A Classification and Description of Some Northeastern Ontario Lakes Influenced by Acid Precipitation

J. Great Lakes Res., 1980 Intemat. Assoc. Great Lakes Res. 6(3):247-257

A CLASSIFICATION AND DESCRIPTION OF SOME NORTHEASTERN ONTARIO LAKES INFLUENCED BY ACID PRECIPITATION

J. Roger Pitblado, W. Keller~ and N. I. Conroyl Geography Department Laurentian University Sudbury, Ontario P3E 2C6

ABSTRA cr. Water chemistry data, comprising 23 variables for 187 lakes in the greater Sudbury area, were subjected to statistical analyses. Principal components analysis showed that most of the chemical variability in these systems was attributable to four components - defined as nutrient status, buffering status, atmospheric deposition status, and sodium chloride status. Grouping, by a hierarchical classification system followed by multivariate discriminant analysis, isolated seven distinct groups of lakes within the study area. One set of lakes, including three groups, encompasses lakes demonstrating varying degrees of impact (ranging from severe to minimal) associated with emissions from the Sudbury smelting complex. A second set, divided into two groups based on nutrient supply, includes the characteristic, dilute lakes of the Precambrian Shield showing little obvious anthropogenic influence. The remaining study lakes fall within two groups characterized by atypically high (with respect to the study area) nutrient abundance or ionic strength.

ed elsewhere" (Beamish, et al. 1975). Located in this area is the world's largest single point source of sulphur dioxide emissions, the Sudbury smelting complexes of the Inco Metals Company and Falconbridge Nickel Mines Limited. In response to the real threat of permanent damage to Sudbury area ecosystems, the Ontario Ministry of the Environment mounted a major programme, the Sudbury Environmental Study (S.E.S.), to investigate the severity of impacts related to smelting emissions. Under this programme, water chemistry data (provided in Conroy, Hawley, and Keller 1978) were collected on over 200 lakes in the greater Sudbury area (within a 200 km radius) in order to document the extent of water quality problems related to Sudbury smelting activity and provide a background data base to permit determination of future changes and trends. In this paper, selected data from Conroy et al. (1978) are examined and described in order to evaluate the infuence of atmospherically derived contaminants on northeastern Ontario lakes. Employing a multistage, multivariate statistical approach, the data are used to numerically classify the lakes and the resulting lake groups are mapped and their discriminating features are outlined.

INTRODUCTION It is now generally known and acknowledged that atmospherically conveyed contaminants, particularly acid precipitation, are seriously affecting the character and stability of many of the earth's natural aquatic ecosystems. An increasing body of evidence documents water quality impacts, with potentially severe biological consequences, by acid precipitation in many areas including Norway (Jensen and Snekvik 1972, Forland 1973), Sweden (Willen 1972, Holt Jensen 1973), the U. S. Northeast (Likens and Bormann 1974, Schofield 1975) and Ontario (Dillon et al. 1978; Jeffries, Cox, and Dillon 1979). Although effects associated with inputs of airborne contaminants are widespread, reflecting long-range pollutant transport, the problem appears most pronounced in areas of the Northern Hemisphere at or in proximity to locations emitting large amounts of sulphur and nitrogen oxides (which combine with atmospheric moisture to form relatively strong mineral acids) to the atmosphere. In northeastern Ontario, "the extent of acidification is as great or greater than any recordlOntari.o Ministry of the Environment, 199 Larch Street, Sudbury, Ontano P3E SP9.

247

248

PITBLADO, KELLER, and CONROY

METHODS Twenty-three water chemistry variables, averaged over the period 1974 to 1976, for 187 lakes in the Greater Sudbury area were selected from the S.E.S. report (Conroy et al. 1978). The general geological environments within which these lakes are located and the methods and criteria for lake sampling have been outlined elsewhere (Conroy, Jeffries, and Kramer 1974; Conroy et al. 1978). The locations of the study lakes are indicated in Figure 1. The data were subjected to a principal components analysis in order to achieve parsimony. Factor scores were calculated for the four most significant components; those components having an eigenvalue of unity or greater and which contributed five percent or more to the variance. Using these factor scores, the lakes were numerically classified using a hierarchical classification algorithm (Pitblado 1978a). The next stage in the analysis involved a somewhat subjective grouping of the lakes by visual examination of the dendrogram output from the classification algorithm. The groups were then modified as to their constituent lake membership, but without 83'

