Ministry of Natural Resources and Forestry Science and Regional Projections of Research Climate Change Effects on Thermal Habitat Space for 41 Fishes in Stratified Ontario CLIMATE Lakes CHANGE RESEARCH REPORT CCRR-41

Responding to Climate Change Through Partnership Sustainability in a Changing Climate: An Overview of MNR’s Climate Change Strategy (2011-2014)

Climate change will affect all MNR programs and • Facilitate the development of renewable energy the natural resources for which it has responsibility. by collaborating with other Ministries to promote This strategy confirms MNR’s commitment to the the value of Ontario’s resources as potential green Ontario government’s climate change initiatives such energy sources, making Crown land available as the Go Green Action Plan on Climate Change for renewable energy development, and working and outlines research and management program with proponents to ensure that renewable energy priorities for the 2011-2014 period. developments are consistent with approval requirements and that other Ministry priorities are Theme 1: Understand Climate Change considered. MNR will gather, manage, and share information • Provide leadership and support to resource users and knowledge about how ecosystem composition, and industries to reduce carbon emissions and structure and function – and the people who live and increase carbon storage by undertaking afforestation, work in them – will be affected by a changing climate. protecting natural heritage areas, exploring Strategies: opportunities for forest carbon management • Communicate internally and externally to build to increase carbon uptake, and promoting the awareness of the known and potential impacts increased use of wood products over energy- of climate change and mitigation and adaptation intensive, non-renewable alternatives. options available to Ontarians. • Help resource users and partners participate in a • Monitor and assess ecosystem and resource carbon offset market, by working with our partners conditions to manage for climate change in to ensure that a robust trading system is in place collaboration with other agencies and organizations. based on rules established in Ontario (and potentially • Undertake and support research designed in other jurisdictions), continuing to examine the to improve understanding of climate change, mitigation potential of forest carbon management including improved temperature and precipitation in Ontario, and participating in the development of projections, ecosystem vulnerability assessments, protocols and policies for forest and land-based and improved models of the carbon budget and carbon offset credits. ecosystem processes in the managed forest, the settled landscapes of southern Ontario, and the Theme 3: Help Ontarians Adapt forests and wetlands of the Far North. MNR will provide advice and tools and techniques to • Transfer science and understanding to decision- help Ontarians adapt to climate change. Strategies makers to enhance comprehensive planning and include: management in a rapidly changing climate. • Maintain and enhance emergency management capability to protect life and property during extreme Theme 2: Mitigate Climate Change events such as flooding, drought, blowdown and MNR will reduce greenhouse gas emissions in wildfire. support of Ontario’s greenhouse gas emission • Use scenarios and vulnerability analyses to develop reduction goals. Strategies: and employ adaptive solutions to known and • Continue to reduce emissions from MNR operations emerging issues. though vehicle fleet renewal, converting to other • Encourage and support industries, resource users high fuel efficiency/low-emissions equipment, and communities to adapt, by helping to develop demonstrating leadership in energy-efficient facility understanding and capabilities of partners to adapt development, promoting green building materials their practices and resource use in a changing and fostering a green organizational culture. 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

1 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

2 Department of Ecology and Evolutionary Biology, University of Toronto, 25 Willcocks Street Toronto, ON M5S 3B2

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 © 2014, Queen’s Printer for Ontario Printed in Ontario, Canada

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Cette publication hautement spécialisée, Regional Projections of Climate Change Effects on Ice Cover and Open-Water Duration for Ontario Lakes Using Updated Ice-Date Models n’est disponible qu’en anglais en vertu du Règlement 671/92 qui en exempte l’application de la Loi sur les services en français. Pour obtenir de l’aide en français, veuillez communiquer avec le Ministère des Richesses naturelles et des Forêts au [email protected].

