special publication sj 92-sp-4 ichthyofauna …
TRANSCRIPT
Special Publication SJ 92-SP-4
ICHTHYOFAUNA RECONSTRUCTION FORTHE MANAGEMENT OF PHYTOPLANKTON
by
Jerome V. Shiremanand
Karol K. Opuszynski
University of FloridaDepartment of Fisheries and Aquaculture
Prepared for
St. Johns River Water Management DistrictPalatka, Florida
1992
CONTENTS
Executive Summary iii
List of Figures v
List of Tables vii
ABSTRACT 1
INTRODUCTION 2
STUDY SITE 5
Lake Apopka 5Experimental Ponds 5
METHODS 9
Experimental Design and Fish Stocking 9Physico-chemical Water Quality Parameters 9Phytoplankton 12Zooplankton 12Fish Food Habits and Growth 15Statistical Analyses 16
RESULTS 19
Water Quality 19Water and Nutrient Budget 31Phytoplankton 31Zooplankton 42Fish Food Habits 42Fish Growth 52
DISCUSSION 60
CONCLUSIONS 67
References 68
ii
Executive Summary
Experimental ponds were used to test the hypothesisthat bighead carp, a filter-feeding fish, could improvewater quality and reduce the excessive growth of nuisancealgae in Lake Apopka. Six experimental ponds were builtadjacent to the lake and received water from Lake Apopka.Four ponds were stocked with bighead carp. Two ponds werenot stocked and used as control ponds.
Out of sixteen physico-chemical parameters measured,seven were significantly different between Lake Apopka andthe ponds. Secchi disk visibility was greatest in theponds, along with higher values of specific conductance.Total alkalinity in the fish stocked ponds was higher thanin the lake, but no difference was found between thecontrol ponds and the lake. Total nitrogen, totalphosphorus, total chlorophyll a_, and filtered chlorophyll _awere higher in the lake.
No differences in plankton abundance were foundbetween the lake and the control ponds for blue-greenalgae, Botryococcus Braunii, total algae number, rotifers,copepods, and total zooplankton number groups. Theseparameter values, however, were significantly lower in theponds stocked with bighead carp than in the lake. Itsuggests that bighead carp exerted some effect on the pondecosystem, but this effect was not large enough to causesignificant differences between the stocked and unstockedponds. The algal community in the ponds and lake wascharacterized by an extreme dominance of blue-green algae,reduced number of total algal species, and a cleardominance by several algal species (Spirulina lesissuna,Lyngbya contorta, L_. limnetica, L_. lagerheinii andMicrosvstis incerta). A large green algae, BotryococcusBraunii, despite low numerical occurrence, constituted animportant component of the algal biomass (more than 45% atthe lake intake site and more than 25% in the ponds, basedon chlorophyll _§_ determination) . Bighead carp fedselectively on B_. Braunii, which comprised 66 to 70% of thevolume and 50 to 60% of the dry weight of the fish food.Bighead carp did not reduce algal numbers in the ponds butdid decrease the ratio of blue-green/green species in thepond algal community. Using the data collected in thisstudy, we calculated that a biomass of 750 kg/ha of bigheadcarp would be needed to cause a significant reduction in B_.Braunii abundance in Lake Apopka within 8 days. Thisbiomass was not achieved during the study due to the slowgrowth and high mortality of stocked fish, and short
iii
experimental time period. The small size of the fish alsocontributed to their inability to reduce the algal biomass,
iv
FIGURES
Figure Page
1 Location of Lake Apopka in the Oklawaha Chainof Lakes 6
2 Land use distribution in the Lake Apopkawatershed (modified from Brezonik et al.1978) 7
3 Experimental pond relationship to Lake Apopka(arrows indicate direction of water flow;numbers indicate pond number and water samplingstations) 8
4 Relationship between percentage of BotryococcusBraunii in fish food estimated by volume anddry weight methods 17
5 Secchi disk depths in control ponds and LakeApopka 23
6 Seasonal pH values for the control pond groupand Lake Apopka 24
7 Seasonal total alkalinity values for theexperimental pond group and Lake Apopka . . . 25
8 Seasonal specific conductance values for thecontrol pond group and Lake Apopka 26
9 Seasonal total nitrogen values for the controlpond group and Lake Apopka 28
10 Seasonal total phosphorus values for thecontrol pond group and Lake Apopka 29
11 Seasonal total chlorophyll a_ values for thecontrol pond group and Lake Apopka 30
12 Nutrients retained in the ponds (in % of totalincome) 33
13 Seasonal blue-green algae numbers for theexperimental pond group and Lake Apopka . . . 38
FIGURES
14 Seasonal Botryococcus Braunii numbers for theexperimental pond group and Lake Apopka . . . 39
15 Seasonal total algae numbers for theexperimental pond group and Lake Apopka . . . 40
16 Seasonal rotifer numbers for the experimentalpond group and Lake Apopka 44
17 Seasonal copepod numbers for the experimentalpond group and Lake Apopka 45
18 Seasonal total zooplankton numbers for theexperimental pond group and Lake Apopka . . . 46
19 Relationship between dry and wet weight ofbighead carp food 55
20 Weight-class distribution of bighead carpfrom the ponds (12-21-90 to 01-02-91) . . . . 57
VI
TABLES
Table Page
1 Total number and average weight (g) atstocking of bighead carp in experimentalponds 10
2 Grass carp stocking rates (number of fishper pond) in experimental ponds 11
3 Qualitative and quantitative analysis ofalgae retained by and prefiltered througha 35 Jim nitex screen (ind./ml of water) . . 13
4 Statistical test performed 18
5 Statistical analysis of the differencesbetween the experimental pond groups andLake Apopka for the period 02-27-90 to08-22-90 20
6 Mean values and standard deviation ofphysical-chemical parameters for theperiod 02-27-90 to 08-22-90 22
7 Water budget for the period 02-27-90 to08-22-90 (mVha) 32
8 Nitrogen budget for the period 02-27-90to 08-22-90 (kg NT/ha) 34
9 Phosphorus budget for the period 02-27-90to 08-22-90 (kg PT/ha) 35
10 Mean values and standard deviation of thephytoplankton data for the period 02-27-90to 08-22-90 36
11 The ratio of blue-green/green algae fromthe lake and ponds 41
12 Mean values and standard deviation of thezooplankton data for the period 02-27-90to 08-22-90 43
Vll
TABLES
13 Characteristics of bighead carp food,percentage of zooplankton and planktonand detritus (by volume) 48
14 Characteristics of bighead carp food,percentage of Botryococcus Braunii(by volume and by dry weight) 49
15 Characteristics of bighead carp food, numberof algae (x 103 g fish body weight"1) andselectivity for IB. Braunii 50
16 The ratio of blue-green to green algaein the fish food 51
17 Fullness of three sections of bighead carpalimentary tract 53
18 Quantity of food in intestinal tract . . . . 54
19 Mean weight of fish collected each date andused for food analysis 56
20 Fish survival rate and biomass estimated bymark-recapture procedure (12-21-90 to01-02-91) 59
21 Hypothetical Botryococcus consumption perhectare-meter by different stock densities ofbighead carp for Lake Apopka 64
viii
ABSTRACT
This study was conducted to determine if bighead carp,(Hvpophthalmichthvs nobilis), an asiatic filter feedingfish, could reduce the abundance of nuisance algae in LakeApopka. Six 0.2 hectare experimental ponds adjacent toLake Apopka received water from the lake by gravity flow.Water clarity in Lake Apopka was significantly lower thanin the ponds throughout the study. Lake waterconcentrations of total nitrogen, total phosphorus andchlorophyll a. were also greater. This last constituentreflects algal biomass in water. Bighead carp had nostatistically proven influence on any of the water qualityparameters tested, except for a decreased ratio of blue-green/green algal species. Algal species collected in boththe ponds and lake were similar, although algal abundancein the lake was greater.
The biomass of bighead carp needed to impact the algaewas not achieved in our experiment due to slow growth andhigh mortality of stocked fish and the short experimentaltime. Therefore, the hypothesis that bighead carp wouldreduce nutrients and change the algal community was notfully tested. Bighead carp selectively ate BotryococcusBraunii, a large green algal species present in LakeApopka. We postulated that a biomass of about 750 kg/ha ofbighead carp could alleviate this nuisance algae in thelake in 8 days. This biomass figure is probablyoverestimated because small fish and low algal densitieswere used for the calculations.
INTRODUCTION
Shapiro et al. (1975) originally defined the termbiomanipulation as "the management of aquatic communitiesby controlling natural populations of organisms aimed atwater quality improvement". Verigin (1979) proposed thatbalanced ecosystems could be developed by changing the fishpopulations in lakes. He termed this "ichthyofaunareconstruction". Although biomanipulation has been largelyignored as a management and restoration technique (Shapiro1979a), experiments in Israel (Leventer 1979, 1972), Europe(Opuszynski 1979), and the United States (Henderson 1978,1979) indicate that the method might be used to reducenutrients and algae. Shireman et al. (1979), Shireman andMaceina (1981) and Shireman et al. (1983) demonstrated thatgrass carp (Ctenopharyngodon idella) can be used to manageexcessive growths of aquatic plants. This is the firststep in alleviating one of the problems of eutrophication,because macrophytes in abundance may be unacceptable to thegeneral public.
