Phytofauna of Eleven Macrophyte Beds of Differing Trophic Status,
Depth, and Composition1
Sophie Lalonde and John A. Downing
DGpartement de Sciences biologiques, University de Montreal, C.P. 6128, Succursale A, Montreal (Quebec) H3C 317, Canada
Lalonde, S., and J. A. Downing. 1992. Phytofauna of eleven macrophyte beds of differing trophic status, depth,
and composition. Can. J. Fish. Aquat. Sci. 49: 992-1000.
Macrophyte beds in 11 lakes of differing trophic conditions were sampled intensively to examine the influence
of macrophyte abundance and composition, epiphyton biomass, phytoplankton concentration, and water depth
on the abundance of phytophilous invertebrates. Numerical abundance and biomass of phytofaunal taxa were
only weakly correlated. Phytofauna biomass ranged from 17 to 270 mg dry mass-g macrophyte dry mass"1
(1-29 g dry mass-m"2) among the macrophyte beds. Multiple regression analysis showed that total phytofaunal
biomass was positively correlated with the biomass of the three primary producers in the littoral zone: macro
phytes, epiphyton, and phytoplankton. Phytofauna biomasses in deeper macrophyte beds or near the water
surface were lower than those found in shallower water or near the sediment surface. Correlations of phytofauna
biomass with macrophytes, epiphyton, and depth varied somewhat among phytofaunal taxa. The phytofauna
biomass was often dominated by chironomid larvae, but gastropods, water mites, and oligochaetes were also
important components of the phytofauna biomass. Small crustaceans such as cladocerans and copepods fre
quently were numerically dominant but usually composed only a small fraction of the biomass. Preference of
various invertebrate taxonomic groups for particular species of aquatic macrophyte was slight.
Onze herbiers de macrophytes situes dans des lacs differents furent echantillonnes afin d'etudier I'influence de
I'abondance et de la composition en macrophytes, la biomasse d'e*piphyton, la concentration de phytoplancton
et la profondeur de I'eau sur I'abondance des invertebres phytophiles. Bien que la plupart des etudes anterieures
portant sur la phytofaune analyse I'abondance relative des invertebres en fonction des nombres d'organismes,
nous avons trouv£ que I'abondance numerique et la biomasse des divers taxa sont faiblement correl£es. La
biomasse de phytofaune variait beaucoup entre les herbiers allant de 17 a 270 mg masse seche-g masse seche
de macrophyte"1 et representant de 1 a 29 g masse seche-rrT2. Une analyse de regression multiple a demontre
que la biomasse totale de phytofaune £tait corre'le'e de fac,on positive avec la biomasse des trois producteurs
primaires de la zone littorale : les macrophytes, I'e'piphyton et le phytoplancton. Dans les herbiers les plus creux
ou pres de la surface de I'eau, les biomasses de phytofaune £taient plus faibles que dans les eaux peu profondes
et pres des sediments. Les correlations entre la biomasse de phytofaune et les macrophytes, I'e'piphyton et la
profondeur etaient variables entre les divers taxa d'inverte'bre's. La biomasse de phytofaune etait frequemment
dominee par les larves de chironomides mais les gasteropodes, les acariens et les oligochetes constituaient aussi
d'importants representants de la biomasse de phytofaune. Les petits crustac£s tels les copepodes et les cladoceres,
bien que frequemment dominants en nombres, constituaient generalement une petite fraction de la biomasse.
La preference de certains groupes taxonomiques d'invert£bres pour des especes particulieres de macrophytes
aquatiques e"tait faible.
Received March 13, 1991
Accepted November 7, 1991
(JA940)
Invertebrates colonizing the surfaces of aquatic macrophytes
(phytofauna) are very abundant and can contribute a large
fraction of the secondary production in lakes (StraSkraba
1965; Pieczyriski 1973; Lim and Fernando 1978; Schramm and
Jirka 1989). They are important food for fish and waterfowl
(Krull 1970; Danell and Sjoberg 1980; Kaminski and Prince
1981; Fairchild 1982; Keast 1984; Schramm and Jirka 1989).
The phytofauna is a strategic link in the cycling of energy and
nutrients in aquatic ecosystems (Jonasson 1978; Miura et al.
1978; Koibdziejczyk 1984b; Kairesalo and Koskimies 1987).
Unfortunately, the technical difficulty and expense of sampling
this important fauna have impeded study of it (Downing 1984).
Most studies of the phytofauna have been based upon qualita
tive or inherently biased sampling methods (see Downing and
'Publication No. 376 of the Groupe d'ecologie des eaux douces de
1'Universite de Montreal.
992
Requ le 13 mars 1991
Accepte le 7 novembre 199 7
Cyr 1985), and few have attempted to make comparisons among
the phytofauna found in more than a few ecosystems.
