Download Regional projections of climate change effects on thermal habitat

Ministry of Natural Resources
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41
CLIMATE
CHANGE
RESEARCH
REPORT
CCRR-41
Responding to
Climate Change
Through Partnership
Regional Projections of
Climate Change Effects on
Thermal Habitat Space for
Fishes in Stratified Ontario
Lakes
Sustainability in a Changing Climate: An Overview of MNR’s Climate Change Strategy (2011-2014)
Climate change will affect all MNR programs and
the natural resources for which it has responsibility.
This strategy confirms MNR’s commitment to the
Ontario government’s climate change initiatives such
as the Go Green Action Plan on Climate Change
and outlines research and management program
priorities for the 2011-2014 period.
Theme 1: Understand Climate Change
MNR will gather, manage, and share information
and knowledge about how ecosystem composition,
structure and function – and the people who live and
work in them – will be affected by a changing climate.
Strategies:
• Communicate internally and externally to build
awareness of the known and potential impacts
of climate change and mitigation and adaptation
options available to Ontarians.
• Monitor and assess ecosystem and resource
conditions to manage for climate change in
collaboration with other agencies and organizations.
• Undertake and support research designed
to improve understanding of climate change,
including improved temperature and precipitation
projections, ecosystem vulnerability assessments,
and improved models of the carbon budget and
ecosystem processes in the managed forest, the
settled landscapes of southern Ontario, and the
forests and wetlands of the Far North.
• Transfer science and understanding to decisionmakers to enhance comprehensive planning and
management in a rapidly changing climate.
Theme 2: Mitigate Climate Change
MNR will reduce greenhouse gas emissions in
support of Ontario’s greenhouse gas emission
reduction goals. Strategies:
• Continue to reduce emissions from MNR operations
though vehicle fleet renewal, converting to other
high fuel efficiency/low-emissions equipment,
demonstrating leadership in energy-efficient facility
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and fostering a green organizational culture.
• Facilitate the development of renewable energy
by collaborating with other Ministries to promote
the value of Ontario’s resources as potential green
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for renewable energy development, and working
with proponents to ensure that renewable energy
developments are consistent with approval
requirements and that other Ministry priorities are
considered.
• Provide leadership and support to resource users
and industries to reduce carbon emissions and
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to increase carbon uptake, and promoting the
increased use of wood products over energyintensive, non-renewable alternatives.
• Help resource users and partners participate in a
carbon offset market, by working with our partners
to ensure that a robust trading system is in place
based on rules established in Ontario (and potentially
in other jurisdictions), continuing to examine the
mitigation potential of forest carbon management
in Ontario, and participating in the development of
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carbon offset credits.
Theme 3: Help Ontarians Adapt
MNR will provide advice and tools and techniques to
help Ontarians adapt to climate change. Strategies
include:
• Maintain and enhance emergency management
capability to protect life and property during extreme
events such as flooding, drought, blowdown and
wildfire.
• Use scenarios and vulnerability analyses to develop
and employ adaptive solutions to known and
emerging issues.
• Encourage and support industries, resource users
and communities to adapt, by helping to develop
understanding and capabilities of partners to adapt
their practices and resource use in a changing
climate.
• Evaluate and adjust policies and legislation to
respond to climate change challenges.
Regional Projections of Climate Change
Effects on Thermal Habitat Space for
Fishes in Stratified Ontario Lakes
Charles K. Minns1,2, Brian J. Shuter2,3, and Simon Fung3
Great Lakes Laboratory for Fisheries and Aquatic Sciences, Fisheries and Oceans Canada
Bayfield Institute, 867 Lakeshore Road, P.O. Box 5050, Burlington, ON L7R 4A6
1
Department of Ecology and Evolutionary Biology, University of Toronto, 25 Willcocks Street
Toronto, ON M5S 3B2
2
3
Harkness Lab Fisheries Research, Aquatic Research and Monitoring Section, Science and
Research Branch, Ontario Ministry of Natural Resources and Forestry, Peterborough, ON K9J 8M5
2014
Science and Research Branch • Ontario Ministry of Natural Resources and Forestry
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i
Summary
To better understand the effects of projected changes in climate on suitable habitat space for fish in
Ontario’s inland lakes, models for ice break-up and freeze-up dates and for seasonal open water temperature
profiles were joined to project future thermal regimes in a representative stratified lake for each of Ontario’s
secondary watersheds under future climates using four global climate models (GCMs) under alternate
greenhouse gas emissions scenarios. The seasonal availability of preferred temperature habitat in those
representative lakes was projected for fishes in three thermal guilds (cold, cool, and warm). The observed
1971 to 2000 climate averages (referred to as norms) were applied as a baseline to assess changes in
suitable habitat availability. Both volume and area habitat availability measures were computed. Four
measures of seasonal habitat availability by fish type were assessed: (a) the proportion of the year when
suitable habitat was available, (b) the proportion of total lake space (volume or area) supporting suitable
habitat, averaged over those parts of the year when some suitable space was present, (c) the proportion of
suitable lake space available over a year—the product of (a) and (b), and (d) the proportion of suitable lake
space available on the midsummer day when lake surface temperature reached its peak. The results showed
different regional response patterns among the three fish types. Coldwater fish such as lake trout will face
longer periods in summer confined to ever smaller suitable thermal spaces. Coolwater fish such as walleye
will gain more seasonal habitat space in the north of the province while becoming more constricted in southern
areas. Warmwater fish such as smallmouth bass will be able to expand northwards regionally and enjoy more
suitable space, although if climate warming reaches the upper bounds projected by some GCMs even they will
eventually become constricted. Further development of this thermal habitat model is warranted to account for
more factors affecting lakes and their fishes and to allow projections for more than one type of lake.
Résumé
Prévisions régionales des effets du changement climatique sur l’habitat thermique du
poisson dans les lacs stratifiés de l’Ontario
Afin de mieux comprendre les effets que le changement climatique aurait sur l’habitat du poisson des lacs
intérieurs de l’Ontario, des modèles ont été établis pour les dates de la formation et de la rupture des glaces
et pour les courbes de température saisonnières des eaux libres. Ces modèles ont ensuite été réunis dans le
but de prédire les régimes thermiques futurs dans un lac stratifié représentatif des lacs de chacun des bassins
versants secondaires de l’Ontario exposés à des climats futurs, prédits au moyen de quatre modèles du climat
mondial établis d’après divers scénarios d’émissions de gaz à effet de serre. La présence saisonnière d’un
habitat d’une température idéale dans les lacs représentatifs a été prédite pour le poisson dans trois strates
thermiques (froide, fraîche et assez chaude). Les moyennes climatiques observées entre 1971 et 2000 (ce
qu’on appelle les normes) ont servi de points de référence pour déterminer les changements relatifs à la
présence d’un habitat convenable. Le volume et la superficie de l’habitat ont été calculés. Quatre mesures pour
la présence d’un habitat saisonnier convenable, établies selon le type de poissons ont été examinées. Ce sont
les mesures suivantes : a) le pourcentage de l’année quand il existe un habitat convenable; b) le pourcentage
de l’espace total du lac (volume ou superficie) pouvant soutenir un habitat convenable, réparti en moyenne
sur les mois de l’année quand un habitat convenable est présent; c) le pourcentage de l’espace du lac qui
soutient un habitat convenable au cours d’une année, soit le produit de a), b) et d) indiquant le pourcentage de
l’espace du lac soutenant un habitat convenable au milieu de l’été, quand la température à la surface atteint
son zénith. Les résultats indiquent différentes tendances régionales relativement aux réactions chez les trois
types de poissons. Le poisson d’eau froide comme le touladi passera plus de temps pendant l’été confiné
dans un habitat dont la température lui convient, et cet habitat se fera de plus en plus petit. Le poisson d’eau
fraîche comme le doré aura un plus vaste habitat saisonnier dans le nord de la province, mais son habitat
s’amenuisera dans le sud de la province. Le poisson d’eau chaude comme l’achigan à petite bouche pourra
étendre son territoire vers le nord et y jouira d’un habitat plus vaste. Toutefois, si le réchauffement du climat
ii
devait atteindre la plage supérieure qui a été prévue par des modèles du climat mondial, même l’achigan à
petite bouche sera éventuellement confiné à un plus petit habitat. Il faudra élaborer davantage ce modèle de
l’habitat thermique pour tenir compte d’un nombre accru de facteurs qui touchent les lacs et leurs poissons, et
établir des prévisions pour plus qu’un seul type de lacs.
Acknowledgements
We thank Dr. Paul Gray for reviewing an earlier version of the manuscript and Trudy Vaittinen for report
layout. Support for this study was provided by the Ontario Ministry of Natural Resources and Forestry (OMNRF)
and the University of Toronto. Special thanks to Paul Gray, OMNRF, for his continuing support and advice.
Direct funding was provided by OMNRF’s Climate Change Program.
