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257 northeastern USA lakes and reservoirs

Soil & Water Conservation Society of Metro Halifax (SWCSMH)

July 26, 2006      Paleolimnology Homepage

Excerpts from:

Dixit, S.S., Smol, J.P., Charles, D.F., Hughes, R.M., Paulsen, S.G., and Collins, G.B. 1999. Assessing water quality changes in the lakes of the northeastern United States using sediment diatoms. Can. J. Fish. Aquat. Sci. 56:131-152.


Img-pin.gif  Conclusions/Summary
Img-Blue_Arrow11F3.gif  Discussion:
Img-Blue_Arrow11F3.gif  Planning realistic trophic state targets
Img-pin.gif  Study area and lake selection
Img-pin.gif  Diatom inference model


Diatom assemblages were selected as indicators of lake condition and to assess historical lake water quality changes in 257 lakes in the northeastern United States. The "top" (surface sediments, present-day) and "bottom" (generally from >30 cm deep, representing historical conditions) samples from sediment cores collected from lakes and reservoirs were analyzed for diatom assemblages. The distribution of diatom species was closely related to several environmental variables, primarily lake water pH, total phosphorus, and chloride. Using weighted-averaging calibration and regression approaches, predictive models were constructed to infer these variables from the diatom assemblages. The diatom-based inference models were then used to assess the current status of lake water quality and to assess historical changes in lake water conditions in natural lakes over the past 150 years. Changes were also assesed in reservoirs.

Population estimates of historical changes in limnological variables were made for all lakes of the northeast United States and also for lakes in the Adirondacks, New England Uplands, and Coastal Lowlands/Plateau ecoregions.

stop sign icon The extent of cultural impact has been quite variable among the ecoregions, with marked water quality deterioration occurring in hundreds of lakes. Chloride and phosphorus levels have increased, especially in lakes that currently have high concentrations. Low-pH lakes have become more common in all three ecoregions.

Chloride levels:

Marked population changes have occurred in Cl levels in natural lakes since pre-1850. The background levels of Cl in surface waters should be in the range of 50 - 100 畫q/L unless there are other sources than "clean" rainfall and clean seepage. A level of 100 畫q/L indicates disturbance of some sort, whereas <50 畫q/L is expected in pristine wilderness waters lacking natural sources.

The population of lakes that have Cl levels <200 畫q/L has increased threefold (6-18%), whereas the population of lakes that have Cl levels <100 畫q/L has decreased by 5%.

pH levels:

The lake water pH data for the target population of natural lakes indicate that the percentages of both acidic (pH<5.6) and high-pH (>7.5) lakes have increased since pre-industrial times, whereas the number of lakes that had pH between 5.6 and 7.5 has declined. Among ecoregions, ADIR (Adirondacks) contains the highest proportion of acidic lakes (23%). Although the region also contained some naturally acidic lakes (11%), diatom data clearly indicate that the proportion of acidic lakes has greatly increased. In the NEU (New England Uplands) and CLP (Coastal Lowlands/Plateau) ecoregions, the increases have been from 1 to 7% and from 0 to 18%, respectively. The pH-related population changes were small in reservoirs. On a regional basis, changes in any of the pH groups were no more than 2%.

Alkalinization of high-pH lakes:

Although the overall population of naturally alkaline sites (pH>7.5) in the northeast has increased from 46 to 49%, in the ADIR (Adirondacks) and CLP (Coastal Lowlands/Plateau) ecoregions, their populations have increased by 10 and 15%, respectively, whereas in the NEU (New England Uplands) ecoregion, it has declined by 6% since pre-industrial times.

Although the lake water pH decline is mainly due to acidic precipitation in the region, many factors may be responsible for the alkalinization of high-pH lakes.

