National Wetlands Research Center 

Bioindicators from Mosquitofish (Gambusia 

affinis) Sampled from the Imperial Valley in

Southern California 

By Jill A. Jenkins and Rassa O. Draugelis-Dale 

Open-File Report 2006-1307 

U.S. Department of the Interior 

U.S. Geological Survey 
U.S. Department of the Interior 

DIRK KEMPTHORNE, Secretary 

U.S. Geological Survey 

Mark D. Myers, Director 

U.S. Geological Survey, Reston, Virginia 2006 

For more information on the USGS—the Federal source for science about the Earth, its natural 

and living resources, natural hazards, and the environment: World Wide Web: 

http://www.usgs.gov 

Telephone: 1-888-ASK-USGS 

Outside front cover photograph: Imperial Valley, California, showing sampling sites. Figure contributed 

by the Environmental Contaminants Division, USFWS, Carlsbad, California. 

Suggested citation: 

Jenkins, J.A., Draugelis-Dale, R., 2006, Bioindicators from mosquitofish (Gambusia affinis) sampled from 

the Imperial Valley in southern California: U.S. Geological Survey Open-File Report 2006-1307, 

48 p. 

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement 

by the U.S. Government. 

Although this report is in the public domain, permission must be secured from the individual copyright 

owners to reproduce any copyrighted material contained within this report. 

ii
Contents 

Background Information ...................................................................................................................................................1

Materials and Methods .....................................................................................................................................................3

Collections..............................................................................................................................................................3 

Preliminary Experiments at NWRC ....................................................................................................................4

Morphological Measures....................................................................................................................................6

Sperm Counts ........................................................................................................................................................8

Sperm Motility .......................................................................................................................................................9

Sperm Cell Viability and Mitochondrial Function..........................................................................................10

Sperm Maturity....................................................................................................................................................11 

Contaminants Analyses .....................................................................................................................................12 

Whole Body Collections and Tissue Analyses ................................................................................12 

Bed Sediments.......................................................................................................................................12 

Polar Organic Chemical Integrated Samplers .................................................................................12 

Methodologies and Results ............................................................................................................................................13

Comparison of Microscopy and Flow Cytometry Methods for Counting Cells........................................13

Comparison of 2003 Sperm Counts per Site by Using Flow Cytometry .....................................................14

Comparison of 2003 Sperm Mitochondrial Function and Sperm Viability per Site .................................15 

Comparison of Sperm Maturity per Site .........................................................................................................20 

Comparison of GSI, HSI, and Motility per Site ..............................................................................................21 

Comparison of Gonopodia per Site..................................................................................................................25 

Creation of GI Index (Gonopodia Length/Total Body Length) .....................................................................27 

Contaminants Analyses .....................................................................................................................................30 

Discussion..........................................................................................................................................................................32 

Acknowledgments............................................................................................................................................................37 

References Cited ..............................................................................................................................................................37 

Figures

1. Standard curve demonstrating verification of a flow cytometric membrane integrity 

(viability) assay for use with mosquitofish (Gambusia affinis) ............................................................................5 

2. Standard curve demonstrating verification of flow cytometric particle counting 

methodology developed for use with sperm from mosquitofish (Gambusia affinis) .......................................6 

3. Gonopodium on male mosquitofish (Gambusia affinis).........................................................................................7 

4. Dissected testis of mosquitofish (Gambusia affinis)..............................................................................................7 

5. Flow cytometric dot plot illustrating the unknown sperm cell concentration compared 

with a known number of microspheres ...................................................................................................................9 

6. Mosquitofish (Gambusia affinis) sperm magnified 600 X using phase microscopy.......................................10 

7. Edge of a sperm packet where sperm are closely aligned ................................................................................10 

8. Average sperm counts per mg testes from Thousand Palms by using two methods....................................14 

9. Average sperm counts (raw data) per mg testes.................................................................................................14 

10. Adjusted means of sperm mitochondrial function ...............................................................................................18 

11. Adjusted means of viability of sperm .....................................................................................................................19 

iii
12. Flow cytometric histogram with DNA fluorescence intensity on the x-axis ...................................................20 

13. Average proportions of immature mosquitofish (Gambusia affinis) sperm per site ......................................21 

14. Average, nontransformed gonadosomatic index per site ..................................................................................23 

15. Average hepatosomatic indices at recategorized sites......................................................................................24 

16. Mean male mosquitofish (Gambusia affinis) body weights sampled in 2001, 2003, and 

2004...............................................................................................................................................................................25 

17. Average adjusted mean gonopodia lengths from 2001 .......................................................................................26 

18. Average adjusted mean gonopodia lengths from 2003 .......................................................................................26 

19. Average gonopodia indices per site in 2001..........................................................................................................28 

20. Average gonopodia indices per site in 2003..........................................................................................................28 

21. Average gonopodia indices per site pooled for 2001 and 2003..........................................................................29 

22. Organic contaminants sequestered by POCIS in 2003 ........................................................................................31 

Tables 

1. Water Quality Data 2003 .............................................................................................................................................13 

2. Correlations of transformed mitochondrial function values with covariates....................................................16 

3. Correlations of transformed viable sperm values with covariates ....................................................................16 

4. ANCOVA (Arcsin[sqrt]) results using mitochondrial function adjusted means ................................................17 

5. ANCOVA (Arcsin[sqrt]) results using viability adjusted means ...........................................................................19 

6. Average values of morphological characteristics .................................................................................................22 

7. Discriminant analysis results showing rates of misclassification using GI ......................................................29 

 

iv
Background Information 

The Sonny Bono Salton Sea National Wildlife Refuge (SSNWR) is located 64 

km north of the Mexican border at the southern end of the Salton Sea in California’s 

Imperial Valley. Freshwater ponds and managed habitats at the SSNWR, Calipatria, 

Calif. are supplied with Colorado River water that carries compounds from upstream 

sources. Components include municipal and industrial discharges, agricultural drainage, 

and sewage plant inputs. Aquatic animals in these ecosystems are continuously exposed 

to multiple constituents, several of which have been demonstrated to be associated with 

hormonal disturbances (Carey and Bryant, 1995; Gross and others, 2003). To 

investigate possible endocrine impacts to fish in the Imperial Valley, Calif. these 

experiments addressed the null hypothesis that aquatic species in impacted sites did not 

exhibit evidence of endocrine disruption as compared with those from nonimpacted sites. 

The results presented are intended to provide managers with science-based 

information and interpretations about the condition of the animals in their ecosystems for 

the minimization of potential adverse effects to trust fish and wildlife resources and for 

the maximization of available water resources. These data address IAG FWS#11430-

10HO32 in the USFWS proposal entitled “CA – Effects of Endocrine Disruptors on 

Aquatic Species Using Pond Habitats at the Sonny Bono Salton Sea National Wildlife 

Refuge.” 

Many human-made chemicals can disrupt endocrine systems of wildlife (Colborn 

and Clement, 1992) and can affect tissues at concentrations well below detectable levels. 

Hence, for investigating causal effects, the use of biomarkers for assessing contaminant 

exposure is necessary (Carey and Bryant, 1995). Bioindicator data are measurable and 

directly reflect the condition of the animal. Two important features of bioindicators are 

the ability to detect interactions between stressors and organisms and the capability of 

quantifying sublethal effects. Obtaining data from more than one biomarker can furnish 

a more precise assessment of the physiologic effect and bioavailability. Xenobiotic 

pollutants may disrupt reproductive endocrine function by acting at the level of several 

organs, such as the hypothalamus, gonad, and liver. Disruption at any of these organs 

may result in either changes in the rate of gonadal development or in the viability of the 

gametes, as well as the arrest of gametogenesis (Kime and Nash, 1999) or altered 

1
organosomatic indices. Most endocrine disrupting studies have focused on reproductive 

impacts; however, other effects have been documented, including those on growth, 

metabolism, thyroid, and immune function (Gross and others, 2003). 

A large part of this report highlights studies on sperm cells from mosquitofish 

(Gambusia affinis) from Imperial Valley sites. A sperm cell consists of several 

membrane compartments, and cell competency requires that each of these membrane 

compartments be intact (Graham and others, 1990). The combination of multiple assays 

on sperm is a better predictor of male fertility than any individual test. The classic 

method of assessing the viability of sperm is to determine the percentage of progressively 

motile cells by using a microscope (Jenkins, 2000). This is an indirect method of 

assessing metabolic activity, and results reflect inherent variability because of the 

subjective nature of collecting data on motility by individual researchers using 

microscopy. In this study, sperm membrane integrity was assessed by cell viability 

staining, where nucleic acids inside intact membranes were stained fluorescent green by 

the stain SYBR-14, whereas nonintact or permeable membranes allowed a red 

counterstain (propidium iodide) to enter the cells so that “dead” or moribund cells stained 

fluorescent red. Upon cell death, propidium iodide (PI) rapidly overwhelmed the 

fluorescence exhibited by SYBR-14. Both the sperm viability assay and mitochondrial 

function assay assessed the functional capacity of sperm in an objective manner. This 

fluorometric staining combination of SYBR-14 and PI has been shown to be a rapid and 

reliable means for determining the proportions of living and dead sperm in several 

species across taxonomic lines (Ericsson and others, 1990; McNiven and others, 1992; 

Garner and Johnson, 1995; Donoghue and Donoghue, 1997; Thomas and others, 1998; 

Segovia and others, 2000; Adams and others, 2003; Salinas-Flores and others, 2005; 

Lezcano and others, 2004). In this study, flow cytometry technology was used for sperm 

viability and mitochondrial function as well as for sperm counts per mg testis and testis 

cell meiotic stage of maturation. 

