Download Stoichiometry of nutrient excretion by fish: interspecific variation in a

Oikos 116: 259 270, 2007
doi: 10.1111/j.2006.0030-1299.15268.x,
Copyright # Oikos 2007, ISSN 0030-1299
Subject Editor: Dag Hessen, Accepted 22 September 2006
Stoichiometry of nutrient excretion by fish: interspecific
variation in a hypereutrophic lake
Lisette E. Torres and Michael J. Vanni
L. E. Torres ([email protected]) and M. J. Vanni, Dept of Zoology, Miami Univ., Oxford, OH 45056, USA.
This study investigates how nutrient cycling rates and ratios vary among fish species, with a particular focus on
comparing an ecologically dominant detritivore (gizzard shad) to other fishes in a productive lake. We also
examined how nutrient cycling rates are mediated by body size (as predicted by allometry theory), and how
variation in nutrient cycling is related to body and food nutrient contents (according to predictions of ecological
stoichiometry). As predicted by allometry, per capita nitrogen and phosphorus excretion rates increased and
mass-specific excretion rates decreased, with increasing mass. Body phosphorus content was correlated with body
mass only in one species, bluegill. Contrary to stoichiometric predictions, there was no relationship between
body P and mass-normalized P excretion rate, or between body N:P and excreted N:P, when all individuals of all
species were considered.
However, at the species level, we observed some support for a body nutrient content effect on excretion as
predicted by stoichiometry theory. For example, gizzard shad had lower body P (high body N:P) and also
excreted P at higher rates (lower N:P) than bluegill, which had high body P (lower body N:P). We applied the
Sterner (1990) homeostatic stoichiometry model to the two most common species in the study gizzard shad
and bluegill - and found that food N:P had a greater effect than consumer body N:P on excreted N:P. This
indicates that, in terms of variation among these species, nutrient excretion may be more of a function of food
nutrient content than the nutrient content of the consumer. These results suggest that stoichiometry can provide
a framework for variation among species in nutrient cycling and for evaluating the ecosystem consequences of
biodiversity loss.
Human-induced decreases in biodiversity may cause
functional shifts in ecosystem processes, leading to a
debate among ecologists as to the relative importance of
how biodiversity mediates ecosystem functioning (Hooper et al. 2005). Some authors have concluded that
differential impacts of species (i.e. species identity) on
their environment and the types of interactions that
take place may be the most important mechanisms by
which biodiversity enhances ecosystem functioning
(Hooper et al. 2005). To evaluate the importance of
species identity in regulating ecosystem processes, more
information is needed on how different species mediate
such processes.
Ecological stoichiometry theory (sensu Sterner and
Elser 2002) has emerged as a conceptual framework for
how species vary in mediating nutrient cycling, an
important ecosystem process. This theory predicts that
nutrient release by a consumer is a function of the
imbalance between the consumer’s body nutrient
content and its food’s nutrient content as well as the
efficiency at which the consumer assimilates nutrients
into biomass (Sterner and George 2000, Vanni et al.
2002). Of particular interest is the ratio at which
nutrients are released. A model proposed by Sterner
(1990) suggests that the N:P ratio of nutrient release
(hereafter excretion N:P) by a consumer will increase
curvilinearly with food N:P and will decrease with
consumer N:P, assuming that the consumer is homeostatic with respect to body N and P contents and has an
equal maximum gross growth efficiency (GGEmax) for
each nutrient.
Animals such as fish and invertebrates are often
important in nutrient cycling within freshwater ecosystems, but few studies have explicitly examined inter-
259
specific variation (Vanni 2002). Fish species vary greatly
in their diets (Mathews 1998) and in their body
nutrient contents (Davis and Boyd 1978, Tanner et
al. 2000, Vanni et al. 2002). Thus, the potential exists
for substantial interspecific variation in the rates and
ratios by which they release nutrients (Elser et al. 1996,
Vanni et al. 2002). However, more studies are needed
to explore how nutrient release by fish follows stoichiometric predictions.
Gizzard shad (Dorosoma cepedianum ) are facultative
detritivores (Yako et al. 1996) that are found in most
reservoirs, natural lakes and large rivers in the lower
midwest and southern United States (Johnson et al.
1988, Vanni et al. 2005). Larval shad are obligate
zooplanktivores, but when they reach a total length of
/30 mm, they can consume sediment detritus (Heinrichs 1982, Mundahl 1991, Smoot and Findlay 2000,
Schaus et al. 2002). In reservoirs, gizzard shad often
comprise a large portion of fish biomass, and diets of
non-larval shad are dominated by sediment detritus
(Mundahl and Wissing 1986, Yako et al. 1996, Vanni
et al. 2005, Higgins et al. 2006). A negative correlation
has been found between gizzard shad and bluegill
(Lepomis macrochirus) abundances in these systems,
with bluegill densities being consistently low when
gizzard shad densities are high (Garvey and Stein 1998,
Vanni et al. 2005). If these two fishes recycle nutrients
at different rates and/or ratios, then it is possible that a
shift in the abundance of one of these species could lead
to an important alteration in consumer-mediated
nutrient fluxes within a reservoir.
