growth and reproduction of southern flounder ( paralichthys lethostigma ... · growth and...

Growth and reproduction of Southern Flounder (Paralichthys lethostigma) in the north-central Gulf of Mexico

A Master’s Thesis Prospectus submitted by:

Morgan M. Corey

Department of Coastal Sciences

The University of Southern Mississippi

Ocean Springs, MS

June 29, 2015

Dr. Robert T. Leaf ________________________________________

Major Professor

Nancy J. Brown-Peterson _________________________________

Committee Member

Dr. Mark S. Peterson _____________________________________

Committee Member

Morgan Corey Research Prospectus 06/29/2015

1

Ecology of Southern Flounder

Southern Flounder (Paralichthys lethostigma) is the most commonly harvested flatfish

species that occurs in the north-central Gulf of Mexico (GOM) (Hensley and Ahlstrom 1984).

Southern Flounder are found as far north as Albermarle Sound, North Carolina on the Atlantic

coast and throughout the GOM (Reagan and Wingo 1985). However, the Atlantic and GOM 5

populations are separated geographically around the southernmost Florida peninsula. There is

evidence for genetic distinction between the Atlantic and GOM Southern Flounder populations,

and some small-scale genetic differences have been reported within the GOM (Blandon et al.

2001, Anderson and Karel 2012).

Southern Flounder are a euryhaline, estuarine-dependent species with variable spatial 10

dynamics (Deubler 1960, Etzold and Christmas 1979). Southern Flounder migrate to offshore

continental shelf waters for spawning in winter months and larvae are transported to lower-

salinity inshore waters in the late winter and spring (Stokes 1977, Shepard 1986, Ditty et al.

1988). Southern Flounder spawning may also occur in freshwater, and this behavior is

supported by otolith microchemistry analyses in the Mobile-Tensaw River Delta of Alabama and 15

in Texas coastal waters (Lowe et al. 2011, Farmer et al. 2013, Nims and Walther 2014).

However, little is known about the spawning habitats and seasonal migrations of Southern

Flounder in the GOM.

The Southern Flounder stock is a valuable marine resource in the GOM and supports

both a recreational and commercial fishery. Although Southern Flounder and Gulf Flounder 20

(Paralichthys albigutta) are managed as a single stock, Southern Flounder is the more abundant

of the two species harvested in the north-central GOM (VanderKooy 2000) and is primarily

harvested recreationally using hook-and-line fishing or gigging (Riechers 2008). The Gulf-wide

recreational harvest averaged over 400,000 kg per year for the past decade (National Marine

Fisheries Service, http://www.st.nmfs.noaa.gov/st1/recreational/ queries, accessed February 25

2015). However, long-term declines in population size were observed in Texas between 1975

and 2008 (Froeschke et al. 2011). Despite the economic value of this species and evidence for

overfishing, life-history information for Southern Flounder in the north-central GOM is limited.


2

An understanding of life history improves the ability to manage a population sustainably

(Adams 1980). Age-specific growth parameters and fecundity estimates are particularly 30

valuable for predicting future stock biomass and the effects of fishing mortality on a species in

stock assessment models. However, characteristics of growth and reproduction for Southern

Flounder in the north-central GOM have not been reported. Further research on the life history

of Southern Flounder is therefore beneficial for management of the stock.

The objective of this research is to describe the growth and reproduction of Southern 35

Flounder in the north-central GOM. A field sampling effort will be conducted using multiple

gear types to collect monthly fish samples. Size measurements and otoliths will be collected

from each fish to estimate maximum length, sex-specific length-at-age and weight-at-length

relationships, and to describe condition over time. Reproductive tissue will be processed using

histological techniques to estimate age- and length-at-maturity, spawning frequency, and 40

spawning duration. Fecundity will be estimated by counting oocytes from actively-spawning

females. The knowledge gained from this research will improve understanding of Southern

Flounder life history and the ability to manage the GOM stock.

45

50


3

Chapter I: Age and Growth of Southern Flounder in the north-central Gulf of Mexico

Introduction 55

Growth is a fundamental life-history characteristic that reflects the ecology and

evolutionary history of a species. An understanding of individual growth is valuable for studying

fish population dynamics and informing fisheries management (Denney et al. 2002).

Specifically, individual growth parameter estimates are used in some stock assessment models

to calculate mortality rates and predict future stock biomass (Pauly 1980). Growth of Southern 60

Flounder is variable within the Gulf of Mexico (GOM) and may be determined in part by

environmental conditions (Midway et al. 2015). The length-at-age and weight-at-length

relationships of Southern Flounder (Paralichthys lethostigma) have been reported in the GOM

but have not been described in Mississippi (Table 1 and 2). In this chapter, I will describe sex-

specific age and growth characteristics of Southern Flounder. 65

Counting otolith annuli is a widely-used method of age estimation in teleost fishes

(Campana 2001). Otolith annuli deposition varies due to changes in individual growth rates,

which are influenced by environmental factors (Campana and Neilson 1985). For example,

timing and rate of annuli deposition was related to water temperature in North Sea Cod (Gadus

morhua) otoliths using linear models (Pilling et al. 2007). Because annuli deposition is variable, 70

age validation should be used to confirm that annual increment formation occurs consistently

(Beamish and McFarlane 1983). Marginal increment analysis (MIA) is one age validation

technique in which the periodicity of annuli formation is determined based on the growth area

beyond the most recently-formed annulus (Hyndes 1992). MIA has been used as an age

validation technique for Southern Flounder otoliths with consistent annuli deposition reported 75

(Shepard 1986, Wenner et al. 1990). In the GOM stock, researchers in Texas and Louisiana

compared monthly mean marginal increment distances from Southern Flounder otolith cross-

sections to determine that annuli form between January and May (Stunz et al. 2000, Fischer

and Thompson 2004). However, I observed high variability in marginal increment widths during

the months of annuli formation in age-one Southern Flounder otoliths (Figure 1). This indicates 80

that there may be individual or inter-annual variability in timing of annuli deposition, which


4

complicates the assignment of birthdates for stock assessment analyses. In this research,

variability in otolith annuli deposition will be examined in relation to water temperature and

annuli formation will be validated with MIA to improve the precision of birthdate assignment in

Southern Flounder. 85

An understanding of the length-at-age relationship is valuable for estimating growth

parameters used in age-structured stock assessment models. Fishing can affect population-level

dynamics, such as changes in age-structure or mean length, by selective removal of fish. For

example, both average age and length decreased in Chinook Salmon (Oncorhynchus

tshawytscha) due to harvest of immature individuals between the 1920s and the 1970s (Ricker 90

1981). Because many fish stocks are managed based on minimum length limits (Allen and Pine

2000), it is critical to understand individual growth dynamics. The length-at-age relationship can

also be used to estimate ages from a length frequency distribution. The von Bertalanffy growth

function (VBGF) is a non-linear model that is widely used to describe the length-at-age

relationship (von Bertalanffy 1938). The longest mean length (L∞) for Southern Flounder was 95

estimated as 1461 mm standard length (SL) using the VBGF (Nall 1979). However, this estimate

is far greater than the longest observed length from any location in the GOM (Table 3). Other

approximations of L∞ for Southern Flounder from South Carolina and Texas (Wenner et al.

1990, Stunz et al. 2000) are based on age estimates validated by MIA (Table 1). Although the

VBGF has been used to model the length-at-age relationship in other locations, the length-at-100

age relationship for Southern Flounder in Mississippi has not been described (Table 1). The

VBGF is one candidate model that will be used to understand the length-at-age relationship for

Southern Flounder because its parameters can be easily compared to published parameter

values.