The field of flow cytometry had practical research and clinical applications for 

immunotoxicology (Hudson and others, 1985), for testing in vitro toxicity of chemicals 

(Tuschl and Schwab, 2004), and for male human infertility diagnostics. It is increasingly 

being used in sperm cryopreservation studies. This is multiparameter analytical 

instrumentation for assessing nuclear and cellular components of interest in freely 

2
flowing cells. Individual cells or nuclei of any tissue from any species can be probed by 

a laser light, and emitted light signals are transferred quickly into electronic measures so 

that typical sample sizes approximate 10K – 50K events and data are collected within ~1 

min per sample. This report is the first such comprehensive multiparameter study of 

potential sperm impacts in an environmental field study. This report documents the use 

of this technology for detection of potential cellular and molecular impacts on sperm 

from mosquitofish in ecosystems in the Imperial Valley. 

Just as the study of more than one biomarker per individual increases confidence 

in health assessments, in addition to reproductive endpoints, other measures of animal 

condition (such as hepatosomatic index – HSI) were included in this study. In these 

studies, we assessed the quality of sperm and morphological indices and analyzed 

hormone concentrations from multiple years. Morphological indices included 

gonopodium length, hepatosomatic indices, and gonadosomatic indices. Contaminants 

data obtained from fish and the sites were analyzed. Multiple researchers and other 

personnel contributed data and efforts in this study. 

Materials and Methods 

Collections 

Gambusia affinis were collected by personnel in California by using pulsed DC 

electroshocking, hoop nets, or seining. Blood samples were collected (Goodbred and 

others, 1997). Fish, blood, and soil samples were sent out for respective analyses, 

including live fish shipped overnight in July 2003 for analyses at the National Wetlands 

Research Center (NWRC). Samples were received at the NWRC from the following 

sites: “Hazard Pond 6” on July 15, 2003, “Trifolium Drain 19” on July 16, 2003, and 

Thousand Palms on July 17, 2003. Thousand Palms was a reference site where male 

mosquitofish were available. 

Overall, samples were obtained in 2001, 2003, and 2004. In 2001 (June 11-13), 

fish were collected for analyses from “Rock Hill Trail Pond,” Hazard Pond 6, “No Name 

Drain,” Trifolium 19 Drain, “Bruchard Drain,” and the reference site San Felipe Creek. 

No males were available from San Felipe Creek in 2001. In 2004, the five sites sampled 

3
were Prado Dam, “Rialto Dam,” “Rix,” “Sunny Slope,” and Thousand Palms. This 

report includes statistical analyses of data obtained over these three sampling years. 

Preliminary Experiments at NWRC 

Dissection methods, buffer choice, and sperm cell preparation methods were 

optimized. The duration of motility of sperm cells was sometimes over 26 min; hence, 

duration of motility as a metric was not feasible for use as a biomarker, and percentage 

motility as a metric did not prove to be a powerful metric for condition as substantiated 

by statistical analysis (see results below). Less subjective sperm motility analyses may 

be investigated by using computer assisted sperm motion analysis (CASA), as routinely 

applied with domestic mammalian sperm (Xu and others, 2001), and from which we 

have data using sperm from fathead minnows (Pimephales promelas) whereby 

progressive motility was significantly positively related to gonadosomatic index (GSI) 

(Jenkins, unpublished data). 

The sperm cell viability assay based on a membrane integrity principle, whereby 

membrane-intact cells are considered viable, was employed with Gambusia affinis

sperm. With individual fish (n=3) obtained locally in Louisiana, standard curves were 

generated by using known live and dead cell mixtures. Sperm at 1 x 106 per mL (3 mL 

in a 10 mL tube) were killed by heating in a waterbath at 80ΕC for 10 min. The assay 

was verified for identifying viable and nonviable cells of known live and dead mixtures 

(fig. 1) in triplicate. The R2

 values for each of the curves were 0.9911 (fig. 1), 0.9867, 

and 0.9951. The buffer used for analyses was Hank’s Balanced Salt Solution (HBSS) 

(Glenn, 1998) without Ca++ or Mg++ at pH 7.5 at 311 mosm/kg (HBSS). 

4
0.883

0.606

0.452

0.262

0.000

R2

 = 0.9911

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1 0.75 0.5 0.25 0

Proportion Viable Sperm (Expected)

Proportion Viable Sperm (Actual)

 

Figure 1. Standard curve demonstrating verification of a flow cytometric membrane 

integrity (viability) assay for use with mosquitofish (Gambusia affinis). Data were 

generated by using known proportions of live and heat-killed sperm from one fish. 

Representative data are presented from one fish. 

A flow cytometric assay for sperm counting was verified for use with dilutions of 

fresh sperm from Nile tilapia (Oreochromis niloticus), green swordtail (Xiphophorus 

helleri), and Gambusia affinis (fig. 2) with R2 values of 0.9364, 0.9941, and 0.9456, 

respectively. By using Gambusia affinis sperm from the July 17, 2003 collection, counts 

obtained by both microscopy and flow cytometry methods were compared statistically 

(see statistical results below). 

5
R2 = 0.9456

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

10 7.5 5 2.5

Relative Dilution

Gambusia Fresh Sperm Count per mL (x 10^6)

Figure 2. Standard curve demonstrating verification of flow cytometric particle counting 

methodology developed for use with sperm from mosquitofish (Gambusia affinis) 

generated by using known dilutions of fresh sperm. 

Morphological Measures 

Fish arrived by overnight mail, live fish were processed completely, and 

morphological measures were made by using intact but not yet decomposed dead fish. 

Live fish were euthanized with tricaine methane sulfonate (Nickum and others, 2004). 

Total fish length and gonopodia lengths (fig. 3) were measured with digital calipers, and 

fish were weighed. Gonopodia were severed and stored in buffered formalin at 4ΕC for 

potential future analysis of gonopodial rays and hooks as secondary sex characteristics 

(Toft and others, 2003). Fish were dissected with microtools by using a dissecting 

microscope, and liver and testis (fig. 4) were extracted and weighed. Condition and color 

of organs were noted. During the few minutes between organ handling and sperm cell 

processing, the testis was placed in a humidified chamber until it was cut in two pieces. 

One piece was weighed for sperm count analysis, and the other portion was used for 

assessing sperm motility, mitochondrial function, and viability. 

Biomarker data were collected on GSI and hepatosomatic index HSI. 

6
 

Figure 3. Gonopodium on male mosquitofish (Gambusia affinis). 

Figure 4. Dissected testis of mosquitofish (Gambusia affinis) overlaying the bottom half 

of scissors. 

7
Sperm Counts 

For sperm extraction prior to counting, the weighed testis half was placed in 100 

μl 0.175 mM salt concentration KCl (13.046 mg/L) (Toft and others, 2003). The tissue 

was minced for exactly 1 min, maintained in the KCl solution for 10 minu, 100 μl 

buffered formalin was added, and the tube stored at 4 °C until counting. After thorough 

resuspension of stored cell suspensions, sperm cells, partial sperm packets, and whole 

sperm packets were enumerated in triplicate with a hemocytometer and after trypan blue 

staining for ease of cell visualization by using microscopy, the following formulae were 

used: 

For sperm: 

Number sperm counted in 5 small squares X (4.0 x 106) X (dilution factor) 

 80 

 For packets: 

Number sperm counted in 4 large squares X 1000 X 160 X (dilution factor) 

 64 

By flow cytometry, sperm cells and cells from mashed testes were enumerated by 

using a Bacteria Counting Kit (Molecular Probes, Eugene, Oreg.), whereby florescent 

SYTO BC dye and a known concentration of polystyrene microspheres were included 

with 10 Φl sperm cell aliquots in 250 sheathe buffer (Becton Dickinson 

Immunocytometry System [BDIS], San Jose, Calif.) (fig. 5). Cell count results were 

expressed as both cells per mL of buffer and cells/mg testis. Both microscopy and flow 

cytometry counting methods were employed with samples received from Thousand 

Palms July 17, 2003, and statistical analyses were performed to compare counts by the 

methods (see Number 1, below in Results). 

8
Figure 5. Flow cytometric dot plot illustrating the experimental, unknown sperm cell 

concentration in Region 1 (R1) compared with a known number of microspheres in R2. 

Particle size is on the x-axis (forward scatter or FSC-H) parameter, and green 

fluorescence of stained sperm and microspheres is on the y-axis (fluorescence detector 

FL1-H). 

Sperm Motility 

The percentage of sperm showing forward movement was assessed by 

visualization with darkfield microscopy at 100X magnification. An aliquot of 0.25 Φl 

sperm was mixed with 25 Φl HBSS, and progressive movement in triplicate by three 

separate readers was estimated to the nearest 5%. Sperm morphology (figs. 6 and 7) and 

obvious parasites or bacteria, if present, were noted.

9
Figure 6. Mosquitofish (Gambusia affinis) sperm magnified 600 X by using phase 

microscopy. Individual sperm heads with tails are noted. 

Figure 7. Edge of a sperm packet, or spermatozeugmata, where sperm are closely 

aligned. 

10
Sperm Cell Viability and Mitochondrial Function 

Cell suspensions were filtered with 30 Φm nylon mesh (Small Parts, Miami 

Lakes, Fla.) prior to dilution to 1 x 106 /mL. Suspensions of cells at 250 Φl aliquots 

were stained by using a live/dead sperm viability kit (Molecular Probes, Eugene, Oreg.) 

with a starting stock solution of 1:100 SYBR-14 (Segovia and others, 2000). For 

mitochondrial membrane potential, dual fluorescent staining with Rhodamine 123(R123) 

(Sigma-Aldrich Chemical Company Co., St. Louis, Mo.) and PI was used according to 

Segovia and others (2000). The analytical instrumentation used to obtain data was a flow 

cytometer (FACScan, [BDIS]). For the verification of cell condition and probes 

employed, epifluorescence microscopy (Leitz Diaplan) was used in conjunction with 

flow cytometry. 

Sperm Maturity 

Stored cell suspensions were stained with PI, RNAse A at 1 μg/mL, and 0.1% 

(v/v) Triton X-100 for 30 min at 24°C. Stained cells were filtered through a 30 μm nylon 

mesh, and distributions of nuclei in different meiotic stages were analyzed with a flow 

cytometer (FACScan [BDIS]). Nuclei were analyzed at 1 x 106

 per mL at a rate of 300 

per second, and 5-10 K events were collected by using a 1024-channel FL2 parameter at 

340 linear, with linear size and scatter parameters, and doublet discrimination mode. 

