Mingelbier, Brodeur & Morin. (28). Spatially explicit model predicting the spawning habitat and Hydrobiologia 61(1) : 55-69 1 Spatially explicit model predicting the spawning habitat and early stage mortality of Northern pike (Esox lucius) in a large system: the St. Lawrence River between 196 and 2 Marc Mingelbier, Philippe Brodeur and Jean Morin ABSTRACT Discharge fluctuations in the St. Lawrence River (Canada) affect reproduction habitat for Northern pike (Esox lucius). We developed a spatially explicit model for that large-scale river system to predict spawning habitat surfaces available for egg deposition and the potential mortality by dewatering occurring during the embryonic-larval stages. The spatial model used simulated current velocity, wetland type and water temperature at a high spatial resolution over the entire fluvial St. Lawrence River. Those three variables were integrated into a habitat suitability index (HSI) and weighted according to the literature. A new thermal preferendum curve, based on a field experiment, was included in the HSI, reflecting that the probability of observing pike spawners in a given area increased with temperature. The reproduction chronology was predicted every year with an original model based on air temperature in order to reconstitute the historic habitat surfaces for the period 196-2. The results revealed that discharge had a substantial effect on both suitable habitat for egg deposition and potential mortality following dewatering. The best and the largest spawning habitats were identified, as well as the most limiting regions in the river. The present findings have already been used to prepare a new discharge regulation plan for the Lake Ontario-St. Lawrence River system. Keywords Northern pike (Esox lucius) Spatial habitat modelling Reproduction Early life stage mortality Flow regulation Temperature Guest editors : J. M. Farrell, C. Skov, M. Mingelbier, T. Margenau & J. E. Cooper International Pike Symposium : Merging Knowledge of Ecology, Biology, and Management for a Circumpolar Species M. Mingelbier P. Brodeur Ministère des ressources naturelles et de la faune du Québec, Direction de la recherche sur la faune, 88 chemin Ste-Foy, 2 e étage, Québec, G1S 4X4 marc.mingelbier@mrnf.gouv.qc.ca philippe.brodeur@mrnf.gouv.qc.ca J. Morin Meteorological Service of Canada, Environment Canada, 1141 route de l Église, Québec, Québec, G1V 4H5 jean.morin@ec.gc.ca INTRODUCTION Fish species using shallow, low-velocity waters, such as the Northern pike, are particularly sensitive to changes in discharge and water level that influence habitat supply in large river systems. The habitat requirements of the Northern pike have received particular attention because of its ecological and economical importance. Several authors have described and ranked the critical habitat needs of this particular species (Casselman & Lewis 1996), quantified them through habitat suitability indices (Inskip 1982, Anderson 1992), and simulated some effects of habitat supply on pike population dynamics and production (Minns et al. 1996, Farrell et al. 26). Some studies indicate that water temperature controls the spatial distribution of pike eggs and affects fish production (Farrell et al. 1996, Farrell et al. 26), but temperature has never been included in spatially explicit fish models. Since the Northern pike spawns during the spring flood, which is particularly altered in regulated systems (Petts and Calow 1996), this particular species is a relevant indicator for habitat management and protection. High spring discharge connects the river bed with the floodplain and allows access to spawning areas (Fortin et al. 1982, Brodeur et al. 24). Generally, Northern pike spawn in sheltered, shallow water areas over inundated vegetation of wetlands or shorelines (Casselman & Lewis 1996). Pike recruitment is positively influenced by the abundance and quality of the spawning habitat, a high water temperature, and a high water level maintained for several weeks after egg deposition (Johnson 1957, Casselman & Lewis 1996). Sudden dewatering in the spring, during the first life stages, can potentially lead to high mortality when the embryos and larvae are dewatered (Dumont & Fortin 1977, Fortin et al. 1982). Modelling reproduction habitat forces a consideration of potential mortality events occurring at different life stages. Habitat is an essential integrative foundation upon which fish populations thrive and fisheries prosper (Minns et al. 1996). It is therefore crucial to understand and quantify the effects of habitat supply on fish populations and to protect the habitats of different critical life stages from numerous anthropogenic pressures (Inskip 1982, Lewis et al. 1996). Instream Flow Incremental Methodology (IFIM) has led to a greater understanding of the relations between stream flow and aquatic habitats, combining fish habitat preferenda with
Mingelbier, Brodeur & Morin. (28). Spatially explicit model predicting the spawning habitat and Hydrobiologia 61(1) : 55-69 2 hydrodynamical modelling (e.g., Stalnaker 1979, Bovee 1982, Souchon et al. 1989). To date, many spatial evaluations of fish habitats have been conducted for salmonids in small stream portions (e.g., Boudreau et al. 1996, Leclerc et al. 1996, Lamouroux et al. 1998, Guay et al. 2). A few studies have focused on lentic species such as the Northern pike (Esox lucius) in specific embayments (Minns et al. 1996, Anderson 1992), or restricted areas of large rivers (Farrell et al. 1996, Farrell 21), but not over large spatial scales. In the present study, we developed a spatially explicit model for the St. Lawrence River to predict the Northern pike spawning habitat surfaces available for egg deposition and the potential mortality by dewatering during the embryonic-larval stages. The description of the spawning habitat includes a new thermal preferendum curve for pike spawners, based on a field experiment. The model was used to quantify the effect of a wide spectrum of discharge and level on Northern pike spawning habitat and on potential embryonic-larval mortality. We compared sensitivity to discharge variation among four hydrographically contrasted regions of the St. Lawrence River, and predicted the annual spawning habitat surfaces between 196 and 2. The reproduction chronology, needed to compute the historical habitat surfaces, was reconstructed for every year with an original model based on recorded air temperature. MATERIAL AND METHODS Study area The St. Lawrence River (Canada), which flows from the Great Lakes to the Atlantic Ocean, is one of the largest rivers in North America (Fig. 1). It is inhabited by as many as 1 freshwater fish species and contains ~25 km 2 of aquatic habitats (La Violette et al. 23). In the present study, we focused on the fluvial corridor of the river, between Cornwall and Trois-Rivières, where the daily tide is much reduced and does not mask seasonal variations in water level or those induced by discharge regulation (Fig. 1). Figure 1 Study area: four hydrographical regions in the fluvial St. Lawrence Lake St. François was excluded from the study area since its water level is extremely regulated (annual variation <2 cm), and the region between the Lachine Rapids and La Prairie basin was not covered. Given the high physical and biological heterogeneity of the river system, the study area was divided into four different hydrographical