CLIMATE CHANGE RESEARCH REPORT CCRR-41
Contents
Summary........................................................................................................................................................ i
Résumé.......................................................................................................................................................... i
Acknowledgements....................................................................................................................................... ii
Introduction...................................................................................................................................................1
Methods........................................................................................................................................................1
Overall conceptual model.......................................................................................................................1
Parameterization of model components................................................................................................1
Spatial units......................................................................................................................................1
Fish types and their thermal optima.................................................................................................3
Choosing a representative lake.......................................................................................................3
Ice date models................................................................................................................................4
Seasonal temperature-profile model (STM)....................................................................................4
Climate scenarios for ice projections.....................................................................................................5
Overview of thermal habitat space model..............................................................................................5
Results and Discussion................................................................................................................................9
Caveats..................................................................................................................................................9
Thermal habitat space for fishes.........................................................................................................10
Conclusions.................................................................................................................................................18
Recommendation........................................................................................................................................18
References..................................................................................................................................................19
Appendix.....................................................................................................................................................20
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CLIMATE CHANGE RESEARCH REPORT CCRR-41
CLIMATE CHANGE RESEARCH REPORT CCRR-41
Introduction
Temperature plays a key role in the success of fishes in fresh waters (Magnuson et al 1979). Freshwater fishes
are often assigned according to their thermal preferences to cold-, cool- and warmwater guilds (Magnuson et al.
1990), with adult preferences lying close to the temperatures producing optimal growth under unlimited feeding.
Christie and Regier (1988) showed that sustained yields, from North American fisheries based on fish species
common in Ontario lakes, were well predicted by integrated annual levels of thermal habitat space, as defined by the
optimal growth temperature of the relevant species.
Climate warming is causing lake temperatures to increase (Schindler 1997), which will affect the amount of
suitable habitat space for selected fish species in the future. The purpose of this report is to provide regional
fishery managers across Ontario with first order estimates of how suitable habitat space might change for three
fish species—lake trout, walleye, and smallmouth bass—representative of the main thermal guilds found in typical
stratified Ontario lakes. We projected changes in thermal habitat space for a range of future climate projections
obtained with various global climate models (GCMs) under alternate greenhouse gas emissions scenarios.
Methods
Overall conceptual model
Recent models projecting ice date phenomena (Shuter et al. 2013) and seasonal open water lake temperature
profiles (Minns et al. 2013) were linked to estimate available thermal habitat in a typical stratified Ontario lake that is
subjected to climate warming. Air temperature variables and lake dimensions were key determinants in the models
predicting ice cover and water temperatures. These models were coupled with a range of projected future climates
derived from GCMs and two greenhouse gas emissions scenarios, and used to project future suitable thermal space
availability for selected examples of coldwater, coolwater and warmwater fish common to Ontario lakes.
Parameterization of model components
Spatial units
Secondary watersheds (SWSs) were selected to illustrate the spatial variation in projected future thermal habitat
space conditions for fish in Ontario lakes (Figure 1). The SWSs provided convenient, computationally manageable
areas to model the projected climate and physiographic conditions across Ontario. For simulations of lake thermal
regimes, we assumed the lakes were located at the watershed centroids (Table 1).
1
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CLIMATE CHANGE RESEARCH REPORT CCRR-41
Table 1. The longitude, latitude, and elevation at the centroid of each of Ontario’s secondary
watersheds (SWS) used in the lake thermal regime simulations.
SWS
02A
02B
02C
02D
02E
02F
02G
02H
02J
02K
02L
02M
04A
04B
04C
04D
04E
04F
04G
04H
04J
04K
04L
04M
04N
05P
05Q
05R
Watershed description
Northwestern Lake Superior
Northeastern Lake Superior
Northern Lake Huron
Wanipitai and French
Eastern Georgian Bay
Eastern Lake Huron
Northern Lake Erie
Lake Ontario and Niagara Peninsula
Upper Ottawa
Central Ottawa
Lower Ottawa
Upper St. Lawrence
Hayes
Southwestern Hudson Bay - Coast
Severn
Winisk - Coast
Ekwan - Coast
Attawapiskat - Coast
Upper Albany
Lower Albany - Coast
Kenogami
Moose
Missinaibi-Mattagami
Abitibi
Harricanaw - Coast
Winnipeg
English
Eastern Lake Winnipeg
Long.
°
-88.807
-85.519
-82.406
-80.271
-79.749
-81.479
-81.204
-78.283
-79.945
-77.496
-75.529
-75.657
-92.165
-89.061
-90.908
-87.783
-84.118
-86.710
-88.698
-83.082
-85.432
-81.338
-82.603
-80.778
-79.959
-92.795
-92.639
-94.093
Lat.
°
49.251
48.138
46.442
46.539
45.034
44.328
42.734
44.105
47.361
45.505
45.128
44.712
54.434
56.217
53.912
53.826
54.082
52.376
51.114
51.728
50.074
50.774
48.986
49.142
50.278
49.058
50.298
51.711
Elev
m
294
376
361
244
215
232
210
213
310
391
88
99
271
87
227
143
192
204
335
59
197
33
274
293
270
397
379
362
Figure 1. Boundaries of Ontario’s secondary watersheds and their geographic centroids (black circles).
CLIMATE CHANGE RESEARCH REPORT CCRR-41
3
Fish types and their thermal optima
This study focuses on three fish species representing the main thermal guilds: cold, cool, and warm. Following the
approach of Magnuson et al. (1990) and Christie and Regier (1988), each guild was assigned a 4 °C optimal growth
temperature interval: coldwater – 8-12 °C, coolwater – 16-20 °C, and warmwater – 22-26 °C. In Ontario, typical fish
species of each guild are coldwater lake trout (Salvelinus namaycush), coolwater walleye (or sander) (Sander vitreus),
and warmwater smallmouth bass (Micropterus dolomieu). These species occur widely in Ontario and are highly
valued fishery species.
Choosing a representative lake
To compare estimates of suitable thermal habitat space for selected fish types in lakes among SWS given various
climate conditions, we chose a representative lake to be simulated in each watershed. Minns et al. (2008) estimated
that Canada has about 29,000 lakes with surface areas ranging between 2.0 and 5.0 km2 of which just over 5,000
are deep enough to stratify and support lake trout. Most of these lake trout lakes are located in the boreal and taiga
ecosystems of central and northern Ontario. Lakes of this size range are typically capable of supporting the three
fish types considered here. The Ontario Lake Inventory Database (OLID), compiled mostly between 1960 and 1985,
contains 106 lakes with an area of 3 to 5 km2 and maximum depth of 25 to 35 m (Figure 2; Appendix Table 1). For the
thermal habitat simulations, we chose a representative lake with a surface area of 5 km2 and a maximum depth of 30 m.
Figure 2. A map of Ontario secondary watershed units showing the location of lakes previously inventoried by OMNR with similar area and
maximum depth characteristics to the reference lake used to project thermal habitat space under future projected climates (lakes are identified
in Appendix Table 1)
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CLIMATE CHANGE RESEARCH REPORT CCRR-41
The average of the ratios of mean to maximum depth for the 106 lakes in OLID (Appendix Table 1) was used
to estimate mean depth (9.42 m) in our representative lake. The ratio is a measure of lake basin shape. For our
representative lake, the hypsometric equation of Livingstone and Imboden (1996; equation 3 page 926) was used to
estimate the area (AZ) at any depth (Z):
AZ = A0 [1 – Z/ZMX]q
Where, q = (1-ZMEAN/ZMX)/(ZMEAN/ZMX), and A0 is the surface area of the lake, ZMEAN and ZMX are the mean and maximum lake depths.
Ice date models
Shuter et al. (2013) used historical records of ice dates (break-up and freeze-up) from 44 lake sites across Canada
to develop statistical models for projecting ice break-up and freeze-up dates. These models were validated using
observed ice dates from 2001 to 2003 obtained via remote sensing of 150 of Canada’s large lakes (≥100 km2) using
methods described by Latifovic and Pouliot (2007).
The ice break-up equation (JBU, Table 2) has an intercept and five input variables (coefficients): intercept (481.0),
spring 0 °C date (+0.73048), previous fall 0 °C date (-0.73048), longitude (+0.73145), solar elevation at local noon on
the spring 0 °C date (-3.008), lake surface area (0.0009417) and elevation above sea level (+0.01477). The spring 0
°C date is the day of year when the 31-day running average air temperature rises above the 0 °C threshold. The fall 0
°C date is the day of year when the 31-day running average air temperature falls below the 0 °C threshold.
The ice freeze-up equation (JFU, Table 2) is simpler, with an intercept and three input variables: intercept (58.092),
fall 0 °C date (+0.8303), the square-root of the lake’s mean depth (+7.2925), and mean air temperature for three
months centred on the month in which the fall 0 °C date occurs (+0.9435).
Seasonal temperature-profile model (STM)
Minns and Shuter (2013) developed a semi-mechanistic model (STM) for projecting seasonal temperature profiles
in stratified lakes (Figure 3). The input parameters for STM can be estimated using a combination of lake and climate
variables. To simplify this assessment, we assumed that the temperature at the onset and end of stratification (TN),
the depth of the thermocline (ZTH), and the steepness (S) of the epi- to hypolimnion transition versus depth does
not change as a result of future increased temperatures (Table 2). The peak summer surface temperature (TX*,
Table 2), which occurs on day of year JM, (timing of peak surface temperature) was estimated using the maximum
of values projected by models 1 and 2 in Sharma et al. (2007): Model 1 = -57.88 + 0.79*TJUL + 0.26*TANN + 0.617*JM
– 0.00151*JM2 – 0.019*Longitude and Model 2 = -44.72 + 0.76*TJUL + 0.59*JM – 0.0015*JM2 – 0.019*Longitude –
0.23*Latitude, where TJUL and TANN are mean July and annual air temperatures (°C), respectively.