The potential for using biomanipulation, particularlyichthyofauna reconstruction and management, for improvinggame-fish populations through the removal of rough-fish wasfirst suggested in early fish management programs in theupper midwest (Ricker and Gottschalk 1941; Moyle 1949;Threinen 1949; Rose and Moen 1952) . Test seining inhypereutrophic East Okoboji Lake (Iowa) in 1940 showed thelake had a very large population of rough-fish includingbigmouth buffalo (Ictiobus cyprinellus), carp (Cvprinuscarpio), and freshwater drum (Aplodinotus grunniens), andrelatively few game-fish (Rose and Moen 1952). Inaddition, the lake was subject to dense blooms of blue-green algae, particularly Aphanizomenon sp. and Microcvstissp., which greatly reduced water clarity. After extensiveremoval of rough-fish by use of haul seines, Rose and Moen(1952) showed that game-fish populations improvedsignificantly. Aquatic macrophytes, particularly submersedplants, returned to the lake in abundance. Dense growthsof blue-green algae were greatly limited, whichsignificantly improved water clarity. Similar changes alsooccurred in other lakes (Ricker and Gottschalk 1941; Moyle1949; Threinen 1949), suggesting the changes represented ageneral response pattern in lakes. In addition, theprocess is reversible. Studies by Bachmann and Jones(1974) and Canfield (1979) showed that East Okoboji Lakehad lost its macrophyte community and redeveloped dense
blooms of blue-green algae by the 1970s after rough-fishremoval programs were discontinued in the 1950s.
Although changes in the overall quality of lakes havelong been correlated with changes in fish populations, onlyrecently have hypotheses been developed to explain thecausal mechanisms. Many scientists contend the influenceof fish is directly related to their effect on zooplanktongrazing. Lake studies have shown that small fish of allspecies and obligate zooplanktivorous fish can, throughtheir feeding activities, alter not only the abundance, butsize-distribution and species composition of thezooplankton community (Hrbacek et al. 1961, Brooks andDodson 1965, Galbraith 1967, Hutchinson 1971) . Studies byAnderson et al. (1978) and Lynch (1979) showed that theaddition of zooplanktivorous fish to enclosures in northernlakes reduced zooplankton levels and increased algallevels, whereas the removal of zooplanktivorous fishresulted in increased zooplankton abundance and reductionsin algal abundance. There is evidence, however, thatzooplankton sometimes have little effect on algal biomassin some northern lakes and many southern lakes (Hoyer andJones 1983, Canfield and Watkins 1984). Other studies alsosuggest that the zooplankton size-efficiency hypothesis isnot as simple as once believed. As suggested by Shapiro(1979a,b), the phytoplankton population response to grazingby large zooplankters is not uni-directional, but dependson the community structure and species composition of theinitial algal assemblage. For example, increased daphnidpopulations resulted in a shift in algal dominance fromblue-greens to greens, chrysophytes, diatoms, andeuglenoids in Severson Lake (Schindler and Comita 1972) andWirth Lake, Minnesota (Shapiro 1979a). The appearance ofsimilar daphnid populations in Lake Washington (Shapiro1979b), caused blue-green populations, especiallyAphanizomenon. to increase. This seemingly unpredictablephytoplankton response is probably controlled by thebiochemically induced formation of large coloniesunsuitable for zooplankton grazing, such as observed forAphanizomenon in the presence of large Daphnia (Hrbacek1964, Shapiro 1979a,b). Thus, the complex response ofphytoplankton to an alteration of trophic levels remainspoorly known (Crisman 1986).
Manipulations of fish populations for the managementof nuisance growths of aquatic plants received increasedattention during the 1970s. Several phytophagous fishincluding Tilapia aurea, Tilapia galilia, silver carp,
(Hvpophthalmichthvs molitrix), and bighead carp,(Hvpophthalmichthvs nobilis), were identified (see Shireman(1984) for a review of the literature). Of the knownphytophagous species, only the Chinese carp (i.e., silvercarp, bighead carp, and grass carp) have been routinelyused for the control of nuisance growths of phytoplanktonand aquatic macrophytes (Vovk 1973, Leventer 1979 and 1987,Verigin 1979, Shireman & Maceina 1981, Shireman 1984,Shireman and Hoyer 1986) .
Silver carp and bighead carp have been used primarilyto consume phytoplankton (Moskul 1977) and detritus (Moskul1977, Vovk 1973) . Henderson (1978, 1979) reported thatgrazing of plankton in Arkansas oxidation ponds by silverand bighead carp reduced ammonia nitrogen levels by 27% andphosphate levels by 2.72%. Organic loads (BOD5) werereduced by 96% and total suspended solids were reduced by78% (Henderson 1983) . These ponds contained 2280 pounds ofsilver carp/acre and 156 pounds of bighead carp/acre. Theadvantage of using bighead carp over silver carp forphytoplankton control, however, has been that bighead carpconsume larger algae (Huisman and Hogendoorn 1979) andutilize greater amounts of blue-green algae (Lazareva etal. 1977, Aliyev 1976, Verigin 1979), which often leads toincreased fish production (Verigin 1979) .
This research project has been aimed to test thehypothesis (Leventer 1979, Verigin 1979) that ichthyofaunareconstruction and management (biomanipulation-Shapiro1975) could be used to manage many of the deleteriouseffects (e.g. excessive growths of phytoplankton) of lakeeutrophication. Although Leventer (1972, 1979) used thistechnique to reduce nuisance macrophytes, algae, andnutrients in Israeli reservoirs, the technique has not beenused to manage total lake ecosystems in the U.S. Theobjective of the project was to determine the potentialimpact of bighead carp on algal biomass and composition,and water quality in Lake Apopka.
STUDY SITE
Lake Apopka
Lake Apopka is a large hypereutrophic lake located inOrange and Lake counties (latitude 28° 37' N and longitude81° 38' W). Lake Apopka is the first lake in the Oklawahachain of lakes (Figure 1) with a drainage basin of 31,100ha. Population centers within the basin are Winter Garden,Ocoee, Apopka, Montverde, Tavares, Mont Dora, Eustis, andLeesburg. The basin is characterized by undulating hillsunderlain with limestone of the Florida aquifer (Brezoniket al. 1978) . Muck farming is restricted to the northernend of the lake (Figure 2). Prior to recent freezes,citrus groves also abounded around the lake. Many of thesegroves are no longer in production.
Lake Apopka has a surface area of 12,467 ha, meandepth of 1.5 m, maximum depth of 4.9 m and a shorelinedevelopment (SLD) of 1.391. The lake bottom consistsprimarily of unconsolidated muck averaging 1.8 m deep,(Danik and Tomlinson 1989) . These sediments are relativelyconsistent in appearance (black-brown) and have a watercontent ranging from 67-95%. (Schneider and Little 1968) .
Experimental Ponds
Six ponds were constructed adjacent to Lake Apopka bythe Zellwood Drainage and Water Control District (Figure3). Each pond had an area of approximate 0.2 ha and depthsranging from 91 to 104 cm. In order to preventpercolation, the ponds were lined with high-densitypolyethylene fabric. The plastic liners were covered with15 cm of organic soil.
Lake Apopka water was used to fill the ponds and forflow-through water. Gravity-flow water entered the pondsthrough valved inflow pipes and left through outflow pipes.However, when adequate pond water levels could not beachieved by gravity flow, water was pumped into the pondsfrom Lake Apopka.
1 SSLD= _ , where S = length of shoreline,
a = area of lake
BurrellLock & Dam
Apopka-Beauciai rLock & Dam
Miles
0 1 2 3 4 5I I ! 1 ! I
I i 1 i 1 I i I I
0 1 2 3 4 5 6 7 8
Kilometers
WinterGarden
Figure 1. Location of Lake Apopka in the Oklawaha Chain of Lakes.
PLYMOUTH
APOPKA5PRING
APOPKA
LAKE APOPKAMAGNOLIACOUNTYPARK
OCOEE
WtffTERGARDEN
1 2 3
MILES
Figure 2. Land use distribution in the Lake Apopka
watershed (modified from Brezonik et al. 1978).
1
a;a.
LAKE APOPKA
LEVEE
6LSD
5C
4HSD
3LSD
2C
1HSD
Figure 3. Relationship of experimental ponds to Lake Apopka
(arrows indicate direction of water flow; numbers indicate pond
number and water sampling stations). LSD = low stock density, and
HSD = high stock density ponds. C = control ponds.
8
METHODS
Experimental Design and Fish Stocking
Ponds were selected randomly for three experimentalgroups. Ponds 2 and 5 were not stocked with bighead carpand were used as control ponds. Ponds 3 and 6 were lowstock density (LSD) bighead carp ponds, and ponds 1 and 4were high stock density (HSD) ponds. Pond stockingcommenced on January 4, 1990, and continued until June 20,1990. Completion of pond stocking was significantlydelayed due to slow growth of the fish, problems with theploidy verification procedure, and the cold winter of1989/90 which caused heavy mortality of fish in holdingtanks. The number and biomass of stocked fish was 2,564•and 28.4 kg in the HSD ponds and 425 and 4.6 kg, in the LSDponds (Table 1). The stocking values calculated perhectare were 12,671 fish and 141 kg in the HSD ponds, and2,100 fish and 23 kg in the LSD ponds.
All ponds were stocked with grass carp to controlmacrophytes. Different numbers of grass carp were stockedinto each pond to keep macrophytes in check during thegrowing season (Table 2). All fish used for the experimentwere sterile triploids to prevent the possibility of theirreproduction in case of escape into the lake.
