© 2004 by CRC Press LLC chapter six Lake trout (Salvelinus namaycush) habitat volumes and boundaries in Canadian Shield lakes Bev J. Clark Dorset Environmental Science Centre, Ontario Ministry of the Environment Peter J. Dillon Environmental and Resource Studies, Trent University Lewis A. Molot Faculty of Environmental Studies, York University Contents Introduction Habitat volume Volume-weighted habitat Estimating habitat boundaries Effects of external stresses on habitat volume References Introduction Lake trout Salvelinus namaycush populations generally require large volumes of cold, well- oxygenated water to thrive (Martin and Olver, 1980); thus, their optimal habitat boundaries have been defined by temperatures of less than 10 ο C and by oxygen concentrations greater than 6 mg/L (Evans et al., 1991). Oxygen and temperature criteria have been used to define other classes of lake trout habitat; for example, Evans et al. (1991) defined a “usable” habitat as one with O 2 > 4 mg/L and temperature <15 ο C. There is increasing evidence that some populations can be successful at higher temperatures under some circumstances (Snucins and Gunn, 1995), but in most cases, examining the potential for success or failure of lake trout populations requires, as a minimum, a measurement of suitable habitat volumes for the lakes in question (Christie and Regier, 1988; MacLean et al., 1990; Evans et al., 1991). Because these boundaries are measured easily using portable field equipment (tempera- ture/oxygen meters), they present a relatively simple means of assessing habitat suitability. © 2004 by CRC Press LLC Habitat volume Lake trout habitat volumes are at their minimum each year immediately before the time when surface waters have cooled enough (to <15 ο C) to be usable. This occurs before thermal destratification in the fall. At this time, oxygen concentrations in the hypolimnion will be at their minimum, and the depth of the metalimnion as well as the depth of the 10 ο C isotherm, Z 10 , will be at their greatest. These dates are determined each year by the rate of cooling of the mixed layer and are therefore subject to external forces associated with weather. The most appropriate time for these measurements is therefore the late summer period when minimum hypolimnetic oxygen concentrations and maximum tem- peratures, i.e., worst-case conditions with respect to lake trout habitat, usually are found in dimictic lakes (Evans et al., 1991). Evans et al. (1991) used habitat volumes “standardized” to August 31, and Molot et al. (1992) standardized end-of-summer oxygen profiles to September 1. Although optimal habitat often will continue to decrease after September 1, it is difficult to obtain data sets that are closely spaced (temporally) to model the exact minimum habitat volumes or to predict the dates that these occur because of between-year variation in the turnover dates. Measured Z 10 (i.e., the depth of the 10 ο C isotherm) depression rates (Dillon et al., in press) during the late summer and fall ranged from 0.013 to 0.051 m/d and were correlated with transparency, measured as DOC. This means that Z 10 would not likely depress more than ca. 1.5 additional meters after September 1 for most lakes if conditions continued to deteriorate for the entire month. Oxygen concentrations in the bottom waters may continue to diminish; potentially this would present more severe problems for lake trout, especially in those cases where habitat volumes are minimal earlier in the year, which can be the situation in lakes that are relatively shallow. However, the greatest stress on populations occurs after all of the optimal habitat has disappeared; hence, we believe that the optimal habitat estimated for September 1 describes close to minimal volumes. By the end of September, temperatures are almost always such that the optimal habitat for lake trout (Evans et al., 1991) has started to increase through cooling of the mixed layer. Models that have been developed to estimate habitat volumes usually express the volume as a percentage of the total lake volume. In addition, most existing optimal habitat models acknowledge the link between habitat volume and some measure of both lake morphometry and nutrient status. For example, the optimal habitat model used for lake trout management in inland lakes in southeastern Ontario (Ontario Ministry of the Environment and Ontario Ministry of Natural Resources, 1993) uses mixing ratios and mean summer chlorophyll a to estimate