The seasonal pattern of availability for thermally suitable habitat depends on the position of the preferred
temperature range of each fish relative to the range of temperatures encountered between ice break-up and ice
freeze-up in the lake.
Since the preferred temperature range of coldwater fish (8-12 °C) brackets the temperature at the onset and end
of stratification (TN = 8.66 °C in our representative lake) when the whole lake is isothermal, there are periods in the
spring and fall when the entire lake provides suitable space (Figure 4, lower panel). Once stratification sets in and
the surface temperature (TX) rises above the upper preferred temperature of 12 °C, the proportion of the lake that
is suitable declines to a minimum, representing a thermal bottleneck for coldwater fish. For growth, coldwater fish
species such as lake trout rely heavily on lake-wide foraging in those spring and fall periods and spend much of the
summer confined to limited thermal space with little food. As the climate warms, and the length of the stratification
period increases peak summer surface temperatures rise and the length of the stratification period increases. As a
result, there is a general increase in the amount of suitable thermal space that is available in spring and fall for most
species. However, in the hottest weeks of summer, a thermal bottleneck may develop, where the only thermally
suitable habitat available is found in deep, and often small, thermal refuges. This kind of bottleneck would be the
CLIMATE CHANGE RESEARCH REPORT CCRR-41
5
most severe for coldwater species living in shallow lakes. Accordingly, the depths at which the preferred temperature
range occurs for coldwater fish become greater and therefore, because lake area decreases with increasing depth as
determined by the hypsometric curves, the amount of suitable thermal space decreases.
For warmwater fish such as smallmouth bass, the pattern is different because their preferred temperature range
is more closely aligned with the higher surface temperatures attained in summer (Figure 4b). Suitable thermal space
for warmwater fish is created long after stratification begins, and expands to a peak as surface temperatures and the
preferred temperature range align. With climate warming, surface temperatures will rise and the volume and area of
warmwater fish habitat will increase until the surface temperature exceeds the preferred range, at which time available
space begins decreasing. Optimal coolwater fish habitat occupies the space between coldwater and warmwater fish.
Climate scenarios for ice projections
The Canadian Forest Service (Natural Resources Canada; CFS) maintains a webserver (http://cfs.nrcan.gc.ca/
projects/3) where spatial extrapolation methods have been applied to generate climate values by geographic location,
with allowance for elevation above sea level, from the networks of observational stations and the standard grids used
in global climate models (McKenney et al. 2011). Their results are directly comparable with the climate scenarios
being used by the Ontario Ministry of Natural Resources (OMNR) to assess the potential effects of climate change
on selected natural assets (Colombo et al. 2007). The OMNR has used the 1971 to 2000 observed climate averages
(norms) to represent a baseline condition. We obtained the 1971 to 2000 climate norms data for the centroid location
for each Ontario SWS from the CFS website (Figure 1). For future climates, we extracted the 30-year averages
for three future time periods (2011-2040, 2041-2070, and 2071-2100) for each of two greenhouse gas emissions
scenarios (A2 and B1) from each of four GCMs (for details about the climate models see McKenney et al. 2011):
see below. The A2 scenario anticipates global atmospheric CO2 equivalents reaching 1,320 ppm by 2100 while the
B1 scenario is more conservative and anticipates a level of 915 ppm. The monthly mean minimum and maximum
temperatures at 2 m aboveground were averaged to estimate the monthly daily mean temperatures. For each climate
condition monthly mean daily air temperature data (the average of the mean daily highs and lows) were used, when
possible, to estimate spring and fall 0 °C isotherm dates, along with quarterly and annual mean temperatures.
The climate metrics obtained for the 1971 to 2000 base period and for each GCM-scenario-time period
combination were combined with the thermal habitat space model to project future thermal space for the coldwater,
coolwater, and warmwater thermal guilds.
Overview of thermal habitat space model
Using the parameters in Table 2, the calculation procedure for thermal habitat space is as follows:
1. A spreadsheet containing the climate measures required for projecting aquatic thermal space is prepared
using climate data for the centroid of each SWS obtained from the CFS web-server.
2. The reference lake characteristics (area, mean, and maximum depth) are defined for a lake in each SWS.
3. For each SWS reference lake, climate projections (for each of four GCMs, two emissions scenarios, and three
time periods) are completed and compared to the baseline of observed climate norms for 1971 to 2000.
4. Climate and lake metrics are used to calculate the peak summer surface temperature (TX*); several
parameters are fixed (timing of the peak surface temperature (JM), hypolimnion temperature at the onset of
stratification (TN), thermocline depth (ZTH is a function of ZM and ZJ), and steepness (S) of the temperature
transition with depth from epi- to hypolimnion), and the dates of onset and end of stratification (JS and JE) are
determined from the projected ice break-up and freeze-up dates in combination with other STM parameters.
5. Ice break-up and freeze-up dates are projected using the model of Shuter et al. (2013) with a check for
anomalies such as lack of ice or JFU and JBU occurring in the same calendar year rather than straddling Jan 1st.
6. If no ice cover is projected, the minimum lake surface temperature is assumed to match the minimum mean
monthly air temperature and the transition from one thermal year to the next is assumed to occur at the
midpoint of that minimum month (this option was invoked in a few instances in some of the 2071 to 2100 A2
climate projections).
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CLIMATE CHANGE RESEARCH REPORT CCRR-41
• Canadian Coupled Global Model (CGCM3.1)
• U.S. National Centre for Atmospheric Research Community Climate System Model (NCAR CCSM 3.0)
• Australian Commonwealth Scientific and Industrial Research Oganisation Model (CSIRO 3.5)
• Japanese Model for Interdisciplinary Research on Climate (MIRO C3.2)
7. The spring warming and fall cooling surface temperature rates are computed from JM and JBU or JFU assuming
TX* occurs at JM , JBU at 4 °C and JFU at 0 °C. The surface temperature rates are used to interpolate: (i) the
dates JS and JE when bottom water temperature is at TN; and (ii) the dates in the spring and fall when the
surface temperatures are 4 °C (JS4 and JE4).
9. The STM of Minns et al. (2013) is used to project daily temperature profiles for the lake for the dates JS4 to JE4
inclusively.
10.For each day and species guild, the availability of suitable thermal space is computed as follows:
a. The model determines the depths where the surface and bottom temperatures lay with respect to the fish
type’s upper and lower temperature limits.
b. Where the fish’s temperature limits lie outside the lake’s temperature profile range, only the portion of
the fish type’s temperature range within the lake’s range is considered for calculating suitable thermal
space. When fish limits lay outside the profile range, the upper or lower depth limit is either 0.0 or ZMAX,
respectively.
c. If a limit lies within the profile range, an interpolation function is used to determine the depth at which the
limit occurs, with an accuracy of 0.005 m. This is performed separately to generate upper and lower depth
limits from the temperature limits for each fish type.
d. The depth limits are then applied to the hypsometric function linking area and depth for the lake to
compute both the lake volume and surface area that lie between these two depth limits; these values are
then expressed as proportions of total lake volume and area, respectively.
e. These daily volume and area values are then accumulated, along with a count of the number of days
when the volume/area values exceed zero.
11. Once the calculations for a season are complete, the mean and maximum daily volume and area proportions
for non-zero days are determined and the proportion of the year when suitable space is present is computed.
12.These calculations are iterated for all three fish types across all SWS and climate scenarios.
For each simulation of a single lake, the presence of suitable thermal space for each fish type can be mapped
(Figure 4a). Several thermal indicator metrics can be computed from the daily volume and area of suitable thermal
space: (1) PYear - the percentage of days in the year when the suitable volume and area space values exceed zero,
(2) PVol (or PArea) - the mean daily percentage of total lake volume (or area) occupied by suitable thermal space
on those days when the suitable space exceeds zero (Figure 4b), illustrates how the percent of lake volume that is
suitable varies seasonally), and (3) YVol (or YArea) - the product of PYear and PVol (or PArea) provides a combined
annual measure of the proportion of the lake occupied by suitable thermal space across all days of the year when
suitable space is available. The PVol, PArea, YVol, and YArea measures of suitable thermal space are the same
as those used by Christie and Regier (1988) to predict sustained yield of selected fishery species in lakes. Hence,
those measures are indicators of potential sustainable fishery yield. Additional measures can be derived such as the
standard deviation of the PVol and PArea means, reflecting the seasonal variation in availability of thermal space, and
the thermal space available on the day (JM) when the peak midsummer surface water temperature is attained (JMVol.
and JMArea); this JM measure corresponds to the metric used by Mackenzie-Grieve and Post (2006).
Once the set of calculations were completed, various summaries were prepared. For each SWS, the climate norm
results were subtracted from all of the projected future climate scenario results to estimate the delta changes (∆s) in
the indicator metrics. Then the deltas themselves were summarized, by projected future time period and emissions
scenario, by determining: (i) the minimum and maximum changes across the eight GCM-GHG scenario projections
CLIMATE CHANGE RESEARCH REPORT CCRR-41
used; and (ii) the mid-point of those minimum and maximum values. The norm and delta summary results were used
to create the tables and plots presented in this report. The delta summaries are referred to as the mid-point changes
(the mid-point of the minimum and maximum delta changes across the four GCM projections relative to the 1971
to 2000 baseline norm observations for each emissions scenario) because they reflect an approximate consensus
projection across the eight GCM-GHG scenario projections. All computational procedures were programmed using R
(R Development Core Team 2008).
