1130
Gross primary production and respiration
differences among littoral and pelagic habitats
in northern Wisconsin lakes
George H. Lauster, Paul C. Hanson, and Timothy K. Kratz
Abstract: Net ecosystem production (NEP) trends among lakes have been ascribed to differences in nutrient and
allochthonous carbon inputs, but little is known on how different habitats within lakes contribute to these trends. We
sampled pelagic and littoral surface waters using sonde (i.e., free-water) and bottle methods concurrently in lakes spanning a range of trophic conditions. We considered whether the typically higher metabolism estimates found with sonde
methods are due to contributions from littoral habitats not reflected by bottle estimates. We sought the source of littoral
contributions by selecting sites with maximum differences in macrophyte abundance. Sonde estimates for pelagic primary production and respiration were two–three times greater than bottle estimates. Sonde/bottle ratios were higher in
productive lakes and lakes with more littoral area. Bottle estimates were similar among all sites, and sonde estimates in
macrophyte-poor sites were similar to pelagic sondes. However, sonde estimates in macrophyte-rich areas were four–
nine times greater than bottle estimates. Results suggest littoral zones increase whole-lake NEP in eutrophic systems,
whereas the Sphagnum mat surrounding dystrophic lakes decreases NEP. Non-planktonic organisms associated with
macrophytes provide important littoral contributions to whole-lake metabolism and to understanding NEP trends among
lakes.
Résumé : On explique les variations de la production nette de l’écosystème (NEP) des lacs par des différences dans
les apports de nutriments et de carbone allochtone, mais on connaît mal de quelle façon les différents habitats des lacs
contribuent à ces tendances. Nous avons échantillonné les eaux de surface pélagiques et littorales simultanément dans
des lacs représentant une gamme de conditions trophiques au moyen des méthodes de la sonde (c.-à-d., en eau libre) et
de la bouteille à prélèvement. Nous avons examiné si les estimations plus élevées généralement obtenues par la
méthode de la sonde sont dues à des contributions des habitats littoraux non représentées dans les estimations faites à
partir de la méthode de la bouteille. Nous avons recherché la source des contributions littorales en choisissant des sites
qui présentent des différences maximales d’abondance de macrophytes. Les estimations à la sonde de la production
primaire et de la respiration pélagiques sont deux–trois fois plus élevées que les estimations à la bouteille. Les rapports
sonde:bouteille sont plus forts dans les lacs productifs et dans les lacs ayant une plus grande zone littorale. Les
estimations à la bouteille sont semblables dans tous les sites et les estimations à la sonde dans les sites pauvres en
macrophytes ressemblent aux estimations à la sonde dans la zone pélagique. Cependant, les estimations faites à la
sonde dans les zones riches en macrophytes sont quatre–neuf fois plus élevées que celles à la bouteille. Nos résultats
indiquent que les zones littorales augmentent la NEP dans l’ensemble du lac dans les systèmes eutrophes, alors que les
tapis de sphaignes qui entourent les lacs dystrophes réduisent la NEP. Les organismes non planctoniques associés aux
macrophytes fournissent des contributions littorales importantes au métabolisme de l’ensemble du lac; ils permettent de
comprendre les tendances de la NEP parmi les lacs.
[Traduit par la Rédaction]
Lauster et al.
1141
Introduction
Ecosystem respiration (R) tends to exceed gross primary
production (GPP) in the pelagic surface waters of north temperate lakes, resulting in negative net ecosystem production
(NEP = GPP – R) (del Giorgio and Peters 1994; Cole et al.
2000). Although evidence suggests that allochthonous carbon loading drives this balance (Jansson et al. 2000; Prairie
et al. 2002; Hanson et al. 2003), little is known about how
different lake habitats contribute to whole-ecosystem metabolism estimates, especially when estimates are based on
free-water dissolved gas measured at pelagic sites. The con-
Received 6 November 2004. Accepted 22 December 2005. Published on the NRC Research Press Web site at http://cjfas.nrc.ca on
19 April 2006.
J18399
G.H. Lauster1 and P.C. Hanson. Center for Limnology, University of Wisconsin, 680 North Park Street, Madison, WI 53706,
USA.
T.K. Kratz. Trout Lake Station, Center for Limnology, University of Wisconsin-Madison, 10810 County Highway N, Boulder
Junction, WI 54512, USA.
1
Corresponding author (e-mail: [email protected]).
Can. J. Fish Aquat. Sci. 63: 1130–1141 (2006)
doi:10.1139/F06-018
© 2006 NRC Canada
Lauster et al.
tributions of periphyton and macrophytes (Lodge et al. 1998;
Vadeboncoeur et al. 2001, 2002) and sediment organisms
(den Heyer and Kalff 1998) to whole-ecosystem metabolism
are potentially quite large. The degree to which such littoral
processes affect pelagic dissolved gas will depend, in part,
on the relative magnitude of littoral versus pelagic metabolism.
Littoral contributions to surface water metabolism may
help explain discrepancies between pelagic sonde (freewater) and bottle incubation estimates of lake metabolism.
Studies using dissolved oxygen (DO) sondes, in which
changes are measured directly in the water column (Cole et
al. 2000; Hanson et al. 2003), yield estimates of GPP and R
that are two–three times higher than those in studies using
bottles (del Giorgio and Peters 1994; Carignan et al. 2000).
One study in which bottle and sonde estimates of R were
made concurrently found that bottle estimates were consistently lower (Hanson 2003). Investigators using non-sonde,
free-water estimates of photosynthesis have also found these
to be similar to or in excess of estimates from bottles
(Melack 1982). Although differences may be due to container effects or uncertainties in scaling from bottles to lakes
(Schindler and Fee 1973; Fee 1980; Schindler 1998), we focus on an alternative explanation — that sondes and bottles
measure different components of metabolism (Hanson et al.
2003). Bottle experiments measure pelagic planktonic metabolism, whereas sondes integrate planktonic metabolism
and contributions from the hypolimnion and littoral zone.