regions: two fluvial lakes (Lake St. Louis and Lake St. Pierre), one lotic corridor between Montréal and Sorel, and the Sorel Archipelago (Fig. 1; Mingelbier & Morin 23). The St. Lawrence floodplain includes thousands of hectares of riparian wetlands suitable for Northern pike reproduction. Most of them are still natural, but some have been created with dykes and managed since the 198s to compensate for wildfowl habitat losses ( 4 ha). The managed marshes used by pike cover approximately 15 ha in the fluvial St. Lawrence (Brodeur et al. 24). In the spring time, their flood duration is extended and their water level stabilized. The resulting stable level for approximately four weeks after the spring flood also benefits fish since it protects embryo and larvae from drying out due to dewatering and enhances their growth by increasing warming of water. These flood characteristics are typical of pristine conditions, before discharge regulation (Morin & Bouchard 2). The managed marsh at Rivière aux Pins (45º38'N, 72º26'W; 15 ha; Fig. 1), a small tributary of the St. Lawrence River, was investigated to measure the thermal preferendum of pike spawners. The vegetation in this specific marsh, which is typical of Northern pike spawning habitat in the St. Lawrence River, is mainly composed of wet meadows mixed with shallow and deep marshes (Turgeon et al. 24). Spatially explicit modelling The discharge regulation plan of the Lake Ontario-St. Lawrence River system was revised by the International Joint Commission in 2. This provided an opportunity to develop a physical habitat model with high spatial resolution over the entire fluvial St. Lawrence (Morin et al. 23, Morin et al. 25). This physical model is based on field observations combined with the numerical modelling of key physical variables. Using detailed maps of the topography and substratum of the floodplain and riverbed, we modelled the hydrodynamics on a high resolution finite element mesh for several discharge scenarios. Hydrodynamics was then used to simulate water depth, water temperature and light penetration. All physical variables were supported on a grid containing 16, square units with an average size of 8 m by 8 m, which covers the entire floodplain of the river from Lake St. Louis to Trois-Rivières. This grid supported both physical information and several biological models, such as wetland classes and the current Northern pike model. The detailed methodology about the physical model is available in Morin et al. (25) and references therein.
Mingelbier, Brodeur & Morin. (28). Spatially explicit model predicting the spawning habitat and Hydrobiologia 61(1) : 55-69 3 To estimate the spawning habitat quality of Northern pike, we developed a habitat suitability index (HSI, see below) based on their specific habitat requirements, described in the literature. The HSI values, calculated in each square unit of the physical model, were mapped to represent the quality of accessible surfaces for egg deposition during the maximum spawning period. The HSI values (-1) were estimated for eight reference spring discharge -1 scenarios of between 5 and 2 5 m 3 s as estimated at Sorel. The mean discharge during spring time is 12 5 m 3 s -1 and we presented the model with the three following scenarios: 14 5 m 3 s -1 (observed -1 in 1998), 95 m 3 s (observed in 2) and 65 m 3 s -1 (anticipated for future low discharge). The spawning habitat surface (S HSI ) was then calculated as being the sum of the products between the surfaces of the square grid units and the HSI value: S = S (1) HSI Unit HSI Pike spawning where S Unit is the surface of the square unit in the spatial grid and HSI Pike spawning the value obtained for the HSI in eq. 2 (see below). The relationship between S HSI and discharge was then plotted for the four regions and the entire river to test their sensitivity to discharge variations. In addition, a potential mortality index (PMI) was used to measure the spawning habitat surfaces exposed to dewatering during the period when embryo or larvae are vulnerable to drying. The S PMI represents the difference between the S HSI and the surface at the lowest water level recorded during the following four weeks of the embryonic-larval stages, and is calculated as in eq. 1 by replacing HSI with PMI values. We determined that an average of four weeks after the spawning date is necessary for the eggs to incubate and the larvae to reach 2 mm in length. At this size, young larvae are capable of swimming and can thus avoid being trapped in vegetation during dewatering (Fortin et al. 1982). Five PMI reference scenarios were computed, corresponding to the five dewatering situations of -.14 m, -.28 m, -.5 m, -1. m and -3. m at Sorel, for each of the eight reference discharge scenarios, the four regions and all of the St. Lawrence River. The relationship between S PMI (%) and water level decrease observed between 196 and 2 was plotted for the four regions and the entire fluvial St. Lawrence River. The difference between S HSI and S PMI was estimated every year between 196 and 2 to characterize historical variations in pike spawning habitat. Each yearly spawning habitat surface was calculated using the specific discharge value observed at the maximum spawning date, as determined by a spawning chronology model (see below). In the same way, the four-week critical period used for S PMI calculation was adjusted every year using the maximum spawning dates. Habitat suitability index The HSI was inspired by a review of Casselman & Lewis (1996). These authors classified and ranked the key habitat requirements for pike spawning and embryonic-larval development: vegetation type and density, water level, warming exposure, river connectivity and substrate type. In the present study, we selected three key variables to characterize pike spawning habitat, relative to their importance in the literature (e.g., Machniak 1975, Nelson 1978, Inskip 1982, Fortin et al. 1982, Craig & Kipling 1983, Verret & Savignac 1985, Massé et al. 1991, Anderson 1992, Casselman & Lewis 1996, Farrell et al. 1996, Farrell 21, Farrell et al. 26) and to the spatial modelling capacities (Table 1). First, the most important variable refers to the wetland type, with a specific reference to pike avoidance of Typha sp. assemblages. The wetland type, classified for the particular dynamic of the St. Lawrence River (Table 1), is predicted using an independent model described by Turgeon et al. (24). Second, water temperature plays a crucial role in the spawning habitat selection of Northern pike, in that attractive wetlands may be rejected by pike spawners if they are too cold (Morin et al. 24). However, since the water temperature effect on habitat selection was not quantitatively described in the literature, we conducted a specific field experiment to develop an original thermal preferendum in the HSI (see below). Third, current velocity, used to discriminate lentic and lotic environments, was included in the HSI. To avoid habitat overestimation and other biases, the HSI was expressed as the product of the three selected habitat variables rather than their sum, and the variables were weighted using exponents (eq. 2; Leclerc et al. 1995, Vadas and Orth 21). The Northern pike spawning HSI was expressed as: HSI Pike spawning V RV T K RT C RC = (2) where V, T, and C are the potential value of vegetation, temperature and current velocity, and RV, RT, and RC are their respective ranks (Table 1). The rank is the log 1 of the original values proposed by Casselman and Lewis (1996) and K is a constant to scale HSI estimates between and 1 (K = 9). Thermal spawning preferendum We conducted a field experiment in the Rivière aux Pins managed marsh to quantify the pike thermal preferendum during the spawning period and to obtain an operational term in the HSI. The preferendum was quantified by comparing the temperatures available in the spawning grounds with temperatures directly selected by pike. Between April 8 and 27, 24, 174 adult pike were trapped at the entrance of the marsh (Alaska trap, length: 6.2 m; height: 1.3 m; stretched mesh:.2 m) during the spawning migration. From them, 18 individuals (9 males and 9 females; daily n = 4-11), equally distributed between
