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Competition, predation and environmental
factors as structuring forces in freshwater fish
communities: Sumari (1971) revisited
Lennart Persson
Abstract: A study by Sumari (O. Sumari. 1971. Ann. Zool. Fenn. 8: 406–421) of the fish communities in 32 Finnish lakes
concluded that the main factors affecting perch (Perca fluviatilis) populations were biotic, of which the competitive
interspecific effect of roach (Rutilus rutilus) was the main one analysed. A reanalysis of this data set suggests that abiotic
factors such as conductivity and pH are also important in structuring fish communities. It is suggested that abiotic factors
affect perch abundance mainly by their effects on other species’ performance, particularly roach. The analyses of the whole
data set and a subset of this data set consisting of nine lakes having perch only, or perch and piscivores only, also provided
evidence that piscivores affect perch biomass. A positive relationship between piscivore biomass and roach biomass suggests
that the piscivore–perch–roach interaction may have involved the presence of apparent competition between roach and perch.
Résumé : Une étude réalisée par Sumari (O. Sumari. 1971. Ann. Zool. Fenn. 8 : 406–421) des communautés de poissons dans
32 lacs de Finlande permettait de conclure que les principaux facteurs influant sur les populations de perches communes
(Perca fluviatilis) étaient des facteurs biotiques dont le principal, d’après l’analyse, était la compétition interspécifique avec le
gardon (Rutilus rutilus). Une nouvelle analyse de cet ensemble de données indiquerait que des facteurs abiotiques tels la
conductivité et le pH jouent également un rôle important dans l’établissement de la structure des communautés de poissons.
On pense que les facteurs abiotiques influent sur l’abondance de la perche principalement par le biais de leurs effets sur le
rendement d’autres espèces, en particulier du gardon. Les analyses de l’ensemble complet de données et d’un sous-ensemble
de données portant sur neuf lacs ne contenant que des perches, ou des perches et des piscivores seulement, ont également
donné des indications que les piscivores influent sur la biomasse de perches. Une relation positive entre la biomasse de
piscivores et la biomasse de gardons laisse entendre que l’interaction piscivores–perche–gardon peut avoir fait intervenir la
présence d’une compétition apparente entre la perche et le gardon.
[Traduit par la Rédaction]
Introduction
A major task in ecology is to understand the influence of different forces such as competition, predation, and environmental factors on the structure of ecological communities
(Lubchenko 1986; Schoener 1986; Polis 1988; Tonn et al.
1990). In fish, as in most other taxa, the impacts of these forces
are closely linked to size-dependent ontogenetic niche shifts.
It is therefore not often meaningful to treat each factor separately because the dominating structuring force will change
over an individual’s ontogeny. Rather, the appropriate task is
to analyse how different forces interact to shape fish communities (Werner 1986; Tonn et al. 1986; Mittelbach 1988; Persson 1988; Wilbur 1988).
Comparisons among lakes are useful in a number of ways,
including the testing of theoretical predictions and the generation of hypotheses about community structure that subsequently can be tested in experimental studies. The quality of
the data from such comparative studies is usually constrained
by the methods used to estimate fish abundances and is usually
restricted to presence–absence data or relative measures (catch
per unit effort) (Mills and Schiavone 1982; Robinson and Tonn
Received October 17, 1995. Accepted June 14, 1996.
J13114
L. Persson. Department of Animal Ecology, Umeå
University, S-901 87 Umeå, Sweden. e-mail:
[email protected]
Can. J. Fish. Aquat. Sci. 54: 85–88 (1997)
1989; Tonn et al. 1990; Persson et al. 1991). An unusual exception to this rule is a study of Finnish lakes carried out by
Sumari (1971). In this study, absolute estimates of fish
biomasses of different species were obtained for 32 lakes. Additionally, a number of environmental variables were measured. A major conclusion drawn by Sumari (1971) was that
biotic factors were more important in structuring the studied
fish communities than abiotic factors, although lake area was
shown to affect both the number of species present and perch
(Perca fluviatilis) biomass. The main factors affecting perch,
the only species present in all 32 lakes, were suggested to be
competition from roach (Rutilus rutilus) and predation from
pike (Esox lucius), burbot (Lota lota), roach, and perch (cannibalism). Of these factors, only competition from roach and
cannibalism within perch were considered in detail (see also
Svärdson 1976; Tonn et al. 1990).