Description of the weight-at-length relationship is also useful for informing stock 105

assessments. Weight-at-length relationships are modeled using a power function characterized

by two parameters controlling the shape of the curve (Le Cren 1951). Although the weight-at-

length relationship often follows a cubic power function (Froese 2006), the parameter b is

species-specific and should be described in order to understand a species’ growth. Sex-specific

differences in the weight-at-length relationships have been documented for Southern Flounder 110


5

in Atlantic waters (Wenner et al. 1990) and in Texas (Stunz et al. 2000). The weight-at-length

parameter estimates vary within the GOM stocks, and Texas and Louisiana Southern Flounder

have generally greater b values than those in the eastern (Florida) Gulf (Table 2). However,

confidence intervals of parameter estimates were not reported so it is uncertain whether sex-

and location-specific differences are significant. The Southern Flounder weight-at-length 115

parameters and confidence intervals derived from samples collected in this study will be

compared to previously published weight-at-length mean parameter estimates to determine if

significant differences exist (Table 2). Modeling the weight-at-length relationship in Southern

Flounder from the north-central GOM will improve understanding of this species’ individual

growth. 120

Condition is a measure of weight relative to length that can be used to evaluate the

fitness of an individual (Froese 2006). Heavier fish at a given length are assumed to be in better

condition than lighter individuals (Le Cren 1951). Relative condition varies spatially and

temporally. For example, Atlantic Cod (Cadus morhua) stocks have different condition due to

mean regional water temperatures. Specifically, warmer-water Atlantic Cod stocks have 125

generally greater observed average condition than cold-water stocks (Rätz et al. 2003).

Seasonal changes in length-weight relationships were observed for the Comber (Serranus

cabrilla), indicative of changes in reproduction or feeding activity (Moutopoulos and Stergiou

2002). The use of condition as an indicator of growth and development has not been reported

for Southern Flounder. 130

Sexual dimorphism exists in Southern Flounder. Males have shorter life spans than

females, and maximum ages of four years for males and eight years for females have been

observed in both the Atlantic Ocean and GOM (Table 3). Total length (TL) is similar between

sexes during the first year post-hatch, but diverges during the second year of growth. For

example, age-zero females and males in Texas waters reached an average 253 mm and 243 mm 135

TL, respectively. However, age-one females grew to an average 374 mm TL compared to an

average 291 mm TL in age-one males (Stunz et al. 2000). Maximum average total length is

greater for females than for males (Table 1). Because of the differences observed between


6

male and female growth (Fischer and Thompson 2004), the use of sex-specific models will likely

result in more accurate descriptions of individual growth. 140

The description of a biological relationship involves uncertainty associated with model

structure, parameter estimates, and natural variation (Chatfield 1995). Model misspecification

can result from choosing only one model based on convenience or the frequency with which

the model is used to describe the relationship. Fitting multiple statistical models and choosing

the best model based on an objective criterion reduces model selection uncertainty and 145

improves accuracy of parameter estimates (Burnham and Anderson 2004, Katsanevakis 2006).

The three-parameter von Bertalanffy growth function is the most commonly used model for

describing the length-at-age relationship of Southern Flounder (Table 1). However, other

models for the length-at-age relationship do exist, including the two-parameter von Bertalanffy,

the Gompertz growth model, and the logistic model. Therefore, multiple models should be 150

evaluated to avoid model misspecification and to improve Southern Flounder growth

parameter estimates.

The objectives of this research are: (1) to determine factors influencing otolith growth

and to validate the formation of annuli in Southern Flounder otoliths using MIA methods; (2) to

quantify the sex-specific length-at-age relationships using multiple models for Southern 155

Flounder; (3) to quantify the sex-specific weight-at-length relationships of Southern Flounder;

(4) to compare results with previously-published growth parameter estimates; and (5) to

evaluate seasonal changes in condition of Southern Flounder.

Materials and Methods 160

Southern Flounder will be sampled in the north-central GOM using primarily hook and

line fishing and gigging. A target sample size of 30 fish will be collected each month, but the

objective will be to collect a sufficient sample of fish to represent the population dynamics.

Collection will occur at multiple locations primarily within Mississippi waters (Figure 2). Fish

caught in other Gulf-states and offshore will be included when possible. The gear type used for 165

collection will vary throughout the study with maximum effort used for each as appropriate.


7

Additional samples will also be obtained from local fishing tournaments or incidental catch

from research surveys. Fish will be immediately placed on ice following collection and

processed in the laboratory.

Each fish will be measured for TL (mm), standard length (SL, mm) and wet body weight 170

(g). The paired sagittal otoliths will be removed from each fish by exposing the brain cavity with

a transverse cut. Otoliths will be rinsed to remove membranous tissue and stored in a labeled

envelope. Following methods presented by VanderKooy (2009), the left sagittal otolith from

each fish will be processed for age determination. The otolith will be embedded in a mold with

Epoxicure resin and allowed to harden for a minimum of 24 hours. Once the resin is hardened, 175

the resin block will be marked to target the otolith core and several sections will be cut at a

thickness of about 0.4 mm with a Buehler diamond blade saw. Otolith sections will then be

polished to increase the visibility of annuli and mounted on slides with Crystalbond and Flo-

Texx mounting mediums.

Age estimates will be determined using annuli counts from otoliths and validated with 180

MIA. Southern Flounder scales were reported to have inconsistent markings (Palko 1984),

making otoliths the preferred structures for age estimation. Otolith-based age estimation is

recommended for this species (VanderKooy 2009), and therefore will be used in this research.

Annuli will be counted from images taken at 2x to 5x magnification under transmitted light with

a Stemi 2000-C microscope. Two independent readers will record an age estimate by counting 185

fully-formed annuli, and a third reader will reexamine otoliths in case of a discrepancy between

initial readings. If an agreement cannot be reached between readers, the age estimate will not

be used for analysis. The otolith radius, annuli width, and translucent area formed on the outer

edge margin will be measured from images using i-Solution Lite. Otoliths will be assigned a

margin code (one = 0% translucent area, two = 33%, three = 66%, four = 99%) based on the 190

percentage of outer margin width relative to the width of the last fully-formed annuli, where a

margin code of one indicates opaque ring formation (VanderKooy 2009). The proportions of

otoliths with each margin code will be examined as a function of capture month to determine

timing of annuli formation. Linear models will be used to determine the influence of year of

capture, month of capture, degree-days (the cumulative water temperature experienced over 195


8

time as a continuous variable), otolith radius, and annuli count on margin width. Inter-annual

variability will be assessed by including measurements from Southern Flounder otoliths

collected by the Mississippi Department of Marine Resources between 2007 and 2013. Water

temperature data will be obtained from the USGS National Water Information System Web

Interface for the Mississippi Sound. 200

The length-at-age relationships of Southern Flounder will be described using non-linear

models. A three-parameter VBGF will be used to estimate length-at-age:

Lt = 𝐿𝐿∞[1− 𝑒𝑒−𝑘𝑘(t−𝑡𝑡0)],

where t represents time (y), Lt is the length (mm) at a given time, 𝐿𝐿∞ is the mean hypothetical

maximum TL (mm), k is the growth coefficient (y-1), and 𝑡𝑡0 is a theoretical age at length of zero 205

(y). Other candidate models to describe length-at-age, including the two-parameter von

Bertalanffy growth function, Gompertz growth model, and logistic model, will also be fit to the

data. The two-parameter von Bertalanffy growth function is described by the following

equation:

Lt = 𝐿𝐿∞(1− 𝑒𝑒−𝑘𝑘t). 210

The Gompertz growth model (Gompertz 1825) is:

Lt = 𝐿𝐿∞ e(−1𝑘𝑘

𝑒𝑒−𝑘𝑘(t−1𝑘𝑘 𝑙𝑙𝑙𝑙𝑙𝑙)),

where λ is the theoretical initial relative growth rate at age zero (y-1) and k is the rate of

exponential decrease of the relative growth rate with age (y-1). The logistic length-at-age model

(Ricker 1975) is: 215

Lt = 𝐿𝐿∞(1 + 𝑒𝑒−𝑘𝑘(t−𝑡𝑡𝑖𝑖)),

where k is a relative growth rate parameter (y-1) and ti corresponds to the inflection point of the

sigmoidal curve. These candidate length-at-age models will be evaluated for goodness-of-fit

and parsimony using Akaike information criterion (AIC). Calculated AIC values will be compared

to determine the best-fit model, indicated by the lowest AIC value. 220

The weight-at-length relationship will be modeled using a power function:

W = 𝑎𝑎L𝑏𝑏,

where W represents wet weight (g), L represents TL (mm), a is a coefficient term and b is an

exponent describing change in length relative to weight. The 95% confidence intervals will be


9

calculated for each mean parameter estimate. The mean parameter estimates will be 225

compared to published mean parameter estimates using the 95% confidence intervals. Mean

parameter estimates that are within the confidence interval range of published values indicate

that no significant difference exists.