Physico-chemical Water Quality Parameters
Water quality, phytoplankton, zooplankton, and fishsamples used for preparation of this report were collectedfollowing fish stocking from February 27, 1990 to August22, 1990.
Surface water samples (0.5 meter depth) for physico-chemical analyses were collected biweekly (twice monthly)from a midpond station in each of the experimental pondsand at the Lake Apopka inlet site. The followingparameters were determined for the ponds: temperature,dissolved oxygen, Secchi disk visibility, depth, waterinflow and outflow rate, pH, total alkalinity, specificconductance, calcium, magnesium, sodium, potassium,chloride, total nitrogen, total phosphorus, totalchlorophyll a. and filtered chlorophyll a. (filter mesh size= 35 |lm) . The same parameters, excluding water depth andflow rate, were determined simultaneously for the LakeApopka inlet site.
Table 1. Total number and average weight (g) at stocking of bighead carp inexperimental ponds.
1 (HSD)
Date
01/04/9001/12/9001/19/9001/26/9004/10/9005/15/9006/18/9006/20/90
number
87048346236540503
21
Avg.weight
11.111.111.111.912.010.0
10.0
PONDS
4 (HSD)
number
87048346236540503
23
Avg.weight
11.111.111.111.912.010.0
10.0
3 (LSD)
number
100
150
175
Avg.weight
11.1
11.9
10.0
6 (LSD)Avg.
number weight
100 11.1
150 11.9
175 10.0
2564 11.1 2566 11.1 425 11.0 425 11.0
Note: LSD and HSD - low and high stocking density ponds.
Table 2. Grass carp stocking rates (number of fish per pond) in experimental ponds
Date
09/15/8910/18/8910/25/8911/09/8905/15/9005/25/9006/14/9006/20/9007/10/9007/30/9008/16/90
Pond 1
410
512
Pond 2
410
2
520547
Pond 3
410147
2
Pond 4
410
5
1028
20547
Pond 5
410
6
2
Pond 6
410
5
2
205
Total 22 93 37 129 22 46
Water temperature and dissolved oxygen concentrationswere determined using a YSI oxygen-temperature probe.Water transparency was measured with a Secchi disk. Waterinputs and outputs through inflow and outflow pipes weremeasured by collecting water in a calibrated cylinder andtiming with a stop-watch. All other chemical parameterswere determined following standard methods (APHA 1980) .
Phytoplankton
One liter surface water (0.5 meter depth) samples forphytoplankton were collected biweekly from each pond andthe lake. Algal abundance, as indicated by chlorophyll _aconcentrations, was determined using the methods ofRichards and Thompson (1952) and Yentsch and Menzel (1963).Water samples were also filtered through a 35 (J.m nitexscreen to determine the relative abundance of net andnanoplankton components. However, as shown in Table 3,this method mainly allowed separation of BotryococcusBraunii- from other algal species. Larger 13. B.. colonieswere retained by the 35 (im screen, whereas smaller B_.B_.colonies together with the bulk of other algae passedthrough the screen. Therefore, this method underestimatedthe percentage of B_.B_. in the phytoplankton biomass.
Algae samples were collected monthly for quantitative andqualitative analyses. Samples were preserved in Lugol'ssolution immediately after collection and were transportedin a cooler filled with ice. Quantitative analysis ofalgae was made using the Edmondson (1971) method, whereasspecies composition was determined using Smith (1950),Prescott (1982), and Whitford and Schumacher (1984) keys.
Zooplankton
Initially, zooplankton samples were collected by threevertical net tows with an 80 }im Wisconsin plankton net.This method proved to be impractical in the shallow ponds,and was replaced beginning in October 1989 with a 3-litercapacity water sampler. Four samples were collected andcomposited from each pond. Zooplankton were preserved in4% formalin solution, enumerated, and identified to speciesusing Edmonton (1976), Pennak (1978) and Stemberger (1979).
2We followed Prescott's (1982) capitalization of the speciesname to commemorate Alexander Braun. However, lower case (B_.braunii) is also used (e.g., Whitford and Schumacher 1984).
12
Table 3. Qualitative and quantitative analysis of algae retainedby and prefiltered through a 35 /xm nitex screen(ind./ ml of water)
Species
08-08-90 Lake Apopka
Macrocistis incertaSpirulina laxissimaLyngbya contortaL. limneticaL. lacrerheimii
Total algae exc. BotryococcusBotryococcusBotrvococcus mean size (jum)Botryococcus mean volume (/m3)Botryococcus total volume (wm3)
Retained
242036301210
00
726017133
198817733799014
Prefiltered
209330164560217802780010890
434360240
83369191749
08-08-90 Pond 4
Macrocystis incertaSpirulina laxissimaMerismopedia tenuissimaLyngbya contortaChroococcus sp.Merismopedia sp.Lyngbya limneticaL. lagerheimiiMicrocystis aeruginosaAnkistrodesmus falcatusAphanothece nidulans
00000000
40300
Total algae exc. BotryococcusBotryococcusBotryococcus mean size (/im)Botryococcus mean volume (jum3)Botryococcus total volume
08-08-90 Pond 5
Macrocystis incertaSpirulina laxissimaLyngbya limneticaL. lagerheimiiL. contortaScenedesmus guadricaudaAphanocapsa delicatissimaMerismopedia tenuissimaDiatomsTetraedron sp.Chroococcus sp.
403675
3359181948324
060492016
040300000
403
37507104861210363032262823604920168064840403
72996346
66603193149
3992717261241137604972594034031210403403403
13
Total algae exc. Botryococcus 8871 270209Botryococcus 8 4Botrvococcus mean size (Mm) 72 40Botryococcus mean volume (/mS) 474438 58982Botryococcus total volume (Mro3) 3937835 265419
14
Fish Food Habits and Growth
When possible, 10 fish were collected monthly fromeach pond. They were killed immediately after capture andtransported on ice to the laboratory. The fish weremeasured, weighed, and their alimentary tracts (AT)dissected. Each AT was divided into three equal sectionsand the degree of filling was determined according to afive-degree scale (Pavlovskij 1961) . Food was removedcarefully from all AT and weighed to determine wet biomass.Index of filling (wet weight of food expressed inpercentage of fish body weight) was used to comparequantity of food in the AT of different size fish. Allfood from each AT was mixed in a known volume of 4%formalin solution and a subsample equal to 9/10 of thetotal volume was taken to determine dry food weight. Thistotal subsample was used for analysis when food was in asmall quantity. Two aliquots of the first subsample weretaken when food was present in great quantity. Thesmallest subsample volume was 2.5 ml. This sample wasfiltered through a fiber glass filter (Gelman A/E) and theresidue dried at 103°C. The remaining 1/10 of AT contentfrom individual fish was mixed and qualitative andquantitative determinations of the contents were madeaccording to the methods previously described forphytoplankton and zooplankton examinations. The food offish smaller and larger than the mean of a sample wasexamined separately when the sizes of fish in a sample weredifferent.
Phytoplankton and zooplankton were identified tospecies when possible, and the number of organisms eatenwas calculated. Using these data the ratio of blue-green/green algae in the fish food was calculated. Theproportion of different food categories was also determinedusing the volumetric method. The bulk of the food wasdivided into three groups: 1) zooplankton, 2) BotryococcusBraunii (BB), and 3) phytoplankton/detritus. Volumetricproportions of each group in the AT were estimated.Volumetric proportions were calculated as a mean of twenty10 x 4 power microscopic fields examined. The volumetricmethod is a subjective one, because it consists of visualdetermination of the proportion of different food items ina sample. We found it possible to separate BB from theother food-items by sedimentation. This alga floated tothe surface in a 4% formalin solution, whereas the otherfood items sank to the bottom. Therefore, BB could be
15
separated by syphoning. Using this technique, the dryweight fraction of BB in the food was determined. Itallowed us to compare the results of the volumetricanalysis with the more objective weight method. Theresults of both methods proved to be in good agreement ascharacterized by a statistically significant correlationcoefficient r = 0.71 (Figure 4).
Food selectivity was measured using Ivlev's (1961)index (Ei), calculated as Ei = [zi - pi] / [zi + pi]where zi = the proportion of food type i in the AT, and pi- the proportion of the food type i in the environment.Values for this index range between -1 and +1, where -1indicates complete avoidance of a given food item, and +1indicates complete preference.
Statistical Analyses
Data were analyzed according to statistical testsshown in Table 4.
16
100
80-
60
dP
40-
20
V = 36.75 + 0.48W (r = 0.71)
i i i i i0 20 40 60 80 100
% DRY WEIGHT
Figure 4. Relationship between percentage of Botryococcus Braunii
in fish food estimated by volume (V) and dry weight (W) methods.
17
Table 4. Statistical tests performed.
Data set Statistical procedure
1. Pond differences - water
2. Control pond and Lake differences - water
3. Differences between treatmentgroups (control and experimental ponds)
Analysis of variance (ANOVA)Scheffe multiple-range test
Student "t" test
Student "t" test
oo
RESULTS
Water Quality
Mean temperature, dissolved oxygen, calcium,magnesium, sodium, potassium, and chloride values were notsignificantly different between the ponds and the lake(Table 5). Mean values for individual ponds for the studyperiod are shown in Table 6.