Possible mechanisms include:

  1. land use changes that increase cation export,
  2. eutrophication accompanied by increased pH,
  3. greater carbonate weathering in watersheds as a result of sulphate and nitrate deposition,
  4. sulphate and nitrate reduction by bacteria in lakes, and
  5. enhanced algal uptake of nitrate that is replaced by bicarbonates.
Although the relative importance of these processes probably varies among ecoregions, the diatom data clearly indicated that, due to human disturbances, the pH in many alkaline sites has been gradually increasing during this century. These inferred pH data are vital in understanding the effects of acidic precipitation on freshwaters and in developing management strategies to document lake responses to emission reduction scenarios.

TP levels:

The target population data for inferred TP suggest that, on a regional basis, the percentages of oligotrophic (TP<10 痢/L), mesotrophic (TP=10-30 痢/L), and eutrophic (TP>30 痢/L) lakes have not changed much for both natural lakes and reservoirs. However, marked population changes are evident for individual ecoregions.

Although natural lakes in the ADIR (Adirondacks) ecoregion had experienced distinct change in lake water pH, the region has not been adversely affected by nutrient enrichment since pre-industrial time. No eutrophic lakes were detected either.

For the natural lakes of the NEU (New England Uplands) ecoregion, the population of eutrophic lakes has increased (from 2 to 4%) and of oligotrophic lakes has declined (from 41 to 38%) whereas the population of mesotrophic lakes has remained relatively unchanged (57-58%). Reservoirs in the NEU region have responded somewhat differently. The population of eutrophic sites has declined (from 22 to 9%), and both oligotrophic and mesotrophic reservoirs have increased from 12 to 17 and from 65 to 75%, respectively.

An increasing number of CLP (Coastal Lowlands/Plateau) ecoregion lakes have undergone nutrient enrichment. In natural lakes, the proportion of eutrophic and oligotrophic lakes have increased from 6 to 8 and from 48 to 63%, respectively, whereas the population of mesotrophic lakes has declined from 46 to 29% since pre-industrial/pre-European times. Although 38% of the reservoirs were eutrophic in the past, their population has increased to 46%. The populations of both oligotrophic and mesotrophic reservoirs have declined in the CLP (Coastal Lowlands/Plateau) ecoregion.

right-hand icon  Although there are more eutrophic lakes in the northeast than in the past, the data also suggest that there were some naturally productive lakes in the region. Land use, land cover, physiography, soil, vegetation cover, and bedrock and surficial geology can greatly influence the eutrophic status of lakes. Although lakes experience changes in trophic state naturally, the major limnological changes that have been identified in this study are mainly due to increased human disturbances in the lakes' drainage basins. These disturbances increase the loads of sediment and nutrients and lead to accelerated eutrophication and water quality degradation.

tree landscape icon Forest cover:

Anthropogenic activity in watersheds generally increases biological productivity in waters as a result of nutrient inputs. Forest cover can act as either a sink or a source of nutrients to lakes, and it has been found that removal of terrestrial vegetation generally introduces nutrients to a lake through leaching processes.

lake in fall picture Planning realistic trophic state targets:

The diatom-inferred regional patterns for current TP not only closely follow the regional patterns of archival TP for the glaciated portion of the northeastern United States, but also provide data on background TP levels in northeastern waters. These regional population data are necessary to provide the rationale for prioritizing restoration efforts and planning realistic trophic state targets.

Study area and lake selection

In EMAP-SW (EPA's Environmental Monitoring and Assessment Program -Surface Waters), 257 lakes and reservoirs were sampled for multiple indicators during July and August of 1991-1994 in Maine, New Hampshire, Vermont, Massachusetts, Connecticut, Rhode Island, New York, and New Jersey. The study area can be broadly divided into three ecoregions: Adirondacks (ADIR), New England Uplands (NEU), and Coastal Lowlands/Plateau (CLP). An ecoregion framework has been useful for assessing regional water quality and setting regionally attainable restoration goals.

The ADIR and NEU ecoregions contained the majority of natural lakes, whereas the majority of sites in the CLP ecoregion were reservoirs. A reservoir was defined as any lake that was created by human activity, where there was probably not a lake in presettlement times.