The relative condition of individuals and temporal changes in condition will be evaluated

using Fulton’s condition factor. Condition is calculated based on the relationship between 230

weight and length:

𝐾𝐾 = 100 WL𝑏𝑏

,

where K represents Fulton’s condition factor and b is an exponent parameter. Mean monthly

condition will be calculated with 95% confidence intervals. The condition values will be tested

for normality with a Shapiro-Wilk test and for homogeneity of variance with a Bartlett’s test. If 235

the condition data are not normally distributed, the data will be arcsine square root

transformed before analysis. If the condition data are normally distributed and meet the

homogeneity of variance assumption, a parametric one-way analysis of variance (ANOVA) test

will be carried out to determine if condition is significantly different between months. If the

assumptions of normality and homogeneity of variance are violated, a non-parametric Kruskal-240

Wallis ANOVA test will be used. A post-hoc Tukey’s test will be used to determine which

months’ condition values are significantly different. The significance level will be set to P < 0.05.

245

250


10

Chapter II: Reproductive Biology of Southern Flounder in the north-central Gulf of Mexico

Introduction

Reproduction is a fundamental aspect of a species’ life history. In fisheries science, an

understanding of reproductive biology is essential because reproduction greatly influences fish

population dynamics and the resilience of stocks (Beverton and Holt 1957). Length-at-maturity 255

and fecundity estimates are particularly valuable to inform stock assessment models of

spawning stock biomass and egg production (Lowerre-Barbieri et al. 2011a). Characteristics of

Southern Flounder reproduction, including length-at-maturity, spawning season timing,

spawning frequency, and fecundity estimates, have not been described in the north-central

Gulf of Mexico (GOM). This chapter will describe the reproductive biology of Southern Flounder 260

in the north-central GOM.

Timing of reproductive maturity is a life-history trait that affects population dynamics

(Lowerre-Barbieri et al. 2011b). Age- and length-at-maturity vary within populations, as well as

temporally and spatially (Trippel 1995). The description of accurate age- and length-based

maturity estimates would be beneficial for Southern Flounder management because changes in 265

maturity were shown to greatly affect biological reference points for this species (Midway and

Scharf 2012). Southern Flounder females reach greater lengths and have longer life spans than

males (Stokes 1977, Stunz et al. 2000, Fischer and Thompson 2004), which complicates

reported estimates of age- and length-at-maturity when both sexes are considered together.

For example, Southern Flounder spawned at an estimated two years of age in Texas waters 270

(Stokes 1977). Southern Flounder in Mississippi waters were reported mature at three years of

age (Etzold and Christmas 1979). However, in South Carolina, males were reported mature at

two to three years of age and females were reported mature at three to four years (Wenner et

al. 1990). Dimorphism was also reported in length-at-maturity, which ranges from about 230

mm to 310 mm total length (TL) for males and 320 mm to 380 mm TL for females in South 275

Carolina. These sex-specific differences in age- and length-at-maturity have not been reported

for Southern Flounder in the GOM. A 305 mm (12 inch) minimum size limit was established for

the Mississippi Southern Flounder fishery in 2002 (Mississippi Department of Marine Resources,


11

www.dmr.state.ms.us/recreational-fishing/recreational-catch-limits, accessed June 2015).

However, the length-at-first-maturity for female Southern Flounder reported by Wenner et al. 280

(1990) is greater than the minimum size limit, which suggests that some proportion of females

may be harvested before spawning. Improved understanding of the length-at-maturity

relationship for Southern Flounder would therefore be valuable knowledge to GOM state

management agencies.

Spawning seasonality can be determined by monitoring gonadal development 285

throughout the year. One measure used to describe temporal gonad development patterns is

the gonadosomatic index (GSI), which is a ratio of gonad weight relative to gonad-free body

weight. Gonad weight can be used as an indicator of reproductive maturation (Htun-Han 1978),

so the observation of monthly GSI values is used to describe annual reproductive development

and spawning preparedness. The use of GSI is advantageous because weight measurements are 290

easily obtained, but requires a continuous sampling effort for a minimum of one year to

accurately describe annual maturation patterns. In the GOM, the Southern Flounder spawning

season occurs from late autumn through early winter (Reagan and Wingo 1985, Ditty et al.

1988). Increasing gonadal development from August through November was indicated by GSI

values measured from Southern Flounder in Louisiana, suggesting that peak spawning activity 295

occurs in December (Shepard 1986). However, Shepard (1986) only recorded GSI from May to

December, which does not fully detail the annual trends in maturation for this species. Fischer

(1995) used both GSI and ovarian histology to determine that the Southern Flounder spawning

season lasts about 60 days from December through January in Louisiana. Further research on

Southern Flounder GSI would provide a better understanding of temporal gonadal development 300

and an estimate of the spawning season duration.

Histological analyses are more time- and cost-intensive than GSI measures, but provide

a precise characterization of gonad developmental phase and frequency of spawning events

(Lowerre-Barbieri et al. 2011a). Histology involves examination of gonadal tissue at the cellular-

level. The use of histology is preferable to macroscopic maturity-stage classification because 305

defining characteristics can be clearly identified (Hunter and Macewicz 1985). Spawning

frequency can be determined with histological analysis based on the presence of postovulatory


12

follicle complexes (POFs) or oocytes undergoing oocyte maturation (OM) from reproductively-

active ovaries (Hunter and Macewicz 1985). Batch spawning behavior (multiple spawning

events per individual in a season) can be identified by examining developmental stages 310

throughout the spawning season. Batch spawning throughout the spawning season is common

in flatfishes, including the North Sea Dab, Limanda limanda (Htun-Han 1978), Dover Sole,

Microstomus pacificus (Hunter et al. 1992), Tasmanian Greenback Flounder, Rhombosolea

tapirina (Barnett and Pankhust 1999), and Summer Flounder, Paralichthys dentatus, in the

Middle Atlantic Bight (Morse 1981). Batch spawning was observed in laboratory-reared 315

Southern Flounder and each female spawned more than three times throughout the spawning

season duration (Arnold et al. 1977). However, spawning behavior in a laboratory setting likely

does not reflect spawning behavior in a natural population. In Southern Flounder collected

from Louisiana waters, the presence of different oocyte stages throughout the spawning season

was indicative of batch spawning (Fischer 1995). To my knowledge, this is the only example of 320

batch spawning behavior documented in wild-caught Southern Flounder from the GOM

population. Examination of gonadal development with histology is needed to confirm batch-

spawning behavior in Southern Flounder.

Assessment of egg production requires an understanding of fecundity, which is a

measure of individuals’ potential reproductive capability each reproductive season. The 325

fecundity of individuals and the recruitment of their offspring to the population has a great

effect on population growth potential (Beverton and Holt 1957, Goodyear 1993). There are two

types of life-history strategies for fecundity in fishes defined by oocyte recruitment patterns

(Lowerre-Barbieri et al. 2011a). Determinate fecundity is characterized by all oocytes in a

reproductive cycle being recruited to secondary growth prior to the beginning of the spawning 330

period, and indeterminate fecundity is characterized by oocytes continuously entering

secondary growth throughout the spawning period (Hunter et al. 1992, Ganias et al. 2015).

Determinate fecundity has been observed in flatfish, such as the common Sole, Solea solea, in

the Atlantic Ocean (Witthames and Walker 1995), and the Dover Sole, Microstomus pacificus, in

the Pacific Ocean (Hunter et al. 1992). Most flatfish species occur in cold-water regions, and 335

winter-spawning fish tend to have a determinate fecundity strategy (Rijnsdorp and Witthames


13

2005, Lowerre-Barbieri et al. 2011b). The fecundity strategy of Southern Flounder, a warm-

water flatfish species, is currently undescribed and will be determined through this research.

Estimation of individual fecundity is necessary for informing stock assessment models.

