aim to promote natural regeneration, which includes protecting pre-established
natural regeneration at the time of harvest, otherwise creating adequate germination beds.
Management also focuses on reforesting or restocking forests with insufficient natural generation or to
improve and promote a desired species composition. During the regeneration process, pre-commercial
thinning may be used to control stand composition and density to result in a desired species having
larger diameter and better-quality stems. Commercial thinning is also used in managed stands.
In the LSJRF, forests are primarily harvested using commercial timber harvesting and, in
northern regions, clearcutting with variable retention harvesting. LSJRF is one of the most important
forest regions of Québec for its high volume of harvesting; in 2013 – 2014, the region harvested
5,442,500 m3 of wood, representing 27% of the total volume of the province’s public forests (Ministère
des Forêts de la Faune et des Parcs, 2018). The LSJ area aims to increase regional timber production
from 7 mm3 year-1 to 10 mm3 year-1 by 2050. The goal is to specifically increase the amount and quality
of fiber available for harvest, the area of productive forest land and the qualify of both paper and yellow
birch (Betula alleghaniensis Britt.).
Over the last few decades, the greatest loss of woody material due to pathogens has been to
root and heart rot of fir and spruce, as well as hypoxylon cankers (Entoleuca mammata Wahlenb) in
poplars (MFFP, 2018). Primary damages due to insects are caused by the spruce budworm
(Choristoneura fumiferana Clemens) and Swaine Jack pine sawfly (Neodiprion swainei Middleton)
(Ministère des Forêts de la Faune et des Parcs, 2018). Forest fires in the region have been known to
ravage large areas, with the most damaging of the last 100 forest fires occurring between 1996 and
2005. A severe fire in 2005 burned more than 27, 500 ha in northern parts of the LSJRF, where forests
are particularly vulnerable to fires (Ministère des Forêts de la Faune et des Parcs, 2018).
The LSJRF maintains forest management that integrates the interests, values and needs of the
population of Québec and Aboriginal Nations. The aboriginal Innu and Atikamekw nations, divided into
five communities, have recognized rights, claims or use of the territory within the LSJRF. In order to
facilitate ongoing exchanges and discussions with the First Nations communities, the MFFP, the Ministry
of Energy and Natural Resources (MERN) and the First Nations communities of Essipit, Mashteuiatsh and
Pessamit maintain a regional coordination committee to exchange ongoing concerns involving local land
and businesses.
21
HISTORICAL CLIMATE DATA
The LSJRF maintains a relatively cool climate with a mean annual temperature of -0.8°C. The
region is relatively drier compared to further east of Québec and receives 928 mm of precipitation
annually. The growing season is between 140 – 160 days. Observed climate normal data for the LSJRF for
the reference period of 1981 – 2010 are shown in Table 5.1.
FUTURE PRECIPITATION
For the reference period of 1981 – 2010, the 30-year normal of annual precipitation was 928
mm per year. Normals for total precipitation by season are shown in Table 5.1. Projected changes using
the 13 GCMs showed an overall increase in precipitation over the next century. By 2050, annual
precipitation is likely to increase by 18% (the equivalent of 164 mm). By 2090, annual precipitation is
likely to increase by 23% (the equivalent of 217 mm) for a total of 1145 mm per year by the end of the
century. These values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER PRECIPITATION
Projected changes in winter precipitation for each SSP scenario are shown in Figure 6.2. By the
year 2050, winter precipitation is projected to increase between 25 and 32%, the equivalent of 41– 52
mm. By 2090, these projections are expected to reach an increase between 24 and 56%, the equivalent
of 39 – 90 mm. The mean across all four SSP scenarios of the 13 GCM ensemble suggests that by the end
of the century, Lac St-Jean will receive a total of 230 mm precipitation during the winter months, an
increase of 68 mm compared to the reference period.
SUMMER PRECIPITATION
Projected changes in summer (June, July, August) precipitation for each SSP scenario are shown
in Figure 6.2. By the year 2050, summer precipitation is projected to increase by 17 – 18 %, the
Table 6.1. Observed climate normal from 1981 – 2010 at the Lac St-Jean Research Forest generated by
ClimateNA at 250 m resolution. Total precipitation includes both rainfall and snowfall.
Winter
(Dec – Feb)
Spring
(Mar – May)
Summer
(Jun – Aug)
Autumn
(Sep – Nov)
Annual
Minimum Temperature (°C)
-23.5
-8.2
7.9
-2.1
-6.5
Maximum temperature (°C)
-11.2
4.5
19.8
6.1
4.8
Average temperature (°C)
-17.4
-1.8
13.8
2.0
-0.8
Total precipitation (mm)
162
179
317
270
928
22
equivalent of 55 – 56 mm. By the year 2090, summer precipitation could increase by 16 – 20%, the
equivalent of 52 – 64 mm. The mean across all four SSP scenarios of the 13 GCM ensemble suggests that
by the end of the century, Lac St-Jean Forest will receive a total of 374 mm precipitation during the
summer months, an increase of 57 mm compared to the reference period.
FUTURE MINIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of minimum temperature was -
6.5°C. Normals for minimum temperature by season are shown in Table 5.1. Projected changes using the
13 GCMs showed an overall increase in minimum temperature over the next century. Minimum
temperature is likely to increase by 3.7°C and 5.9°C by years 2050 and 2090, respectively, indicating that
mean minimum temperature could be as high as -0.6°C by the end of the century. These values
represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER MINIMUM TEMPERATURE
Mean minimum winter temperature for the reference period of 1981 – 2010 was -23.5°C.
Projected changes in winter minimum temperature for each SSP scenario are shown in Figure 6.3. By the
year 2050, minimum temperature during winter months is projected to increase between 4.9°C and
6.5°C. By 2090, minimum temperature is projected to increase between 5.0°C and 11.7°C. The mean
across all four SSP scenarios of the 13 GCM ensemble suggests a winter minimum temperature of -
14.9°C by the end of the century, an increase of 8.6°C compared to the reference period.
SUMMER MINIMUM TEMPERATURE
Mean minimum summer temperature for the reference period of 1981 – 2010 was 7.9°C.
Projected changes in summer minimum temperature for each SSP scenario are shown in Figure 6.3. By
the year 2050, minimum temperature throughout the summer is projected to increase between 2.3°C
and 3.2°C. By 2090, minimum temperatures are projected to continue to increase between 2.4°C and
6.3°C. The mean across all four SSP scenarios of the 13 GCM ensemble suggests summer minimum
temperature of 12.3°C by the end of the century, an increase of 4.4°C compared to the reference period.
FUTURE MAXIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of maximum temperature was
4.8°C. Normals for maximum temperature by season are shown in Table 5.1. Projected changes using
the 13 GCMs showed an overall increase in maximum temperature over the next century. Maximum
temperature is likely to increase by 2.7°C and 4.7°C by years 2050 and 2090, respectively, indicating that
mean maximum temperature could reach as high as 9.5°C by the end of the century. These values
represent the average change across all four SSP scenarios of a 13 GCM ensemble.
23
WINTER MAXIMUM TEMPERATURE
Mean winter maximum temperature for the reference period of 1981 – 2010 was -11.2°C.
Projected changes of winter maximum temperature for each SSP is shown in Figure 6.4. By the year
2050, maximum temperature throughout the winter months is projected to increase between 3.0°C and
4.2°C. By 2090, maximum temperature is projected to continue to increase between 3.0°C and 7.9°C.
The mean across all four SSP scenarios of the 13 GCM ensemble suggests winter maximum temperature
of -5.6°C by the end of the century, an increase of 5.6°C compared to the reference period.
SUMMER MAXIMUM TEMPERATURE
Mean summer maximum temperature for the reference period for 1981 – 2010 was 20°C.
Projected changes of summer maximum temperature for each SSP is shown in Figure 6.4. By the year
2050, maximum temperature throughout the summer months is projected to increase between 2.1°C
and 2.9°C. By 2090, maximum temperature is projected to increase by 2.0°C and 6.6°C. The mean across
all four SSP scenarios of the 13 GCM ensemble suggests summer maximum temperature of 24.2°C by
the end of the century, an increase of 4.4°C compared to the reference period.
----
Means of seasonal and annual variables by SSP scenario and 20-year interval from 2001 – 2100 for each
climate variable can be found in ANNEX 2: Supplementary Data
24
Figure 6.2. Projections for change in seasonal precipitation (mm) for the years 2050 and 2090 relative to the reference period (1981 – 2010).
25
Figure 6.3. Projections for change in seasonal minimum temperature (°C) for the years 2050 and 2090 relative to the reference period (1981 –
2010).
26
Figure 6.4. Projections for change in seasonal maximum temperature (°C) for the years 2050 and 2090 relative to the reference period (1981 –
2010).
27
7.0 ROMEO MALETTE FOREST
EXECUTIVE SUMMARY
There is a general agreement across all global circulation models that the Romeo Malette Forest will see an
increase in precipitation and general warming. By 2090, precipitation is likely to increase during the winter months
(an average increase of 31%, the equivalent of 45 mm), whereas summer months will remain similar to historical
averages (average of 0% change, the equivalent of 15 mm).
Few seasonal trends were observed between summer and winter temperatures, all indicating a general
warning, particularly during winter months. Minimum temperature during the winter months was projected to see
the greatest change in temperature (warming of 6.7°C) compared to other seasonal fluctuations. Changes in both
minimum and maximum temperature are likely to be more extreme in the next 30 years, compared to the following
50.
Key implications for forest management include drought mitigation, as warmer summers with no change in
precipitation can increase risk of drought conditions. Warmer winters also suggest less precipitation falling as snow,
as well as an increase risk of forest pests, therefore pest management should also be prioritized.
STUDY AREA
The Romeo Malette Forest (RMF) is
located within the Timmins District in northeastern
Ontario (Figure 7.1). The RMF falls entirely in the
boreal forest region and based on the province of
Ontario’s land classification, falls within the
Ontario Shield ecozone and the Lake Abitibi (3E)
ecoregion. The majority of the forest is within the
Foleyet ecodistrict (3E-5), with northern parts
falling onto the Clay Belt (3E-1) and the eastern
region falling within Kirkland Lake (3E-6)
ecodistricts (Wester et al., 2018).
The area of RMF is comprised of 586,607
ha of crown land, of which 92% is forested land
and the remaining is non-forested land such as
water, grassland and agricultural land. The main
tree species include Jack pine, black spruce, white
spruce (Picea glauca (Moench) Voss), poplar
(Populus spp.) and white birch with small
components of balsam fir, cedar (Thuya spp.), larch
(Larix spp.) and white and red pines (Pinus strobus L.
and Pinus resinosa Soi ex. Aiton). The RMF can be
characterized as a young forest, as 19% of the forest is older than 100 years (Arbex Forest Resource
Figure 7.1. The Romeo Malette Forest located in Ontario, Canada
(top right) near the city of Timmins (bottom).
28
Consultants Ltd, 2019). The majority of the RMF consists of glacial deposits of boulder sand till overlying
bedrock, while the northern portion in the Clay Belt is relatively flat to gentle rolling terrain interspersed
with eskers and depressions.
At the RMF, Green First Forest Products holds a Sustainable Forest License. Between 2012 and
2019, 2,935,969 m3 of wood volume was harvested. Wood utilization is often high for tree species such
as spruce, pine (Pinus spp.), fir (Abies spp.) and poplar and less often for white birch, cedar (Thuja spp.)
and larch. The main forest operations utilized by Green First Forest are clear-cut followed by mechanical
site preparation (on 5,716 ha) prior to natural (19.410 ha) or planted (9,206 ha) regeneration with both
seed and seedlings and some chemical herbicide use (3,513 ha). Natural disturbances that occur at the
RMF include fire (40,000 ha burned in 2012), and insect attack by spruce budworm and forest tent
caterpillar (Malacosoma disstria Hübner), along with windthrow.
The RMF also maintains a Local Citizens Committee and includes eight forms of resource-based
tourism, 67 traplines and 19 bear management areas. Due to the high proximity of RMF to the city of
Timmins, the city promotes the use of the forest to local and regional population for recreational
activities. The RMF acknowledges traditional territories of five First Nations communities including
Mattagami First Nation, Matachewan First Nation, Taywa Tagamou First Nation, Wahgoshig First Nation
and Flying Post First Nation, as well as the interest from the Métis Nation of Ontario.
HISTORICAL CLIMATE DATA
As part of Ontario’s Abitibi Lake ecoregion, the RMF has long, cold snowy winter and warm,
short summers with a mean annual temperature of 1.8°C and receives 773 mm of precipitation annually.
Observed climate normal data for the RMF for the reference period of 1981 – 2010 are shown in Table
5.1.
Table 7.1. Observed climate normal from 1981 – 2010 at the Romeo Malette Forest generated by
ClimateNA at 250 m resolution. Total precipitation includes both rainfall and snowfall.
Winter
(Dec – Feb)
Spring
(Mar – May)
Summer
(Jun – Aug)
Autumn
(Sep – Nov)
Annual
Minimum Temperature (°C)
-21
-6.0
8.9
-0.8
-4.6
Maximum temperature (°C)
-7.5
8.3
23
9.3
8.2
Average temperature (°C)
-14
1.2
16
4.2
1.8
Total precipitation (mm)
147
163
238
226
773
29
FUTURE PRECIPITATION
For the reference period of 1981 – 2010, the 30-year normal of annual precipitation was 773
mm per year. Normals for total precipitation by season are shown in Table 5.1. Projected changes using
the 13 GCMs showed an overall increase in precipitation over the next century. By 2050, annual
precipitation is likely to increase by 14% (the equivalent of 108 mm). By 2090, annual precipitation is
likely to increase by 19% (the equivalent of 143 mm) for a total of 916 mm per year by the end of the
century. These values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER PRECIPITATION
Projected changes in winter precipitation for each SSP scenario are shown in Figure 7.2. By the
year 2050, winter precipitation is projected to increase between 16 and 24%, the equivalent of 24 and
35 mm, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, these projections are expected to
reach an increase between 16 - 41%, the equivalent of 24 and 60 mm, according to SSP1-2.6 and SSP5-
8.5, respectively. The mean across all four SSP scenarios of the 13 GCM ensemble suggests that by the
end of the century, and will receive a total of 192 mm precipitation during the winter months, and
increase of 45 mm compared to the reference period.