Until recently, studies of invertebrate:macrophyte relation
ships have focused primarily on the preference of various inver
tebrate species for certain macrophyte species (e.g. Krecker
1939; Andrews and Hasler 1943; Rosine 1955; Soszka 1975a;
Pip and Stewart 1976; Biggs and Malthus 1982; Talbot and
Ward 1987) or the direct use of macrophytes by the phytofauna
(e.g. McGaha 1952; Gaevskaya 1966; Soszka 1975b). The
importance of the phytofauna as food for other trophic levels,
however, suggests the importance of knowing which charac
teristics of lakes and macrophyte beds influence the develop
ment of phytofaunal biomass.
A few recent studies have attempted to quantify the influence
of some environmental characteristics on the biomass of phy
tophilous invertebrates in macrophyte beds. Some (e.g. Vin
cent et al. 1982; Cyr and Downing 1988a) have investigated
Can. J. Fish. Aquat. Sci., Vol. 49. 1992
the influence of macrophyte species composition, sediments,
current speed, or other environmental characteristics on the
numerical abundance of the phytofauna. Although the numer
ical abundance is useful in discovering factors influencing spe
cific phytofaunal taxa, biomass estimates would yield infor
mation more relevant to the study of energy transfers in
lacustrine ecosystems. Rasmussen (1988) developed several
models predicting the biomass of littoral zoobenthos based on
the littoral slope, wave exposure, sediment characteristics,
trophic status, and the chemical composition of the water. This
important study treats only the aggregate of the littoral benthos
(sediment and plant-dwelling animals) and thus furnishes no
information specific to the phytofauna, nor does it allow pre
dictions of the biomass of groups of organisms that are of par
ticular importance to the nutrition of littoral fish and waterfowl
(e.g. Gascon and Leggett 1977; Mittelbach 1984; Keast 1985).
The phytofauna biomass found in a given ecosystem could
be influenced by several factors. Several authors have sug
gested that the abundance of littoral invertebrates is correlated
with the biomass and species composition of their macrophytic
substrate (Vincent et al. 1982; Downing 1986; Cyr and Down
ing 1988a). High standing macrophyte biomass may decrease
wave-induced turbulence which could detach epiphytic animals
(Bownik 1970), thus favoring high phytofauna biomass. Epi
phytic algae are an important food source for invertebrates
(Mason and Bryant 1975; Cattaneo and Kalff 1980), and epi-
phyton-grazing invertebrates constitute a large proportion of the
phytofauna. Several authors, therefore, have suggested that
epiphytes are important to phytofaunal production (Petersen and
Boysen-Jensen 1911; Entz 1947; Rosine 1955; Gaevskaya
1958; Harrod 1964; Foerster and Schlichting 1965; Soszka
1975b; Schramm et al. 1987), although few explicit tests exist
(Downing 1981; Fairchild 1981; Cattaneo 1983; Ohtaka and
Morino 1986). Because many phytofaunal organisms can also
filter-feed (Downing 1981; Iversen et al. 1985; Harper 1986),
phytoplankton biomass may have a positive influence on phy
tofaunal biomass. We might thus expect higher phytofaunal
biomasses in eutrophic lakes (Lemly and Dimmick 1982; Talbot and Ward 1987). Because shallow macrophyte beds receive
greater solar radiation and are closer to sediment nutrients,
lower invertebrate biomasses may be found in deeper macro
phyte beds (Soska 1975a). On the other hand, animals found
on macrophyte stems nearest the water's surface might be most
frequently detached by wave action (Entz 1947; Pieczynski
1964; Bownik 1970).
The objective of this study was to find whether the phyto
fauna biomass in diverse macrophyte beds in several dissimilar
lakes is related to the biomass and composition of macrophytes,
the biomass of epiphytic and phytoplanktonic algae, the mean
depth of the macrophyte bed, as well as the relative proximity
of the fauna to the sediment and lake surface.
Methods
This study was performed in 11 lakes in southern Quebec
(Fig. 1) during July and August 1985 and July 1986. Sampling
sites covered a wide range of density and composition of macro
phytes, epiphyton biomass, and lake trophic status. Data col
lection began in July, shortly after macrophyte biomass was
well established and the macrophytes had been well colonized
by invertebrates. One macrophyte bed was sampled once in
each lake. The 11 macrophyte beds were sampled in random
order. The biomass of the phytofauna was estimated at each
Can. J. Fish. Aquat. Sci., Vol. 49, 1992
site and the relationship between these standing biomasses and
environmental characteristics was determined using regression
analysis. Macrophyte, epiphyton, and phytoplankton biomass
and depth were considered independent variables in these
regression analyses.
The phytofauna was sampled following the protocol of
Downing (1986). Divers collected animals by gently closing a
water-tight Plexiglas box (6 L) around the macrophyte stems
and leaves without disrupting the epiphytic flora or fauna.