For example, egg-per-recruit models are used to evaluate changes in egg production in 340

response to fishing (Prager et al. 1987), and accurate estimates of fecundity improve the

accuracy of these models. Fecundity estimates are commonly obtained using the relationships

between ovary weight or volume to the density of oocytes in the ovary (Murua et al. 2003).

Fecundity varies with body size, and larger fish produce more eggs relative to body mass than

smaller fish (Buckley et al. 1991). However, variability in body size and individual spawning 345

capabilities was not reported in previous Southern Flounder fecundity estimates. In laboratory-

spawned Southern Flounder, 13 spawning events from three large females (each weighing

more than 2,000 g) produced about 120,000 eggs total (Arnold et al. 1977). Another laboratory

experiment showed that each spawning event yielded about 5,000 fertilized eggs in hormone-

induced spawning Southern Flounder females (Lasswell et al. 1978). The only known fecundity 350

estimate from Southern Flounder collected in the GOM is a mean batch fecundity of 44,000 to

62,000 ova per batch (Fischer 1995). Better classification and estimation of Southern Flounder

fecundity will be useful to inform stock assessment for this species.

The objectives of this research are: (1) to describe sex-specific age- and length-at-

maturity; (2) to determine the approximate spawning season using monthly GSI values and 355

histology; (3) to describe characteristics of gonadal development in males and females and to

estimate spawning frequency using histological analyses; (4) to determine fecundity type; and

(5) to estimate batch fecundity in Southern Flounder.

Materials and Methods 360

Southern Flounder will be sampled in the north-central GOM using primarily hook and

line fishing and gigging. A target sample size of 30 fish will be collected each month, but the

objective will be to collect a sufficient sample of fish to represent the population dynamics and

all reproductive phases. Collection will occur at multiple locations primarily within Mississippi


14

waters (Figure 2). Fish caught in other Gulf states and offshore will also be included when 365

possible. Gear used for collection will vary throughout the study with maximum effort used for

each technique as necessary. Additional samples will also be obtained from local fishing

tournaments or incidental catch from research surveys. Fish will be immediately placed on ice

following collection and processed in the laboratory within 24 hours.

Each specimen will be measured for TL (mm), standard length (SL, mm), and total weight 370

(TW, g). The sex of each fish will be determined by macroscopic examination of gonads. Whole

gonads will be removed and weighed to the nearest 0.01 g. A cross section no larger than 1 cm3

from the middle of one gonad will be placed into a histology cassette and fixed in 10% neutral

buffered formalin for at least one week. A 1:20 ratio of tissue volume to formalin volume will be

maintained to ensure adequate penetration and preservation of the gonadal tissue. Any gonad 375

tissue samples that cannot be weighed fresh will be preserved whole in 10% neutral buffered

formalin. A regression analysis will be used to examine the relationship between fresh gonad

weight and gonad weight as a function of time in solution, and a conversion factor will be used

to account for any shrinkage in sample weight over time. Tissue will be examined from the

anterior, middle, and posterior sections of both the left and right gonad in three spawning 380

capable females to determine if oocyte development is homogenous throughout the gonad.

Mean TL at 50% maturity (MTL) will be estimated using a 2-parameter logistic model:

𝑀𝑀𝑇𝑇𝑇𝑇 = 11+𝑒𝑒−𝑟𝑟(TL−𝑇𝑇𝑇𝑇50),

where r is the instantaneous growth rate and TL50 is the TL at 50% maturity. Maturity will be

coded as immature (0) or mature (1) and the 95% confidence interval of the MTL estimate 385

reported. Age-at-maturity will be back-calculated using the length-at-age relationship of

Southern Flounder. The gonadosomatic indices (GSI) will be calculated for each sex using the

following equation:

GSI = � GWGFBW

� ∙ 100,

where GW is the gonad weight (g) and GFBW is the gonad-free body weight of the fish (g). A 390

linear regression will be performed to determine if there is a relationship between GSI and


15

GFBW, with no relationship meaning that GSI is an indicator of spawning preparedness (Jons

and Miranda 1997). The GSI values for both females and males will be tested for normality with

a Shapiro-Wilk test and for homogeneity of variance with a Bartlett’s test. If the GSI data are

not normally distributed, the proportional data will be arcsine square root transformed before 395

analysis. If the GSI data are normally distributed and meet the homogeneity of variance

assumption, a parametric one-way analysis of variance (ANOVA) test will be carried out for GSI

differences among months by sex. If the assumptions of normality and homogeneity of variance

are violated, a non-parametric Kruskal-Wallis ANOVA test will be used. A post-hoc Tukey’s test

will be used to determine which months’ GSI values are significantly different. The significance 400

level for all tests will be set to P < 0.05.

Preparation of gonads for analysis will follow standard histology procedures, which

include rinsing and dehydrating the preserved gonad tissue, embedding in paraffin, sectioning

into thin slices, differentially staining tissue, and mounting sections to slides for examination. To

prepare for dehydration of the gonad samples and embedding in paraffin, the sample cassettes 405

will be rinsed overnight with low-flowing tap water. After rinsing, samples will be placed in 60%

ethanol for two hours, drained, placed in 70% ethanol for two hours, drained, and replaced in

70% ethanol for a minimum of two hours. Next, the preserved gonad samples will be

dehydrated using various dilutions of ethanol up to 100%, cleared using Shandon Xylene

substitute, and impregnated with Paraplast Plus in a Shandon Excelsior Tissue Processor (Table 410

4). All steps will be performed under vacuum to maximize the penetration of reagents into the

tissues. Tissues will be embedded within one hour of cycle completion using a Shandon

Histocentre 2 Embedding Center. To embed tissues, a small amount of Paraplast will be placed

in the bottom of a stainless-steel mold and the gonad tissue will be positioned in a manner to

obtain the best cross-section. The tissue will be secured by briefly cooling the paraffin and the 415

cassette base placed on top of the mold. The mold will then be completely filled with Paraplast.

The cooled Paraplast and tissue block will be removed from the mold and the excess paraffin

trimmed off. To prepare for tissue sectioning, an S/P Brand Tissue Flotation Bath will be filled

with distilled water. One cap-full of Surgipath STAY ON, a tissue section adhesive, will be added

and the bath will be heated to 37-42°C. Prior to sectioning, the blocks will be placed on ice. 420


16

Blocks will be sectioned at a thickness of 4 µm using an AO Rotary Microtome with a disposable

Accu-Edge Low Profile Microtome Blade. Sections will be placed in the water bath and the best

two from each specimen will be floated onto a slide. Each slide will be labeled and placed on a

slide warmer for a minimum of two hours to completely dry. The staining process will include

removing the paraffin, rehydrating the sample, staining the various tissue components, and 425

then dehydrating the section. Slide baths will be created in a sequence with varying solutions

and soak times (Table 5). Slides will be stained following a regressive method of hematoxylin

staining (Luna 1968) using Hematoxylin 2 and counterstained with Eosin Y (Richard-Allan

Scientific). Solution baths will be rotated or discarded and replaced as needed. Slides will be

cover-slipped using a mounting medium (Richard-Allan Scientific) and allowed to dry 430

completely. Stained slides will be evaluated microscopically to define developmental phases for

both males and females. Each sample will be sorted in one of five reproductive phases

(immature, developing, spawning capable, regressing, and regenerating), including the

subcategories of early developing and actively spawning (Table 6 & 7), based on the

classification scheme presented by Brown-Peterson et al. (2011). This analysis will provide a 435

definitive classification of reproductive phase for each individual. A chi-square contingency

table will be used to determine if the frequency distributions of reproductive phases are

different among months.

The reproductive development of males will be examined using histological classification

of samples. Males will be classified sexually mature when primary spermatocytes are observed 440

(Brown-Peterson et al. 2011). The spermatogenic maturity index (SMI) will be used in

combination with GSI to describe the gonadal development of males (Tomkiewicz et al. 2011).

The SMI method involves estimation of the area fractions of various tissue categories

characterized by progressive gamete development stages in histological sections of the testes.