This paper contains recycled materials. 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 iiiv

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 vi CLIMATE CHANGE RESEARCH REPORT CCRR-41 CLIMATE CHANGE RESEARCH REPORT CCRR-41 1

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). 2 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. Long. Lat. Elev SWS Watershed description ° ° m 02A Northwestern Lake Superior -88.807 49.251 294 02B Northeastern Lake Superior -85.519 48.138 376 02C Northern Lake Huron -82.406 46.442 361 02D Wanipitai and French -80.271 46.539 244 02E Eastern Georgian Bay -79.749 45.034 215 02F Eastern Lake Huron -81.479 44.328 232 02G Northern Lake Erie -81.204 42.734 210 02H Lake Ontario and Niagara Peninsula -78.283 44.105 213 02J Upper Ottawa -79.945 47.361 310 02K Central Ottawa -77.496 45.505 391 02L Lower Ottawa -75.529 45.128 88 02M Upper St. Lawrence -75.657 44.712 99 04A Hayes -92.165 54.434 271 04B Southwestern Hudson Bay - Coast -89.061 56.217 87 04C Severn -90.908 53.912 227 04D Winisk - Coast -87.783 53.826 143 04E Ekwan - Coast -84.118 54.082 192 04F Attawapiskat - Coast -86.710 52.376 204 04G Upper Albany -88.698 51.114 335 04H Lower Albany - Coast -83.082 51.728 59 04J Kenogami -85.432 50.074 197 04K Moose -81.338 50.774 33 04L Missinaibi-Mattagami -82.603 48.986 274 04M Abitibi -80.778 49.142 293 04N Harricanaw - Coast -79.959 50.278 270 05P Winnipeg -92.795 49.058 397 05Q English -92.639 50.298 379 05R Eastern Lake Winnipeg -94.093 51.711 362

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) 4 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):

q AZ = A0 [1 – Z/ZMX]

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 2 2 – 0.00151*JM – 0.019*Longitude and Model 2 = -44.72 + 0.76*TJUL + 0.59*JM – 0.0015*JM – 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 st anomalies such as lack of ice or JFU and JBU occurring in the same calendar year rather than straddling Jan 1 . 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). 6 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 7

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. 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)

Temperature of hypolimnion at the onset of stratification; function of lake area T = 8.66 °C Minns et al. (2013) N and maximum depth Peak summer surface water temperature is the maximum of the Model 1 and Sharma et al. T * = f( ) °C X 2 estimates in Sharma et al. (2007) (2007)

ZM = 6.135 Maximum thermocline depth (metres) Minns et al. (2013)

Time (days) for thermocline depth to reach half of the maximum thermocline ZJ = 0 Minns et al. (2013) depth (ZM)

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

Day of year of the onset of stratification at NT , estimated here using linear JS = f( ) * Minns et al. (2013) interpolation from TBU at JBU to TX at JM

