LIGHT AND HEAT IN AQUATIC ECOSYSTEMS

Contents

Color of Aquatic Ecosystems

Ice

Light, Biological Receptors

Optical Properties of Water

Temperature as a Driving Factor in Aquatic Ecosystems

Turbidity

Ultraviolet Light

Color of Aquatic EcosystemsL A Molot, York University, Toronto, ON, Canada

ã 2009 Elsevier Inc. All rights reserved.

Introduction

Many natural waters appear colored to the eye becauseof the presence of dissolved, colloidal, and suspendedparticulate substances, which alter the quality of lightseen by an observer. The color of a lake as seen from adistance may also be affected by reflectance of lightfrom the sky. Some lakes may appear blue while othersmayappear green, yellow, or dark brown, dependingontheir constituents. For example, the surface of a highlyeutrophic lake covered with an algal bloomwill appeargreen while an unproductive lake with major peatlandsin its catchment will appear dark brown.True color is defined as the color imparted by dis-

solved and colloidal substances whereas apparentcolor refers to the color imparted by all substancesincluding suspended particulate matter. In most natu-ral waters, the main source of true color is chromo-phoric (‘colored’) dissolved organic carbon (CDOC),also called humic substances. CDOC is primarilyallocthonous, with peatlands being the main source.CDOC imparts a color ranging from light yellow todark brown in unproductive waters with the hue andintensity dependent on the quality and concentrationof the CDOC. However, the term ‘color’ as used hererefers only to the measurement of an optical propertyof water and not how color is perceived by the humanbrain. This article begins by describing the measure-ment and interpretation of true color. It then discussesthe impacts of colored substances on light transmis-sion and the thermal structure of lakes, and ends witha brief discussion of the effects of human activities oncolor. More detailed discussions are presented else-where of the optical properties of water, heat in sur-face waters, and the composition and characteristicsof humic substances.

Methods for Measuring Color

The most common limnological method for measuringcolor in natural waters is based on comparing the lossof light passing through a sample (i.e., absorbance) ator about 420nm to the absorbance of a standardplatinum–cobalt solution. The choice of 420nm isprobably based in part on the observation that CDOCpreferentially absorbs shorter wavelengths in the blue-violet region relative to longer wavelengths in the redregion, and thus a shorter wavelength increases thesensitivity of an absorbance-based method.

Absorbance is typicallymeasured using either a spec-trophotometer capableofmeasuring light ina relativelynarrow bandwidth centered at about 420nm or a col-orimeter fittedwith a broadband glass filter with upperand lower limits between �400 and 450 nm. Theupper and lower limits of the colorimeter will dependon the properties of the glass filter used. Some authorshave referred to absorbance without calibrating againa Pt–Co solution as color or have used awavelength inthe 400–450-nm region other than 420 nm.

The platinum–cobalt standard solution consists of2.492 g K2PtCl6 with 2 g CoCl2�6H2O in 200ml ofconcentrated hydrochloric acid diluted to 1 l with800ml of deionized water. The absorbance of thissolution containing 1000mg Pt per liter at 420 nm isdefined as 1000 Pt units. Pt units are sometimes writ-ten as mg l�1 Pt. The Pt unit is sometimes also called aHazen unit in honor of one of the first investigatorsof color.

The true color of natural waters ranges from0 to <400 Pt units. In practice, apparent color is thecolor of unfiltered water and true color is the color offiltered water (the pore size should be specified). TheOntario Ministry of the Environment (OMOE) in

657

658 Light and Heat in Aquatic Ecosystems _ Color of Aquatic Ecosystems

Canada uses an empirical method for calculatingthe true color of an unfiltered sample based on thePt–Co method. OMOE calculates color in Pt units as1.35A � 1.68Bwhere A is the broadband absorbanceat 405–450 nm and B is the broadband absorbance at660–740 nm in an automated colorimeter.A qualitative index that is infrequently used today

to classify lake color is the Forel–Ule color-comparisonscale. It consists of 21 standard solutions made upof various inorganic salts with colors ranging fromblue (I) to brown (XXI). As Franz Ruttner wroteover 50years ago, ‘‘The colours seen in deep waterswithin the reflection of a dark screen, or simply inthe shadow of a boat, can be compared with these[standards].’’ Sample vials may also be comparedwith vials with Forel–Ule standards, against a whitebackground.