Mingelbier, Brodeur & Morin. (28). Spatially explicit model predicting the spawning habitat and Hydrobiologia 61(1) : 55-69 4.5 m and.9 m total length, were tagged externally under the dorsal fin using a micro thermograph (IB Bass TM ; 1 g under water; ±.1 C) after being briefly anaesthetized using a clove oil solution (.5%). Each fish was observed for 16 hours before being released into the marsh. No mortality was observed following marking. Between April 16 and May 11, 24, three traps, randomly installed in the marsh, and a fourth, placed at the exit of the marsh (Alaska trap, length: 5.2 m; height: 1.5 m; stretched mesh:.2 m), were visited every day to monitor pike maturity (partial extrusion of gametes). When a tagged pike was captured, the available temperature data were downloaded. All fish were released inside the marsh, 1 m away from the trap. Eight additional thermographs (Minilog-T; Vemco; ±.1ºC) were placed in the marsh to monitor the water temperature in the main stream, the secondary channels and the flooded wet meadows. Following the classification presented in Table 1, those three types of habitat were judged suitable for spawning relative to vegetation and current velocity. The thermographs were protected from direct solar radiation and installed.2 m from the bottom in a water column of.5-1. m. All temperature measurements were recorded every 15 minutes. Temperature records were averaged daily to be consistent with the time scale of the temperature model available for the study area (Morin et al. 24). Data recorded 24 hours before fish catch were eliminated to avoid measuring temperature in the traps. Temperatures recorded by the 18 tagged pike were compared to in situ temperatures measured in the eight potential spawning sites. A simple linear regression between the mean temperature recorded by the tagged pike and that measured in the spawning habitat (mean and maximum values) was used to describe the distribution of pike relative to available temperatures. A covariance analysis (ANCOVA) using the general linear model procedure was used to compare the slope and the intercept to those of a 1:1 relationship. We hypothesized that fish were actively selecting a given temperature when the relationship between the mean temperature measured by tagged fish and the mean values available in the spawning sites significantly differed from the 1:1 relationship. For the modelling needs and since there were daily temperature variations during the spawning season, it was necessary to express the pike thermal preferendum in relative terms at the daily scale. We thus scaled the average daily temperature recorded by each tagged pike by attributing a percentile value (x) relative to the range of daily temperatures available in the spawning habitat. For example, if the daily mean temperature recorded by a single pike was 7 C and the daily range of temperature available in the spawning ground was 4-7 C, the percentile value of this pike was 1. (1%; the percentiles were rescaled between and 1). We then plotted the frequency (y) of these percentiles (classes of.1 values) for all pikes over the complete spawning period, to get a generalized relationship measuring the probability of observing pike spawners in a relative range of temperatures. This relationship was used to represent the thermal term T in the habitat suitability index (eq. 2), after linearly rescaling y between and 3 to meet HSI needs (see Table 1). Statistical analyses were conducted using SYSTAT 1.. Spawning and embryonic-larval stages chronology It was essential to predict the yearly maximum spawning date to enable a calculation of the habitat surface available every year for egg deposition and to determine the period of embryonic-larval stages. The Massé et al. (1991) model, predicting the date of maximum in situ spawning in Rivière aux Pins, was adapted to the present study area. Daily air temperature records at Dorval Airport, located near Montréal, for the period 196-2 (Morin et al. 24) were used as basic data to build the spawning chronology model. Daily mean and maximum temperatures were used to calculate cumulated degreedays above 5 C and 1 C. These variables were related to the maximum in situ spawning dates (when 5% females have spawned) available in the literature. Table 1 Variables and ranks used in the habitat suitability index describing Northern pike spawning habitat. Potential values of each variable are low (), medium (1) or high (3). Variable Rank Potential Description Wetland type 1. Absence 1 Tree swamp or Thypha sp. dominant 3 Deep or shallow marsh or shrub marsh or meadow Potential water temperature.78-3 Probability of observing pike spawners (see eq. 4) Current velocity.22 >2 cm s -1 1 1-2 cm s -1 3 <1 cm s -1
Mingelbier, Brodeur & Morin. (28). Spatially explicit model predicting the spawning habitat and Hydrobiologia 61(1) : 55-69 5 Because water level influences the spawning chronology of Northern pike (Fabricius & Gustafson 1958), the model was built using field data recorded in Rivière aux Pins during a period of high flows in the St. Lawrence (1975-1977), when the access to spawning sites did not delay spawning (Massé et al. 1991). The model was validated using field data recorded between 1974 and 23 in the St. Lawrence River and the nearby Richelieu River (Fortin et al. 1982, Dumont & Fortin 1977, Massé et al. 1991, Mingelbier et al. 25). A simple linear regression was used to establish the relationship between predicted spawning date and observed values. Since there is a delay of only 3-4 days at the two extremes of the study area (Yves Mailhot, MRNF, pers. comm.) and since historic discharge is available on a weekly basis, the same model was applied simultaneously in the four hydrographical regions of the river system. The embryonic-larval stage was determined to last four weeks after the maximum spawning date and was assumed to be constant between years, as suggested by extensive field data collected in the study area (Dumont & Fortin 1977, Massé et al. 1988). During this critical period, dewatering may cause significant mortality, since the young pike (<2 mm) have not gained sufficient mobility and are still located close to the spawning sites. RESULTS Pike spawning and embryonic-larval stage chronology In order to predict annual spawning and embryoniclarval stage chronology for a long historical period, a model was developed using air temperature. In temperate systems, temperature and photoperiod are the main variables triggering fish reproduction (Dabrowski et al. 1996). Only air temperature was considered since photoperiod