Samples were run in triplicate. Histograms, dot plots, and density plots were generated 

by using CellQuest software (BDIS), with each sample analyzed in three ways: FSC-H 

versus side scatter (SSC), fluorescence detector 2 area (FL2A) histogram, and 

fluorescence detector 2 width (FL2W) versus FL2A in doublet discrimination mode 

(DDM). Nuclei were gated in DDM so to disregard aggregated nuclei in the analyses, 

and gated FL2A histograms were used to obtain event numbers under the peaks 

representative of different meiotic stages. 

11
Contaminants Analyses 

Whole Body Collections and Tissue Analyses 

The two replicate composites per site of male and female mosquitofish of random lengths and of 

a minimum weight of 15 g were analyzed for 28 chlorinated compounds having a Log octanol-water 

partition coefficient (KOW)>4 by using capillary-column gas chromatography (GC) and electron-capture 

detection (Leiker and others, 1996). The fish composites had been placed into chemically cleaned jars, 

frozen on dry ice in the field, and stored at -20oC until shipment to the USGS National Water Quality 

Laboratory (NWQL) in Denver, Col. Processing, analyses, quality assurance parameters, recoveries, 

and methods performance standards are detailed in Leiker and others (1996). 

Bed Sediments 

From 10 locations within each fish sampling site, bed sediments were collected by using a 

modified procedure (Shelton and Capel, 1994). A chemically cleaned teflon scoop was used to collect 

two replicate bed sediment samples from the first 2 to 3 cm of the bottom material and composited. The 

samples were thoroughly mixed in chemically cleaned glass jars, frozen on dry ice, and stored at -20 oC 

until ready for analyses at the NWQL. Chemical analyses for 31 organochlorine compounds and 

polychlorinated biphenyls (PCBs) were done by dual capillary-column GC with electron-capture 

detection (Foreman and others, 1995). 

Polar Organic Chemical Integrated Samplers (POCIS) 

In order to sequester very hydrophilic compounds such as pharmaceuticals, personal care 

products, hormones, and newer generation pesticides having low Log KOWs, POCIS were deployed at 

each site for 30 days in June/July 2003. Passive samplers integrate environmental contaminants during 

deployment, therefore compounds at very low levels, or present episodically, are enriched. Thus, these 

contaminants are better able to be detected than by using other sampling methods. The POCIS, made 

with an admixture of solid phase sequestering media encased in a microporous polyethersulfone 

membrane (Alvarez and others, 2004), were prepared by the USGS Columbia Environmental Research 

Center (CERC), Columbia, Miss. The two different types of sorbents constructed to maximize the 

retention and recovery of a wide variety of analytes were the Type “A” sorbent tailored for 

pharmaceuticals and the Type “B” sorbent containing the triphasic sorbent admixture tailored for most 

12
pesticides, herbicides, and hormones. The discs with each sorbent were placed in stainless deployment 

devices and secured at each site to ensure it was underwater during the entire sampling time. A field 

blank was opened during both deployment and retrieval of the POCIS to account for any potential 

atmospheric contamination. After the 30 days, samplers were retrieved, put in air tight cans on ice, and 

shipped to CERC for enrichment and dialysis according to procedures in Petty and others (2004). 

Methodologies and Results 

Physical conditions at the three sites are presented in table 1. 

Table 1. Water quality data per site on collection dates (July 14-16, 2003) 

Temperature 

(

Β

C) 

Specific Conductivity 

(ms/cm) 

Dissolved Oxygen 

(mg/L)(%) 

pH Turbidity 

NTU* 

Hazard Pond 6 28.53 1.126 5.93 (76.2) 7.98 75.5 

Trifolium Drain 19 27.88 6.420 6.67 (88) 6.92 5.3 

Thousand Palms 29.21 1.881 6.23 (81.7) 7.69 0.5 

* Nephelometric units. 

In this report, the scientific hypothesis is provided per experiment, there is a brief 

description of methods, and statistical results are presented. Statistics were run with 

reference to analyses in Toft and others (2003), with an alpha level at 0.05. All statistics 

were performed by using SAS (1990). 

1. Comparison of Microscopy and Flow Cytometry Methods for Counting Cells 

H01: There is no difference in cell counts as determined by hemocytometer use and flow cytometry.

 

Cells were extracted from fish from Thousand Palms, suspended, stored, and then 

diluted for duplicate counts by each method (microscopy and flow cytometry). 

Respective formulae for back-calculating sperm per ml were employed, and testis weight 

was used to adjust values to obtain counts per mg testis. 

The general linear models procedure determined that there was no difference in 

counts/mg testis when using both counting methods (p=0.9271)(F(1,40)=0.01; P = 0.9271) 

(fig. 8.) All statistics were performed by using SAS (1990). Therefore, count data for 

2003 were obtained by using flow cytometry. 

13
0.00E+00

1.00E+07

2.00E+07

3.00E+07

4.00E+07

5.00E+07

6.00E+07

Microscopy Flow Cytomety

Cells Counted

a 

a 

Figure 8. Average sperm counts per mg testes (n=21) of mosquitofish (Gambusia affinis) 

received July 17, 2003 from Thousand Palms by using two different methods (P=0.9271). 

2. Comparison of 2003 Sperm Counts per Site Determined by Using Flow 

Cytometry 

H01: There is no difference in Gambusia affinis sperm counts per site. 

By using samples received July 15-17, 2003, cells per mg testis were determined 

by using flow cytometric methods. 

0.00E+00

1.00E+07

2.00E+07

3.00E+07

4.00E+07

5.00E+07

6.00E+07

Hazard Pond 6 Trifolium Drain

19

Thousand Palms

Cells Counted (Exponent)

b

a 

a

Figure 9. Average sperm counts (raw data) per mg testes (n=12, 13, 21 of mosquitofish 

[Gambusia affinis] per site, respectively) for 2003 (P<0.0002). 

14
The data on sperm counts/mg testis were log transformed. The covariates fish 

length, gonopodium length, and weight were not correlated with log (count) as 

determined by a correlation analysis; however, an analysis of covariance run with these 

values as covariates resulted in significant differences in sperm counts between sites 

(p=0.0002). By using Duncan’s and Tukey’s multiple comparisons tests, sperm counts at 

Thousand Palms were found to be significantly higher than those at both Hazard Pond 6 

and Trifolium Drain 19 sites, with both grouped alike. Covariates were not significant, 

so there was no need for them to serve as covariates in analysis of variance. The results 

from an ANOVA achieved by using nontransformed values are reportable. 

3. Comparison of 2003 Sperm Mitochondrial Function and Sperm Viability per 

Site 

H01: There is no difference in Gambusia affinis sperm mitochondrial function (membrane 

potential) and membrane integrity (viability) and per site. 

For mitochondrial function, statistical analyses were performed both with 

proportions of functional or live cells (in other words, the proportions of sperm that had 

functioning mitochondria/[functional + nonfunctional]), where values were arcsin[sqrt] 

transformed for a one-way ANOVA and analyzed with the exact proportions formulae 

(Zar, 1984) between pairs of sites [pairwise comparisons between each pair of sites]. No 

covariates were used in the model. 

The results of the ANOVA found that site was significant, F (2,129) =40.25, 

p<0.0001. Both Duncan’s multiple range test and Tukey’s studentized range (HSD) test 

showed significant groupings of both contaminated sites having higher proportions of 

sperm with functioning mitochondria than the control site. 

By the exact proportions formulae, pairwise comparisons are: 

Hazard Pond 6 vs Thousand Palms t=244.138, p<0.0000 

Trifolium Drain 19 vs Thousand Palms t=235.743, p<0.0000 

 Hazard Pond 6 vs Trifolium Drain 19 t=8.9140, p<0.0000 

15
For sperm viability, statistical analyses were performed similarly (one way 

ANOVA with arcsin[sqrt] transformed data) without covariates, with similar results, in 

that the fish from the reference site showed significantly lower viable sperm than did that 

from the experimental sites, which were similarly grouped, with F (2,129) =29.33, p<0.0001. 

By the exact proportions formulae: 

Hazard Pond 6 vs Thousand Palms t=258.006, p<0.0000 

Trifolium Drain 19 vs Thousand Palms t=225.399, p<0.0000 

Hazard Pond 6 vs Trifolium Drain 19 t=32.8186, p<0.0000 

 In a second analysis, covariates were used in a one-way ANCOVA for both 

mitochondrial function (table 2) and viability (table 3). The covariates included fish 

length, gonopodia lengths, and fish weight. Correlations of proportions (arcsin[sqrt] 

transformed) were checked, and it was found that for mitochondrial function, there were 

some significant correlations with length and weight: 

Table 2. Correlations (P values) of transformed mitochondrial function values with 

covariates for all sites combined and for each site 

 A l l S i t e s H a z a r d P o n d 6 T r i f o l i u m D r a i n 1 9 T h o u s a n d P a l ms

Length 0.25 (0.0033) -0.36 (0.0325) 0.21 (NS)* 0.12 (NS) 

Gonopodium length 0.12 (NS) -0.43 (0.0095) 0.097 (NS) 0.31 (0.0206)

Weight 0.43 (0.0001) -0.18 (NS) 0.22 (NS) 0.24 (NS) 

*NS= not significant. 

Table 3. Correlations (P values) of transformed viable sperm values with covariates for all sites 

combined and for each site. 

All Sites Hazard Pond 6 Trifolium Drain 19 Thousand Palms

Length 0.2 (0.0151) -0.29 (0.0852) 0.31 (NS)* 0.03 (NS) 

Gonopodium length 0.11 (NS) -0.40 (0.0162) 0.207 (NS) 0.27 (0.0421)

Weight 0.40 (0.0001) -0.09 (NS) 0.34 (0.0351) 0.18 (NS) 

*NS= not significant. 

 For mitochondrial function, length and weight were significant, thereby 

explaining some of the variance, and site remained significant (F(2,126)=5.89 P=0.0036). 