Through nutrient excretion, gizzard shad populations can represent a significant source of N and P for
phytoplankton in reservoirs (Schaus et al. 1997, Shostell
and Bukaveckas 2004, Vanni et al. 2005, 2006). Due to
the low N:P ratios at which they excrete, these fish can
alter phytoplankton communities, possibly favoring the
growth of cyanobacteria (Schaus et al. 1997, Shostell
and Bukaveckas 2004). To some extent, the importance
of gizzard shad in nutrient cycling in reservoir ecosystems is probably due to their relatively high biomass
(Vanni et al. 2005, 2006). Yet, it is not known whether
the ecosystem-level importance of shad in nutrient
cycling is due simply to their great abundance, or also
because they have higher per capita excretion rates than
other species. Information on how different species vary
in nutrient cycling is thus essential.
We investigated the effect of species identity and
abundance on ecosystem functioning by measuring the
variation among fish species in nutrient excretion rates
and ratios in a hypereutrophic reservoir. The objectives
were to quantify and compare excretion rates of several
species (over a range of body sizes), including gizzard
shad, and to understand the stoichiometric factors
underlying interspecific variation in nutrient excretion
rates and ratios. Body nutrient contents and diets were
260
quantified to correlate them with excretion rates and to
test predictions of ecological stoichiometry theory.
Because gizzard shad dominate fish biomass and have
strong community- and ecosystem-level effects in many
reservoirs, and because we already know a great deal
about nutrient cycling by this species, we explicitly
focused on comparisons between gizzard shad and other
species. We addressed several hypotheses. Our first null
hypothesis was that fish species other than gizzard shad
would have similar excretion rates and ratios (per
individual or per biomass) as shad. The alternative
hypothesis was that fish species vary significantly in
nutrient excretion rates and/or ratios. If the alternate
hypothesis was supported, we further hypothesized that
variation among species could be explained by ecological stoichiometry theory (i.e. by the imbalance
between consumer and body nutrient contents). Finally, we tested the hypothesis that gizzard shad are
important in nutrient cycling simply because of their
high abundance vs the alternative hypothesis that they
are important because they excrete nutrients at high
rates or at unique N:P ratios. While we quantified
nutrient excretion by five fish species in four families,
we focus particular attention on gizzard shad and
bluegill due to the inverse relationship between their
abundances in reservoir ecosystems.
Methods
Nutrient excretion experiments
Nutrient excretion experiments were conducted JulySeptember 2004 in Acton Lake, a 231-ha hypereutrophic reservoir in southwestern Ohio. Excretion rates
were measured on a total of 164 fish of various body
sizes, collected via electroshocking in the upstream
portion of the reservoir. We studied five fish species gizzard shad (D. cepedianum , family Clupeidae, n /
49), bluegill (L. macrochirus , family Centrarchidae, n /
52), longear sunfish (Lepomis megalotis, family Centrarchidae, n /23), logperch (Percina caprodes , family
Percidae, n /23), and golden shiner (Notemigonus
crysoleucas , family Cyprinidae, n /17). The fish assemblage was dominated by shad and bluegill, and sample
sizes varied according to seasonal availability.
Excretion experiments followed established methods
(Schaus et al. 1997, Gido 2002, Shostell and Bukaveckas 2004, Higgins et al. 2006). Each fish was
transferred to a container filled with Acton water that
was pre-filtered using Advantec high-volume filters
(0.3 mm nominal pore size) (Advantec MFS, Dublin,
California) that removed phytoplankton and bacteria
that could take up excreted nutrients. Containers with
fish and controls without fish were kept at epilimnetic
temperatures that ranged from 23-288C throughout the
study. Initial water samples were taken from 50-l
carboys before filling the containers to quantify initial
nutrient concentrations prior to fish addition. Fish and
controls were incubated for 4560 min. The water was
then filtered through Pall A/E glass-fiber filters (1.0 mm
pore size) (Pall Corporation, Ann Arbor, Michigan) and
analyzed for NH3-N and SRP using the phenolhypochlorite technique (Solorzano 1969) and molybdenum blue method (Stainton et al. 1977), respectively,
using a Lachat (Loveland, Colorado) Series 8000 autoanalyzer. Excretion rates were determined as the
difference between initial and final nutrient concentrations, corrected for controls (Schaus et al. 1997).