Twelve samples (six in lac Fournelle) were taken at randomly
chosen points along a 50-m transect parallel to shore at each
sampling site. We sampled near the water surface, middepth,
and near bottom, and the distance between the box-sampler and
the sediment surface (Zb, metres) was noted for each sample
(Zb ranged from 0.1 to 2.5 m). The average depth of the macro
phyte bed along the transect (Z, metres; mean of six measure
ments) was determined at each site.
The volume of each 6-L box-sample was reduced in the field
by passing it through a filter-funnel (Nytex, 100 jim; Likens
and Gilbert 1970). Samples were kept cold during transport to
the laboratory where the phytofauna was separated from the
macrophytes by rinsing the plant surfaces with a gentle jet of
filtered water over a 100-jxm sieve. Rinsed pieces of macro
phytes were examined regularly to make certain that animals
were removed quantitatively. Invertebrates were preserved in
80% ethanol with 1% glycerine added to avoid desiccation. The
macrophyte pieces collected in these samples were identified
following Fassett (1957), rinsed again, dried (60°C), and
weighed (±0.1 mg).
All of the invertebrates found in our 126 samples were iden
tified and counted using a dissecting microscope (16 x).
Detailed taxonomic analysis was not performed, but inverte
brates were classified into eight major groups: Copepoda, Cladocera, Chironomidea, Trichoptera, Oligochaeta, Acari,
Ostracoda, and Gastropoda. Biomasses of these groups were
determined by measuring the lengths of individuals of different
taxa in a subsample of each of the 126 samples. The frequency
distribution of body length for each taxon was determined for
each sampling site. This length-frequency distribution was
converted to a mass-frequency distribution using published
length-mass relationships (e.g. Dumont et al. 1975; Bottrell
et al. 1976; Smock 1980; Rosen 1981; see Lalonde 1988). Gas
tropod biomasses excluded the shell.
After each box-sample was sealed and brought to the boat,
a subsample of macrophyte and its epiphytes was withdrawn
through an opening in the side of the sampler. The epiphyton
biomass (EPI, micrograms chlorophyll a per gram dry mass of
macrophyte) was determined using Cattaneo and Kalff s (1978)
method. Each small macrophyte subsample was transferred
gently to a clean jar containing 200 mL of filtered lake water,
and the epiphytes were dislodged from the macrophytes by vig
orous shaking. A subsample of 20-200 mL of epiphyte sus
pension was filtered (Millipore prefilters) and chlorophyll a was
later extracted by soaking filters in 96% ethanol for 24 h in the
dark under refrigeration. The chlorophyll solution was filtered
to reduce turbidity and read spectrophotometrically at 665 and
649 nm (Bergman and Peters 1980). The macrophytes from
which epiphyton was removed were identified, dried, and
weighed as above.
The chlorophyll concentration of the lake water around the
macrophytes (5, micrograms chlorophyll a per litre) was esti
mated at 18 random points along the transect at each site. Water
993
46°10'
Lac Waterloo
Lac D'Argent^
Lac
Orford
44° 54
74° 33
71° 51'
Fig. 1. Map of southern Quebec showing the location of the 11 lakes in which macrophyte beds were
sampled.
Table 1. Characteristics of the 11 macrophyte beds sampled. AMB is the mean areal macrophyte biomass (g macrophyte dry mass-unit lake
bottom"'); TP is the mean total phosphorus concentration of the water column (n-g-L"1); S is the average phytoplankton biomass within the
macrophyte bed (jig chlorophyll a-L~'); EPI is the mean epiphyton biomass (\i.g chlorophyll a-g macrophyte dry mass"1); and Z is the mean
depth of the sampled site (m). Phytofauna biomass is expressed per unit of macrophyte biomass (mg dry mass-g dry mass"1) and per unit of
lake bottom (g-m"2). Standard deviations are in parentheses. The species of macrophytes that represented >1% of the total areal biomass are
listed by decreasing order of relative importance. Cd, Ceratophyllum demersum; Ch, Chora sp.; Cla, Cladophora sp.; Ec, Elodea canadensis;
Hd, Heteranthera dubia; J, Juncus sp.; M, Myriophyllum spicatum (except for lac des lies, where we found M. humile); N, Nitella sp.; Pa,
Potamogeton amplifolius; Pr, Potamogeton robbinsii; Pri, Potamogeton richardsonii; Pp, Potamogeton praelongus', P, Potamogeton sp. (similar
to P. epihydrus in form); S, Sagittaria sg.; Va, Vallisneria americana. Taxonomy followed Fassett (1957). Sample sizes (n): AMB = 17-25,
TP = 4-6, 5 = 13-18, EPI = 20-32, Z = 6, and phytofauna biomass = 12 (6 in Lake Fournelle).