Secchi disk. Mean secchi disk readings were from 36cm to 72 cm in the ponds and 24 cm in Lake Apopka (Table6). The values among ponds were not significantlydifferent; however, all pond values were significantlyhigher than Lake Apopka values (Table 5). The readingswere more consistent in the lake, showing little seasonalvariability (Figure 5).
pH. Mean pH values were from 8.5 to 8.9 in the ponds(Table 6) and 9.0 in the lake, and were significantlydifferent between the ponds and the lake (Table 5).Seasonal pH variation was greatest in Lake Apopka (Figure6) .
Total Alkalinity. Mean values ranged from 117 mgCaCo3/l to 145 mg CaCo3/l in the ponds and 124 mg CaCo3/l inLake Apopka (Table 6). The control ponds were notsignificantly different from the lake, whereas theexperimental ponds were different from the lake (Table 5).Seasonal dynamics of the alkalinity values is shown onFigure 7.
Specific Conductance (SC). Mean SC in the ponds wasfrom 408 |lmhos/cm to 460 |j,mhos/cm (Table 6) . Mean SCvalues for the lake were significantly lower (409 \Jimhos/cm; Table 5). SC values were lower in the lake thanin the ponds during the summer months and higher during thewinter months (Figure 8). These seasonal trends weresimilar to those found by Brezonik et al (1978).
19
Table 5. Statistical analysis of the differences between the experimental pondgroups and Lake Apopka for the period 02-27-90 to 08-22-90. Mean values +. S.D. arelisted.
Parameter
Temperature (°C)Dissolved Oxygen (mg/1)Secchi Disc (cm)Water inflow rate (I/sec)PHTotal alkalinity
(mg/1 CaCo3)Specific conductance
((imhos/cm)Calcium (mg/1)Magnesium (mg/1)Sodium (mg/1)Potassium (mg/1)Chloride (mg/1)Total nitrogen (mg/1)Total phosphorus (mg/1)Chlorophyll a (p.g/1)Filtered chlorophyll a
Lake
2 8 . 0 + 5 . 0 a
9 . 4 + 1.93
2 4 . 4 + 3 . 5 a
0 .53+0 .24 b
9 .0+0 .5 a
124il8a
409i26a
33 .6+8 .7 a
2 0 . 0 + 2 . 8 a
19.7+3.0 a
13.2+0.7 a
4 8 . 5 + 2 . 4 a
5.01+0.72 a
0. 174+0. 065a
116. 4+29 . la
64. 3+11. la
Control(2, 5)
26 .5+4 .1 a
8.5+2.13
51. 9+20. 2b
0.55+0.38 b
8 . 7 + 0 . 4 b
133±14ab
440i30b
35.2+5.7 a
20.4+1.3 3
19.8+2.2 a
13.4+1.0a
4 9 . 7 + 3 . 9 a
3 .33+0 .72 b
0. 070 + 0. 026b
30. 8+11. Ob
2 3 . 2 + 7 . 6 b
Experimental(1, 3, 4, 6)
2 6 . 7 + 4 . 0 3
8 .5+2 .0 a
53.5il7.4b
8 . 7 + 0 . 4 b
135+_14b
442±38b
35.8+5.8a
20.5+1.8 a
19.7+2.0 3
13.7+1.2a
5 0 . 0 + 3 . 6 a
3 .27+0 .73 b
0. 0 6 7 + 0 . 021b
31. 4+10. 3b
2 4 . 7 + 8 . 3 b
Blue-green Algae/ml x 1000
Green Algae/mlBotryococcus/mlTotal Algae/ml x 1000Rotifers/1Nauplii & Copepodids/1Copepods/1
272.3±96.4 a
1108±1032a
145.3jtl43.9ab
3866i8876aab
274.8i95.6a
1096±1802a
197±165a
20 + 30a
150. 1^141. 3ab
187J:188ab
156±112a
5+5ab
128.5±105.7b
2297i3016a
7i4b
131 .4 l05 .2 b
95±107a
3+5b
o04
Table 5. (Cont'd)
Parameter
Cladocera/1Other Zooplankton/1Total Zooplankton/1
Lake
323 + 356a
0 + 0a
1640+1683a
Control(2, 5)
221+444a
0.1+0.5a
569 + 523ab
Experimental(I, 3, 4, 6)
100+2343
0.2+0.73
342+355b
Note: Means with the different letters are statistically different (P=0.05)
Table 6. Mean values and standard deviation of physical-chemical parameters for the period 02-27-90 to 08-22-90.
ParameterL S D H S D
1 4L a k e
Temperature (°C)Dissolved oxygen (mg/1)Secchi disc reading (cm)Depth (cm)Water inflow rate (I/sec)PHTotal alkalinity
(mg Co.Co3/l)Specific conductance
((Jmhos/cm)Calcium (mg/1)Magnesium (mg/1)Sodium (mg/1)Potassium (mg/1)Chloride (mg/1)Total nitrogen (mg/1)Total phosphorus (mg/1)
Total chlorophyll a
Filter chlorophyll a(jig/D
26.7+ 4.19.1+1.936+9102+7
0.49+0.208.9+0.313516
439122
35+421+220+314+150+4
3.64+0.660.09210.023
41.519.1
32 . 315 . 3
26.8+4.28.2+2.059+7108+2
0.45+0.198.5+0.214217
460129
39+321+220+214 + 150 + 4
3.17+0.750.05310.012
26.217.3
22.117.7
.4+4.18.5+1.547 + 13109+3
0.45+0.198.7+0.314517
60126
40+121+220+214+151+4
3.27+0.660.06710.011
31.115.5
23.314.3
26.8+4.18.2+2.772+1399 + 10
0.79+0.648.7+0.5117115
408146
29+619+119+213+148+3
3.02+0.770.05510.009
27.6111.5
21.2110.2
26.6+4.17.9+2.468+19108+3
0.55+0.198.5+0.412417
430117
32 + 420 + 119+213+149+4
3.10+0.770.05610.025
24.419.9
18.114.4
26.5+4.29.1+1.638+6106+4
0.51+0.308.9+0.3141115
450138
39+421+120+214+150+4
3.57+0.610.08410.018
37.218.0
28.316.8
28.0+5.09.4+1.92413
9.0+0.5124118
409126
34+920+320+313+148+25.01+0.720.174+0.065
116.4129.1
64.3111.1
CMCN
Note: C - control ponds, LSD - low stocking density and HSD - high stocking density ponds.
OTccUJ
UJs
UJo
CONTROL PONDS
LAKE APOPKA
SEP NOV JAN
1989
MAR
MONTH
MAY JUL
1990
Figure 5. Secchi disc depths in control ponds and Lake Apopka.
The arrow shows beginning of the period included in the present
analysis.
23
• CONTROL PONDS
a LAKE APOPKA
8-
SEP MOV JAN MAR
1989
MAY JUL
1990
MONTH
Figure 6. Seasonal pH values for the control pond group and Lake
Apopka (the arrow - See Figure 5) .
24
LAKE APOPKA
ccIS
cc(3
155•* EXPERIMENTAL PONDS
145-
135-
105-
95
SEP NOV JAN MAR
1989
MAY JUL
1990
MONTH
Figure 7. Seasonal total alkalinity values for the experimental
pond group and Lake Apopka (the arrow - See Figure 5) .
25
LAKE APOPKA
£o
W
480CONTROL PONDS
460-
440-
420 i
400-
380-
360
SEP MOV JAN MAR MAY JUL
1989 1990
MONTH
Figure 8. Seasonal specific conductance values for the
control pond group and Lake Apopka (the arrow - See Figure 5).
26
Total Nitrogen (TN). Mean TN values were from 3.0mg/1 to 3.64 mg/1 in the ponds. These values weresignificantly lower than the 5.0 mg/1 mean value for LakeApopka (Tables 5 and 6). All seasonal values for LakeApopka were higher than those in the ponds (Figure 9).Seasonal variations in the ponds and lake were very similareven though the mean lake values were significantly higher.TN was highest during Oct.-Nov., 1989, and Feb.-March,1990. Lowest values were recorded during July-September,1989, and July and August, 1990. These seasonalrelationships are common to many Lakes and are similar toBrezonik et al. (1978) results. Pond values were lowestduring winter months (Dec. - Feb., 1989-90) highest duringMay, 1990, and lower during the summer.
Total Phosphorous (P). Mean total P values were from0.053 mg/1 to 0.092 mg/1 in the ponds. The mean value forthe lake was significantly higher (0.174 mg/1; Tables 5 and6). Seasonally P values was very similar in allexperimental ponds with little variation in the data. Lakefluctuation was greater (Figure 10) with maxima inNovember, February, June and August. During the othermonths values remained near 0.15 mg/1.
Total Chlorophyll a. Mean total chlorophyll a. valueswere from 24.4 (O.g/1 to 41.5 |ig/l in the ponds and 116.4JJ.g/1 in Lake Apopka (Table 6) . All pond values weresignificantly lower than lake values (Table 5). Similarly,as in the case of P, the dynamics of this parameter werevery similar in the experimental pond group with littlevariation among ponds. Seasonal variation in lake sampleswas much greater (Figure 11). Maximum values occurred fromDecember to May. Minimum values occurred from July throughSeptember, 1989, and from July through August, 1990.