Here I will do a more complete analysis of Sumari′s (1971)
data set. The purpose of my analysis is twofold. First, I will
examine the role of abiotic and biotic factors in explaining
patterns in species abundance with the purpose of more fully
testing Sumari’s (1971) conclusion that biotic factors were
more important structuring forces than abiotic factors in the
lakes studied. Furthermore, I was interested in whether abiotic
factors affected perch and roach differently. I predicted that
roach biomass should show a stronger connection to abiotic
factors than perch biomass, for two reasons. First, roach performance has been shown to be more sensitive to abiotic conditions (Degerman 1987; Persson et al. 1991; Bergqvist 1991).
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Can. J. Fish. Aquat. Sci. Vol. 54, 1997
Table 1. Principal components analysis of environmental and
biological variables in the Sumari (1971) data set.
Factor Factor Factor Factor Factor
1
2
3
4
5
pH
0.719 0.217 0.174
Roach biomass (kg/ha)
0.676 –0.286 0.154
Piscivore biomass (kg/ha) 0.557 –0.480 0.371
Total hardness (dH°)
0.640 –0.205 –0.049
Conductivity (µS)
0.610 –0.208 0.149
Alkalinity (mequiv./L)
0.478 –0.180 –0.402
Area (m)
0.306 0.877 0.121
Perimeter (m)
0.252 0.887 0.198
Other fish biomass (kg/ha) 0.180 0.006 0.370
Ruffe biomass (kg/ha)
0.074 0.559 –0.292
Maximum depth (m)
–0.349 –0.025 0.867
Mean depth (m)
–0.452 –0.018 0.825
Perch biomass (kg/ha)
–0.673 –0.148 –0.357
Variance explained
(proportion)
0.251 0.182 0.170
–0.075
–0.040
–0.247
0.505
0.624
–0.579
–0.093
–0.224
–0.123
0.568
0.074
0.071
0.128
0.100
–0.232
–0.052
–0.028
–0.140
–0.194
–0.182
–0.138
0.864
0.136
–0.187
–0.169
–0.139
0.113
0.079
Second, the competitive interaction between roach and perch
has been shown to be highly asymmetric, with a strong effect
of roach on perch, whereas to date, no experimental demonstration of a competitive impact of perch on roach has been
presented (Persson 1987; Persson and Greenberg 1990b). My
analyses focus on biomass relationships rather than species
presence–absence patterns (for the latter, see Tonn et al. 1990).
I will give a more complete analysis of the potential for top
predators (piscivores) to limit and regulate the perch populations as compared with competition from roach, which was the
main interspecific structuring force analysed by Sumari (1971)
(see also Svärdson 1976). This analysis is partly made possible
by the fact that 9 of the 32 lakes studied by Sumari (1971) had
only perch or only perch and top piscivores (pike, burbot),
which allows an analysis of the importance of top predators
unconfounded by the influence of other species.
Fig. 1. Scores for the environmental and biological variables
included in the principal components analysis along the first two
principal components.
collapsed into the group piscivores. The less common species were
grouped in a category called other fish.
Principal components analysis (PCA; Orthotran–Varimax transformation method) was used to investigate the best association among
variables followed by pairwise correlation tests. Partial correlation
analyses were performed to test whether abiotic varaibles (conductivity, pH) had different influences on roach and perch biomass, respectively, when their internal correlation had been controlled for. All data
except pH were ln transformed to stabilize variances. Variables expressed as proportions were arcsine square-root transformed.