is constant from year to year in a given area (Vollestad et al. 1986). The best model revealed that maximum spawning occurred when the daily air temperature conditions at Dorval airport met the two following conditions: Condition 1: DD Tmax >5 C 8 C (3a) Condition 2: T max 8 C (3b) where DD corresponded to cumulated degree-days >5 C using maximum daily temperature records and T max to maximum daily temperature. The predicted spawning dates were validated using field data collected during several hydrologically contrasted periods. Predicted dates were close to observed dates with a mean difference of 1.7 ±.2 days (Fig. 2). Pike spawning thermal preferendum Data selected for the analyses were recorded between April 8 and May 4, 24, a period including both spawning site selection and egg deposition (Fig. 3). Predicted spawning date 12 115 11 15 1 95 y =.89 x + 11.73 R 2 =.89 n = 16 95 1 15 11 115 12 Observed spawning date (Julian) Figure 2 Spawning dates predicted every year using equation 3ab compared to field values recorded in the St. Lawrence River and the nearby Richelieu River between 1974 and 23 Temperature ( C) 18 16 14 12 1 8 6 4 2 7 9 11 13 15 17 19 21 23 25 27 29 1 3 Date in April and May Figure 3 Daily water temperature (mean, min. and max.) measured using thermographs attached to Northern pike (black; n=18) and placed in the spawning ground (dashed grey; n=8) of the Rivière aux Pins marsh, fluvial St. Lawrence River, spring 24. Pike observed frequency 1..8.6.4.2...2.4.6.8 1. Field water temperature Figure 4 Frequency of observations of Northern pike as a function of the daily water temperature available on the spawning sites (expressed as a percentile) in the spring of 24, Rivière aux Pins marsh, fluvial St. Lawrence River. Frequency represents the number of individuals observed in a given temperature range over the spawning period. During this period, the daily water temperatures available at the spawning sites exhibited a higher spatial heterogeneity than those collected by the tagged pike (Fig. 3). The slope of the linear relationship between the daily mean water temperature selected by pike and the mean water temperature available in the spawning ground (y = 1.22 x.27; R 2 =.96; p <.1) was significantly higher than 1 (F = 9.83; p =.4; n = 27). There was a significant linear relationship between the daily mean water
Mingelbier, Brodeur & Morin. (28). Spatially explicit model predicting the spawning habitat and Hydrobiologia 61(1) : 55-69 6 temperature selected by pike and maximum water temperature measured in the spawning ground (y = 1.4 x.54; R 2 =.97; p <.1), which did not differ significantly from a 1:1 relationship (F =.51 and.8; p =.479 and.378 for slope and origin respectively; n = 27). It was necessary to generalize the thermal preferendum in relative terms, for the modelling needs and also because the thermal preferendum varied as a function of the range of absolute water temperature values available in the spawning sites. The generalized thermal preferendum can be expressed as follows (R 2 =.99): y = -272.65 x 6 + 639.96 x 5 549.74 x 4 + 219.45 x 3 39.38 x 2 a. + 2.87 x 14 Lake St. Louis (4) where y is the probability of observing pike spawners, expressed as the frequency of pike observations and x, the daily water temperature available in the spawning ground, expressed as a percentile (see methods). Equation 4 was used to represent the thermal term T in the HSI (eq. 2). This polynomial relationship indicates that the probability of observing pike spawners in a given area increased with temperature, independently of its absolute range of values (Fig. 4). The highest probabilities corresponded to percentiles.7-1.. Spawning habitat vs. river discharge To quantify the impact of water supply on spawning habitat availability for Northern pike, the suitable habitat surfaces were estimated for eight reference spring discharge scenarios and illustrated with two recent contrasted years. High discharge had a positive effect on the abundance of spawning habitats in the entire St. Lawrence River, with optimum values reached at flows 17 5 m 3 s -1 (Fig. 5a). There is a high contrast between the four hydrographical regions of the river system in terms of both absolute abundance of spawning sites and their relative response to discharge variation (Fig. 5ab). The largest potential spawning areas are located in Lake St. Pierre and the Sorel Archipelago. The discharge-habitat relationships, expressed in relative values, indicate a rapid rise of habitat availability at low discharge in Lake St. Louis and the Montréal-Sorel regions, followed by a plateau or a decrease of habitat abundance at the most frequently observed spring discharges (95-14 m 3 s -1 ; Fig. 5b). In contrast, the habitats in Lake St. Pierre and the Sorel Archipelago progressively increase with discharge. As revealed by the slope of the discharge-habitat relationship, Lake St. Pierre and the Sorel Archipelago represent the most sensitive regions to discharge variations. The abundance of the highest-quality spawning habitats, as revealed by the spatial representation of HSI values, also increased with discharge (Fig. 6). Hydrological conditions observed during the spring of 1998 and 2 (7136 and 3664 ha respectively; 42% variation) illustrate the high interannual variability in spawning habitat surfaces. We also tested the effect of discharge on interannual wetlands dynamics for the entire St. Lawrence River, which indirectly influences Northern pike spawning habitat. The results (not shown) indicated that this indirect discharge effect is rarely observed (only 1% of the years during 196-2 period) because it mainly occurs at very low spring discharge (up to 77% variation at flow 95 m 3 s -1 ). For the most frequently observed spring discharges, the interannual wetlands dynamics had less impact on Northern pike spawning habitats than the direct influence of discharge on fish access and spawning site properties (maximum effect of 4% and 62% on habitat surfaces, respectively). Spawning habitat (ha) Spawning habitat (%) 12 1 8 6 4 2 1 8 6 4 2 b. Montreal-Sorel Sorel archipelago Lake St. Pierre Total St. Lawrence 4 9 14 19 24 Discharge at Sorel (m 3 s -1 ) Figure 5 Northern pike spawning habitat area (HSI) for eight discharge scenarios measured at Sorel in the four regions and entire fluvial St. Lawrence River. Surfaces were calculated considering spring temperatures and wetland types that are typical of mean climatic and hydrological conditions. Suitable areas are translated into absolute (a) and relative (b) values vs the total potential of a given region Potential mortality vs. discharge and water level To quantify potential mortality caused by dewatering during the embryonic-larval stages, the proportion of the affected spawning habitats was estimated with discharge records for the 196-2 period. Results reveal that habitat losses are frequent, occurring in 68% of analyzed years (Fig. 7). The mean proportion of habitat lost by dewatering corresponds to -25% ± -2%, with a maximum value reaching -56% for the entire St. Lawrence River. During this period, habitat availability is influenced by dewatering at a highly variable degree depending on the annual discharge dynamic after egg deposition and the hydrological region considered (Fig. 7). Once again, the Sorel Archipelago is the region most sensitive to discharge variations due to its particular topography.