Day of year of the end of stratification at TN, estimated here using linear JE = f( ) * Minns et al. (2013) interpolation from TX at JM to TFU at JFU 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 mid- summer 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 TANN Coldwater species Coolwater species Warmwater species °C PYear PVol. PArea YVol. YArea PYear PVol. PArea YVol. YArea PYear PVol. PArea YVol. YArea 02A 1.23 0.39 0.60 0.68 0.23 0.26 0.14 0.42 0.32 0.06 0.05 0.00 0.00 0.00 0.00 0.00 02B 1.50 0.36 0.65 0.73 0.24 0.26 0.09 0.42 0.31 0.04 0.03 0.00 0.00 0.00 0.00 0.00 02C 4.13 0.43 0.56 0.65 0.24 0.28 0.19 0.35 0.27 0.07 0.05 0.01 0.25 0.18 0.00 0.00 02D 3.95 0.43 0.55 0.65 0.23 0.28 0.20 0.34 0.26 0.07 0.05 0.02 0.30 0.22 0.01 0.00 02E 5.87 0.48 0.54 0.64 0.26 0.31 0.23 0.32 0.24 0.07 0.06 0.05 0.33 0.24 0.02 0.01 02F 6.88 0.50 0.54 0.64 0.27 0.32 0.24 0.31 0.24 0.08 0.06 0.05 0.34 0.25 0.02 0.01 02G 8.27 0.53 0.51 0.62 0.27 0.33 0.29 0.27 0.21 0.08 0.06 0.10 0.40 0.29 0.04 0.03 02H 6.71 0.50 0.53 0.63 0.26 0.31 0.25 0.30 0.23 0.08 0.06 0.07 0.36 0.27 0.02 0.02 02J 2.72 0.40 0.57 0.66 0.23 0.26 0.17 0.37 0.28 0.06 0.05 0.00 0.00 0.00 0.00 0.00 02K 4.07 0.42 0.56 0.66 0.24 0.28 0.19 0.36 0.28 0.07 0.05 0.01 0.21 0.15 0.00 0.00 02L 6.09 0.47 0.53 0.63 0.25 0.30 0.24 0.30 0.23 0.07 0.06 0.07 0.37 0.27 0.03 0.02 02M 6.54 0.49 0.52 0.62 0.25 0.30 0.25 0.29 0.22 0.07 0.06 0.08 0.38 0.28 0.03 0.02 04A -2.51 0.31 0.64 0.72 0.20 0.22 0.08 0.43 0.32 0.03 0.03 0.00 0.00 0.00 0.00 0.00 04B -5.00 0.26 0.76 0.82 0.20 0.21 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 04C -2.23 0.32 0.63 0.71 0.20 0.23 0.09 0.43 0.33 0.04 0.03 0.00 0.00 0.00 0.00 0.00 04D -2.82 0.31 0.67 0.74 0.21 0.23 0.06 0.40 0.30 0.02 0.02 0.00 0.00 0.00 0.00 0.00 04E -4.11 0.27 0.77 0.82 0.21 0.22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 04F -1.68 0.33 0.63 0.71 0.21 0.24 0.09 0.44 0.33 0.04 0.03 0.00 0.00 0.00 0.00 0.00 04G -0.71 0.35 0.61 0.70 0.21 0.24 0.12 0.45 0.34 0.05 0.04 0.00 0.00 0.00 0.00 0.00 04H -0.99 0.35 0.63 0.72 0.22 0.25 0.10 0.44 0.33 0.04 0.03 0.00 0.00 0.00 0.00 0.00 04J 0.29 0.37 0.60 0.69 0.22 0.25 0.13 0.43 0.33 0.06 0.04 0.00 0.00 0.00 0.00 0.00 04K -0.16 0.36 0.62 0.70 0.22 0.26 0.12 0.45 0.34 0.05 0.04 0.00 0.00 0.00 0.00 0.00 04L 1.03 0.37 0.60 0.68 0.22 0.26 0.13 0.44 0.33 0.06 0.04 0.00 0.00 0.00 0.00 0.00 04M 0.53 0.36 0.61 0.69 0.22 0.25 0.12 0.46 0.35 0.06 0.04 0.00 0.00 0.00 0.00 0.00 04N -0.68 0.34 0.63 0.71 0.21 0.24 0.09 0.43 0.32 0.04 0.03 0.00 0.00 0.00 0.00 0.00 05P 2.50 0.40 0.56 0.66 0.22 0.26 0.17 0.36 0.28 0.06 0.05 0.01 0.23 0.16 0.00 0.00 05Q 1.64 0.38 0.57 0.66 0.22 0.25 0.16 0.37 0.29 0.06 0.05 0.00 0.00 0.00 0.00 0.00 05R 0.42 0.36 0.58 0.68 0.21 0.25 0.14 0.41 0.31 0.06 0.04 0.00 0.00 0.00 0.00 0.00 1 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. CLIMATE CHANGE RESEARCH REPORT CCRR-41 13

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). 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 15

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. 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 17

