Oxygen Consumption of the Gag Grouper

Home , Esox, Grouper, Respirometer

METABOLIC RATE OF THE GAG GROUPER (Mycteroperca microlepis) IN RELATION TO SWIMMING SPEED, BODY SIZE, AND SEASONAL TEMPERATURE

RICHARD JOSEPH KLINE

A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2004

Richard Joseph Kline

To my parents, Nancy and Ron for providing support and encouragement through all of my journeys (and especially for buying my first aquarium and grouper)

To Joe Kuban, my high school ecology teacher, who first introduced me to the science of ecology and the marine environment

ACKNOWLEDGMENTS

I give thanks to Dr. Debra Murie for the opportunity to work in her lab, and on her boat conducting research on gag in the shallow Gulf of Mexico reefs. Without her extensive support, keen eye for what was feasible, and guidance regarding bioenergetic studies, this work may never have been completed. I thank Dr. Daryl Parkyn for his initial advice on theory and construction of respirometer; and for his generous contributions to my knowledge of fish physiology and metabolism. I thank the members of my committee (Dr. Lauren Chapman and Dr. Bill Lindberg). Dr. Chapman also provided advice on initial experimental design, and added to my knowledge of fish physiology. Dr. Lindberg provided a great foundation of knowledge regarding gag grouper, through the Suwannee Regional Reef System; and extensive insight into the history and ecology of the shallow gulf ecosystem.

Three other faculty members who played a role in my research regarding fish physiology and ecology were Dr. Frank Chapman, Dr. Chuck Cichra, and Dr. Ken

Portier. Dr. Chapman contributed significantly to my education as a physiologist, and emphasized the importance of basic concepts that are often overlooked. Dr. Cichra’s door was always open. He contributed to my knowledge of ecology and was invaluable for his statistical advice and the value of simple explanations. Dr. Portier helped with

iv initial experimental design and generously provided several hours of assistance in the

analyses of the data and application of the Proc Mixed procedure.

This master’s project would not have been possible without help from many

people in regards to gag collection and maintenance, extended loans of testing

equipment, construction of the holding facility and respirometer, and help with the

experimental design implementation and interpretation. I especially thank all of the

wonderful people who made this project possible: Dr. Mike Allen, Dr. Shirley Baker, Liz

Berens, Dr. Erin Bledsoe, Mark Butler, Doug Colle, Jackie Debicella, Jon Fajans, Dr. Ruth

Francis‐Floyd, Jason Hale, Jon Kao, Stephen Larsen, Eddie Leonard, Doug Marcinek, Dr.

Frank Nordlie, Sky Notestein, Pat O’Day, Dr. Ed Phlips, Erin Reardon, Dr. Allen Riggs,

and Larry Tolbert. I give special thanks to Mark Hebert at Microelectrodes Inc.

(Bedford, NH) for custom‐building and donating the oxygen probe used in this study.

Financial support for my graduate assistantship was provided through a variety of

sources, but primarily the UF College of Agricultural and Life Sciences, the Department

of Fisheries and Aquatic Sciences, and the U.S. Department of Agriculture. I thank them

all for providing support. Collections of the many gag used in this study, and the

materials for building the respirometer, were supported by research funds provided by

Dr. Debra Murie and Dr. Daryl Parkyn; and through an associated project in conjunction

with Florida Sea Grant. I also thank the Department of Fisheries and Aquatic Sciences

for funding construction of the recirculating seawater system and aquatic facilities used

for my grouper research. All gag used in this study were captured under a Scientific

Activity License issued by the Florida Fish and Wildlife Conservation Commission.