Phytofauna
AMB
Macrophyte bed
des lies
Orford
Fournelle
Quenouilles
Echo
d'Argent
(g-m"2)
(Bay of Venise)
Massawippi
S
(M-g-L
6
2
(1)
480
(616)
2
235
(34)
(2)
(1)
(1%)
(382)
7
261
7
(194)
(1)
(1)
(3)
(1)
39
(18)
521
(375)
34
11
13
(6)
13
(3)
70
18
(51)
(4)
112
(60)
215
23
3
2
8
(8)
8
(2)
3
(1)
4
(4)
(2)
24
16
(9)
Magog
149
58
(12)
20
(21)
(13)
Waterloo
(62)
105
73
(17)
42
(157)
(11)
Z
(m)
(1)
(121)
994
EPI
36
(35)
61
(25)
Memphr6magog
(Cove Island Bay)
Champlain
TP
466
217
(219)
142
(127)
209
(164)
114
(83)
120
(89)
995
(484)
414
(310)
122
(52)
Dominant
mg-g
1.6
74
(0.1)
(10)
36
2.0
(0.3)
1.6
(0.3)
1.3
(0.1)
1.6
g-m"
3
(4)
2
(45)
47
(37)
17
12
(10)
(11)
0)
(3)
1
33
17
(0.1)
1.5
(0.3)
2.2
(13)
80
(29)
60
(7)
(0.1)
(30)
24
(12)
22
(10)
2.0
(0.0)
2.2
(0.4)
1.6
(0.1)
1.1
(0-1)
3
0)
macrophytes
M, Pa, Pr,
Ni, P
Pa, Ec, Ni
Pr, Ec
Pa, J, Ch, S,
Va
Ch, Pa, Pr,
Pp
M, Ni, Va
4
M, Va, Hd,
(2)
Ec
Va, Cla, Pri
3
0)
5
(2)
192
29
(87)
270
(131)
(13)
28
(14)
M
Ec, M, Pr,
Cd
M, Va
Can. J. Fish. Aquat. Sci., Vol. 49, 1992
samples were taken by a diver using a 1-L opaque plastic bottle
at randomly chosen depths beneath the water surface. The chlo
rophyll a concentration of the Filtrate (Millipore prefilters) was
determined as above, before and after acidification (Nusch
1980). The total phosphorus concentration in unfiltered lake
water (TP, micrograms per litre) was determined at 6 points
along the transect at each site (every 10 m). Water samples
were taken ^O cm under the water surface. TP was measured
using persulfate digestion followed by the ascorbic acid colorimetric method (American Public Health Association et al.
1985). Because variations in TP and S within macrophyte beds
were very small (Table 1) (Cyr and Downing 1988a), TP and
S estimates were not paired with invertebrate biomass estimates
but were analyzed as macrophyte bed averages.
Average areal macrophyte biomass at each sampling site
(AMB, grams per square metre) was estimated by the quanti
tative collection of macrophytes in 20 square quadrats (361 cm2;
Downing and Anderson 1985) placed randomly along the
50-m transect at each site. Phytofaunal biomass per unit area
was estimated as the product of phytofauna biomass per gram
of macrophyte dry mass and the standing macrophyte biomass
(grams dry macrophyte per square metre).
We collected our samples within the shortest possible time
period because we wanted to minimize temporal variability in
phytofaunal biomass. Other researchers have often found the
maximum phytofauna biomass during early summer. Our sam
ples were taken during mid- to late summer, when phytofauna
biomass is usually relatively stable (Soszka 1975a; Cattaneo
1983). Because the phytofauna biomass is not perfectly stable
throughout this short period, however, the sampling date as
elapsed time (days) was employed as an independent variable
in the statistical analyses to ensure that seasonal variation would
not confound our analyses. The value of this variable ranged
from 1 (earliest date sampled) to 44 (latest date sampled).
The correlation of phytofauna biomass to macrophyte, epi
phyte, and phytoplankton biomass, TP, and depth was tested
using multiple, linear, stepwise regression analysis employing
backward eliminations of insignificant variables. Regression
analyses were thus performed both for the biomass of different
taxa and the sum of all phytofauna biomass. Candidate varia
bles in these analyses were the biomass of macrophyte from
which invertebrates were collected (BP), EPI, phytoplankton
biomass (S), TP, AMB, Z, Zb, and the sampling date. Some of
these explanatory variables were estimated independently for
each phytofauna sample (i.e., BP, EPI, and Zb), while others
varied little within macrophyte beds (i.e. AMB, TP, 5, Z, and
date) and their averages within beds were used as ranked
dummy variables in the multiple regression analyses. Regres
sion analyses were thus performed following the protocol out
lined by Draper and Smith (1981) for regressions using mix
tures of quantitative and qualitative variables. Only variables
with significant (p < 0.05) partial F-values were retained.
Because S and TP are often highly correlated in lakes (e.g.