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. 18 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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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. SWS Latitude Longitude Year Area Z Z a.s.l.* Lake Name MAX MEAN OLIDID km2 m m m 1 L23027 Crescent Lake 2A 50.47 -88.47 1973 3.105 33.6 10 310 2 L23035 Disraeli Lake 2A 49.12 -88.12 1970 4.448 32.9 10.6 351 3 L23123 Pikitigushi Lake 2A 50.42 -88.42 1973 3.007 25.3 9.5 320 4 L25112 Hawkeye Lake 2A 48.68 -89.68 1976 4.358 33.6 11.7 458 5 L25330 Waterhouse Lake 2A 49.90 -89.90 1979 3.006 26.5 5.5 457 6 L47136 Hambleton Lake (Boot) 2B 48.85 -85.85 1969 3.545 25.6 9.2 336 7 L47165 Kakakiwibik Lake (Crow) 2B 48.58 -85.58 1985 4.236 31.7 6.9 404 8 L47264 Montreal River 2B 47.23 -84.23 1975 3.329 29.9 11.6 300 9 L47331 Sand Lake 2B 47.75 -84.75 1964 3.283 29.1 6.5 381 10 L47365 Tikamaganda Lake 2B 47.52 -84.52 1976 4.388 33.6 13.1 427 11 L47372 Tukanee Lake 2B 48.63 -85.63 1970 3.322 32 14.6 397 12 L31028 Burntwood Lake 2C 47.25 -83.25 1970 3.458 26.2 6.5 458 13 L41222 Mount Lake (Mountain) 2C 46.67 -82.67 1985 3.464 29.9 8.6 358 14 L41263 Red Rock Lake 2C 46.32 -83.32 1978 4.452 26 11.5 205 15 L41285 Seabrook Lake 2C 47.02 -83.02 1985 4.735 30.5 9 427 16 L41286 Semiwite Lake 2C 46.58 -82.58 1985 3.043 33.5 12.4 366 17 L42068 Kecil Lake 2C 46.27 -82.27 1973 4.259 26.2 12.1 244 18 L45077 Geneva Lake 2C 46.77 -81.77 1970 3.561 25.3 6.3 419 19 L45094 Helen Lake 2C 47.02 -81.02 1980 3.42 26 6.5 396 20 L45105 Johnnie Lake (Bushcamp) 2C 46.10 -81.10 1972 3.954 33.6 7.9 209 21 L43134 Patterson Lake (Stormy) 2D 46.08 -79.08 1975 3.334 28.4 10.7 210 22 L45194 Paradise Lake (Alphretta) 2D 46.98 -80.98 1977 4.874 35 8.2 314 23 L46129 Jumping Cariboo Lake 2D 46.88 -79.88 1976 4.087 33.6 8.9 302 24 L46238 Red Squirrel Lake 2D 47.17 -80.17 1973 3.873 33.6 11.3 305 