the proportion of the habitat that is optimal. Ryan and Marshall (1994) presented a rapid diagnostic method based on mean depth and habitat quality using phosphorus, Secchi depth, and chlorophyll. Models that esti- mate habitat based on specific oxygen and temperature boundaries are discussed later in the chapter Volume-weighted habitat Management guidelines that are based on habitat volumes may be difficult to interpret because these volumes vary considerably between lakes. Similar volumes, for example, may have very different meanings when expressed as a percent of the total lake volume, and vice versa. It also may be difficult to assess the importance of habitat loss, especially in bottom waters where the loss may represent a relatively small proportion of the total volume. The use of a volume-weighted hypolimnetic oxygen concentration (VWHO) would eliminate many of these problems. A standardized (end-of-summer) VWHO allows the use of a single number to compare conditions among lakes. These lakes may otherwise © 2004 by CRC Press LLC show seasonal and spatial variability with respect to O 2 concentrations and often different orders of magnitude with respect to habitat volumes. It is suggested for lake trout that VWHO should not be allowed to drop below 7 mg/L (Evans, 1999). Calculating VWHO requires morphometry data and at least one end-of-summer oxygen and temperature profile. Ideally the means of several oxygen and temperature profiles would be used to reflect long-term conditions. Temperature profiles are used only to establish the upper limit of the hypolimnion, which is defined as the lower depth of the first 1-m interval where the temperature change is less than 1 ο C per meter. Once the thermal hypolimnetic boundaries are established, the volumes for each stratum are calculated by: V = m[A t + A b + v(A t *A b )]/3 (6.1) where V is volume (m 3 ) A t is the area of the top of the stratum (m 2 ) A b is the area of the bottom of the stratum (m 2 ) m is the depth (thickness) of the stratum (m) VWHO is calculated as the summed products of the measured dissolved oxygen concen- tration in each stratum and the proportion of the hypolimnetic volume represented by that stratum. It can also be estimated by volume-weighting the oxygen concentrations (at a given depth) that are predicted from the hypolimnetic oxygen profile model developed by Molot et al. (1992). More details with respect to modeling oxygen concentrations are given in the following section. Estimating habitat boundaries Models that predict the percentage optimal habitat in lakes or calculations that give VWHOs offer no specific information about the location of the habitat boundaries defined by temperature and oxygen. Furthermore, proportional volumes alone cannot provide information regarding how environmental change might affect the habitat boundaries. For example, it has long been realized that increases in the nutrient status of a lake will deplete hypolimnetic oxygen (Molot et al., 1992) and thereby reduce lake trout habitat by raising the lower (oxygen) boundary in the lake. On the other hand, determining the effect of transparency on habitat volumes is of recent interest because of work linking climate change as well as other regional-scale stresses such as acid rain to changes in transparency (Dillon et al., 1987; Schindler, 1997; Schindler et al., 1990, 1996b; Fee et al., 1996; Molot and Dillon, 1997). For example, Fee et al. (1996) found that mixing depths (which have a strong effect on the determination of upper habitat boundaries) were best identified using extinc- tion coefficients (converted to percentage transmission), which principally are functions of dissolved organic carbon (DOC) except in those cases where algal levels are high (i.e., eutrophic lakes). Two simple models were previously developed and combined to estimate long-term average optimal habitat boundaries for lake trout defined by temperature and oxygen criteria. A hypolimnetic oxygen profile model (Molot et al., 1992; Clark et al., 2002) was used to define the mean long-term lower boundary (Z 6 mg/L ) of the optimal habitat. Because this model uses lake morphometry and total phosphorus (TP) to predict hypolimnetic oxygen profiles for the late summer period (Sept. 1), it can be used to estimate the depth of the specific O 2 concentration of interest. © 2004 by CRC Press LLC Oxygen concentrations at each stratum z are determined by: log 10 O 2 (f) z = 1.83 – 1.91/VSA z – 7.06/O 2 (i) z – 