Results
Materials and methods
I used the data from Sumari’s (1971) study of 32 Finnish lakes. The
area of these lakes varied between 0.6 and 64 ha. Environmental variables measured and presented in his paper were area, circumference,
maximum depth, mean depth, colour, KMnO4 consumption, conductivity, pH, total hardness (dHo), alkalinity, and total iron content.
Three of these 11 environmental variables (colour, KMnO4 consumption, total iron content) were not measured in all lakes; therefore, I
used only the remaining 8 environmental variables.
The lakes were poisoned with rotenone in the summers of 1963,
1964, 1965, and 1967. The numbers, lengths, and weights of the
poisoned fish were measured to yield biomass estimates and population size structures in the different lakes. The most common fish
species overall was perch, which occurred in all lakes studied. Other
frequently occurring species were pike, burbot, roach, and ruffe
(Gymnocephalus cernuum). Less common species were whitefish
(Coregonus sp.), brown trout (Salmo trutta), Miller’s thumb (Cottus
gobio), eel (Anguilla anguilla), three-spined stickleback (Gasterosteus aculeatus), bream (Abramis brama), and rainbow trout (Oncorhynchus mykiss) (Sumari 1971). As the major purpose of my study
was to analyse the biomass relationships between piscivores and other
species, biotic variables are expressed in currency of biomass (kilograms per hectare). The five most common fish species were placed
in separate categories except for pike and burbot, which were
Five principal components explained 79% of the variation in
the data set (Table 1). Factor 1, explaining 25% of the variation, was a composite factor consisting of both biotic and
abiotic variables: roach biomass, piscivore biomass, pH, alkalinity, conductivity, and total hardness, of which the two last
variables had similar scores along all five principal components (Fig. 1). Perch biomass was strongly negatively related
to this factor. The second factor, which explained 18% of the
variance, had a high score for area, circumference, and ruffe
biomass. Factor 3, which explained 17% of the variance, included depth (maximum and mean) and other fish biomass.
Factors 4 and 5, which together explained 19% of the variance,
consisted of both environmental variables such as conductivity
and total hardness and biotic variables such as ruffe biomass
and other fish biomass (Table 1).
A negative relationship was found between roach biomass
and perch biomass (r = –0.49, p = 0.004) in accordance with
Sumari’s (1971) analysis. However, the PCA analysis only
partly supports Sumari’s conclusion that the main factors affecting perch biomass in the studied lakes are biotic, as conductivity, pH, and total hardness also were strongly associated
with the first principal component (Fig. 1). A positive relationship
between conductivity and roach biomass was found (r = 0.44,
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Persson
p = 0.01), and there was also a tendency for pH to covary with
roach biomass (r = 0.33, p = 0.069). The positive correlation
between roach biomass and conductivity remained when perch
density had been controlled for, but that between roach
biomass and pH did not (partial correlation analysis, conductivity: r = 0.35, p = 0.05; pH: r = 0.18, p = 0.34). Perch
biomass was negatively related to pH (r = –0.36, p = 0.04), and
there was a tendency for conductivity to covary with perch
biomass (r = 0.30, p = 0.09). However, neither of these correlations remained after roach biomass had been controlled for
(partial correlation analysis, conductivity: r = –0.11, p = 0.56;
pH: r = –0.25, p = 0.17).
Piscivore biomass scored as high as roach biomass along
the first principal component and piscivore biomass was positively related to roach biomass (r = 0.51, p = 0.002) and negatively related to perch biomass (r = –0.49, p = 0.004) (Fig. 2).
Controlling for roach and perch biomass resulted in partial
correlations that were similar for the perch–roach and
perch–piscivore reationships, respectively (piscivore–perch
controlling for roach: r = –0.31, p = 0.09; roach–perch controlling for piscivores: r = –0.33, p = 0.07). Sumari’s data set included lakes with only perch (n = 4) and with only perch and
piscivores (pike and burbot) (n = 5). An analysis of this restricted data set showed that perch biomass was higher in lakes
lacking piscivores than in lakes having piscivores (one-tailed
t test, t7 = 1.86, p = 0.050).
