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Ministry of Natural Resources and Forestry Science and Research 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 development, promoting green building materials 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 energy sources, making Crown land available 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 increase carbon storage by undertaking afforestation, protecting natural heritage areas, exploring opportunities for forest carbon management 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 protocols and policies for forest and land-based 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 © 2014, Queen’s Printer for Ontario Printed in Ontario, Canada To request copies of this publication: [email protected] 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 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 v iii vi 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 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. 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) 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): 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). 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 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 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 References Christie, G. C. and H. A. Regier. 1988. Measures of optimal thermal habitat and their relationship to yields for four commercial fish species. Can. J. Fish. Aquat. Sci. 45(2): 301-314. 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. Ont. Min. Nat. Resour., Appl. Res. Devel. Br., Sault Ste. Marie, ON. Climate Change Res. Rep. CCRR-05. 37p + CD-ROM. Finlay, K.P., H. Cyr and B.J Shuter. 2001. Spatial and temporal variability in water temperature in the littoral zone of a multi-basin lake. Can. J. Fish. Aquat. Sci. 58: 609-619. Latifovic, R. and D. Pouliot. 2007. 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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. 62836 (0.2k P.R.,14 04 30) ISBN 978-1-4606-4037-1 (print) ISBN 978-1-4606-4038-8 (pdf)