The differences in estimates from the two approaches may
provide valuable information about littoral contributions to
whole-lake metabolism.
Incorporating the littoral zone into our understanding of
whole-lake metabolism is complicated by the variety of littoral metabolism sources, some of which occur in the water
column while others occur in the macrophytes or sediments.
These sources may be broadly distinguished by using both
bottle and sonde measurements. In littoral habitats where
non-plankton biota such as macrophytes and sedimentassociated organisms are substantial, we expect sonde estimates of metabolism to reflect this additional non-planktonic
activity, while bottle estimates would not. Mixing or
resuspension events can also cause detectable changes in a
variety of important chemical and biological variables, including nutrients (MacIntyre et al. 1999), phytoplankton,
and suspended sediments (Hamilton and Mitchell 1997). Resuspended sediments can elevate ecosystem R (Biddanda
and Cotner 2002), enhance primary productivity in some
systems (Ogilvie and Mitchell 1998), or reduce it in others
(Hellstrom 1991), depending on degree of nutrient upwelling
versus light attenuation. We expect both sonde and bottle
methods to detect mixing- or resuspension-induced enhancements to water-column metabolism.
We examine whether differences in biota associated with
the water column, sediment, or macrophytes impact metabolic estimates using paired measurements by sonde and
bottle methods in pelagic sites and in two littoral sites differing in macrophyte abundance. We apply this sampling regime to lakes of differing trophic status to gauge the
influence of nutrient concentration on littoral versus pelagic
contributions to whole-lake metabolism. We use data obtained from the sonde and bottle methods to explore the fol-
1131
lowing questions. Are sonde estimates of GPP and R greater
than those of bottle estimates? What do comparisons between littoral zone bottle and sonde measurements tell us
about contributions by benthos, macrophytes, or littoral water column to whole-lake metabolism? Do littoral contributions to whole-lake metabolism differ across trophic
conditions? Our answers indicate that littoral habitats, and
particularly macrophytes, can be a source of metabolism differences among lakes.
Materials and methods
Study sites and field sampling
We sampled lakes from the Northern Highland Lake District of northern Wisconsin during the summer of 2002.
Seven lakes were chosen to include one or two lakes from
each of four lake types and to differ in extent of littoral zone
coverage (Table 1). Lake trophic status is noted as a subscript in the following lake abbreviations: oligotrophic
(SPO), mesotrophic (BMM, ALM), eutrophic (LAVE, MUE),
and dystrophic (TBD, CBD). ALM and SPO were studied during two periods to contrast the beginning (AL1M, SP1O) and
peak (AL2M, SP2O) of macrophyte growth. Three sites were
chosen in each lake to span the range of conditions available. Pelagic sites were located above the deepest location in
each lake. Macrophyte sites were located in the littoral area
of maximum macrophyte density. Sediment littoral sites
were chosen that had no or minimal macrophyte density.
Macrophyte sites may have differred from sediment sites not
only because of presence of plants and associated microbes,
but also indirectly through macrophyte effects on turbulence,
circulation, temperature, and resuspended material. Temperature differences among all three sites were always less than
1 °C. Bottle samples from macrophyte sites should have captured some of the effect of resuspended material on metabolism; however, any other effects of turbulence and
circulation could not be separated from biotic effects at
macrophyte sites. Site locations were chosen based on previous knowledge of macrophyte beds and field observations
(Stelzer 1999; North Temperate Lake Long Term Ecological
Research Station 2004). Sites in the two dystrophic lakes
had conditions differing from those in the other five lakes.
Dystrophic lake macrophytes were limited to floating Sphagnum mats along the lake edge. In dystrophic lakes, the
macrophyte site sonde was located within 1 m of the
macrophytes along the lake edge, while the third site was
positioned midway between the pelagic and macrophyte
sites. There was no equivalent midway site in the nondystrophic lakes; therefore, these sites were not included in
any comparison of sediment and macrophyte sites and in any
statistical analysis.
Water-column profiles of temperature and DO were collected at each site using a YSI DO meter (model 52, YSI
Inc., Yellow Springs, Ohio). Water-column samples were
collected in an integrated sample from the mixed layer.
Color was quantified as absorbance at 440 nm on a Kontron
930 spectrophotometer (Kontron Instruments) for lake water
prefiltered by 0.4 µm pore size, polycarbonate track-etched
filter, using ultrapure water as a standard (NANOpure system, Barnstead, Dubuque, Iowa). Phytoplankton were collected on precombusted Whatman GF/F filters (Whatman
© 2006 NRC Canada
1132
Can. J. Fish Aquat. Sci. Vol. 63, 2006
Table 1. Characteristics of sites in the seven study lakes.