Body nutrient analysis
Upon completion of excretion experiments, fish were
measured for total length, weighed, euthanized, and
then frozen for analysis of tissue C, N, and P. The
entire gastrointestinal tract was dissected and removed
for later gut content analysis. The fish were then ovendried at 608C until they reached a stable weight. Entire
fish bodies (minus the gut) were ground into powder,
using a Retsch (Haan, Germany) Model ZM100 tissue
grinder (for large individuals) and a mortar and pestle
(for small individuals), and homogenized. These samples were analyzed for C and N using a Perkin Elmer
(Oak Brook, Illinois) Series 2400 elemental analyzer (1
sample per fish), and for P using HCl digestion
followed by SRP analysis (2 replicate samples per fish)
(Vanni et al. 2002).
Correlation of body nutrient content, nutrient
excretion and gut contents
Per capita nutrient excretion rates and ratios were
regressed against body mass and against corresponding
body nutrient content and body nutrient ratios to
determine if nutrient excretion was a function of body
nutrient content, as predicted by stoichiometry theory.
Log-log plots were used in certain instances to stabilize
the variance among species and to explicitly examine
allometric relationships. Log per capita excretion rates
were expected to be correlated with log body mass, with
an exponent B/1, according to allometry theory (Peters
1983, West et al. 1997).
Because excretion rates are a function of size, it is
desirable to remove size effects when comparing species
or when trying to ascertain the effect of body nutrient
contents. Therefore, mass-normalized rates were obtained to explicitly evaluate the relationship between
body nutrient contents and excretion using the following formula:
Xn X
Wb
where X is the non-normalized excretion rate, Xn is the
mass-normalized excretion rate, W is body mass, and b
is the scaling exponent relating log body mass and log
per capita excretion rate for a particular species (Brown
et al. 2002). The scaling exponent, b, was obtained
empirically from log-log plots generated by our data
and accounted for the fact that this scaling exponent
may be species-specific.
According to stoichiometric predictions, diet nutrient content and ratios can affect excretion rates and
ratios (Sterner 1990). Because we wished to explore
how both body nutrients and dietary nutrients affect
excretion rates and ratios, the gut contents of 21 gizzard
shad gizzards and 32 bluegill stomachs, which were
randomly chosen to represent a range of dates and sizes,
were removed. We focused only on shad and bluegill
because they were the dominant species in Acton Lake
(and thus, had the largest sample sizes), and because of
the aforementioned inverse relationship between their
abundances in reservoir ecosystems. We examined diets
of more bluegill than gizzard shad because earlier work
had revealed that non-larval shad feed almost entirely
on sediment detritus (Mundahl and Wissing 1986,
Schaus et al. 2002, Sigler 2002, Higgins et al. 2006).
Gut contents were examined under a dissecting scope to
identify and quantify food items. N and P contents of
food items were estimated from the literature rather
than from direct quantification because gut material
from fish used in excretion experiments may have been
partially digested during the experiments, leading to
possible biases in nutrient contents.
To further evaluate the potential roles of body N:P
and food N:P in driving excretion N:P, we applied the
Sterner (1990) homeostatic stoichiometry model to
gizzard shad and bluegill. This curvilinear model
predicts N:P recycling ratios as a function of food
N:P and consumer body N:P using two equations based
on the nutrient limitation of the consumer. If P is
deficient in the food (i.e. food N:P /body N:P), then
the recycled N:P ratio is described by:
(N:P)r (N:P)f (GGEmax (N:P)c )
1 GGEmax
;
when (N:P)f (N:P)c
where (N:P)c is the nutrient ratio of the consumer,
(N:P)f is the nutrient ratio of the food, GGEmax is the
maximum gross growth efficiency for the limiting
nutrient, and (N:P)r is the consumer nutrient recycling
ratio. When N is scarce in food relative to the
consumer’s body, then the following equation applies:
261
(N:P)r (N:P)f (1 GGEmax )
;
(GGEmax (N:P)f ))
1
(N:P)c
when (N:P)f 5(N:P)c
The model assumes that individuals maintain a constant body N:P, which is reasonable given the temporal
scale over which diets and excretion rates were measured
(diets reflect food consumed within a few hours and
excretion rates were measured over 4560 min).
We used the body N:P ratios we observed for shad
and bluegill and initially set GGEmax for N and P to
0.70. Data on GGEmax for N and P are not available for
either fish species, to our knowledge. Therefore,
GGEmax was estimated from maximal growth efficien-
cies and body nutrient content data presented in Fig. 1
in Schindler and Eby (1997). From this figure, GGEmax
for wet mass (maximum growth in wet mass/consumption of prey in wet mass) for fish consuming Daphnia
was estimated to be 0.24. Then we used body P
contents of fish and Daphnia to convert GGEmax for
wet mass to GGEmax for P, yielding a value of 0.71.