Mingelbier, Brodeur & Morin. (28). Spatially explicit model predicting the spawning habitat and Hydrobiologia 61(1) : 55-69 7 Figure 6 Northern pike spawning habitat (S HSI ) available in Lake St. Pierre and the Sorel Archipelago (similar maps for the other regions were not shown) for three discharge scenarios at Sorel: (i) 65 m 3. s -1 as anticipated for the future, (ii) 95 m 3. s -1 as observed in 2 (low) and 14 5 m 3. s -1 as observed in 1998 (high)
Mingelbier, Brodeur & Morin. (28). Spatially explicit model predicting the spawning habitat and Hydrobiologia 61(1) : 55-69 8 Historical habitat reconstitution In order to quantify the interannual variation in habitat access induced by flow, the annual difference between spawning surfaces (S HSI ) and habitat lost by dewatering (S PMI ) was estimated for the period 196-2. The resulting series of S HSI - S PMI habitat surfaces exhibit significant variability over time, induced by discharge variations (Fig. 8). The four regions of the St. Lawrence exhibit varying degrees of sensitivity to discharge variations, at different intensities and sometimes with opposite responses. The historic pattern of water supply has mostly affected habitat availability in the Sorel Archipelago, which is the most sensitive region of the river. Low discharge regime in the mid-196s reduced pike reproduction habitats, while high discharge recorded in the mid-197s opened access to large spawning surfaces. Later in the historic series, the habitat values display a progressive decrease and a higher interannual variability. Discharge (m 3 s -1 ) 17 15 13 11 9 7 12 8 4 6 4 2 Total St. Lawrence Lake St. Louis Habitat loss (%) 1 8 6 4 Lake St. Louis (1) Montreal-Sorel (2) Sorel archipelago (3) Lake St. Pierre (4) Total St. Lawrence (5) 3 5 4 2 1 Habitat surface (ha) 6 4 2 6 4 2 Montreal-Sorel Sorel Archipelago 2..2.4.6.8 1. 1.2 1.4 1.6 1.8 6 Lake St. Pierre Water level decrease at Sorel (m) 4 Figure 7 Habitat loss surface (S PMI ) as a function of the decrease in water level observed at Sorel during Northern pike embryonic-larval stages between 196 and 2 for the four regions and entire fluvial St. Lawrence River 2 196 1965 197 1975 198 1985 199 1995 2 Year Figure 8 Discharge measured at Sorel during Northern pike spawning and habitat surfaces available for reproduction (S HSI - S PMI ) between 196 and 2 in the four regions and entire fluvial St. Lawrence River
Mingelbier, Brodeur & Morin. (28). Spatially explicit model predicting the spawning habitat and Hydrobiologia 61(1) : 55-69 9 DISCUSSION Pike spawning and embryonic-larval stage chronology It was crucial to predict the spawning date with a relatively high degree of precision since it triggers the complete modelling sequence. The mean precision of the selected model using air temperature was less than 2 days. Since the discharge is regulated on a weekly time scale (in fact, a quarter of a month), this level of precision is appropriate (.2 ±.4 quarter of a month) because the margin of error on predicted dates is much lower than the maximum interannual variability in the study area (4 weeks; results not shown). The temperature model predicting spawning time can likely be upscaled to the Great Lakes-St. Lawrence River system and to other types of environments, after validation in the field. Pike spawning thermal preferendum Results suggest that the pike thermal preferendum changed over time, relative to water temperature available in the field, and that pike were systematically and actively selecting the highest temperatures available in the marsh. Since the tagged pikes spent the most time in the warmest water, we assumed they spread their eggs in the warmest spots. This point was corroborated with egg collection in the same marsh (not shown). The thermal preferendum suggests that even if a habitat is suitable with respect to current velocity or vegetation type, its potential for Northern pike spawning also depends on water temperature. Previous authors used water depth, which partially reflects the water temperature effect, as one of the main variables for modelling Northern pike spawning grounds (Inskip 1982, Casselman & Lewis 1996, Minns et al. 1996). A 2D description of water temperature is likely more difficult to model but more efficient to describe habitat, because it integrates other fish habitat variables such as water depth, wind exposure, solar radiation, vegetation cover, and water turbidity (Morin et al. 24). Using 1D temperature, Farrell et al. (26) demonstrated in the upper St. Lawrence River that the temporal progression in Northern pike egg deposition, resulting from thermal differences in spawning locations, regulated the growth season length and thermal condition during nursery. Warm habitats led to earlier spawning and greater year-class strength. The present study, as well as the results of Farrell et al. (26), suggest that a 2D description of water temperature, reflecting differences in habitat quality, should be included in future pike modelling. The field experiment conducted on pike thermal preferendum led to a mathematical function which represents the probability of spawner occurrence in the spawning ground. The generalized thermal potential for spawning can likely be upscaled to the Great Lakes-St. Lawrence River system and perhaps to other types of environments, after field validation. Spawning habitat vs. water flow The present model reveals that discharge fluctuations have a direct and positive effect on both abundance and quality of pike spawning habitats in the entire fluvial St. Lawrence. These results reflect the impact of discharge on both fish access to particular habitats and on the abiotic properties of available spawning sites. It suggests that vegetation, water temperature and current velocity are particularly suitable for spawning when the upper part of the floodplain is being submerged at high discharge. The St. Lawrence River topography mainly explains the high contrast between the four hydrographical regions of the system in terms of both absolute abundance of spawning sites and their relative response to discharge variation. Lake St. Pierre, which is the largest potential spawning area, is a shallow fluvial lake with a mean depth of 3.17 m at mean discharge and a vast floodplain (Frenette et al. 23). The gentle lateral slope combined with a low current velocity and rapid water warming in the spring explain the presence of large spawning areas. The negative part of the relationship in the lotic Montréal- Sorel region is caused by the flooding of numerous islands and littoral wetlands where the current velocity increases and water temperature decreases at high discharge. Since pike can exhibit fidelity to both natal and spawning sites (Miller et al. 21), unfavourable conditions in a given region likely have marked effects on local populations. As suggested by Lewis et al. (1996), our results indicate the prime importance of considering the spatial scale in habitat conservation and