SUMMER PRECIPITATION
Projected changes in summer (June, July, August) precipitation for each SSP scenario are shown in Figure
7.2. By the year 2050, summer precipitation is projected to increase by 7 – 9%, the equivalent of 17 – 21
mm, according to SSP2-4.5 and SSP1-2.6, respectively. By the year 2090, summer precipitation could
increase between 3 – 11%, the equivalent of 8 – 26 mm, according to SSP3-7.0 and SSP1-2.6,
respectively. The mean across all four SSP scenarios of the 13 GCM ensemble suggests that by the end of
the century, Romeo Malette Forest will receive a total of 252 mm precipitation during the summer
months, an increase of 15 mm compared to the reference period.
FUTURE MINIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of minimum temperature was -
4.6°C. Normals for minimum temperature by season are shown in Table 5.1. Projected changes using the
13 GCMs showed an overall increase in minimum temperature over the next century. Minimum
temperature is likely to increase by 2.9°C and 5.0°C by years 2050 and 2090, respectively, indicating that
mean minimum temperature could be as high as 0.4°C by the end of the century. These values represent
the average change across all four SSP scenarios of a 13 GCM ensemble.
30
WINTER MINIMUM TEMPERATURE
Projected changes in winter minimum temperature for each SSP scenario are shown in Figure
7.3. By the year 2050, minimum temperature during winter months is projected to increase by between
3.0 – 4.6°C, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, minimum temperature is
projected to increase by between 3.1 – 9.8°C, according to SSP1-2.6 and SSP5-8.5, respectively. The
mean across all four SSP scenarios of the 13 GCM ensemble suggests a winter minimum temperature of
-13.8°C by the end of the century, an increase in 6.7°C compared to the reference period.
SUMMER MINIMUM TEMPERATURE
Projected changes in summer minimum temperature for each SSP scenario are shown in Figure 7.3. By
the year 2050, minimum temperature throughout the summer is projected to increase by 1.9 – 2.7°C,
according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, minimum temperatures are projected to
continue to increase by 1.9 – 6.0°C, according to SSP1-2.6 and SSP5-8.5, respectively. The mean across
all four SSP scenarios of the 13 GCM ensemble suggests summer minimum temperature of 13.0°C by the
end of the century, an increase of 4.1°C compared to the reference period.
FUTURE MAXIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of maximum temperature was
8.2°C. Normals for maximum temperature by season are shown in Table 5.1. Projected changes using
the 13 GCMs showed an overall increase in maximum temperature over the next century. Maximum
temperature is likely to increase by 2.9°C and 4.8°C by years 2050 and 2090, respectively, indicating that
mean maximum temperature are projected to be 13.0°C by the end of the century. These values
represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER MAXIMUM TEMPERATURE
Projected changes of winter maximum temperature for each SSP are shown in Figure 7.4. By the
year 2050, maximum temperature throughout the winter months is projected to increase between 2.6
and 3.7°C, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, maximum temperature is
projected to continue to increase between 2.7 and 7.3°C, according to SSP1-2.6 and SSP5-8.5,
respectively. The mean across all four SSP scenarios of the 13 GCM ensemble suggests winter maximum
temperature of -2.4°C by the end of the century, an increase of 5.1°C compared to the reference period.
SUMMER MAXIMUM TEMPERATURE
Projected changes of summer maximum temperature for each SSP are shown in Figure 7.4. By
the year 2050, maximum temperature throughout the summer months is projected to increase between
2.4 and 3.3°C, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, maximum temperature is
31
projected to increase between 2.3 and 7.1°C, according to SSP1-2.6 and SSP5-8.5, respectively. The
mean across all four SSP scenarios of the 13 GCM ensemble suggests summer maximum temperature of
26.9°C by the end of the century, an increase of 4.1°C compared to the reference period.
----
Means of seasonal and annual variables by SSP scenario and 20-year interval from 2001 – 2100 for each
climate variable can be found in ANNEX 2: Supplementary Data.
32
Figure 7.2. Projections for change in seasonal precipitation (mm) for the years 2050 and 2090 relative to the reference period (1981 – 2010).
33
Figure 7.3. Projections for change in seasonal minimum temperature (°C) for the years 2050 and 2090 relative to the reference period (1981
2010).
34
–
Figure 7.4. Projections for change in seasonal maximum temperature (°C) for the years 2050 and 2090 relative to the reference period (1981 –
2010).
35
8.0 NEWFOUNDLAND FORESTS
EXECUTIVE SUMMARY
There is general agreement across all global circulation models that over the next century, the
Newfoundland forests will see a general warming and – with minimal increases to precipitation – the potential of a
drying climate. Overall, precipitation is projected to increase within the Newfoundland forests, with the greatest
increases likely to occur in the winter months (a potential increase of 47 mm by 2090). Summer precipitation is likely
to stay constant, with a slight increase near the end of the century (up to 28 mm by 2090).
Increasing minimum temperatures over the winter months (increase of 6.2°C by 2090) are expected to be
greater compared to summer months (increase of 4.4°C by 2090). Increasing maximum temperature shower fewer
seasonal trends, though greatest during the winter months (up by 3.2°C) compared to summer months (up by 2.5°C),
particularly in the upcoming 30 years.
Key forestry implications suggest that with warmer growing season temperatures, there is potential for
greater forest productivity, as long as soil moisture availability remains adequate. Given the proximity to the Atlantic
Oceans, forest management plans should consider to monitor potential dangers to windthrow.
STUDY AREA
The Newfoundland Forests, or more
specifically the Corner Brook Pulp and Paper
Woodlands (CBPPW), cover 1.4 million ha of
crown land on the island of Newfoundland
(Figure 8.1) and is privately managed by Corner
Brook Pulp and Paper Limited (hereafter referred
to as Corner Brook Ltd), part of Kruger Industrial.
The CBPPW is located in the Appalachian
region of northeastern Canada, characterized by
rolling hills, mountainous areas, upland plateaus,
bogs, barrens and ponds with elevation ranging
from 600 – 814 metres above sea level. Surface
deposits include glacial till, washed sediments,
peat deposits and rock outcrops. The most
common soil type in the province is podzols and
soils usually found with an organic layer over a
rich iron layer that are acidic and coarse in
texture.
The island of Newfoundland is divided into
three large boreal zones and is subdivided into
nine ecoregions (Figure 8.2). The CBPPW is spread
Figure 8.1. The Newfoundland Forest research sites, located in
Newfoundland, Canada (top right), along the northwest and
northeastern coast (bottom).
36
across five of these ecoregions, with the largest portion
(50% of the forested area) found in Central Newfoundland;
a region dominated by black spruce with white birch and
aspen (Populus spp.) found on richer sites. Another large
area (30%) can be found in the Western Newfoundland
ecoregion where balsam fir dominates the forest cover with
white birch and yellow birch being common in valleys. Red
maple (Acer rubrum L.) can also be found in this ecoregion.
A smaller percentage of the CBPPW (8%) can be found in
the Long-Range Barrens, a mountainous area where black
spruce, balsam fir and eastern larch (Larix laricina (Du Roi)
K. Koch) dominate and are often stunted (Krummholz). In
the Maritime Barrens (6%) fog and strong winds dominate
the ecoregion and are dominated by balsam fir forests.
Lastly, in the Northern Peninsula Forest (5%), the forest is
dominated by black spruce and has the shortest growing
season on the island. Across these regions, forest fires are
the most common natural disturbance occurring in the
CBPPW, in addition to invasive pests such as hemlock looper
(Lambdina fiscellaria Guenée), balsam fir sawfly (Neodiprion abietis Harris), spruce budworm, balsam
wood adelgid (Adelges piceae (Ratz.)) and birch casebearer (Coleophora serratella Linnaeus) (Kruger
Industrial, 2021).
Since 1983, Corner Brook Ltd has had exclusive ownership of the timber that now make up
CBBPW. The company is responsible for producing forest management plans, timber harvesting and
applying silvicultural practices. Corner Brook Ltd has used public consultations in the forest management
planning process since the 1980s and bases silvicultural treatment and harvesting practices to meet
environmental and sustainable standards as proposed by the Canadian Council of Forest Ministers
(Kruger Industrial, 2021). The CBPPW supplies fiber to Corner Brooks Ltd newsprint mill in the town of
Corner Brook.
In addition to timber harvesting, the defined forest area of the CBPPW has many other uses
including hunting, trapping, fishing, berry picking, skiing, snowmobiling and bird watching. These
recreation activities are maintained as part of an agreement between Corner brook Ltd and the
Appalachian Trail Newfoundland and Labrador (Kruger Industrial, 2021). First Nation communities in the
region include the Mi’kmaq, who have aboriginal rights on the Island of Newfoundland and maintain a
548-ha reserve in Baie d’Esport. The Qualipu Mi’kmaq First Nation Band is also in the region, though
they maintain a landless band. Kruger Inc. and Corner Brooks Ltd have drafted a Vision for Harmonious
Relations with First Nations and Memorandums of Understanding between Corner Brook Ltd with each
of the two First Nation Bands.
Figure 8.2. The ecoregions of Newfoundland after
Damman (1983) and Meades and Moores (1994).
37
HISTORICAL CLIMATE DATA
The island of Newfoundland is characterized by cold winters and short, warm summers. The
climate is moderated by currents from the Atlantic Ocean and the mild gulf stream-north Atlantic drift
ocean current system in the south. For this reason, many of the climatic characteristics are attributed to
the cold “ex-Arctic” water that encircles the island and local climate is highly variable by ecoregion. The
30-year historical seasonal and annual averages for the reference period of 1981 – 2010 are listed in
Table 8.1.
FUTURE PRECIPITATION
For the reference period of 1981 – 2010, the 30-year normal of annual precipitation was 1,183
mm per year. Normals for total precipitation by season are shown in Table 8.1. Projected changes
showed an increase in precipitation over the next century, as shown in Figure 8.3. By 2050, annual
precipitation is likely to increase by 6% (the equivalent of 70 mm). By 2090, annual precipitation is likely
to increase by 10% (the equivalent of 113 mm) for a total of 1,296 mm per year by the end of the
century. These values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER PRECIPITATION
Projected changes in winter precipitation for each SSP scenario are shown in Figure 8.3. By the
year 2050, winter precipitation is projected to increase between 9 and 12%, the equivalent of 28 and 38
mm. By 2090, these projections are expected to reach an increase between 8 and 22%, the equivalent of
25 and 69 mm. The mean across all four SSP scenarios of the 13 GCM ensemble suggests that by the end
of the century, the region will receive a total of 355 mm precipitation during the winter months, an
increase of 47 mm compared to the reference period.
Table 8.1. Observed climate normal from 1981 – 2010 at the Corner Brook Pulp and Paper Woodlot
generated by ClimateNA at 250 m resolution. Total precipitation includes both rainfall and snowfall.
Winter
(Dec – Feb)
Spring
(Mar – May)
Summer
(Jun – Aug)
Autumn
(Sep – Nov)
Annual
Minimum Temperature (°C)
-10.9
-3.7
8.9
2.0
-0.9
Maximum temperature (°C)
-2.9
5.3
19.3
9.7
7.8
Average temperature (°C)
-6.9
0.8
14.1
5.9
3.5
Total precipitation (mm)
309
237
302
335
1,183
38
SUMMER PRECIPITATION
Projected changes in summer precipitation for each SSP scenario are shown in Figure 8.3. By the
year 2050, summer precipitation is projected to show minimal changes with an increase between 3%
and 4%, the equivalent of 9 and 12 mm. By the year 2090, summer precipitation could increase slightly
more between 6% and 9%, the equivalent of between 18 and 28 mm. The mean across all four SSP
scenarios of the 13 GCM ensemble suggests that by the end of the century, the region will receive a
total of 325 mm precipitation during the summer months, an increase of 28 mm compared to the
reference period.
FUTURE MINIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of minimum temperature was -
0.9°C. Normals for minimum temperature by season are shown in Table 8.1. Projected changes using the
13 GCMs showed an overall increase in minimum temperature over the next century; likely to increase
by 3.1°C and 4.8°C by years 2050 and 2090, respectively. Projections indicate mean minimum
temperature could be as high as 3.9°C by the end of the century, an increase of 3.0°C from the reference
period. These values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER MINIMUM TEMPERATURE
Projected changes in winter minimum temperature for each SSP scenario are shown in Figure
8.4. Minimum temperature is expected to increase between 3.8 and 4.9°C in 2050 and between 3.9 and
8.1°C by 2090 during the winter months. The mean across all four SSP scenarios of the 13 GCM
ensemble suggests a winter minimum temperature of -4.7°C by the end of the century, an overall
increase of 6.2°C compared to the reference period.
SUMMER MINIMUM TEMPERATURE
Projected changes in summer minimum temperature for each SSP scenario are shown in Figure
8.4. Minimum temperature is projected to increase between 2.3 and 3.2°C by 2050 and between 2.4
and 6.2 °C by 2090 during the summer months. The mean across all four SSP scenarios of the 13 GCM
ensemble suggests summer minimum temperature of 13.3°C by the end of the century, an overall
increase of 4.4°C compared to the reference period.