Lake
Sparkling*
(SP1O)
Crystal Bog
Site
P
S
M
P
(CBD)
Mid
M
Allequash*
P
(AL1M)
S
M
Trout Bog
P
(TBD)
Mid
M
Sparkling*
P
(SP2O)
S
M
Little Arbor Vitae
P
(LAVE)
S
M
Allequash*
P
(AL2M)
S
M
Muskellunge
P
(MUE)
S
M
Big Muskellunge
P
(BMM)
S
M
Location
46°00.449′N
89°36.376′W
46°00.469′N
89°36.368′W
46°00.469′N
89°36.365′W
46°02.290′N
89°37.170′W
46°02.429′N
89°37.059′W
46°02.670′N
89°37.549′W
46°02.471′N
89°41.181′W
46°02.462′N
89°41.169′W
46°02.441′N
89°41.146′W
46°00.489′N
89°42.070′W
46°00.341′N
89°42.159′W
46°00.244′N
89°41.775′W
45°54.826′N
89°37.077′W
45°54.966′N
89°36.874′W
45°55.051′N
89°37.576′W
46°02.290′N
89°37.171′W
46°02.429′N
89°37.045′W
46°02.668′N
89°37.545′W
45°56.925′N
89°22.779′W
45°57.005′N
89°23.025′W
45°75.384′N
89°22.766′W
46°01.283′N
89°36.709′W
46°01.205′N
89°36.556′W
46°00.534′N
89°37.397′W
Area
(ha)
64.0
64.0
64.0
0.5
Littoral
area (%)
16
16
16
0
Depth
(m)
3.0
2.0
2.1
0.5
Temperature
(°C)
15.1
15.1
15.0
18.2
MI
—
0
1
—
ηt
(m–1)
0.42
—
—
1.91
Color
(cm–1)
–0.003
–0.001
–0.002
0.139
Chl a
(µg·L–1)
2.0
1.7
1.6
—
TOC
(mg·L–1)
3.7
—
—
10.2
—
—
—
0.5
0
1.9
18.3
—
—
0.5
0
1.3
18.4
—
—
0.131
168.4
35
2.0
19.5
—
0.74
0.049
168.4
35
3.1
19.4
1
—
0.048
—
4.2
168.4
35
2.1
19.5
3
—
0.107
10.2
4.0
1.1
0
1.0
17.0
—
3.13
0.497
56.8
24.4
1.1
0
7.1
18.4
—
—
—
—
1.1
0
1.8
18.0
—
—
0.545
32.7
23.7
64.0
16
3.0
25.1
—
0.35
0.036
1.4
64.0
16
2.5
25.2
0
—
0.010
1.2
3.8
64.0
16
2.3
25.8
2
—
0.009
1.2
3.6
216.1
42
3.0
26.5
—
1.67
0.0203
9.3
4.2
216.1
42
2.8
26.3
0
—
0.0220
8.8
4.1
216.1
42
1.7
26.7
2
—
0.0191
12.8
4.2
168.4
44
3.0
26.1
—
0.74
0.0485
0.3
—
168.4
44
2.2
26.6
2
—
0.0477
0.3
—
168.4
44
1.8
26.7
3
—
0.0503
0.9
—
107.7
100
4.7
22.9
—
1.51
0.0638
74.7
107.7
100
2.3
23.2
0
—
0.0681
56.5
—
107.7
100
2.1
23.3
3
—
0.0651
66.2
—
396.3
55
8.0
23.1
—
0.31
0.0081
2.3
396.3
55
2.5
23.2
0
—
0.0079
1.9
—
396.3
55
1.3
23.4
2
—
0.0126
7.5
—
—
—
5.1
9.5
5.8
—
7.3
3.9
Note: Lake names are followed by a two–three letter abbreviation and subscript denoting trophic status: oligotrophic (O), mesotrophic (M), eutrophic
(E), or dystrophic (D). Site refers to pelagic (P), macrophyte (M), sediment (S), or middle (Mid) sampling stations. Littoral area is the percentage of lake
area with sediments in the epilimnion. Depth refers to either depth to sediments (littoral sites) or to depth of top of the thermocline (pelagic sites).
Macrophyte index (MI) ranges from 0 (none) to 3 (high density). Vertical extinction coefficients (η t ) are from photosynthetically active radiation (PAR)
measurements. Color is absorbance of lake water at 440 nm compared with ultrapure water. Chl a is chlorophyll a concentration. TOC is total organic
carbon concentration. Site coordinates were not measured for SP1. Dashes indicate other measurements that were not available.
*Sparkling and Allequash lakes were studied twice, at the beginning (SP1O, AL1M) and peak (SP2O, AL2M) of macrophyte growth.
© 2006 NRC Canada
Lauster et al.
1133
Inc., Clifton, New Jersey) for chlorophyll a analysis (Marker
et al. 1980). Two independent observers using an underwater camera characterized macrophyte biomass (height and
abundance) in a ~5 m radius around each site as a macrophyte index of 0 (no macrophytes), 1 (low density), 2 (medium density), and 3 (high density). Light extinction
coefficients were measured each week, or adjacent week, at
the pelagic site by the North Temperate Lakes Long Term
Ecological Research (NTL-LTER) program. Total organic
carbon (TOC) and total inorganic carbon (TIC) were determined by chemical oxidation on an Ionics TOC analyzer
(Ionics Co., Watertown, Massachusetts). An instrument raft
moored on Sparkling Lake measured photosynthetically active radiation (PAR), wind speed, and precipitation every
half hour. Distances from lakes to the raft were less than
8 km, except for LAVE (14 km) and MUE (26 km).
Lake areas were taken from the NTL-LTER database or
the Surface Water Resource of Vilas County (Black et al.
1963). The extent of littoral zone that potentially impacts
our epilimnetic metabolism estimates was calculated from
digitized bathymetric and contour maps and was defined as
any part of the lake with a depth to sediments less than or
equal to the depth of the thermocline. At this depth, adequate light of at least 1% surface PAR was present in all
lakes except MUE, where macrophytes were observed at the
deepest location. Littoral percent for each lake was calculated from the digitized images as the ratio of pixels in the
littoral area to pixels for the entire lake.
duction in clear bottles (NPPbottle). Changes in DO were analyzed by the Winkler reaction according to detailed procedures outlined in Carignan et al. (1998) unless noted
otherwise. Rbottle estimates are based on six initial and six final replicates (only four replicates in SP1O), and NPPbottle
estimates are based on 10 light levels for which half were
replicated. From each bottle a 3 mL rinse and 3 mL sample
were aliquoted into a 1 cm2 cuvette, and the Winkler reaction end product I2 was quantified spectroscopically as the
absorbance at 430 nm (Roland et al. 1999). The equation relating absorbance at 430 nm to DO concentration was prepared by additionally estimating I2 visually by sodium
thiosulfate titration using a buret with a volume resolution of
0.025 mL. Titrations were performed on the remaining solution in 10–15 bottles per lake, thereby covering a DO range
between 6.70 and 10.67 mg·L–1. Thiosulfate concentration
was calibrated each day from three replicate titrations of
iodate standard (precision mean = 0.46%, standard deviation
(SD) = 0.27%, n = 9). The final DO equation was DO =
3.22 + 0.00501 × CA (n = 121, R2 = 77.5%, p < 0.0005),
where CA is absorbance at 430 nm corrected for turbidity
quantified as absorbance at 750 nm, with absorbance multiplied by 1000 (Roland et al. 1999). All solutions were commercially prepared (Lab Chem, Pittsburgh, Pennsylvania;
Fisher Scientific, Fair Lawn, New Jersey). DO concentration
outliers were removed only if they differed from other replicates by at least 2 SDs (14 occurrences among 756 total measurements).