Filtered Chlorophyll a. Mean seasonal values werefrom 18.1 |lg/l to 32.3 fig/1 in the ponds and 64.3 ug in thelake (Table 6). The mean lake value was significantlyhigher than for all the experimental ponds (Table 5). Thedifference between total chlorophyll a. and the
27
DCUJ
V)
<oco
LAKE APOPKA
CONTROL PONDS
SEP NCV JAN MAR
1989
MAY JUL
1990
MONTH
Figure 9. Seasonal total nitrogen values for the control pond
group and Lake Apopka (the arrow - See Figure 5).
28
cc1Ut
DC0
SEP NOV JAN MAR MAY JUL
1989 1990
MONTH
Figure 10. Seasonal total phosphorus values for the control pond
group and Lake Apopka (the arrow - See Figure 5).
29
200-LAKE APOPKA
CONTFO. PONDS
ccUJ
V)5
100-
SEP NOV JAN MAR
1989
MAY JUL
1990
MONTH
Figure 11. Seasonal total chlorophyll a values for the control
pond group and Lake Apopka (the arrow - See Figure 5).
30
chlorophyll a. retained by a 35 (im screen (retainedchlorophyll a. is calculted as the difference between totalchlorophyll a. and filtered chlorophyll a., see Methodssection p. 14) indicates the relative amount of BB andother "net" plankton in each sample. In the ponds, theamount of retained chlorophyll a. amounted to 21 to 25% ofthe total chlorophyll values, whereas in the lake theretained chlorophyll a. amounted to 45% of the totalchlorophyll value. This indicates that the share of BB andother "net" plankton in the lake was about 20% higher.
Water and Nutrient Budget
Water budget. Water inflow from Lake Apopka was themain source of water to the ponds. The highest seepage inpond 4 was reflected in the smallest outflow. This pondneeded an increased inflow to maintain an appropriate waterlevel (Table 7).
Nutrient budget. Water inflow from Lake Apopka wasthe main source of nitrogen and phosphorus in the ponds.About 50% of the nitrogen and 65% of the phosphorus wasretained in the ponds (Figure 12). There were no apparentdifferences in nutrient retention between the control andfish-stocked ponds. This is understandable considering thenegligible proportion of nutrients in the fish biomass(Table 8 and 9).
Phytoplankton
Bluegreen algae (BG). Mean total number of BG algaeranged from 58 x 103 to 233 x 103 individuals/ml in theponds (Table 10). The mean lake value was 272 x 103
individuals/ml, which was significantly greater than theexperimental pond values but not greater than the controlpond values (Tables 5 and 10). BG algal numbers increasedin all the experimental pond groups during the study.Maximum pond values were recorded in June, 1990. This wascontrary to the situation observed in the lake where twopeaks (October, 1989 and June, 1990) of algal abundanceoccurred during the season. Algal levels in the ponds
31
Table 7. Water budget for the period 02-27-90 to 08-22-90 (m3/ha).
Ponds
Sources Iof R
Water Total
Output
I - inflow0 - outlet
0ES
/ R -, E -
1
47,0206,875
53,895
7,66012,46533,770
2
52,3906,875
59,265
13,93012,46532,870
3
51,9656,875
58,840
4,80512,46541,570
rainfall (data from Sanford Station)evaporation (data from Lisbon Station;
4
68,8706,875
75,745
35512,46562,925
data for
5
44,7956,875
51,670
9,05512,46530,150
July and
6
46,7656,875
53,640
11,62012,46529,555
August are for 1989S - seepage (calculated as the differance between total income and the outlet plus the evaporation)
CMCO
UloDCUJQ.
TOTAL NITROGEN
TOTAL PHOSPHORUS
POND
Figure 12. Nutrients retained in the ponds in percentage of the
total input.
33
Table 8. Nitrogen budget for the period 02-27-90 to 08-22-90 (Kg NT/ha)
Ponds
Sourcesof
Nitrogen
Output
*N = T.iv •'-in
I
P
Total
0SF
Total
— T•••out
1
235.58.5
2 4 4 . 0
22.2108.0
Ox
130.2
113.8
2
2618
269
4296
138
131
.0
.5
.5
.0
.5
.5
.0
3
2558
264
16148
1165
98
.5
.5
.0
.0
.0
.2
.2
.8
4
345.8.
354.
1.182.
Ox
183.
170.
550
25
7
3
5
2298
237
29102
132
105
.0
.5
.5
.5
.5
.0
.5
6
235.08.5
243.5
32.589 .51.0
123.0
120.5
I - inflow, P - precipitation (data from Brezonik et al. 1979)0 - outflow, S - seepageF - nitrogen in fish tissue, Ox - no fish biomass increase
Table 9. Phosphorus budget for the period 02-27-90 to 08-22-90 (Kg PT/ha).
Ponds
Sourcesof
Phosphorus
Output
AP = Tln -
IPTotal
OSFTotal
•"•out
1
7.770.328.09
0.502.18Ox2.68
5.41
808
11
2
6
2
.66
.32
.98
.02
.72
.74
.24
809
0304
4
3
.76
.32
.08
.33
.45
.42
.20
.88
110
11
03
3
8
4
.62
.32
.94
.02
.50Ox.52
.42
707
02
3
4
5
.53
.32
.85
.79
.34
.13
.72
6
7.630.327.95
0.661.530.352.54
5.41
I - inflow, P - precipitation (data from Brezonik et al. 1979)0 - outflow, S - seepageF - phosphorus in fish tissue, Ox - no fish biomass increase
Table 10. Mean values and standard deviation of the phytoplankton data for the period 02-27-90 to 08-22-90,
Parameter
Blue-green Algae/ml x 1000
Green Algae/ml
Botryococcus /ml
Total Algae/ml x 1000
% Blue-green Algae
% Green Algae
% Botryococcus
L S3
224+_121
3753+_5552
8+_4
228+_117
96.1+6.2
3 . 5.+ 6 . 2
0.00+0.00
D6
74+34
1618+.1633
5+_5
7 6 +2 9
9 6 . 3+5 . 1
. 8 +3 . 4
0.00+.0.00
H S1
174+_96
1968+_1824
8+2
176+.97
98.6+JL.O
1 . 1 +_0 . 9
0.00+.0.00
D4
42+17
1850+.866
6+2
4 5 +.17
93.2̂ 3.3
4 . 4 ±2 . 4
0.00+.0.00
C2
58±35
7148+.12043
3+_3
66+.S2
81.4+26.2
14.3+25.5
0.00+0.00
5
233+.160
585̂ 728
9±9
234+_161
99.4+.0.5
0 . 2 _+ 0 . 2
0.00+.0.00
L a k e
272+96
1108+1032
12+_7
275+96
98.9±0.8
0 . 4+0 . 4
0.00+.0.00
Note: C - control ponds, LSD - low stock density, HSD - high stock density ponds.
gradually approached the levels observed in the lake(Figure 13). The major species in both the ponds and lakewere Spirulina laxissima, Lyngbya contorta, L_. liminetica,L_. lagerheimii and Microcystis incerta. These species werealso reported as the major BG species by Brezonik et al.(1978).
Green algae (GA). Mean total number of GA ranged from585 to 7,148 individuals/ml in the ponds, and 1,108individuals/ml in the lake (Table 10). No significantdifferences existed among the ponds or the lake (Table 5).
BB. Mean total number of BB ranged from 3 to 9individuals/ml in the ponds and 12 individuals/ml in LakeApopka. No significant differences existed between thecontrol ponds and the lake, whereas a difference was foundbetween the lake and the experimental ponds (Tables 5 and10). All values for the lake and ponds were similar exceptfor one sample date in December, 1989, when a very highlevel of BB was observed in the lake (Figure 14). Althoughthe numbers of BB are relatively low, it constitutes animportant component of the algal biomass (see Chlorophyllsection).
Total Algae (TA). The mean number of TA ranged from62 x 103 to 158 x 103 /I. In the lake this value was 275 x103/1., which was significantly higher than experimentalpond group values (Table 5 and 10). The seasonal TAdynamics is shown in Figure 15.
Blue-green/green algal group ratio. Differences inthe numerical proportion of blue-green/green algae werefound between the experimental pond groups and the controlponds. This proportion was lower in HSD ponds and alsolower in LSD ponds than in the unstocked control ponds(Table 11). However, the differences in algal group ratioscan not be explained by the mean differences in algal groupabundance. Differences in numerical occurrence were notfound in blue-green and green algae when the control andexperimental pond groups were compared (Table 5).
37
600000 -i
ocUJ
111o
500000 •
400000 -
300000 -
200000 -
100000
Q LAKE APOPKA
EXPERIMENTAL PONDS
SEP MOV JAN MAR MAY JUL
1989 1990
MONTH
Figure 13. Seasonal bluegreen algae numbers for the experimental
pond group and Lake Apopka (the arrow - See Figure 5) .
38
160
cc111
tn_iUJo
120-
LAKE APOPKA
EXPERIMENTAL PONDS
SEP NOV JAN MAR MAY JUL
1989 1990
MONTH
Figure 14. Seasonal Botryococcus Braunii numbers for the
experimental pond group and Lake Apopka (the arrow - See Figure 5) .