By using both Duncan’s multiple range test and Tukey’s studentized range (HSD) test, 

16
there was significant grouping of both contaminated sites with higher proportions than 

the reference site. 

 For viability, length and weight were significant thereby explaining some of the 

variance, whereby site did not remain significant (F(2,126)=2.62, NS). In other words, 

sperm viabilities were not significantly different between the three sites. 

 Therefore, the analyses were redone without using gonopodia as a covariate. By 

using both Pearson (parametric) and Spearman (nonparametric) correlations of 

proportions (arcsin[sqrt transformed]) for data from all sites, both weight and length were 

positively correlated, whereas gonopodia data were not. For mitochondrial function, a 

proportions (arcsin[sqrt] transformed) one-way ANCOVA was run with covariates of 

length and weight. The analysis was run on all three sites, then with sites recategorized 

as only experimental (Trifolium Drain 19 and Hazard Pond 6) and reference (Thousand 

Palms). 

Table 4. ANCOVA (Arcsin[sqrt]) results using mitochondrial function adjusted means. 

 THREE-SITE TWO-SITE 

Site F(2,127)=7.45 P=0.0009 F(1,128)=15.01 P=0.0002 

Length F(1,127)=9.52 P=0.0025 F(1,128)=10.32 P=0.0017 

Weight F(1,127)=10.02 P=0.0019 F(1,128)=10.15 P=0.0018 

 

 

 Covariates length and weight were significant and explained some of the 

variance, whereby site still remained significant in both the three-sites and two-site 

analyses of mitochondrial function. Pairwise comparisons for the three sites were 

performed by using least squares means, where Hazard and Trifolium were not 

significantly different from each other, but both Hazard and Trifolium differed 

significantly from Thousand Palms (P=0.0004 and 0.0015, respectively, P

=0.05/3=0.0167.) Adjusted means (average proportions) and standard errors are plotted 

(fig. 10) for the three-site and two-site analyses. 

17
63.87% 63.70%

38.48%

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Hazard Trifolium ThousPalms

Site

Proportion of Functional Mitochondria

a a

b

63.79%

38.46%

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Experimental Reference

Site

Proportion of Functional 

Mitochondria

a

b

Figure 10. Adjusted means of sperm mitochondrial function (SE) from mosquitofish 

(Gambusia affinis) in the three site (top) (P=0.0004) and two site statistical analyses 

(bottom)(P=0.0015). 

Thus, for mitochondrial function, site was significant in both the three-site and 

two-site analyses, and weight and length were significant covariates. 

For viability, a proportions (arcsin[sqrt]) transformed) one-way ANCOVA was 

run with covariates of length and weight. Site remained significant in the presence of 

these covariates. 

18
Table 5. ANCOVA (Arcsin[sqrt]) results using viability adjusted means 

 THREE-SITE TWO-SITE 

Site F(2,127)=3.15 P=0.0462* F(1,128)=6.07 P=0.0151 

Length F(1,127)=13.93 P=0.0003 F(1,128)=16.48 P<0.0001 

Weight F(1,127)=15.42 P=0.0001 F(1,128)=15.93 P=0.0001 

 

Again, in a pairwise comparison, Hazard and Trifolium did not differ 

significantly from one another, but only Hazard differed significantly from Thousand 

Palms (p=0.0140). Trifolium did not significantly differ from Thousand Palms 

(p=0.077), where =0.05/3=0.0167. Adjusted means (average proportions) and 

standard errors are plotted (fig. 11) for the three-site and two-site analyses. 

67.23%

63.15%

46.30%

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Hazard Trifolium ThousPalms

Site

Proportion of Viable Sperm

a,b a

b

65.44%

45.92%

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Experimental Reference

Site

Proportion of Viable Sperm

a

b

Figure 11. Adjusted means of viability (SE) of sperm from mosquitofish (Gambusia 

affinis) per site in the three site (top) (P=0.0140) and two site analyses (bottom)(P=0.0151). 

19
Summarily, site was significant for both sperm mitochondria and viability 

analyses in both the three-site and two-site analyses using ANCOVA with fish length and 

weights as significant covariates. Mean proportions were adjusted with corresponding 

error terms (fig. 11). 

4. Comparison of Sperm Maturity per Site 

H01: There is no difference in counts of immature sperm from Gambusia affinis per site. 

 

Sperm were grouped into two categories, immature (M1) or mature (M2) (fig. 12). 

Figure 12. Flow cytometric histograms with DNA fluorescence intensity on the x-axis. 

More mature nuclei with less DNA are under Marker (M)2. Sperm of lesser maturity are 

delineated by M1. The top sample was fish 23 from Trifolium Drain 19, and the bottom 

sample was fish 55 from Thousand Palms. 

20
Numbers of immature sperm (M1) and mature sperm (M2) were identified 

according to M1/(M1+M2) for determining proportions of immature sperm. For 

statistical analyses, Proc ANOVA was run on arcsin[sqrt]proportion data. There were 

significantly higher numbers of immature sperm at Hazard Pond 6 than those at either 

Thousand Palms or Trifolium Drain 19. By Duncan’s and Tukey’s multiple 

comparisons, Trifolium grouped with both of the other sites: Therefore, for counts of 

immature sperm, Hazard>Trifolium>Thousand Palms, and Hazard>Thousand Palms. 

Raw data are presented in figure 13. 

Correlations were examined for the count response with length, gonopodium 

length, and weight as covariates, and no significant correlations were found over all sites. 

Therefore, no analysis of covariance was needed. 

40.83%

50.81%

58.29%

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Hazard Trifolium Thousand Palms

Site

Proportion Immature Sperm

a

ab

b

Figure 13. Average proportions of immature mosquitofish (Gambusia affinis) sperm per 

site (P=0.0031). 

5. Comparison of GSI, HSI, and Motility per Site (2003 data from fish received at 

NWRC) 

H01: There is no difference in Gambusia affinis GSI among sites. 

H02: There is no difference in Gambusia affinis HSI among sites. 

H03: There is no difference in Gambusia affinis sperm motilities among sites. 

21
The GSI was calculated as = (testis weight/fish weight) x 100. The HSI was 

calculated as = (liver weight/fish weight) x 100, and sperm motility was estimated as the 

percentage (to 5%) of progressively moving sperm as determined visually by darkfield 

microscopy observations in triplicate by three independent readers. 

Table 6. Average values (SE) of morphological characteristics of mosquitofish (Gambusia affinis)

collected July 14-16, 2003 

Site Hazard Pond (n = 12) Trifolium 19 (n = 13) Thousand Palms (n = 21)

GSI 3.17 (0.36)a

 2.44 (0.13)a 1.60 (0.11)b

testis weight (mg) 3.85 (0.49) 4.12 (0.37) 1.38 (0.14) 

fish weight (mg) 123.61 (9.05) 167.53 (11.18) 85.23 (5.00) 

gonopodium length (mm) 6.483 (0.161) 7.238 (0.157) 6.568 (0.095) 

liver weight (g) 1.77 (0.23)* 1.71 (0.17) 0.76 (0.07) 

fish length (mm) 23.998 (0.628) 27.365 (0.605) 23.153 (0.432) 

a,b = Different superscripts per row indicate significant differences in log transformed GSI 

data. 

* n = 3 for liver weights for this site. 

The GSI was not normally distributed, therefore a log transformation was applied 

to achieve normality and homogeneity. A one-way ANOVA was applied on log (GSI), 

where site was strongly significant F(2,43)=14.91; P<0.0001. Duncan’s and Tukey’s 

multiple comparison tests grouped both contaminated sites with higher values than those 

of Thousand Palms. An additional one-way nonparametric analysis on untransformed 

GSI led to the same conclusion (i.e., Kruskal-Wallis test, p<0.0001)(see fig. 14). 

A discriminant analysis was performed in order to obtain the rates of 

misclassification into the sites based on the log GSI data. For Hazard Pond 6 (n=12), the 

rate of misclassification was calculated to be 0.1667 (or 16.67% of the time). For 

Trifolium Drain 19 (n=13), the rate of misclassification was found to be 0.6154 (or 

61.54%), and Thousand Palms (n=21) had a rate of 0.2381 (or 23.81%). 

Both experimental sites were grouped together by Duncan’s and Tukey’s tests, so 

the analysis was rerun on recategorized sites where both experimental sites were grouped 

as “contaminated.” Again, the one-way ANOVA on log GSI showed significant site 

differences with values of log GSI in experimental sites more than twice that of the 

reference site. A nonparametric analysis result was the same. The discriminant analysis 

gave strong evidence of correct classification, whereby log GSI correctly identified the 

sites more than 80% of the time. The rate of misclassification found by using log GSI 

22
was 0.1600 (or 16.00% of the time) for the experimental sites, and 0.1905 (or 19.05%) 

for the reference site. 

3.170

2.440

1.600

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Hazard Pond Trifolium Thousand Palms

GSI

a 

a

b

Figure 14. Average, nontransformed gonadosomatic index (SE) of mosquitofish 

(Gambusia affinis) per site (P<0.0001). 

Most liver weights were missing from the Hazard Pond 6 site, so the analyses 

were run only on recategorized sites, where Hazard Pond 6 was put together with 

Trifolium Drain 19. The HSI data were not normally distributed, and a log 

transformation was applied to achieve normality and homogeneity. A one-way ANOVA 

was applied on log HSI, and site was strongly significant (F(1,43) = 8.11; p < 0.0067)(fig. 

15). Duncan’s and Tukey’s multiple comparison tests verified this result whereby 

experimental site values were significantly higher than the values from the reference site. 

An additional one-way nonparametric analysis on untransformed HSI led to the same 

conclusion (i.e., Wilcoxon 2-sample test, p<0.0017 and Kruskal-Wallis test, p < 0.0016). 

The discriminant analysis gave strong evidence of correct classification, where log HSI 

correctly identified the sites about 73% of the time, with a misclassification rate of 

0.2609 (or 26.09% of the time) for the experimental sites, and a misclassification rate of 

0.2727 (or 27.27%) for the reference site. 