Color as a Surrogate for DOC

In many unproductive waters (saline ponds and lakesbeing the exceptions), there is a strong linear relation-ship between long-term, mean annual total DOCconcentration, and mean annual color based onabsorbance (Figure 1). Hence, color is sometimesused as a surrogate for CDOC (and vice versa) instudies of transparency and thermal structure.Long-term color budgets (i.e., mass balances) have

been calculated for seven unproductive lakes in theDorset area of Ontario, analogous to mass balancesfor DOC, and used to calculate in-lake loss coeffi-cients of color at steady state. The steady state massbalance equation is given by,

Color ¼ Load=ðvc þ qÞ ½1�

0

10

20

30

40

50

6543210DOC, mg L−1

Col

or, P

t uni

ts

Figure 1 Mean annual (1980–86) true color versus dissolved

organic carbon (DOC) for eight lakes (one lake with two basins)

near Dorset, Ontario. Data from the Ontario Ministry of theEnvironment.

where Color is the mean annual, volume-weightedlake color (Pt units or g Pt per cubic meter), Loadis the annual color export to the lake (g Pt persquare meter per year), vc is the net loss coefficient(m year�1) representing internal loss mechanisms(e.g., photooxidation and microbial mineralizationin the lake), and q is the areal water discharge ratefrom the lake (myear�1). Values for vc were largerthan the loss coefficients for all of the DOC, indicat-ing that the CDOC fraction is preferentially oxidizedalthough ratios can be altered in situ by production ofuncolored DOC. Preferential destruction of CDOC isconsistent with observations that larger color/DOCratios occur in headwater tributaries than in lakeoutflows.

While the long-term, mean relationship betweenCDOC and color is relatively constant within a streamor lake, it is not constant over time and space. There isa strong seasonality to the color/DOC ratio in unpro-ductive boreal lakes and streams near Dorset, Ontario(Figure 2). Lowest ratios occur in the epilimnion dur-ing the summer, due in part to photooxidative loss ofchromophores, the light absorbing centers. In contrast,the highest ratios in flowing waters typically occurduring low flow periods in summer. High summerratios have been observed in small boreal streams incentral Ontario and in the Yukon River in Alaska.Temporal variation in the color/DOC ratio can pro-duce scatter in DOC–color plots when discrete valuescollected over several seasons are used rather thanlonger-term mean values (Figure 3). This may explainwhy temporal fluctuations in DOC and ‘color’ (i.e.,absorbance at 440nm) in a set of 20 lakes in northernMichigan were not always synchronous.

Spatial variation in ratios occurswithin a lake duringthermal stratification with smaller ratios in the epilim-nion and higher ratios in the deeper layers (Figure 3).

Factors external to lakes also affect the color/DOCratio. The long-term ratio in a set of seven study lakesnear Dorset, Ontario, was lowest in an acidic lakebecause acidity enhances photochemical loss of DOC,especially the chromophoric fraction. The ratio wasalso quite low in a lake lacking peatlands in the catch-ment because peatlands are a major source of CDOCin lakes. Indeed, the proportion of DOC that is coloredincreases with increasing area of peatland in thecatchment.

Some water bodies such as saline ponds on theCanadian prairies have very high levels of DOC yetare relatively clear or transparent (Figure 4), presum-ably because the organic chromophores (i.e., lightabsorbing centers) have been destroyed over timeleaving the nonabsorbing moieties.

For these reasons, care must be taken when usingcolor as a surrogate for DOC.

4

6

8

10

12

14

16

18

20

3603303002702101801501209060300 240Julian day

Col

or/D

OC

rat

io

Figure 2 Seasonal color/DOC ratios (Pt units (mg C l�1)�1) in Dickie Lake (solid symbols) and one of its headwater tributaries,

Dickie 11 (open symbols) in 1983. In Dickie lake, days 145–284 are epilimnetic values and other days are whole-lake values.The stream was dry in August. Data from the Ontario Ministry of the Environment.

876540

50

100

150

200

250

DOC, mg L−1

Col

or

Figure 3 Scatter plot of discrete measurements of true color (Ptunits) versusDOC inDickie Lake nearDorsetOntario, fromOctober

1980 to January 1987. Values are epilimnion (□; solid trend line),

metalimnion (*; dotted trend line) and hypolimnion (♦; dashed trendline). Data from the Ontario Ministry of the Environment.