Bottle estimates of metabolism
Metabolism measurements by both bottles and sondes
were limited to the epilimnetic portion of pelagic and littoral
zones. Bottle metabolism estimates were generated from the
DO method (GPPbottle, Rbottle, NEPbottle) using a lab incubator
with a 1000 W Multi-Vapor light (model MV 1000/u; General Electric Company, Fairfield, Connecticut) providing a
gradient of irradiance levels (Adams et al. 1990). Irradiance
levels were measured at each bottle position during each incubation. Incubation temperature was adjusted throughout
the incubation to remain within 1 °C of in situ temperature.
All GPP and R bottles were incubated concurrently. GPP
bottles were incubated for 6 h, while R bottles were incubated for 12–20 h, depending on lake productivity. GPPbottle
was measured from samples taken at all three sites in each
lake, except in the two dystrophic lakes where it was measured from samples taken only at the pelagic and
macrophyte sites, for a total of 25 measurements. Depthintegrated samples for bottle methods were collected from
the mixed layer within 2 h of dawn using a rinsed polyvinyl
chloride tube with shut-off valve and transported to the lab
in a dark, rinsed 20 L carboy. Pelagic samples were collected from the surface to the top of the thermocline, while
littoral samples were collected from the surface to a few
centimetres above the sediments, avoiding sediment resuspension and inclusion in samples. Lake water was mixed
and aliquoted into autoclaved 60 mL BOD bottles (Roland et
al. 1999; Wheaton Science Products, Millville, New Jersey)
using a carboy with floating lid (Carignan et al. 1998). Respiration bottles were previously coated with black rubber.
The bottle method used changes in DO concentration to
estimate R in opaque bottles (Rbottle) and net primary pro-
Calculation of bottle primary production
Production–irradiance (P–I) curves were generated from
the primary production estimates from the GPPbottle method
using the procedure outlined for the 14C method at our study
site (Adams et al. 1990). P–I parameters were estimated using the model of Platt et al. (1980) for each P–I curve. Chlorophyll a was assumed to be constant during the week of
sample collection and GPP estimation; therefore, production
values and model parameters were not normalized to chlorophyll a. Both primary production and R occur in the clear
bottles for the DO method, resulting in estimates of net primary production. GPPbottle values were estimated by adjusting all NPPbottle values, such that there was zero primary
production at the 0 µmol quanta·m–2·cm–2 light level. In situ
PAR was estimated at each half metre from surface PAR,
and light extinction coefficients were measured at the pelagic location. In situ GPP was estimated at each half hour
and half meter depth at each site from P–I model coefficients and light levels. GPP was summed over all depths and
during the entire daylight period to provide the areal daily
estimate of GPPbottle in units of mg O2·m–2·day–1. We lacked
information to account for loss of the irradiance spectrum
usable by photosynthesis with depth caused by DOC and
phytoplankton absorption (Markager and Vincent 2001). The
effect of this spectral shift would be overestimation of GPP
by our bottle method, particularly in the high-DOC lakes
CBD and TBD. Differences between bottle and sonde estimates of GPP in this study are therefore conservative.
Sonde estimates of metabolism
Three sondes were deployed simultaneously to sample
DO and water temperature for 3–5 days on each lake. Sonde
© 2006 NRC Canada
1134
estimates of metabolism assumed a vertically well-mixed
epilimnion at the time scale of our study to reflect depthdependent changes in metabolism. DO and water temperature were measured with YSI model 600-XLM sondes (YSI
Inc.) fitted with Rapid Pulse oxygen probes (model 6562;
YSI Inc.) and temperature sensors. Each sonde was attached
to a small float that was anchored to the bottom of the lake.
DO and water temperature were sampled every 10 min at a
depth of 1 m. The assignment of sondes to lake locations
was randomized for each lake. Before deployment, each DO
probe was reconditioned and calibrated in air, with a correction for barometric pressure. Calibrations were repeated after
retrieval, and data were corrected by assuming linear drift
between calibrations.
We used the models as described in Hanson et al. (2003)
for calculating GPP, R, and NEP from diel DO data. The following is a brief description as it applies to each sonde. During darkness, the change in gas concentration for each 10
min interval was assumed to be due to R and flux with the
atmosphere (F). During daylight hours, changes in gas concentrations were assumed to be due to R, F, and GPP. We
calculated metabolism for each 10 min interval and divided
by the day fraction to get an estimate for R at night or NEP
during day. We calculated R for each 10 min interval from
30 min past dusk until 30 min before dawn. The results were
divided by the day fraction to produce estimates for 24 h R,
which then were averaged to produce reported values for
each lake (Rsonde; Table 2). Our methods differed from
Hanson et al. (2003) in that we measured DO every 10 min
instead of every 30 min and we assumed a piston velocity
(K600) of 0.5 m·day–1.
We calculated NEPdaylight for each 10 min interval from 30
min past dawn until 30 min before dusk. The results were divided by the day fraction, which in turn were multiplied by
the fraction of the day during which light was greater than
10 µmol photons·m–2·s–1. This produced estimates for
NEPdaylight. GPP was the sum of NEPdaylight and Rdaylight.
Rdaylight was estimated by multiplying R by the fraction of
the day during which light was greater than 10 µmol
quantam–2·s–1. We assumed daytime R equaled nighttime R,
in keeping with the literature (Carignan et al. 2000; Cole et
al. 2000). Individual estimates of GPP were averaged for
each lake to produce reported values (GPPsonde; Table 2).
NEPsonde was calculated as the difference between Rsonde and
GPPsonde.