TABLE OF CONTENTS page

ACKNOWLEDGMENTS ...... iv

LIST OF TABLES...... viii

LIST OF FIGURES...... ix

ABSTRACT ...... x

CHAPTER

1 INTRODUCTION ...... 1

Bioenergetics ...... 2 Respirometry ...... 5 Gag Grouper ...... 11 Objectives ...... 14

2 METHODS ...... 16

Design of the Blazka Respirometer...... 16 Collection and Maintenance of Gag ...... 19 Experimental Protocols ...... 21 Statistical Analysis ...... 25

3 RESULTS ...... 31

Oxygen Consumption at Temperature and Swimming Speed ...... 31 Swimming Performance...... 31 Multivariate Model Derivation ...... 32

4 DISCUSSION ...... 39

Comparisons of Aerobic Metabolism and Performance...... 39 Metabolic Temperature Compensation ...... 42

6 Utility of the Models...... 45 Costs Associated with Offshore Movements ...... 46 Costs Associated with Annual Metabolic Rates ...... 49 Factors Affecting Respirometry Studies ...... 51 General Conclusions...... 53

LIST OF REFERENCES ...... 58

BIOGRAPHICAL SKETCH ...... 65

vii

LIST OF TABLES

Table page

3‐1 Average gag grouper sizes, oxygen consumption rates, and critical swimming speeds at three acclimation temperatures...... 38

4‐1 Annual and summer energy expenditure for gag grouper for standard, routine, and maximum aerobic oxygen consumption rates modeled in this study...... 57

viii

LIST OF FIGURES

Figure page

2‐1 Modified‐Blazka respirometer used to measure oxygen consumption of gag grouper...... 29

2‐2 Mean and range of monthly water temperature in the northeastern Gulf of Mexico during 1996 to 2001, at a depth of 13 m, off the mouth of the Suwannee River ...... 30

3‐1 Relationship of ln scaled oxygen consumption as a function of swimming speed, and temperature in gag grouper, displaying the non‐uniform effects of warm and cold acclimation temperatures...... 35

3‐2 Mass‐independent oxygen consumption as an exponential function of swimming speed and mean critical swimming speed (drop lines) for gag grouper at three acclimation temperatures...... 36

3‐3 Effect of acclimation temperature on mass‐independent maximum oxygen consumption metabolic scope and standard oxygen consumption of gag grouper...... 37

4‐1 Standard oxygen consumption as a function of temperature for gag (this study) compared to spotted seatrout, a metabolic compensator, and sand seatrout, a metabolic conformer (modified from Vetter, 1982)...... 55

4‐2 Predicted daily metabolic expenditure (in kJ and kcal) for a 1.8 kg gag grouper at temperatures encountered in the northeastern Gulf of Mexico...... 56

Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science

METABOLIC RATE OF THE GAG GROUPER (Mycteroperca microlepis) IN RELATION TO SWIMMING SPEED, BODY SIZE AND SEASONAL TEMPERATURE

Richard Joseph Kline

December 2004

Chair: Debra J. Murie Major Department: Fisheries and Aquatic Sciences

Energy costs associated with standard and active metabolic rates for gag grouper

(Mycteroperca microlepis) were estimated using models of oxygen consumption as a function of swimming speed, temperature, and body mass. Gag grouper ranging in size from 420 to 620 mm total length and 0.8‐3.2 kg were sequentially acclimated to three water temperatures representing winter (15°C), spring and fall (22°C), and summer

(30°C) in the northeastern Gulf of Mexico. At each temperature, the oxygen consumption of each fish was measured while it was swimming in a modified Blazka respirometer at incrementally increasing water velocity speeds of 10, 20, 35, 50, 65, and

80 cm/s. Oxygen consumption increased exponentially with swimming speed at all three temperatures.

A multivariate linear model with auto‐regressive covariance structure applied to the data resulted in three separate equations due to an interaction between swimming

x speed and temperature. An allometric coefficient for body size of 0.718 was significant

at all temperature treatments. Standard and maximum metabolic rates were lower in

gag, on a per kg basis, when compared to rates measured previously in fast swimming

species, such as sockeye salmon (Oncorhynchus nerka) and yellowfin tuna (Thunnus albacares). Conversely, gag metabolic rates were similar to more typically demersal

species, such as largemouth bass (Micropterus salmoides) and European seabass

(Dicentrarchus labrax). In addition, similar responses for standard metabolic rate in

relation to temperature for gag and spotted seatrout (Cynoscion nebulosus) provided

evidence for metabolic compensation in gag at low temperatures. Performance

measures of gag, including critical swimming speed and metabolic scope, increased with

increasing temperature up to 30°C.