Figure 3. Diagrams illustrating how the seasonal temperature model operates and how the thermal space values are estimated: (a)
the parameters of the seasonal temperature profile model (see Table 2 for details ), (b) temperature profiles vary through the season
(numbers below temperature axis are selected days of year; ZTH is thermocline depth ), (c) how the temperature limits are projected
onto the depth profile via the temperature profile, and (d) how the depths are integrated with respect to the lake’s hypsometric profile to
obtain habitat volume and area each day.
7
8
CLIMATE CHANGE RESEARCH REPORT CCRR-41
Figure 4. Diagrams illustrating (a) how thermally suitable habitat space is mapped for depth versus day of year and (b) how the percent
of thermally suitable volume varies with day of year.
Table 2. Parameters in models used to predict ice break-up and freeze-up dates and seasonal open water temperature profiles in an
Ontario inland lake. Several parameters are functions of climate variables (f( )).
Parameter
Description
Source
JBU = f()
Day of year when ice break up is completed
Shuter et al. (2013)
JFU = f()
Day of year when ice freeze up is completed
Shuter et al. (2013)
JM = 206.5
Day of year of peak summer surface lake temperature (TX*)
Minns et al. (2013)
TN = 8.66 °C
Temperature of hypolimnion at the onset of stratification; function of lake area
and maximum depth
Minns et al. (2013)
TX* = f( ) °C
Peak summer surface water temperature is the maximum of the Model 1 and
2 estimates in Sharma et al. (2007)
Sharma et al.
(2007)
ZM = 6.135
Maximum thermocline depth (metres)
Minns et al. (2013)
ZJ = 0
Time (days) for thermocline depth to reach half of the maximum thermocline
depth (ZM)
Minns et al. (2013)
S = 4.385
Thermocline steepness coefficient
Minns et al. (2013)
TBU = 4 °C
Surface water temperature at the completion of ice break up
Assumed
TFU = 0 °C
Surface water temperature at the completion of ice freeze up
Assumed
JS = f( )
Day of year of the onset of stratification at TN, estimated here using linear
interpolation from TBU at JBU to TX* at JM
Minns et al. (2013)
JE = f( )
Day of year of the end of stratification at TN, estimated here using linear
interpolation from TX* at JM to TFU at JFU
Minns et al. (2013)
CLIMATE CHANGE RESEARCH REPORT CCRR-41
9
Results and Discussion
Caveats
The first order results obtained here should be interpreted with some caution as they are contingent on the
following assumptions:
•
•
•
•
•
Representative lake: Changing the area and depth dimensions can greatly alter the projection outcomes. For
example, if a deeper lake with similar surface area was considered, the hypolimnion temperature at the onset
of stratification would be much lower; perhaps as low as 4 °C. This would mean that coldwater fish (optimal
growth range 8-12 °C) would be restricted to a thin intermediate depth layer during the summer. Conversely in
a very shallow lake, stratification might not occur and suitable cold and possibly cool thermal space would be
absent during much of the summer.
Lake temperature regime – inshore-offshore variation: The model used here assumes that the temperature
profiles predicted for the centre of the lake represent all areas of the lake. Shallow inshore areas, particularly
those in sheltered areas and downwind of prevailing winds, perhaps with macrophytes present, can become
much warmer during summer as horizontal mixing is incomplete and winds push warmer surface waters
downwind (Finlay et al. 2001). This explains why the present model underestimates the distribution of thermal
habitat suitable for warmwater fish such as smallmouth bass across Ontario (Sharma et al. 2007).
Lake temperature regime – ice events: This version of the model uses simplifying assumptions about the
vertically uniform lake temperature conditions prevailing at the end of ice break-up and the completion of ice
freeze-up. Changes in temperature at these times, and any stratification, may affect the estimation of suitable
thermal space.
Lake temperature regime – stratification constants: This version of the model assumes the depth and
steepness features of stratification are constant. Climate warming may lead to changes in these features and
thereby alter projections of thermal space (Stefan et al. 1998). Thermocline depth is strongly linked to vertical
light extinction in lakes, which in turn is linked with the amount of colour in the water, as indicated by dissolved
organic carbon levels (Perez-Fuentetaja et al. 1999).
Lake ice regime: In some of the warmest future climate projections, the ice model projects a lack of complete
ice cover. This is an issue because the current seasonal temperature profile model requires associated
benchmark dates as inputs.
10
CLIMATE CHANGE RESEARCH REPORT CCRR-41
• Absence of any consideration of biotic interactions: Where thermal space increases are projected, benefits for
target fish types will not necessarily occur. For example, given the projected regional increases in warmwater
fish thermal space, species such as smallmouth bass are expected to invade many lakes and will compete
with existing fish species for food resources. Smallmouth bass invasions threaten lake trout populations
because they reduce littoral forage that is important to lake trout in spring and fall when thermal conditions
allow trout access to littoral habitats (Sharma et al. 2009).
• Inferring yield changes from habitat space changes: Interpretation of the annual space measures (YVol and
YArea) as indicators of potential sustainable yield based on the Christie and Regier (1983) results must
be completed cautiously with regard to projected changes in these measures given climate warming. For
example, even though the projected annual space for coldwater fish such as lake trout may increase, the
increasing mid-summer bottleneck may ultimately determine the potential yield. Overall increases in suitable
thermal space may well lead to increased yields as long as seasonal bottlenecks are absent or unchanged as
is expected for warmwater fish habitat.
Thermal habitat space for fishes
In the projections for our representative lakes based on the 1971 to 2000 climate norms, the regional gradients
of thermal space varied across the three fish types (Table 3). Among the three guild species, the thermal space
measures were highest for coldwater fish but varied less among SWS. PYear values ranged from 0.27 to 0.53, PVol
from 0.51 to 0.77, and PArea from 0.62 to 0.82. The combined year-space measures were lower, ranging from 0.20
to 0.27 and from 0.21 to 0.33 for YVol and YArea, respectively. For the coolwater fish guild, PYear varied from 0.06 to
0.29 except for two watersheds with zero space; non-zero PVol values ranged from 0.27 to 0.46 and non-zero PArea
values ranged from 0.21 to 0.35. The non-zero year–space measures ranged from 0.02 to 0.08 and from 0.02 to 0.06
for YVol and YArea, respectively. For the warmwater fish guild, 17 of 28 watersheds had zero space, indicative of a
latitudinally restricted distribution that is projected to change as temperatures increase. Where warmwater fish habitat
was available, PYear ranged from 0.01 to 0.10, PVol from 0.21 to 0.40, and PArea from 0.15 to 0.29. The non-zero
year-space values ranged from 0.01 to 0.04 and from 0.01 to 0.03 for YVol and YArea, respectively.
Based on the 1971 to 2000 climate norms, the pairs of projected volume and area measures (PVol and PArea, and
YVol and YArea; the indices of potential sustainable fishery yield) across Ontario SWS show similar response patterns
in relation to the proportion of the year with suitable space present (Figure 5). The distinct patterns for the three fish
types arise from their differing preferred temperature ranges relative to the gradient of climate conditions in the recent
past. The coldwater guild shows a declining mean proportion of lake space but some space is present for a larger
portion of the year. The presence of stratification in the representative type lake favours the persistence of suitable
space, although a bottleneck begins to form in midsummer when warmer climates support longer seasons (see
Figure 4b); the midsummer bottleneck is indicated by the suitable thermal space present at midsummer (day of year
JM) (i.e., JMVol and JMArea). The coolwater guild has a higher preferred temperature range that is more closely aligned
with the range of conditions present in Ontario, although stratification restricts the overall supply. Hence, response to
increasing season length peaks as climate in the south begins to generate a bottleneck in summer. The warmwater
guild has the highest preferred temperature range, sitting above what the climate conditions in much of Ontario can
support. Hence, the space and time measures of suitable habitat increase from zero, though with a tendency to
plateau for the space measures. In warmer climates, the warmwater fish guild response pattern is expected to extend
northward resembling the norms response pattern of the coolwater fish guild.
Comparisons between volume and area measures of thermal space also showed that they are highly correlated,
with distinct lines for each fish type based on the relative positions of the thermal preference ranges compared to the
general patterns of the thermal regimes in stratified lakes across Ontario for a fixed lake type. As the P-space and
Y-space habitat supply measures exhibited similar patterns, discussion of further results in this report are confined to
the PYear, YVol, and JMVol measures.
CLIMATE CHANGE RESEARCH REPORT CCRR-41
11
In the climate norms period, both the percentage of the year when suitable space is available and the annual
volume index values for all three fish guilds are partially determined by the duration of open water in the lakes
(Figure 6). The warmwater fish guild has little or no space north of North Bay in the east and Dryden in the west. The
coolwater fish guild has more space, particularly across the central and southern part of northern Ontario, but tapers
towards zero in the Far North of Ontario. The coldwater fish guild has substantial thermal space across Ontario; PYear
ranges from 0.258 to 0.529 and YVol ranges from 0.197 to 0.271 from north to south.