We realize there is uncertainty in our assumptions about
gas transfer velocity coefficient, K600, and that the uncertainty may influence the sonde metabolism estimates. It is
possible that highly turbulent water would have a higher
K600 and a corresponding higher atmospheric F component
than calm surface waters. It also is possible that
microstratification could create a barrier between much of
the mixed layer and the atmosphere, resulting in a lower
K600 and a corresponding lower F estimate than the nominal
conditions. Although we do not have the data to adequately
characterize the turbulence of the system or the thermal
stratification, we explore the sensitivity of our results to our
assumptions for K600 through a Monte Carlo analysis. We
use a random number generator to create a normal distribution of 1000 K600 values, with a distribution mean of
Can. J. Fish Aquat. Sci. Vol. 63, 2006
0.5 m·day–1 (Cole and Caraco 1998) and a standard deviation of 0.25 m·day–1. Because a negative K600 value is not
possible, we truncate the distribution at 0 and 1 (for symmetry), setting all values <0 to 0 and all values >1 to 1. We reran the metabolism model 1000 times, using the 1000 K600
values, and report the standard deviations of R, GPP, and
NEP in Table 2.
Data analysis
We were concerned about meteorological effects causing
differences between metabolism estimates made using bottle
and sonde methods and on different lakes — especially turbulence and mixing due to high winds. We therefore used
data only from days that were mostly sunny and had low
wind speeds according to data collected from the instrument
raft moored in Sparkling Lake. There were at least two such
days for each lake. For each site in each lake, we averaged
individual estimates for GPP and R, resulting in GPPbottle
and GPPsonde estimates for each location in each lake (Table 2).
We analyzed for location effects by one-way analysis of
variance (ANOVA) of sonde/bottle means by site and lake
trophic status. We analyzed for method effects using a t test
to determine if paired sonde and bottle differences were
greater than zero. We based our interpretation for ecosystem
implications on summaries of data across both sites and
methods.
We examined whether extent of littoral habitat contributes
to pelagic sonde/bottle R and GPP using least-squares regression analysis. Bog lakes were excluded from the regression analysis because of the metabolic effect of their littoral
area not being captured by our definition. Bog lakes CBD
and TBD had zero littoral area by our definition despite being surrounded by extensive and metabolically active bog
mats. We graphically analyzed the effect littoral habitats
may have on NEP, utilizing the macrophyte and sediment
sites as a possible range of littoral conditions.
Statistical analyses were conducted using Minitab 8
(Minitab Inc., State College, Virginia) and a significance
level of p ≤ 0.05. All variables in the form of ratios or percentages were square-root-transformed (ANOVA) or logtransformed (regression) to meet parametric assumptions as
indicated by the Shapiro–Wilk test for normality and the
Brown–Forsythe modification of the Levene test for homogeneous variance (Upton and Cook 2004). Post-analysis
comparisons for ANOVA utilized Tukey’s paired comparison
procedure with a total error rate of 5%.
Results
Lakes spanned a wide range of chlorophyll a (0.3–
66.2 µg·L–1) and color (–0.003–0.545 cm–1) conditions (Table 1). The percent littoral area ranged from 0% in the
dystrophic systems to 100% for the shallow eutrophic lake
(MUE). All other percentages ranged from 16% to 55% littoral. Sites were generally shallow, with depth to sediment or
thermocline greater than 3.1 m for only 3 of the total 27
sites. For Allequash Lake, there were no littoral areas without macrophytes, so a site with the lowest macrophyte density was chosen as the sediment location. A site without
© 2006 NRC Canada
Lauster et al.
1135
Table 2. Respiration (R; mg O2·m–2·day–1), gross primary production (GPP; mg O2·m–2·day–1), net ecosystem
production (NEP; mg O2·m–2·day–1), and mean sonde temperature (Tempsonde; °C) for all study sites.
Lake
Pelagic site
SP1O
SP2O
Mean
Rbottle
GPPbottle
NEPbottle
Rsonde
GPPsonde
NEPsonde
Tempsonde
4296
1503
2900
1740
849
1295
–2556
–654
–1605
18 (33)
213 (14)
116
267 (1)
378 (3)
323
249 (34)
168 (17)
209
15.63
25.44
AL1M
AL2M
BMM
Mean
1440
1467
1696
1534
1394
3069
344
1602
–46
1602
–1352
68
824 (27)
2 673 (20)
3 568 (25)
2 355
854 (2)
3 069 (5)
2 656 (1)
2 193
30 (28)
396 (25)
–912 (26)
–162
19.25
25.68
23.14
MUE
LAVE
Mean
7421
966
4194
5743
2661
4202
–1678
1695
9
32 125 (17)
5 424 (51)
18 774
35 194 (6)
6 906 (10)
21 050
3064 (12)
1479 (61)
2272
22.88
25.88
CBD
TBD
Mean
289
1015
652
274
1305
790
–15
290
138
2 171 (8)
23 (51)
1 097
846 (1)
735 (2)
790
–1326 (9)
712 (52)
–307
18.64
17.31
Sediment site
SP1O
2370
SP2O
358
Mean
1364
560
240
400
–1810
–118
–964
180 (22)
408 (9)
294
492 (4)
443 (5)
467
312 (26)
38 (15)
175
15.66
25.57
AL1M
AL2M
BMM
Mean
1404
882
330
872
1101
1489
880
1157
–304
607
550
284
2 647 (49)
2 534 (19)
1 640 (21)
2 274
2 545 (2)
2 427 (7)
1 825 (4)
2 266
–99 (51)
–108 (26)
185 (25)
–7
19.23
25.76
23.25
MUE
LAVE
Mean
4239
784
2511
4835
2142
3488
596
1358
977
11 719 (50)
4 122 (58)
7 920
13 920 (<1)
5 706 (4)
9 808
2192 (49)
1585 (62)
1883
23.04
25.83
Macrophyte site
SP1O
4238
SP2O
909
Mean
2573
210
1212
711
–4028
304
–1862
2 186 (29)
2 468 (15)
2 327
1 420 (3)
2 176 (5)
1 798
–767 (32)
–292 (21)
–529
15.72
25.78
AL1M
AL2M
BMM
Mean
622
1033
727
794
890
1310
594
932
269
277
–133
138
6 166 (38)
3 904 (21)
2 744 (83)
4 271
5 254 (3)
3 789 (20)
4 471 (22)
4 505
–911 (41)
–115 (41)
1726 (105)
233
19.39
25.39
23.42
MUE
LAVE
Mean
3133
498
1816
7768
1804
4786
4635
1306
2970
9 246 (86)
9 869 (38)
9 557
12 285 (8)
10 062 (13)
11 174
3039 (94)
192 (51)
1615
23.43
26.00
CBD
TBD
Mean
417
1278
848
965
1386
1175
547
108
328
6 855 (62)
12 019 (271)
9 437
2 521 (23)
6 577 (5)
4 549
–4334 (85)
–5443 (266)
–4889
19.12
18.37
22 507 (40)
3 784 (91)
13 146
20 248 (12)
5 929 (16)
13 088
–2259 (52)
2151 (108)
–54
18.47
19.20
Middle site
CBD
—
TBD
—
Mean
—
—
—
—
—
—
—
Note: Metabolism measurements are limited to epilimnetic portion of pelagic and littoral zones. Subscripts refer to the
method used. Lakes are organized by location and grouped by trophic status in the order oligotrophic (O), mesotrophic (M),
eutrophic (E), and dystrophic (D); means for metabolism values by lake trophic status and location are shown. Values in
parentheses are one standard deviation.