General multivariate models developed to quantify oxygen consumption rates in

relation to swimming speed and body size for seasonal temperatures explained 90 to

94% of the variation. Models derived for oxygen consumption due to swimming speed,

body size, and temperature therefore have utility in modeling movements and activity

budgets of gag. As part of a fully parameterized bioenergetics model, the metabolic

component developed in the present study has the potential to significantly advance our

understanding of the energy allocation and growth of gag grouper in the fluctuating

shallow‐reef environments of the Gulf of Mexico.

xi CHAPTER 1 INTRODUCTION

Bioenergetics (the study of energy flow through a system) has been used extensively in studies of fish metabolism. This is especially true for cold‐temperate species, such as the salmonids and trouts (Oncorhynchus spp. and Salmo spp.); and other species, such as large mouth bass (Micropterus salmoides). These studies have increased our understanding of the physical performance of these fish, and allowed the estimation of energy requirements, from the individual to the population level. Researchers have developed bioenergetic models to predict a variety of scenarios, including the effects of manipulating habitat, optimal foraging strategies, field activity levels, and growth rates.

To date, however, there is little bioenergetic information available for warm‐ temperate and tropical marine fishes; and what is known has been limited primarily to the endothermic tunas. In low‐latitude ecosystems, groupers (Serranidae) and snappers

(Lutjanidae) are important reef predators. The rapid growth and hence productivity of these fish are exploited for food and recreation, yet virtually no bioenergetic data exist for any of these species; and information on metabolic rates is totally lacking. Metabolic‐ rate data can be incorporated into a bioenergetic model to predict costs of maintenance and activity on a daily to yearly basis. These costs ultimately affect the amount of assimilated energy that can go towards growth or reproduction. The present study used a bioenergetic approach to examine the metabolic rates of a warm‐temperate grouper,

1 2 the gag (Mycteroperca microlepis), over a range of activity levels and seasonal

temperatures.

Bioenergetics

Bioenergetic models have been used as a framework for investigating

consumption, growth, and activity in many fish species. Warren and Davis (1967)

presented a modified version of the Winberg (1956) bioenergetic model (Equation 1‐1)

C= (Mr+Ma+SDA) + (F+U) + (Gs+Gp) (1‐1)

where all values are expressed in units of energy (kJ or kcal), and C = rate of

consumption; Mr = standard metabolic rate; Ma = metabolic increase due to activity; SDA

= specific dynamic action or metabolic increase during breakdown and assimilation of a

meal; F = fecal wastes; U = urine wastes; Gs = somatic growth; and Gp = gonadal growth.

Since the equation is theoretically balanced, the energy input (C) and energy used in

metabolic functions has a direct effect on the amount of energy left for growth and

reproduction (Jobling, 1994; Brett, 1995). Bioenergetic models have been widely used in

aquaculture to model and maximize growth through optimizing feeding rates (Boisclair

and Sirois, 1993), water flow rates that influence swimming activity and aggression

(Davison, 1989; Jobling et al., 1993), and stocking densities (Cooke et al., 2000). Balanced

energy budgets (derived from Eq. 1‐1) have also been used to estimate swimming costs

(Boisclair and Tang, 1993), growth (Kerr, 1971; Ware, 1975), and impacts of predators on

their prey (Kitchell and Breck, 1980), Commonly, known values (measured under

controlled conditions), and/or estimates from the same or similar species, are inserted

into the model to solve for the component of interest. When more than one variable is

3 estimated (rather than measured directly), large errors have been reported when verified

in field and laboratory studies (Kerr, 1982; Boisclair and Sirios, 1993). This has been a

problem, especially for estimates of metabolic rate due to activity (Mr + Ma), which is

affected by a variety of environmental parameters (Lucas, 1992; Jobling, 1994; Brett,

1995) and can vary greatly from species to species (Adams and Breck, 1990).