39
600000 n
ccUJ
to
111u
500000 -
400000 •
300000 -
200000 -
100000
LAKE APOPKA
EXPERIMENTAL PONDS
SEP NCV JAN MAR MAY JUL
1989 1990
MONTH
Figure 15. Seasonal total algae numbers for the experimental pond
group and Lake Apopka.40
Table 11. The ratio of blue-green/green algae from the lake and ponds
Date
ControlPond 2Pond 5
LSDPondPond
HSDPondPond
Lake
36
14
02-27-90
663092
1621
26720
521
03-27-90
262536
3451726
4917
80
04-25-90
3932433274
50038
3628
139
05-30-90
2216
164226
12138
211
06-27-90
18015273
797157
25523
551
07-25-90
17343318
15755
9010
609
08-22-90
0.429577
59
17154
30922
Mean
10164
301
84
4719
Note: LSD - low stocking density ponds, HSD - high stocking density ponds.The differences between C-LSD and C-HSD are significant (t-Student's test, P<0.05)
ZooplanktonThe zooplankton community in both the ponds and lake
was dominanated by rotifers and copepods (nauplii,copepodids and adults). Cladocerans were poorlyrepresented. The major rotifer species were (body size injim and S.D. are given in parenthesis) : Keratellacochlearis (184 + 17), Brachionus havanaensis (24S.+35) , B_.quadridentata (305+41), B. caudatus (191̂ 45), B.calvciflorus (274̂ 38), Filinia lonqiseta (124+19) ,Monostvla sp (119+13), Hexarthra sp. (150±23) andTrichocerca lonqiseta (200+29) _ Diaptomus dorsalis (<f1130-1200, ? 1130-1375, mean 1188+117) was the mostnumerous copepod representative. The cladoceran assemblagewas dominated by two small species, Bosmina sp. (364 +_ 87)and Chydorus sphaericus (250 + 41) . The larger cladoceranspecies, Daphnia ambiqua (772̂ 105), was found insignificant numbers only in the samples on January 26,1990. Because larger cladoceran species were not presentin most of the samples, and adult copepods were found onlyin token numbers (Table 12), the zooplankton assemblageconsisted of the same small species, both in the treatmentpond group and in the lake.
The total number of zooplankton (TZ) was highest inLake Apopka. Significant differences existed between theexperimental pond group and the lake (Table 5). Theseasonal dynamics of rotifers, copepods, and TZ numbers isshown in Figure 16, 17 and 18.
Fish Food Habits
The materials eaten by bighead carp were divided intothree general categories, zooplankton, phytoplankton/detritus (excluding BB), and BB.
Zooplankton. The amount of zooplankton in the ATconsisted of 1% of the total volume of food (Table 13).Zooplankton eaten by the fish consisted mainly of smallforms, primarily rotifers and young copepod stages.
42
Table 12. Mean values and standard deviation of the zooplankton data for the period02-27-90 to 08-22-90.
L S D H S D LakeParameter
Rotifers/1 231+258 111+66 165+32 67±28Nauplii & 159+108 117+159 82+50 21+10copepodi4s/l
Copepods/I 5+7 4+7 1+1 1+1Cladocera/1 207+426 98+200 45+47 51+64Other 0.0+0.0 0.3+0.7 0.3+0.7 0.4±1.1zooplankton/1
Total 603+539 330+362 294+104 141+79zooplankton/1
% Rotifers 45.1+30.1 50.9+24.0 61.7+19.0 54.4+22.1% Nauplii 32.2+19.2 31.5+14.0 25.4+9.5 16.0+3.1& Copepodid s
% Copepods 1.0+0.7 0.8+0.8 0.3+0.4 0.6+0.8% Chadocera 21.6+25.4 16.4+14.9 12.5+10.7 28.7±21.5% Other 0.0+0.0 0.4+1.0 0.0+0.00 0.2+0.6zooplankton
92±36123±137
4+5206±4210.3+0.7
424+531
282±232190+76
6±5236+5000.0+0.0
1096+1802197±165
23+30323+3560.0+0.0
714+511 1640+1683
46.4+27.4 46.8+25.8 46.7+37.732.5+12.7 31.7+12.5 16.9+16.0
1.0+1.7 0.9±0.3 2.5±3.819.6+27.0 20.6±26.6 33.8+30.90.4+1.0 0.0+0.0 0.0+0.0
Note: C - control ponds, LSD - low stock density and HSD - high stock densityponds.
6000
ccUJ
DCUJCO
4500-
3000-
1500-
EXPERIMENTAL PONDS
SEP NOV JAN MAR MAY JUL
1989 1990
MONTH
Figure 16. Seasonal rotifer number for the experimental pond
group and Lake Apopka.
44
LAKE APOPKA
EXPERIMENTAL PONDS
80
60-
ocujH3^ 40-
oc111CD
D
20-
1
SEP NOV
1989
JAN MAR
MONTH
MAY JUL
1990
Figure 17. Seasonal copepod numbers for the experimental pond
group and Lake Apopka.
45
DCUJ
CCUJCD
7500
6000 -
4500-
3000
1500-
EXPERIMENTAL PONDS
SEP NOV JAN MAR MAY JUL
1989 1990
MONTH
Figure 18. Seasonal total zooplankton numbers for the experimental
pond group and Lake Apopka.
46
Phytoplankton/ Detritus (P/D). The present volume ofP/D was 32 and 28% in the AT of small and large fish,respectively (Table 13). Algal species most often found inthe AT were the common BG species in the ponds.
BB. The percent volume of BB found in fish AT was 66and 70 in small and large fish, respectively. On a dryweight basis the volume of BB amounted to 50 and 60% in theAT of small and large fish, respectively. From these datait can be seen that the percentage of BB in the fish foodincreased slightly with the size of the fish (Table 14).
In addition to the percent volume of food consumed,the total number of each item eaten was also determined.The number of BB colonies eaten by small fish was 4.8 x103/g of fish body weight and 15.3 x 103/g of fish bodyweight in the larger fish (Table 15). This relationshipbetween fish size and consumption of BB is unusual because,as a general rule, larger fish consume less food/g of bodyweight than smaller ones (Webb 1978) .
Total Algal Consumption: Small fish ate an average of426 x 103 algal colonies/g of fish body weight whereas thisnumber was 712 x 103 for larger fish. The samerelationship as pertained to fish size existed for thetotal amount of algae consumed (Table 15).
Blue-green/qreen algal group ratio. The proportion ofblue-green/green algae in the fish food was 24 and 29 inLSD and BSD ponds, whereas the same proportion in the pondwater was 301 and 84, respectively (Table 11 and 16). Thealgal group proportion in fish food was significantly lowerthan in the ponds (t-test, P=0.05).
Food Selectivity: BB and zooplankton were highlypreferred by bighead carp. This was confirmed by Ivlev'sselectivity index. In all samples the index for both wasclose to +1 (x = +0.99) in small and large fish (Table 15).Zooplankton biomass was low in the ponds and made up only asmall portion of the fish food. Selectivity for otheralgae was variable.
47
Table 13. Characteristics of bighead carp food, percentage of zooplankton and phytoplankton & detritus(by volume).
Date
02-28-9002-28-9002-28-9004-26-9004-26-9005-31-9005-31-9006-28-9006-28-9006-28-9006-28-9007-26-9007-26-9007-26-9007-26-90
Mean ± SD
Note : s
Pond No .
146141413461346
- small fish,
s
1010
1
511
0
1 -
Zooplanktonm
151124
1
1
1+1.5
large fish, m
Phytoplankton &1
201112
103
1
- fish
s
43432310
21
274139
46
1̂ 1
not divided
m
888
27
45
53
32+12 . 6
detritus1
3338178
30
223243
30
28+11
into either small or large fish.
oo
Table 14. Characteristics of bighead carp food, percentage of Botryococcus Braunii(by volume and by dry weight).
Date
02-28-9002-28-9002-28-9004-26-9004-26-9005-31-9005-31-9006-28-9006-28-9006-28-9006-28-9007-26-9007-26-9007-26-9007-26-90
Mean +. SD
Pond No.
146141413461346
% of B. Braunii(volume)
s m
778168
56577690
7278
54685860
4654
66̂ 12.5
% of B. Braunii(dry weight)
1
65628191
68
776854
69
70 +.11
s
57434642
65
405954
47
50±8.7
m
878775
68
36
11
1
64537876
76
366755
37
60+16
Note: s - small fish, 1 - large fish, m - fish not divided into size groups.
Table 15. Characteristics of bighead carp food, number of algae (xlO3 g fish body weightand selectivity for B_. Braunii.
Date Pond No.
2-28-902-28-902-28-904-26-904-26-905-31-905-31-906-28-906-28-906-28-906-28-907-26-907-26-907-26-907-26-90
Mean +_ SE
146141413461346
B. Braunii
s m
18.418.55.6
7.68.53.01.8
15.10.6
5.27.2
4 . 8 ±3 . 4
1
15.49.4
33.123.5
4.3
6.3
15.3+11.5
Other
s m
14118017
58430913977
66329
16071386
421+.514
1
5054131050681
221
1311
697+_411
Ivlev' s
s m
+ 1.+ 1.+ 1.
+1.00+0.99+1.00+0.98
+1.00+ 0,
+0.99
+0.99
index
1
.00
.00
.00+1.00+0.99+1.00+0.99
+1.00.97
+0.99
+0.99
Note: s = small fish, 1 = large fish, m = fish not divided into size groups
Table 16. The ratio of blue-green algae in the fish food.