FUTURE MAXIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of maximum temperature was
7.8°C. Normals for maximum temperature by season are shown in Table 8.1. Projected changes using
the 13 GCMs showed an overall increase in maximum temperature over the next century, indicating an
increase of 2.6°C and 4.2°C by years 2050 and 2090, respectively. Mean maximum temperature could
39
reach as high as 12.0°C by the end of the century, an increase of approximately 4.2°C compared to the
reference period. These values represent the average change across all four SSP scenarios of a 13 GCM
ensemble.
WINTER MAXIMUM TEMPERATURE
Projected changes of winter maximum temperature for each SSP are shown in Figure 8.5.
Maximum temperature during the winter months are projected to increase between 2.8°C and 3.7°C by
2050 and between 2.8°C and 6.3°C by 2090. The mean across all four SSP scenarios of the 13 GCM
ensemble suggests winter maximum temperature of 1.7°C by the end of the century, an overall increase
of 4.6°C compared to the reference period.
SUMMER MAXIMUM TEMPERATURE
Projected changes of summer maximum temperature for each SSP are shown in Figure 8.5.
Maximum temperature during the summer months is projected to increase by 2.1°C and 3.0°C by 2050
and between 2.2 and 6.3°C by 2090. The mean across all four SSP scenarios of the 13 GCM ensemble
suggests summer maximum temperature of 23.6°C by the end of the century, an overall increase in
4.3°C compared to the reference period.
----
Means of seasonal and annual variables by SSP scenario and 20-year interval from 2001 – 2100 for each
climate variable can be found in ANNEX 2: Supplementary Data.
40
Figure 8.3. Projections for change in seasonal precipitation (mm) for the years 2050 and 2090 relative to the reference period (1981 – 2010).
41
Figure 8.4. Projections for change in seasonal minimum temperature (°C) for the years 2050 and 2090 relative to the reference period (1981 –
2010).
42
Figure 8.5. Projections for change in seasonal maximum temperature (°C) for the years 2050 and 2090 relative to the reference period (1981 –
2010)
43
9.0 MONTMORENCY RESEARCH FOREST
EXECUTIVE SUMMARY
There is a general agreement across all global circulation models that the Montmorency Research Forest
(MRF) will see a general warming without significant changes to annual precipitation. By 2090, precipitation is likely
to increase during the winter months (an average increase of 25%, the equivalent of 69 mm), whereas there are
likely to be no significant changes during the summer months (a slight increase of 25 mm).
Seasonal trends showed that changes to minimum temperature are likely to be prominent during winter
months (a 7.8°C increase by 2090) and are likely to be more extreme in the upcoming 30 years. By comparison, the
greatest changes to maximum temperatures are likely to occur during the summer months (a 5.4°C increase by 2090)
with the more extreme changes occurring in the second half of the century.
Climate projections for the Montmorency Research Forest therefore suggest that the combination of
warmer winter temperatures and greater winter precipitation will decrease the amount of precipitation falling as
snow which is likely to impact thaw cycles and rain-on-snow events. Winter precipitation may carry into warmer
spring to provide greater soil water availability during an earlier growing season; however, warmer summer
temperatures and little change to summer precipitation suggest potential drying, particularly during the later
months of the growing season. This is likely to affect growth rates of certain tree species, of which drought-tolerant
species are likely to out-compete others. This is particularly true given the location of the Montmorency Research
Forest along the transitional zone of boreal and temperate hardwood forests, which is most likely to see this kind of
competition compared to other regions. Therefore, forest management should incorporate greater abundance of
northern migrating hardwoods and shifting species compositions, as well as drought mitigation and pest
management.
STUDY AREA
The Montmorency Research Forest (MRF) is located approximately 60 km north of Québec City,
Québec (47°09’N, 71°17’W; Figure 9.1) and is part of the Côte-de-Beaupré regional municipality in the
administrative region of Capitale-Nationale. Montmorency Research Forest is located on the ancestral
territories claimed by three Aboriginal communities: the Huron-Wendat, the Innu community of Essipit
and the Innu community of Mashteuiatsh.
Initially covering an area of 66 km2, the Montmorency Forest was expanded in 2014 to an area of
397km2. The forest is located in the southern part of the boreal forest and is part of the eastern fir —
white birch bioclimatic domain. The region, which is dominated by rugged terrain and high hills with
thick till deposits, lies on top of the Canadian Shield with crystallin bedrock and consists mainly of
igneous rocks. Geological deposits are fairly uniform with thick till found on slopes and in valleys and
thin till at higher altitude summits and more often as glaciofluvial deposits. The forest cover is mostly
coniferous and mixed with little diversity due to the relatively cool and wet climate. The dominant tree
44
species includes balsam fir, white spruce and
white birch. Historically, the forest territory has
been marked by epidemics of spruce budworm,
creating a landscape characterized by stands of
varying ages.
Since 1964, management delegation has
been granted to Laval University to carry out
research and teaching activities. Management
decisions are made by a committee made up of
representatives of University Laval’s scientific
and development committee, made up of
researchers, students, close neighbours,
environmental non-government organizations,
native communities and legal authorities. The
MRF follow’s Québec provincial sustainable
development of forest practices (l’aménagement durable des forêts) law and produces nearly 12,550 m3
of wood per year. Northern parts of the forest are managed at reduced intensity due to the presence of
the woodland caribou (Rangifer tarandus caribou).
Lastly, the region is known for recreational tourism activities, including cross-country skiing,
snowshoeing, fishing and boreal wildlife observation, which is managed by the Laurential Wildlife
Reserve as part of the Société des établissements de plein air du Québec (Sépaq).
HISTORICAL CLIMATE DATA
The Montmorency Research Forest is part of the vegetative boreal zone, which maintains a
subpolar humid continental climate (Blouin & Berger, 2004) with a mean annual temperature of 0.4°C.
The climate is relatively wet and receives 1,368 mm of precipitation annually. Observed climate normal
data for the Montmorency Research Forest for the reference period of 1981 – 2010 are shown in Table
9.1.
Table 9.1. Observed climate normal from 1981 – 2010 at the Montmorency Research Forest generated
by ClimateNA at 250 m resolution. Total precipitation includes both rainfall and snowfall.
Winter
(Dec – Feb)
Spring
(Mar – May)
Summer
(Jun – Aug)
Autumn
(Sep – Nov)
Annual
Minimum Temperature (°C)
-18.9
-5.8
8.5
-1.4
-4.4
Maximum temperature (°C)
-8.9
4.5
19.0
6.6
5.3
Average temperature (°C)
-13.9
-0.7
13.8
2.6
0.4
Total precipitation (mm)
279
306
392
391
1,368
Figure 9.1. The Montmorency Research Forest, located in Québec,
Canada (bottom left) in the region of La Côte-de-Beaupré (right).
45
FUTURE PRECIPITATION
For the reference period of 1981 – 2010, the 30-year normal of annual precipitation was 1,368
mm per year. Normals for total precipitation by season are shown in Table 9.1. Projected changes using
the 13 GCMs showed an overall increase in annual precipitation over the next century (Figure 9.2. ). By
2050, annual precipitation is likely to increase by 4% (the equivalent of 52 mm). By 2090, annual
precipitation is likely to increase by 8% (the equivalent of 107 mm) for a total of 1,475 mm per year by
the end of the century. These values represent the average change across all four SSP scenarios of a 13
GCM ensemble.
WINTER PRECIPITATION
Projected changes in winter precipitation for each SSP scenario are shown in Figure 9.2. . By the
year 2050, winter precipitation is projected to increase between 13 and 18%, the equivalent of 35 and
50 mm (according to SSP1-2.6 and SSP5-8.5, respectively). By 2090, these projections are expected to
increase between 13 and 35%, the equivalent of 36 and 98 mm (according to SSP1-2.6 and SSP5-8.5,
respectively). The mean across all four SSP scenarios of the 13 GCM ensemble suggests that by the end
of the century, and will receive a total of 348 mm precipitation during the winter months, an increase of
69 mm compared to the reference period.
SUMMER PRECIPITATION
Projected changes in summer (June, July, August) precipitation for each SSP scenario are shown
in Figure 9.2. . By the year 2050, summer precipitation is projected to increase between 4 and 7%, the
equivalent of 17 and 29 mm (according to SSP2-4.5 and SSP5-8.5, respectively). By the year 2090,
summer precipitation could increase between 4 and 9%, the equivalent of 16 and 37 mm (according to
SSP3-7.0 and SSP1-2.6, respectively). The mean across all four SSP scenarios of the 13 GCM ensemble
suggests that by the end of the century, Montmorency Research Forest will receive a total of 417 mm
precipitation during the summer months, an increase of 25 mm compared to the reference period.
FUTURE MINIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of minimum temperature was -
4.4°C. Normals for minimum temperature by season are shown in Table 9.1. Projected changes using the
13 GCMs showed an overall increase in minimum temperature over the next century (Figure 9.3).
Minimum temperature is likely to increase by 3.8°C and 5.8°C by years 2050 and 2090, respectively,
indicating that mean minimum temperature could be as high as 1.4°C by the end of the century. These
values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
46
WINTER MINIMUM TEMPERATURE
Projected changes in winter minimum temperature for each SSP scenario are shown in Figure
9.3. By the year 2050, minimum temperature during winter months is projected to increase between
4.4°C and 6.0°C, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, minimum temperatures are
projected to continue to increase between 4.5°C and 10.6°C, according to SSP1-2.6 and SSP5-8.5,
respectively. The mean across all four SSP scenarios of the 13 GCM ensemble suggests a winter
minimum temperature of -11.1°C by the end of the century, an increase of 7.8°C compared to the
reference period.
SUMMER MINIMUM TEMPERATURE
Projected changes in summer minimum temperature for each SSP scenario are shown in Figure
9.3. By the year 2050, summer minimum temperature is projected to increase between 2.7°C and 3.5°C,
according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, the minimum temperature is projected to
continue to increase between 2.7°C and 6.7°C, according to SSP1-2.6 and SSP5-8.5, respectively. The
mean across all four SSP scenarios of the 13 GCM ensemble suggests summer minimum temperature of
13.3°C by the end of the century, an increase of 4.8°C compared to the reference period.
FUTURE MAXIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of maximum temperature was
5.3°C. Normals for maximum temperature by season are shown in Table 9.1. Projected changes using
the 13 GCMs showed an overall increase in maximum temperature over the next century (Figure 9.4).
Maximum temperature is likely to increase by 3.2°C and 5.1°C by years 2050 and 2090, respectively,
indicating that mean maximum temperature could reach as high as 10.4°C by the end of the century.
These values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER MAXIMUM TEMPERATURE
Projected changes of winter maximum temperature for each SSP are shown in Figure 9.4. By the
year 2050, maximum temperature throughout the summer is projected to increase between 2.7°C and
3.8°C, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, the maximum temperature is projected
to continue to increase between 2.6°C and 7.0°C, according to SSP1-2.6 and SSP5-8.5, respectively. The
mean across all four SSP scenarios of the 13 GCM ensemble suggests summer maximum temperature of
-4.0°C by the end of the century, an increase of 5.0°C compared to the reference period.
SUMMER MAXIMUM TEMPERATURE
Projected changes of summer maximum temperature for each SSP are shown in Figure 9.4. By
the year 2050, maximum temperature throughout the summer is projected to increase between 3.1°C
47
and 3.9°C, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, the maximum temperature is
projected to continue to increase between 3.0°C and 7.6°C, according to SSP1-2.6 and SSP5-8.5,
respectively. The mean across all four SSP scenarios of the 13 GCM ensemble suggests summer
maximum temperature of 24.4°C by the end of the century, an increase of 5.4°C compared to the
reference period.
----
Means of seasonal and annual variables by SSP scenario and 20-year interval from 2001 – 2100 for each
climate variable can be found in ANNEX 2: Supplementary Data.
48
Figure 9.2. Projections for change in seasonal precipitation (mm) for the years 2050 and 2090 relative to the reference period (1981 – 2010).
49
Figure 9.3. Projections for change in seasonal minimum temperature (°C) for the years 2050 and 2090 relative to the reference period (1981 –
2010).
50
Figure 9.4. Projections for change in seasonal maximum temperature (°C) for the years 2050 and 2090 relative to the reference period (1981 –
2010).
51
52
--TEMPERATE HARDWOOD FOREST SITES--
Temperate
Hardwood
Forest Sites
53
10.0 ESTRIE FORESTS
EXECUTIVE SUMMARY
There is general agreement across all Global circulation models that the Estrie Forests will see a general
warming and potential drying by the end of the century.
Precipitation is projected to increase during winter months (an overall increase of 45 mm), but remain
constant (decrease of 5 mm) during the summer months. Changes to temperature over the next century will most
likely be felt in terms of rising minimum temperature during the winter months (a projected 5.9°C increase) and
rising maximum temperature during the summer months (a projected increase of 5.1°C). Changes to winter
temperature are likely to be felt more intensely in the next 30 years, whereas maximum temperatures will increase
steadily until 2100.
Key forest management implications for the Estrie Forests include drought mitigation given the longer,
warmer growing seasons and potential decrease in summer precipitation. Forests are likely to see an increase in
competition for soil water availability and therefore the increase of abundance of drought-tolerant species. Warmer
summer temperatures also increase the risk of forest pest outbreaks; therefore, pest management should be
considered as well.