To adequately measure the cost of swimming, a major component of active

metabolism (Mr + Ma) in fish, many researchers have used respirometry in the controlled

environment of the laboratory (Brett, 1964; Beamish, 1970; Diana, 1983; Kitchell, 1983) or

mobile respirometers in the field (Smith and Newcomb, 1970; Farrell et al., 2003). . Respirometry uses the oxygen consumption rate (VO2) as an indirect measure of aerobic

metabolic rate.

Indirect measures of metabolism (oxygen consumption) rather than direct

measures of heat released through metabolism (calorimetry) are typically used with

aquatic organisms because of the high temperature capacity of water and relatively

small heat output by ectothermic fish (Lucas, 1992). This is possible because oxygen is

used in the final stage of aerobic metabolism. In the initial process, pyruvate is formed

from glucose in the cell cytoplasm to yield 2 ATP. If oxygen is available, pyruvate is

transferred to the mitochondria, where it is processed through the Krebs cycle and

electron transport chain, to yield an additional 36 ATP for every molecule of glucose.

Oxygen is used as the terminal electron (e‐) and proton (H+) acceptor to form metabolic

water (H2O) at a rate of 5.5 to 6 ATP per molecule O2, depending on the substrate . metabolized. Since oxygen consumption rate (VO2 ) is tied to this process of ATP

4 production, it is a good measure of aerobic metabolism in aquatic organisms

(Hochachka and Somero, 2002).

In contrast, anaerobic glycolytic pathways are used when oxygen is in short

supply, or cannot be taken up quickly enough through the gills. The initial process of

pyruvate formed from glucose still takes place in the cytoplasm to yield 2 ATP; but with

no oxygen present, a backup of electrons occurs, and pyruvate becomes the terminal

proton and electron acceptor, forming lactic acid. This process is less efficient, but ATP

production still occurs, and oxygen consumption measurements can not account for this.

Only when lactic acid is de‐protonated, oxidized to pyruvate in the liver and red

muscle, and then recycled via the Krebs cycle, can the accrued debt from anaerobic

metabolism be measured by oxygen consumption (Hochachka and Somero, 2002). This

has been investigated in some studies but it typically has taken several hours to record the full repayment of the oxygen debt; and if not sampled continuously, can lead to

large errors (Goolish, 1991). This is a potential problem, because fish can incur an

oxygen debt chasing prey, fleeing predators, or avoiding aggressors during daily

activities (Brett, 1995). These cannot be replicated effectively in a respirometer; but, in

field observations, anaerobic activity of fish is a small portion of their overall budget,

compared to their resting and aerobic activity (Rice, 1981; Diana, 1983). Therefore,

quantifying energy expenditure of aerobic activities should be adequate for modeling

most of the activity budget of demersal predators.

Respirometry

Respirometry has been used to estimate metabolic costs of swimming in a variety

of fishes, including

• Fast‐swimming ram ventilators, such as skipjack tuna (Katsuwonus pelamis) (Kitchell, 1983), and Pacific bonito (Sarda chiliensis) (Selpulveda et al., 2003)

• Anadromous species such as sockeye salmon (Oncorhyncus nerka) (Brett, 1964) and European seabass (Dicentrarchus labrax) (Herskin and Steffensen, 1998)

• Ambush predators such as largemouth bass (Micropterus salmoides) (Beamish, 1970) and common snook (Centropomis undecimalis) (Tolley and Torres, 2002).

Most respirometry studies use swimming flumes, with either a recirculating Brett‐style

(Brett, 1964) or Blazka‐style (Blazka et al., 1960) respirometer. The Brett‐respirometer is a relatively large device consisting of a single, closed‐loop circuit of water with a pump

or propeller to drive the water and various ports for sampling (e.g., Brett, 1964; Bell and

Terhune, 1970). The Blazka‐respirometer, also a closed circuit, uses a more compact,

concentric tube design with a propeller driving the water (e.g., Blazka et al., 1960; Cech,

1990).