The site selection was based on a statistical design so that the probability of including any particular site can be calculated. The 257 study sites represent the "target population" of 10,608 lakes and reservoirs in the region that are at least 1 m deep and have a surface area of 1 - 10,000 ha. Because most of these sites are <10 ha in size, a random sample of sites would have been dominated by small water bodies. This situation was corrected by varying the inclusion probability by size so that a reasonable number of large water bodies were also included. The inverse of the inclusion probability of a site is its weighting factor. By using the weighting factor, it is possible to estimate the number of sites in the target population represented by each sampled site.

19 reservoir-sites were problematic. Of the remaining 238 sites, 159 were natural lakes and 79 were reservoirs. Among the 159 natural lakes, 139 were the probability sites, representing the target population of 4638 lakes in the northeast. Among the 79 reservoirs, 78 were probability sites, representing an estimated 4906 reservoirs in the northeast.

Diatom inference model

Table: Number of occurrences, maximum and mean occurrences, and weighted-averaging optima for pH, TP, and Cl for the 235 common diatom taxa found in the 309 sites (238 EMAP and 71 Adirondack PIRLA sites) in the northeastern United States

No.TaxonNo. of
1Achnanthes altaica616.8720
2Achnanthes austriaca var. helvetica1757.11057
3Achnanthes bicapitata537.41069
4Achnanthes clevei128.17244
5Achnanthes detha2237.31046
6Achnanthes didyma657.4724
7Achnanthes exigua618.01341
8Achnanthes exigua var. hetrovelvata157.81185
9Achnanthes flexella707.5928
10Achnanthes hungarica117.947391
11Achnanthes lanceolata897.722113
12Achnanthes lanceolata var. rostrata458.01590
13Achnanthes lapidosa137.811135
14Achnanthes laterostrata587.6742
15Achnanthes levanderi367.2858
16Achnanthes linearis1647.61253
17Achnanthes marginulata1526.6724
18Achnanthes minutissima2927.813105
19Achnanthes peragalli347.7938
20Achnanthes stewartii147.512152
21Achnanthes suchlandtii647.6849
22Actinella punctata595.5925
23Amphora ovalis1238.022118
24Amphora perpusilla308.325592
25Amphipleura pellucida307.91873
26Anomoeoneis follis226.9913
27Anomoeoneis serians var. brachysira1816.4815
28Anomoeoneis serians505.5614
29Anomoeoneis vitrea2467.61140
30Asterionella formosa2097.610128
31Asterionella ralfsii var. americana (<45 痠)135.32138
32Asterionella ralfsii var. americana (>45 痠)1355.81124
33Aulacoseira ambigua2417.51489
34Aulacoseira crassipunctata165.52368
35Aulacoseira distans1696.6824
36Aulacoseira distans var. humilis257.41043
37Aulacoseira distans var. nivalis446.3719
38Aulacoseira distans var. nivaloides1096.91128
39Aulacoseira distans var. tenella1747.21055
40Aulacoseira granulata247.829241
41Aulacoseira italica subsp. subarctica757.5870
42Aulacoseira italica subsp. subarctica f. tenussima137.911180
43Aulacoseira italica var. valida307.41347
44Aulacoseira lirata f. biseriata126.8730
45Aulacoseira lirata var. lacustris436.5919
46Aulacoseira lirata1856.8925
47Aulacoseira nygaardii1006.51021
48Aulacoseira perglabra var. floriniae796.6727
49Aulacoseira perglabra396.0510
50Caloneis ventricosa417.5936
51Cocconeis placentula1268.028387