The interpretation of such integral measures of thermal space is complicated by the shifting seasonal patterns of
available suitable space. Taking selected projected seasonal habitat volumes (Figure 7) for the representative lake in
watershed 02E (Eastern Georgian Bay, Figure 1) shows how the shifts in thermal space with climate warming vary
among fish guilds. Under the 1971 to 2000 climate norms, the mean annual air temperature (TANN) is 5.9 °C and the
peak summer surface water temperature (TX*) of 02E is 23.5 °C. Under the A2 emissions scenario, the CGCM3.1
GCM projected TANN and TX* values are respectively 9.1 °C and 26.9 °C in the 2041 to 2070 period, and 10.8 °C and
28.8 °C in the 2071 to 2100 period. Under the 1971 to 2000 climate norms, the thermal space for coldwater fish is
already constricted during much of the stratification period, declining to its lowest volume and area just prior to the
autumn lake turnover (Figure 7, cold). However, the whole lake remains within a suitable temperature range for
coldwater species for extended periods in both spring and fall. With climate warming, periods when the whole lake
is thermally suitable and therefore accessible to coldwater fish occur earlier in the spring and later in the fall, while
during summer the fish are confined to increasingly smaller habitat spaces for longer periods. Thus, for coldwater fish,
increases in annual totals for both the amount of time that thermally suitable space (PVol and PArea) is available, and
the amount of suitable space (YVol and YArea) are projected with climate warming. At the same time, these fish will
be confined to a smaller space for longer periods in mid- to late summer as indicated by the amount of space present
at midsummer (JMVol and JMArea).
For coolwater and warmwater fishes, the total lake space is never completely within their preferred temperature
envelopes (Figure 7, cool and warm). The seasonal coolwater fish habitat space pattern is similar to that of coldwater
fish but truncated in spring and fall; stratification sets in before the preferred temperatures are reached and suitable
space is more limited in spring than fall. The seasonal pattern for warmwater fish begins with a single peak in
midsummer under the 1971 to 2000 climate norms (Figure 7, warm). With climate warming, peak summer surface
temperatures exceed the upper limit preferred by warmwater fish and the same spring-fall peaked pattern projected
for coldwater and coolwater fishes emerges. Further north, the coolwater fish pattern shows a single peak in midsummer under climate norms, which are replaced by spring-fall peaks with climate warming. The warmwater fish
pattern may begin with no space being suitable until climate warming sufficiently raises surface temperatures to the
preferred temperature range. This detailed illustration of how seasonal thermal space patterns change with climate
warming highlights the need to examine more than one measure of change in thermal space; both seasonal integrals
(e.g., YVol and YArea) and bottleneck indicators (e.g., JMVol, JMArea) should be considered.
The mid-points of changes in thermal habitat space measures projected in the eight GCM model-scenarios
provide a consensus indication of the patterns and extent of changes under climate warming. Under the A2 emissions
scenario, the more extreme alternative, the patterns of change in the percent of the year with suitable thermal volume
present (∆PVol) are similar across the three fish groups for the three future time periods (Figure 8) though the change
ranges differ: coldwater fish – 0.025 to 0.190, coolwater fish – 0.030 to 0.180, and warmwater fish – 0.0 to 0.200.
Warmwater fish species are the greatest beneficiaries of climate warming as large areas of Ontario become suitable
relative to the climate norms period. The greater changes for the coldwater and coolwater fish are generally found
north of those for warmwater fish in an area roughly defined by an east-west line from Cochrane to Dryden. The
mid-point changes in the projected annual suitable thermal volume index (∆YVol) reveal more contrast among the
fish guilds (Figure 9). Changes in coldwater fish habitat are fairly evenly distributed while the coolwater fish habitat
increases are concentrated in the Far North. Warmwater fish habitat increases are concentrated in the south for the
first two time periods but reach the far northern reaches of the province by the end of the century.
The projected mid-point changes in the suitable midsummer thermal volume (JMVol) under A2 emissions reveal
more complicated patterns (Figure 10). For coldwater fish, all the habitat changes are negative with a range of -0.09
12
CLIMATE CHANGE RESEARCH REPORT CCRR-41
to -0.01 (Figure 10, cold; note that the colour gradient is reversed in this set of maps to highlight greater decreases
– darker blue). With climate warming coldwater fish are expected to become more thermally constrained in summer.
The coolwater fish habitat changes at mid-summer range from -0.275 to +0.328 (Figure 10, cool). The decreases are
concentrated in the middle north (roughly the area between east-west lines drawn from North Bay to Thunder Bay and
from Cochrane to Sioux Lookout) as rising surface water temperatures exceed coolwater fish thermal preferences
while the greatest increases occur in the far northern reaches of Ontario. The smallest changes mostly occur in
southern areas. The warmwater fish habitat changes at mid-summer range from -0.236 to +0.298 (Figure 10, warm).
The increases begin in the middle north and spread northwards later at similar levels. The uninhabitable areas in
the far north during the 1971 to 2000 and 2011 to 2040 periods (Figure 10, warm – white areas) become thermally
habitable later in the century. The decreases are mostly concentrated in the southern areas with mid-summer surface
water temperatures exceeding the upper preferred limits of even indigenous warmwater fish, which has significant
implications to aquatic biodiversity as the climate warms.
The projected thermal habitat shifts described here for the three thermal fish guilds are consistent with previous
assessments of potential changes in fisheries. Minns and Moore (1992) projected yield declines of coldwater lake
whitefish (Coregonus clupeaformis) across Ontario as the spatial location of peak yields shifts northward. Shuter et al.
(2002) projected regional shifts in the peak coolwater walleye yields as climate warming shifts optimal thermal space
northward. Sharma et al. (2007) projected future shifts in the distribution of warmwater smallmouth bass under climate
change in response to the formation of suitable thermal habitat throughout Ontario.
Table 3. Projected measures of thermal spatial habitat1 for coldwater, coolwater, and warmwater fishes in each reference lake located
in Ontario’s 28 secondary watersheds (SWS) (projections based on the 1971-2000 climate norms).
SWS
02A
02B
02C
02D
02E
02F
02G
02H
02J
02K
02L
02M
04A
04B
04C
04D
04E
04F
04G
04H
04J
04K
04L
04M
04N
05P
05Q
05R
TANN
°C
1.23
1.50
4.13
3.95
5.87
6.88
8.27
6.71
2.72
4.07
6.09
6.54
-2.51
-5.00
-2.23
-2.82
-4.11
-1.68
-0.71
-0.99
0.29
-0.16
1.03
0.53
-0.68
2.50
1.64
0.42
PYear
0.39
0.36
0.43
0.43
0.48
0.50
0.53
0.50
0.40
0.42
0.47
0.49
0.31
0.26
0.32
0.31
0.27
0.33
0.35
0.35
0.37
0.36
0.37
0.36
0.34
0.40
0.38
0.36
Coldwater species
PVol. PArea YVol.
0.60 0.68 0.23
0.65 0.73 0.24
0.56 0.65 0.24
0.55 0.65 0.23
0.54 0.64 0.26
0.54 0.64 0.27
0.51 0.62 0.27
0.53 0.63 0.26
0.57 0.66 0.23
0.56 0.66 0.24
0.53 0.63 0.25
0.52 0.62 0.25
0.64 0.72 0.20
0.76 0.82 0.20
0.63 0.71 0.20
0.67 0.74 0.21
0.77 0.82 0.21
0.63 0.71 0.21
0.61 0.70 0.21
0.63 0.72 0.22
0.60 0.69 0.22
0.62 0.70 0.22
0.60 0.68 0.22
0.61 0.69 0.22
0.63 0.71 0.21
0.56 0.66 0.22
0.57 0.66 0.22
0.58 0.68 0.21
Coolwater species
YArea PYear PVol.
0.26
0.26
0.28
0.28
0.31
0.32
0.33
0.31
0.26
0.28
0.30
0.30
0.22
0.21
0.23
0.23
0.22
0.24
0.24
0.25
0.25
0.26
0.26
0.25
0.24
0.26
0.25
0.25
0.14
0.09
0.19
0.20
0.23
0.24
0.29
0.25
0.17
0.19
0.24
0.25
0.08
0.00
0.09
0.06
0.00
0.09
0.12
0.10
0.13
0.12
0.13
0.12
0.09
0.17
0.16
0.14
0.42
0.42
0.35
0.34
0.32
0.31
0.27
0.30
0.37
0.36
0.30
0.29
0.43
0.00
0.43
0.40
0.00
0.44
0.45
0.44
0.43
0.45
0.44
0.46
0.43
0.36
0.37
0.41
PArea
0.32
0.31
0.27
0.26
0.24
0.24
0.21
0.23
0.28
0.28
0.23
0.22
0.32
0.00
0.33
0.30
0.00
0.33
0.34
0.33
0.33
0.34
0.33
0.35
0.32
0.28
0.29
0.31
Warmwater species
YVol. YArea PYear PVol. PArea YVol. YArea
0.06
0.04
0.07
0.07
0.07
0.08
0.08
0.08
0.06
0.07
0.07
0.07
0.03
0.00
0.04
0.02
0.00
0.04
0.05
0.04
0.06
0.05
0.06
0.06
0.04
0.06
0.06
0.06
0.05
0.03
0.05
0.05
0.06
0.06
0.06
0.06
0.05
0.05
0.06
0.06
0.03
0.00
0.03
0.02
0.00
0.03
0.04
0.03
0.04
0.04
0.04
0.04
0.03
0.05
0.05
0.04
0.00
0.00
0.01
0.02
0.05
0.05
0.10
0.07
0.00
0.01
0.07
0.08
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.25
0.30
0.33
0.34
0.40
0.36
0.00
0.21
0.37
0.38
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.23
0.00
0.00
0.00
0.00
0.18
0.22
0.24
0.25
0.29
0.27
0.00
0.15
0.27
0.28
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.16
0.00
0.00
0.00
0.00
0.00
0.01
0.02
0.02
0.04
0.02
0.00
0.00
0.03
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.01
0.03
0.02
0.00
0.00
0.02
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
TANN – Mean annual air temperature; PYear - the proportion of year when thermal space is non-zero; PVol and PArea - daily mean proportion of thermal space when non-zero; YVol and YArea - the
annual thermal space indices are the product of PYear with PVol and PArea.