GGEmax is much higher for P than for wet mass because
fish have much higher body P content than zooplankton. Using the same approach, we also calculated
GGEmax for P for fish feeding on other zooplankton
and found slightly lower values (0.65 when feeding on
Bosmina and 0.64 when feeding on copepods). Because
GGEmax represents maximal efficiency for the most
limiting nutrient (Sterner 1990), we used 0.70 in our
10
N excretion rate
(mg N fish-1 hr-1)
A
Bluegill
Gizzard shad
Logperch
Longear sunfish
Golden shiner
1
0.1
0.1
1
10
Wet mass (g)
100
1000
1000
P excretion rate
(ug P fish-1 hr-1)
B
Bluegill
Gizzard shad
Logperch
Longear sunfish
Golden shiner
100
10
0.1
1
10
Wet mass (g)
100
1000
Fig. 1. Per capita excretion rates for N (A) and P (B) by fishes in Acton Lake. Linear regressions for gizzard shad and bluegill are
represented by black and grey trendlines, respectively. Dashed black and grey trendlines depict the linear regressions for logperch
and golden shiner, repectively, while the trendline for longear sunfish is symbolized by the bold dashed line. Only trendlines with
slopes significantly different from 0 are depicted.
262
initial approach and assumed that P is limiting since
prey items have a higher N:P than fish bodies.
Based on our gut analyses, bluegills fed mainly on
chironomids (Results). Therefore, in our simulations,
we set N:P ratios for bluegill prey equal to 29 (molar),
based on an average of values for dipterans from Cross
et al. (2003) (n /11 individuals from a reference
stream) and Frost et al. (2003) (n /8 Canadian lakes
differing in productivity, number of individuals collected not presented). We set the N:P ratio of detritus
consumed by gizzard shad to be 12 (molar) based on
aerobic detritus actually consumed by shad in Acton
Lake, not ambient detritus, as shad selectively feed
on detritus that has higher C, N, and P content than
ambient detritus (Higgins et. al. 2006).
Statistical analyses
Data were log-transformed when appropriate to equalize variances and were analyzed using an analysis of
covariance (ANCOVA) with Bonferroni (slopes) and
Dunnett (intercepts) adjustments for multiple comparisons with gizzard shad (proc glm SAS, Version 9.1).
In all cases, species was considered the categorical
variable. Nutrient excretion rates and ratios, as well as
fish body nutrient contents and ratios, were considered
dependent variables in ANCOVAs (separate ANCOVAs for each dependent variable), with wet mass as a
covariate. To examine the relationship between body
N:P and excretion N:P, excretion N:P was modeled as a
dependent variable using ANCOVA with body N:P as a
covariate. Finally, to explicitly examine the relationship
between body nutrient content and excretion rate
without the potentially confounding influence of size
effects, mass-normalized N and P excretion rates were
used as dependent variables and body N and P,
respectively, used as covariates. Regression lines were
also fitted to the data for all variables, using least
squares regression, to obtain the slopes and intercepts
for each species.
Results
Nutrient excretion experiments
Per capita N excretion was highly and positively
correlated with mass for all 164 fish analyzed together
(Fig. 1a, p/0.0295, ANCOVA). There was also a
significant species effect (p B/0.0001) as well as a
mass /species interaction (p B/0.0001). As predicted
by allometry theory, all slopes of log-log plots were
found to be B/1 (Appendix A). Logperch and golden
shiner were the only species with slightly negative
slopes, but the size ranges of these two species were
quite narrow and slopes thus need to be interpreted with caution. Gizzard shad had higher N release
rates than logperch and shiner but shad N excretion
rates were not statistically different from other fish
species (Fig. 1a, Appendix B). The presence of a very
small gizzard shad in the dataset (Fig. 1) had minimal
influence on the regression analysis conducted for N
excretion as well as for all other dependent variables.
The presence of a significant species x size interaction
precludes direct interspecific comparisons of N excretion rates using all data. Thus, we separated gizzard
shad and bluegill into two size classes (small and large),
within which fish of both species were similar in size.
Then we calculated species means for each size class to
look at how size of a particular species can influence
interspecific differences in excretion. We found that
large shad tended to excrete more N than longear
sunfish, small bluegill, and logperch (p B/0.05) but that
N excretion rates of large shad were statistically similar
to large bluegill and shiner. Small shad had lower N
release rates than large bluegill (p B/0.05) but were not
statistically different from the other fishes.
Per capita P excretion was also a function of
increasing mass for all fishes (Fig. 1b, p /0.0437).
There was a significant species effect (p B/0.0001) as
well as a mass /species interaction (p /0.0015). Slopes
were B/1, again indicating allometric scaling for all fish
species. Once again, logperch had a slightly negative
slope that was statistically different from shad. The
slope for gizzard shad was statistically indistinguishable
from all other fish species (Fig. 1b, Appendix B). When
considering species means, large and small shad tended
to excrete more P per capita than other fish of the same
body size (Fig. 1b; also see section on mass-normalized
rates below).
Body nutrient analysis
Mass had no effect on fish body N content (Fig. 2a,
p/0.9088) but there was an effect of species (p /
0.0001) and a mass /species interaction (p /0.0051).