52Cyclotella comta2007.4644
53Cyclotella meneghiniana268.3661113
54Cyclotella michiganiana1208.09142
55Cyclotella ocellata197.9658
56Cyclotella stelligera2857.3759
57Cymbella amphicephala v. hercynica467.61465
58Cymbella cf. aequalis957.71219
59Cymbella cesatii557.81019
60Cymbella cistula418.01736
61Cymbella cuspidata537.41335
62Cymbella delicatula258.18120
63Cymbella descripta327.81018
64Cymbella cf. gaeumanii586.6829
65Cymbella hebedrica1126.0711
66Cymbella lunata1417.0924
67Cymbella microcephala1357.91134
68Cymbella minuta f. latens127.81281
69Cymbella minuta var. minuta1467.713103
70Cymbella minuta var. silesiaca297.71042
71Cymbella cf. schubartii366.51221
72Cymbella sp. 1 PIRLA595.7712
73Diatoma hiemale var. mesodon126.9626
74Diploneis marginestriata627.71156
75Diploneis ovalis447.81098
76Epithemia species238.01172
77Eunotia bidentula625.61034
78Eunotia bigibba var. pumila135.91018
79Eunotia carolina var. 1 PIRLA655.91153
80Eunotia curvata1726.1924
81Eunotia elegana357.1930
82Eunotia exigua1275.91020
83Eunotia fallax266.1945
84Eunotia flexuosa var. eurycephala166.6736
85Eunotia flexuosa1557.21290
86Eunotia hemicyclus505.7912
87Eunotia implicata257.514114
88Eunotia incisa2106.81141
89Eunotia incisa var. 6 PIRLA135.3619
90Eunotia intermedia676.3827
91Eunotia itiarensis396.3716
92Eunotia lapponica104.9834
93Eunotia lunaris var. attenuata1026.31251
94Eunotia meisteri var. bidens215.9835
95Eunotia meisteri375.5719
96Eunotia microcephala226.41491
97Eunotia monodon947.314104
98Eunotia naegelii656.716125
99Eunotia pectinalis var. minor716.61340
100Eunotia pectinalis866.71046
101Eunotia pectinalis var. ventricosa1627.117140
102Eunotia praerupta626.81029
103Eunotia rhomboidea1206.1924
104Eunotia serra385.81139
105Eunotia vanheurckii826.5930
106Eunotia zasuminensis586.91154
107Eunotia sp. 1 PIRLA196.11178
108Eunotia sp. 2 PIRLA336.41055
109Fragilaria acidobiontica324.938
110Fragilaria brevistriata1847.71349
111Fragilaria brevistriata var. capitata527.71061
112Fragilaria capucina var. mesolepta228.346362
113Fragilaria constricta716.31023
114Fragilaria constricta f. stricta197.712221
115Fragilaria construens var. binodis727.4932
116Fragilaria construens1087.91342
117Fragilaria construens var. venter487.3815
118Fragilaria crotonensis1498.014194
119Fragilaria hungarica var. tumida495.71825
120Fragilaria lata265.9814
121Fragilaria leptostauron118.41590
122Fragilaria cf. oldenburgiana786.2618
123Fragilaria pinnata var. acuminata1287.61489
124Fragilaria pinnata var. intercedens198.31872
125Fragilaria pinnata var. lancettula437.8862
126Fragilaria pinnata2417.61457
127Fragilaria vaucheriae1387.820166
128Fragilaria virescens var. exigua1727.0937
129Fragilaria virescens466.91438
130Fragilaria sp. 2 PIRLA318.22189
131Frustulia cf. magaliesmontana815.5613
132Frustulia rhomboides1436.2932
133Frustulia rhomboides var. saxonica2046.1922
134Gomphonema acumenatum727.61454
135Gomphonema angustatum1707.615109
136Gomphonema gracile776.918113
137Gomphonema subtile var. sagitta128.0910
138Gomphonema sp. 1 PIRLA127.2762
139Gyrosigma acumenatum438.22765
140Gyrosigma obscurum108.021690
141Krasskela kriegeriana207.41035
142Meridion circulare328.014104
143Meridion circulare var. constricta477.614118
144Navicula arvensis727.21469
145Navicula bacillum308.04352