© 2006 NRC Canada
1136
Can. J. Fish Aquat. Sci. Vol. 63, 2006
Fig. 1. Examples of diel dissolved oxygen (mg·L–1) changes in (a) Sparkling and (b) Big Muskellunge lakes over 2 days. Lines represent pelagic (solid), sediment (dotted), and macrophyte (broken) locations.
macrophytes was used for the sediment location in all other
lakes.
Comparisons among sites
Differences in sonde measurements between locations are
highlighted (Fig. 1). Sparkling Lake, which is an
oligotrophic lake with a relatively small (16%) littoral area,
had diel DO excursions of <1 mg·L–1 at all sites. Big Muskellunge showed diel DO excursions in the sediments and
pelagic sites of the same magnitude as Sparkling Lake.
However, the amplitude of the macrophyte signal covered
nearly 3 mg·L–1.
Variation was found among sites for bottle and sonde
GPP, R, and NEP (Fig. 2). Each panel separately compared
macrophyte and sediment metabolism with pelagic metabolism, normalized to pelagic values. Rbottle and GPPbottle differences among sites were low in nearly all lakes.
For sondes, macrophyte sites often had much higher Rsonde
and GPPsonde values than the pelagic sites. Sediment Rsonde
and GPPsonde differences with pelagic values spanned a
range similar to differences among locations for bottle mea-
surements. The first Sparkling Lake measurements (SP1O)
had an especially low Rsonde at the pelagic site, causing differences among sites to be much higher than in other lakes.
NEPsonde values ranged above and below zero. Highest NEP
values were found at the macrophyte sites in MUE and
BMM; lowest values were at the macrophyte locations in
CBD and TBD.
The ratio of sonde/bottle pairs for R and GPP was significantly higher at macrophytes sites than at other sites, but ratios were not significantly different between pelagic and
sediment sites (one-way ANOVA, p = 0.003, N = 49). Separate one-way ANOVA indicated means of sonde/bottle ratios
(both R and GPP) were different among the four types of
lakes (p = 0.006, N = 49). Means for sonde/bottle ratios increased in the order of oligotrophic < mesotrophic <
dystrophic < eutrophic. Tukey’s paired comparison of means
indicated the oligotrophic mean was different than the
dystrophic and eutrophic means, while no differences were
found between other pairs of lake types.
Sondes deployed in dystrophic lakes midway between the
pelagic site and the Sphagnum mat had GPP and R values
© 2006 NRC Canada
Lauster et al.
1137
Fig. 2. Differences in metabolism between littoral and pelagic sites, normalized to pelagic metabolism. Comparisons are between
macrophyte (M) and pelagic (P) values and between sediment (S) and P values for each of the following metabolism components:
gross primary production (GPP) as measured by (a) sondes and (b) bottles; respiration (R) as measured by (c) sondes and (d) bottles;
net ecosystem production (NEP) as measured by (e) sondes and (f) bottles. Macrophyte and pelagic site comparisons were too high to
include for oligotrophic Sparkling Lake (SP1O) (Rsonde = 120) and dystrophic Trout Bog (TBD) (Rsonde = 522).
more similar to the pelagic values in Trout Bog Lake. In
Crystal Bog Lake, the middle sondes had GPP and R rates
twice those found at the other locations. CBD had the lowest
values for NEP at both the middle and macrophyte site,
while TBD had negative NEP only at the macrophyte location next to the Sphagnum mat. There were no midway sites
in the other lakes, and these sites were not included within
comparisons of sediment and macrophyte sites.
Comparisons between sondes and bottles
Sonde estimates of both GPP and R were almost always
elevated over bottle estimates for the littoral sites (Fig. 3).
The t test for difference between paired sonde–bottle estimates was significantly greater than zero for R (p = 0.001,
N = 25) and GPP (p = 0.0005, N = 25). In the pelagic sites,
sonde estimates of GPP and R were greater than bottle estimates in CBD, MUE, AL2M, and BMM. Three of these lakes,
CBD, MUE, and BMM, were also the three most productive
lakes as indicated by pelagic GPPsonde. Sonde estimates of
GPP and R were lowest compared with bottle estimates in
dystrophic lake TBD and oligotrophic lake SPO on both
dates. Despite these individual differences among lakes, the
mean of sonde to bottle ratios were similar at the pelagic
and sediment sites, ranging only from 2.0 to 2.7 for both
GPP and R. Macrophyte locations, however, had larger average ratios of 4.4 (GPP) and 7.7 (R). The ANOVA of squareroot-transformed ratios indicated that macrophyte site ratios
were significantly different than pelagic and sediment ratios,
while pelagic and sediment ratios were similar. The high
GPP and R outliers at all locations in Fig. 3 were from
eutrophic lake MUE.