1
CLIMATE CHANGE RESEARCH REPORT CCRR-41
Figure 5. Co-variation among thermal habitat supply measures for coldwater (blue), coolwater (green), and warmwater (red) fishes
across Ontario SWSs given the 1971 to 2000 climate norms: The proportion of the year with suitable thermal space present (PYear)
versus daily mean suitable thermal space as a proportion of the lake’s volume or area, (a) volume (PVol) and (b) area (PArea); and the
annual suitable space indices (YVol and YArea equals PYear times PVol and PArea), an index of potential sustainable fishery yield,
versus daily mean suitable thermal space as a proportion of the lake’s volume or area, (a) volume (PVol) and (b) area (PArea).
13
14
CLIMATE CHANGE RESEARCH REPORT CCRR-41
Figure 6. Estimated habitat supply during the 1971 to 2000 norms period: Percent of year (PYear) with suitable thermal
habitat space for (a) coldwater, (b) coolwater, and (c) warmwater fishes and annual volume index (YVol) for (d) coldwater,
(e) coolwater, and (f) warmwater fishes.[Legends show the percentage intervals by colour here and in Figures 8-10.]
Figure 7. Seasonal habitat volumes for a lake in secondary watershed 02E (Eastern Georgian Bay) for coldwater (blue),
coolwater (green), and warmwater (red) fishes during the 1971 to 2000 climate norms (dotted lines) and in response to the
CGCM3.1-A2 climate model-scenario during the 2041 to 2070 period (30-year mean, dashed lines) and during the 2071 to
2100 period (30-year mean, solid lines).
CLIMATE CHANGE RESEARCH REPORT CCRR-41
Figure 8. Mid-point changes in percent of year with suitable thermal space (∆PYear) for coldwater, coolwater, and warmwater
fishes during the 2011 to 2040, 2041 to 2070, and 2071 to 2100 periods relative to the 1971 to 2000 climate norms projected
using the CGCM3.1-A2 climate model-scenario.
15
16
CLIMATE CHANGE RESEARCH REPORT CCRR-41
Figure 9. Mid-point changes in annual volume (∆YVol) for coldwater, coolwater, and warmwater fishes in the 2011 to
2040, 2041 to 2070, and 2071 to 2100 periods relative to the 1971 to 2000 climate norms period projected using the
CGCM3.1-A2 climate model-scenario.
CLIMATE CHANGE RESEARCH REPORT CCRR-41
Figure 10. Mid-point changes in proportion of volume suitable for coldwater, coolwater, and warmwater fishes at midsummer
(∆JMVol) in the 2011 to 2040, 2041 to 2070, and 2071 to 2100 periods relative to the 1971 to 2000 climate norms period
projected using the CGCM3.1-A2 climate model-scenario.
17
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CLIMATE CHANGE RESEARCH REPORT CCRR-41
Conclusions
•
The simple lake ice and temperature profile models used here in conjunction with GCM-based climate
projections suggest that in typical deep stratified Ontario lakes large changes will occur for coldwater,
coolwater, and warmwater fishes.
• Coldwater fish such as lake trout are expected to have greater overall habitat space although the summer
period, when they are thermally confined below the thermocline, will lengthen. Increased food competition
from species expected to benefit from climate warming may result in net productivity losses for lake trout.
• Coolwater fish such as walleye are likely to gain habitat space in the far north of the province, as surface
temperatures increase, and decrease in the south, as summer habitat becomes more thermally confined,
while the spatial peak of potential yield shifts northwards with climate warming.
• Warmwater fish such as smallmouth bass generally will gain more thermally suitable habitat and greater
geographic range as the climate warms.
Recommendation
• Further development of the lake temperature model will be needed to better capture the effects of changing
lake dimensions and climate conditions on the key parameters driving the thermal space projections. A range
of representative lakes should be selected (and if necessary inventoried) to better represent the range of lake
types present across Ontario, with particular attention to the fish species they contain and the water quality
conditions that prevail in them.
CLIMATE CHANGE RESEARCH REPORT CCRR-41
19
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southern Yukon lakes. Can. J. Fish. Aquat. Sci. 63(4): 788–797.
Magnuson, J.J., L.B. Crowder and P.A. Medvick. 1979. Temperature as an ecological resource. Amer. Zool. 19(1): 331-343.
Magnuson, J.J., J.D. Meisner, and D.K. Hill. 1990. Potential changes in the thermal habitat of Great Lakes fish after global climate
warming. Trans. Amer. Fish. Soc. 119(2): 254-264.
McKenney, D.W., M.F. Hutchinson, P. Papadopol, K. Lawrence, J. Pedlar, K. Campbell, E. Milewska, R.F. Hopkinson, D. Price and T.
Owen. 2011. Customized spatial climate models for North America. Bull. Am. Meteorol. Soc. Dec: 1613-1622.
Minns, C.K. and J.E. Moore. 1992. Predicting the impact of climate change on the spatial pattern of freshwater fish yield capability in
eastern Canada. Climatic Change 22: 327-346.
Minns, C.K. and B.J. Shuter. 2013. A semi-mechanistic seasonal temperature profile model (STM) for stratified dimictic lakes. Can. J.
Fish. Aquat. Sci. 70(2): 169-181 (dx.doi.org/10.1139/cjfas-2012-0253).
Minns, C.K., J.E. Moore, B.J.Shuter, and N.E. Mandrak. 2008. A preliminary analysis of some key characteristics of Canadian lakes.
Can. J. Fish. Aquat. Sci. 65:1763-1778.
Perez-Fuentetaja, A., P.J. Dillon, N.D. Yan and D.J. McQueen. 1999. Significance of dissolved organic carbon in the prediction of
thermocline depth in small Canadian Shield lakes. Aquat. Ecol. 33: 127-133.
R Development Core Team. 2008. R: A language and environment for statistical computing. R Foundation for Statistical Computing,
Vienna, Austria. http://www.R-project.org.
Schindler, D.W. 1997. Widespread effects of climate warming on freshwater ecosystems in North America. Hydrol. Processes 11:
1043-1067.
Sharma, S., D.A. Jackson, C.K. Minns and B.J. Shuter. 2007. Will northern fish populations be in hot water because of climate
change? Global Change Biol. 13: 2052-2064.
Sharma, S., D.A. Jackson and C.K. Minns. 2009. Quantifying the effects of climate change and the invasion of smallmouth bass on
native lake trout populations across Canadian lakes. Ecography 32: 517-525.
Shuter, B.J., C.K. Minns and N. Lester. 2002. Climate change, freshwater fish and fisheries: Case studies from Ontario and their
use in assessing potential impacts. Pp. 77-88 in N.A. McGinn, ed. Fisheries in a Changing Climate. American Fisheries Society,
Symposium 32, Bethesda, MD.
Shuter, B.J., C.K. Minns and S.R. Fung. 2013. Empirical models for forecasting changes in the phenology of ice cover for Canadian
lakes. Can. J. Fish. Aquat. Sci. 70(7): 982-991.
Stefan, H.G., X. Fang and M. Hondzo. 1998. Simulated climate change effects on year-round water temperatures in temperate zone
lakes. Climatic Change 40(3-4): 547-576.
20
CLIMATE CHANGE RESEARCH REPORT CCRR-41
Appendix
Appendix Table 1. Lakes with an area of 2 to 5 km2 and maximum depth of 25 to 35 m identified in the Ontario Lake Inventory
Database.
No.