Dillon and Rigler 1974), they are redundant measures of lake
trophic status; thus, only the variable with the greatest signif
icance was retained in regression analysis. We interpret the sta
tistical significance of either of these variables to mean that
phytofauna biomass was correlated with the abundance of sus
pended matter. The only other high collinearity among inde
pendent variables (|r| > 0.5) was a marginally significant (p
= 0.037) negative correlation between log 5 and date. Gujarati
(1978) suggested that collinearities with \r\ < 0.05 pose little
Can. J. Fish. Aquat. Sci., Vol. 49, 1992
danger to interpretation of regression results. Because the data
from the two sampling years were pooled, we have tested for
year-to-year differences using an analysis of variance on the
residuals of the multiple regressions.
The importance of particular macrophyte species was exam
ined by multiple regression analysis as above, except that the
macrophyte biomass per sample was partitioned into the biomasses represented by each of the 12 macrophyte species found
in these macrophyte beds. The added ecological information
content of the macrophyte biomass thus partitioned was judged
by testing for significant increases in R2 when considering
macrophyte species biomasses (Gujarati 1978, p. 132-134).
Data were transformed, where necessary, to normalize and sta
bilize the variance of the residuals, and the residuals of all
regression analyses were examined using standard methods
(Gujarati 1978).
Results and Discussion
The macrophyte beds sampled covered much of the range of
ecological conditions found in littoral zones of north temperate
lakes (Table 1). AMB varied between 34 and «500 g dry
mass-m ~2 which covers much of the range seen in natural lakes
(Wetzel 1983; Duarte et al. 1986). TP and chlorophyll concen
trations indicated oligotrophic to eutrophic conditions (Wetzel
1983). EPI ranged from 114 to 995 |xg chlorophyll-g macro
phyte biomass"1. Average phytofaunal biomass also varied
widely, representing as little as 17 mg dry mass-g macro
phytes" ' to as much as 27% of standing macrophyte biomass
(Table 1).
The majority of previous studies of the phytofauna have
reported abundance as numbers of organisms and used these
estimates to judge the relative importance of taxonomic groups
to the phytofauna. We found no correlation (r = 0.15, p =
0.19) between relative numerical abundance and biomass of
various taxonomic groups in these 11 macrophyte beds (Fig. 2).
Ostracods and crustaceans were very important on a numerical
basis but only made up a small fraction of the phytofaunal bio
mass. Gastropods, water mites, chironomids, and other insects,
on the other hand, contributed much to the biomass but were
numerically unimportant. Numerical abundance estimates
therefore would not yield accurate descriptions of the com
munity biomass composition. There was, however, a correla
tion between the total numbers and biomass of the total phy
tofauna (Fig. 3). The broad scatter around this relation indicates
that the average body size of phytofaunal organisms varied
widely among lakes of different trophic status. Contours of
average body masses plotted in Fig. 3 show that average body
sizes in eutrophic lakes such as Waterloo and Magog (macro
phyte beds 10 and 11 in Fig. 3) were as much as 10 times those
found in oligotrophic lakes such as lac des lies or lac Quenouilles (macrophyte beds 1 and 4 in Fig. 3). An analysis of
covariance showed that phytofaunal organisms in eutrophic
lakes were significantly larger (p < 0.0001) than those in oli
gotrophic lakes.
Mean biomass of phytofauna varied widely among the 11
sampling sites (Table 1), ranging from 1 to29 g dry mass-m~2.
A survey of phytofaunal biomass in other ecosystems (Fig. 4;
58 estimates expressed in comparable units, from eight litera
ture sources) shows that the median phytofauna biomass is
1 g-m~2 (mean of 2.2) with extreme values ranging from
0.01 g-irT2 (Dvorak and Best 1982) to 12.48 g-m"2 (Scheffer
et al. 1984). Ninety-one percent of our estimates of phytofauna
995
u
a
3
o
H
0
0
10
20
30
40
50
60
70
80
90
Organisms -g macrophyte"1
Fig. 3. Relation between the total biomass and the total numbers of
all phytofaunal taxa (n = 126). All masses are as micrograms dry
mass. Macrophyte beds: 1, des lies; 2, Orford; 3, Fournelle; 4, Quenouilles; 5, Echo; 6, d'Argent; 7, Memphremagog; 8, Champlain; 9,
Massawippi; 10, Magog; 11, Waterloo. Contours indicate the relation
for phytofaunal individuals of given dry mass.
o
u
0
8
10
12
14
16
IB
20
Contribution to Total Biomass (%)
Fig. 2. (A) Relative contribution of various taxonomic groups to the
total number and to the total biomass of the phytofauna (r = 0.15,
p = 0.19). The line represents a 1:1 correspondance. Taxonomic
groups: Ac, Acari; Ch, Chironomidae; Cr, Crustacea (Copepoda and
Cladocera); Ga, Gastropoda; In, Insecta; Ol, Oligochaeta; Os, Ostracoda. Observations for each of the 11 macrophyte beds are plotted.