2001501005000

30

60

90

120

150

180

DOC, mg C L−1

UV

B e

xtin

ctio

n co

effic

ient

, m−1

Non-saline lakesSaline lakesNon-saline pondsSaline ponds

Figure 4 Ultraviolet B radiation extinction coefficients versus

DOC for freshwater and salines systems on the Canadia prairies.Reproduced from Arts MT, Robarts RD, Kasai F, et al. (2000) The

attenuation of ultraviolet radiation in high dissolved organic

carbon waters of wetlands and lakes on the northern GreatPlains. Limnology and Oceanography 45: 292–290, with

permission from the American Society of Limnology and

Oceanography.

Light and Heat in Aquatic Ecosystems _ Color of Aquatic Ecosystems 659

Effect of Color on Water Transparency

Transparency (ameasure of the depth of penetration ofvisible light) is affected by both CDOC and particulatesubstances because of their ability to absorb and scat-ter light. Measures of transparency include true andapparent color, wavelength-specific absorbance, in situattenuation of photosynthetically active radiation(PAR) and Secchi depth. Only true color and the absor-bance of filtered samples (which are related measure-ments) measure the effect of dissolved substances ontransparency with the other measurements combiningthe effect of dissolved and particulate substances. Theeffect of particulate matter on transparency can be con-sidered relativelyminor in unproductive, coloredwaters

but particulate matter has a strong effect on transpar-ency in productive waters andwaters with high levels ofsuspended inorganic matter (i.e., clay and silt).

Color restricts the penetration of light into waterby increasing the absorption of photons in near sur-face waters. The effect of color, then, is to limit thedepth of the euphotic zone. The PAR extinction coef-ficient (KPAR, m

�1) in 10 small, Finnish lakes withchlorophyll levels less than 10 mg l�1 was positivelycorrelated with true color (Figure 5) where KPAR is

0

1

2

3

4

5

6

7

Color, Pt units

KP

AR a

nd Z

1%

Z1%

KPAR

350300250200150100500

Figure 5 The extinction coefficient for photosynthetically

active radiation (PAR), KPAR (m�1), and the depth of 99% PARattenuation, Z1% (m) versus true color in 10 Finnish lakes with

chlorophyll levels less than 10mg l�1. Reproduced from Jones RI

and Arvola L (1984) Light penetration and some selected

characteristics in small forest lakes in Southern Finland.Verhandlungan International Verein Limnology 22: 811–816, with

permission from E. Schweizerbart Science Publishers.

0.00

0.05

0.10

0.15

0.20

0.25

0.30

June 23June 9June 2May 26

Abs

orba

nce

at 4

20 n

m

UnfilteredFilteredParticulate

Figure 6 Absorbance at 420nm using a 5 cm path length in

eutrophic Lake 227 in the Experimental Lakes Area, northwestern

Ontario in 2005. The absorbance contributed by the particulatefraction was calculated by difference between filtered (0.4mm)

and unfiltered samples. Reproduced from L. Molot.

660 Light and Heat in Aquatic Ecosystems _ Color of Aquatic Ecosystems

calculated as the slope of a plot of ln(IZ/I0) versusdepth, Z, and Iz and I0 are the light intensities atdepth Z and the surface, respectively. The regressionformula for the Finnish lakes is given by,

KPAR ¼ 0:01C þ 0:71; R2 ¼ 0:93 ½2�The bottom of the euphotic zone is often taken byconvention to be the depth at which 1% of surfaceradiation occurs, Z1% where

Z1% ¼ lnð0:01Þ=KPAR ½3�Hence,

Z1% ¼ 4:61=ð0:01C þ 0:71Þ ½4�The nonlinear effect of color on the size of the eupho-tic zone is illustrated in Figure 5 with the Finnishlake data.The separate effects of dissolved and particulate

matter can be seen in a plot of absorbance at420 nm (not calibrated for Pt–Co) in eutrophic Lake227 (Figure 6). The absorbance in a filtered sampleremained relatively constant between late May andlate June, increasing by a maximum of only 18%. Incontrast, the absorbance of the particulate fractionwas similar to the absorbance of the filtered sample inlate May, contributing 43% of the unfiltered absor-bance but increased to over 300% by late June as thephytoplankton abundance increased, contributing68% of the absorbance in an unfiltered sample.The effects of true color and particulate substances