This was also seen for body C:N and body C:P ratios
(Torres 2005). Bluegill was the only species in which N
content increased with mass, and this increase was slight
(Fig. 2a, m /0.06, p/0.0001). Gizzard shad had less
body N than bluegill but was statistically similar to all
other species (Appendix C).
There was a significant effect of mass (Fig. 2b, p/
0.0258), species (p B/0.0001), and mass /species interaction (p B/0.0001) on body P content. This was also
seen for C body content (Appendix C, Torres 2005).
Bluegill was the only species for which body P content
increased with mass (p B/0.0001, Fig. 2b). A marginally
significant increase in body P with mass was observed
for longear sunfish (p /0.0787). Similarly, bluegill had
263
Gizzard shad
Bluegill
Logperch darter
Golden shiner
Longear sunfish
16
14
%N
12
mass /species interaction (p /0.0006), but there was
no species effect (p /0.2730). Both gizzard shad
(p /0.0198) and bluegill (p B/0.0001) showed decreasing body N:P with mass, but the decrease was
steeper for bluegill than it was for shad (Fig. 2c,
Appendix D). The slope for gizzard shad body N:P
was statistically similar to all other fish species
(Appendix D).
10
Relationships between body nutrients and
nutrient excretion
8
6
A
4
0
20
40
60
80
100
120
6
%P
5
4
3
2
B
1
0
20
40
60
80
100
120
10
9
Molar N:P
8
7
6
5
4
C
For mass-normalized N excretion rates, there was a
non-significant body N /species interaction (Fig. 3a,
p/0.0741). However, there was a significant species
effect (p B/0.0001) and a main effect of body N (p /
0.0078). Gizzard shad and logperch were the only
species in which mass-normalized N excretion varied
with body N; in both cases, body N and N excretion
were positively related (p /0.0217 for shad and p /
0.0271 for logperch). Gizzard shad was found to have a
lower N excretion rate than logperch and golden shiner
but a higher N excretion rate than bluegill and longear
sunfish (Fig. 3a, Appendix E). For mass-normalized per
capita P excretion rates, there was no body P/species
interaction (p /0.7789) or effect of body P (p /
0.1079) but there was an effect of species (Fig. 3b,
pB/0.0001). Mass-normalized P excretion rates of shad
were higher than all other fishes except logperch (Fig.
3b, Appendix E).
There was a significant effect of species on excreted
N:P (Fig. 3c, pB/0.0001), but no effect of body N:P
(p /0.5254) and no body N:P /species interaction
(p /0.9064). Overall, gizzard shad had a lower, and
less variable, excretion N:P than the other fish species
(Fig. 3c, Appendix E).
3
0
20
40
60
80
Wet mass (g)
100
120
Fig. 2. (A) Body N content as a function of wet mass for
freshwater fishes in Acton Lake. Dashed trendline depicts
increasing N content with increasing mass for bluegill. (B)
Body P vs wet mass. Dashed trendline shows a significant
increase in P content with mass for bluegill. (C) Body N:P vs
wet mass. Solid and dashed lines depict decreasing body N:P
with increasing mass for shad and bluegill, respectively.
a greater increase in body P content with mass (i.e.
steeper slope) than gizzard shad; body P and mass were
unrelated in shad (Fig. 2b, Appendix C).
Considering all species combined, there was a
significant effect of mass (Fig. 2c, p/0.0.0034) and
264
Dietary nutrients
Five out of 32 bluegills examined for gut contents had
empty stomachs. The other 27 fish had gut contents
that were comprised primarily of benthic invertebrates,
with 60 99% of the identifiable food items being
chironomid larvae. As for gizzard shad, 7 out of 21
individuals were found with empty gizzards. The rest of
the shad had gut contents consisting of only sediment
detritus obtained from sediments of Acton Lake that are
overlain with well-oxygenated water. Although nonlarval gizzard shad are primarily detritivorous in this
and other reservoirs (Higgins et al. 2006), we do not
know whether the origin of the detritus is allochthonous and/or autochthonous.
Mass-normalized N excretion rate
(umol N fish-1 hr-1)
400
A
300
Bluegill
Gizzard shad
Logperch
Longear sunfish
Golden shiner
200
100
0
Mass-normalized P excretion rate
(umol P fish-1 hr-1)
4
6
8
10
12
Body N (% dry mass)
14
16
100
B
10
Bluegill
Gizzard shad
Logperch
Longear sunfish
Golden shiner
1
0.1
0.01
1
10
Body P (% dry mass)
200
Excretion ratio N:P
C
150
Bluegill
Gizzard shad
Logperch
Longear sunfish
Golden shiner
100
50
0
0
2
4
6
8
N:P body
10
12
14
Fig. 3. Mass-normalized per capita N (A) and P (B) excretion vs body N and body P content, respectively, for Acton Lake fishes.