The entire testis tissue section will be imaged at 10x magnification with a Nikon compound 445

microscope and three areas will be randomly selected from each slide for examination using an

Image J software point grid. The number of squares of coverage for each testis tissue type

(testicular somatic cells, spermatogonia, spermatocytes, spermatids, spermatozoa) and atresia


17

will be counted and divided by the total number of counts, resulting in a percentage of area

covered by each. The SMI will be calculated using the following equation: 450

SMI = 0.0FTs + 0.4FSg + 0.6FSc + 0.08FSt + 1.0FSz + 0.2Fatresia,

where F is the frequency of occurrence for the indicated cell type (Ts = testicular somatic cells,

Sg = spermatogonia, Sc = spermatocytes, St = spermatids, Sz = spermatozoa, and atresia). The

index weighs the volume fractions of the different tissues (somatic cells and germ cell stages)

and describes testis development on a scale of 0 to 1. 455

The monthly proportions of female samples in each ovarian phase will be used in

combination with GSI data to determine the spawning season timing. Females will be classified

sexually mature when fish enter the developing phase and cortical alveoli oocytes are observed

(Brown-Peterson et al. 1988, Brown-Peterson et al. 2011, Lowerre-Barbieri 2011b). The percent

coverage of each oocyte stage present in female ovarian sections will be determined using 460

images taken at 4x magnification with a Nikon compound microscope. The entire tissue section

will be imaged and three areas will be randomly selected from each slide for oocyte

examination using an Image J software point grid. All oocytes, postovulatory follicle complexes

(POF), and atretic oocytes will be counted. The number of grids of coverage will be counted and

divided by the total number of grid points, resulting in a percentage of total area for each 465

oocyte, POF, and atresia stage (modified from Tomkiewicz et al. 2011). A qualitative descriptive

analysis of the oocyte stage frequency distributions will be used to examine any changes in the

most-frequently occurring oocyte stage among months. The oocyte stage frequency

distributions will be tested for normality using a Shapiro-Wilk test to determine if it is

appropriate to calculate error within oocyte stages. 470

Histological data will be used to determine spawning frequency of Southern Flounder

females. Two methods will be used to determine the spawning frequency. One method uses

samples from fish undergoing oocyte maturation (OM) whereas the other method uses samples

with POFs less than 24 hours old (Hunter and Macewicz 1985). The OM method is based on the

observation of fish that are going into the final stages of oocyte maturation. The POF method is 475


18

based on the presence of a thinly-stretched and folded follicle that remains behind after the

ovulated egg is released. All specimens that are categorized as spawning capable or actively

spawning will be counted for each month. The sum of the total spawning capable and actively

spawning fish within a month will then be divided by the number of specimens within that

month that contained 0 to 24 hour POFs or OM. The result gives an estimate of the number of 480

days between spawns for each month. Annual spawning frequency will be calculated as the

sum of the spawning capable and actively spawning fish within the spawning season divided by

the total number of fish that contained 0-24 hour POFs or OM in a year. The total number of

potential spawns per year will be calculated by dividing the total number of days in the

spawning season by the annual spawning frequency. Differences in spawning frequency among 485

months will be tested with a chi-square test.

An oocyte size-frequency analysis will be used to determine whether Southern Flounder

have a determinate or an indeterminate fecundity strategy. Oocytes from spawning capable

females collected early and late in the spawning season will be sorted into 50 µm size bins. The

oocyte size-frequency distributions will be compared between early- and late-spawning 490

individuals using a Kolmogorov-Smirnov test for differences between the distributions. A

determinate fecundity strategy will be indicated by a low frequency of smaller oocytes and a

high frequency of larger oocytes late in the spawning season. An indeterminate fecundity

strategy will be indicated by the presence of smaller oocytes late in the spawning season.

Samples classified as actively spawning will be used to estimate batch fecundity, relative 495

batch fecundity, and total annual fecundity. If an ovary is identified as actively spawning, a

subsample (~5 g) of the gonad will be removed, weighed (0.01 g), placed in a labeled jar, sliced

into smaller sections, and preserved in modified Gilson’s fluid (Table 8) for a minimum of three

months (Bagenal 1966). All actively-spawning ovarian samples collected after January 2016 will

be preserved in 10% neutral buffered formalin due to limited time. Gilson’s fluid is used to 500

harden the outer most layer of the oocyte and separate the oocyte from the ovarian tissue.

Repeated shaking of the jar over the duration of storage helps break apart the ovarian tissues

and aides in releasing and suspending the oocytes, thus allowing better fluid penetration and

preservation. The volumetric method for estimating fecundity will be used in this study


19

(Bagenal and Braum 1971). Samples will be rinsed overnight in running water and oocytes will 505

be teased from the tissue and placed in 100 ml of water. While the sample is being stirred, six

aliquots of 1-2 ml each will be sub-sampled with replacement. An oocyte size frequency

distribution will be developed for a spawning capable fish and an actively spawning fish and the

two distributions will be compared. A distinct pattern of large oocyte frequency will be evident

in actively spawning fish, indicating the size at which an oocyte undergoes maturation and thus 510

the size at which oocytes need to be counted for fecundity analysis. The same analysis will be

done for samples preserved in modified Gilson’s fluid and in 10% neutral buffered formalin to

account for differences in preservation methods. Both batch fecundity (number of eggs/female)

and relative batch fecundity (number of eggs/g ovary free body weight) will be calculated and

reported as a mean ± standard error (SE) of the mean fecundity estimate. Batch fecundity (BF) 515

will be estimated using the following equation:

BF = N � DLDLS

� � GWPGW

�,

where N is the number of oocytes undergoing maturation, DL is dilution water volume (ml), DLS

is the dilution water subsample volume (ml), GW is gonad weight (g), and PGW is the portion of

the whole gonad used (g). Relative batch fecundity (RBF) will be estimated using the following 520

equation:

RBF = � BFOFBW

�,

where BF is the batch fecundity (number of eggs) and OFBW is the ovary-free body weight (g).

Total annual fecundity will be estimated using the following equation:

Total Annual Fecundity = # spawning events ∙ (BF), 525

where the total number of potential spawning events per year is defined as the total number of

days in the spawning season divided by the spawning frequency, and BF is the batch fecundity

(number of eggs). Linear regressions will be used to determine whether relationships exist

between BF and TL, GFBW, or age. The data will be tested for normality with a Shapiro-Wilk test

and for homogeneity of variance with a Bartlett’s test to determine if the use of a linear model 530

is appropriate.


20

Literature Cited

Adams, P. 1980. Life history patterns in marine fishes and their consequences for fisheries management. Fishery Bulletin 78(1): 1-12. 535 Allen, M. S., and W. E. Pine III. 2000. Detecting fish population response to a minimum length limit: effects of variable recruitment and duration of evaluation. North American Journal of Fisheries Management 20: 672-682. 540 Anderson, J. D., and W. J. Karel. 2012. Population genetics of southern flounder with implications for management. North American Journal of Fisheries Management 32: 656-662. Arnold, C. R., W. H. Bailey, T. D. Williams, A. Johnson, and J. L. Lasswell. 1977. Laboratory spawning and larval rearing of red drum and southern flounder. Texas Parks and Wildlife 545 Department Inland Fisheries Department, Austin, TX. pp 437-440. Bagenal, T.B. 1966. The ecological and geographical aspects of fecundity of the plaice. Journal of the Marine Biological Association of the United Kingdom 46: 161-168. 550 Bagenal, T.B. and E. Braum. 1971. Eggs and early life history. In: W.E. Ricker, ed. Methods for Assessment of Fish Production in Fresh Waters. International Biological Program Handbook 3, 2nd ed. Blackwell Science Publishing, Oxford, England. pp 159-181. Barnett, C. W. and N. Pankhurst. 1999. Reproductive biology and endocrinology of greenback 555 flounder Rhombosolea tapirina (Günther 1862). Marine and Freshwater Research 50(1): 35-42. Beamish, R. and G. McFarlane. 2000. Reevaluation of the interpretation of annuli from otoliths of a long-lived fish, Anoplopoma fimbria. Fisheries Research 46(1): 105-111. 560 Beverton, R. J. and S. J. Holt. 1957. On the dynamics of exploited fish populations. Fishery Investigations, Ser. 2 Vol. 19. 533 p. Blandon, I. R., R. Ward, T. L. King, W. J. Karel, and J. P. Monaghan Jr. 2001. Preliminary genetic population structure of southern flounder, Paralichthys lethostigma, along the Atlantic coast 565 and Gulf of Mexico. Fishery Bulletin 99: 671-678. Brown-Peterson, N., P. Thomas, and C. R. Arnold. 1988. Reproductive biology of the spotted seatrout, Cynoscion nebulosus, in south Texas. Fishery Bulletin 86(2): 373-388. 570 Brown-Peterson, N. J., D. M. Wyanski, F. Saborido-Rey, B. J. Macewicz and S. K. Lowerre-Barbieri. 2011. A standardized terminology for describing reproductive development in fishes. Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Sciences 3(1): 52-70.


