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Amphora ovalis v. pediculus

54 south-central Ontario lakes

Soil & Water Conservation Society of Metro Halifax (SWCSMH)

July 26, 2006   Paleolimnology Homepage

Excerpts from:

Hall, R.I. and Smol, J.P. 1996. Paleolimnological assessment of long-term water-quality changes in south-central Ontario lakes affected by cottage development and acidification. Can. J. Fish. Aquat. Sci. 53:1-17

Little, J.L., Hall, R.I., Quinlan, R., and Smol, J.P. 2000. Past trophic status and hypolimnetic anoxia during eutrophication and remediation of Gravenhurst Bay, Ontario: comparison of diatoms, chironomids, and historical records. Can. J. Fish. Aquat. Sci. 57:333-341.


Img-pin.gif  Conclusions/Summary
Img-Blue_Arrow11F3.gif  Exceptions:
Img-pin.gif  Approach
Img-Blue_Arrow11F3.gif  Sediment cores
Img-pin.gif  Study area and lake selection
Img-pin.gif  Diatom inference model


Sediment diatom assemblages were used to evaluate water-quality changes since preindustrial times in south-central Ontario lakes receiving acidic deposition and moderate shoreline (mainly cottage) development. Canonical correspondence analysis identified significant relationships between surface sediment diatoms and environmental factors. Relationships were sufficiently strong to develop weighted-averaging regression-calibration models for inferring lake water pH and total phosphorus concentrations ([TP]) from diatoms. These models were accurate to within ±0.21 pH units and &plusmn4.2 µg TP.L-1.

Postindustrial pH and [TP] changes were inferred from surface and pre-1850 sediment diatom assemblages. Results suggest that presently acidic lakes (pH <6) have acidified, and the pH of alkaline lakes (pH >7) has increased as observed in other regions receiving elevated acidic deposition. Diatom-inferred [TP] suggests that cultural eutrophication has not been widespread. In almost all lakes, present-day [TP] is not higher than before European settlement. In many mesotrophic lakes, preindustrial [TP] was higher than at present.

Several factors could account for declining lake water [TP], including:

  1. lake and (or) watershed acidification processes that retain P within catchments or that increase the rate of P loss from lakes (e.g., the formation and enhanced precipitation of P-Al compounds).
    • For example, three of the lakes (Chub, Crosson, and Leech) with the largest diatom-inferred [TP] declines (9, 7, and 7 µg.L-1, respectively) also had the greatest inferred pH declines, on the order of 0.4 to 1.0 pH units.
    • In all cases where inferred lake water pH declined significantly since before 1850, diatom-inferred [TP] never increased, suggesting at least some relationship between pH and [TP] trends within this lake set; and

  2. reductions in nutrient loading from watersheds as a result of reforestation. The mature old-growth forest that existed prior to European settlement may have supplied greater P loads to lakes than the younger (50 to 100 year old), logged, and aggrading forests that surround the lakes today.

However, many other anthropogenic changes have taken place that could also reduce lake water [TP], including

  1. reduction in forest fires,
  2. alterations in aquatic food-web structure as a result of increases in fish stocking, fish harvesting (angling), and other lake-management activities, and
  3. altered hydrology through dam construction.

pH increase in alkaline lakes:

The diatom-inferred pH data from this study, long-term monitoring and paleolimnological data from Sudbury, and modelling data from the Adirondacks all indicate that the pH of alkaline lakes has increased in areas receiving elevated acidic deposition.
Atleast two factors may be responsible for these inferred pH increases, including
i) watershed disturbances that increase ANC (acid-neutralizing capacity), and
ii) biogeochemical ANC-generating reactions, such as sulphate reductions by bacteria and assimilation of atmospherically deposited nitrogen compounds by plants.

Initial surprise- Gravenhurst Bay:

Initially, surprise was expressed that diatoms inferred no significant increases in lake water [TP] in Gravenhurst Bay since preindustrial times. Gravenhurst Bay has received the greatest amount of human activity of all the lakes in this study, including nutrient-rich sewage water inputs and industrial activity from the town of Gravenhurst. Prior to 1972, [TP] concentrations were high (40-50 µg.L-1) and Gravenhurst Bay often had severe algal blooms, poor water clarity, and hypolimnetic anoxia. However, since the installation of improved P removal technologies from sewage waste water in 1972, [TP] steadily declined to 12.5 µg.L-1 in 1992. Sediment diatom assemblages suggest that lake water [TP] has returned to concentrations similar to those that existed naturally in Gravenhurst Bay.