N excretion is on an arithmetic scale while P excretion is on a log-scale. (C) Nutrient release ratios as a function of fish body N:P.
Discussion
Nutrient excretion
As allometry theory predicts, per capita N and P
excretion increased with increasing mass, but with slopes
less than 1 on a log-log scale (Elser et al. 1996, Schaus et
al. 1997). Mass-specific P excretion rates for gizzard
shad in our study were similar to ranges reported for
gizzard shad in Taylorsville Reservoir, Kentucky (Shostell and Bukaveckas 2004), and those found in previous
studies of shad in Acton Lake (Mather et al. 1995,
Schaus et al. 1997, Higgins et al. 2006). However, the
slope for P excretion was low compared to other studies
on Acton Lake gizzard shad (Schaus et al. 1997, Higgins
et al. 2006), despite similarities in lake temperature.
Ranges for gizzard shad mass-specific N excretion
rates were considerably wider than estimates of prior
265
studies (Appendix F). The ranges for mass-specific
P and N excretion for bluegill sunfish (0.01 0.99 mmol P g 1 h1; 1.7 86.7 mmol N g1 h 1)
were considerably wider than laboratory values reported
by Mather et al. (1995) (0.04 0.18 mmol g 1 h 1 for
P; 2.53.4 mmol g 1 h 1 for N). Nutrient excretion
rates for the other fishes in Acton Lake could not be
compared to literature values because no previous
studies have been conducted using those species.
The null hypothesis that other fish species within
Acton Lake would have similar excretion rates and
ratios (per individual or per biomass) as gizzard shad
was partially supported. We found that gizzard shad was
unique in its per capita nutrient excretion as compared
to other fishes. Shad had higher N release rates than
logperch and golden shiner, and the slope of the P
excretion vs. mass relationship was greater for shad than
logperch. When excretion rates were mass-normalized,
shad had higher P excretion rates than all other fish
species except logperch (Fig. 3b). Thus, the effect of
body size on nutrient recycling may be species
dependent, but, given that logperch are scarce in Acton
Lake and other reservoirs, we can conclude that gizzard
shad have consistently higher P excretion rates than all
other common fish species of similar size.
Body nutrients
We found no significant effect of mass on fish body N
content, contrary to Davis and Boyd (1978), who
found that N content decreased with increasing mass
for bluegill. In fact, we found a slight increase in body
N content with mass for bluegill (m /0.06, P /
0.0001). Bluegill was also the only fish species that
had increasing body P with increasing mass, possibly
due to stiffer and greater numbers of scales. This
suggests that bluegill likely have a greater relative
allocation of P to the formation of bones and scales
than the other fishes studied here (Sterner and George
2000, Sterner and Elser 2002). A similar trend was
reported by Davis and Boyd (1978) and may be
characteristic of the family Centrarchidae (Sterner and
Elser 2002), though a significant mass vs body P
relationship was not seen for longear sunfish in our
study (but this may be due to low sample size, as the
correlation between body size and body P was marginally significant). It has also been proposed that high and
low consumer body P may be a manifestation of
evolutionary adaptations in ‘‘stoichiometric niches’’
(e.g. development of reduced body demands for N or
P; Hessen et al. 2004). Thus, the body nutrient
stoichiometry of freshwater fishes has a phylogenetic
component that needs further exploration.
Compared to bluegill, gizzard shad’s higher mean
body N:P is a consequence of (1) the low body P
266
content relative to body N for shad and (2) the high
body P content of sunfish. Both shad and bluegill had
decreasing body N:P with increasing mass, a result that
supports Vanni’s (1996) prediction that there should be
a decreasing allometric trend for body N:P with
increasing fish size. The other fishes in this study did
not show the same trend, indicating that fish body N:P
may decrease with size only over broad size ranges or
that the relationship between body size and body N:P
may be species-specific. Ultimately, to evaluate differences in body nutrient stoichiometry among fish, one
must consider constituent elements as well as their
ratios and their biochemical form (Anderson et al.
2004).
Correlations between body nutrients and
excretion
Can ecological stoichiometry theory explain the variation among Acton Lake fishes? With respect to the
relationships between body nutrient contents (or ratios)
and excretion rates (or ratios), we found mixed support
for stoichiometric predictions. Contrary to stoichiometric predictions, per capita N excretion increased
with increasing body N, but this trend was driven
entirely by bluegill. Unlike Vanni et al. (2002), we
found no relationship between body P and massnormalized P excretion rate, or between body N:P
and excreted N:P, when all individuals of all species
were considered. Yet, at the species level, we observed
some support for a body nutrient content effect on
excretion. When mean mass-normalized P excretion
rates were plotted against mean body P content for each
species (i.e. n /5) on a log-log scale, there was a
significant negative correlation between these two
variables (p /0.0327). For example, gizzard shad had
lower body P (high body N:P) and also excreted P at
higher rates (lower N:P) than bluegill, which had high
body P (lower body N:P). However, golden shiner and
logperch showed trends unlike bluegill and shad, with
relatively high body N:P and high excretion N:P,
possibly due to a higher N:P diet than bluegill (Fig.