0.0013TP 2 so (6.2) where O 2 (f) z = the end-of summer oxygen concentration at depth z (mg/L) O 2 (i) z = the oxygen concentration at depth z at spring turnover (mg/L) TP so = the total phosphorous concentration at spring turnover (µg/L) VSA z = the ratio of the stratum volume (V)/sediment surface area (SA) at depth z (m) Spring turnover oxygen concentrations [O 2 (i)] are measured directly or determined for each stratum by: log 10 O 2 (i) z = 0.99 – 5.74/A o + 0.64/z (6.3) when the maximum distance from shore to shore at z max (= MD) < 1.4 km or by: log 10 O 2 (i) z = 1.07 – 6.95/A o – 0.0043z/MD (6.4) when MD > 1.4 km. A second recently developed model (Dillon et al., in press) predicts the depth at which 10 ο C occurs (Z 10 ) for the same late summer period. For the set of 37 lakes used for the model development, transparency was the primary determinant of Z 10 , with the morpho- metric or lake size parameters playing a secondary role. A water clarity parameter, either Secchi depth or 1/DOC (the reciprocal of the dissolved organic carbon concentration) together with either lake area (A 0 ) or MD, was used to generate a linear relationship with Z 10 . The combination of 1/DOC and A 0 gave the best fit as: Z 10 = 3.52 + 11.3/DOC + 0.139* (6.5) (r 2 = 0.88, p < 0.01, std. error of estimate = 0.87). This was somewhat better than the fit obtained using Secchi depth as the transparency parameter and MD as the lake size parameter: Z 10 = 3.35 + 0.956*Secchi + 0.33*MD (6.6) (r 2 = 0.78, p < 0.01, std. error of estimate = 1.17) These two modeled boundary depths (i.e., Molot et al., 1992, and Dillon et al., in press) were combined with measured morphometric data (strata volumes) to calculate long-term optimal lake trout habitat volumes standardized to the end of summer i.e., Sept. 1 (Dillon et al., in press). These authors suggest that the combined models could be used to predict the effects of changes in trophic status or transparency on the upper and lower optimal habitat boundaries for a given lake. In a similar fashion, a modeling approach analogous to those described here could be used to delineate other oxygen or temperature boundaries and thus define usable lake trout habitat, or any other class of habitat. A 0 © 2004 by CRC Press LLC Effects of external stresses on habitat volume It is clear that because these oxygen and temperature models use TP, Secchi depth (or DOC), and physical factors (morphometry, MD, or A 0 ), changes in either the nutrient status or transparency of a lake will impact directly on the optimal habitat volumes. These relationships, in fact, allow us to predict the loss in optimal habitat volume that would result from projected changes in water quality. It should be noted that, in some instances, the changes in conditions controlling Z 10 and Z 6mg/L may in part, have counteracting effects on optimal habitat volume. Increasing nutrient levels (TP), for example, will increase oxygen deficits near the bottom (Molot et al., 1992), resulting in a shallower lower bound- ary for optimal habitat. However, the same change in TP may result in reduced Secchi depth because of increased chlorophyll a concentrations (Dillon and Rigler, 1974), a shal- lower Z 10 , and therefore increased habitat volume. In general, however, water clarity in lake trout lakes is controlled by DOC rather than TP, so the effects of an increase in nutrient levels will be largely transmitted through the decrease in the lower oxygen boundary rather than the increase in the upper temperature boundary. Many lakes will likely become more transparent as a consequence of changes in climate (Magnuson et al., 1997; Schindler et al., 1990, 1996a, 1997). It has been proposed that this will be the result of declining DOC production in watersheds during prolonged periods of above-normal temperatures and below-normal precipitation (Dillon et al., 1996; Dillon and Molot, 1997; Schindler et al., 1997). This change in transparency in combination with the direct effects of increased air temperatures will result in deeper Z 10 s (Snucins and Gunn, 2000) and decreased optimal lake trout habitat volumes. Fee et al. (1996) estimated that there is the potential for the epilimnia in smaller lakes to increase in thickness by 1 to 2 m as a result of a twofold increase in atmospheric CO 2 levels. Acidification of lakes by the input of mineral acids also results in increased transparency (Effler et al., 1985), again via removal of DOC (Schindler et al., 1996b). For example, the