Some advantages of the Blazka‐ over the Brett‐style respirometer include smaller

overall dimensions in relation to the total water volume, improved temperature control

due to reduced exposure of water surface area to the ambient environment, and reduced

biological oxygen demand (BOD) in the system due to a smaller surface area available to

microbial attachment (relative to the respirometer volume). The Brett‐style respirometer

can be advantageous if changes in water volume and swim chamber size are necessary,

since some of the tubing sections in the circuit can be removed. It is difficult to change

6 the volume of a Blazka‐style respirometer due to its compact design; and it must be

tailored to a range of fish sizes that cause a measurable drop in dissolved oxygen level.

In flume respirometry, oxygen consumption is measured over the range of

swimming ability of the fish up to its maximum sustainable swimming speed, for

prolonged durations of 30 min to 1 h (Beamish, 1970; Cech, 1990; Brett, 1995). Maximum

swimming speed is determined by increasing the speed at set intervals until the fish

becomes physically exhausted. It is assumed that the majority of the swimming motion,

before exhaustion, is driven by slow‐twitch red muscle fiber and is aerobic in nature

(Rome et al., 1990). Anaerobic activity cannot be maintained for durations of prolonged

swimming due to lactic acid accumulation, therefore fatigue results and swimming

ceases (Brett, 1995). The critical swimming speed (Ucrit) is defined as the maximum

speed that can be maintained during stepwise intervals of prolonged swimming (Brett,

1964). This is assumed to be the maximum aerobic, swimming speed for fish in many

studies (Brett, 1964; Beamish, 1970; Sepulveda et al., 2003) and therefore maximum . oxygen consumption rate (VO2 max ) can be calculated at Ucrit (Brett, 1995).

In respirometry studies where failure occurs between swimming speed

increments, Ucrit is calculated by interpolation between the last completed speed and the

speed and time at failure with Brett’s (1964) equation

Ucrit = V + [(T/Ti)*Si] (1‐2) where V = last velocity completed (cm s‐1); T = time of trial completed (min); Ti = time

increment of trials (min); and Si = speed increment of trials (cm s‐1).

Standard metabolic rate (Mr) was defined by Fry (1971) as the minimum aerobic

metabolic rate of an intact, post‐absorptive, and quiescent organism. This has been . approximated in several studies by recording the lowest VO2 of a quiescent, fasted fish . over one to several days in a respirometer (VO2 SMR )(Fry, 1971; Claireaux et al., 2000). For

fish actively forced to swim over several incremental speeds in a flume, the relationship . of VO2 as a function of swimming speed is extrapolated back to zero activity (i.e., 0 . velocity) as an approximation of the fish’s VO2 SMR (Brett, 1964; Beamish, 1970). Both . extrapolation and actual measurement of VO2 SMR at no activity have yielded similar

results in studies of sockeye salmon and yellowfin tuna (Thunnus albacares) (Brett 1964;

Brill, 1987; Bushnell et al., 1994; Dewar and Graham, 1994; Farell et al., 2000). . . The difference between VO2 max and VO2 SMR is the metabolic scope (Fry, 1971; Brett,

1995). This is the theoretical range in metabolic rate that an organism must utilize for

prolonged periods (h to d). Although metabolic rates may periodically oscillate outside

this range for short periods (min), it is not sustainable without jeopardizing survival

(Fry, 1971). Since animals must remain within the bounds of metabolic scope for most of

their daily activities, it is a useful value for comparison of environmental effects within a

species and also for interspecific comparisons of performance. Metabolic scope has been

shown to be directly related to the temperature a species is adapted to, and the optimal

performance temperature is commonly identified by the temperature where metabolic

scope is maximized (Fry, 1971; Soofiani and Priede, 1985).

Factors, such as body size, temperature, swimming speed, and specific dynamic . action (SDA) have been shown to affect VO2 in fish and all should be incorporated into

8 models of metabolic expenditure due to activity (Beamish, 1974; Brett, 1995). The effect . of body size on metabolic rate (as measured by VO2 ) has been well documented in the

literature (Brett, 1964; Beamish, 1970; Brett and Groves, 1979; Diana, 1983; Holker, 2003).

At many levels of activity, the relationship is allometric, with oxygen consumption

increasing with fish size (Brett, 1995).