3c). This agrees with findings of Vanni et al. (2002),
who found a negative correlation between body P and P
excretion at the species level. However, we found no
relationship between body N content and N excretion
rate (p /0.3696; in agreement with Vanni et al.
(2002)) or excretion N:P (p /0.9062, in contrast to
the findings of Vanni et al. 2002).
Application of Sterner’s homeostasis model
Comparison of the diets of gizzard shad and bluegill
suggests that food N:P may play a strong role in
determining excreted N:P, because the N:P ratio of
invertebrates and sediment detritus is quite different.
Consistent with other studies, examination of gut
contents revealed that gizzard shad primarily ingest
detritus (Higgins et al. 2006) whereas bluegills tend to
consume chironomids (Olson et al. 2003). Although
bluegill diet preference has not been assessed in Acton
Lake, it is reasonable to assume that resident bluegills
prefer chironomids, as they are very abundant in
shallow, oxygenated areas in this lake (Devine and
Vanni 2002). It is possible that differences in the
nutrient contents of chironomids and detritus may
explain the variation in excretion rates between bluegill
and shad.
To assess this possibility, we applied the Sterner
(1990) homeostasis model, and this produced two
noteworthy results (Fig. 4). First, overall, there was
A 100
Chironomid N:P = 29
Body N:P = 6.2
GGEmax = 0.70
Recycled N:P = 66
N:P recycled
80
Detritus N:P = 12
Body N:P = 7.5
GGEmax = 0.70
Recycled N:P = 19
60
Gizzard shad
Bluegill
40
1:1
20
0
0
B 100
30
Chironomid N:P = 29
Body N:P = 6.2
GGEmax = 0.665
Recycled N:P = 66
80
N:P recycled
10
20
N:P food
Detritus N:P = 12
Body N:P = 7.5
GGEmax = 0.605
Recycled N:P = 19
60
Gizzard shad
Bluegill
40
1:1
20
0
0
10
20
30
N:P food
Fig. 4. The Sterner model (1990) applied to the N:P of
nutrient release by gizzard shad and bluegill from Acton Lake.
(A) It was assumed that both fishes were homeostatic, had
equal maximum gross growth efficiencies for N and P
(GGEmax), and consumed the same N:P food. The black
and gray data points represent the mean recycled N:P of shad
and bluegill as determined experimentally. (B) GGEmax was
adjusted for each species in order to obtain mean recycled N:P
values from the nutrient excretion experiment. Note that
differences in the recycled N:P of shad and bluegill appear to
be driven more by differences in food N:P than solely by body
N:P. For both A and B, increasing recycled N:P with
increasing food N:P are depicted relative to a line with a
slope of one (dashed line). Error bars represent 95%
confidence intervals for recycled N:P ratios.
close agreement between modeled and measured excretion N:P; N:P excretion ratios predicted by this model
were only slightly greater than those obtained in
nutrient excretion experiments for both gizzard shad
and bluegill (Fig. 4a). Furthermore, the relative
difference between species in N:P excretion ratio was
preserved. We observed a 3.5 / difference between N:P
excretion ratios of these two species (excretion N:P /19
for shad and 66 for bluegill) from direct measurement,
whereas the model predicted N:P excretion ratios of 23
and 79, which is a 3.4 / difference. Second, the
difference in body N:P between the two fishes appears
to be insufficient to explain the observed variation in
excretion N:P. For example, if food N:P is held
constant at 12 (equivalent to that of detritus consumed
by shad), the model predicts excretion N:P to be only
13% higher for bluegill than for shad, in contrast to the
aforementioned 3.5/ difference. Similar results were
obtained using food N:P values typical of bluegill diets
(Fig. 4a).
In contrast, the difference in dietary N:P between
shad and bluegill can apparently explain much more of
the difference between these two species in N:P
excretion ratio (Fig. 4a). By adjusting GGEmax for
each species until the excretion N:P values in the model
corresponded to those found in the nutrient excretion
experiments, we were able to generate GGEmax values of
0.620 for bluegill and 0.605 for shad, values that seem
reasonable given the estimates presented above for
bluegill feeding on zooplankton (Fig. 4b).
Results of these model simulations suggest that the
observed difference in excretion N:P between shad and
bluegill may be more a function of differences in food
N:P and GGEmax than consumer body N:P (Fig. 4b).
Elser and Urabe (1999) also concluded that nutrient
release by zooplankton is more a function of food N:P
than consumer N:P, but Vanni et al. (2002) concluded
that interspecific variation in N:P excretion ratio among
fish in a tropical stream was driven by variation in body
N:P (mainly due to body P). Our results thus differ
from those of Vanni et al. (2002), most likely because
the interspecific range in body P and body N:P was
much narrower in our study than that observed by
Vanni et al. (2002).