STUDY AREA
The Estrie forests, located in the Eastern
Townships of Québec (Figure 10.1. are private forests
owned by The Domtar Corporation that cover 1,603
km2 across three administrative regions of Estrie
(102,019 ha) and Chaudière-Appalaches (53,550 ha)
and Centre-du-Québec (4,251 ha).
The Estrie forests are located across the
Appalachian geological region, characterized by a
sloping plateau with an altitude up to 900 m near the
Canadian-American border, down to 150 m in
northern regions closer to the St. Lawrence Lowlands.
The Estrie forests are divided between two
ecological regions, both found in the northern
temperate vegetation zone and are part of the
deciduous forest subzone. The first ecological zone –
the Coteaux de l’Estrie (2c) – is part of the maple-
basswood bioclimatic zone and is a relatively
homogenous across the landscape. Agricultural
activities are established along the valleys, whereas forests are confined on rugged reliefs on mesic sites
with medium-fast drainage. Hardwood stands cover nearly 50% of all hardwood stands and are
composed of high-density mature maple stands including beech (Fagus spp.), American ash (Fraxinus
Figure 10.1. The Estrie forests, located in Québec, Canada
(top right) in the Eastern Townships (bottom).
54
americana L.) and yellow birch are also present (Gosselin, 2007). Mixed forests occupy another 35% of
the territory and are dominated by red maple and intolerant hardwoods, such as trembling aspen
(Populus tremuloides Michx.) and white birch. Conifer stands are also present, though are less common
(covering 15% of the land area), consisting mostly of fir, cedar and red spruce (Picea rubens Sarg.) and
are often confined to well-drained sites.
The second ecological zone – the Coteaux des basses-Appalaches (3d) – is part of the eastern
maple-yellow birch bioclimatic subdomain. Parts of this ecoregions are made up of gently sloping
hillsides, covered with thick till deposits with lands used primarily for forestry and sometimes for
agriculture (20% of the area) (Gosselin, 2005). This ecoregion is part of the sugar maple—yellow birch
bioclimatic domain with stands most often found on mesic sites at mid-slope and with maple-basswood
stands dominating the best sites.
Forests across Estrie are principally utilized for economic activities, specifically pulp and paper
production (which contributed to 83% of revenues in 2014) and personal care products such as
absorbent hygiene materials. To manage these resources, various types of silviculture are applied to
across the forests. The main treatments include partial cuts, stem retention, thinning and clearcuts.
Domtar also practices additional silvicultural treatments in specialized forest sections including a)
management of maple groves in agricultural zones), b) hybrid poplar plantations, and, c) management of
white-tailed deer (Odocoileus virginianus Zimmerman) ravages. Small to medium sized disturbances
occur across the landscape, mostly caused by spruce budworm, emerald ash borer (Agrilus planipennis
Fairmaire), heart rot disease in beech, and wind and snow accumulation.
Though the study area described here is private, Domtar also allows access to this private
forested land for local tourism and recreational activities. This includes access for maple grove tenants
to produce maple syrup, local hunting and fishing clubs, trappers with permits, and recreation activities
such as scouting groups, hiking, biking, snowmobiling and cross-country skiing. Domtar’s forests are
located on the ancestral territory of the W8banaki Nation which are currently made up of the Wôlinak
and the Odanak communities. Under Forestry Stewardship Council (FSC) certification, Domtar must
consult with First Nation communities in connection with forest-related activities. Recently, an
agreement between Domtar and First Nations allows exclusive hunting access to First Nation members.
HISTORICAL CLIMATE DATA
Historically, the Estrie region has a humid, continental climate; characterized by hot summers
and cold winters with abundant rainfall. The region has a mean annual temperature of 4.0°C and
receives 1,173 mm of precipitation annually. The 30-year climate normals for the reference period of
1981 – 2010 for the Estrie forests are shown in Table 10.1.
55
FUTURE PRECIPITATION
30-year climate normals for the reference period of 1981 – 2010 show the Estrie forests receive
1,173 mm of precipitation per year. Historical normals for precipitation by season can be found in Table
10.1. Projected changes using the 13 GCMs showed a slight increase in precipitation over the next
century. By 2050, annual precipitation is likely to increase by 4% (the equivalent of 47 mm). By 2090,
annual precipitation is likely to increase by 8% (the equivalent of 89 mm) for a total of 1,262 mm per
year by the end of the century. More of this projected precipitation is likely to fall to the east of the
region (projected annual rainfall of 1,290 mm by 2090) compared to the western regions (projected
annual rainfall of 1,229 mm by 2090). These values represent the average change across all four SSP
scenarios of a 13 GCM ensemble.
WINTER PRECIPITATION
Projected changes in winter precipitation for each SSP scenario are shown in Figure 10.2. By the
year 2050, winter precipitation is projected to increase between 7 and 13%, the equivalent of 18 and 31
mm, according to the SSP1-2.6 and SSP5-8.5 scenarios, respectively. By 2090, these projections are
expected to reach an increase between 8 and 28%, the equivalent of 20 and 68 mm, according to the
SSP1-2.6 and SSP5-8.5 scenarios, respectively. The mean across all four SSP scenarios of the 13 GCM
ensemble suggests that by the end of the century, and will receive a total of 291 mm precipitation
during the winter months, with more falling to the east (approximately 302 mm), compared to the west
(approximately 280 mm). Overall, this represents an increase of 45 mm compared to the reference
period.
SUMMER PRECIPITATION
Projected changes in summer (June, July, August) precipitation for each SSP scenario are shown
in Figure 10.2. By the year 2050, summer precipitation is projected to change by a decrease of 1 to 4%,
Table 10.1. Observed climate normal from 1981 – 2010 at the Montmorency Research Forest generated
by ClimateNA at 250 m resolution. Total precipitation includes both rainfall and snowfall.
Winter
(Dec – Feb)
Spring
(Mar – May)
Summer
(Jun – Aug)
Autumn
(Sep – Nov)
Annual
Minimum Temperature (°C)
-15.2
-2.8
10.9
1.0
-1.5
Maximum temperature (°C)
-4.4
8.8
22.6
11.0
9.5
Average temperature (°C)
-9.8
3.0
16.7
6.0
4.0
Total precipitation (mm)
246
265
367
305
1,173
56
the equivalent of 2 to 15 mm of precipitation. By the year 2090, summer precipitation could remain the
same as the reference period or decrease by up to 4%, the equivalent of 15 mm. The mean across all
four SSP scenarios of the 13 GCM ensemble suggests that by the end of the century, Estrie Forests will
receive a total of 262 mm precipitation during the summer months, an overall decrease in 5 mm
compared to the reference period.
MINIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of minimum temperature was -
1.5°C. Normals for minimum temperature by season are shown in Table 10.1. Projected changes using
the 13 GCMs showed an overall increase in minimum temperature over the next century (Figure 10.3).
Minimum temperature is likely to increase by 2.6°C and 4.5°C by years 2050 and 2090, respectively,
indicating that mean minimum temperature could be as high as 3.0°C by the end of the century. These
values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER MINIMUM TEMPERATURE
Projected changes in winter minimum temperature for each SSP scenario are shown in Figure
10.3. By the year 2050, minimum temperature during winter months is projected to increase between
2.9 and 4.3°C, according to SSP1-2.6 and SSP5-8.5 scenarios, respectively. By 2090, minimum
temperature is projected to increase between 2.8 and 8.5°C, according to SSP1-2.6 and SSP5-8.5
scenarios, respectively. The mean across all four SSP scenarios of the 13 GCM ensemble suggests a
winter minimum temperature of -9.3°C by the end of the century, an overall increase of 5.9°C compared
to the reference period.
SUMMER MINIMUM TEMPERATURE
Projected changes in summer minimum temperature for each SSP scenario are shown in Figure
10.3. By the year 2050, minimum temperature throughout the summer is projected to increase between
1.7 and 2.5°C, according to SSP1-2.6 and SSP5-8.5 scenarios, respectively. By 2090, the minimum
temperature is projected to continue to increase between 1.7 and 5.6°C, according to SSP1-2.6 and
SSP5-8.5 scenarios, respectively. The mean across all four SSP scenarios of the 13 GCM ensemble
suggests summer minimum temperature of 14.7°C by the end of the century, an overall increase of
3.8°C compared to the reference period.
MAXIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of maximum temperature was
9.5°C. Normals for maximum temperature by season are shown in Table 10.1. Projected changes using
the 13 GCMs showed an overall increase in maximum temperature over the next century (Figure 10.4).
Maximum temperature is likely to increase by 3.0°C and 4.8°C by years 2050 and 2090, respectively,
57
indicating that mean maximum temperature could reach as high as 14.3°C by the end of the century.
These values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER MAXIMUM TEMPERATURE
Projected changes of winter maximum temperature for each SSP are shown in Figure 10.4. By
the year 2050, maximum temperature throughout the winter months is projected to increase between
2.4 and 3.4°C, according to SSP1-2.6 and SSP5-8.5 scenarios, respectively. By 2090, maximum
temperature is projected to rise to between 2.3 and 5.5°C, according to SSP1-2.6 and SSP3-7.0
scenarios, respectively. The mean across all four SSP scenarios of the 13 GCM ensemble suggests winter
maximum temperature of -0.2°C by the end of the century, an overall increase of 4.2°C compared to the
reference period.
SUMMER MAXIMUM TEMPERATURE
Projected changes of summer maximum temperature for each SSP are shown in Figure 10.4. By
the year 2050, maximum temperature throughout the summer months is projected to increase between
2.8 and 3.7°C, according to SSP1-2.6 and SSP5-8.5 scenarios, respectively. By 2090, maximum
temperature is projected to increase between 2.8 and 7.3°C, according to SSP1-2.6 and SSP5-8.5
scenarios, respectively. The mean across all four SSP scenarios of the 13 GCM ensemble suggests
summer maximum temperature of 27.7°C by the end of the century, an overall increase of 5.1°C
compared to the reference period.
----
Means of seasonal and annual variables by SSP scenario and 20-year interval from 2001 – 2100 for each
climate variable can be found in ANNEX 2: Supplementary Data.
58
Figure 10.2. Projections for change in seasonal precipitation (mm) for the years 2050 and 2090 relative to the reference period (1981 – 2010).
59
Figure 10.3. Projections for change in seasonal minimum temperature (°C) for the years 2050 and 2090 relative to the reference period (1981 –
2010).
60
Figure 10.4. Projections for change in seasonal maximum temperature (°C) for the years 2050 and 2090 relative to the reference period (1981 –
2010).
61
11.0 PETAWAWA RESEARCH FOREST
EXECUTIVE SUMMARY
There is a general agreement across all global circulation models that the Petawawa Research Forest (PRF)
will become a warmer and wetter location with changes in temperature increasing by 3 – 5°C and precipitation
increasing by up to 9% by the end of the century.
Few seasonal trends were observed between summer and winter temperatures, all indicating a general
warming, though increases in minimum temperature during the winter months was projected to see the greatest
change in temperature (warming of 6.5°C) compared to other seasonal fluctuations (summer warming of 4.3°C –
4.6°C). Increases in winter precipitation (+ 40 mm) outweighed reductions in summer precipitation (- 12 mm),
indicating a shift towards an overall warmer and wetter climate by the end of the century. Changes in the next 30
years are likely to be more extreme than the following 50.
Key forestry implications of these changes for PRF suggest an overall increase in productivity given the
warmer and wetter climate. However, this could also indicate an associated risk of invasive tree and pest species
which would also benefit from a warm, wet climate. Species that are more drought tolerant, such as black spruce
and oak (Quercus spp.), will likely be a regional competitor within the next 50 years.
STUDY AREA
The Petawawa Research Forest (PRF),
located in Chalk River, Ontario (Figure 11.1) in the
municipality of Laurentian Hills and part of the
Great Lakes-St Lawrence Forest region (Rowe,
1972). Established in 1918, the PRF is property of
the Department of National Defense, and since
1926, has been managed by Natural Resources
Canada through the Canadian Wood Fibre Centre.
The PRF maintains status as a research forest and
contributes to the protection, sustainability,
innovation and economic development of Canadian
forests and to global forest research and
management.
The PRF covers approximately 10,000 ha of
land and is covered by 8,500 ha of forest. These
forests are a mix of hardwood and conifers,
dominated by white pine (Pinus strobus L), red
pine, trembling aspen and white birch (Wetzel et
al., 2011). Red oak (Quercus rubra L.) is the dominant species on poor, dry and hilly sites, whereas Jack
pine dominates on flat, dry sites. Overall, the soil is characterized by an acidic, mor-type forest floor with
a depth greater than 2 m, alluvial medium sand, likely classified as a Dystric Brunisol (Soil Classification
Figure 11.1. The Petawawa Research Forest, located in Ontario,
Canada (top right), south of the Laurentian Hills (bottom).
62
Working Group, 1998). Soil lays on top of the Precambrian shield, where bedrock is composed of
granites and gneisses.
The PRF contains an extensive area of forest research, which over the years has included
approximately 500 growth and yield permanent sample plots, 100 silvicultural field studies, 125 research
plantations, 1100 intensive forest management plots, 300 genetic trials, 100 forest fire experimental
sites, 13 ecological reserves and 30 remote sensing sites (D’Eon, 2006). Common silvicultural practices
studied at the PRF include uneven-aged forests using tree selection (1 forest unit, cover 7% area), even-
aged forests using shelterwood systems (three forest units cover 52% area) and clearcutting (10 units
cover 41% area) (FMP, p. 37). The PRF’s 2021-2032 Forest Management Plan aims to harvest 8% of the
growing stock, approximately 20,000 m3. Lastly, Friends of the Petawawa Research Forest is a local non-
profit organization established to support, promote and protect the PRF for scientific study,
environmental education and public recreation. This includes raising awareness, generating support and
facilitating youth programs. They are also responsible for the maintenance and development of hiking,
walking and cross-country skiing trails, as well as an arboretum.