(B) Enlargement of the lower left-hand corner of Fig. 2A.
biomass were greater than the median of literature values, and
those found in lac Magog and lac Waterloo were greater than
any of these literature values (Table 1). The higher values found
in our study probably result from our use of a fine-mesh sieve
which retains more of the invertebrate community and the
enclosure method of sampling that we used (Downing 1986).
Because the sampler tightly encloses a volume, it does not lose
loosely attached invertebrates. Downing (1986) found this
method to yield population estimates substantially higher (from
2 to 10 times) than other methods, especially for mobile, active
organisms such as chironomids, water mites, cladocerans,
copepods, and insects.
Phytofauna biomass in these macrophyte beds was frequently
dominated by chironomid larvae (Fig. 5) which comprised 30%
or more of the total biomass in 8 of 11 sites and made up to
80% of the biomass in lac Waterloo (Fig. 5). Co-dominance of
996
0
2
4
6
8
10
12
14
Invertebrate Biomass (g-m"E)
Fig. 4. Frequency histogram of standing phytofaunal biomass (dry
mass) found in other published studies. Data represent 58 observations
of phytofauna biomass from eight literature sources: Pieczyriski (1977),
Mittelbach (1981), Biggs and Malthus (1982), Dvorak and Best
(1982), Scheffer et al. (1984), Talbot and Ward (1987), and Komij6w
(1989, 1990). If published data were given as wet mass, they were
transformed to dry mass as 0.15-wet mass.
the phytofauna by chironomids and oligochaetes has been
reported (Mrachek 1966; Pieczyriski 1973; Gerrish and Bristow
1979; Cattaneo 1983; Keast 1984), but oligochaetes made up
only 2-11% of the biomass in our samples, being slightly more
abundant in eutrophic lakes (p = 0.02). Many authors have
reported the dominance of snails in the phytofauna of some
lakes (e.g. Biggs and Malthus 1982; Vincent et al. 1982;
Kotodziejczyk 1984a; Talbot and Ward 1987). Gastropods rep
resented only 15% of the biomass, on average, in the 11 macro
phyte beds (Fig. 5) but made up over 50% of the biomass at
two sites (Fig. 5). An overall mean of 18% of the biomass was
composed of water mites.
Some organisms such as ostracods, copepods, and cladocer
ans were present in great numbers but contributed little to the
Can. J. Fish. Aquat. ScL, Vol. 49, 1992
Table 2. Signs of the significant {p < 0.05) regression coefficients
associated with biotic variables and macrophyte bed characteristics.
BP is the total macrophyte biomass in samples, EPI is the epiphyton
biomass, S is the phytoplankton biomass, TP is the total phosphorus
concentration, AMB is the areal macrophyte biomass, Z is the macro
phyte bed mean depth, Zb is the sampling depth, and date represents
the sampling date. BP was transformed to its fourth root and EPI and
5 to their logarithm. We used a fourth-root transformation for the total
biomass of the phytofauna, Copepoda, Cladocera, Gastropoda, Ostra
coda, and Acari. A logarithmic transformation was applied to the biomasses of Chironomidae, Trichoptera, and Oligochaeta. A blank space
indicates that the particular regression coefficient was not statistically
significant (p > 0.05).
c
Taxon
R2
Total biomass (Eq. 1) 0.71
Copepoda
0.51
Cladocera
0.67
Chironomidae
0.73
Trichoptera
0.40
Oligochaeta
0.45
Gastropoda
0.59
Ostracoda
0.52
Acari
0.48
BP EPI
+
+
S
TP AMB
Z
Zh Date
-
-
+
-I-
strate, and abiotic conditions. In general, the total biomass (TB,
micrograms dry mass) of phytofauna found on samples of
aquatic macrophytes varied as
c
o
(1)
(TB)025 = 11.40 (BP)025 + 0.113 (TP) - 2.01 (Z)
+ 0.86 log (EPI) + 3.22
(R2 = 0.70, n = 126, p < 0.0001) where BP is grams of
Macrophyte Beds
Fig. 5. Phytofauna community composition in the 11 macrophyte beds
sampled, as indicated by the percentage contribution of each taxonomic group to the total biomass of invertebrates. Abbreviations of
the taxonomic groups are as in Fig. 2 except that Ot = "others".
Crustacea includes Copepoda and Cladocera, Insecta includes insects
other than Chironomidae, and "others" represents Hirudinea, Amphipoda, and Turbellaria. Macrophyte beds are arranged in increasing
order of TP ((xg'L"1; Table 1), and macrophyte bed numbers are as
in Fig. 3.
phytofauna biomass due to their small body size. We found
more small organisms in our phytofauna samples than other
researchers, probably because samples were completely
enclosed before removal from the lake (see Downing 1986) and
we counted all organisms retained on a fine-mesh sieve
(100 fim). Small organisms are seldom considered in studies
of littoral communities (e.g. Soszka 1975a; Schramm et al.