23
1.29 a

0.93 b

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Experimental Reference

Site

Hepatosomatic Index

Figure 15. Average hepatosomatic indices from mosquitofish (Gambusia affinis) at 

recategorized sites, where dissimilar letters indicate significant differences (P<0.0067). 

For the experimental sites of Hazard Pond 6 and Trifolium Drain 19, n = 23, and for the 

reference site of Thousand Palms, n = 22. 

Sperm motility average percentages obtained by the three readers were converted 

to proportions and arcsin[sqrt] transformed. Although many values fell within the 30-

70% range in a manner that transformation would not be needed (Zar, 1984), the extreme 

values necessitated transformation of the data. One-way ANOVA indicated no 

significant differences among sites F(2,41)=2.12; P = 0.1325, thus no further analyses 

were performed. The average sperm motility for Hazard Pond 6 was 51% (SE 5), for 

Trifolium Drain 19 was 55% (SE 2), and for Thousand Palms was 39% (SE 3), with no 

significant differences in motilities among sites. 

Weights of fish are presented in figure 16. 

24
0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

Hazard Pond '01

Trifolium Drain '01

Hazard Pond '03

Trifolium Drain '03

Thousand Palms '03

Thousand P

Mean Male Fish Weight (kg) (SE)

alms '04

 

Figure 16. Mean male mosquitofish (Gambusia affinis) body weights from sites 

sampled in 2001, 2003, and 2004. 

6. Comparison of Gonopodia per Site (2001 and 2003) 

H01: There is no difference in Gambusia affinis gonopodia lengths among the sites. 

Gonopodia lengths from five sites in 2001 and from three sites in 2003 were 

obtained. From 2001, sites included Bruchard Drain, Hazard Pond 6, No Name Drain, 

Rock Hill Pond, and Trifolium Drain 19. From 2003, sites included Hazard Pond 6, 

Trifolium Drain 19, and Thousand Palms. 

An analysis of covariance was performed (Toft and others, 2003), whereby 

gonopodia length was corrected for body length (covariate), and estimated marginal 

means (SE) from the LSMEANS statement (e.g. adjusted means) were plotted. Based on 

tests of normality and plots of residuals, however, log transformations of gonopodia 

length did not improve normality or homogeneity of gonopodia length. Body length was 

already normally distributed and did not require transformation. In order to reconstruct 

the analyses and plots as per Toft and others (2003), if log transformations were used on 

gonopodia length, then the LSMEANS or adjusted means (SED) for the covariate would 

be back-transformed to enable plotting in the original units. 

For the 2001 data, preliminary correlations indicated a significant positive 

correlation of gonopodia length with body length, and so an analysis of covariance was 

performed by using log (10) transformation for both gonopodia and body lengths. There 

25
were significant differences among the sites (p=0.0203) with covariate body length (p < 

0.0001), where alpha=0.05/10=0.005 (fig. 17). 

6.51,a

6.41,ab 6.42, ab 6.45,ab

6.09b

5.6

5.7

5.8

5.9

6

6.1

6.2

6.3

6.4

6.5

6.6

6.7

Bruchard Hazard NoName Rock Hill Trifolium

Site (2001)

Adjusted Mean Gonadopodia 

Length 

 

Figure 17. Average adjusted mean gonopodia lengths from mosquitofish (Gambusia 

affinis) collected per site in 2001, where dissimilar letters indicate significant differences 

between sites (P=0.0203). 

For the 2003 data, an analysis of covariance was applied for correlated body 

length by using log (10) transformation. Again, significant differences were found 

between sites (p < 0.0001) with covariate length p < 0.0001, where alpha=0.05/3=0.0167 

(fig. 18). 

6.58,a

6.74,a

7.19,b

6

6.2

6.4

6.6

6.8

7

7.2

7.4

Hazard Pond Trifolium 19 Thousand Palms

Site (2003)

Adjusted Mean Gonadopodia 

Length 

 

Figure 18. Average adjusted mean gonopodia lengths from mosquitofish (Gambusia 

affinis) collected per site in 2003, where dissimilar letters indicate significant differences 

between sites (P<0.0001). 

26
7. Creation of GI Index (Gonopodia Length/Total Body Length) 

H01: A new index can be applied to fish per site with 2001 and 2003 data to test potential differences 

between sites, separately by year. 

In 2001 (June 11-13), fish were collected for analyses from Rock Hill Trail Pond, 

Hazard Pond 6, No Name Drain, Trifolium 19 Drain, Bruchard Drain, and the reference 

site San Felipe Creek. At San Felipe Creek, no phenotypic males were available for 

collection. 

In 2003, (July 15-17), males were sampled from Trifolium 19 Drain and Hazard 

Pond 6, and from Thousand Palms, another reference site where male mosquitofish were 

more abundant. 

Based on the significant differences among sites for 2001 (p=0.0203) and 2003 (p 

< 0.0001), whereby ANCOVAs using body length as a covariate in the analyses of 

gonopodia differences between sites, a new index was applied where GI = gonopodium 

length/total body length. 

Based on tests of normality and plots of residuals, GI was normally distributed 

for Bruchard, Hazard Pond 6, and Trifolium Drain 19 for 2001 and for all three sites 

sampled in 2003. Log transformations only slightly improved normality or homogeneity 

of GI for 2001 in Hazard and Rock Hill sites, and worsened normality for data from No 

Name, Trifolium (2001), and Hazard Pond 6 (2003). Because data from most sites were 

already normally distributed before applying a log transformation, no transformations 

were applied in the analyses. Results of ANOVA are fairly robust in spite of some 

irregularities. 

For 2001 data, GI data from sites were significantly different, F (4,91) = 3.63, P = 

0.0087. Looking at pairwise comparisons with Duncan’s multiple range test, where ∀ = 

0.05/10 = 0.005, Bruchard > Trifolium (P = 0.0042), and No Name > Trifolium (P = 

0.0006). All other pairwise comparisons were not significant (fig. 19). 

27
0.235

0.24

0.245

0.25

0.255

0.26

0.265

0.27

0.275

0.28

0.285

Bruchard Hazard NoName Rock Hill Trifolium

Site (2001)

Gonopodium Index (G/L)

a

a,b

a

a,b

b

Figure 19. Average gonopodia indices from mosquitofish (Gambusia affinis) collected 

per site in 2001, where dissimilar letters indicate significant differences between sites (P

= 0.0087). 

For 2003 data, GI data from sites were significantly different, F (2,136) = 39.36, P < 

0.0001. Looking at pairwise comparisons with Duncan’s multiple range test, where ∀ = 

0.05/3 = 0.0167, Thousand Palms > Hazard and Trifolium, with both P < 0.0001, and 

Hazard =Trifolium, P = 0.5168 (fig. 20). 

0.24

0.245

0.25

0.255

0.26

0.265

0.27

0.275

0.28

0.285

0.29

0.295

Hazard Pond Trifolium 19 Thousand Palms

Site (2003)

Gonopodia Index

 Figure 20. Average gonopodia indices from mosquitofish (Gambusia affinis) collected 

per site in 2003, where dissimilar letters indicate significant differences between sites (P

< 0.0001). 

b

a a

28
In order to test the appropriateness of pooling data from 2001 and 2003 for the 

Trifolium and Hazard Pond 6 sites, an ANOVA using year effect by both sites and per 

sites showed nonsignificance (P = 0.7917), and by least squares means comparisons, 

where ∀ = 0.05/2 = 0.025, for Hazard 2001 and 2003, P = 0.0475 and for Trifolium 2001 

and 2003, P = 0.1007. Therefore, years were pooled and an ANOVA for the three sites 

was performed. Sites were significantly different, F(2,175) = 44.56, P < 0.0001. By 

Duncan’s, where ∀ = 0.05/3 = 0.0167, Thousand Palms > Hazard and Trifolium (both P

< 0.0001) and Hazard = Trifolium (P = 0.3420) (fig. 21). 

0.24

0.245

0.25

0.255

0.26

0.265

0.27

0.275

0.28

0.285

0.29

0.295

Hazard Pond Trifolium 19 Thousand Palms

Site (2001 and 2003 pooled)

Gonopodia Index

 

Figure 21. Average gonopodia indices (gonopodia length/body length) from mosquitofish 

(Gambusia affinis) collected per site for pooled years 2001 and 2003, where dissimilar 

letters indicate significant differences between sites. 

In testing whether GI could correctly classify individuals into appropriate sites by 

using all three sites or two sites recategorized as experimental or reference, 

recategorization improved classification (Table 7). 

Table 7. Discriminant analysis results showing rates of misclassification using GI 

Site Hazard Pond 6 Trifolium Drain 19 Thousand Palms OR Experimental Reference

Rate 0.689 0.429 0.255 0.191 0.255 

Probability 0.33 0.33 0.33 0.50 0.50 

29
When three sites were used in the discriminant analysis, many Hazard individuals 

were misclassified as Trifolium and vice versa. Overall, GI (untransformed) is a good 

indicator for distinguishing between contaminated and uncontaminated sites. 

8. Contaminants Analyses (2001, 2003) 

H01: There is no difference in contaminants among sites sampled in 2001 using fish tissue data and 

2003 using a polar organic compound integrated sampler. 

Data were not normalized for lipids for the 2001 data. Further analyses may be 

needed for better interpretation of these data from these two years. 

In 2001, contaminants data were obtained from male and female fish tissue, 

whereby trifluralin, chlorthal-dimethyl (DCPA), chlorpyrifos (phosphorthioic acid 0, 0-

diethyl O-[3,5,6-trichloro-2-pyridinyl] ester), trans-nonachlordane, cis-nonachlordane, 

dichlorodiphenyldichloroethylene (DDE), dieldrin, endosulfan, pp,’-DDE (from bed 

sediment), total organochlorines, and percent lipid were variables in the analyses. In 

2003, contaminants data from an integrated sampling device included trifluralin, DCPA, 

fipronil, fipronil sulfide, fipronil sulfone, trans-chlordane, endosulfan I, endosulfan II, 

endosulfan sulfate, dieldrin, and total organochlorines (fig. 22). 