destroying the integrity of the dendrogram, by employing a MANOVA (multivariate analysis of variance) followed by multivariate discriminant analysis. These latter steps were undertaken to ensure that within-group variance was minimized and between-group variance was maximized. The final stage of the analysis involved the mapping and description of the lake classes. This type of multistage, multivariate statistical approach has been successfully employed in the numerical taxonomy of soils (Webster 1977, Pitblado 1978b), climate (Powell and MacIver 1977), and has recently been recommended for the analysis of environmental factors which control the pattern of species composition in aquatic environments (Green and Vascotto 1978, Green 1979). RESULTS AND DISCUSSION Principal Components Analysis Four principal components were derived from the analysis of the 23 water chemistry variables for the study lakes (Table 1). Component 1, Nutrient Status. Total Kjeldahl

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ONTARIO LAKES INFLUENCED BY ACID PRECIPITATION TABLE 1. Varimax rotated factor matrix (for each variable, an asterisk has been placed beside the highest component loading).

Variable pH Conductivity Alkalinity Calcium Magnesium Sodium Potassium Sulphate Silica Chloride Total Kjeldahl N Free ammonia Nitrite Nitrate Total phosphorus Sol. phosphorus Secchi disc Chlorophyll a Zinc Copper Nickel Lead Iron Eigenvalue

%Variance Cum. %

I

Component 11 III

IV

0.24 -0.01 0.04 -0,01 0.08 0.10 0.33 -0.17 0.00 0.10 0.84*

0.49* 0.93* 0.96* 0.96* 0.87* 0.15 0.25 0.27 0.20* 0.21 0.17

-0.46 0.27 -0.09 0.10 0.12 0.31 0.46* 0.76* 0.11 0.26 -0.23

0.30 0.23 -0.00 0.07 0.15 0.92* 0.44 0.25 -0.06 0.90* 0.13

0.62* 0.45* -0.09* 0.89*

-0.04 0.04 -0.09* 0.09

0.10 -0.11 0.07 -0.00

0.07 0.02 0.05 0.08

0.63* -0.58* 0.64* -0.10 0.05 -0.05 0.09 0.57* 5.75 36.6 36.6

0.16 -0.00 -0.06 -0.12 0.01 0.01 0.21 -0.21 4.18 26.6 63.2

0.06 0.19 -0.12 0.58* 0.69* 0.66* 0.58* 0.22 3.08 19.5 82.7

-0.02 -0.20 0.13 0.02 0.24 0.53 0.17 -0.10 1.24 7.9 90.6

nitrogen and total phosphorus recorded high (absolute value of loading greater than or equal to 0.70), positive loadings on this component and are therefore considered to be the major variables which characterize Component 1. A number of minor (absolute value of loadings between 0.50 and 0.69) variables can also be recognized. The majority of these, including free ammonia, soluble phosphorus, chlorophyll a, and total iron, load positively. Secchi disc measurements load as a minor, negatively related variable. Component II, Buffering Status. This dimension reflects the complexity of, and the interrelationships between, variables which determine pH and buffering capacity in aquatic environments. As indicated in Table 1, conductivity, alkalinity, calcium, and magnesium load on this component in a very high positive manner. Also, pH loads

249

higher on this component than on the other three, but the loading value is only 0.49. Component III, Atmospheric Deposition Status. The variables which load significantly on this component are those which would be expected to be directly related to smelting activity in Sudbury. Sulphate is the most significant variable according to the principal components analysis. Additional variables which are related to smelting activity and which are associated with this dimension are zinc, copper, and nickel. The loading of pH on this component is -0.46.