Study area and lake selection

The 54 study lakes are all situated within the Muskoka-Haliburton region of south-central Ontario, Canada, a largely undeveloped area underlain mainly by Precambrian bedrock. Tills and soils are generally shallow, but locally thicker clay, sand, and gravel deposits occur. The nutrient-poor acidic, podzolic soils have low ANC (acid-neutralizing capacity). The regional climate is cool, with an average of 189 frost-free days per year. Mean annual January and July temperatures are 11.0 and 17.7°C, respectively. Precipitation amounts to 90-110 cm.yr-1, 24-30 cm of which falls as snow.

The study area lies within the Great Lakes — St. Lawrence Forest Region. The landscape is predominantly forested and non-agricultural owing to the rough topography, thin soils, and cool climate. Several rural municipalities exist in the region, but seasonal recreation is the dominant human activity. The shores of most lakes are dotted with cottages, and most are serviced with septic sewage systems.

Clear-cut logging was a major industry of the past, with the last major forest clearing 60-100 years ago. Agricultural activity is almost nonexistent.

Lakes were specifically chosen to sample the broadest trophic status gradient possible, and they ranged from very oligotrophic (spring overturn [TP] =2.7 µg.L-1) to mesotrophic (24.3 µg.L-1). Few, if any, eutrophic lakes exist in this region. To minimize the influence of pH and pH-related variables on the distribution of diatom taxa, lakes with pH <5.5 or with [DOC] >6.5 mg.L-1 were not included. Otherwise, the lake set included broad gradients of physical and water chemistry characteristics typical of this region.

Diatom inference model

Classical deshrinking regression equations were as follows:
for pH: y = 0.315x + 4.51, and
for [TP] (µg.L-1): y = 0.134x + 6.56

Table: The optima and effective number of occurrences (Hill's N2) of the diatom taxa used in ordinations and weighted-average regression and calibration models