Differences between sites for all years could not be tested because only one 

contaminant value was provided per site. Standard errors could not be computed either. 

30
24.2

0 0

1.9

8.3

2.4

0000

2 2.8

35.8

1.9

0

0

5

10

15

20

25

30

35

40

DCPA Fipronil

sulfide

Fipronil Fipronil

sulfone

Dieldrin

Compound

Organic Contaminant from POCIS 

(ng/POCIS)

0 0

12.2

0

2.7 2.8

6.6

0 0 0

4.1

2

0

2

4

6

8

10

12

14

Endosulfan I Endosulfan II Endosulfan

sulfate

Chlordane

Compound

Organic Contaminant from POCIS 

(ng/POCIS)

6.5

53.1

873 887.5

0

48.6

0

100

200

300

400

500

600

700

800

900

1000

Trifluralin Total OCs

Compound

Organic Contaminant from 

POCIS (ng/POCIS)

Hazard Trifolium Thousand Palms

 

Figure 22. Organic contaminants sequestered by the polar organic compound 

integrated samplers (POCIS) in 2003. 

31
Discussion 

Because aquatic animals are generally more sensitive than humans are to 

environmental stressors (Adams and others, 2003), they can act as sentinels for resource 

degradation. Species occupying particular trophic levels or having particular life 

histories may preferentially reflect environmental conditions. Sublethal stress is 

generally manifested first at the suborganismal level where immune systems are 

compromised, reproductive success is reduced, and genetic integrity is altered. Because 

molecular and biochemical responses of cells are preceded by chemical changes in 

nuclei, cytoplasm, membranes, and extracellular fluids, these responses can be diagnostic 

and contribute to an assessment of ecosystem health. Gambusia affinis are good 

sentinels, as they are ubiquitously distributed and have readily measurable sexual 

characteristics that are affected by exposure to chemicals with estrogenic or 

antiandrogenic activity (Toft and others, 2003). Male mosquitofish have mature sperm 

cells in their testes year-round (Fraile and others, 1992). 

In this study, combinations of biomarkers indicative of whole animal and 

reproductive conditions were employed. A special focus was on sperm, the cells of 

which consist of several membrane compartments, and cell competency requires that 

each of these membrane compartments be intact. Such biomarker data integrate well 

contaminants data, may reflect transgenerational effects, and can be interpreted in terms 

of long-term hazards to a community or population. 

Pollutants may disrupt reproductive endocrine function by acting at the 

hypothalamus, pituitary, gonad, or liver (Kime and Nash, 1999), whereby gonadal 

development or viability of gametes is impacted. Strategies for coping with stress affect 

reproductive fitness by gamete or progeny quality (Schreck and others, 2001). Sperm 

viability has been most rigorously investigated with mammalian sperm in 

cryopreservation studies. Although the conditions of cryopreservation experiments are 

not directly correlated to environmental studies, many of the molecular mechanisms 

behind integrity of cellular structures and in vitro conditions are related. Flow cytometry 

technology can quickly provide an estimation of sperm cell membrane integrity and has 

been used with terrestrial species including horse (Equus caballus) (Merkies and others, 

2000; Graham, 2001), turkey (Meleagris spp.) (Donoghue and others, 1995), wild boar 

(Sus scrota), ram (Apistogramma ramirezi), dog (Canis spp.), mouse (Amphipyra 

32
tragopoginis), human (Homo sapiens), bull (Bos taurus) (Garner and others, 1986; 

Ericsson and others, 1990), and with some aquatic species including tilapia 

(Oreochromis niloticus) (Segovia and others, 2000), trout (Salmonidae spp.) (Cabrita and 

others, 2001), eastern oyster (Crassostrea virginica) (Paniagua-Chavez and others, in 

press), red abalone (Haliotis rufescens) (Salinas-Flores and others, 2005), whiteleg 

shrimp (Litopenaeus vannamei) (Lezcano and others, 2004), and other marine 

invertebrates (Adams and others, 2003). Gamete viability has been suggested as an 

indicator of reproductive endocrine disruption in fish caused by exposure to xenobiotics 

(Kime and Nash, 1999), and this report addresses several sperm quality parameters. 

In this study, a proportions (arcsin[sqrt]) transformed) one-way ANCOVA was 

run for detecting sperm viability differences between sites and employed covariates fish 

length and weight. Site remained significant in the presence of these covariates, whereby 

the fish from the experimental sites had sperm viabilities significantly higher than those 

from the reference site (fig. 11). Chemicals from the POCIS that were highest at 

Thousand Palms included fipronil and its metabolites and chlordane. Chemicals do not 

have a single mode of action in the organism, and they affect a variety of physiological 

factors (Heath, 1987). That relatively fewer contaminated sites had fish with lower 

sperm viabilities and mitochondrial function may reflect fewer nutrition resources at 

those sites. 

Gonadal development and fecundity are affected by certain essential dietary 

nutrients, especially in continuous spawners (Izquierdo and others, 2001). Lipid and 

fatty acid compositions have been identified as major dietary factors that determine 

successful reproduction and survival of offspring. The most common reaction that 

occurs between toxicants and lipids is lipid peroxidation (Schlenk, 2001). Dietary 

polyunsaturated fatty acids in sperm membrane phospholipids have been manipulated in 

sea bass (Dicentrarchus labrax) (Bell and others, 1996) to influence sperm motility and 

fertility in domestic chicken (Gallus spp.) (Cerolini and others, 2005) and sperm 

membrane integrity in rainbow trout (Oncorhynchus mykiss) (Pustowka and others, 

2000). Highly unsaturated fatty acids with 20 or more carbon atoms, either directly or 

through their metabolites, affect fish maturation and steroidogenesis (Izquierdo and 

others, 2001). Sperm plasma membrane organization, fluidity, permeability, and lipid 

composition are parameters important to membrane integrity. Sperm integrity has been 

33
interrupted by membrane peroxidation (Donoghue and Donoghue, 1997) whereby 

reactive oxygen species induce tissue damage and motility can be lowered. Nutrients 

that add to the protection of reactive oxygen species contribute to the protection of 

membrane integrity, such as the selenium-dependent enzyme glutathione peroxidase (Wu 

and others, 1979). Dietary intake of antioxidants such as vitamins C and E, and 

micronutrients such as folate and zinc are critical for normal semen quality in animals 

and humans (Eskenazai and others, 2005). 

Evaluating milt characters directly reflects on fertilization potential, where 

several quality bioindicators, in addition to sperm viability, are associated with sperm 

physiology. These include mitochondrial membrane potential, sperm count, seminal 

plasma components, sperm cell maturity, and sperm function. If changes caused by 

external chemicals are severe enough, histological changes may be seen. Because organs 

are composed of many cell types, effects on one or more of these cell types will be 

reflected in changes in organ function. For example, cellular composition of testes is 

reflective of endocrine impacts, whereby the larval stages are most sensitive (Heath, 

1987). Fish testes are composed of cellular cysts containing Sertoli cells, and all cells 

with a cyst and cysts with a lobule are normally at the same stage of spermatogenesis 

(Dawson, 1998). Therefore, assessing ploidy of single cell suspensions stained with PI 

from mosquitofish testes is indicative of spermatogenic stage, whereby diploid stem cells 

(spermatogonia) either undergo mitotic divisions to reproduce themselves or differentiate 

into primary spermatocytes (4N, containing twice as much DNA per cell). These cells 

undergo meiosis, followed by two cell divisions to produce four haploid cells (1N, 

spermatids) (Levek-Motola and others, 2005). In this study, the ploidy of cells from 

testes were determined and categorized into tetraploid or primary spermatocytes (least 

mature) and other, lesser ploidy levels (fig. 12). When the spermatogenesis pathway is 

disrupted, there is a reduction in the production of mature sperm forms. In a histological 

study of sperm relative to other germ cell stages of feral common carp (Cyprinus carpio) 

from contaminated and reference sites, fewer sperm were found at the contaminated site 

and GSI values were lower (Patino and others, 2003). In this study, there were 

significantly higher numbers of immature sperm at the Hazard Pond 6 site than at 

Thousand Palms (fig. 13), where DCPA, endosulfan sulfate, dieldrin, and total 

organochlorines were more numerous by POCIS. 

34
Reproductive performance depends on metabolic processes (Zrimsek and others, 

2004). Damage to sperm mitochondria causes a decrease in ATP production and thus in 

sperm motility, although this association is sometimes not made because of the nature of 

visual imprecise assessments (Thomas and others, 1998; Garner and others, 1997). The 

most widely used mitochondrial-specific probe, R123, is a cationic compound that 

excites at 488 nm and emits at 515-575 nm (green fluorescence). It accumulates in the 

mitochondria as a function of transmembrane potential, of R123 concentration, and of 

sperm numbers. Mitochondrial membrane function in sperm is sometimes correlated 

with membrane integrity and with motility (Garner and others, 1997; O’Connell and 

others, 2002; Paniagua-Chavez and others, in press). Estradiol administration in vivo is 

known to affect sperm metabolism and motility (Saberwal and others, 2003), whereby 

patients with asthenozoospermia (reduced sperm motility) show improvement in sperm 

motility with estradiol, indicating that it is involved in an aspect of sperm metabolism 

that is associated with motility (Saberwal and others, 2003). Tamoxifen, a nonsteroidal 

estrogen antagonist, was shown to increase R123 uptake in rat (Murida spp.) sperm, yet 

membrane integrity was not impacted, suggesting disturbance of transmembrane ion 

pumps and increased calcium levels which alters sperm motility (Saberwal and others, 

2003). In this study, mitochondrial function at the reference site was significantly lower 

than at each of the experimental sites (fig. 10), where more endocrine disruptive 

chemicals were detected (fig. 22). 