Component IV, Sodium-Chloride Status. This component is of less significance than the previous three with respect to its contribution to the variance of the Sudbury area lakes (Table l). It does however, discriminate between lakes, as sodium and chloride recorded high positive loadings. At this point in the investigation it is relevant to examine the apparent direct influence of the Sudbury smelting complex on the extracted components. If it were assumed that the study area was a uniform plane of similar geological material and that airborne pollutants or potential pollutants radiated in all directions solely from Sudbury, the spatial distribution of the factor scores for components associated with smelter emissions might be expected to produce relatively uniform zones also radiating from Sudbury. When this hypothesis is tested by regressing the factor scores of the four dimensions against jistance from Sudbury, it is partially confirmed. The correlation coefficients computed when comparing distance with the dimensions nutrient status, buffering status, atmospheric deposition status, and sodium-chloride status are 0.04, -0.02, -0.66, and 0.31 respectively. Only atmospheric deposition status conforms significantly with the hypothesis using this mode of analysis. Similar results are illustrated in Table 2 which lists the linear correlation coefficients when comparing distance from Sudbury with the major and minor variables associated with the four lake dimensions. This is additionally confirmed by the second column of Table 2 which relates the respective variables with the reciprocal of distance. These data demonstrate that variables directly related to smelting activity, particularly sulphate, are distributed in relationship to distance from Sud-

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PITBLADO, KELLER, and CONROY

TABLE 2. Correlation coefficients com[JfJring selected variables with distance from Sudbury.

With Distance

Variable Total Kjeldahl N Total phosphorus Free ammonia Sol. phosphorus Secchi disc Chlorophyll a Iron Conductivity Alkalinity Calcium Magnesium

pH Sulphate

Zinc Copper Nickel Lead Sodium Chloride

0.18 -0.05

With the Reciprocal of Distance

-0.17 -0.12 0.09 -0.07 -0.20 0.07 -0.11 -0.05 0.26

-0.04 0.15 0.12 0.13 -0.02 0.08 0.07 0.33 -0.02 0.16 0.16 -0.08

-0.66 -0.37 -0.40 -0.38 -0.38 -0.23 -0.16

0.74 0.26 0.48 0.77 0.44 0.61 0.54

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bury in a distance decay manner, a pattern suggested by earlier investigators (Gorham and Gordon 1960). Examination of maps of the factor scores (Figures 2-5) provides further support for the hypothesis. Again, the map of factor scores for the atmospheric deposition dimension (Figure 4) illustrates a distance decay relationship, but in addition, it shows that the pattern is skewed in a southwest-northeast direction. This is the pattern that would be expected if the direction of the prevailing winds of the area, modified by seasonal variations, were taken into account. Maps of the factor scores for the nutrient status and buffering status dimensions (Figures 2 and 3 respectively) show little relationship to Sudbury, reflecting rather the influence of lithological and morphological controls (Conroy and Keller 1976). The factor score map (Figure 5) for the sodium-chloride dimension shows a strong association with areas of urban development (particularly the cities of Sudbury, Sundridge, and North Bay) within the study area.

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FIG. 2. Factor score map for Component I, nutrient status.

251

ONTARIO LAKES INFLUENCED BY ACID PRECIPITATION

Lake Taxonomy Based on the computed factor scores, a hierarchical cluster analysis of the 187 lakes was undertaken producing the dendrogram shown in Figure 6. Seven groups of lakes were identified. These groups are statistically different from each other with respect to their respective variance-covariance matrices (Box 1949), and with respect to their group means when employing Wilks' Lambda as a test (Cooley and Lohnes 1971). The quantitative characteristics of each of these groups are provided in Table 3. Group 1. The lakes in this group are typified by high concentrations of the nutrients, nitrogen and phosphorus. Correspondingly, concentrations of chlorophyll a are higher than those of other lake groups and Secchi disc transparency is much lower. Conductivity, pH, alkalinity, and concentrations of most major ions for Group 1 lakes approach mean concentrations for the study area. Concentrations of sodium and chloride appear moderately elevated in comparison to the other lake groups (with the exception of Group 7). The productive nature of these lakes in some cases appears directly related to cultural eutrophication since many of the lakes exhibit con-

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siderable shoreline development. The abundant nutrient supply in undeveloped Group 1 lakes may reflect morphometric influences (i.e. large drainage basin area relative to lake size) since some Group 1 lakes are located on major river systems. Group 1 lakes are scattered throughout the study area, although most are located within an 87 km radius of Sudbury. As a group, they do not appear overly affected by airborne pollutants. However, those closest to Sudbury contain elevated concentrations of copper and moderately high sulphate, nickel, and zinc concentrations. Concentrations of iron are high, however no association with atmospheric inputs is evident. The iron source is unclear. Locally high geological abundance or efficient iron recycle promoted by the productive (therefore dynamic) character of Group 1 lakes may be implicated. Groups 2 and 3. The dendrogram position (Figure