on transparency can be empirically separated. In ananalysis of transparency in a synoptic survey of 205Florida lakes, Canfield and Hodgson developed aregression model that predicted Secchi depth (SD) as

a function of chlorophyll a concentration (Chl a) andtrue color (C),

lnðSDÞ ¼ 2:01� 0:37lnðChl aÞ � 0:28lnðCÞ; R2 ¼ 0:78 ½5�where chlorophyll concentration is in m grams perliter and color is in Pt units. A similar relationshipbetween long-term mean color and long-term meanSD was observed in the Dorset, Ontario, study lakeswhere chlorophyll levels are low,

lnðSDÞ ¼ 2:77� 0:43lnðCÞ; R2 ¼ 0:94 ½6�

Effect of Color on Thermal Structureof Lakes

It has long been recognized that the depth of the mix-ing layer during the ice-free season is influenced bymixing energy (e.g., wind speed), which, in turn,is affected by morphometric factors such as lake area(a surrogate for fetch) and the degree to which the lakesurface is protected from winds by surrounding hills.

DOC (often used as an indicator of color) alsohas a significant effect on the thermal structure ofunproductive boreal lakes, especially in small lakeswith surface areas less than 700 ha, although windexposure also affects thermal structure in small lakes.Color affects thermal structure by increasing theabsorption of visible solar radiation, a major sourceof heat, in shallower waters, which limits the heatgained by deeper waters. In lakes larger than 700 ha,mixing depths are controlled primarily by featuresthat affect wind speed.

As a result of increased absorption in shallowerwater, unproductive colored lakes have the followingfeatures: (1) the thermocline is closer to the surface at

20

21

22

23

True color, Pt units

Tem

pera

ture

, �C

160140120100806040200

Figure 7 Mean July temperature in upper waters (0–3m)

versus true color in seven lakes near Dorset, Ontario 1984–86.Color from volume-weighted epilimnetic samples. Data provided

by the Ontario Ministry of the Environment.

Light and Heat in Aquatic Ecosystems _ Color of Aquatic Ecosystems 661

the end of the summer and hence the hypolimnion islarger, and (2) the hypolimnion is cooler.Several regression relationships have been devel-

oped to predict mixing depth or thermocline depthfor small lakes on the Precambrian Shield in centralOntario, Canada. In each of the formulas, the mostimportant predictor of mixing depth was the DOCconcentration with smaller contributions from othervariables. The mean July–August thermocline depth,Zther (defined as the depth with the maximum densitydifference between successive depths), for a six-yearperiod in 54 lakes ranging in area from 2.3 to 679 haand with maximum effective length (MEL) between0.2 and 6.1 km was estimated as

LogðZtherÞ ¼ �0:515 logðDOCÞ þ 0:115 logðMELÞ þ 0:991;

R2 ¼ 0:81 ½7�In a separate study,Zther at the end of August for a two-year period in 21 lakes ranging in area from 3.4 to795ha and with the fetch ranging from 0.2 to 2.8 km,was estimated as

Zther ¼ �1:25DOCþ 0:04DTSþ 9:65; R2 ¼ 0:72 ½8�where DTS is the number of days to onset of stratifica-tion after ice-out. Lake area was not a significant vari-able in the latter study and fetch was not consideredalthough the two variables are strongly correlated.A consequence of a shallower mixing layer is a

larger, cooler hypolimnia. Several studies of smalllakes on the Precambrian Shield in central Ontarioillustrate the inverse relationship between DOC (i.e.,color) and the size of the hypolimnion. The studiesfocused on the size of lake trout habitat, a species thatfavors temperatures cooler than 10 �C, developingregression formulas to predict the depth at which10 �C occurred, Z10. In a 22-year study of one smalllake recovering from acidification, Z10 at any timeafter ice-out is given by

Z10¼�2:999DOCþ0:003W �0:373Tþ19:224;R2¼0:83 ½9�where W is wind-days (the product of mean dailywind speed and number of ice-free days) and T isthe mean daily air temperature. In a second study of37 small lakes sampled from 3 to 19 years each (mean13 years), Z10 at the end of August is given by

Z10¼11:3=DOCþ0:139ffiffiffi

Ap

þ3:52;R2¼0:88 ½10�where A is the lake area. W and A are similar in thatthey provide information on wind energy, although Aonly provides indirect information. While W has theadvantage of including both the length of timebetween ice-out and the target date, and actual windspeed, on-site wind speed data and accurate ice-outdates may not be readily available in some cases.Hence, A is more expedient.

