186
R. A. Ribeiro Filho et al.
According to the results found, the model predicts that
increasing concentrations of cyanobacteria involves depletion of fish catches in the Itaipu Reservoir. The correlation
coefficient explained 68 % ( p = 0.05). Piana et al. (2005), in
a study of 29 reservoirs of the state of Paraná, developed
a multivariate model, in which fish biomass was explained
by the chlorophyll-a and zooplankton variables. The authors
emphasize that the bottom-up effect in these environments is
explained by the positive relationship with chlorophyll-a and
negative with zooplankton.
The inference of fish yield calculated by the equation of
Meleck (1974) was 8.1 kg/ha/year and this result is similar to
that obtained by Agostinho and Gomes (2005), who found an
average of 7.9 kg/ha/year for the years 2000–2004, indicating that an analysis for the formulation of a specific model
for the reservoir can reveal accurate predictions.
It is important to stress that these models provide a quick
estimate, but the continued monitoring of professional and
amateur fishing over a long period of time (as it is currently
done by Itaipu) are of utmost importance for the understanding of fishing yield, as well as the dynamics of the structure
of species of the reservoir.
The relationship between MEI and water transparency
was verified by regression analysis. This relationship indicates that the increase in water transparency influences the
depletion of MEI (R = 0.687, p = < 0.001, F = 62.59), and the
relationship between chlorophyll-a and the MEI is inverse
to water transparency (R = 0.325, p = 0.005, F = 8.268). The
same behavior of relationships was also observed in Indian
reservoirs (Hasan et al. 2001), in which water transparency
had a negative effect and chlorophyll-a, positive. These relationships indicate that the analysis of the MEI and a series
of fish production data can generate a predictive model of
fishing yield for the reservoir. An analysis using the morphoedaphic index and catches may reveal a more accurate
model for fishing yield. According to Marouelli et al. (1988),
estimates on abundance and fishing yield are necessary as
tools for solving problems related to fisheries management
in reservoirs.
Another aspect to be considered is that all analyses of
water quality variables were performed with data collected
from the water surface. This may explain why the model
created that showed in Fig. 13.9 regarding data from cyanobacteria. This group of algae is dominant in the superficial
regions of lakes and reservoirs, and the action of winds is
a determining factor for the appearance of blooms (Tundisi
1990).
The lack of detailed information on fish production prevented the creation of more efficient and powerful predictive models. This line of research is of great value, and good
models that can infer the production and fishing yield in
lakes and reservoirs are tools that can be used by the agencies responsible for aquatic resources management in Brazil.
13.5 Conclusions
Evaluating the results, it was possible to conclude that the
trophic cascade hypothesis in the Itaipu Reservoir showed
both top-down and bottom-up effects, and the negative effect of piscivores was seen only in the trophic level below,
and the effect of the other levels were positive, featuring a
stronger bottom-up force. The cycle of the food web seems
to be explained by the omnivore and detritivore biomasses,
an effect observed in tropical and subtropical environments,
being of extreme importance in the (indirect) relationships,
and determining the controlling forces of primary productivity in the reservoir. The limnological variables in the Itaipu
Reservoir showed a pattern of spatial (horizontal) and temporal variations that is strongly dependent on the hydrological
regime. The forms of nutrients influenced the development
of primary productivity (as measured by chlorophyll-a),
and while the TKN and total phosphorus had a positive effect, ammonia nitrogen and nitrate had a negative effect.
The models created answer how these variables influence
the concentration of chlorophyll-a. The negative effect of
turbidity and suspended solids on water transparency was
confirmed by means of linear regression analyses, and the
generated models explain around 61 % of this effect at a high
significance level.
The transition zone was the one with the highest concentrations of nutrients, higher chlorophyll concentration, higher density of cyanobacteria and zooplankton and a higher
trophic degree, characterizing eutrophic conditions, but, on
average, it was considered mesotrophic.
The average results of the trophic state indices indicate
an oligotrophic status for the entire reservoir as well as for
the riverine, transition, and lacustrine zones separately. It is
possible to verify, during years of study, that the process of
eutrophication of the reservoir is occurring slowly, but some
high values found highlight larger inputs of nutrients.
The increase in primary productivity, expressed by chlorophyll-a, was explained by increased levels of total phosphorus in which the models were significant and responded
for more than 40 % of this ratio.
Cyanobacteria were dominant in the Itaipu Reservoir, and
their highest values were obtained in the transition zone. Increasing concentrations of chlorophyll-a were positive and
significantly related to the greater density of cyanobacteria.
Cyanobacteria also suffered the influences of abiotic variables such as water transparency, turbidity, suspended solids,
and TKN, and the latter had a negative effect on the development of algae. The model created explains 57 % of these
relationships.