6) of Group 2 and Group 3 lakes suggests that these lakes are related and could belong to a more encompassing taxa. Indeed, when examining their respective mean factor scores, both groups are characterized by a very significant inverse relationship to the atmospheric depostion status

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252

PITBLADO, KELLER, and CONROY

and buffering status dimensions. They share a similar relationship to the sodium-chloride status dimension but differ significantly with respect to the nutrient status dimension. In regard to Component 1 (nutrient status), the mean of the factor scores for Group 2 is moderately high and positive while that of Group 3 is high and negative. The relationships between these two groups can be further seen by examining Figure 7. The lakes in these groups are the most widely spread of the study lakes, occurring further from Sudbury than those in the other groups. Group 2 lakes, on the average, are located 133 km from Sudbury. The average distance from Sudbury for Group 3 lakes is 127 km. In addition, it is noteworthy that Group 2 and Group 3 lakes are absent from the southwest-northeast trending zone within which prevailing winds would carry significant amounts of potential airborne pollutants generated in Sudbury. As shown in Table 3, Group 2 lakes have mean concentrations of nitrogen and phosphorus well above those in Group 3 lakes. Associated with these nutrient characteristics are concentrations of chlorophyll a which are relatively high and

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low for Groups 2 and 3 respectively. Correspondingly, Secchi disc values are low and high for Groups 2 and 3, respectively. For both of these groups, concentrations of sulphate and trace metals (zinc, copper, nickel) related to smelting activity are commonly well below mean concentrations found in the other lake groups and average values in the study area as a whole. Groups 2 and 3 apparently encompass the characteristic dilute lakes of the Precambrian Shield, located in highly resistant basins and relatively unaffected by human activity. The division between the groups is based on trophic status (degree of nutrient enrichment), with Group 3 lakes exhibiting a generally oligotrophic status while Group 2 lakes approach mesotrophy. The differing nutrient (particularly phosphorus - the usual limiting factor in lentic systems) and associated biological activity (chlorophyll a, Secchi disc transparency) characteristics of the group apparently reflect variation in natural nutrient loadings as influenced by morphometric and lithological factors. Groups 4, 5, and 6. These groups may be con-

sidered subsets of a large class of lakes as indicated

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by their relative positions on the dendrogram (Figure 6). This set of lakes most reflects the impact of airborne pollutants originating from the Sudbury smelting complex. As illustrated in Figure 7, all the lakes within these three groups are located relatively close to Sudbury or are within the southwest - northeast zone referred to previously. On average, as one moves away from Sudbury, one encounters Group 5 lakes first, then Group 6 lakes, and finally Group 4 lakes. The latter group appears to be a transitional group having considerable affinity, statistically at least, with lake Groups I and 2 and, to a lesser extent, Group 7. It is evident from the variables listed in Table 3 that Group 5 contains the lakes which have been most strongly influenced by Sudbury emissions. Characterized by a very strong positive correlation with Component III (atmospheric deposition status), Group 5 lakes are typically very acidic showing the combined effect of high acidic loadings and inherently low buffering capacity. Concentrations of trace metals related to smelting activity (copper, nickel, zinc) are strongly elevated, reflecting substantial deposition due to proximity

to Sudbury and/or increased metal dissolution and mobilization under low pH conditions. Group 6 lakes, generally further removed from Sudbury, show a less pronounced impact related to the smelting centre. Although they are generally not highly acidic, the relatively low pH and alkalinity of Group 6 lakes, in comparison to Group 2 and Group 3 lakes, suggests a significant influence by acidic atmospheric inputs. Some lakes within the group are strongly acidic (pH < 5.0). However, since trace metal concentrations are generally only slightly elevated, these lakes are excluded from Group 5, which includes only the most severely affected lakes in the study area. Lakes in Group 4 show slightly elevated concentrations of sulphate and trace metals, indicating a limited impact by Sudbury emissions. These lakes appear inherently more buffered, and more productive, than lakes in Groups 5 and 6, reflecting a greatly increased assimilation capacity for acidic inputs. Group 7. Group 7 encompasses a highly variable and widely distributed group of lakes which, for the most part, are anomalous within the study

254

PITBLADO, KELLER, and CONROY

FIG. 6. Dendrogram showing the distribution of the study lakes within groups.