Major sources of disturbances to the PRF forest include sporadic periods of windthrow and
insect infestations including gypsy moth (Lymantria dispar dispar Linnaeus), forest tent caterpillar,
spruce budworm, spruce and pine sawflies and sugar maple borer (Glycobius speciosus Say). In the last
decade there has been an increasing occurrence of beech bark disease (Fagus grandifolia Ehrh.) along
with historical occurrences of Dutch elm disease (Ophiostoma ulmi (Buisman) Melin & Nannf.), nectria
canker (Neonectria galligena Tul. & C. Tul.), Armillaria root rot (Armillaria heimii Peglar) and diplodia
(Botryosphaeriaceae (Theiss & H. Syd.).
The PRF maintains treaties with the First Nations including the Williams Treaties of 1923. The
closest First Nations community is the Pikwakanagan First Nation – Algonquin community.
HISTORICAL CLIMATE DATA
The PRF represents forests of the Great Lakes – St. Lawrence Forest region with a continental
climate, with a mean annual temperature of 5.1°C. It is slightly drier compared to nearby regions due to
a rain shadow effect caused by the highlands in Algonquin Park and receives 875 mm of precipitation
per year. The average growing season length is 136 days with the coldest and warmest months of the
year being January and July, respectively. Observed climate normal data for PRF for the reference period
of 1980 – 2010 are shown in Table 11.1.
63
FUTURE PRECIPITATION
For the reference period of 1981 – 2010, the 30-year normal of annual precipitation was 875
mm per year. Normals for total precipitation by season are shown in Table 11.1. Projected changes using
the 13 GCMs showed an overall increase in precipitation over the next century. By 2050, annual
precipitation is likely to increase by 5% (the equivalent of 42 mm). By 2090, annual precipitation is likely
to increase by 9% (the equivalent of 75 mm) for a total of 950 mm per year by the end of the century.
These values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER PRECIPITATION
Projected changes in winter precipitation for each SSP scenario are shown in Figure 11.2. By the
year 2050, winter precipitation is projected to increase between 12 to 17%, the equivalent of 20 – 29
mm. By 2090, these projections are expected to reach an increase between 12 and 35%, the equivalent
of 20 – 58 mm. The mean across all four SSP scenarios of the 13 GCM ensemble suggests winter
precipitation of 212 mm by the end of the century, an increase of 40 mm compared to the reference
period.
SUMMER PRECIPITATION
Projected changes in summer (June, July, August) precipitation for each SSP scenario are shown
in Figure 11.2. By the year 2050, summer precipitation is projected to decrease between 2 to 5%, the
equivalent of 5 – 13 mm. By the year 2090, summer precipitation could decrease between 1 to 8%, the
equivalent of 2 – 21 mm. The mean across all four SSP scenarios of the 13 GCM ensemble suggests
summer precipitation of 251 mm by the end of the century, a decrease of 12 mm compared to the
reference period.
Table 11.1. Observed climate normal from 1981 – 2010 at the Petawawa Research Forest generated by
ClimateNA at 250 m resolution. Total precipitation includes both rainfall and snowfall.
Winter
(Dec – Feb)
Spring
(Mar – May)
Summer
(Jun – Aug)
Autumn
(Sep – Nov)
Annual
Minimum Temperature (°C)
-15.0
-2.1
11.9
2.1
-0.8
Maximum temperature (°C)
-4.3
10.9
25.1
12.4
11.0
Average temperature (°C)
-9.7
4.4
18.5
7.3
5.1
Total precipitation (mm)
172
198
262
244
875
64
FUTURE MINIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of minimum temperature was -
0.8°C. Normals for minimum temperature by season are shown in Table 11.1. Projected changes using
the 13 GCMs showed an overall increase in minimum temperature over the next century (Figure 11.3).
Minimum temperature is likely to increase by 3.2°C and 5.2°C by years 2050 and 2090, respectively,
indicating that mean minimum temperature could be as high as 4.4°C by the end of the century. These
values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER MINIMUM TEMPERATURE
Projected changes in winter minimum temperature for each SSP scenario are shown in Figure
11.3. By the year 2050, minimum temperature during winter months is projected to increase between
3.3°C and 4.8°C. By 2090, minimum temperature is projected to increase between 3.2°C and 9.3°C. The
mean across all four SSP scenarios of the 13 GCM ensemble suggests winter minimum temperature of -
8.5°C by the end of the century, an increase of 6.5°C compared to the reference period.
SUMMER MINIMUM TEMPERATURE
Projected changes in summer minimum temperature for each SSP scenario are shown in Figure
11.3. By the year 2050, minimum temperature throughout the summer is projected to increase between
2.2°C and 3.0°C. By 2090, minimum temperatures are projected to continue to increase between 2.2°C
and 6.2°C. The mean across all four SSP scenarios of the 13 GCM ensemble suggests summer minimum
temperature of 16.2°C by the end of the century, an increase of 4.3°C compared to the reference period.
FUTURE MAXIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of maximum temperature was
11.0°C. Normals for maximum temperature by season are shown in Table 11.1. Projected changes using
the 13 GCMs showed an overall increase in maximum temperature over the next century (Figure 11.4. ).
Maximum temperature is likely to increase by 2.6°C and 4.4°C by years 2050 and 2090, respectively,
indicating that mean maximum temperature could reach as high as 15.4°C by the end of the century.
These values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER MAXIMUM TEMPERATURE
Projected changes of winter maximum temperature for each SSP are shown in Figure 11.4. . By
the year 2050, maximum temperature throughout the winter months is projected to increase between
2.1°C and 3.1°C. By 2090, maximum temperature is projected to continue to increase between 2.0°C
and 6.4°C. The mean across all four SSP scenarios of the 13 GCM ensemble suggests winter maximum
temperature of 0°C by the end of the century, an increase of 4.3°C compared to the reference period.
65
SUMMER MAXIMUM TEMPERATURE
Projected changes of summer maximum temperature for each SSP are shown in Figure 11.4. . By
the year 2050, maximum temperature throughout the summer months is projected to increase between
2.2°C and 3.1°C. By 2090, maximum temperature is projected to increase between 2.2°C and 6.8°C. The
mean across all four SSP scenarios of the 13 GCM ensemble suggests summer maximum temperature of
29.7°C by the end of the century, an increase of 4.6°C compared to the reference period.
----
Means of seasonal and annual variables by SSP scenario and 20-year interval from 2001 – 2100 for each
climate variable can be found in ANNEX 2: Supplementary Data.
66
Figure 11.2. Projections for change in seasonal precipitation (mm) for the years 2050 and 2090 relative to the reference period (1981-2010).
67
Figure 11.3. Projections for change in seasonal minimum temperature for the years 2050 and 2090 relative to the reference period (1981-
2010).
68
Figure 11.4. Projections for change in seasonal maximum temperature for the years 2050 and 2090 relative to the reference period (1981-
2010).
69
12.0 HALIBURTON FOREST
EXECUTIVE SUMMARY
There is a general agreement across all global circulation models that the Haliburton Forest will become a
warmer location with warmer annual temperatures. By 2090, precipitation is projected to increase by up to 26% (the
equivalent of 60 mm) during winter months but decrease by 7% (the equivalent of 19 mm) during summer months,
resulting in a slight increase in annual precipitation amounts. During this same time, annual temperatures are
expected to increase dramatically. The greatest increase is expected for maximum temperature during summer
months which is expected to increase by 8.0°C. Similarly, minimum temperatures during both summer and winter
months are expected to increase by 7.7 and 6.4°C, respectively. Such changes are likely to be more extreme closer
to the end of the century.
Key forestry implications of these projections suggest summer drought conditions are extremely likely. This
is likely to increase competition amongst tree species, resulting in an increasing abundance of drought-resistant
species. This is also likely to perpetuate forest insect outbreaks, which will also be a result of warmer winters.
Warmer winter temperatures also suggest that there will be less precipitation falling as snow, which is likely to cause
interactions between rain-on-snow events and root stability.
STUDY AREA
The Haliburton Forest (HF) is located in
the county of Haliburton, 270 km north of
Toronto, Ontario (Figure 12.1). Following the
province of Ontario’s land classification system,
the HF is part of the Georgian Bay ecoregion (5E)
and the Algonquin Park ecodistrict (5E-9). This
ecodistrict is associated with the Eastern
Temperate Mixed Forest Vegetation Zone and
the Algonquin-Pontiac Section of the Great
Lakes-St Lawrence Forest Region. This region is
atop the Canadian Precambrian Shield on the
southwest face of the Algonquin Dome, at
elevation between 400 and 550 m. Major
landforms in the region include moraines with
some low-profile drumlins. In areas with
relatively deep soil that are well drained, the
Sherborne till is an excellent forest soil. However,
in shallow depths, a shallow rooting zone
combined with moisture stress is often a limiting
factor for tree growth in this region.
Within the Algonquin Park ecodistrict, land cover is dominated by deciduous forest (42%), mixed
forest (40%), coniferous forest (12%) and other natural land cover (6%). Deciduous forests consist of
Figure 12.1. Haliburton Forest located in Ontario, Canada (top
right) north of the town of Haliburton (bottom).
70
sugar maple (Acer saccharum Marsh.), American beech (Fagus grandifolia Ehrh.), and yellow birch which
dominate on deeper substrates, often with large-toothed aspen (Populus grandidentata Michaux), red
maple, northern red oak, and black cherry (Prunus serotina Ehrh.). Paper birch (Betula papyrifera
Marsh.) and trembling aspen are more common on cooler-than-normal sites and in areas of disturbance.
Balsam poplar (Populus balsamifera L.), black ash (Fraxinus nigra Marsh.), American elm (Ulmus
americana L.), silver maple (Acer saccharinum L.), and green ash (Fraxinus pennsylvanica Marsh.) grow
along major river valleys on fresh to moist sites, and species found farther south such as American
basswood (Tilia americana L.), bur oak (Quercus macrocarpa Michx.), and white ash (Fraxinus americana
L.) inhabit south-facing slopes or can be found along the southern edge of the ecodistrict.
The HF specifically is located in hardwood country. It includes 35,000 ha of forested land, of
which 29,000 ha is considered to be productive and part of the timber harvesting land base for the
province. Although conifers, particularly pine and hemlock (Tsuga spp.) were once better represented,
hardwoods predominate on 70% of the productive forest land and virtually all the protected forest lands
in the Haliburton Forest.
The HF is private tenured land, operated by the Haliburton Forest and Wild Life Reserve Ltd.
which owns and operates multi-use lands, which gains revenue from its own private sawmill, as well as
recreation (cabin rentals, camping, snowmobiling, etc.) and the leasing of hunting lots. Forestry
operations are maintained by independent logging contractors that operate within the Haliburton
Highlands. Currently, forest stands are grouped into strata called ‘Working Groups’, of which there are
20 in the HF. Each is based on the dominant species (or species group) within the stand if it dominates at
least 60% of that stand. For example, if a stand consists of 60% hard maple, it is classified in the Hard
Maple Working Group. It is expected that over time, the working group system will be abandoned in
favor of Ontario’s ecological land classification system and be classified by ecosite. Regardless, each
Working Group is managed using a particular selection harvesting regime using both uneven-aged and
even-aged silvicultural systems. Uneven-aged management is prescribed for Hard Maple Working Group
and other mixed hardwood working groups. Even-aged management may be prescribed for the poplar
and white birch working groups, while shelterwood management will be used in the red oak and yellow
birch working groups. The hemlock working group is treated with a modified selection system due to
difficulty with natural regeneration.
A historical lack of human disturbance at the HF has helped to retain a pristine ecosystem, which
largely reflects that of an era prior to anthropogenic impacts. Natural disturbances in the area are
largely due to windthrow events, from which storm damage has been part of the ecological dynamics of
these forest ecosystems for millennia. However, a recent increase in the frequency and severity of wind
and storm events has been observed at the HF. Most noticeably a summer storm in 1995 that damaged
2,000 ha of land and leveled 567 ha of forest. At a significantly earlier time, in 1913, a large forest fire
burned 3,200 ha of forested land.
The HF has not historically known to have been made of use by First Nations, likely due to
rugged topography, small water bodies, colder climate and difficult access, with the exception of
temporary settlements.
71
HISTORICAL CLIMATE DATA
The region around HF is characterized by a continental climate with cold winters and warm
summers. The average frost-free period is 104 days and the growing season lasts about 180 days. The HF
receives more annual precipitation, 1,011 mm per year, compared to nearby towns. Northern regions of
the forest also receive significantly more snowfall compared to southern areas. Historical drought
events have occurred for three consecutive years between 1988 and 1990 and in the summers of 1997
and 1998 when there were seven consecutive weeks with lack of significant rainfall. The 30-year climate
normals for the reference period of 1981 – 2010 for the Haliburton forests are shown in Table 12.1.
FUTURE PRECIPITATION
For the reference period of 1981 – 2010, the 30-year normal of annual precipitation was 1,011
mm per year. Normals for total precipitation by season are shown in Table 12.1. Projected changes
using the 13 GCMs showed a slight increase in precipitation over the next century (Figure 12.2). By 2050,
annual precipitation is likely to increase slightly by 2% (the equivalent of 21 mm). By 2090, annual
precipitation is likely to increase by 6% (the equivalent of 59 mm) for a total of 1,070 mm per year by
the end of the century. These values represent the average change across all four SSP scenarios of a 13
GCM ensemble.