21

Buckley, L., A. Smigielski, T. Halavik, E. Caldarone, B. Burns and G. Laurence. 1991. Winter 575 flounder Pseudopleuronectes americanus reproductive success. II. Effects of spawning time and female size on size, composition and viability of eggs and larvae. Marine Ecology Progress Series 74(2): 125-135. Burnham, K. P. and D. R. Anderson. 2004. Multimodel inference understanding AIC and BIC in 580 model selection. Sociological Methods & Research 33(2): 261-304. Campana, S. 2001. Accuracy, precision and quality control in age determination, including a review of the use and abuse of age validation methods. Journal of Fish Biology 59(2): 197-242. 585 Campana, S. E. and J. D. Neilson. 1985. Microstructure of fish otoliths. Canadian Journal of Fisheries and Aquatic Sciences 42(5): 1014-1032. Chatfield, C. 1995. Model uncertainty, data mining and statistical inference. Journal of the Royal Statistical Society 158(3): 419-466. 590 Denney, N. H., S. Jennings, and J. D. Reynolds. 2002. Life-history correlates of maximum population growth rates in marine fishes. Proceedings of the Royal Society of London. Series B: Biological Sciences 269(1506): 2229-2237. 595 Deubler Jr, E. E. 1960. Salinity as a factor in the control of growth and survival of postlarvae of the southern flounder, Paralichthys lethostigma. Bulletin of Marine Science 10(3): 338-345. Ditty, J. G., G. G. Zieske and R. F. Shaw. 1988. Seasonality and depth distribution of larval fishes in the northern Gulf of Mexico above latitude 26 degree 00'N. Fishery Bulletin 86(4): 811-823. 600 Etzold, D. and J. Christmas. 1979. A Mississippi marine finfish management plan. Mississippi-Alabama Sea Grant Consortium MASGP-78-046. Ocean Springs, MS. 36 p. Farmer, T. M., D. R. DeVries, R. A. Wright and J. E. Gagnon. 2013. Using seasonal variation in 605 otolith microchemical composition to indicate Largemouth Bass and Southern Flounder residency patterns across an estuarine salinity gradient. Transactions of the American Fisheries Society 142(5): 1415-1429. Fischer, A. J. 1995. The life history of southern flounder (Paralichthys lethostigma) in Louisiana 610 waters. Unpublished MS Thesis, Louisiana State University, Baton Rouge, LA. 68 p. Fischer, A. J. and B. A. Thompson. 2004. The age and growth of southern flounder, Paralichthys lethostigma, from Louisiana estuarine and offshore waters. Bulletin of Marine Science 75(1): 63-77. 615


22

Froeschke, B. F., B. Sterba-Boatwright, and G. W. Stunz. 2011. Assessing southern flounder (Paralichthys lethostigma) long-term population trends in the northern Gulf of Mexico using time series analyses. Fisheries Research 108: 291–298. 620 Froese, R. 2006. Cube law, condition factor and weight–length relationships: history, meta-analysis and recommendations. Journal of Applied Ichthyology 22(4): 241-253. Ganias, K., S. K. Lowerre-Barbieri, and W. Cooper. 2015. Understanding the determinate-indeterminate fecundity dichotomy in fish populations using a temperature dependent oocyte 625 growth model. Journal of Sea Research 96: 1-10. Gompertz, B. 1825. On the nature of the function expressive of the law of human mortality and on a new mode of determining the value of life contingencies. Philosophical Transactions of the Royal Society 115: 515-585. 630 Goodyear, C. P. 1993. Spawning stock biomass per recruit in fisheries management: foundation and current use. In: S. J. Smith, J. J. Hunt, and D. Rivard. Risk evaluation and biological reference points for fisheries management. Canadian Special Publication of Fisheries and Aquatic Sciences 120: 67-82. 635 Hensley, D. A. and E. H. Ahlstrom. 1984. Pleuronectiformes: Relationships. In: H. Moser, W. Richards, D. Cohen, M. Fahay, A. Kendall, and S. Richardson, eds. Ontogeny and systematics of fishes. American Society of Ichthyologists and Herpetologists. Allen Press, Lawrence, KS. pp 670–687. 640 Htun-Han, M. 1978. The reproductive biology of the dab Limanda limanda (L.) in the North Sea: seasonal changes in the ovary. Journal of Fish Biology 13(3): 351-359. Hunter, J. and B. Macewicz. 1985. Measurement of spawning frequency in multiple spawning 645 fishes. NOAA Technical Report NMFS 36. pp 79-94. Hunter, J. R., B. J. Macewicz, N. C. Lo, and C. A. Kimbrell. 1992. Fecundity, spawning, and maturity of female Dover sole Microstomus pacificus, with an evaluation of assumptions and precision. Fishery Bulletin 90: 101-128. 650 Hyndes, G., N. R. Loneragan, and I. C. Potter. 1992. Influence of sectioning otoliths on marginal increment trends and age and growth estimates for the flathead Platycephalus speculator. Fishery Bulletin 90(2): 276-284. 655 Jons, G. D., and L. E. Miranda. 1997. Ovarian weight as an index of fecundity, maturity, and spawning periodicity. Journal of Fish Biology 50: 150-156. Katsanevakis, S. 2006. Modelling fish growth: model selection, multi-model inference and model selection uncertainty. Fisheries Research 81(2): 229-235. 660


23

Lasswell, J. L., B. W. Lyons, and W. H. Bailey. 1978. Hormone-induced spawning of southern flounder. The Progressive Fish-Culturist 40(4): 154-154. Le Cren, E. 1951. The length-weight relationship and seasonal cycle in gonad weight and 665 condition in the perch (Perca fluviatilis). The Journal of Animal Ecology 20(2): 201-219. Lowe, M. R., D. R. DeVries, R. A. Wright, S. A. Ludsin and B. J. Fryer. 2011. Otolith microchemistry reveals substantial use of freshwater by southern flounder in the Northern Gulf of Mexico. Estuaries and Coasts 34(3): 630-639. 670 Lowerre-Barbieri, S. K., N. J. Brown-Peterson, H. Murua, J. Tomkiewicz, D. M. Wyanski and F. Saborido-Rey. 2011a. Emerging issues and methodological advances in fisheries reproductive biology. Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Sciences 3(1): 32-51. 675 Lowerre-Barbieri, S. K., K. Ganias, F. Saborido-Rey, H. Murua, and J. R. Hunter. 2011b. Reproductive timing in marine fishes: variability, temporal scales, and methods. Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Sciences 3(1): 71-91. 680 Luna, L. G. 1968. Manual of Histological Staining Methods of the Armed Forces Institute of Pathology, Third Edition, McGraw-Hill Inc., Washington D.C. 46 p. Midway, S. R., and F. S. Scharf. 2012. Histological analysis reveals larger size at maturity for southern flounder with implications for biological reference points. Marine and Coastal 685 Fisheries: Dynamics, Management, and Ecosystem Science 4: 628-638. Midway, S. R., T. Wagner, S. A. Arnott, P. Biondo, F. Martinez-Andrade, and T. F. Wadsworth. 2015. Spatial and temporal variability in growth of southern flounder (Paralichthys lethostigma). Fisheries Research 167: 323-332. 690 Mississippi Department of Marine Resources, 2015. www.dmr.state.ms.us/recreational-fishing/recreational-catch-limits/ (accessed on 06/18/2015). Morse, W. 1981. Reproduction of the summer flounder, Paralichthys dentatus (L.). Journal of 695 Fish Biology 19(2): 189-203. Moutopoulos, D. and K. Stergiou. 2002. Length–weight and length–length relationships of fish species from the Aegean Sea (Greece). Journal of Applied Ichthyology 18(3): 200-203. 700 Murua, H., G. Kraus, F. Saborido-Rey, P. R. Witthames, A. Thorsen, and S. Junquera. 2003. Procedures to estimate fecundity of marine fish species in relation to their reproductive strategy. Journal of Northwest Atlantic Fishery Science 33: 33-54.