Date
LSDPondPond
HSDPondPond
36
14
02-38-90
0.6
47
04-26-90
447
05-31-90
2014
06-28-90
1950
4323
07-26-90
4013
3436
08-23-90
1726
88
Mean
24
29
Index of Filling: Only a few fish in all samples werefound to have empty AT. However, AT were not uniformlyfilled with food. Usually, the first part of AT containedthe smallest amount of food or was empty, whereas the lastpart contained the largest amount (Table 17). The index offilling averaged 2.8 and 3.8 in HSD and 2.3 and 3.2 in LSD(Table 18). This index was calculated on a food wet weightbasis in order to make our data comparable with theliterature. Determination of wet weight can not be done asaccurate as determination of dry weight. However, the highcorrelation between wet and dry food weight determinationsobtained in our study indicates high accuracy of themeasurements (Figure 19) .
Fish Growth: From the data collected it is difficultto describe growth of the fish (Table 19). It was noticedimmediately that two sizes of fish existed, which added tosample variation. This variance could have been reduced iflarger samples were taken, but during the experiment, wedetermined that fish survival and fish food habits were ofmost importance. Seining during the summer when watertemperatures were warm caused mortalities; therefore, wedecided not to collect large samples for length and weightmeasurements. The larger samples of fish were collectedbetween 12-21-90 and 01-02-91. Weight class distributionof the sample of 100 fish from each pond is shown in Figure20. This distribution is clearly a negative bionomial asthe variance values (between 3261 and 6736) are many timesgreater than the mean weight of fish. There is not a
52
Table 17. Fullness of the three sections of bighead carp alimentary tracts.
Date
02-28-9004-26-9005-31-9006-28-9007-26-9008-23-90
Pond 1I II III
1.20.80.40.11.90.9
2.41.80.90.51.91.4
3.02.61.51.42.72.5
Pond 3I II
0.30.00.0
0.60.60.4
III
2.12.11.9
Pond 4I II
1.00.90.20.51.2
1.91.90.51.01.4
III
2.72.61.61.51.2
Pond 6I II
0.0
0.10.20.0
0.5
0.51.61.3
III
1.0
2.02.82.4
Note: 0 = no food, 1 = little, 2 = medium, 3 = much, and 4 = very much food.I, II, III - first, second, and third section of the alimentary tract.
Table 18. Quantity of food in intestinal tracts.
Date
2/28/902/28/902/28/904/26/904/26/905/31/905/31/906/28/906/28/906/28/906/28/907/26/907/26/907/26/907/26/908/23/908/23/908/23/90
Pond
146141413461346136
Numberof fish
10102
10'10101010104
101010510101010
Meanfishtotallength
114.094.6
120.0136.4147.8148.7150.0147.7181.4115.5196.1181.0206.5103.6224.3185.8214.1231.3
Meanfishweightg
14.58.118.828.735.934.346.124.257.212.174.671.785.39.1123.372.295.1124.7
Wetweightfood
g0.7580.3920.3900.8910.9721.1641.8320.5451.3900.2981.6794.1002.2270.2105.4183.1223.0026.727
Mean Dryweightfoodg
0.1370.0700.0390.1060.1220.5251.0930.0490.381-
0.2020.4380.281-
0.574--**"
Wt. of food17
as % ofBody wt .
5.04.91.53.02.41.91.82.01.92.42.15.92.42.34.15.32.73.7
I/ index of filling
3-1
2-
oo
>.Q
1 -
DW = 0.01 + 0.11WW (r = 0.93)
Wet food (g)
Figure 19. Relationship between dry (DW) and wet weight (WW) of
bighead carp food.55
Table 19. Mean weight of fish collected each date and used forfood analysis.
Date
02-28-9004-26-9005-31-9006-28-9007-26-9008-23-9006-28-9007-26-9008-23-9002-28-9004-26-9005-31-9006-28-9007-26-9002-28-9006-28-9007-26-9008-23-90
Pond
111111333444446666
Mean weight (G)andrange
1429342472725785958
3646129
1875123125
( 8- 20)( 9-105)( 7-113)(14- 37)(22-148)(21-211)(15-106)(46-134)(62-177)( 7- 8)( 9-100)( 7-237)(10- 13)( 8- 10)(10-r 26)
(43-124)(37-358)(43-313)
Mean weight (g)S L
1314
48273571
2110
545774
9382
12614079118
97130
122189200
S = small fish, L = large fish
30 -i
20-
10-
POND 6N = 100MEAN=85.7gSE=6.3
30 H
u.O
UM
BE
R
z
20
10
0
30
POND 4N = 100MEAN=83.8gSE=8.2
POND 3N = 100MEAN=85.7gSE=5.8
POND 1N = 100MEAN=76.9gSE=6.9
20 40 60 80 100 120 140 160 180 2 0 0 > 2 0 0
WEIGHT CLASS (GRAMS)
Figure 20. Weight-class distribution of bighead carp from the
ponds (12-21-90 to 01-02-91).
57
definitive answer for these growth differences, but itmight be related to the triploid production technique.
Fish survival and biomass: Fish survival and finalbiomass was determined between 12-21-90 and 01-02-91 usingmark-and-recapture procedures (Ricker 1975). Because ofslow fish growth and high mortality, especially in HSDponds, the final biomass of fish was low (Table 20). Fishproduction in the HSD ponds was lower than the initialstocked biomass of fish.
58
Table 20. Fish survival rate and biomass estimated by mark - recapture procedures(12-21-90 - 01-02-91).
Pond no.
3614
(LSD)(LSD)(HSD)(HSD)
Fish weight (g)Mean _+ S.E.
85.7+5.885.7+6.376.9+6.983.8+8.2
Fish survival (%)and 95% C.I.
44(33-62)39(33-47)10(8-12)6(5-7)
Fish biomassand 95% C.I.
80(59-111)71(60-85)97(81-116)60 (50-74)
(kg/ha)
Note: LSD - low stock density ponds, HSD - high stock density ponds.1) Ricker's (1975) method was used to calculate 95% confidence interval (C.I.)
DISCUSSION
Water temperature during the study period followedtypical seasonal trends for Lake Apopka as described byBrezonik et al. (1978), and for other Central Florida Lakes(Shireman et al. 1979, 1983) . Minimum temperatures werefound in December and January. Maximum temperaturesoccurred in August, 1989 and 1990. The lake and ponds hadsimilar seasonal changes in water temperature. Dissolvedoxygen concentrations were high in the ponds and lake andremained favorable for fish life throughout the study.
Water clarity as measured by Secchi disk was extremelypoor in Lake Apopka during our studies. This has been along lasting and stable phenomenon in the lake. SimilarSecchi disk readings were reported in 1977 by Brezonik etal. (1978) . Water clarity in all experimental ponds wasgreater than in the lake, indicating less suspendedmaterials or algae in the ponds.
An important issue of this study is whether thecontrol pond group was comparable to Lake Apopka. If thepond group does not compare with the lake, the results ofthe bighead carp experiments in the ponds may not beapplicable to Lake Apopka. There were significantdifferences between the lake and the control ponds in somewater quality parameters, such as Secchi disk visibility,pH, total nitrogen, total phosphorus, and chlorophyll a..No differences in plankton abundance were found between thelake and the control ponds in blue-green algae, B.B., totalalgal number, rotifers, copepods, and total zooplanktonnumber.
The ponds stocked with bighead carp occupy anintermediate position between Lake Apopka and the controlpond group in all plankton abundance parameters. Theseparameter values are not different between the control andbighead carp stocked ponds, but there are significantdifferences between the bighead carp ponds and the lake.It suggests that bighead carp exerted some effect on thepond ecosystem, but the effect was not large enough tocause significant differences between the stocked andunstocked ponds.
Despite the differences in algal abundance between thelake and the ponds, the structure of the algal communityremained the same in the compared water bodies. This
60
structure was characterized by extreme dominance of blue-green algae (> 90 percent), a reduced number of total algalspecies, and a clear dominance of several algal species(approximately 10 species), which remained relativelyconstant during the study period.
Clear differences in zooplankton assemblages were notfound among the lake and the ponds. A zooplankton peakoccurred shortly after filling the ponds, but for the mostpart zooplankton numbers averaged between 300 and 600/1,'which is close to the zooplankton numbers found in LakeApopka in 1977 and 1978 (Brezonik et al. 1978).Zooplankton abundance in Lake Apopka averaged about 1600/1,which is almost three times as high as reported by Brezoniket al. (1978). Zooplankton species composition found inour study was similar to that reported earlier. Dominanceof small cladocerans, (Bosmina sp., Chydorus sphaericus),and small-bodied rotifer species is indicative of eutrophicconditions (Edmondson 1985) .
Lower concentrations of nutrients were found in theexperimental ponds probably because of the low inflow ofnutrient-rich lake water into the ponds and/or was possiblydue to lack of resuspension of nutrients from the pondsediments. Brezonik et al. (1978) stated that internalloading from the sediments contributed to higher nutrientconcentrations in the lake water. The mean inflow rateaveraged between 0.53 and 0.55 I/sec, which would beindicative of a total water volume exchange in the pondsabout every 43 days.