Discussion
The analysis supports Sumari’s (1971) conclusion that biotic
interactions are important in structuring the fish communities
in the lakes studied. However, abiotic factors such as conductivity and pH were also found to affect fish community structure. In a larger data set of Finnish lakes (including the data
used here), Tonn et al. (1990) found that the relative abundance of roach depended on lake isolation, pH, lake area,
maximum depth, and conductivity. Maximum depth mainly
distinguished systems dominated by crucian carp (Carassius
carassius), which were not included in Sumari’s 32 lakes, from
roach-dominated systems. A positive relationship between
conductivity and roach biomass agrees with previous studies
that have shown that cyprinid biomass (including roach) increases with lake productivity as a result of increased pelagic
resource productivity and the appearance of blue-green algae
in highly productive systems (Persson et al. 1991 and references therein). In connection with the acidification of Scandinavian lakes, it has also been documented that perch are one of
the least sensitive species to acidification, whereas roach are
one of the most sensitive species to acidification (Degerman
1987; Bergqvist 1991). Given the relationships between biotic
(roach, perch, piscivore biomasses) and abiotic (conductivity,
pH) variables, the structure and biomasses of the studied perch
populations can be suggested to be a result of the interaction
between biotic and abiotic factors rather than biotic factors
only. A similar conclusion was reached by Tonn et al. (1990)
with respect to relative abundance patterns in the larger Finnish lakes data set. Furthermore, my analysis and existing literature information indicate that abiotic factors such as pH and
conductivity primarily affect roach and that the effects of these
factors on perch may primarily be indirect through their effects
on roach (and piscivores).
Fig. 2. Three-dimensional plot of perch biomass as a function of
roach and piscivore biomasses.
Svärdson (1976) and Tonn et al. (1990) attributed the negative relationship between roach and perch biomass in the Finnish data set to competition of roach with perch. My analysis,
however, suggests that the abundance relationship between
perch and roach is affected by piscivores and cannot solely be
related to roach competition (for environmentally dependent
interactions between roach and perch, see also Persson 1988).
Sumari (1971) considered the possible impact of predation on
perch populations (both cannibalism and interspecific predation), but his analysis of the impact of interspecific predation
(from pike and burbot) was restricted to a calculation of the
piscivore/prey fish ratio, and no further analyses were carried
out. The evidence for a negative effect of piscivores on perch
biomass in my analysis comes from two sources: (i) the comparison restricted to lakes with perch only or perch and piscivores only and (ii) the comparison including all lakes,
although this comparison is confounded by the positive correlation between piscivore biomass and roach biomass (and the
presence of other species). Evidence for effects of piscivores
(pike) on perch populations in piscivore–perch systems has
also been provided by other studies (Rask 1983; Rask and
Arvola 1985; Persson et al. 1996).
Experimental evidence for competition between perch and
roach has until recently been restricted to highly productive
systems (Persson 1986; Persson and Greenberg 1990a, 1990b
and references therein). However, there is now also evidence
from low-productivity systems (L. Persson, J. Andersson,
E. Wahlström, and P. Eklöv, unpublished data), to which most
of Sumari’s (1971) study lakes belong. Although an experimental analysis of the relative role of predation and competition on perch biomass is lacking, the available evidence
suggests that both competition from roach and predation by
piscivores affect perch biomass in the fish communities studied by Sumari (1971). Given the positive relationship between
roach and piscivores, it can also be hypothesized that the
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roach–piscivore–perch interaction involved an element of apparent competition (roach positively affect piscivore biomass,
which, in turn, affects perch biomass negatively) (Holt 1977).
Acknowledgements
First of all, I thank O. Sumari for carrying out his study so
carefully, which resulted in a high-quality data set forming the
empirical basis of the present paper. I have also been influenced by the ideas and conclusions advanced in Sumari’s
(1971) paper. I thank S. Henriksson and A. Persson for calculations and B. Christensen and two anonymous reviewers for
comments. My long-term research, which forms the template
for the ideas presented here, has been generously supported by
the Swedish Natural Science Research Council.
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