1987; Talbot and Ward 1987), probably because the majority
of research has been performed with sieves >100 \im. In most
cases, however, our data uphold Talbot and Ward's (1987) sug
gestion that cladocerans and copepods do not contribute sig
nificantly to phytofauna biomass. In lac Massawippi, however,
these crustaceans were far from negligible, constituting 24% of
the phytofaunal biomass. Because of their small body size and
high PIB ratio (Plante and Downing 1989) and the fact that
cladocerans are favored prey of invertebrates and fish (e.g.
Goulden 1971; Fairchild 1982; Schramm and Jirka 1989), these
organisms are probably very important to the productivity of
many littoral zones.
Multiple regression analysis was employed to find how phy
tofauna biomass covaried with the abundance of food, subCan. J. Fish. Aquat. Sci., Vol. 49, 1992
macrophyte dry mass, TP is micrograms of total phosphorus
per litre of water surrounding the macrophytes, EPI is micrograms of chlorophyll a per gram macrophyte dry mass, and Z
is in metres. Equation 1 suggests that phytofauna increases rap
idly with TP, epiphyton concentration appears to have a more
dramatic effect at lower EPI, and very small differences in Z
have a marked influence on the standing invertebrate biomass.
Analysis of variance on the residuals of Eq. 1 shows that there
was no significant difference (p > 0.05) in phytofauna biomass
in the two study years.
A regression analysis analogous to Eq. 1 was performed
individually for several taxonomic groups: Copepoda, Clado
cera, Chironomidae, Trichoptera, Oligochaeta, Gastropoda,
Ostracoda, and Acari. The signs of the regression coefficients
for these analyses (Table 2) show that the biomass of every
group of phytofauna was correlated with the abundance of at
least one potential food source (EPI, S, TP) and the quantity
of macrophyte substrate from which samples were collected
(BP).
It is logical that biomass of fauna dwelling on the surfaces
of macrophytes should be correlated with the quantity of sub
stratum sampled (BP). This was the case for nearly every taxon
sampled (Table 2), as it has been found in several other eco
systems (e.g. Gerking 1957; Mrachek 1966; Fairchild 1981;
Downing 1986; Schramm et al. 1987). AMB in our sampling
areas had a positive influence on the biomass of copepods, cla
docerans, chironomids, and water mites (Table 2). The pres
ence of dense macrophyte beds in the littoral zone probably
influences the phytofauna biomass by increasing the habitat
surface and complexity (Mittelbach 1981; Crowder and Cooper
1982; Schramm et al. 1987), offering protection against tur
bulence (e.g. Bownik 1970) and decreasing predation pressure
(Crowder and Cooper 1982; Savino and Stein 1982).
997
The abundance of potential food sources (EPI, S) was
strongly and positively correlated with the biomasses of many
taxa (Table 2). This upholds the findings of Cattaneo (1983),
Mason and Bryant (1975), and Soszka (1975b) for chironomid
and oligochaete biomass. Cladoceran and copepod biomasses
were also positively correlated with EPI, possibly because many
of these littoral crustaceans can feed on epiphyton (Fryer 1968).
Although gastropods are generally considered to be efficient
grazers of epiphytic matter (Kolbdziejczyk 1984b), we
observed no significant correlation between gastropod biomass
and EPI. This may be because we measured EPI as chlorophyll
a which may be a poor estimate of the food available to littoral
gastropods (Kolbdziejczyk 1984b).
Two measures of phytoplanktonic food, the chlorophyll a (S)
and TP of the water column, were also strongly correlated with
phytofauna biomass (Table 2). Littoral cladocerans not only
consume epiphyton but can also be filter-feeders (Fryer 1968;
Downing 1981). Prosobranchia (comprising Hydrobiidae,
abundant in our samples) can capture particles suspended in the
water (Kolbdziejczyk 1984b, but cf. Gaevskaya 1966). These
results are reiterated by the positive effects of TP indicating
that eutrophic lakes yield higher biomasses of chironomids, trichopterans, and oligochaetes (Table 2). Chlorophyll a and TP
have often been used as predictors of biological activity in other
benthic systems (e.g. Hanson and Peters 1984; Rasmussen and
Kalff 1987; Rasmussen 1988) and it appears that they can also
be used as predictors for phytofauna abundance (Table 2).
Z and Zb were negatively correlated with the biomass of about
half the taxa (Table 2). The total phytofaunal biomass and the
biomasses of chironomids, copepods, oligochaetes, and water
mites were greater in shallower water, regardless of distance
from sediments. This suggests that the greater amount of solar
radiation and proximity to rich sediments is translated into
greater invertebrate abundance in shallower macrophyte beds.