146Navicula bremensis466.2713
147Navicula cf. capitata188.113326
148Navicula cocconeiformis887.2829
149Navicula cryptocephala628.123104
150Navicula cuspidata268.153329
151Navicula disjuncta827.51264
152Navicula explanata367.71133
153Navicula globosa248.11041
154Navicula gysingensis487.418105
155Navicula halophila168.412465
156Navicula cf. heimansii1246.6823
157Navicula laevissima317.11117
158Navicula mediocris1006.51023
159Navicula minima1597.41152
160Navicula modica1137.71436
161Navicula mutica297.611120
162Navicula pseudoscutiformis897.3934
163Navicula pupula2207.51341
164Navicula pupula var. rectangularis377.51234
165Navicula radiosa var. parva1717.81643
166Navicula radiosa887.91240
167Navicula radiosa var. tenella1048.01150
168Navicula rhyncocephala888.020253
169Navicula seminuloides1427.4931
170Navicula submolesta567.312161
171Navicula subtilissima886.41017
172Navicula tenuicephala425.038
173Navicula trivialis128.133147
174Navicula vitiosa1677.41138
175Navicula vulpina137.9914
176Navicula sp. 2 PIRLA127.9954
177Navicula sp. 25 PIRLA267.415107
178Neidium affine1456.0914
179Neidium bisulcatum386.5932
180Neidium iridis var. amphigomphus996.51336
181Neidium iridis var. ampliatum107.11120
182Neidium iridis956.91338
183Nitzschia acicularis318.01466
184Nitzschia amphibia178.11980
185Nitzschia angustata187.715163
186Nitzschia denticula268.1770
187Nitzschia dissipata1097.81477
188Nitzschia fonticola837.71120
189Nitzschia gracilis2147.61577
190Nitzschia linearis107.61045
191Nitzschia microcephala127.4822
192Nitzschia palea827.818134
193Nitzschia perminuta357.31245
194Pinnularia abaujensis1036.71125
195Pinnularia abaujensis var. rostrata247.31413
196Pinnularia abaujensis var. 2 PIRLA776.1710
197Pinnularia biceps1166.81019
198Pinnularia borealis157.830154
199Pinnularia braunii696.71241
200Pinnularia hilseana136.31035
201Pinnularia maior227.01547
202Pinnularia mesolepta347.11022
203Pinnularia microstauron506.51115
204Pinnularia pogoii376.21420
205Pinnularia polyonca257.11333
206Pinnularia subcapitata706.11325
207Pinnularia viridis717.11330
208Pinnularia sp. 11 PIRLA415.598
209Stauroneis anceps736.91124
210Stauroneis anceps f. gracilis1287.01136
211Stauroneis nobilis var. baconiana367.41144
212Stauroneis phoenicenteron1447.31438
213Stenopterobia intermedia1516.4823
214Stephnodiscus hantzschii168.434540
215Stephnodiscus niagrae288.116296
216Stephnodiscus species118.4331036
217Surirella delicatissima1295.8714
218Surirella linearis807.21937
219Surirella sp. 2 PIRLA177.03122
220Synedra acus257.715127
221Synedra acus var. angustissima308.022110
222Synedra delicatissima727.8985
223Synedra famelica997.713170
224Synedra filiformis var. exilis377.5975
225Synedra parasitica697.818250
226Synedra pulchella247.948683
227Synedra rumpens var. familiaris937.725180
228Synedra ulna1337.915126
229Tabellaria binalis275.5510
230Tabellaria fenestrata867.51350
231Tabellaria flocculosa var. linear1717.11039
232Tabellaria flocculosa strain III2297.0943
233Tabellaria flocculosa strain IIIp2367.2850
234Tabellaria flocculosa strain IV2056.8938
235Tabellaria quadriseptata905.51130

Note: Taxa listed here were present in at least 10 sites and had an abundance of 1% in at least one site.

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