1Achnanthes bioreti Germ.6.546.9413.7
2Achnanthes chlidanos Hohn & Hellermann6.745.744.8
3Achnanthes Kütz. (Brun)6.976.597.8
4Achnanthes laevis Řstrup7.026.987.4
5Achnanthes levanderi Hustedt6.486.4015.5
6Achnanthes linearis (W. Smith) Grun. sensu auct. nonnull.6.959.5611.4
7Achnanthes marginulata Grun.6.287.428.7
8Achnanthes minutissima Kütz.6.857.5726.6
9Achnanthes subatomoides (Hust.) Lange-Bertalot & Archibald6.538.1321.6
10Aulacoseira distans var.humilis (Cleve-Euler) Simonsen6.747.835.3
11Aulacoseira distans var. tenella (Nygaard) (Florin) Simonsen6.368.0912.5
12Aulacoseira distans var. 3 PIRLA6.644.893.7
13Aulacoseira lirata (Ehr.) Ross6.188.7114.9
14Aulacoseira lacustris (Grun.) Krammer6.265.644.3
15Anomoeoneis brachysira (Bréb) Grun. (in Cleve)6.267.3419.5
16Anomoeoneis vitrea (Grun.) Ross6.666.7127.6
17Aulacoseira perglabra var. fluoriniae (Camburn) Simonsen6.207.8614.4
18Asterionella formosa Hassall6.687.9233.9
19Asterionella ralfsii var. americana Körner5.906.709.5
20Achnanthes suchlandtii Hust.6.857.376.9
21Aulacoseira ambigua (Grun.) Simonsen6.4911.7812.7
22Aulacoseira distans (Ehr.) Simonsen6.616.6122.5
23Aulacoseira nygaardii (Camburn) Simonsen6.079.573.9
24Aulacoseira perglabra Řstrup) Haworth6.427.606.4
25Aulacoseira subarctica (O. Müll.) Haworth6.8414.5310.0
26Aulacoseira cf. sp. 1 PIRLA6.309.016.9
27Cyclotella bodanica var. lemanica (O. Müll.) Bachmann6.707.8326.5
28Cyclotella kuetzingiana var. radiosa sensu Fricke6.745.2216.6
29Cyclotella kuetzingiana sensu Thwaites6.555.209.2
30Cyclotella michiganiana Skvortzow7.087.2610.7
31Cyclotella ocellata Pantocsek6.664.5511.2
32Cyclotella stelligera Cleve & Grun. (in Van Heurck)6.616.4933.4
33Cymbella cesatii (Rabenh.) Grun.6.797.2210.7
34Cymbella microcephala Grun. (in Van Heurck)6.787.3918.5
35Cymbella silesiaca Bleisch6.8610.0916.4
36Diatoma tenue var. elongatum Lyngb.
37Eunotia bilunaris var. mucophila Lange-Bertalot & Nörpel6.1911.113.6
38Eunotia pectinalis var. minor (Kütz.) Rabenh.6.338.207.4
39Eunotia bilunaris (Ehr.) Mills6.216.538.8
40Eunotia exigua (Bréb.) Rabenh.
41Eunotia meisteri Hust.6.115.505.3
42Eunotia paludosa Grun.5.868.862.8
43Eunotia rhomboidea Hust.6.277.657.2
44Eunotia zasuminensis (Cab.) Körner6.099.572.8
45Fragilaria brevistriata Grun.6.718.3426.1
46Fragilaria construens (Ehr.) Grun.7.056.706.8
47Fragilaria crotonensis Kitton7.057.6414.3
48Fragilaria pinnata Ehr.6.839.2117.1
49Fragilaria sp. 5 PIRLA6.096.699.1
50Fragilaria vaucheriae (Kütz.) Petersen6.957.8011.6
51Fragilaria brevistriata var. papillosa Cleve-Euler6.715.798.6
52Fragilaria capucina var. mesolepta (Rabenh.) Rabenh.7.1612.774.8
53Fragilaria construens var. binodis (Ehr.) Grun.6.326.235.4
54Fragilaria construens var. pumila Grun.6.547.074.4
55Fragilaria construens f. venter (Ehr.) Hust.6.797.2713.4
56Fragilaria pinnata var. lancettula (Schumann) Hust.6.6813.398.2
57Frustulia magaliesmontana Cholnoky5.885.193.4
58Frustulia rhomboides (Ehr.) De Toni6.227.2914.1
59Fragilaria virescens var. exigua Grun.6.338.5413.2
60Gomphonema cf. lateripunctatum Reichardt & Lange-Bertalot6.875.963.2
61Navicula laevissima Kütz.6.6011.566.8
62Navicula leptostriata Jřrgensen6.066.367.5
63Navicula mediocris Krasske6.297.815.7
64Navicula pseudoscutiformis Hust.6.485.496.7
65Navicula pupula Kütz.6.398.5015.6
66Navicula pseudoventralis Hust.6.7610.386.5
67Navicula rhynchocephala Kütz.6.876.977.9
68Navicula vitiosa Schimanski6.627.537.1
69Navicula cryptocephala Kütz.6.689.5521.1
70Nitzschia cf. fonticola Grun.6.716.207.7
71Nitzschia cf. gracilis Hantzsch6.558.2022.6
72Nitzschia cf. palea (Kütz.) W. Smith7.0510.175.8
73Nitzschia cf. perminuta (Grun.) M. Peragallo6.066.117.7
74Navicula subminiscula Manguin6.319.386.1
75Navicula submuralis Hust.6.678.8513.2
76Pinnularia abaujensis (Pantoscek) Ross6.469.166.7
77Pinnularia braunii (Grun.) Cleve6.387.463.3
78Rhizoselenia cf. eriensis H.L. Smith6.748.1412.5
79Stauroneis anceps Ehr.6.349.599.0
80Stauroneis phoenicenteron (Nitzsch) Ehr.6.097.706.6
81Synedra acus var. angustissima Grun.7.1510.453.0
82Synedra cyclopum Brutschy7.136.243.5
83Synedra famelica Kütz.6.5112.945.5
84Synedra filiformis var. exilis Ceve-Euler6.797.1718.4
85Synedra nanana Meister6.627.1215.3
86Synedra rumpens Kütz.7.038.995.2
87Synedra tenera W. Smith6.968.386.2
88Tabellaria flocculosa str. III sensu Koppen6.637.4410.3
89Tabellaria flocculosa str. IIIp sensu Koppen6.397.9930.1
90Tabellaria flocculosa var. linearis Koppen6.557.0510.5
91Tabellaria flocculosa str. IV sensu Koppen6.367.4725.5
92Tabellaria quadriseptata Knudson6.417.026.4

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