Brett and Groves (1979) generalized the weight‐dependent function of oxygen

consumption as Bb where B is body mass and b is a species‐specific exponent. Winberg

(1956) suggested a value of b = 0.80 for all fish. Values from respirometry studies in the

literature range from 0.65 for largemouth bass (Beamish, 1970) to 1.05 for sockeye

salmon (Brett, 1964), although Hochachka and Somero (2002) reported an overall trend

of this value towards 0.75 for all endothermic and ectothermic animals. In a sensitivity

analysis of data from oxygen consumption of largemouth bass, Rice (1981) found the

exponent b to be the most sensitive to error when compared with temperature and

swimming speed. When metabolic rate is scaled by the weight‐dependent relationship,

a mass‐independent function can be derived and used for examining the effects of other

factors on metabolism (McNab, 2002). . In general, VO2 has a positive exponential relationship to temperature in fish (Brett,

1995; Holker, 2003), but has exhibited a sigmoidal relationship when tested over a wide

range of temperatures (Brett, 1964; Beamish, 1970; Vetter, 1982; Claireaux and Lagardere,

1999). Temperature independence is encountered over the optimal range in some fish

and at extremes can have a negative relationship (Jobling, 1994). Because of this, it is

important to test each fish species over the range of temperatures normally experienced

9 in their environment. Temperature‐dependent processes are commonly represented by

a unit‐less scaling factor, Q10, which is defined as the rate of change in a physiological

process resulting from a 10°C increase in temperature (Winberg, 1956). This Q10 value is

useful for comparing the rates of various biochemical processes in living organisms

relative to temperature, such as metabolism in ectothermic animals. When intervals less

than 10°C are to be calculated, Eq. 1‐3 is used where R2 and R1 are oxygen consumption

rates (mgO2 kg‐1 hr‐1) measured at high and low temperatures (t2 and t1), respectively.

Q10 = (R2/R1)10/[t2‐t1] (1‐3)

Although Q10 values from 2 to 3 are generalized from interspecific comparisons of fish

species (Fry, 1971; Schmidt‐Neilson, 1990), it has been demonstated that Q10 values . relating VO2 to temperature (T) are not constant in many species when they are tested

throughout their biological range of temperatures (Brett, 1964; Beamish, 1970; Claireaux . et al., 2000). In cases where VO2 follows a constant Q10 with temperature, the exponential . mT ° function e , where m is a constant for temperature related VO2 and T is temperature ( C), can be used for modeling purposes (Rice, 1981).

Oxygen consumption rate in relation to increasing swimming speed has been

investigated for many species and is commonly tested over the entire aerobic range of

the fish (Brett, 1964; Beamish, 1970; Lowe, 1996). This relationship is commonly . characterized as exponential and Brett (1964) related VO2 to swimming speed, for a given

sized fish, as the exponential function egS, where g is a species‐specific constant, and S is

swimming speed. Values of g reported in a literature review by Rice (1981) ranged from

0.0196 for largemouth bass, 0.020 to 0.032 for sockeye salmon, and 0.030 for aholehole

(Kuhlia sandvicensis).

Specific Dynamic Action (SDA), or the energy used during the breakdown and . assimilation of a meal, affects VO2 and activity rates of fish for several hours after food

consumption (Soofiani and Priede, 1985; Brett, 1995). Energy expenditure due to SDA

has commonly been eliminated from respirometry experiments by fasting the fish for a

period of time following its last meal (24 to 48 h) (Beamish, 1970; Brett, 1995). However,

Brett (1995) cautioned against excessively prolonged periods of fasting and noted . substantive changes in VO2 of sockeye salmon after 144 h (6 d).

Parameterizing metabolic rate due to changes in activity level and temperature is a

complex relationship involving several variables and sources of error. When measured

accurately, parameters for metabolic rate, along with growth and consumption, can be

used to predict energy expenditure in the natural environment with a bioenergetic

model. Rice (1981) synthesized the components affecting oxygen consumption, body

size, swimming speed, and temperature into one equation for largemouth bass (Eq. 1‐4) . b gS mt VO2 = a B e e (1‐4) .

where: VO2 = oxygen consumption rate (Mr + Ma); T = temperature; S = swimming speed;

B = body mass; a = a constant; and b, g, and m are species‐specific coefficients for body

mass, swimming speed, and temperature, respectively. This synthesis proved useful in

modeling of daily activity budgets for largemouth bass (Rice, 1981).