Secchi depth mea- sured in Plastic Lake increased by ca. 2 m (Dillon et al., 1987) during the lake’s last 7 or 8 years of acidification and probably by much more over the total period in which acidifi- cation occurred. For the 37 lakes in the Dorset area used to test/develop their model, Dillon et al. (in press) calculated that a 1-m increase in transparency would result in an increase in Z 10 of ca. 1 m. Following a 2-m increase in transparency, optimal habitat volumes in the same lakes would be reduced by between 8 and 100%. These calculations are based on the assumption that clarity changes result from loss of DOC and that there is no change in TP concentrations that would affect the lower optimal habitat boundaries (Z 6mg/L ). Any such changes resulting from changes in TP would be much less significant than those resulting from DOC-induced changes in clarity. The proportional amount of optimal habitat that would be lost for any lake is greatest when the optimal habitat volume is relatively small. Lakes having high percentages (>50%) of their total volume as optimal habitat would lose only 10 to 20% of their optimal habitat, whereas lakes with only 10 to 25% of their volume as optimal habitat could lose 50% or more of the remaining habitat, putting the continued success of the lake trout populations in jeopardy. There are other factors that were not included in either of the two models defining the habitat boundaries, which may be important. For example, France (1997) established linkages between lake thermocline depth and riparian deforestation, which would indicate that the Z 10 for lakes of similar size, clarity, and nutrient status might vary with differences in riparian cover or surrounding topography. We cannot quantify the influence of this parameter on the variation observed between predicted and measured boundary depths because such data are not available. © 2004 by CRC Press LLC Finally, recent studies show that the effects of logging on the mixing depths of adjacent lakes may be minimal (Steedman and Kushneriuk, 2000) or that one consequence of increasing temperature may be a reduction in mixed layer depths that results from rapid stratification caused by high air temperatures in the first part of the ice-free season (Snucins and Gunn, 2000). 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Schindler, D.W., Beaty, K.G., Fee, E.J., Cruikshank, D.R., DeBruyn, E.D., Findlay, D.L., Linsey, G.A., Shearer, J.A., Stainton, M.P., and Turner, M.A., 1990, Effects of climate warming on lakes of the central boreal forest, Science 250:967–970. Schindler, D.W., Bayley, S.E., Parker, S.E., Beaty, K.G., Cruikshank, D.R., Fee, E.J., Schindler, E.U., and Stainton, M.P., 1996a, The effects of climate warming on the properties of boreal lakes and streams at the Experimental Lakes Area, northwestern Ontario, Limnology and Oceanog- raphy 41:1004–1017. Schindler, D.W., Curtis, P.J., Parker, B.R., and Stainton, M.P., 1996b, Consequences of climate warming and lake acidification for UV-B penetration in North American boreal lakes, Nature 379:705–708. Schindler, D.W., Curtis, P.J., Bayley, S.E., Parker, B.R., Beaty, K.G., and Stainton, M.P., 1997, Climate- induced changes in the dissolved organic carbon budgets of boreal lakes, Biogeochemistry 36:9–28. Snucins, E.J. and Gunn, J., 1995, Coping with a warm environment: behavioral thermoregulation by lake trout, Transactions of the American Fisheries Society 124:118–123. Snucins, E.J. and Gunn, J., 2000, Interannual variation in the thermal structure of clear and colored lakes, Limnology and Oceanography 45:1639–1646. Steedman, R.J. and Kushneriuk, R.S., 2000, Effects of experimental clearcut logging on thermal stratification, dissolved oxygen, and lake trout (Salvelinus namaycush) habitat volume in three small boreal forest lakes, Canadian Journal of Fisheries and Aquatic Sciences 57(Suppl. 2):82–91. . H.E., in press, Predicting optimal habitat boundaries for lake trout (Salvelinus namaycush Walbaum) in Canadian Shield lakes, Canadian Journal of Fisheries and Aquatic Sciences. Dillon, P.J. and. experimental clearcut logging on thermal stratification, dissolved oxygen, and lake trout (Salvelinus namaycush) habitat volume in three small boreal forest lakes, Canadian Journal of Fisheries and Aquatic. input of mineral acids also results in increased transparency (Effler et al., 1985), again via removal of DOC (Schindler et al., 1996b). For example, the Secchi depth mea- sured in Plastic Lake