OLIDID
1
L23027
2
L23035
3
L23123
4
L25112
5
L25330
6
L47136
7
L47165
8
L47264
9
L47331
10
L47365
11
L47372
12
L31028
13
L41222
14
L41263
15
L41285
16
L41286
17
L42068
18
L45077
19
L45094
20
L45105
21
L43134
22
L45194
23
L46129
24
L46238
25
L55252
26
L55095
27
L55108
28
L55221
29
L52299
30
L54051
31
L54156
32
L54208
33
L36361
34
L36396
35
L46011
36
L46201
37
L51023
38
L51018
39
L51037
40
L51187
Crescent Lake
Disraeli Lake
Pikitigushi Lake
Hawkeye Lake
Waterhouse Lake
Hambleton Lake (Boot)
Kakakiwibik Lake (Crow)
Montreal River
Sand Lake
Tikamaganda Lake
Tukanee Lake
Burntwood Lake
Mount Lake (Mountain)
Red Rock Lake
Seabrook Lake
Semiwite Lake
Kecil Lake
Geneva Lake
Helen Lake
Johnnie Lake (Bushcamp)
Patterson Lake (Stormy)
Paradise Lake (Alphretta)
Jumping Cariboo Lake
Red Squirrel Lake
Wauquimakog Lake (Wilson)
Horn Lake
Kashegaba Lake
Spider Lake (Cowper)
Wollaston Lake (Eagle)
Crystal Lake
Mountain Lake (Minden)
Twelve Mile Lake
St. Anthony Lake
Wendigo Lake
Banks Lake
Mendelssohn Lake
Biggar Lake
Big Crow Lake
Booth Lake
Lower Hay Lake
2A
2A
2A
2A
2A
2B
2B
2B
2B
2B
2B
2C
2C
2C
2C
2C
2C
2C
2C
2C
2D
2D
2D
2D
2D
2E
2E
2E
2H
2H
2H
2H
2J
2J
2J
2J
2J
2K
2K
2K
50.47
49.12
50.42
48.68
49.90
48.85
48.58
47.23
47.75
47.52
48.63
47.25
46.67
46.32
47.02
46.58
46.27
46.77
47.02
46.10
46.08
46.98
46.88
47.17
45.90
45.67
45.70
45.25
44.85
44.75
44.98
45.02
47.97
47.87
47.48
47.53
45.95
45.82
45.65
45.40
-88.47
-88.12
-88.42
-89.68
-89.90
-85.85
-85.58
-84.23
-84.75
-84.52
-85.63
-83.25
-82.67
-83.32
-83.02
-82.58
-82.27
-81.77
-81.02
-81.10
-79.08
-80.98
-79.88
-80.17
-80.90
-79.67
-80.70
-80.25
-77.85
-78.75
-78.98
-78.02
-79.97
-79.87
-80.48
-80.53
-78.95
-78.82
-78.65
-78.40
41
42
43
44
45
46
47
48
49
50
51
52
Mcintosh Lake
Mckenzie Lake
Merchant Lake
Pen Lake
Shirley Lake
Buckshot Lake (Indian)
Otter Lake (Cotter)
Rieder Lake
Zeemel Lake
Harris Lake
Opichuan Lake
Little Caribou Lake
2K
2K
2K
2K
2K
2K
2K
4A
4D
4G
4G
4G
45.67
45.37
45.77
45.45
45.68
45.00
45.07
54.88
52.57
50.27
51.25
50.37
-78.67
-78.37
-78.77
-78.45
-78.68
-77.00
-77.07
-91.88
-90.57
-90.27
-87.25
-89.37
L51206
L51208
L51210
L51263
L51313
L66032
L66175
L16270
L16359
L16108
L22159
L23080
Lake Name
SWS Latitude Longitude Year
1973
1970
1973
1976
1979
1969
1985
1975
1964
1976
1970
1970
1985
1978
1985
1985
1973
1970
1980
1972
1975
1977
1976
1973
1974
1983
1975
1968
1973
1980
1976
1974
1969
1985
1976
1985
1973
1975
1971
1986
Area
km2
3.105
4.448
3.007
4.358
3.006
3.545
4.236
3.329
3.283
4.388
3.322
3.458
3.464
4.452
4.735
3.043
4.259
3.561
3.42
3.954
3.334
4.874
4.087
3.873
4.733
4.718
4.166
4.805
3.63
4.832
3.194
3.365
4.889
4.683
3.075
4.605
3.815
4.4
4.937
4.199
ZMAX
m
33.6
32.9
25.3
33.6
26.5
25.6
31.7
29.9
29.1
33.6
32
26.2
29.9
26
30.5
33.5
26.2
25.3
26
33.6
28.4
35
33.6
33.6
33.6
34.7
25.9
34.5
31.1
32.9
31.4
27.5
30.5
28
29.3
33.5
32
27.1
29.3
32.3
ZMEAN
m
10
10.6
9.5
11.7
5.5
9.2
6.9
11.6
6.5
13.1
14.6
6.5
8.6
11.5
9
12.4
12.1
6.3
6.5
7.9
10.7
8.2
8.9
11.3
10.4
11.3
8
8.1
9.4
11.2
13.5
12
10.1
9.1
10
10.7
9.7
8.2
7.8
9.3
a.s.l.*
m
310
351
320
458
457
336
404
300
381
427
397
458
358
205
427
366
244
419
396
209
210
314
302
305
206
329
229
183
307
284
306
308
305
213
360
282
373
407
391
408
1975
1970
1985
1968
1971
1969
1976
1978
1982
1977
1984
1973
3.168
3.116
4.116
3.786
4.809
4.393
3.056
4.88
3.546
4.194
3.102
3.152
29.6
27.8
32
34.8
26.8
29
29.3
32
30.2
28
27
31.1
7.4
9
8.9
9.2
7.4
9.7
8.6
9.1
6.4
6.4
7.6
7.3
442
406
438
403
401
299
317
145
293
460
265
381
CLIMATE CHANGE RESEARCH REPORT CCRR-41
Appendix Table 1. Cont.
No.
OLIDID
53
L25175
54
L22031
55
L34016
56
L34166
57
L33156
58
L36272
59
L12014
60
L12029
61
L12073
62
L12091
63
L12164
64
L12190
65
L12193
66
L12203
67
L12214
68
L13036
69
L13161
70
L14085
71
L14253
72
L15206
73
L21047
74
L21048
75
L21053
76
L21066
77
L21124
78
L21130
79
L21133
80
L21145
81
L21159
82
L21161
83
L21181
84
L21215
85
L25265
86
L25290
87
L25304
88
L11072
89
L11171
90
L11179
91
L11224
92
L13010
93
L13037
94
L13042
95
L13077
96
L14013
97
L14017
98
L14067
99
L14075
100
L14111
101 L14270
102 L15248
103 L15266
104 L15276
105 L16146
106 L21002
Lake Name
Little Sparkling Lake
Charon Lake
Big Skunk Lake
Linbarr Lake
Marne Lake
Midlothian Lake
Bat Lake
Brooks Lake
Hector Lake
Kaminni Lake
Pickwick Lake
Strong Lake
Sullivan Lake
Vane Lake
Winkle Lake
Dimple Lake
Paddy Lake
Ethelma Lake
Sword Lake
Paull Lake
David Lake
Doan Lake
Fish Lake (E Campus)
French Lake
Little Turtle River (Ne Basin)
Mabel Lake
Marion Lake
Miranda Lake
Old Man Lake
Oriana Lake
Rawn Lake
Trout Lake
Ross Lake
Squeers Lake
Tilly Lake
Ghost Lake
Peak Lake
Portal Lake
Walleye Lake
Barnard Lake
Divided Lake
Eady Lake
Kay Lake
Beauty Lake
Bert Lake
Direct Lake
Dumpy Lake
Havik Lake
Trout Lake
Suffel Lake
Underbrush Lake (Echo)
Washagomis Lake
Kimmewin Lake
Adele Lake
SWS Latitude Longitude Year
4G
4J
4J
4J
4L
4L
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5P
5Q
5Q
5Q
5Q
5Q
5Q
5Q
5Q
5Q
5Q
5Q
5Q
5Q
5Q
5Q
5Q
5Q
5Q
5Q
49.83
49.62
49.60
49.23
47.78
47.92
49.07
49.22
49.32
49.37
49.00
48.97
49.17
48.97
49.02
49.23
49.27
49.70
49.98
50.77
48.38
49.15
49.18
48.67
49.07
49.15
48.68
48.78
49.03
48.58
48.57
48.28
48.37
48.52
48.63
49.83
49.50
50.33
49.48
50.17
50.00
50.12
49.22
50.28
50.05
50.05
50.32
50.12
50.30
50.97
50.88
51.22
50.28
49.18
-90.83
-86.62
-84.60
-85.23
-81.78
-81.92
-93.07
-93.22
-93.32
-92.37
-93.00
-93.97
-93.17
-93.97
-92.02
-91.23
-92.27
-93.70
-94.98
-94.77
-92.38
-91.15
-91.18
-91.67
-91.07
-91.15
-91.68
-91.78
-91.03
-91.58
-91.57
-92.28
-90.37
-90.52
-90.63
-92.83
-92.50
-93.33
-93.48
-90.17
-91.00
-90.12
-91.22
-94.28
-94.05
-94.05
-94.32
-93.12
-94.30
-94.97
-94.88
-92.22
-91.28
-91.18
1982
1980
1969
1985
1986
1985
1976
1979
1979
1977
1970
1974
1976
1974
1970
1978
1978
1975
1975
1985
1977
1976
1974
1969
1976
1974
1973
1978
1976
1971
1973
1985
1980
1974
1980
1985
1974
1973
1979
1983
1979
1977
1977
1976
1985
1978
1976
1972
1983
1974
1979
1976
1973
1978
Area
km2
3.173
3.049
3.225
3.809
3.605
3.673
3.132
4.919
4.684
3.294
4.921
3.505
3.375
3.464
3.82
3.735
4.588
3.872
3.646
4.487
3.335
4.41
3.242
3.019
4.955
4.728
4.366
3.999
4.732
3.901
3.359
3.057
3.12
3.841
4.09
4.61
3.312
4.591
3.043
3.854
4.362
4.605
3.622
3.06
3.136
4.383
3.501
3.911
4.215
3.807
3.987
3.953
4.617
3.338
ZMAX
m
35
30.5
30.2
34.1
30.5
32.3
28.4
34
27
32
31.1
25.3
30.5
29.6
27.5
25
26
33.6
29
30
33
29.6
31
25.9
34.2
25.3
28.1
28
26.5
30.5
30.5
33
26
33.6
31
29
25.3
26.5
25.9
29
25
28.9
29.9
25.9
29.3
28
33.6
29
32.2
27.1
25
28.7
34.8
30.5
ZMEAN
m
9.8
10.8
8.8
5.9
9.5
8.2
7.9
6.3
10.4
7.3
8.2
8.6
9.5
12.8
7.6
12.3
8.1
14.4
8.6
8
13.8
7.2
10.8
12.5
7.6
10.6
7
8.5
13.5
10.4
10
14.3
10.1
11.5
9.5
16
11.8
11.3
9.6
10.2
5.7
7.7
6.9
12.3
11.7
9.6
14.1
11.9
12
9.1
7.9
9.7
8.2
9.9
a.s.l.*
m
434
300
297
366
343
305
381
372
356
375
366
349
357
349
409
424
424
375
366
381
343
442
445
409
441
441
412
419
473
381
408
351
435
488
464
366
424
366
382
403
409
427
440
351
397
339
323
427
327
375
412
384
412
473
21
Climate Change Report Series
CCRR-01 Wotton, M., K. Logan and R. McAlpine. 2005. Climate
Change and the Future Fire Environment in Ontario: Fire Occurrence
and Fire Management Impacts in Ontario Under a Changing Climate.