The ratio of liver to body weight differs greatly between species of fish, and their 

nutritional state has considerable influence on liver size (Heath, 1987). In this study, the 

HSI values at the experimental sites were higher than those at the reference site, thereby 

lending additional support toward there being a difference in the nutritional resources 

available to the fish. The liver is responsible for enzymatic decontamination processes, 

vitellogenin production, and stores glycogen as energy reserves. The largest store of 

carbohydrate in the fish body is in the liver. Stressors raise serum glucose, and liver 

glycogen stores can be depleted in adverse conditions. The HSI values have been shown 

to increase after exposure to certain types of contaminants, particularly petroleum 

hydrocarbons (Fletcher and others, 1982; Fabacher and Baumann, 1985; Baumann and 

others, 1991), perhaps because of herplasia and hypertrophy caused by the induction of 

the missed-function-oxidase system in the liver to detoxify the contaminants (Poels and 

35
others, 1980). In this study, the HSI was significantly greater at the experimental sites 

than that at the reference site (fig. 15). 

Mature male mosquitofish posses a highly modified anal fin called a gonopodium 

that develops under the influence of endogenous androgens at sexual maturity, and this 

structure is a useful marker for quantifying the effects of known or suspected 

environmental androgens (Angus and others, 2001). In this study, analyzing gonopodia 

adjusted for fish length showed that those at the reference site were significantly longer 

than those at the experimental sites (fig. 18). In this study the new index, GI, was 

developed for comparing differences between sites. The untransformed GI for a single 

year (fig. 20) and pooled over years (fig. 21) indicated significantly greater indices at the 

reference site and nonsignificance between the experimental sites in each case. 

Gametogenesis is largely under the control of steroid hormones in vertebrates 

(Song and Gutzeit, 2003), whereby xenobiotics may interfere with hormone action and 

consequent impacts. Although it is suggested that the molecular and cellular effects of 

hormonally active compounds are best studied under well-defined conditions in vitro 

(Song and Gutzeit, 2003), observations from sperm cell maturity levels and sperm cell 

counts indicated that the animals at the experimental sites were less sexually advanced 

than those at the reference site. Sperm count is a very common biomarker of testis 

function in humans, and the use of flow cytometry in fertility assays has been helpful, 

and it allows for other analysis such as DNA content and integrity (Eustache and others, 

2001). Dibromochloropropane has been found to cause sperm count depression in male 

humans (Glass and others, 1979). Appropriate levels of zinc are crucial for proper sperm 

physiology, counts, and motility (Turgut and others, 2003), and pp-DDE, vinclozolin, 

and flutamide were found to inhibit guppy (Poecilia reticulata) gonopodia development 

and sperm count (Bayley and others, 2002). In this study, a flow cytometric technique 

for counting Gambusia affinis sperm was verified (fig. 8), and the results from examining 

samples from 2003 established that there were significantly higher numbers of sperm 

from the reference site than from each of the experimental sites. 

Overall, there are several lines of evidence pointing toward hormonal disturbance 

in male Gambusia affinis at experimental sites in the Imperial Valley. A new index for 

communicating endocrine impacts on morphology, GI, is recognized, and a method for 

36
counting fish sperm was verified. There is room for further development of ideas 

relative to the parameters studied. 

Acknowledgments 

The authors thank Steve Goodbred from USGS and Scott Sobiech from FWS for the opportunity 

to contribute to these studies, B. Vairin and J. Davis at NWRC for editorial support, D. Johnson at 

NWRC for statistical review, and E. Theall and J. Shin at NWRC for technical support. The concept of 

the gonopodia indices (gonopodia length/body length) is attributed to Steve Goodbred. The authors 

thank Dr. A. Rocha from the University of Portugal, T. Campbell from LSU, and R.G. Thomas from the 

LSU AgCenter for critical reviews. 

References Cited 

Adams, S.L., Hessian, P.A., and Mladenov, P.V., 2003, Flow cytometric evaluation of 

mitochondrial function and membrane integrity of marine invertebrate sperm: 

Invertebrate Reproduction and Development, v. 44, p. 45-51. 

Alvarez, D.A., Petty, J.D., Huckins, J.N., Jones-Lepp, T.L., Getting, D.T., and Manahan, D.T., 2004, 

Development of a passive, in situ, integrative sampler for hydrophilic organic contaminants in aquatic 

environments: Environmental Science and Technology, v. 23, p.1640-1648. 

Angus, R.A., McNatt, H.B., Howell, W.M., Peoples, S.D., 2001, Gonopodium 

development in normal meal and 11-ketotestosterone-treated female mosquitofish 

(Gambusia affinis): A quantitative study using computer image analysis: General and 

Comparative Endocrinology, v. 123, p. 222-234. 

Baumann, P.C., Mac, M.J., Smith, S.B., and Harshbarger, J.C., 1991, Tumor frequencies 

in walleye (Stizostedion vitreum) and brown bullhead (Ameiurus nebulosus) and 

sediment contaminants in tributaries of the Laurentian Great Lakes: Canadian Journal 

of Fisheries and Aquatic Sciences, v. 48, p. 1804-1810. 

Bayley, M., Junge, M., Baatrup, E., 2002, Exposure of juvenile guppies to three 

antiandrogens causes demasulinization and a reduced sperm count in adult males: 

Aquatic Toxicology, v. 56, p.227-239. 

37
Bell, M.V., Dick, J.R., Thrush, M., and Navarro, J.C., 1996, Decreased 20:4n-6/20:5n-3 

ratio in sperm from cultured sea bass, Dicentrarchus labrax, broodstock compared 

with wild fish: Aquaculture, v. 144, p. 189-199. 

Cabrita, E., Martinez, F., Real, M., Alvarez, R., and Herraez, M.P., 2001, The use of 

flow cytometry to assess membrane stability in fresh and cryopreserved trout 

spermatozoa: CryoLetters, v. 22, p. 263-272. 

Carey, C., and Bryant, C.J., 1995, Possible interrelations among environmental toxicants, 

amphibian development, and decline of amphibian populations. Environmental Health 

Perspectives, v. 103, p. 13-17. 

Cerolini, S., Pizzi, F., Gliozzi, T., Maldjiani, T., Zaniboni, L., and Parodi, L., 2005, Lipid 

manipulation of chicken semen by dietary means and its relation to fertility: a review: 

Worlds Poultry Science Journal, v. 59, p. 65-75. 

Colborn, T., and Clement, C., 1992, Chemically Induced Alterations in Sexual and 

Functional Development: The Wildlife/Human Connection: Princeton, Princeton 

Scientific Publishing Co., 403 p. 

Dawson, A., 1998, Natural and anthropogenic environmental oestrogens: the scientific 

basis for risk assessment. Comparative reproductive physiology of nonmammalian 

species: Pure and Applied Chemistry, v. 70, p. 1657-1669. 

Donoghue, A.M., and Donoghue, D.J., 1997, Effects of water- and lipid-soluble 

antioxidants on turkey sperm viability, membrane integrity, and motility during liquid 

storage: Poultry Science, v. 76, no. 10, p. 1440-1445. 

Donoghue, A.M., Garner, D.L., Donoghue, D.J., and Johnson, L.A., 1995, Viability 

assessment of turkey sperm using fluorescent staining and flow cytometry: Poultry 

Science, v. 74, p. 1191-1200. 

Ericsson, S.A., Garner, D.L., Johnson, L.A., Redelman, D., and Ahmad, K., 1990, Flow 

cytometric evaluation of cryopreserved bovine spermatozoa processed using a new 

antibiotic combination: Theriogenology, v. 33, p. 1211-1220. 

Eskenazi, B., Kidd, S.A., Marks, A.R., Sloter, E., Block, G., and Wyrobek, A.J., 2005, 

Antioxidant intake is associated with semen quality in healthy men: Human 

Reproduction, v. 20, p. 1006-1012. 

Eustache, F., Jouannet, and Auger, J., 2001, Evaluation of flow cytometric methods to 

measure human sperm concentration: Journal of Andrology v. 22, p. 558-567. 

38
Fabacher, D.L., and Baumann, P.C., 1985, Enlarged livers and hepatic microsomal 

mixed function oxidase components in tumor-bearng brown bullheads from a 

chemically contaminated river: Environmental Toxicology and Chemistry, v. 4, p. 703-

710. 

Fletcher, G.L., King, M.J., Kiceniuk, J.W., and Addison, R.F., 1982, Liver hypertrophy 

in winter flounder following exposure to experimentally oiled sediments: Comparative 

Biochemistry and Physiology, Part C, v. 73, p. 457-462. 

Foreman W.T., Connor, B.F., Furlong, E.T., Vaught, D.G., and Merten, L.M., 1995, Methods of 

analysis by the U.S. Geological Survey National Water Quality Laboratory—determination of 

organochlorine pesticides and polychlorinated biphenyls in bottom sediment by dual capillary-column 

gas chromatography with electron-capture detection. U.S. Geological Survey Open-File Report 95-

140, Denver, 78p. 

Fraile, B., Saez, F.J., Vicentini, C.A., De Miguel, M.P. Paniagua R., 1992, The testicular 

cycle of Gambusia affinis holbrooki (Teleostei: Poeciliidae): Journal of Zoology, v. 

228, p. 115-126. 

Garner, D.L., and Johnson, L.A., 1995, Viability assessment of mammalian sperm using 

SYBR-14 and propidium iodide: Biology of Reproduction, v. 53, p. 276-284. 

Garner, D.L., Pinkel, D., Johnson, L.A., and Pace, M.M., 1986, Assessment of 

spermatozoal function using dual fluorescent staining and flow cytometric analyses: 

Biology of Reproduction, v. 34, p. 127-138. 

Garner, D.L., Thomas, C.A., Joerg, H.W., DeJarnette, J.M., and Marshall, C.E., 1997, 

Fluorometric assessments of mitochondrial function and viability in cryopreserved 

bovine spermatozoa: Biology of Reproduction, v. 57, p. 1401-1406. 

Glass, R.I., Lyness, R.N., Mengle, D.C., Powell, K.E., Kahn, E., 1979, Sperm count 

depression in pesticide applicators exposed to dibromochloropropane: American 

Journal of Epidemiology, v.109, p.346-351. 