restoration programs. The topographical or hydrological differences between the regions of a river should thus be considered when making management and restoration decisions. The St. Lawrence River experience suggests that discharge should be managed, prioritizing the Sorel Archipelago and Lake St. Pierre, which are the most sensitive and show the greatest abundance of spawning sites. There is also an effect of discharge on interannual wetland dynamics in the entire St. Lawrence River, which indirectly influences Northern pike spawning habitat. Wetlands of the St. Lawrence River follow a temporal succession mainly driven by local topography and recent hydrology (Turgeon et al. 24). The hydroperiod characteristics measured between April and November over the preceding three years determines the annual wetland type at a given location, influencing the abundance of spawning habitat. Even though the hydrological regime has been highly variable over the historic series, this indirect effect has had less impact on Northern pike spawning habitats than its direct influence on fish access and spawning site properties because low and high water regime occurred relatively progressively during this period. Such an effect might have a greater importance in the context of climatic changes, since more frequent extreme events are anticipated, decreasing the length of time that wetlands will have to adapt. For example, extremely low (high) spring discharge, occurring abruptly during years of high (low) water regime,
Mingelbier, Brodeur & Morin. (28). Spatially explicit model predicting the spawning habitat and Hydrobiologia 61(1) : 55-69 1 leads to less spawning habitat than a comparable event occurring progressively over a number of years. Potential mortality vs. discharge and water level Since pike spawners select shallow habitats exposed to rapid water warming and slow current velocity in the spring, the species is highly vulnerable to dewatering after egg deposition. The first spawning habitats affected generally correspond to the highest quality spawning sites. The potential mortality resulting from the eggs exposed to dewatering is substantial. Habitat losses occurred frequently over the period 196-2 (68% of the time), reaching up to - 78% in the most exposed region of the river (Sorel Archipelago). Our results suggest that the availability of early life-stage habitats depends on both the abundance of spawning habitats for egg deposition and the proportion of those habitats being lost by dewatering. This effect has been amplified since 1912 by the regulation of the main affluent of the St. Lawrence River (the Ottawa River), which has had a profound effect on it, shortening the spring flood by approximately three weeks (Morin & Bouchard 2). It is likely that this has resulted in Northern pike being more vulnerable to habitat loss through dewatering. Historical habitat reconstitution The S HSI - S PMI series integrated for the period 196-2 the habitat available for egg deposition and the potential mortality following dewatering, both induced by flow. The high variations in those habitat surfaces between the years and the four regions of the St. Lawrence suggest that management should pay particular attention to the most limiting region in the St. Lawrence, where detrimental spawning conditions are marked and frequent. Interannual variability of S HSI - S PMI habitat surface, which is mostly driven by long-term climatic variations (snow accumulation, temperature, ice melt, rain, wind), is out of anthropogenic control. Nevertheless, discharge regulation, dredging and ice jam control have systematically reduced the spring flood amplitude, with significant negative effects on spawning surfaces. The effects of regulation are potentially pronounced during years of low discharge. Detrimental conditions are likely more prejudicial for pike populations when repeated over consecutive years. The age at maturity, estimated at three years for Northern pike, would be an appropriate criterion to estimate such risk of damage to fish populations (Parent and Schriml 1995). Since discharge in the St. Lawrence River is expected to decrease by 4% and air temperature will be altered (Mortsch & Quinn 1996), it is obvious that climate change will have significant effects on Northern pike spawning and recruitment (Casselman 22). Strengths, weaknesses and further modelling steps Substantial human development, resulting in the loss of nearshore wetlands over the past 5 years in the St. Lawrence River, has increased the need to quantify the habitats of floodplain spawners. One strength of the present spatial model resides in its ability to measure potential habitat surfaces with high spatial and temporal resolution, over a large river. The model was based on the generally accepted fact that the reproduction success of Northern pike in the St. Lawrence River and other systems largely depends on the abundance and quality of spawning habitats and on the stability of the water level after egg deposition (Johnson 1957, Casselman & Lewis 1996, Farrell et al. 26). An independent study conducted in the Montréal region of the river corroborated this point with a highly significant relation between the year class strength and the minimum water level during the spawning period (R 2 =.51; Armellin et al. 23). Even if not direct or causal, this relation indicates the great importance of access to spawning habitat for pike. From the ecological point of view, the greatest weakness of the present model is that it does not provide an ecosystemic understanding with respect to pike. There were no attempts here to represent Northern pike population dynamics (e.g., Minns et al. 1996, Farrell et al. 26), to quantify other limiting life-history stages of the species (e.g., Inskip 1982, Casselman & Lewis 1996), or to include biological interactions and other environmental confounding factors. At the present modelling stage, the results can only be interpreted as potential habitats available for pike spawning, and not as a direct or causal recruitment index. However, we developed a tool providing accurate measurements of potential spawning habitat surface directly related to water level, temperature and vegetation type. A great force of the present approach resides in the fact that the spatial explicit modelling can integrate numerous additional factors, which could be of great interest from an ecological perspective. In the next version of the Northern pike spawning ground model, we expect to integrate additional habitat classes to refine the description of topography (agriculture and urban land uses), other life-history stages, as well as other abiotic variables influencing survival (water quality and wind effects). One challenge ecological modellers face is understanding and addressing the numerous cumulative natural and anthropogenic stresses on fish and habitats (Lewis et al. 1996) in order to orient future modelling efforts into incorporating other lifehistory stages and other recruitment and survival components. Applications The present findings have already been used to design several indicators for a new plan to regulate discharge outflowing from Lake Ontario. With respect to spring discharge regulation, we suggested protecting pike habitat because it is a very integrative management element and because pike protection also benefits other species using the floodplain. We have recommended that the natural hydrological regime be altered as little as possible, in order that spring