CCRR-02 Boivin, J., J.-N. Candau, J. Chen, S. Colombo and M. TerMikaelian. 2005. The Ontario Ministry of Natural Resources LargeScale Forest Carbon Project: A Summary.
CCRR-22 Walpole, A and J. Bowman. 2011. Wildlife Vulnerability to
Climate Change: An Assessment for the Lake Simcoe Watershed.
CCRR-23 Evers, A.K., A.M. Gordon, P.A. Gray and W.I. Dunlop. 2012.
Implications of a Potential Range Expansion of Invasive Earthworms in
Ontario’s Forested Ecosystems: A Preliminary Vulnerability Analysis.
CCRR-03 Colombo, S.J., W.C. Parker, N. Luckai, Q. Dang and T.
Cai. 2005. The Effects of Forest Management on Carbon Storage in
Ontario’s Forests.
CCRR-24 Lalonde, R., J. Gleeson, P.A. Gray, A. Douglas, C.
Blakemore and L. Ferguson. 2012. Climate Change Vulnerability
Assessment and Adaptation Options for Ontario’s Clay Belt – A Case
Study.
CCRR-04 Hunt, L.M. and J. Moore. 2006. The Potential Impacts of
Climate Change on Recreational Fishing in Northern Ontario.
CCRR-25 Bowman, J. and C. Sadowski. 2012. Vulnerability of
Furbearers in the Clay Belt to Climate Change.
CCRR-05 Colombo, S.J., D.W. McKenney, K.M. Lawrence and
P.A. Gray. 2007. Climate Change Projections for Ontario: Practical
Information for Policymakers and Planners.
CCRR-26 Rempel, R.S. 2012. Effects of Climate Change on Moose
Populations: A Vulnerability Analysis for the Clay Belt Ecodistrict (3E-1)
in Northeastern Ontario.
CCRR-06 Lemieux, C.J., D.J. Scott, P.A. Gray and R.G. Davis. 2007.
Climate Change and Ontario’s Provincial Parks: Towards an Adaptation
Strategy.
CCRR-27 Minns, C.K., B.J. Shuter and S. Fung. 2012. Regional
Projections of Climate Change Effects on Ice Cover and Open-Water
Duration for Ontario Lakes
CCRR-07 Carter, T., W. Gunter, M. Lazorek and R. Craig. 2007.
Geological Sequestration of Carbon Dioxide: A Technology Review and
Analysis of Opportunities in Ontario.
CCRR-28 Lemieux, C.J., P. A. Gray, D.J. Scott, D.W. McKenney and S.
MacFarlane. 2012. Climate Change and the Lake Simcoe Watershed:
A Vulnerability Assessment of Natural Heritage Areas and Nature-Based
Tourism.
CCRR-08 Browne, S.A. and L.M Hunt. 2007. Climate Change and
Nature-based Tourism, Outdoor Recreation, and Forestry in Ontario:
Potential Effects and Adaptation Strategies.
CCRR-09 Varrin, R. J. Bowman and P.A. Gray. 2007. The Known
and Potential Effects of Climate Change on Biodiversity in Ontario’s
Terrestrial Ecosystems: Case Studies and Recommendations for
Adaptation.
CCRR-11 Dove-Thompson, D. C. Lewis, P.A. Gray, C. Chu and
W. Dunlop. 2011. A Summary of the Effects of Climate Change on
Ontario’s Aquatic Ecosystems.
CCRR-29 Hunt, L.M. and B. Kolman. 2012. Selected Social Implications of
Climate Change for Ontario’s Ecodistrict 3E-1 (The Clay Belt).
CCRR-30 Chu, C. and F. Fischer. 2012. Climate Change Vulnerability
Assessment for Aquatic Ecosystems in the Clay Belt Ecodistrict (3E-1) of
Northeastern Ontario.
CCRR-31 Brinker, S. and C. Jones. 2012. The Vulnerability of Provincially
Rare Species (Species at Risk) to Climate Change in the Lake Simcoe
Watershed, Ontario, Canada
CCRR-12 Colombo, S.J. 2008. Ontario’s Forests and Forestry in a
Changing Climate.
CCRR-32 Parker, W.C., S. J. Colombo and M. Sharma. 2012. An
Assessment of the Vulnerability of Forest Vegetation of Ontario’s Clay Belt
(Ecodistrict 3E-1) to Climate Change.
CCRR-13 Candau, J.-N. and R. Fleming. 2008. Forecasting the
Response to Climate Change of the Major Natural Biotic Disturbance
Regime in Ontario’s Forests: The Spruce Budworm.
CCRR-33 Chen, J, S.J. Colombo, and M.T. Ter-Mikaelian. 2013. Carbon
Stocks and Flows From Harvest to Disposal in Harvested Wood Products
from Ontario and Canada.
CCRR-14 Minns, C.K., B.J. Shuter and J.L. McDermid. 2009.
Regional Projections of Climate Change Effects on Ontario Lake Trout
(Salvelinus namaycush) Populations.
CCRR-34 McLaughlin, J. and K. Webster. 2013. Effects of a Changing
Climate on Peatlands in Permafrost Zones: A Literature Review and
Application to Ontario’s Far North.
CCRR-15 Subedi, N., M. Sharma, and J. Parton. 2009. An Evaluation
of Site Index Models for Young Black Spruce and Jack Pine Plantations
in a Changing Climate.
CCRR-35 Lafleur, B., N.J. Fenton and Y. Bergeron. 2013. The Potential
Effects of Climate Change on the Growth and Development of Forested
Peatlands in the Clay Belt (Ecodistrict 3E-1) of Northeastern Ontario.
CCRR-16 McKenney, D.W., J.H. Pedlar, K. Lawrence, P.A. Gray, S.J.
Colombo and W.J. Crins. 2010. Current and Projected Future Climatic
Conditions for Ecoregions and Selected Natural Heritage Areas in
Ontario.
CCRR-36 Nituch, L. and J. Bowman. 2013. Community-Level Effects of
Climate Change on Ontario’s Terrestrial Biodiversity.
CCRR-17 Hasnain, S.S., C.K. Minns and B.J. Shuter. 2010. Key
Ecological Temperature Metrics for Canadian Freshwater Fishes.
CCRR-37 Douglas, A., C. Lemieux, G. Nielson, P. Gray, V Anderson and
S. MacRitchie. Responding to the Effects of Climate Change in the
Lake Simcoe Watershed:A Pilot Study to Inform Development of an
Adaptation Strategy on a Watershed Basis
CCRR-18 Scoular, M., R. Suffling, D. Matthews, M. Gluck and P. Elkie.
2010. Comparing Various Approaches for Estimating Fire Frequency:
The Case of Quetico Provincial Park.
CCRR-38 Furrer, M., M. Gillis, R. Mussakowski, T. Cowie and T.
Veer.Monitoring Programs Sponsored by the Ontario Ministry of
Natural Resources and their Relevance to Climate Change.
CCRR-19 Eskelin, N., W. C. Parker, S.J. Colombo and P. Lu. 2011.
Assessing Assisted Migration as a Climate Change Adaptation
Strategy for Ontario’s Forests: Project Overview and Bibliography.
CCRR-39 McKechnie, J., J. Chen, D. Vakalis and H. MacLean.
Energy Use and Greenhouse Gas Inventory Model for Harvested
Wood Product Manufacture in Ontario.
CCRR-20 Stocks, B.J. and P.C. Ward. 2011. Climate Change, Carbon
Sequestration, and Forest Fire Protection in the Canadian Boreal
Zone.
CCRR-40 Minns, C.K., Shuter, B.J. and S. R. Fung. 2014. Regional
Projections of Climate Change Effects on Ice Cover and OpenWater Duration for Ontario Lakes Using Updated Ice Date Models.
CCRR-21 Chu, C. 2011. Potential Effects of Climate Change and
Adaptive Strategies for Lake Simcoe and the Wetlands and Streams
within the Watershed.
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(0.2k P.R.,14 04 30)
ISBN 978-1-4606-4037-1 (print)
ISBN 978-1-4606-4038-8 (pdf)