Glenn, W.D., III, 1998, Effect of osmolality, extender and temperature on gamete storage 

of koi carp (Cyprinus carpio): Baton Rouge, Louisiana State University, 202p. 

Goodbred, S.L., Gillion, R.J., Gross, T.S., Denslow, N.P., Bryant, W.L., and Schoeb, 

T.R., 1997, Reconnaissance of 17beta-estradiol, 11-ketotestosterone, vitellogenin, and 

gonad histopathology in common carp of United States streams: potential for 

39
contaminant-induced endocrine disruption: U.S. Geological Survey Open File Report 

96-627, p. 1-47. 

Graham, J.K., 2001, Assessment of sperm quality: a flow cytometric approach: Animal 

Reproduction Science, v. 68, p. 239-247. 

Graham, J.K., Kunze, E., and Hammerstedt, R.H., 1990, Analysis of sperm cell viability, 

acrosomal integrity, and mitochondrial function using flow cytometry: Biology of 

Reproduction, v. 43, p. 55-64. 

Gross, T.S., Arnold, B.S., Sepulveda, M.S., and McDonald, K., 2003, Endocrine 

disrupting chemicals and endocrine active agents, in Hoffman, D.J., Rattner, B.A., 

Burton, G.A. Jr., and Cairns, J.Jr., eds., Handbook of Ecotoxicology: Boca Raton, 

Lewis Publishers, p. 1033-1098. 

Heath, A.G., 1987, Water Pollution and Fish Physiology: Boca Raton, CRC Press, 245 p. 

Hudson, J.L., Duque, R.E., and Lovett, E.J., 1985, Applications of flow cytometry in 

immunotoxicology, in Dean, J.H., Luster, M.I., Munson, A.E., Amos, H., eds., 

Immunotoxicology and Immunopharmacology: New York, Raven Press, p. 159-177. 

Izquierdo, M.S., Fernandez-Palacios, H., and Tacon, A.G.J., 2001, Effect of broodstock 

nutrition on reproductive performance of fish: Aquaculture, v. 197, p. 25-42. 

Jenkins, J.A., 2000, Infectious disease and quality assurance considerations for the 

transfer of cryopreserved fish gametes, in Tiersch, T.R, and Mazik, P.M., eds., 

Cryopreservation in Aquatic Species: Baton Rouge, World Aquaculture Society, p. 

343-363. 

Kime, D.E., and Nash, J.P., 1999, Gamete viability as an indicator of reproductive 

endocrine disruption in fish: Science of the Total Environment, v. 233, p.123-129. 

Leiker T.J., Madsen, J.E., Deacon, J.R., and Foreman, W.T., 1996, Methods of analysis 

by the U.S. Geological Survey National Water Quality Laboratory-determination of 

chlorinated pesticides in aquatic tissue by capillary-column gas chromatography with 

electron-capture detection. U.S. Geological Survey Open-File Report 94-710, Denver, 

42 p. 

Levek-Motola, N., Soffer, Y., Shochat, L., Raziel, A., Lewin, L.M., and Golan, R., 2005, 

Flow cytometry of human semen: a preliminary study of a non-invasive method for the 

detection of spermatogenic defects: Human Reproduction, v. 20, p. 3469-3475. 

40
Lezcano, M., Granja, C., and Salazar, M., 2004, The use of flow cytometry in the 

evaluation of cell viability of cryopreserved sperm of the marine shrimp: Cryobiology, 

v. 48, p. 349-356. 

McNiven, M.A., Gallant, R.K., and Richardson, G.F., 1992, In vitro methods of 

assessing the viability of rainbow trout spermatozoa: Theriogenology, v. 38, p. 679-

686. 

Merkies, K., Chenier, T., Plante, C., and Buhr, M.M., 2000, Assessment of stallion 

spermatozoa viability by flow cytometry and light microscope analysis: 

Theriogenology, v. 54, p. 1215-1224. 

Nickum, J.G., Bart, H. L. Jr., Bowser, P.R., Greer, I.E., Hubbs, C., Jenkins, J.A, 

MacMillan, J.R., Rachlin, J.W., Rose, J.D., Sorensen, P.W., and Tomasso, J.R., 2004, 

Guidelines for the use of fishes in research: Bethesda, The American Fisheries 

Society, 

http://www.fisheries.org/html/Public_Affairs/Sound_Science/Guidelines2004.shtml

O'Connell, M., McClure, N., and Lewis, S.E.M., 2002, The effects of cryopreservation 

on sperm morphology, motility and mitochondrial function: Human Reproduction, v. 

17, p. 704-709. 

Paniagua-Chavez, C.G., Jenkins, J., Segovia, M., and Tiersch, T.R. (in press), 

Assessment of gamete quality for the eastern oyster (Crassostrea virginica) by use of 

fluorescent dyes: Cryobiology. 

Patino, R., Goodbred, S., Draugelis-Dale, R., Barry, C.E., Foott, J.S., Wainscott, M.R., 

Gross, T.S., and Covay, K.J., 2003, Morphometric and histopathological parameters of 

gonadal development in adult common carp from contaminated and reference sites in 

Lake Mead, Nevada: Journal of Aquatic Animal Health, v. 15, p. 55-68. 

Petty, J.D., Huckins, J.N., Alvarez, D.A., Brumbaugh, W.G., Cranor, W.L., Gale, R.W., 

Rastall, A.C., Jones-Lepp, T.L., Leiker, T.J., Rostad, C.E., and Furlong, E.T., 2004, A 

holistic passive integrative sampling approach for assessing the presence and potential 

impacts of waterborne environmental contaminants: Chemosphere, v. 54, p.695-705. 

Poels, C.L.M., van der Gaag, M.A., and van der Kerkhoff, J.F.J., 1980, An investigation 

into the longterm effects of Rhine water on rainbow trout: Water Research, v. 14, p. 

1029-1035. 

41
Pustowka, C., McNiven, M.A., Richardson, G.F., and Lall, S.P., 2000, Source of dietary 

lipid affects sperm plasma membrane integrity and fertility in rainbow trout 

Oncorhynchus mykiss (Walbaum) after cryopreservation: Aquaculture Research, v. 31, 

p. 297-305. 

Saberwal, G.S., Gill-Sharma, M.K., Balasinor, N., Choudhary, J., Padwal, V., and Juneja, 

H.S., 2003, Tamoxifen, protein kinase C and rat sperm mitochondria: Cell Biology 

International, v. 27, p. 761-768. 

Salinas-Flores, L., Paniagua-Chavez, C.G., Jenkins, J.A., and Tiersch, T.R, 2005, 

Cryopreservation of sperm of red abalone (Haliotis rufescens): Journal of Shellfish 

Research, v. 24, p. 415-420. 

SAS Institute Inc., 1999, SAS/STATR User's Guide, Version 8, Fourth Edition, Volume 2, 

Cary, NC: SAS Institute Inc., p 3569-3590. 

Schlenk, D., 2001, General Mechanisms of Toxicity, in Schlenk, D., and Benson, W. H., 

eds., Target Organ Toxicity in Marine and Freshwater Teleosts: New York, Taylor and 

Francis, p. 1-25. 

Schreck, C.B., Contreras-Sanchez, W., and Fitzpatrick, M.S., 2001, Effects of stress on 

fish reporduction, gamete quality, and progeny: Aquaculture, v. 197, p. 2-24. 

Segovia, M., Jenkins, J.A., Paniagua-Chavez, C., and Tiersch, T.R., 2000, Flow 

cytometric evaluation of antibiotic effects on viability and mitochondrial function of 

stored sperm of Nile tilapia: Theriogenology, v.53, p.1489-1499. 

Shelton L.R., and Capel, P.D., 1994, Guidelines for collecting and processing samples of 

stream bed sediment for analysis of trace elements and organic contaminants for the 

National Water-Quality Assessment Program. U.S. Geological Survey Open-File 

Report 94-458, Sacramento, 20 p. 

Song, M., and Gutzeit, H.O., 2003, Effect of 17-alpha-ethynylestradiol on germ cell 

proliferation in organ and primary culture of nedaka (Oryzias latipes) testis: 

Developmental Growth Differentiation, v. 45, p. 327-337. 

Thomas, C.A., Garner, D.L., DeJarnette, J.M., and Marshall, C.E., 1998, Effect of 

cryopreservation on bovine sperm organelle function and viability as detemrined by 

flow cytometry: Biology of Reproduction, v. 58, p. 786-793. 

42
Toft, G., Edwards, T.M., Baatrup, E., and Guillette, L.J., 2003, Disturbed sexual 

characteristics in male mosquitofish (Gambusia holbrooki) from a lake contaminated 

with endocrine disruptors: Environmental Health Perspectives, v.111, p.695-701. 

Tuschl, H., and Schwab, C.E., 2004, Flow cytometric methods used as screening tests for 

basal toxicity of chemicals: Toxicology in Vitro, v. 18, p. 483-491. 

Turgut, G., Abban, G., Turgut, S., Take, G., 2003, Effect of overdoes zinc on mouse 

testis and its relation with sperm count and motility: Biological Trace Element 

Research, v.96, p.271-279. 

Wu, A.S.H., Oldfield, J.E., Shull, L.R., and Cheeke, P.R., 1979, Specific effect of 

selenium deficiency on rat sperm: Biology of Reproduction, v. 20, p. 793-798. 

Xu, L., Wang, S., Yang, X., and Wang, X., 2001, Effects of cadmium on rat sperm 

motility evaluated with computer assisted sperm analysis: Biomedical and 

Environmental Sciences, v. 14, p. 312-317. 

Zar, J.H., 1984, Data Transformations, in Biostatistical Analysis (2nd ed.): Englewood 

Cliffs, Prentice-Hall, Inc., p. 236-243. 

Zrimsek, P., Kunc, J., Kosec, M., and Mrkun, J., 2004, Spectrophotometric application of 

resazurin reduction assay to evaluate boar semen quality: International Journal of 

Andrology, v. 27, p. 57-62. 

43