24

Nall, L. E. 1979. Age and growth of the southern flounder, Paralichthys lethostigma, in the 705 northern Gulf of Mexico with notes on Paralichthys albigutta. Unpublished MS Thesis, Florida State University, Tallahassee, FL. 58 p. National Marine Fisheries Service, 2014. http://www.st.nmfs.noaa.gov/st1/recreational/queries (accessed on 02/20/2015). 710 Nims, M. K. and B. D. Walther. 2014. Contingents of southern flounder from subtropical estuaries revealed by otolith chemistry. Transactions of the American Fisheries Society 143(3): 721-731. 715 Palko, B. J. 1984. An evaluation of hard parts for age determination of pompano (Trachinotus carolinus), ladyfish (Elops saurus), crevalle jack (Caranx hippos), gulf flounder (Paralichthys albigutta), and southern flounder (Paralichthys lethostigma). NOAA Technical Memorandum NMFS 132. pp 1-11. 720 Pauly, D. 1980. On the interrelationships between natural mortality, growth parameters, and mean environmental temperature in 175 fish stocks. Journal du Conseil 39(2): 175-192. Pilling, G. M., R. S. Millner, M. W. Easey, D. L. Maxwell, and A. N. Tidd. 2007. Phenology and North Sea cod Gadus morhua L.: has climate change affected otolith annulus formation and 725 growth? Journal of Fish Biology 70: 584-599. Prager, M. H., J. F. O'Brien, and S. B. Saila. 1987. Using lifetime fecundity to compare management strategies: a case history for striped bass. North American Journal of Fisheries Management 7(3): 403-409. 730 Rätz, H. J. and J. Lloret. 2003. Variation in fish condition between Atlantic cod (Gadus morhua) stocks, the effect on their productivity and management implications. Fisheries Research 60(2): 369-380. 735 Reagan Jr, R. E. and W. M. Wingo. 1985. Species Profiles: Life Histories and Environmental Requirements of Coastal Fishes and Invertebrates (Gulf of Mexico). Biological Report 82(11.30) TR EL-82-4. Ricker, W. E. 1981. Changes in the average size and average age of Pacific salmon. Canadian 740 Journal of Fisheries and Aquatic Sciences 38(12): 1636-1656. Ricker, W. E. 1975. Computation and interpretation of biological sciences of fish populations. Bulletin of the Fisheries Research Board of Canada 191: 1-382. 745


25

Riechers, R. 2008. Regulations Committee Southern Flounder Update. Texas Parks and Wildlife Department Regulation Committee, Houston, TX. http://www.tpwd.state.tx.us/business/feedback/meetings/2009/1106/transcripts/regulations_750 committee/index.phtml (accessed on 06/29/2015). Rijnsdorp, A. D., and P. R. Witthames. 2005. Ecology of reproduction. In: Gibson, R. N. Flatfishes: biology and exploitation. Fish and Aquatic Resources Series 9. Blackwell Publishing, Oxford, UK. pp 68-93. 755 Shepard, J. 1986. Spawning peak of southern flounder, Paralichthys lethostigma. Louisiana Department of Wildlife Fisheries Technical Bulletin 40: 77-79. Stokes, G. M. 1977. Life history studies of southern flounder (Paralichthys lethostigma) and Gulf 760 Flounder (P. albigutta) in the Aransas Bay area of Texas. Technical Series 25, Texas Parks and Wildlife Department, Austin, TX. 37 p. Stunz, G. W., T. L. Linton and R. L. Colura. 2000. Age and growth of southern flounder in Texas waters, with emphasis on Matagorda Bay. Transactions of the American Fisheries Society 765 129(1): 119-125. Tomkiewicz, J., T. M. N. Kofoed, and J. S. Pedersen. 2011. Assessment of testis development during induced spermatogenesis in the European eel Anguilla anguilla. Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science 3: 106-118. 770 Trippel, E. A. 1995. Age at maturity as a stress indicator in fisheries. Bioscience 759-771. VanderKooy, S. J. 2009. A practical handbook for determining the ages of Gulf of Mexico fishes Second Edition. Gulf States Marine Fisheries Commission, Ocean Springs, MS. 157 p. 775 VanderKooy, S. J. 2000. The flounder fishery of the Gulf of Mexico, United States: a regional management plan. No. 83. Gulf States Marine Fisheries Commission, Ocean Springs, MS. 323 p. von Bertalanffy, L. 1938. A quantitative theory of organic growth (inquiries on growth laws. 780 II). Human Biology 10(2): 181-213. Welch, D. and R. Foucher. 1988. A maximum likelihood methodology for estimating length-at-maturity with application to Pacific cod (Gadus macrocephalus) population dynamics. Canadian Journal of Fisheries and Aquatic Sciences 45(2): 333-343. 785 Wenner, C. A., W. A. Roumillat, J. E. Moran Jr., M. B. Maddox, L. B. Daniel III, and J. W. Smith. 1990. Investigations on the life history and population dynamics of marine recreational fishes in South Carolina. Marine Resources Research Institute, South Carolina Wildlife and Marine Resources Department, Columbia, SC. 35 p. 790


26

Witthames, P. R., and M. G. Walker. 1995. The geographical variation in the potential annual fecundity of Dover sole Solea solea (L.) from European shelf waters during 1991. Netherlands Journal of Sea Research 34(1): 45-58.


27

Figure 1: Boxplot of marginal increment widths relative to the width of the last fully-formed annuli by month for age-one Southern 795

Flounder otoliths. Measurements were taken from Southern Flounder otoliths collected by the Mississippi Department of Marine

Resources from 2007 to 2013. Dark bands indicate the median marginal increment proportion, shaded boxes indicate the first and

third quartiles, dotted lines indicate the 95% confidence intervals, and open circles indicate outliers in the data.


28

Figure 2: Locations within the Mississippi Sound where Southern Flounder will be targeted for collection with hook and line fishing, 800

gigging, gill netting, seining, and trawling from September 2014 through February 2016. Samples from other sites, including offshore

Texas and Louisiana waters, will be collected as available.


29

Table 1: Summary of reported von Bertalanffy length-at-age mean model parameters for Southern Flounder collected in Atlantic and

Gulf of Mexico waters. For the two-parameter model, Lt = 𝐿𝐿∞(1 − 𝑒𝑒−𝑘𝑘t), 𝐿𝐿∞ is the mean hypothetical maximum TL (mm), k is the 805

growth coefficient (y-1), and 𝑡𝑡0 is a theoretical age-at-length zero used in the three-parameter model Lt = 𝐿𝐿∞(1 − 𝑒𝑒−𝑘𝑘(t−𝑡𝑡0)). 95%

confidence intervals are reported for each parameter in parentheses if available.

Citation Location Sex L∞ (mm) k t0 n = Nall 1979 Florida combined 1461 0.03 1.86 153 Frick 1988 Florida/Alabama female 540 (485 to 595) 0.47 (0.34 to 0.60) 0.10 (0.01 to 0.19) 139 Wenner et al. 1990 South Carolina female 759 (658 to 860) 0.23 (0.18 to 0.29) -0.57 (-0.71 to -0.43) 708

male 518 (360 to 677) 0.25 (0.10 to 0.39) -1.07 (-1.48 to -0.65) 573 Matlock 1992 Texas combined 848 (816 to 880) 0.23 (0.21 to 0.25) 21 Stunz et al. 2000 Texas female 660 (205 to 1116) 0.21 (0.00 to 0.48) -1.32 (-2.35 to -0.28) 718

male 309 (239 to 378) 0.70 (-0.06 to 1.46) -0.42 (-1.46 to 0.65) 144 Fischer and Thompson 2004 Louisiana female 556 0.51 -0.62 1128

male 332 1.03 -0.25 137

810


30

Table 2: Summary of reported weight-at-length mean model parameters for Southern Flounder collected in Atlantic and Gulf of 815

Mexico waters. In the weight-at-length relationship W = 𝑎𝑎L𝑏𝑏, a is the coefficient term and b is an exponent term describing the

change in length relative to weight.