Diet, diet shifts, and growth rates may play vital
roles in determining nutrient recycling within aquatic
systems. Aquacultural studies have consistently found
that body P and P excretion increase as dietary P
increases for a few fish species (e.g. rainbow trout
(Oncorhynchus mykiss )-Bureau and Cho 1999; juvenile
haddock (Melanogrammus aeglefinus )-Roy and Lall
2003), possibly due to a decrease in the efficiency of
P utilization or calcium-limitation. Brabrand et al.
(1990) also suggested that P release rates of fish are
influenced by the food they consume; in their study,
sediment-feeding fish tended to have higher P excretion
267
rates than fish feeding on invertebrates. This is
consistent with our results and may reflect a general
tendency for sediment detritus to have lower N:P than
invertebrate tissue. Yet, it is possible that fishes within
the same feeding guild may affect nutrient recycling
differently depending on slight differences in food (e.g.
high vs low organic matter) or differences in assimilation efficiencies (Yossa and Araujo-Lima 1998). Lastly,
the role of growth rates is not clear. Schindler and Eby
(1997) suggest that under most conditions, fish growth
rate has little effect on P excretion rate, because fish
usually are energy limited (not N or P-limited) and
grow at rates that are well below maximal. However,
excretion rates of P-limited fish (e.g. herbivorous fishSchindler and Eby 1997, Hood et al. 2005) may be
sensitive to growth rate. Clearly, more work is needed
to elucidate how food N:P, body N:P, and physiological parameters (GGE, growth rate, etc.) mediate
excretion N:P under various conditions.
Based on our results, gizzard shad may be important
in P cycling both because of their abundance and high
per capita P excretion rates. In Acton Lake during
summer 2004, gizzard shad comprised 66% of total fish
biomass but were also responsible for 81% and 95% of
all N and P excreted by the fish community (Torres
2005). Thus, shad are disproportionately important to
nutrient cycling and, in turn, primary production
within the reservoir due to their abundance and the
amount of N and P they release. It has been suggested
that shad can synergistically regulate primary production in reservoirs with watershed-derived nutrients
(Vanni et al. 2005). Since the Acton Lake watershed
is /90% agricultural, lake N:P is high due to the high
influx of N from fertilizers (Arbuckle and Downing
2001; Vanni et al. 2001), especially in spring-early
summer. Thus, the low N:P excreted by shad may
provide algae with more P for primary production. This
is substantiated by the fact that shad can support up to
50% of primary production in mid-late summer in
Acton Lake (Vanni et al. 2006). Nutrient excretion by
gizzard shad also supports a substantial proportion
(10 20%) of primary productivity in other reservoirs,
but the role of shad in supporting production seems
greatest in highly productive, agriculturally impacted
reservoirs (Vanni et al. 2006).
Conclusion
Gizzard shad are important to nutrient cycling in
reservoirs, and presumably other ecosystems, because
they are abundant and their excretion rates are
stoichiometrically unique, excreting P at high rates
and at a low N:P ratio. Adult shad can decrease
chironomid abundance via bioturbation (Gido 2003)
and larval-juvenile shad can reduce zooplankton via
268
predation; these actions can reduce bluegill populations
and promote shad population growth (Garvey and
Stein 1998, Vanni et al. 2005). At the ecosystem level,
they could shift a system that is P-limited to one that is
N-limited. This, in turn, could cause the algal assemblage to be dominated by N-fixing cyanobacteria.
However, the influence of shad nutrient cycling on
primary production may be dependent on nutrient
inputs from the watershed (Arbuckle and Downing
2001, Vanni et al. 2005) as well as seasonality and
interannual variability in population size and precipitation (Shostell and Bukaveckas 2004, Vanni et al. 2005).
Thus, it appears that species identity and abundance
must be taken into consideration to prevent, control, or
reverse eutrophication in reservoirs and other aquatic
systems.
At least in low-diversity systems like Acton Lake, it
seems that the abundance of a particular species as well
as its per capita effects can mediate its impact on the
functioning of an ecosystem. If species identity is found
to be crucial to ecosystem functioning in other low and
high diversity systems, then the concept of species
redundancy (Walker 1992) needs to be reevaluated.
Acknowledgements This work was supported by the Ohio
Dept of Natural Resources-Division of Wildlife grant
FADR47, NSF grant DEB 0235755, and the Miami Univ.
Dept of Zoology. We would like to thank Thomas O. Crist,
Marı́a González, John Bailer, Mike Hughes and members of
the Vanni and González labs for their comments, suggestions
and assistance. We would like to especially thank Anna
Bowling, Peter Levi, and Alberto Pilati for analyzing our
nutrient samples.
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