Mingelbier, Brodeur & Morin. (28). Spatially explicit model predicting the spawning habitat and Hydrobiologia 61(1) : 55-69 11 discharge management in the St. Lawrence river (i) provide the pike access to key habitats with high water levels for 35-4 days, (ii) avoid any water level variations that may cause massive mortality during incubation and first growth and (iii) let the river system experience natural flow regimes with interannual variations. The present predictive approach, applied here to reconstitute specific historical Northern pike habitat over the last 4 years, can be adapted to a wide spectrum of studies involving other fish species and other critical periods of the year. The approach is helpful for fish management and particularly relevant in the context of climate change. Such modelling could be upscaled to other river systems, with the caveat that each parameter value must be adapted to local characteristics and that the simulations be validated with field measurements. ACKNOWLEDGEMENTS We thank Rémi Bacon, Olivier Champoux, Jean- François Cloutier, Jean Gauthier, Jean Leclerc, Sylvain Martin, Paul Messier, Olivier Roy, and Claude Sirois for their conscientious work in the field and in the laboratory. Funding was provided by the International Joint Commission, the St. Lawrence Action Plan, Natural Resources and Wildlife Quebec, Environment Canada, and the Plan Conjoint des Habitats de l Est. REFERENCES Anderson, P.G. 1992. Adaptation of a suitability model for prioritizing habitat rehabilitation needs of Northern pike (Esox lucius). A thesis submitted to the committee on graduate studies in partial fulfilment of the requirements for the Degree of Master of Science in the Faculty of Arts and Science. Trent University, Peterborough Ontario, Canada. 96 p. Armellin A., M. Mingelbier and J. Morin 23. Water Level Fluctuation and Year-Class Formation of Northern Pike in the St. Lawrence River. American Fisheries Society, 133 rd Conference, Québec City, Canada, August 23. Boudreau, P., Bourgeois, G., Leclerc, M., Boudreault, A., and Belzile, L. 1996. Two-dimensional habitat model validation based on spatial fish distribution: application to juvenile Atlantic salmon of Moisie River (Québec, Canada). In Ecohydraulics 2: Proceedings of the 2nd International Symposium on Habitat Hydraulics, Québec, Qc., June 1996. Edited by M. Leclerc et al. INRS-Eau, Québec. pp. B365 B38. Brodeur P., M. Mingelbier and J. Morin. 24. Impacts des variations hydrologiques sur les poissons des marais aménagés du Saint-Laurent fluvial. Nat Can. 128(2): 66-77 Bovee, K. D. 1982. "A guide to stream habitat analysis using the Instream Flow Incremental Methodology." Instream Flow Information paper n 12, FWS/OBS 82/26, Western Energy and Land Use Team, U.S. Fish and Wildlife Service, Fort Collins, Colorado: 248. Casselman, J. M. and C. A. Lewis. 1996. Habitat requirements of northern pike (Esox lucius). Canadian Journal of Fisheries and Aquatic Sciences 53 (Suppl 1): 161-174. Casselman, John M. 22. Effects of temperature, global extremes, and climate change on year-class production of warmwater, coolwater, and coldwater fishes in the Great Lakes Basin. American Fisheries Society Symposium 32: 39-6. Craig, J.F. and C. Kipling. 1983. Reproduction effort versus the environment; case histories of Windermere perch, Perca fluviatilis L., and pike, Esox lucius L. Journal of Fish Biology 22: 713-727. Dabrowski, K., R.E. Ciereszko, A. Ciereszko, G.P. Toth, S.A. Christ, D. El-Saidy and J.S. Ottobre. 1996. Reproductive physiology of yellow perch (Perca flavescens): environmental and endocrinological cues. Journal of Applied Ichthyology 12: 139-148. Dumont, P. and R. Fortin. 1977. Effects of spring water levels on the reproduction of Upper Richelieu and Missisquoi Bay northern pike (Esox lucius L.). Université du Québec à Montréal, 15 p. Fabricius, E. and K.J. Gustafson. 1958. Some new observations on the spawning behavior of the pike, Esox lucius L. Rep. Inst. Freshwater Res. Drottningholm 39: 23-54. Farrell, J. M., R. G. Werner, S. R. Lapan and K. A. Claypoole. 1996. Egg distribution and spawning habitat of northern pike and muskellunge in a St. Lawrence River Marsh, New York. Trans. Am. Fish. Soc. 125(1): 127-131. Farrell, J. M. 21. Reproductive success of sympatric northern pike and muskellunge in an Upper St. Lawrence River bay. Trans. Am. Fish. Soc. 13: 796-88. Farrell, J.M., J.V. Mead and B.A. Murry. 26. Protracted spawning of St Lawrence River northern pike (Esox lucius): simulated effects on survival, growth, and production. Ecology of Freshwater Fish 15: 169-179. Fortin, R., P. Dumont, H. Fournier, C. Cadieux and D. Villeneuve. 1982. Reproduction et force des classes d âge du grand brochet (Esox lucius L.) dans le Haut-Richelieu et la baie Missisquoi. Canadian Journal of Zoology 6: 227-24. Frenette, J.-J., M. T. Arts, et J. Morin. 23. Spectral gradients of downwelling light in a fluvial lake (Lake Saint-Pierre, St. Lawrence River). Aquatic Ecology 37: 77-85. Guay J.C., D. Boisclair, D. Rioux, M. Leclerc, M. Lapointe, and P. Legendre. 2. Development and validation of numerical habitat models for juveniles of Atlantic salmon (Salmo salar). Can. J. Fish. Aquat. Sci. 57: 265 275 (2) Inskip, P.D. 1982. Habitat suitability index models: Northern pike. U.S. Dept. Int., Fish Wildl. Serv. FWS/OBS- 82/1.17. 4 p. Johnson, F. H. 1957. Northern pike year-class strength and spring water levels. Trans. Am. Fish. Soc. 86: 285-293. La Violette, N., D. Fournier, P. Dumont, et Y. Mailhot. 23. Caractérisation des communautés de poissons et développement d un indice d intégrité biotique pour le fleuve Saint-Laurent, 1995-1997. Société de la faune et des parcs du Québec, Direction de la recherche sur la faune, 237 p. Lamouroux, N., Capra, H., and Pouilly, M. 1998. Predicting habitat suitability for lotic fish: linking statistical hydraulic models with multivariate habitat use model. Regulated Rivers Research Management 14: 1 11. Leclerc, M., A. Boudreault, J. Bechara and G. Corfa. 1995. Two Dimensional Hydrodynamic Modelling: A Neglected Tool in the Instream Flow Incremental Methodology. Trans. Am. Fish. Soc. 124: 645 662. Leclerc, M., Bechara, J.A., Boudreau, P., and Belzile, L. 1996. Numerical method for modelling spawning habitat dynamics of landlocked salmon (Salmo salar). Regul. Rivers Res. Manage. 12: 273 287. Lewis, C.A., Lester, N.P., Bradshaw, A.D., Fitzgibbon, J.E., Fuller, K., Hakanson, L., Richards, C. 1996.