Citation Location Sex a b n = Nall 1979 Florida combined 0.000012 3.10 175 Wenner et al. 1990 South Carolina female 0.000005 3.15 926

male 0.000004 3.17 675 Stunz et al. 2000 Texas female 0.000002 3.30 206

male 0.000002 3.31 33 Fischer and Thompson 2004 Louisiana combined 0.000003 3.21 1236

820

825


31

Table 3: Summary of maximum age and range of lengths for Southern Flounder from studies in the Atlantic and Gulf of Mexico

waters.

Citation Location Sex Max Age (y) n = Length Range (mm) Stokes 1977 Texas female 5 162 170 to 620

male 3 102 170 to 320 Nall 1979 Florida combined 10 153 85 to 585 Frick 1988 Florida/Alabama female 5 139 156 to 623

male 2 32 156 to 340 Wenner et al. 1990 South Carolina female 7 780 232 to 703

male 3 573 188 to 476 Stunz et al. 2000 Texas combined 4 892 102 to 633 Fischer and Thompson 2004 Louisiana female 8 1202 189 to 764

male 4 146 127 to 414 830

835


32

Table 4: Processing sequence for dehydration of gonad tissues. Each step in the processing

sequence is one hour in duration.

Step Solution 1 2

70% EtOH 80% EtOH

3 4 5 6 7 8 9

10 11 12

95% EtOH 95% EtOH 100% EtOH 100% EtOH 100% EtOH Xylene Substitute Xylene Substitute Xylene Substitute Paraplast Plus Paraplast Plus

840

845

850


33

Table 5: Outline of the tissue staining process, which involves dehydrating the sample,

differentially staining each tissue component, and rehydrating the sample. 855

Step Solution Duration 1 Xylene Sub. 3 min. 2 Xylene Sub. 3 min. 3 Xylene Sub. 3 min. 4 100% EtOH 10 dips 5 100% EtOH 10 dips 6 95% EtOH 10 dips 7 95% EtOH 10 dips 8 80% EtOH 10 dips 9 80% EtOH 10 dips

10 50% EtOH 10 dips 11 Distilled Water 1 min. 12 Hematoxylin 2 3-5 min. 13 Water – rinse well ------ 14 Acid water 2 dips 15 Water – rinse well ------ 16 Blueing water 30 sec. 17 Water – rinse well ------ 18 95% EtOH 10 dips 19 Eosin Y 1.5 min. 1-1.5 min. 20 Blot Blot Blot ------ 21 95% EtOH 10 dips 22 95% EtOH 10 dips 23 95% EtOH 10 dips 24 100% EtOH 1 min. 25 100% EtOH 1 min. 26 100% EtOH 1 min. 27 Xylene Substitute 1 min. 28 Xylene Substitute 1 min. 29 Xylene Substitute 1 min. 30 Xylene Substitute 1 min.

860


34

Table 6: Female reproductive classification terminology defined by Brown-Peterson et al.

(2011).

Phase Description of Phase Immature Never spawned. Contains only oogonia and primary growth oocytes,

has a thin ovarian membrane and little space between oocytes, small gonad size with indistinct blood vessels.

Developing

Early Developing

Gonads are developing in preparation to spawn. Gonad can contain primary growth, cortical alveolar, and early and mid vitellogentic oocytes. Late vitellogenic oocytes are rare. Some atresia possible but no postovulatory follicles. Gonad composed only of primary growth and cortical alveolar oocytes. May have early vitellogentic oocytes.

Spawning Capable

Actively Spawning

Fish will spawn during the spawning season. Abundance of late vitellogenic oocytes present. Gonad may also contain primary growth, cortical alveolar, postovulatory follicles, and atresia of vitellogenic and/or hydrated ooxytes (any stage). Early stages of oocyte maturation may be present. Fish is spawning, has spawned within 12 hrs, or will spawn within 12 hrs. Separated from spawning capable fish by evidence of widespread oocyte maturation indicated by lipid and/or yolk coalescence, germinal vesicle migration, and/or hydration of oocyte. Postovulatory follicles ≤12 hrs can be present.

Regressing

Fish will not spawn again this season. Atresia of oocytes at any and possibly all stages present and abundant. Primary growth oocytes becoming more abundant with most vitellogenic oocytes undergoing atresia. Postovulatory follicles possible.

Regenerating

Mature fish not reproductively active. Gonad contains oogonia and primary growth oocytes and has a thick ovarian wall. May have atresia of muscle bundles present.

865


35

Table 7: Male reproductive classification terminology defined by Brown-Peterson et al. (2011).

Phase Description of Phase Immature Never spawned. Contains only primary spermatocyte, no lumen in

lobules, and small gonad size. Developing

Early Developing

Gonads are developing in preparation to spawn. Gonads may contain secondary spermatogonia, primary and secondary spermatocytes, spermatids, and spermatozoa in spermatocysts. Spermatozoa not present in lumen of lobules or in sperm ducts. Germinal epithelium continuous throughout. Gonad composed only of primary spermatogonia, secondary spermatogonia, and primary spermatocytes.

Spawning Capable

Actively Spawning

Early GE Mid GE Late GE

Fish will spawn during the spawning season. Spermatozoa in lumen of lobules and/or sperm ducts. All stages of spermatogenesis can be present. Spermatocysts throughout testes, and active spermatogenesis. Germinal epithelium can be continuous or discontinuous. Fish is spawning, has spawned within 12 hrs, or will spawn within 12 hrs. Release of milt with gentle pressure on abdomen (macroscopic). Histological subphases based on structure of germinal epithelium (GE). Continuous GE in all lobules throughout the testes. Continuous GE in spermatocysts at testes periphery, discontinuous GE in lobules near ducts. Discontinuous GE in all lobules throughout the testes.

Regressing

Fish will not spawn again this season. Residual spermatozoa present in lumen of lobules and in sperm ducts. Widely scattered spermatocysts near periphery containing secondary spermatocytes, spermatids, and spermatozoa. Spermatogonial regeneration of germinal epithelium common in periphery of testes.

Regenerating

Mature fish not reproductively active. No spermatocysts present. Lumen of lobule often nonexistent. Proliferation of spermatogonia throughout testes and germinal epithelium continuous throughout. Residual spermatozoa present in lumen of lobules and in sperm ducts.

870


36

Table 8: Composition of modified Gilson’s fluid, which will be used to separate oocytes from

ovarian tissue in samples classified as actively-spawning.

Amount Product 100 ml 60% EtOH 880 ml Distilled water 15 ml 80% nitric acid 18 ml Glacial acetic acid 20 g Mercuric chloride

875


37

Morgan Corey Master’s Thesis Project Prospective Work Schedule

2015 2016

J F M A M J J A S O N D J F M A M J J A S O N D

Committee Meeting

Prospectus Completed (by 6/30/2015)

Comprehensive Exam

Defend thesis (by 6/20/2016) Final thesis changes (by 7/25/2016)

X X X

X X

X

X

X

Field sampling Process otoliths/analyze

Process histology samples/analyze

Process fecundity samples/analyze

X X X X X X X X X X X X X X

X X X X X X

X X X X X X X X X

X X X

Age/Growth Intro & Methods

Reproduction Intro & Methods

Age/Growth Results & Discussion Reproduction Results & Discussion

Thesis to Committee

Manuscript Preparation

X X X

X X X

X X X

X X X

X

X X X

SD AFS meeting (abstracts Nov. 2015)

MS AFS meeting (abstracts Jan. 2016)

USM Undergraduate Research Forum

ASIH meeting (abstracts March 2016)

X

X

X

X

growth and reproduction of southern flounder ( paralichthys lethostigma ... · growth and...

Documents