A source for elevated pelagic sonde values is indicated by
the increasing ratio of sonde/bottle at pelagic sites with increasing littoral habitat, relative to total lake area (Fig. 4;
r2 = 59.9, p = 0.001, N = 14). A particularly low ratio is
present for RSP1 because of a low sonde value. Only the lit© 2006 NRC Canada
1138
Can. J. Fish Aquat. Sci. Vol. 63, 2006
Fig. 3. Comparison of sonde and bottle estimates for gross primary production (GPP) and respiration (R) among the three primary
study locations: pelagic site (a) GPP and (b) R; sediment site (c) GPP and (d) R; macrophyte site (e) GPP and (f) R. Lines represent
an approximate 1:1 relationship. All GPP and R values are in units of mg O2·m–2·day–1. Note that the y-axis scale is larger for pelagic
comparisons.
toral habitat within the epilimnion was considered in this
analysis.
Uncertainties in K600 may explain a small amount of the
differences between sonde and bottle estimates of metabolism, especially at pelagic and sediment sites (Table 2). Two
SDs in R for sonde estimates rarely encompassed bottle estimates at any site, even though the ranges in metabolism may
be somewhat high in some cases (e.g., BMM). The range in
estimates for GPP was almost always smaller than that for
R, because a change in K600 for any one run of the model
tended to have opposite effects on changes in DO during day
versus night, and GPP is the sum of Rnight and NEPday. Lakes
with shallow mixed layers tended to have higher SDs in metabolism estimates because of their higher surface area to
volume ratios. These lakes also tended to have higher metabolism rates, so their ranges in metabolism as measured by
sondes tended to be small compared with the difference between sonde and bottle estimates.
Discussion
Sondes measure metabolism not captured by bottles
Comparisons of sonde and bottle methods under a variety
of lake conditions indicate substantial differences between
methods, with sondes apparently measuring GPP and R not
captured by bottle incubations. The sonde values were
higher than bottle values at pelagic and sediment sites by a
factor of 2.1–2.7 on average, similar in magnitude as determined for R in a larger set of lakes (Hanson 2003) and consistent with qualitative results presented previously (Cole et
al. 2000). In nearly half the pelagic sites, however, the sonde
GPP and R values were similar to or less than bottle values.
The high average ratio at pelagic sites is due to substantially
higher sonde values in the three most productive lakes, with
the highest pelagic GPP and R rates measured by sondes.
Sparkling Lake, our only oligotrophic lake, had sonde GPP
and R much lower than bottle GPP and R for the pelagic
sites. Besides lake productivity, the ratio of pelagic sonde to
bottle GPP and R in non-bog lakes was positively related to
percentage of littoral area. Although limited by the small
sample size, the results suggest that littoral habitats contribute to the higher sonde estimates relative to bottles found at
pelagic locations. Elevated sonde/bottle ratios at pelagic
sites appear to be related to increased lake productivity and
(or) extent of littoral area.
Littoral sonde estimates were nearly always elevated
above bottle estimates in each lake (29 of 32 comparisons).
Despite this similarity between sediment and macrophyte
© 2006 NRC Canada
Lauster et al.
Fig. 4. Pelagic gross primary production (circles) and respiration
(triangles) sonde to bottle ratios displayed as a function of littoral percentage of total lake area. Values were log-transformed for
least-squares regression analysis. Only littoral habitat within the
epilimnion was included in this calculation. Dystrophic lakes
were excluded because of lack of littoral zone.
sites, the ratios of sonde to bottle estimates were significantly higher at the macrophyte sites, with sonde/bottle ratio
means of 4.4 for GPP and 7.7 for R compared with relative
values of 2.7 and 2.0 at sediment sites. Container and sampling effects, lack of natural light conditions, scaling results
from bottles to lakes, absence of turbulence within bottles,
and assumption of a well-mixed epilimnion by the sonde
method may cause differences between bottle and sonde results at any location (Schindler 1977; Peterson 1980). The
higher ratios at the macrophyte site than at other sites suggest that the effect of these differences between bottle and
sonde methods was smaller than the effect of macrophyte location on metabolism. Macrophyte sondes are measuring a
substantial source of metabolism not included in the bottle
estimates.
Source of non-planktonic littoral GPP and R
Sonde measurements provide different estimates of GPP
and R for a lake depending on where the sondes are located.
The added metabolism at macrophyte-rich sites is very large,
at times reaching an order of magnitude higher GPP compared with the pelagic locations. Differences among sites for
bottles were lower than differences for sondes, suggesting
that planktonic metabolism differences among sites were minor. The elevated sonde estimates indicate that an additional,
non-planktonic source of daytime oxygen production and
nighttime oxygen consumption is present at macrophyte
sites, though we are unable to discriminate among the contributions of macrophytes, periphyton, and attached
heterotrophic organisms. Surprisingly, sonde/bottle ratios at
macrophyte-poor sediment locations were not different from
those in pelagic locations despite the added presence of sediments and their associated biota. The lack of significantly elevated sonde metabolism at the sediment sites points to the
difficulty in studying the complex littoral zone. Metabolism
by sediment biota may be small in these systems or may not
impact DO concentrations in overlying water to a degree as
detectable as macrophyte-associated biota. A more detailed
survey of more lakes would better place the relative impor-
1139
Fig. 5. Macrophyte (circles) and sediment (triangles) net ecosystem production (NEPsonde) for each lake arranged by increasing
NEP. Differences between values are the estimated range of NEP
throughout the littoral zone. Lake abbreviations are Crystal Bog
(CB), Trout Bog (TB), Allequash (AL1, AL2), Sparkling (SP1,
SP2), Little Arbor Vitae (LAV), Big Muskellunge (BM), and
Muskellunge (MU).
tance of sediment- and macrophyte-associated organisms to
overall lake metabolism.