25 L55252 Wauquimakog Lake (Wilson) 2D 45.90 -80.90 1974 4.733 33.6 10.4 206 26 L55095 Horn Lake 2E 45.67 -79.67 1983 4.718 34.7 11.3 329 27 L55108 Kashegaba Lake 2E 45.70 -80.70 1975 4.166 25.9 8 229 28 L55221 Spider Lake (Cowper) 2E 45.25 -80.25 1968 4.805 34.5 8.1 183 29 L52299 Wollaston Lake (Eagle) 2H 44.85 -77.85 1973 3.63 31.1 9.4 307 30 L54051 Crystal Lake 2H 44.75 -78.75 1980 4.832 32.9 11.2 284 31 L54156 Mountain Lake (Minden) 2H 44.98 -78.98 1976 3.194 31.4 13.5 306 32 L54208 Twelve Mile Lake 2H 45.02 -78.02 1974 3.365 27.5 12 308 *Altitude above mean sea level. 33 L36361 St. Anthony Lake 2J 47.97 -79.97 1969 4.889 30.5 10.1 305 34 L36396 Wendigo Lake 2J 47.87 -79.87 1985 4.683 28 9.1 213 35 L46011 Banks Lake 2J 47.48 -80.48 1976 3.075 29.3 10 360 36 L46201 Mendelssohn Lake 2J 47.53 -80.53 1985 4.605 33.5 10.7 282 37 L51023 Biggar Lake 2J 45.95 -78.95 1973 3.815 32 9.7 373 38 L51018 Big Crow Lake 2K 45.82 -78.82 1975 4.4 27.1 8.2 407 39 L51037 Booth Lake 2K 45.65 -78.65 1971 4.937 29.3 7.8 391 40 L51187 Lower Hay Lake 2K 45.40 -78.40 1986 4.199 32.3 9.3 408 41 L51206 Mcintosh Lake 2K 45.67 -78.67 1975 3.168 29.6 7.4 442 42 L51208 Mckenzie Lake 2K 45.37 -78.37 1970 3.116 27.8 9 406 43 L51210 Merchant Lake 2K 45.77 -78.77 1985 4.116 32 8.9 438 44 L51263 Pen Lake 2K 45.45 -78.45 1968 3.786 34.8 9.2 403 45 L51313 Shirley Lake 2K 45.68 -78.68 1971 4.809 26.8 7.4 401 46 L66032 Buckshot Lake (Indian) 2K 45.00 -77.00 1969 4.393 29 9.7 299 47 L66175 Otter Lake (Cotter) 2K 45.07 -77.07 1976 3.056 29.3 8.6 317 48 L16270 Rieder Lake 4A 54.88 -91.88 1978 4.88 32 9.1 145 49 L16359 Zeemel Lake 4D 52.57 -90.57 1982 3.546 30.2 6.4 293 50 L16108 Harris Lake 4G 50.27 -90.27 1977 4.194 28 6.4 460 51 L22159 Opichuan Lake 4G 51.25 -87.25 1984 3.102 27 7.6 265 52 L23080 Little Caribou Lake 4G 50.37 -89.37 1973 3.152 31.1 7.3 381 CLIMATE CHANGE RESEARCH REPORT CCRR-41 21