Increased absorption of solar radiation by coloredsurface waters raises the possibility that colored surfacewaters may be warmer than clear surface waters. How-ever, evidence to support this in thermally stratifiedlakes is lacking. In Ontario, there were no major differ-ences in mean July epilimnetic temperatures (1984–86)among six stratified lakes with color <40Pt units(Figure 7). The epilimnetic temperature in a seventhOntario lake with 143 Pt units was 0.2–0.5 �C coolerthan two of the lakes with <4Pt units. The epilimnionof very small, colored Mustalamni Lake in Finland(230Pt units) was about 2 �C cooler than very smalland much clearer Lake Iso Valkjarvi (7 Pt units) on onesampling day in lateMay. Based on this small data set, itappears that the impact of greater absorption of solarradiation by colored waters on water temperature isnot large. Perhaps increased absorption is offset byincreased heat loss from a thinner mixing layer to theatmosphere. However, in unstratified ponds and lakeswith fixed mixing depths, colored waters may indeedbe warmer than uncolored waters.

Consequences of Human Impactson Color

Since true color is primarily a function of CDOCin the absence of wastewater discharges, changes inCDOC concentration over time will affect light trans-mission and thermal structure in lakes. Althoughannual and seasonal variation about a long-termmean CDOC concentration is a natural feature ofaquatic systems, human activities may result in long-term shifts in mean annual CDOC concentrations,and consequently, long-term shifts in light transmis-sion and lake thermal structure. This section brieflyconsiders the effects of human activities.

662 Light and Heat in Aquatic Ecosystems _ Color of Aquatic Ecosystems

Susceptibility to Change in Color

While the long-term, mean relationship between colorand CDOC is approximately linear, the relationshipbetween color and light transmission is exponential(Figure 5) with small changes in CDOC causing rela-tively large changes in light transmission and heating inclear lakes. For example, a decrease of 10Pt unitsresults in an increase in the euphotic zone depth of6 cm for a lake with 200Pt units. The same absolutedecrease of 10 Pt units produces an increase of 50 cm ina lake with 30 Pt units. Similarly, eqn. [9] predicts that aDOC loss of 0.76 mg carbon�per liter (which corre-s pond s t o a c olo r o f a ppr oxi ma te ly 10 Pt un its ) w oul dresult in Z10 becoming 15 cm deeper in a lake withinitial DOC of 8mg carbon�per liter and 1.28m deeperin a lakewith 3mg carbon�per liter.While thesemodelsdiffer in the magnitude of the displacement of Z10 andZther, both illustrate that clear lakes are more suscepti-ble to absolute changes in CDOC concentration andany associated ecological changes.In Canada, most ecozones outside of the prairies

have large numbers of low DOC (<3mg carbon�perliter) systems, especially on the Precambrian Shieldand in the arctic. The proportion of low DOC systemswill vary globally, being a function of the extent ofpeatlands and annual runoff.

Drivers of Color Change

Two drivers of color change for which adequate dataare available are atmospheric acidification and runoff(water discharge). Color is particularly susceptible toacidification. Acidification of surface waters belowpH 6 greatly enhances iron-mediated, photooxidative

5.0

6.0

7.0

8.0

9.0

10.0

1978–79

1980–81

1982–83

1984–85

1986–87

198889

Col

or

Figure 8 Annual runoff (q, m year�1), annual volume-weighted truePlastic Lake, Ontario. Data provided by the Ontario Ministry of the En

loss of CDOC in surface waters via the photo-Fentonpathway. Acidification has been reversed to a signifi-cant extent in North America and Europe in recentyears but still remains an important issue regionally.

Runoff controls CDOC export from peatlands, amajor source of colored substances, to adjacent sur-face waters, and therefore, runoff affects lake CDOCconcentration and color (Figure 8). Hence, a drierclimate with declining export will produce clearerlakes, and a wetter climate more colored lakes.While changes in export are proportional to changesin runoff, downstream changes in lake DOC concen-tration and color will be less than changes in exportbecause of a dampening effect predicted by the steadystate mass balanc e model (eqn. [1]) .