Mingelbier, Brodeur & Morin. (28). Spatially explicit model predicting the spawning habitat and Hydrobiologia 61(1) : 55-69 12 Considerations of scale in habitat conservation and restoration. Can. J. Fish. Aquat. Sci. 53(Supplement 1): 44-445. Machniak, K. 1975. The effects of hydroelectric development on the biology of Northern fishes (reproduction and population dynamics) II. Northern pike Esox lucius (Linnaeus). A literature review and bibliography. Environment Canada, Fisheries and marine service. Technical report no. 528. 3 p. Massé, G., R. Fortin, P. Dumont et J. Ferraris. 1988. Étude et aménagement de la frayère multispécifique de la rivière aux Pins et dynamique de la population de Grand brochet Esox lucius L., du fleuve Saint-Laurent, Boucherville, Québec, Ministère du Loisir, de la Chasse et de la Pêche: 224 p. Massé, G., P. Dumont, J. Ferraris and R. Fortin. 1991. Influence des régimes hydrologique et thermique de la rivière aux Pins (Québec) sur les migrations de fraye du Grand Brochet et sur l'avalaison des jeunes brochets de l'année. Aquat. Living. Resour. 4: 275-287. Miller, L.M., L. Kallemeyn, and W. Senanan. 21. Spawning-site and natal-site fidelity by Northern pike in a large lake: mark-recapture and genetic evidence. Trans. Am. Fish. Soc. 13: 37-316. Mingelbier M. and J. Morin 23. Hydrological delineation of the St. Lawrence River using water level and discharge variability. American Fisheries Society, 133 rd Conference, Québec City, Canada, August 23. Mingelbier M., P. Brodeur et J. Morin 25. Recommendations concerning fish and their habitats in the fluvial St. Lawrence and evaluation of the regulation criteria for the Lake Ontario St. Lawrence River system. Report presented to the International Joint Commission. Ministry of natural resources and wildlife, Department of wildlife research. 141 p. Minns, C.K., R.G. Randall, J.E. Moore and V.W. Cairns. 1996. A model simulating the impact of habitat supply limits on northern pike, Esox lucius, in Hamilton Harbour, Lake Ontario. Can. J. Fish. Aquat. Sci. 53 (Suppl.1): 2-34. Morin, J. and A. Bouchard. 2. Les bases de la modélisation du tronçon Montréal/Trois-Rivières. Rapport scientifique SMC-Hydrométrie RS-1. Environnement Canada, Sainte-Foy, 56 p. Morin, J., M. Mingelbier, J.A. Bechara, O. Champoux, Y. Secretan, M. Jean and J.J. Frenette. 23. Emergence of new explanatory variables for 2D habitat modelling in large rivers: the St. Lawrence experience. Canadian Water Resources Journal 28(2): 1-24. Morin, J., O. Champoux and Y. Secretan. 24. Simplified bidimensional water temperature modelling during spring time on the St. Lawrence River. Technical Report RT- 136, Meteorological Service of Canada, Environment Canada, Sainte-Foy. 42 p. Morin J., O. Champoux, S. Martin and K. Turgeon. 25. Modélisation intégrée de la réponse de l écosystème dans le fleuve Saint-Laurent : Rapport final des activités entreprises dans le cadre du Plan d étude sur la régularisation du lac Ontario et du fleuve Saint-Laurent. Rapport scientifique - RS-18, Environnement Canada, SMC-Hydrologie, Sainte-Foy. Mortsch, L. and Quinn, F.H. 1996. Climate change scenarios for Great Lakes Basin ecosystem studies. Limn. Oceanogr. 41: 93-911 Nelson, W.R. 1978. Implications of water management in lake Oahe for the spawning success of coolwater fishes. Am. Fish. Soc. Spec. Publ. 11: 154-158. Parent and Schriml (1995). A model for the determination of fish species at risk based upon life-history traits and ecological data. CJFAS 52:1768-1781 Petts, G. and P. Calow. 1996. River Biota: Diversity and dynamics. Blackwell Science, Inc., Cambridge, MA. Souchon, Y., F. Trocherie, E. Fragnoud et C. Lacombe. 1989. " Les modèles numériques des microhabitats des poissons: application et nouveaux développements." Revue des sciences de l'eau 2: 87-83. Stalnaker, C. B. (1979). The use of habitat structure preferenda for establishing flow regimes necessary for maintenance of fish habitat. Pp. 321-337. In: Ward JV, Stanford, JA (eds). The ecology of regulated streams. Plenum Press, New York and London. Turgeon K., O. Champoux, S. Martin and J. Morin 24. Modélisation des milieux humides de la plaine inondable du Saint-Laurent, du lac Saint-Pierre au lac Saint-Louis. Rapport scientifique RS-14. Environnement Canada, SMC-Hydrologie, Sainte-Foy, 7 pages. Vadas, R.L. Jr. and D.J. Orth. 21. Formulation of habitat suitability models for stream fish guilds: do the standard methods work? Trans. Am. Fish. Soc. 13: 217-235. Verret, L. and R. Savignac. 1985. L habitat du poisson dans la plaine d inondation de la rive sud du lac Saint-Pierre. Rapport manuscrit Can. Sci. Halieut. Aquat. 1853. 6 p. Vollestad, L.A., B. Jonsson, N.A. Hvidsten, T.F. Naesje, O. Haraldstad and J. Ruud-Hansen. 1986. Environmental factors regulating the seaward migration of European silver eels (Anguilla anguilla). Can. J. Fish. Aquat. Sci. 43: 199-1916.