area. The group includes lakes situated in areas of paleozoic limestone bedrock, lakes located in pockets of highly calcereous surficial material, and lakes subjected to significant inputs of urban runoff. Although the controlling factors are diverse, Group 7 lakes share the common characteristics of high pH and high ionic strength. CONCLUSIONS Most of the chemical variability within the study lakes can be explained on the basis of four components - defined as nutrient status, buffering status,

atmospheric deposition status, and sodium chloride status. The nutrient status dimension emerges as the major factor, reflecting the overriding influence of nutrient abundance and related productivity characteristics on lentic systems. The importance of the dimensions buffering status and atmospheric deposition status demonstrates the very significant impact of atmospherically conveyed contaminants from the Sudbury smelting complex and the potential moderating influences of lithologically derived buffering species. The sodium-chloride dimension, reflecting urbanization, is of much less significance than the previous

255

ONTARIO LAKES INFLUENCED BY ACID PRECIPITATION TABLE 3. Means of factor scores and water chemistry variables for each of the seven lake groups.

2

3

1.72 -0.07 0.18 0.03

0.40 -0.41 -0.61 0.07

-0.51 -0.33 -0.88 0.15

pH 6.79 Conductivity (~rnhos/cm) 53.6 Alkalinity (mg/L) 8.70 5.5 Calcium (mg/L) Magnesium (mg/L) 2.0 Sodium (mg/L) 1.42 Potassium (mg/L) 0.83 Sulphate (mg/L) 11.44 1.15 Silica (mg/L) Chloride (mg/L) 1.32 358.7 Kjeldahl N (~g/L) 43.6 Free ammonia (~g/L) Nitrite (p.g/L) 3.3 Nitrate (p.g/L) 30.8 T. phosphorus (~g/L) 13.8 Sol. phosphorus (p.g/L) 3.2 Secchi disc (m) 2.89 2.97 Chlorophyll a (mg/m 3 ) Zinc (~g/L) 11.1 16.3 Copper (~g/L) 8.0 Nickel (~g/L) 3.8 Lead (~g/L) 124.8 Iron (~g/L)

6.56 38.8 5.78 4.2 1.1 1.04 0.59 8.82 1.27 1.01 275.7 21.6 2.0 32.9 8.4 1.5 3.81 2.44 10.1 8.7 4.0 2.6 83.7

6.70 37.5 5.85 3.8 1.0 0.95 0.50 8.76 1.19 0.68 193.6 17.2 2.1 45.7 5.1 1.2 6.03 1.64 7.8 7.1 3.0 2.6 34.7

Groups 4

5

6

7

0.16 0.18 0.10 -0.30

-0.62 -0.26 1.41 -0.50

-0.78 -0.19 0.16 -0.05

-0.17 2.97 0.33 1.33

6.77 61.2 12.83 7.5 1.6 1.00 0.62 11.66 1.96 0.64 255.8 18.7 2.2 37.4 7.9 1.7 4.40 2.01 11.1 11.4 6.0 3.8 88.3

4.92 56.1 0.90 4.6 1.1 1.10 0.65 16.99 1.21 0.83 137.5 22.0 1.1 58.1 4.5 1.2 9.36 1.08 26.7 19.2 53.5 4.1 63.8

6.05 51.5 3.70 5.3 1.3 1.07 0.59 15.01 1.24 0.87 162.7 13.3 1.5 21.2 4.9 1.1 6.33 1.36 11.2 10.0 10.6 2.7 46.7

7.81 175.1 60.41 22.2 6.1 3.10 0.94 16.95 1.80 5.05 265.3 18.5 1.8 37.9 8.0 1.8 5.30 1.90 15.8 17.4 59.6 4.7 34.0

Factor Scores Component I Component II Component III Component IV Variables

components since development, within the study area as a whole, is sparse. Grouping of the study lakes provides a useful framework for examination and comparison of chemical characteristics and associated controls within the study area. Of major importance, in this regard, is the large number of lakes (Groups 4, 5, and 6) showing influences by emissions from Sudbury. Group 5 lakes (highly acidic and metal contaminated) represent the worst-effect situation, however the reduced pH and buffering capacity of many Group 6 lakes suggests that severe problems may occur with continued acidic loadings. Lakes within Groups 2 and 3, although showing no obvious impact directly associated with Sudbury, warrant concern over potential effects of the long-range transport of air pollutants, since their extremely dilute nature makes them

very sensitive to acidic inputs. Lakes within Groups 1, 4, and 7, although in some cases receiving significant inputs of atmospheric contaminants (as indicated by elevated concentrations of sulphate, copper, and nickel), appear sufficiently we11buffered to assimilate considerable acidic inputs.