While the general impacts of runoff and acidificationon color are relatively clear, the net impacts of climatechange are much more difficult to predict because theimpactsmay be driven by both temperature and runoff,and regional predictions of runoff may not be asreliable as those for air temperature. Furthermore, thenet effect of temperature on the color of surface waterscould either be reinforced or masked by the effect oftemperature on terrestrial processes and by changes inrunoff, assuming that the extent of peatlands remainsconstant. For example, a warmer climate would resultin higher respiration rates of CDOC and, therefore,clearer lake waters, but the increased clarity could bemasked by increased export rates of CDOC as a resultof higher runoff and higher microbial production ofCDOC in peatlands. On the other hand, the effect ofhigher in-lake respiration rates of CDOC could bereinforced by decreasing runoff. It is not clear, there-fore, how lake colorwill respond to a changing climate.

– 1990–91

1992–93

1994–95

1996–97

1998–99

1.2

1.4

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2.0

2.2

2.4

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3.0

q,D

OC

ColorDOCq

color (Pt units) and annual volume-weighted DOC (mg l�1) invironment.

Light and Heat in Aquatic Ecosystems _ Color of Aquatic Ecosystems 663

See also: Carbon, Unifying Currency; Global Distributionof Wetlands; Ice; Light, Biological Receptors; Turbidity;Ultraviolet Light.

Further Reading

Cahill KL, Gunn JM, and Futter MN (2005) Modelling ice cover,

timing of spring stratification, and end-of-season mixing depth in

small Precambrian Shield lakes. Canadian Journal of Fisheriesand Aquatic Science 62: 2134–2142.

Canfield DE and Hodgson LM (1983) Prediction of Secchi disc

depths in Florida lakes: impact of algal biomass and organic

color. Hydrobiologia 99: 51–60.Dillon PJ, Clark BJ, Molot LA, and Evans HE (2003) Predicting the

location of the optimal habitat boundaries for lake trout (Salve-linus namaycush) in Canadian Shield lakes. Canadian Journal ofFisheries and Aquatic Science 60: 959–970.

Fee EJ, Hecky RE, Kasian SEM, and Cruikshank DR (1996) Effects

of lake size, water clarity, and climatic variability on mixing

depths in Canadian Shield lakes. Limnology and Oceanography41: 912–920.

Hutchinson GE (1957) ATreatise on Limnology. Volume 1, Geog-raphy, Physics and Chemistry. New York: John Wiley and Sons.

Keller W, Heneberry J, and Leduc J (2005) Linkages betweenweather, dissolved organic carbon, and cold-water habitat in

a Boreal Shield lake recovering from acidification. CanadianJournal of Fisheries and Aquatic Science 62: 341–347.

Mazumder A and Taylor WD (1994) Thermal structure of lakesvarying in size and water clarity. Limnology and Oceanography39: 968–976.

Molot LA and Dillon PJ (1997) Colour-mass balances and colour-

dissolved organic carbon relationships in lakes and streams incentral Ontario. Canadian Journal of Fisheries and AquaticScience 54: 2789–2795.

Molot LA, Hudson JJ, Dillon PJ, and Miller SA (2005) Effect of

pH on photo-oxidation of dissolved organic carbon byhydroxyl radicals in a coloured, softwater stream. AquaticSciences 67: 189–195.

Molot LA, Keller W, Leavitt PR, et al. (2004) Risk analysis of

dissolved organic carbon-mediated UVB exposure in Canadianinland waters. Canadian Journal of Fisheries and AquaticSciences 61: 2511–2521.

Pace ML and Cole JJ (2002) Synchronous variation of dissolved

organic carbon and color in lakes. Limnology and Oceanogra-phy 47: 333–342.

Perez-Fuentetaja A, Dillon PJ, Yan ND, and McQueen DJ (1999)

Significance of dissolved organic carbon in the predictionof thermocline depth in small Canadian shield lakes. AquaticEcology 33: 127–133.

Ruttner F (1963) Fundamentals of Limnology. Toronto: Universityof Toronto Press.

Salonen K, Arvola L, and Rask M (1984) Autumnal and vernal

circulation of small forest lakes in Southern Finland. Verhan-dlungan International Verein Limnology 22: 103–107.

Snucins E andGunn JM (2000) Interannual variation in the thermalstructure of clear and colored lakes. Limnology and Oceanogra-phy 45: 1639–1646.

Wetzel RG (2001) Limnology: Lake and River Ecosystems,3rd edn. New York: Elsevier.