Appendix Table 1. Cont. No. SWS Latitude Longitude Year Area Z Z a.s.l.* Lake Name MAX MEAN OLIDID km2 m m m 53 L25175 Little Sparkling Lake 4G 49.83 -90.83 1982 3.173 35 9.8 434 54 L22031 Charon Lake 4J 49.62 -86.62 1980 3.049 30.5 10.8 300 55 L34016 Big Skunk Lake 4J 49.60 -84.60 1969 3.225 30.2 8.8 297 56 L34166 Linbarr Lake 4J 49.23 -85.23 1985 3.809 34.1 5.9 366 57 L33156 Marne Lake 4L 47.78 -81.78 1986 3.605 30.5 9.5 343 58 L36272 Midlothian Lake 4L 47.92 -81.92 1985 3.673 32.3 8.2 305 59 L12014 Bat Lake 5P 49.07 -93.07 1976 3.132 28.4 7.9 381 60 L12029 Brooks Lake 5P 49.22 -93.22 1979 4.919 34 6.3 372 61 L12073 Hector Lake 5P 49.32 -93.32 1979 4.684 27 10.4 356 62 L12091 Kaminni Lake 5P 49.37 -92.37 1977 3.294 32 7.3 375 63 L12164 Pickwick Lake 5P 49.00 -93.00 1970 4.921 31.1 8.2 366 64 L12190 Strong Lake 5P 48.97 -93.97 1974 3.505 25.3 8.6 349 65 L12193 Sullivan Lake 5P 49.17 -93.17 1976 3.375 30.5 9.5 357 66 L12203 Vane Lake 5P 48.97 -93.97 1974 3.464 29.6 12.8 349 67 L12214 Winkle Lake 5P 49.02 -92.02 1970 3.82 27.5 7.6 409 68 L13036 Dimple Lake 5P 49.23 -91.23 1978 3.735 25 12.3 424 69 L13161 Paddy Lake 5P 49.27 -92.27 1978 4.588 26 8.1 424 70 L14085 Ethelma Lake 5P 49.70 -93.70 1975 3.872 33.6 14.4 375 71 L14253 Sword Lake 5P 49.98 -94.98 1975 3.646 29 8.6 366 72 L15206 Paull Lake 5P 50.77 -94.77 1985 4.487 30 8 381 73 L21047 David Lake 5P 48.38 -92.38 1977 3.335 33 13.8 343 74 L21048 Doan Lake 5P 49.15 -91.15 1976 4.41 29.6 7.2 442 75 L21053 Fish Lake (E Campus) 5P 49.18 -91.18 1974 3.242 31 10.8 445 76 L21066 French Lake 5P 48.67 -91.67 1969 3.019 25.9 12.5 409 77 L21124 Little Turtle River (Ne Basin) 5P 49.07 -91.07 1976 4.955 34.2 7.6 441 78 L21130 Mabel Lake 5P 49.15 -91.15 1974 4.728 25.3 10.6 441 79 L21133 Marion Lake 5P 48.68 -91.68 1973 4.366 28.1 7 412 80 L21145 Miranda Lake 5P 48.78 -91.78 1978 3.999 28 8.5 419 81 L21159 Old Man Lake 5P 49.03 -91.03 1976 4.732 26.5 13.5 473 82 L21161 Oriana Lake 5P 48.58 -91.58 1971 3.901 30.5 10.4 381 83 L21181 Rawn Lake 5P 48.57 -91.57 1973 3.359 30.5 10 408 84 L21215 Trout Lake 5P 48.28 -92.28 1985 3.057 33 14.3 351 85 L25265 Ross Lake 5P 48.37 -90.37 1980 3.12 26 10.1 435 86 L25290 Squeers Lake 5P 48.52 -90.52 1974 3.841 33.6 11.5 488 87 L25304 Tilly Lake 5P 48.63 -90.63 1980 4.09 31 9.5 464 88 L11072 Ghost Lake 5Q 49.83 -92.83 1985 4.61 29 16 366 89 L11171 Peak Lake 5Q 49.50 -92.50 1974 3.312 25.3 11.8 424 90 L11179 Portal Lake 5Q 50.33 -93.33 1973 4.591 26.5 11.3 366 91 L11224 Walleye Lake 5Q 49.48 -93.48 1979 3.043 25.9 9.6 382 92 L13010 Barnard Lake 5Q 50.17 -90.17 1983 3.854 29 10.2 403 93 L13037 Divided Lake 5Q 50.00 -91.00 1979 4.362 25 5.7 409 94 L13042 Eady Lake 5Q 50.12 -90.12 1977 4.605 28.9 7.7 427 95 L13077 Kay Lake 5Q 49.22 -91.22 1977 3.622 29.9 6.9 440 96 L14013 Beauty Lake 5Q 50.28 -94.28 1976 3.06 25.9 12.3 351 97 L14017 Bert Lake 5Q 50.05 -94.05 1985 3.136 29.3 11.7 397 98 L14067 Direct Lake 5Q 50.05 -94.05 1978 4.383 28 9.6 339 99 L14075 Dumpy Lake 5Q 50.32 -94.32 1976 3.501 33.6 14.1 323 100 L14111 Havik Lake 5Q 50.12 -93.12 1972 3.911 29 11.9 427 101 L14270 Trout Lake 5Q 50.30 -94.30 1983 4.215 32.2 12 327 102 L15248 Suffel Lake 5Q 50.97 -94.97 1974 3.807 27.1 9.1 375 103 L15266 Underbrush Lake (Echo) 5Q 50.88 -94.88 1979 3.987 25 7.9 412 104 L15276 Washagomis Lake 5Q 51.22 -92.22 1976 3.953 28.7 9.7 384 105 L16146 Kimmewin Lake 5Q 50.28 -91.28 1973 4.617 34.8 8.2 412 106 L21002 Adele Lake 5Q 49.18 -91.18 1978 3.338 30.5 9.9 473

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