WINTER PRECIPITATION
Projected changes in winter precipitation for each SSP scenario are shown in Figure 12.2. By the
year 2050, winter precipitation is projected to increase between 6 and 12%, the equivalent of 14 and 27
mm (according to SSP1-2.6 and SSP5-8.5, respectively). By 2090, these projections are expected to reach
between 6 and 26%, the equivalent of 15 – 60 mm (according to SSP1-2.6 and SSP5-8.5, respectively).
The mean across all four SSP scenarios of the 13 GCM ensemble suggests that by the end of the century,
Table 12.1. Observed climate normal from 1981 – 2010 at the Haliburton Forest generated by
ClimateNA at 250 m resolution. Total precipitation includes both rainfall and snowfall.
Winter
(Dec – Feb)
Spring
(Mar – May)
Summer
(Jun – Aug)
Autumn
(Sep – Nov)
Annual
Minimum Temperature (°C)
-12.1
-10.4
9.4
7.1
-1.4
Maximum temperature (°C)
-2.9
2.2
22.2
18.4
10.0
Average temperature (°C)
-7.5
-4.1
15.8
12.7
4.3
Total precipitation (mm)
229
223
263
296
1,011
72
and will receive a total of 267 mm precipitation during the winter months, an increase of 40 mm
compared to the reference period.
SUMMER PRECIPITATION
Projected changes in summer (June, July, August) precipitation for each SSP scenario are shown
in Figure 12.2. By the year 2050, summer precipitation is projected to remain constant or decrease by up
to 3%, the equivalent of 1.3 mm to 9.0 mm (according to SSP1-2.6 and SSP2-4.5, respectively). By the
year 2090, summer precipitation could remain relatively constant (increase by 1%) or decrease by 7%,
the equivalent of +2.3 or -19mm (according to SSP1-2.6 and SSP3-7.0. The mean across all four SSP
scenarios of the 13 GCM ensemble suggests that by the end of the century, Haliburton Forest will
receive a total of 254 mm precipitation during the summer months, an overall decrease of 8.7 mm
compared to the reference period.
FUTURE MINIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of minimum temperature was -
1.4°C. Normals for minimum temperature by season are shown in Table 12.1. Projected changes using
the 13 GCMs showed an overall increase in minimum temperature over the next century (Figure 12.3. ).
Minimum temperature is likely to increase between 3.4°C and 5.3°C by years 2050 and 2090,
respectively, indicating that mean minimum temperature could be as high as 3.9°C by the end of the
century. These values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER MINIMUM TEMPERATURE
Projected changes in winter minimum temperature for each SSP scenario are shown in Figure
12.3. . By the year 2050, minimum temperature during winter months is projected to increase between
0.8°C and 2.2°C, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, minimum temperature is
projected to increase between 0.7°C and 6.4°C, according to SSP1-2.6 and SSP5-8.5, respectively. The
mean across all four SSP scenarios of the 13 GCM ensemble suggests a winter minimum temperature of
-8.3°C by the end of the century, an increase of 3.8°C compared to the reference period.
SUMMER MINIMUM TEMPERATURE
Projected changes in summer minimum temperature for each SSP scenario are shown in Figure
12.3. . By the year 2050, minimum temperature throughout the summer is projected to increase by
3.7°C and 4.5°C, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, minimum temperatures are
projected to continue to increase between 3.7°C and 7.7°C, according to SSP1-2.6 and SSP5-8.5,
respectively. The mean across all four SSP scenarios of the 13 GCM ensemble suggests summer
minimum temperature of 15.2°C by the end of the century, an increase of 5.8 compared to the
reference period.
73
FUTURE MAXIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of maximum temperature was
10.0°C. Normals for maximum temperature by season are shown in Table 12.1. Projected changes using
the 13 GCMs showed an overall increase in maximum temperature over the next century (Figure 12.4. ).
Maximum temperature is likely to increase by 2.8°C and 4.6°C by years 2050 and 2090, respectively,
indicating that mean maximum temperature could reach as high as 14.6°C by the end of the century.
These values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER MAXIMUM TEMPERATURE
Projected changes of winter maximum temperature for each SSP are shown in Figure 12.4. . By
the year 2050, maximum temperature throughout the winter months is projected to increase between
1.0°C and 1.9°C, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, maximum temperature is
projected to continue to increase by 0.9°C – 5.1°C, according to SSP1-2.6 and SSP5-8.5, respectively. The
mean across all four SSP scenarios of the 13 GCM ensemble suggests winter maximum temperature of
0.3°C by the end of the century, an increase of 3.2°C compared to the reference period.
SUMMER MAXIMUM TEMPERATURE
Projected changes of summer maximum temperature for each SSP are shown in Figure 12.4. . By
the year 2050, maximum temperature throughout the summer months is projected to increase between
3.4°C and 4.3°C, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, maximum temperature is
projected to increase between 3.4°C and 8.0°C, according to SSP1-2.6 and SSP5-8.5, respectively. The
mean across all four SSP scenarios of the 13 GCM ensemble suggests summer maximum temperature of
28.0°C by the end of the century, an increase of 5.8°C compared to the reference period.
----
Means of seasonal and annual variables by SSP scenario and 20-year interval from 2001 – 2100 for each
climate variable can be found in ANNEX 2: Supplementary Data.
74
Figure 12.2. Projections for change in seasonal precipitation (mm) for the years 2050 and 2090 relative to the reference period (1981-2010).
75
Figure 12.3. Projections for change in seasonal minimum temperature for the years 2050 and 2090 relative to the reference period (1981-
2010).
76
Figure 12.4. Projections for change in seasonal maximum temperature for the years 2050 and 2090 relative to the reference period (1981-
2010).
77
78
--ACADIAN FOREST SITES--
Acadian
Forest Sites
79
13.0 BLACK BROOK RESEARCH FOREST
EXECUTIVE SUMMARY
There is a general agreement across all global circulation models that the Black Brook Research Forest will
see an increase in precipitation and general warming over the next century. Precipitation is likely to increase during
the winter months (an average increase of 22%, the equivalent of 51 mm), whereas it will likely stay the same during
summer months (average of 0% change, the equivalent of 7 mm). Minimum temperature during the winter months
was projected to see the greatest change in temperature (warming of 6.9°C) compared to other seasonal fluctuations
(summer warming of 4.9°C – 5.3°C). Changes in minimum temperature are likely to be more extreme in the next 30
years, whereas changes in maximum temperature are likely to be more extreme in the following 50.
Key forestry implications for Black Brook Forest in a warmer and wetter climate suggest an overall increase
in productivity as long as adequate soil moisture remains. A warm and wet climate could also suggest reduced
abundance for certain species, such as balsam fir, and increase in others, such as hardwoods like oak and maple.
This, along with a northern migration of certain species, could result in more mixed hardwood stands with spruce,
fir and pine. Warmer and wetter climates may also bring associated risk of invasive tree species (such as birch, maple
and poplar) and pest species.
STUDY AREA
The Black Brook Forest District (BBFD) is a
210,000-ha forest owned and operated by J.D. Irving
Limited since 1943. The BBFD is part of the Sisson
ecodistrict in the Central Uplands ecoregion of New
Brunswick (Figure 13.1).
In areas of low relief, soils consist mostly of
Ordovician-Devonian sedimentary rocks and deep loam.
By comparison, soils on higher terrain are less fertile
and soils are shallow and stony (Zelazny, 2007).
Aboveground, the forest is comprised of uneven-aged
hardwood stands (25%), accompanied by mixed-wood
(18%), softwood-cedar (15%) and softwood (42%)
forests (Erdozain et al., 2018). Within managed
hardwood stands, shade-tolerant and mid-tolerant
stands consist of sugar maple, American beech, red
maple, and yellow birch. Such trees are managed for
high-quality veneer and sawlogs by selection and patch-
cut systems (Higdon et al., 2005). Intolerant hardwoods,
such as white birch and trembling aspen, and softwoods
are comprised in the natural regeneration that follows clearcuts (Higdon et al., 2005). Primary softwood
tree species include black spruce, white spruce, Norway spruce (Picea abies) and pine (Pinus spp.)
(Etheridge et al., 2006).
Figure 13.1. The Black Brook Forest District, located in
New Brunswick, Canada (top right), east to the city of
Edmunston (bottom).
80
The BBFD is one of the most intensively managed forests in Canada (Etheridge et al., 2006) with
a Forest Stewardship Council (FSC) certification and objective to better understand the relationships
between biodiversity and forest management in order to improve forestry practices. The forests are
managed using site preparation, planting, cleaning and commercial thinning. Plantations are managed
on a 70–80-year rotation, with two or three commercial thinnings. Approximately 20% of the area has
harvesting restrictions, including no harvest scientific reserves (3.5%), winter habitat for white tailed
deer (Odocoileus virginianus) (4%) and partial harvesting only in watercourse buffers (10%) (Etheridge et
al., 2006).
Historically, natural disturbance regimes are dominated by spruce budworm, wind and fire.
These disturbances have been used to define guidelines at the appropriate stand- and forest-level
treatment (MacLean et al., 2010). Presently, fire control is not considered as a natural disturbance due
to the highly developed road network. In the future, it is expected that spruce budworm will continue to
cause damage to spruce and fir trees. Mitigation attempts are in place via adjusting harvesting
schedules. Shoot blight (Siroccocus spp.) is also present in the area and poses a threat to red pine stands
which are currently being salvaged as quickly as possible.
HISTORICAL CLIMATE DATA
The BBFD is part of the Madawaska Uplands which maintains a cooler climate with a mean
annual temperature of 3.1°C. South- and west-facing regions have warmer temperatures compared to
north-facing regions in the Northern Uplands ecoregion. The climate is relatively wetter compared to
the adjacent Valley lowlands due to the effects of orographic lifting across the undulating terrain
(Zelazny, 2007) and receives 1,062 mm of precipitation annually. The 30-year climate normals for the
reference period of 1981 – 2010 for the Haliburton forests are shown in Table 13.1.
FUTURE PRECIPITATION
For the reference period of 1981 – 2010, the 30-year normal of annual precipitation was 1,062
mm per year. Normals for total precipitation by season are shown in Table 13.1. Projected changes using
Table 13.1. Observed climate normal from 1981 – 2010 at the Haliburton Forest generated by
ClimateNA at 250 m resolution. Total precipitation includes both rainfall and snowfall.
Winter
(Dec – Feb)
Spring
(Mar – May)
Summer
(Jun – Aug)
Autumn
(Sep – Nov)
Annual
Minimum Temperature (°C)
-16.8
-3.7
10.1
0.31
-2.5
Maximum temperature (°C)
-5.9
8.1
22.5
10.1
8.7
Average temperature (°C)
-11.3
2.2
16.3
5.2
3.1
Total precipitation (mm)
231
223
320
288
1,062
81
the 13 GCMs showed an overall increase in precipitation over the next century (Figure 13.2). By 2050,
annual precipitation is likely to increase by 5% (the equivalent of 56 mm). By 2090, annual precipitation
is likely to increase by 9% (the equivalent of 98 mm) for a total of 1,160 mm per year by the end of the
century. These values represent the average change across all four SSP scenarios of a 13 GCM ensemble,
indicating a mean annual precipitation of 1,117 mm by 2090.
WINTER PRECIPITATION
Projected changes in winter precipitation for each SSP scenario are shown in Figure 13.2. By the
year 2050, winter precipitation is projected to increase between 9 to 13%, the equivalent of 21 – 30 mm
(according to SSP1-2.6/SSP2-4.5 and SSP5-8.5, respectively). By 2090, these projections are expected to
continue to increase between 9 and 36%, the equivalent of 20 – 84 mm (according to SSP1-2.6 and SSP3-
7.0, respectively). The mean across all four SSP scenarios of the 13 GCM ensemble suggests that by the
end of the century, Black Brook Forest will receive a total of 282 mm precipitation during the winter
months by 2090, an increase of 51 mm compared to the reference period.
SUMMER PRECIPITATION
Projected changes in summer (June, July, August) precipitation for each SSP scenario are shown
in Figure 13.2. By the year 2050, summer precipitation is projected to change by a decrease of 1% or an
increase of 2%, the equivalent of -3 mm to 7 mm (according to SSP2-4.5 and SSP5-8.5, respectively). By
the year 2090, summer precipitation could increase between 1 to 4%, the equivalent of 3 – 11 mm
(according to SSP3-7.0 and SSP5-8.5, respectively). The mean across all four SSP scenarios of the 13 GCM
ensemble suggests that by the end of the century, Black Brook Forest will receive a total of 327 mm
precipitation during the summer months by 2090, a slight increase of 7 mm.
FUTURE MINIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of minimum temperature was -
2.5°C. Normals for minimum temperature by season are shown in Table 13.1. Projected changes using
the 13 GCMs showed an overall increase in minimum temperature over the next century (Figure 13.3).
Minimum temperature is likely to increase by 3.0°C and 5.0°C by years 2050 and 2090, respectively,
indicating that mean minimum temperature could be as high as 2.5°C by the end of the century. These
values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER MINIMUM TEMPERATURE
Projected changes in winter minimum temperature for each SSP scenario are shown in Figure
13.3. By the year 2050, minimum temperature during winter months is projected to increase by 3.6 –
5.2°C, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, minimum temperature is projected to
increase by 3.7 – 9.6°C, according to SSP1-2.6 and SSP5-8.5, respectively. The mean across all four SSP
82
scenarios of the 13 GCM ensemble suggests a winter minimum temperature of -9.9°C by the end of the
century, an increase of 6.9°C compared to the reference period.