Fish food samples included in this report werecollected between February and August, 1990. Theyrepresent fish feeding habits from the coolest and warmestparts of the season. No distinctive seasonal change infood composition was found. Although zooplankton werehighly preferred they were not an important constituent inthe fish diet. The zooplankton share in fish food averaged1%, except for the February, 1990, sample when it rangedfrom 15 to 24% in the individual ponds. The minorimportance of zooplankton in bighead diets may have beendue to the low zooplankton density in the ponds. When thedensity of zooplankton was highest, as in February 1990,the share of zooplankton in the diet increased. Thisfinding is in agreement with literature data. All theauthors dealing with food habits of bighead carp concludedthat this fish feeds mainly on zooplankton (Bobrova 1966,Voropaev 1968, Danchenko 1971, Cremer and Smitherman 1980,
61
Opuszynski 1981, Spataru et al. 1983). However, the sameauthors stated that the amount of zooplankton in the fishdiet depends on the zooplankton density. When zooplanktondensity decreased, bighead carp fed on phytoplankton anddetritus. These two components constituted the bulk ofbighead carp food in our study. BB was especiallyimportant among the algal species eaten by the fish. Theshare in the diet was 66 to 70% of volume and 50 to 60% ofthe dry weight (Table 14), even though the numericalpercentage of this species in the total number of algae wassmaller than 1% (Table 10). High selectivity of BB was dueto its large size. For example, the average size of acolony measured in pond 4 on April 25, 1990 was 112 (im,ranging from 55 to 220 [im. The space between the gillrakers of bighead carp ranges from 20 - 80 |im (Voropaev1968, Spataru et al. 1983); therefore, most of the BBcolonies were probably retained by the filtering apparatus.Small algae apparently pass through the gill rakers.
If the index of filling is known, the daily foodration of bighead carp can be calculated. The daily foodration or, in other words, the daily food consumption (D)is given by the formula: D=A(24/n), where A is the averageamount of food in the intestines, and n is the foodevacuation rate, i.e. the number of hours necessary forcomplete intestinal evacuation. Assuming the evacuationrate equaled 10 hours (Opuszynski and Shireman in press),the mean daily food ration of bighead carp ranged from 5.5%of fish body weight in pond 3 to 9.1% in pond 4. Thesevalues are higher than those (2% to 5.7%) reported byOpuszynski and Shireman (in press) for bighead carp kept incages. No other literature values for bighead carp foodrations were found. Daily food ration data are available,however, for silver carp, a species closely related tobighead carp. Savina (1965) found that daily food rationsof silver carp were 0.02 - 1.1% of fish body weight.Omarov (1970) and Moskul (1977) reported significantlyhigher values of 17.2 and 20.9%, respectively. Bialokozand Krzywosz (1981) studied the seasonal feeding habits ofsilver carp in a Polish lake where daily rations rangedfrom 5.7 to 11.7% during summer months and dropped to 0.007to 0.076% in the winter. If the winter data from Bialokozand Krzywosz (1981) are excluded, their results are veryclose to the results reported in our studies. Gerking(1984) estimated a maintenance ration of 5.6 to 5.9% foranother herbivorous fish, Sarpa salpa, fed on a green algaeunder laboratory conditions.
62
In order to determine the stocking rate of bigheadcarp needed to consume BB in Lake Apopka, the quantity ofBB in both the lake water at the intake site and AT of thecarp was determined. The food evacuation rate determinedby Opuszynski and Shireman (in press) was used in thecalculations. We calculated that a fish biomass of 750kg/ha would consume 13% of the BB standing crop/day (Table21). Therefore, a fish stocking rate of 750 kg/ha wouldconsume the total standing crop of KB in Lake Apopka in 8days (Table 21). These stocking rates are probablyinflated because the calculations were based on theconsumption of small fish. The fish in our study were notlarge enough to have reached their maximum efficiency.
The consumption rate calculated for BB for bigheadcarp is probably underestimated, because the consumptionrates were calculated according to the diets of pond fish.The quantity of BB in the ponds was 3-6 times lower than inthe lake (Table 10). Bearing in mind that the consumptionrate of filter-feeding fish is algae-density-dependent(Drenner et al. 1984), the consumption of BB, by bigheads,if stocked in Lake Apopka, may be more than twofold greaterthan our calculated values. The influence of bighead carpgrazing on BB populations, however, is difficult to predictaccurately, because the P/B ratio (production to biomass)of BB is unknown. The P/B value (turnover rate) of anorganism, or group of organisms, is the ratio of productionto biomass. When calculated on a growing season basis itserves as a general index of the rate of organic substancesynthesized relative to standing stock (biomass). Smallerorganisms are expected to have greater P/B values. Thisratio averages 113 for phytoplankton, but ranges broadlyfrom 8.9 to 359 (LeCren and Lowe-McConnell, 1980). If theP/B ratio of BB is low, which is probable considering thelarge size of this alga, the influence of bighead grazingwould be greater. Even though bighead carp prefer BB, ourstudy did not show a significant effect of the fish on thepopulation of this algae in the experimental ponds. Theprobable reason seems to be the small biomass of fish.This biomass (60-97 kg/ha) is still considerably below thatwhich may be needed to significantly decrease BB in LakeApopka. Higher fish biomass was not achieved because ofthe short experimental period and slow growth and highmortality of the stocked fish. Pond stocking began onJanuary 4, 1990, and was continued until June 20, 1990.Data were collected until August, 1990. Estimation of fishsurvival rate and biomass was made between December 21,1990 and January 2, 1991.
63
Table 21. Hypothetical Botryococcus consumption per hectare-meter by different stockdensities of bighead carp for Lake Apopka.
Bighead carpStock density
(kg/ha)
No. of Botryococcuseaten per day
(colonies x 105)
% of Botryococcusstanding cropeaten per day
No. of days neededfor standing crop
consumption
11002505007501000
52752,700131,750263,500395,250527,000
0.0171.748
1317
588259231286
No. of Botrvococcus/ml in Lake Apopka = 31 (see Table 6)No. of Botryococcus/q fish body weight = 18,500 (see Table 10, February, 1990)Bighead carp food evacuation rate = 8.4 h (Opuszynski and Shireman, in press)
The reasons for the slow fish growth and highmortality are not clear and need further investigation.The fish population was differentiated soon after stockinginto two groups of fish. The growth rate of the firstgroup was apparently retarded, whereas the second group offish grew reasonably well (Figure 16). The differentialgrowth rates might have been caused by the sterilizationtechnique. The triploid production technique involvesexposing fish eggs to high water pressure, about 8000Ibs/square inch (Aldridge et al. 1990). This technique hasbeen used for several years to produce sterile triploids ofthe Asiatic grass carp. It is well known that grass carptriploids grow slower and more abnormally developedindividuals can be found among them in comparison to normaldiploid fish. The production of triploid bighead carp is arelatively new procedure developed at our laboratory.Thus, the fish are not generally available from commercialsources. To date not enough experience has been gained toevaluate the influence of the sterilization technique onthe quality of the fish. Furthermore, it is difficult tosay whether this pattern of growth is typical for triploidbighead carp or if it was specifically due to the batch offish used in this experiment.
Due to low fish biomass, the question as to whetherthe bighead carp would be able to change the structure ofthe phytoplankton community in Lake Apopka was not fullyanswered. The data collected, however, clearlysubstantiate that bighead carp fed selectively on BB, andthat this algae constituted the bulk of the fish food.Moreover, despite low fish biomass, some changes in thephytoplankton community structure were evident, asindicated by the lower ratio of blue-green/green algae inthe bighead stocked ponds. Therefore, we continue tohypothesize that bighead carp could have exerted morepronounced changes in phytoplankton community structurewith a larger fish biomass. This can be confirmed byexperiments with other filter-feeding fish (Drenner andTaylor 1984, Drenner et al. 1984). These fish were able tosuppress populations of large-sized algae, providing thealgal species were large enough to be effectively ingestedby the fish.
Although bighead carp do consume large algae and wouldprobably change the algal community to smaller forms,additional fish species should be used to improve waterquality. For example, Henderson (1978, 1979) reported thatgrazing of plankton by silver and bighead carp reduced
65
ammonia nitrogen levels by 27% and phosphate levels by2.72% in Arkansas oxidation ponds. Organic loads (BOD5)were reduced by 96% and total suspended solids by 78%(Henderson 1983) . These ponds contained 2,280 pounds ofsilver carp/acre and 156 ponds of bighead carp/acre.Leventer (1972, 1979) studied the effects of introducing anumber of different species (polymanipulation) to reducealgae and nutrients. This was done in a large waterreservoir in Israel. Generally, algae and nutrients werereduced by approximately 25%. These studies indicate thatthe polymanipulation method has definite potential.Preliminary results from this study confirm that bigheadcarp consume large algae, but in order to fully investigatethe technique additional time and fish species are neededin the experiments.
66
CONCLUSIONS
1. The experimental ponds adjacent to Lake Apopka weregenerally less eutrophic than the Lake, possiblybecause of low inflow rates of the nutrient-rich lakewater into the ponds and less bottom mixing by thewind.
2. The dynamics of physical/chemical parameters andstructure of plankton communities in the ponds weresimilar to those in the Lake, which made the ponds asuitable experimental site for the Lake Apopkaichthyofauna reconstruction project.
3. Bighead carp had no statistically significanteffects on any of the water quality parameters tested.
4. Botryococcus Braunii, in spite of a low numericaloccurrence, was an important component of the algalbiomass. This alga, because of its large size, is notconsumed by zooplankton.
5. BB_ was selectively eaten by bighead carp.
6. Bighead carp did not cause a reduction in BB number,but they changed the ratio of blue-green to greenalgae in the experimental ponds.
7. No significant changes resulted from the use ofbighead carp at the densities achieved in this study.However, because the biomass and size of fish wereless than desired, the hypotheses were not fullytested at the 750 kg/ha biomass level.
67
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