Flux of gases between the epilimnion and deeper thermal
layers may also contribute to differences between bottle and
sonde estimates. Strong gradients in gas concentration between thermal layers coupled with short distances between
layers may promote vertical mixing. Oligotrophic lakes with
high depth to surface area ratios and pronounced thermal
stratification may have metalimnetic DO peaks due to positive NEP (Wetzel 2001). The metalimnion in these lakes
may act as an oxygen source to the epilimnion. Hypolimnia
are characterized by low productivity and low DO concentrations, which result in large DO gradients between thermal
layers. Although mixing across the thermocline can be negligible in small lakes during summer stratification (Quay at al.
1980; Cole and Pace 1998), vertical eddy diffusion forced by
wind events may be greater in larger lakes (Saggio and
Imberger 1998). Littoral zones do not overlay the
metalimnion, and therefore DO inputs from deeper waters
do not explain the large differences between sondes and bottles found at macrophyte sites.
Uncertainties in K600 may also contribute to differences
between bottle and sonde estimates, though the Monte Carlo
analysis suggests those contributions to be small. We admit
that this analysis does not account for diel biases that may
occur in flux estimates, due, for example, to differing energy
fluxes within or between lakes (e.g., MacIntyre et al. 2002).
We are also not able to quantify the advection or mixing
terms described previously. A more thorough study of the
assumptions used by the sonde method would benefit our
understanding of lake metabolism, especially in the littoral
zone where turbulence and stratification may be more complex. Future studies that focus on physical drivers of dissolved gas dynamics will also help determine the scale at
which physical versus biological processes drive changes in
dissolved gases and may help differentiate contributions by
© 2006 NRC Canada
1140
littoral zones versus subepilimnetic strata to pelagic estimates of metabolism.
Macrophyte sites differed among lake types in their diel
DO signals, as well as in the balance of GPP and R. These
differences may be due in part to the type of macrophytes
present. Dystrophic lake macrophyte sites in particular differed from non-dystrophic lakes in having Sphagnum mats
and emergent macrophytes dominating the macrophyte community, existing primarily at the lake edge. Oxygen production by emergent macrophytes in the dystrophic lakes is lost
to the atmosphere while the organic carbon substrates from
these plants may enter interstitial waters and the lake, causing loss of oxygen via the heterotrophic microbial community. In a study of a nearby dystrophic lake, Fisher et al.
(1998) found bacterial production and abundance to be elevated within interstitial waters of the bog mat compared with
the open water of the lake. This difference may have caused
the macrophyte site NEP in the two dystrophic lakes to be
up to three times more negative than that in the pelagic or
macrophyte sites in the non-dystrophic lakes. The lowest
NEP values previously documented using sonde measurements were from dystrophic lakes (Hanson et al. 2003). In
lakes in this study where submergent macrophytes dominated, NEP was much less negative and even substantially
positive in two lakes.
Implications for surface water NEP
Differences in sonde-based NEP estimates were greater
among lakes than among locations within a lake. Eutrophic
lakes (MUE, LAVE) had positive sonde NEP at all locations,
while one dystrophic lake (CBD) had extremely negative
sonde NEP at all locations. Although within-lake differences
were not as large, there is an indication that consideration of
littoral habitats would change how we view the trophic status of lakes.
Our study sampled two littoral sites at high and low levels
of macrophyte abundance to provide a possible range of littoral NEP for each lake (Fig. 5). The range of littoral NEP
values was much higher than pelagic NEP for two lakes:
BMM and MUE. Additionally, lake size and the extent of the
littoral zone within the lake would determine whether this
littoral effect could be a large (extensive littoral habitat,
small lake) or minor (small littoral habitat, large lake) contribution. The two lakes with higher littoral NEP ranges also
had littoral zones making up more than 54% of the lake
area, suggesting the littoral zone may cause pelagic NEP estimates to be higher than they would be if only pelagic processes dominated. NEP values for the sondes located near
the bog mat edge were much less than pelagic values in both
dystrophic lakes. These lakes may be strongly impacted by
littoral NEP because of their small size and the surrounding
bog mat.
Our study indicates that differences between sonde and
bottle estimates of lake metabolism may be due to substantial, non-planktonic metabolism found at macrophyte-rich
littoral areas. In non-dystrophic lakes, the macrophyte-rich
sites increased both GPP and R. In dystrophic lakes, the
macrophyte-rich zone greatly increased R but not GPP. Nonplanktonic metabolism in littoral habitats appears to affect
dissolved oxygen concentrations throughout the lake. Determining the magnitude of the contribution by littoral habitats
Can. J. Fish Aquat. Sci. Vol. 63, 2006
to whole-lake metabolism was beyond the scope of this
study. However, these lakes had littoral habitats ranging
from 16%–100% of lake area, suggesting that littoral habitats may provide the bulk of surface water metabolism in
some cases. Although our results generally support the assertion that littoral habitats can contribute greatly to wholelake metabolism (Vadeboncoeur et al. 2001, 2002), quantifying the magnitude of the contribution will require coupling
circulation models with more sensors to sample at higher
spatio-temporal densities. Combining these efforts with metabolism estimates for specific littoral biota (e.g.,
periphyton, macrophytes, sediment bacteria) will provide a
better understanding of contributions from the complex littoral habitat. The importance of macrophyte habitats suggests
that variation in littoral habitat, both extent and composition,
may impact overall lake metabolism in addition to the effects of nutrient and DOC inputs.
Acknowledgements
We are grateful to J.J. Coloso and B.J. Belz for their extensive work in the field and laboratory. Research was supported
by the A.W. Mellon Foundation and by the National Science
Foundation through the North Temperate Lakes LTER
(DEB9232863) and Microbial Observatory (DEB9977903)
grants. The manuscript greatly benefited from the comments
by the editor and two anonymous reviewers.
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