SUMMER MINIMUM TEMPERATURE
Projected changes in summer minimum temperature for each SSP scenario are shown in Figure
13.3. By the year 2050, minimum temperature throughout the summer is projected to increase by 2.0 –
2.9°C, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, the minimum temperature is projected
to continue to increase by 2.1 – 6.0°C, according to SSP1-2.6 and SSP5-8.5, respectively. The mean
across all four SSP scenarios of the 13 GCM ensemble suggests summer minimum temperature of 14.2°C
by the end of the century an increase of 4.1°C compared to the reference period.
FUTURE MAXIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of maximum temperature was
8.7°C. Normals for maximum temperature by season are shown in Table 13.1. Projected changes using
the 13 GCMs showed an overall increase in maximum temperature over the next century (Figure 13.4. ).
Maximum temperature is likely to increase by 3.0°C and 4.8°C by years 2050 and 2090, respectively,
indicating that mean maximum temperature could reach as high as 13.5°C by the end of the century.
These values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER MAXIMUM TEMPERATURE
Projected changes of winter maximum temperature for each SSP are shown in Figure 13.4. . By
the year 2050, maximum temperature throughout the winter months is projected to increase between
3.0 – 4.1°C, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, maximum temperature is
projected to continue to increase by 3.0°C – 7.3°C, according to SSP1-2.6 and SSP5-8.5, respectively. The
mean across all four SSP scenarios of the 13 GCM ensemble suggests winter maximum temperature of -
0.6°C by the end of the century, an increase of 5.3°C compared to the reference period.
SUMMER MAXIMUM TEMPERATURE
Projected changes of summer maximum temperature for each SSP are shown in Figure 13.4. . By
the year 2050, maximum temperature throughout the summer months is projected to increase between
2.6 – 3.5°C, according to SSP1-2.6 and SSP5-8.5, respectively. By 2090, maximum temperature is
projected to increase by 2.6 – 7.1°C, according to SSP1-2.6 and SSP5-8.5, respectively. The mean across
all four SSP scenarios of the 13 GCM ensemble suggests summer maximum temperature of 27°C by the
end of the century, an increase of 4.9°C compared to the reference period.
84
Figure 13.2. Projections for change in seasonal precipitation (mm) for the years 2050 and 2090 relative to the reference period (1981-2010).
85
Figure 13.3. Projections for change in seasonal minimum temperature for the years 2050 and 2090 relative to the reference period (1981-
2010).
86
Figure 13.4. Projections for change in seasonal maximum temperature for the years 2050 and 2090 relative to the reference period (1981-
2010).
87
14.0 ACADIA FOREST DISTRICT
EXECUTIVE SUMMARY
There is general agreement across all Global circulation models that the Acadia Research Forest will see a
slight increase in annual precipitation and a general warming in the upcoming century. Precipitation will increase
twice as much during the winter months (a 31% increase, up to by 2090) compared to summer months (a 12%
increase). Few seasonal trends were observed in changes to maximum temperature, though minimum temperature
will be 1.5 times higher in winter months (an increase of 6.3°C increase by 2090) compared to summer months (a
4.3°C increase). The most extreme changes are likely to be seen in the following 30 years compared to the
subsequent 50.
Key forest management implications suggest that the Acadia Forest District may see an increase in forest
productivity with warmer summer temperatures and a slight increase in summer precipitation, which could possible
sustain the greater evaporative demand from warmer temperatures. This will likely be beneficial for tree species
already established, but may also promote other species from more southern regions to migrate northward and
increase inter-species competition. Warmer summers also indicate greater risk of forest pest infestations and should
therefore be monitored.
STUDY AREA
The Acadia Forest District (AFD) is an
8,970-ha forested area located 20km
northeast of Fredericton, New Brunswick,
Canada (Figure 14.1). The AFD was
established in 1993 and is overseen by the
Atlantic Forestry Centre, which conducts
research on applying suitable forest
management principles and managing timber
resources while also protecting aquatic and
wildlife habitats and species at risk.
The AFD is found in the Eastern
Lowlands of the Acadian Forest Region. Most
of the forest is located in the Grand Lake
ecodistrict (The Ecosystem Classification
Working Group, 2007), though the northern
portion is part of the Bantalor Ecodistrict of
the Eastern Lowlands Ecoregion (Swift et al.,
2006). Within these types of ecoregions, soil
is underlaid by Pennsylvanian sedimentary
rock of red and gray sandstones of the Upper Carboniferous age with minor components of red or gray-
brown shale and conglomerates (Rees et al., 1992). The soil is mostly acidic and nutrient-poor and gives
way to forests that are a mix of softwood, hardwood and mixedwood stands.
Figure 14.1. The Acadia Forest District, located in New Brunswick,
Canada (top right), east of Fredericton (bottom).
88
The forests consist of four common species, of which 41% are spruce, 17% are balsam fir, 18%
are red maple and 9% are white birch. Red spruce, a characteristic tree species of the Acadian Forest
Region, also occurs frequently in the research forest (Swift et al. 2006). Among other species, there are
occasional remnants of white pine and tolerant hardwood stands on better drained sites. There are also
small amounts of oak, beech and ash (Fraxinus spp.). Of the previously mentioned species, the main
species for commercial use include black, red and white spruce, balsam fir and white pine. The primary
commercial hardwood species include red maple, white birch and trembling aspen. Forests in this region
have been influenced by natural disturbances that include fire and pest epidemics, such as the spruce
budworm, forest tent caterpillar and eastern larch beetle (Dendroctonus simplex LeConte). Hurricanes
have also influenced stands in the past, such as in Hurricane Ginny in 1963 which affected 42,500 m3 of
timber.
Forest management and harvested objectives are set to generate sufficient revenue to offset
operation costs; however, the primary purpose of the AFD is to harvest for a range of stands that are
typical of the Acadian Forest region and for research opportunities. The AFD aims to support scientific
research and provide a secure and safe area for federal and provincial research scientists, managers and
practitioners, as well as university researchers to enhance the development of new management tactics
and strategies for sustainable forest management. The land is also utilized by the Maritime College of
Forest Technology for field course training and for public fishing (personal communication, RPF).
HISTORICAL CLIMATE DATA
The AFD is a mix of maritime and continental climate, with a mean annual temperature of 5.4°C.
The climate is relatively warmer than other parts of the region due to the presence of New Brunswick’s
Grand Lake. The average growing season is 91 days and receives 1,108 mm of precipitation annually. The
coldest month is usually January while the warmest month if July. Climate normal data for the reference
period of 1981 – 2010 are shown in Table 14.1.
Table 14.1. Observed climate normal from 1981 – 2010 at the Acadia Forest District generated by
ClimateNA at 250 m resolution. Total precipitation includes both rainfall and snowfall.
Winter
(Dec – Feb)
Spring
(Mar – May)
Summer
(Jun – Aug)
Autumn
(Sep – Nov)
Annual
Minimum Temperature (°C)
-12.9
-1.4
11.9
2.6
0.1
Maximum temperature (°C)
-2.7
9.5
23.7
12.5
10.8
Average temperature (°C)
-7.8
4.1
17.8
7.5
5.4
Total precipitation (mm)
265
267
273
303
1,108
89
FUTURE PRECIPITATION
For the reference period of 1981 – 2010, the 30-year normal of annual precipitation was 1,108
mm per year. Normals for total precipitation by season are shown in Table 14.1. Projected changes using
the 13 GCMs showed an overall increase in precipitation over the next century (Figure 14.2. ). By 2050,
annual precipitation is likely to increase by 12% (the equivalent of 112 mm). By 2090, annual
precipitation is likely to increase by 14% (the equivalent of 155mm) for a total of 1,263 mm per year by
the end of the century. These values represent the average change across all four SSP scenarios of a 13
GCM ensemble.
WINTER PRECIPITATION
Projected changes in winter precipitation for each SSP scenario are shown in Figure 14.2. . By
the year 2050, winter precipitation is projected to increase between 22 and 27 %, the equivalent of 58
and 71 mm, according to SSP2-4.5 and SSP5-8.5 scenarios, respectively. By 2090, these projections are
expected to reach an increase between 21 and 40%, the equivalent of 57 and 107 mm, according to
SSP1-2.6 and SSP5-8.5 scenarios, respectively. The mean across all four SSP scenarios of the 13 GCM
ensemble suggests that by the end of the century, and will receive a total of 348 mm precipitation
during the winter months, an increase of 83 mm compared to the reference period.
SUMMER PRECIPITATION
Projected changes in summer (June, July, August) precipitation for each SSP scenario are shown
in Figure 14.2. . By the year 2050, summer precipitation is projected to increase by 8 – 11%, the
equivalent of 22 – 32 mm, according to SSP2-4.5 and SSP1-2.6, respectively. By the year 2090, summer
precipitation could increase between 10 and 15%, the equivalent of 26 – 42 mm, according to SSP3-7.0
and SSP5-8.5 scenarios, respectively. The mean across all four SSP scenarios of the 13 GCM ensemble
suggests that by the end of the century, ARF will receive a total of 306 mm precipitation during the
summer months, an overall increase of 34 mm.
FUTURE MINIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of minimum temperature was
0.1°C. Normals for minimum temperature by season are shown in Table 14.1. Projected changes using
the 13 GCMs showed an overall increase in minimum temperature over the next century (Figure 14.3).
Minimum temperature is likely to increase by 3.3°C and 4.9°C by years 2050 and 2090, respectively,
indicating that mean minimum temperature could be as high as 5.0°C by the end of the century. These
values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
90
WINTER MINIMUM TEMPERATURE
Projected changes in winter minimum temperature for each SSP scenario are shown Figure 14.3.
By the year 2050, minimum temperature during winter months is projected to increase between 3.6 and
4.9°C, according to SSP1-2.6 and SSP5-8 scenarios, respectively. By 2090, minimum temperature is
projected to increase between 3.5 and 8.7°C, according to SSP1-2.6 and SSP5-8.5 scenarios respectively.
The mean across all four SSP scenarios of the 13 GCM ensemble suggests a winter minimum
temperature of −6.6°C by the end of the century, an overall increase of 6.3°C, compared to the
reference period.
SUMMER MINIMUM TEMPERATURE
Projected changes in summer minimum temperature for each SSP scenario are shown in Figure
14.3. By the year 2050, minimum temperature throughout the summer is projected to increase between
2.2 and 3.1°C, according to SSP1-2.6 and SSP5-8.5 scenarios, respectively. By 2090, minimum
temperatures are projected to continue to increase between 2.3 and 6.2°C, according to SSP1-2.6 and
SSP5-8.5 scenarios, respectively. The mean across all four SSP scenarios of the 13 GCM ensemble
suggests summer minimum temperature of 16.2°C by the end of the century, an overall increase of
4.3°C compared to the reference period.
FUTURE MAXIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of maximum temperature was
10.8°C. Normals for maximum temperature by season are shown in Table 14.1. Projected changes using
the 13 GCMs showed an overall increase in maximum temperature over the next century (Figure 14.4).
Maximum temperature is likely to increase by 2.7°C and 4.5°C by years 2050 and 2090, respectively,
indicating that mean maximum temperature could reach as high as 15.3°C by the end of the century.
These values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
WINTER MAXIMUM TEMPERATURE
Projected changes of winter maximum temperature for each SSP are shown in Figure 14.4. By
the year 2050, maximum temperature throughout the winter months is projected to increase between
2.7 and 3.7°C, according to SSP1-2.6 and SSP5-8.5 scenarios, respectively. By 2090, maximum
temperature is projected to continue to increase between 2.6 and 6.7°C, according to SSP1-2.6 and
SSP5-8.5 scenarios, respectively. The mean across all four SSP scenarios of the 13 GCM ensemble
suggests winter maximum temperature of 2.1°C by the end of the century, an overall increase of 4.8°C
compared to the reference period.
91
SUMMER MAXIMUM TEMPERATURE
Projected changes of summer maximum temperature for each SSP are shown in Figure 14.4. By
the year 2050, maximum temperature throughout the summer months is projected to increase between
2.4 and 3.4°C, according to SSP1-2.6 and SSP5-8.5 scenarios, respectively. By 2090, maximum
temperature is projected to increase between 2.5 and 6.7°C, according to SSP1-2.6 and SSP5-8.5
scenarios, respectively. The mean across all four SSP scenarios of the 13 GCM ensemble suggests
summer maximum temperature of 28.3°C by the end of the century, an overall increase of 4.6°C
compared to the reference period.
----
Means of seasonal and annual variables by SSP scenario and 20-year interval from 2001 – 2100 for each
climate variable can be found in ANNEX 2: Supplementary Data.
92
Figure 14.2. Projections for change in seasonal precipitation (mm) for the years 2050 and 2090 relative to the reference period (1981-2010).
93
Figure 14.3. Projections for change in seasonal minimum temperature for the years 2050 and 2090 relative to the reference period (1981-
2010).
94
Figure 14.4. Projections for change in seasonal maximum temperature for the years 2050 and 2090 relative to the reference period (1981-
2010).
95
15.0 NOVA SCOTIA FORESTS
EXECUTIVE SUMMARY
There is general agreement across all Global circulation models that the Nova Scotia forests will see a
general warming and a slight increase of precipitation over the next century. Temperatures are likely to increase at
a faster rate during the winter months compared to the summer months. Both minimum and maximum temperature
are likely to increase by factors of 1.8 in the next 30 years and by 1.4 in the following 50. Minimum temperature is
likely to rise higher compared to maximum temperatures by the end of the century with an increase of 4.4°C and
3.4°C, respectively, compared to the reference period.
The majority of the increase in precipitation is likely to fall during winter months (+93 mm) compared to
summer months (+30 mm). Changes to both temperature and precipitation are likely to occur in the next 30 years
compared to the following 50.