The fishes that exercised the greatest control over cyanobacteria were omnivores and detritivores. The models explain about 88 % of the relationship pressure of these groups
of fish on these algae. Zooplanktivorous fishes did not pres-
R. A. Ribeiro Filho et al.
According to the results found, the model predicts that
increasing concentrations of cyanobacteria involves depletion of fish catches in the Itaipu Reservoir. The correlation
coefficient explained 68 % ( p = 0.05). Piana et al. (2005), in
a study of 29 reservoirs of the state of Paraná, developed
a multivariate model, in which fish biomass was explained
by the chlorophyll-a and zooplankton variables. The authors
emphasize that the bottom-up effect in these environments is
explained by the positive relationship with chlorophyll-a and
negative with zooplankton.
The inference of fish yield calculated by the equation of
Meleck (1974) was 8.1 kg/ha/year and this result is similar to
that obtained by Agostinho and Gomes (2005), who found an
average of 7.9 kg/ha/year for the years 2000–2004, indicating that an analysis for the formulation of a specific model
for the reservoir can reveal accurate predictions.
It is important to stress that these models provide a quick
estimate, but the continued monitoring of professional and
amateur fishing over a long period of time (as it is currently
done by Itaipu) are of utmost importance for the understanding of fishing yield, as well as the dynamics of the structure
of species of the reservoir.
The relationship between MEI and water transparency
was verified by regression analysis. This relationship indicates that the increase in water transparency influences the
depletion of MEI (R = 0.687, p = < 0.001, F = 62.59), and the
relationship between chlorophyll-a and the MEI is inverse
to water transparency (R = 0.325, p = 0.005, F = 8.268). The
same behavior of relationships was also observed in Indian
reservoirs (Hasan et al. 2001), in which water transparency
had a negative effect and chlorophyll-a, positive. These relationships indicate that the analysis of the MEI and a series
of fish production data can generate a predictive model of
fishing yield for the reservoir. An analysis using the morphoedaphic index and catches may reveal a more accurate
model for fishing yield. According to Marouelli et al. (1988),
estimates on abundance and fishing yield are necessary as
tools for solving problems related to fisheries management
in reservoirs.
Another aspect to be considered is that all analyses of
water quality variables were performed with data collected
from the water surface. This may explain why the model
created that showed in Fig. 13.9 regarding data from cyanobacteria. This group of algae is dominant in the superficial
regions of lakes and reservoirs, and the action of winds is
a determining factor for the appearance of blooms (Tundisi
1990).
The lack of detailed information on fish production prevented the creation of more efficient and powerful predictive models. This line of research is of great value, and good
models that can infer the production and fishing yield in
lakes and reservoirs are tools that can be used by the agencies responsible for aquatic resources management in Brazil.
13.5 Conclusions
Evaluating the results, it was possible to conclude that the
trophic cascade hypothesis in the Itaipu Reservoir showed
both top-down and bottom-up effects, and the negative effect of piscivores was seen only in the trophic level below,
and the effect of the other levels were positive, featuring a
stronger bottom-up force. The cycle of the food web seems
to be explained by the omnivore and detritivore biomasses,
an effect observed in tropical and subtropical environments,
being of extreme importance in the (indirect) relationships,
and determining the controlling forces of primary productivity in the reservoir. The limnological variables in the Itaipu
Reservoir showed a pattern of spatial (horizontal) and temporal variations that is strongly dependent on the hydrological
regime. The forms of nutrients influenced the development
of primary productivity (as measured by chlorophyll-a),
and while the TKN and total phosphorus had a positive effect, ammonia nitrogen and nitrate had a negative effect.
The models created answer how these variables influence
the concentration of chlorophyll-a. The negative effect of
turbidity and suspended solids on water transparency was
confirmed by means of linear regression analyses, and the
generated models explain around 61 % of this effect at a high
significance level.
The transition zone was the one with the highest concentrations of nutrients, higher chlorophyll concentration, higher density of cyanobacteria and zooplankton and a higher
trophic degree, characterizing eutrophic conditions, but, on
average, it was considered mesotrophic.
The average results of the trophic state indices indicate
an oligotrophic status for the entire reservoir as well as for
the riverine, transition, and lacustrine zones separately. It is
possible to verify, during years of study, that the process of
eutrophication of the reservoir is occurring slowly, but some
high values found highlight larger inputs of nutrients.
The increase in primary productivity, expressed by chlorophyll-a, was explained by increased levels of total phosphorus in which the models were significant and responded
for more than 40 % of this ratio.
Cyanobacteria were dominant in the Itaipu Reservoir, and
their highest values were obtained in the transition zone. Increasing concentrations of chlorophyll-a were positive and
significantly related to the greater density of cyanobacteria.
Cyanobacteria also suffered the influences of abiotic variables such as water transparency, turbidity, suspended solids,
and TKN, and the latter had a negative effect on the development of algae. The model created explains 57 % of these
relationships.
The fishes that exercised the greatest control over cyanobacteria were omnivores and detritivores. The models explain about 88 % of the relationship pressure of these groups
of fish on these algae. Zooplanktivorous fishes did not pres-