ACKNOWLEDGMENTS The authors wish to thank R. Labbe, Senior Technologist, Geography Department, Laurentian University, for his drafting skills and S. Legault, Ministry of the Environment, Northeastern Region, for typing the manuscript. Part of the work presented was funded under an Experience '79 grant administered through the Ontario Ministry of the Environment.

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PITBLADO, KELLER, and CONROY

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REFERENCES Beamish, R. J., Lockhart, W. L., Van Loon, J. C., and Harvey, H. H. 1975. Long-tenn acidification of a lake and resulting effects on fishes. Ambio 4:98-102. Box, G. E. P. 1949. A general distribution theory for a class of likelihood criteria. Biometrika 36:317-346. Conroy, N. I., Jeffries, D. S., and Kramer, J. R. 1974. Acid shield lakes in the Sudbury, Ontario region. Proc. Symp. Wat. Poll. Res. Can. 9:45-61. _ _ _ _, and Keller, W. 1976. Geological factors affecting biological activity in precambrian shield lakes. Can. Mineral. 14:62-72. _ _ _ _, Hawley, K., and Keller, W. 1978. Extensive monitoring of lakes in the greater Sudbury area, 1974-76. Ontario Ministry of the Environment. Tech. Rep. Cooley, W. W., and Lohnes, P. R. 1971. Multivariate data analysis. New York: John Wiley and Sons. Dillon, P. J., Jeffries, D. S., Snyder, W., Reid, R., Yan, N. D., Evans, D., Moss, J., and Scheider, W. A. 1978.

Acidic precipitation in south-central Ontario; recent observations. J. Fish. Res. Board Can. 35 :809-8 15. Forland, E. J. 1973. A study of the acidity in the precipitation in south-western Norway. Tellus 25 :291-299. Gorham, E., and Gordon, A. G. 1960. The influence of smelter fumes upon the chemical composition of lake waters near Sudbury, Ontario, and upon the surrounding vegetation. Can. J. Bot. 38:477487. Green, R. H. 1979. Sampling design and statistical methods for environmental biologists. New York: John Wiley and Sons. _ _ _ _ , and Vascotto, G. L. 1978. A method for the analysis of environmental factors controlling patterns of species composition in aquatic communities. Wat. Res. 12:583-590. Holt-Jensen, A. 1973. Acid rain in Scandinavia. Ecologist 3:378-382. Jeffries, D. S., Cox, C. M., and Dillon, P. J. 1979. Depression of pH in lakes and streams in central Ontario during snowmelt.J. Fish. Res. Board. Can. 36:640-646.

ONTARIO LAKES INFLUENCED BY ACID PRECIPITATION Jensen, R. W., and Snekvik, E. 1972. Low pH levels wipe out salmon and trout populations in southernmost Norway.Ambio 1:223-225. Likens, G. E., and Bormann, F. H. 1974. Acid Rain: a serious regional environmental problem. Science 184: 1176-1179. Pitb1ado, J. R. 1978a. Computing in the department of geography: a faculty and student guide. Occasional paper no. 1. Sudbury: Depart of Geography, Laurentian University. _ _,---_' 1978b. Multivariate analysis and Tanzanian soil geography. CAG annual meeting. London: University of Western Ontario (unpublished). Powell, J. M., and MacIver, D. C. 1977. A summer climate

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classification for the forested area of the prairie provinces using factor analysis. Information Rep. NOR-X177. Edmonton: Northern Forest Research Centre, Fisheries and Environment Canada. Schofield, C. L. 1975. Lake acidification in the Adirondack Mountains of New York: causes and consequences. p. 477. In Proc. first international symposium on acid precipitation and the forest ecosystem, May 12-15, 1975, Columbus, Ohio. Webster, R. 1977. Quantitative and numerical methods in soil classification and survey. Oxford: Clarendon Press. Willen, T. 1972. The gradual destruction of Sweden's lakes. Ambia 1:6-14.