The biomasses of trichopterans, gastropods; and water mites
were greater closer to the sediment surface than near the water
surface. This may occur because the upper parts of macrophytes
are younger and may not yet have been as densely colonized
as the older leaves closer to the bottom, or invertebrates may
avoid the upper parts of plants where wave and turbulence
effects are strongest.
The total biomass of the phytofauna was not correlated with
sampling date (Table 2). The biomasses of chironomids, gas
tropods, ostracods, and water mites, however, increased sig
nificantly during the 2-mo sampling period. Our results cor
roborate those of Gerking (1957), Cattaneo (1983), and
Koibdziejczyk (1984a) who also found an increase in biomass
of gastropods during these months. Total phytofaunal biomass
did not vary systematically over time but sampling date had
significant effects on community composition.
Table 3. Signs of the regression coefficients associated with the bio
mass of individual macrophyte species in phytofauna samples. Regres
sion analysis was performed as in Table 2, using all the same
independent variables, except that BP was partitioned into its com
ponent species. A/?2 is the difference in R2 between these multiple
regression models and those using only BP. Transformations of the
dependent variables are as in Table 2. Macrophyte species: M, Myriophyllum spicatum; Va, Vallisneria americana; Pa, Potamogeton
amplifolius; Pp, Potamogeton praelongus; Pr, Potamogeton robbinsii',
Pri, Potamogeton richardsonii; Ec, Elodea canadensis; Cd, Ceratophyllum demersum; P, Potamogeton sp.; Hd, Heteranthera dubia; N,
Nitella sp.; Cla, Cladophora sp. Significance of changes in R2-values
was determined by an F-test of the ratio of change in model meansquare to the residual mean-square (Gujarati 1978). NS indicates that
no significant change in the R2 resulted from considering the specific
composition of macrophyte biomass. An asterisk indicates that R2
changed significantly (p < 0.05).
Taxon
Total
Copepoda
Cladocera
Chironomidae
Trichoptera
Oligochaeta
Gastropoda
Ostracoda
Acari
AK2
-0.03 NS
0.05*
0.03*
-0.02 NS
0.02*
0.08*
0.01 NS
0.03*
0.08*
in seven of nine cases), however. Only water mites and oli
gochaetes appeared to show strong preference for certain
macrophyte species (A/?2 = 0.08). BP alone appeared to
account for nearly as much variation in chironomid, gastropod,
and total phytofauna biomass as particular macrophyte species
(A/?2 = NS; Table 3). Most groups of phytofauna showed
nearly equal preference for the various macrophyte species in
these lakes. Effects of macrophyte community composition
might be important, however, where management for specific
fish-food groups is the goal.
This study has shown that numerical abundance and biomass
of invertebrates yield dissimilar descriptions of phytofaunal
community composition. Studies based on the analysis of
numerical abundance of phytofaunal invertebrates yield an
inadequate image of community biomass composition and
potential energy transfers. We found that variations in com
munity biomass composition of phytofauna could be partially
explained by differences in lake trophic status, macrophyte
density and composition, and depth of the macrophyte beds we
studied. Our analysis of a diverse set of macrophyte beds quan
tifies the composite effect of macrophyte bed characteristics on
phytofauna biomass and underlines, for the first time, the
importance of the combined effects of the three primary pro
ducers of the littoral zone: macrophytes, epiphyton, and
It is generally believed that some species of macrophytes are
more conducive than others to the development of high bio
phytoplankton.
masses of phytophilous invertebrates (e.g. Krecker 1939;
Acknowledgements
Soszka 1975a; Vincent etal. 1982; Rooke 1984, 1986a, 1986b;
Talbot and Ward 1987; Cyr and Downing 1988b). When we
partitioned macrophyte biomasses among the individual com
ponent species in regression analyses, we found that little resid
ual variation in phytofauna biomass could be explained
(Table 3). Most R2 values increased because we were using
more independent variables in the analyses, and increases in
/?2-values were significant (p < 0.05) in 67% of the taxa.
Increases in /?2-values were generally very small (Afi2 ^ 0.05
998
M Va Pa Pp Pr Pri Ec Cd P Hd N Cla
We thank Helene Harvey, Martin Pe*russe, Gilbert Dagenais, and
Suzanne Beaudry for invaluable help in the field and laboratory. Com
ments of N. C. Collins and an anonymous reviewer improved this
manuscript. This study was financed by a grant from the Natural Sci
ences and Engineering Research Council of Canada (NSERC) to
J. A. D. and a team grant from the Minister of Education of the Province
of Quebec (FCAR). S.L. was financed by a graduate scholarship from
NSERC and a scholarship from the Canadian Federation of University
Women.
Can. J. Fish. Aquat. ScL, Vol. 49, 1992
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