Key implications for forest management for the Nova Scotia Forests suggest potential increase in forest
productivity given the projected increases in summer precipitation and warmer temperatures for the growing
season. This could have a positive impact for the region, particularly for high productive areas as part of the Triad
Management Approach. Forest management should also consider the increase risk due to windthrow, particularly
during the winter months, since warmer winter temperatures could reduce soil freezing and reduce root stability,
making trees more susceptible during winter storms.
STUDY AREA
The Nova Scotia forests are spread among
the Western Acadian Forests ecoregion, along the
southwestern region of Nova Scotia (Figure 15.1. ).
Within this ecoregion, white pine, hemlock and red
oak are more prominent compared to the rest of
the province. Study forests in this area are spread
among several ecodistricts including Rossignol,
Lahave Dumlins and St. Margaret’s Bay along the
southwest shore of the province but separate from
the South Shore ecodistricts. Soil types are
dominated by stony, medium to coarse textured
glacial tills high in granite and/or quartzite. Orthic
humo-ferric and ferro-humic podzols are the main
soils found in well-drained areas with Gleyed
subgroups commonly found in imperfectly drained
areas (Neily et al., 2017).
The Western ecoregion is surrounded by
three Mi’kmaq communities: to the extreme south
Figure 15.1. The Nova Scotia Forests located in Nova Scotia,
Canada (top right) in the western ecoregion of the province
(bottom). For a closer perspective of climate projections, these
have been divided into south-west and north-east forests for
mapping purposes only.
96
Acadia First Nation, to the West Bear River First Nation and to the North Annapolis Valley First Nations
The Rossignol area (ecodistrict 750) is largely made up of low hills and drumlin-like ridges and
includes Rossignol Lake, Nova Scotia’s largest inland body of water. This part of the western side of the
province has the earliest and warmest springs in the province. Soils tend to be moderately coarse, stony
and shallow with geological deposits made up of quartzite and slate (Neily et al., 2017). In this
ecodistrict forests are more susceptible to fire because of the dry summer conditions. On lower slopes
and better drained sites, forests are composed of hemlock, red spruce and white pine, while black
spruce dominates on imperfectly drained sites.
The Lahave Drumlins (ecodistrict 740) is a drumlinized till plain with deposits of glacial till that
slope southeast towards the Atlantic Ocean which gives way to warm springs, long growing seasons and
relatively mild winter. Soils are generally derived from slate-based parent material with some granite
underlain. The majority of soils are shallow and imperfectly drained and are unsorted glacial tills (Neily
et al., 2017). Lahave Drumlins is dominated by coniferous forests with tolerant hardwoods found on
upper slopes and sugar maple, red oak and beech found on valley floors and near major waterways.
Forests are primarily composed of black spruce, red maple and white pine with red oak, white pine and
red pine found on drier and less fertile soils. Forests also often have dense understories of ericaceous
vegetation that causes problems with regeneration and a fuel hazard for fires. Balsam fir is the common
early succession species to arise after a disturbance and is the source of significant commercial
resources, including the main species for Christmas trees.
The St Margaret’s Bay (ecodistrict 780) encompasses a lot of the Chebucto peninsula and
western Halifax Country. It extends inland to Hands County and includes eastern portions of Lunenburg
Country. This ecodistrict maintains a moisture climate given its proximity to cooler, coastal waters which
cause greater amounts of precipitation and fog, thereby increasing surrounding moisture availability and
reducing summer drought conditions compared to nearby regions. St Margaret’s Bay has mostly well-
drained sandy loams that sit atopic granitic till. This limits both timber harvesting by certain machines
and the relative stocking level of trees (Neily et al., 2017). In this area, forests are the result of cooler
temperatures, higher humidity and soil moisture and are mostly comprised of red spruce with hemlock,
white pine and yellow birch, as well as white and black spruce black spruce are also found along with
heavy ericaceous understory cover.
For the 2013 – 2017 period, Nova Scotia harvested approximately 260 and 160 million m3 of
softwood and hardwood, respectively (Province of Nova Scotia, 2020). The three most harvestable
species of softwoods included red spruce (~83 million m3), balsam fir (~72 million m3), then white pine
(~47 million m3). From hardwoods, the most harvested were red maple (~77 million m3), followed by
yellow birch (~25 million m3) and sugar maple (~20 million m3) (Province of Nova Scotia, 2020). From
harvestable wood volumes, Nova Scotia’s three main export revenues come from pulp and paper, wood-
fabricated materials and primary wood products, which combined totaled over 600 million during 2017
(Province of Nova Scotia, 2020).
Forest management in Nova Scotia is somewhat challenging given the high percentage of
privately owned forests. Approximately 70% of Nova Scotia’s forests are privately owned, with
approximately half considered to be small land owners. Since 2018 Nova Scotia is experiencing a shift of
forest management paradigm from a classical forestry paradigm which emphasizes on growing timber
97
for mills (Lahey, 2018) to embracing the ecological paradigm. The triad model of forest management is
also a key solution for Nova Scotia to favor diverse management objectives (ecological, economical and
social aims). It includes 3 zones of conservation zones, high production forestry zones, and mixed forest
or matrix zones.
In 2018, Nova Scotia had silvicultural treatments performed over approximately 15,000 ha
between private, industrial and crown land (Province of Nova Scotia, 2020). All three land ownerships
implement equal treatments of planting, as well as maintaining plantations with pre-commercial
thinning. All three also maintain natural forests with pre-commercial thinning, though it is most popular
on Crown lands. Industrial and private lands also include chemical application and wedding, which is
minimal on Crown land. Both Crown and provincial forests are aiming to increase the percentage of
harvesting that is performed using non-clearcut methods with 33% and 26% harvesting performed using
of non-clearcut for Crown and across all land tenures in 2018 (Province of Nova Scotia, 2020).
Nova Scotia’s forests main stand-level disturbance includes fire due to the droughty sandy soils
and high amounts of fuel due to ericaceous woody shrubs and conifer forests. Windthrow from
hurricanes is also a common disturbance, especially on sites with shallow, imperfectly drained soils. A
more recent disturbance includes airborne pollutants that originate from long haul transport of
industrial emissions along the eastern coast (Neily et al., 2017).
HISTORICAL CLIMATE DATA
The western region of Nova Scotia is characterized by a milder climate compared to the rest of
Nova Scotia and is influenced by the southeastern access to the Atlantic Ocean. The region is known for
relatively early and warm springs and long warm growing seasons with a mean annual temperature is
6.9°C and that receives 1,340 mm of rain. Observed climate normal data for the Nova Scotia Forests for
the reference period of 1981 – 2010 are shown in Table 15.1.
Table 15.1. Observed climate normal from 1981 – 2010 at the Nova Scotia Forests generated by ClimateNA at 250
m resolution. Total precipitation includes both rainfall and snowfall.
Winter
(Dec – Feb)
Spring
(Mar – May)
Summer
(Jun – Aug)
Autumn
(Sep – Nov)
Annual
Minimum Temperature (°C)
-7.6
0.1
11.6
4.6
2.2
Maximum temperature (°C)
1.0
9.7
22.2
13.8
11.6
Average temperature (°C)
-3.3
4.9
16.9
9.2
6.9
Total precipitation (mm)
376
328
271
365
1,340
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FUTURE PRECIPITATION
For the reference period of 1981 – 2010, the 30-year normal of annual precipitation was 1,340
mm per year. Normals for total precipitation by season are shown in Table 15.1. Projected changes using
the 13 GCMs showed an overall decrease in precipitation over the next century (Figure 15.2 and Figure
15.3). By 2050, annual precipitation is likely to increase slightly by 8% (the equivalent of 100 mm). By
2090, annual precipitation is likely to increase by 11% (the equivalent of 142 mm) for a total of 1,482
mm per year by the end of the century. These values represent the average change across all four SSP
scenarios of a 13 GCM ensemble.
WINTER PRECIPITATION
Projected changes in winter precipitation for each SSP scenario are shown in Figure 15.2. By the
year 2050, winter precipitation is projected to increase between 16 and 21%, the equivalent of between
60 and 80 mm (according to SSP1-2.6 and SSP5-8.5 scenarios, respectively). By 2090, these projections
are expected to reach an increase of between 17 and 31%, the equivalent between 64 and 116 mm
(according to SSP1-2.6 and SSP5-8.5 scenarios, respectively). The mean across all four SSP scenarios of
the 13 GCM ensemble suggests that by the end of the century, the Nova Scotia forests will receive a
total of 469 mm of precipitation during the winter months, an overall increase of 93 mm compared to
the reference period.
SUMMER PRECIPITATION
Projected changes in summer precipitation for each SSP scenario are shown in Figure 15.3. By
the year 2050, summer precipitation is projected to increase between 8 and 11%, the equivalent of 22
and 29 mm (according to SSP3-7.0 and SSP1-2.6 scenarios, respectively). These are projections are likely
to remain relatively constant by 2090, with up to a 12% increase (the equivalent of 32 mm according to
the SSP1-2.6 scenario). The mean across all four SSP scenarios of the 13 GCM ensemble suggest that by
the end of the century, the Nova Scotia forests will receive a total of 302 mm of precipitation during the
summer months, an overall increase of 30 mm compared to the reference period.
FUTURE MINIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of minimum temperature was
2.2°C. Normals for minimum temperature by season are shown in Table 15.1. Projected changes using
the 13 GCMs showed an overall increase in minimum temperature over the next century (Figure 15.4
and Figure 15.5). Minimum temperature is likely to increase by 2.8°C and 4.8°C by years 2050 and 2090,
respectively, indicating that mean minimum temperature could be as high as 6.6°C by the end of the
century. These values represent the average change across all four SSP scenarios of a 13 GCM ensemble.
99
WINTER MINIMUM TEMPERATURE
Projected changes in winter minimum temperature for each SSP scenario are shown in (Figure
15.4. By the year 2050, minimum temperature during winter months is projected to increase between
3.3 and 4.4°C according to the SSP1-2.6 and SSP5-8.5 scenarios, respectively. By 2090, minimum
temperature is projected to increase to between 2.3 and 7.3°C according to the SSP1-2.6 and SSP5-8.5
scenarios, respectively. The mean across all four SSP scenarios of the 13 GCM ensemble suggests a
winter minimum temperature of -2.4°C by the end of the century, an average overall increase of 5.3°C
compared to the reference period.
SUMMER MINIMUM TEMPERATURE
Projected changes in summer minimum temperature for each SSP scenario are shown in Figure
15.5. By the year 2050, minimum temperature throughout the summer is projected to increase between
1.6 and 2.4°C according to SSP1-2.6 and SSP5-8.5 scenarios, respectively. By 2090, the minimum
temperature is projected to continue to increase between 1.6 and 5.2°C. The mean across all four SSP
scenarios of the 13 GCM ensemble suggests summer minimum temperature of 15.5°C by the end of the
century, an overall average increase of 3.5°C compared to the reference period.
FUTURE MAXIMUM TEMPERATURE
For the reference period of 1981 – 2010, the 30-year normal of maximum temperature was
11.6°C. Normals for maximum temperature by season are shown in Table 15.1. Projected changes using
the 13 GCMs showed an overall increase in maximum temperature over the next century (Figure 15.6
and Figure 15.7). Maximum temperature is likely to increase by 1.8°C and 3.3°C °C by years 2050 and
2090, respectively, indicating that mean maximum temperature could reach as high as 14.9°C by the
end of the century. These values represent the average change across all four SSP scenarios of a 13 GCM
ensemble.
WINTER MAXIMUM TEMPERATURE
Projected changes of winter maximum temperature for each SSP are shown in Figure 15.6. By
the year 2050, maximum temperature throughout the winter months is projected to increase between
2.1 and 2.9°C according to SSP1-2.6 and SSP5-8.5 scenarios, respectively. By 2090, maximum
temperature is projected to continue to increase between 2.0 and 5.5°C according to the same
scenarios. The mean across all four SSP scenarios of the 13 GCM ensemble suggests winter maximum
temperature of 4.8°C by the end of the century, an average overall increase of 3.9°C compared to the
reference period.
100
SUMMER MAXIMUM TEMPERATURE
Projected changes of summer maximum temperature for each SSP are shown in Figure 15.7. By
the year 2050, maximum temperature throughout the summer months is projected to increase between
0.9 and 1.8°C, according to SSP1-2.6 and SSP5-8.5 scenarios, respectively. By 2090, maximum
temperature is projected to increase between 1.0 and 4.8°C, according to the same scenarios. The mean
across all four SSP scenarios of the 13 GCM ensemble suggests summer maximum temperature of
25.1°C by the end of the century, an overall average increase of 2.9°C compared to the reference period.
----
Means of seasonal and annual variables by SSP scenario and 20-year interval from 2001 – 2100 for each
climate variable can be found in ANNEX 2: Supplementary Data.
101
Figure 15.2. Projections for change in winter (December, January, February) precipitation (mm) for the years 2050 and 2090 relative to the
reference period (1981-2010).
Figure 15.3. Projections for change in summer (June, July, August) precipitation (mm) for the years 2050 and 2090 relative to the reference
period (1981-2010).
102
Figure 15.4. Projections for change in winter (December, January, February) minimum temperature (°C) for the years 2050 and 2090 relative to
the reference period (1981-2010).
Figure 15.5. Projections for change in summer (June, July, August) minimum temperature (°C) for the years 2050 and 2090 relative to the
reference period (1981-2010).
103
Figure 15.6. Projections for change in winter (December, January, February) maximum temperature (°C) for the years 2050 and 2090 relative to
the reference period (1981-2010).
Figure 15.7. Projections for change in summer (June, July, August) maximum temperature (°C) for the years 2050 and 2090 relative to the
reference period (1981-2010).
104
105
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