When bioenergetic models have been applied to field observations, a wide variety

of allocation regimes have been reported. For example, Boisclair and Leggett (1989)

11 found 3.4 times more energy was allocated to activity than growth in yellow perch (Perca

flavescens), and similarly, skipjack tuna have been found to allocate 5 times more energy

to activity than to growth (Kitchell, 1983). Conversely, largemouth bass were found to

allocate considerably more energy to growth than activity (Adams et al., 1982), even

though a large potential scope for activity existed. To date, these models, ratios of

energy allocation, and metabolic scope are unknown for many large top‐level predators,

including groupers (Serranidae).

Gag Grouper

Groupers are top‐level predators in many warm‐temperate and tropical

ecosystems. In addition, many of the larger groupers are mainstays of both recreational

and commercial fisheries throughout their range. In the southeastern United States, the

gag grouper (Mycteroperca microlepis) (Goode and Bean, 1880) is of particular interest

because of its relatively large size and high production in fisheries. Gag grouper occur

in the Gulf of Mexico as well as on the Atlantic coast of the United States, ranging from

New York, U.S.A., to Rio de Janeiro, Brazil (Parrish, 1987; Hoese and Moore, 1998). The

largest males grow to nearly 130 cm (>4 ft) (Coleman et al., 1996; Brule et al., 2003), but

typically, smaller females less than 80 cm (<2.5 ft) are found on shallow reefs (Koenig et

al., 1996; Lindberg and Loftin, 1998). Gag experience high growth rates in the summer

months while consuming a largely piscivorous diet of schooling fishes, such as round

scad (Decapterus punctatus), and scaled sardine (Harengula jaguana), as well as resident

prey fish such as juvenile tomtate (Haemulon aurolineatum) (Lindberg et al., 2002). Gag

are known to aggregate and can exceed 100 individuals over artificial structures

(Lindberg and Loftin, 1998). Their greatest abundance has been noted on rocky

outcroppings and ledges in the eastern Gulf of Mexico (Parrish, 1987).

Gag are serial protogynous hermaphrodites and have a complex life history.

Juveniles migrate, at 5 to 6 months of age, from inshore seagrass beds (<5 m) to shallow

(10 to 20 m) rocky outcroppings and ledges during the fall months (Koenig et al., 1996).

They remain resident on shallow patch reefs from ages 1 to 6 and then migrate to the

deeper shelf edge (>40 m), where they congregate to spawn from February to April in

the Gulf of Mexico (Sadovy, 1996; Collins et al., 1998).

Gag grouper are important to recreational, as well as commercial, grouper

fisheries along the Gulf coast of Florida. Recent landings from recreational and

commercial Gulf of Mexico fisheries have averaged more than 2,277 metric tons

annually (Turner et al., 2001). Due to their hermaphroditic life history and the

predictability of their large spawning aggregations, gag are susceptible to over‐fishing

and catch‐per‐unit effort can be high, even while overall abundance is in decline

(Huntsman et al., 1999). Past research and stock assessments indicate that gag have been

undergoing over‐fishing (i.e., fishing mortality was above prescribed threshold levels)

(Koenig et al., 1996; NMFS, 2001; Turner et al. 2001). But the most recent National

Marine Fisheries Service (NMFS) Report to Congress (NMFS, 2004) declares the Gulf

stock recovered, even though current estimates of male biomass are only 1 to 7% of pre‐ fishery levels and the South Atlantic stock is still undergoing over‐fishing (Turner et al.,

2001). More information is needed concerning gag growth, movements, and spawning

behavior to adequately monitor and protect this valuable resource (Coleman et al., 1996).

Bioenergetic modeling is one potential tool to explore how these variables can affect

production.

To date, gag have been studied for diet and growth (Weaver,1996; Lindberg et al.,

2002), reproductive style (Collins et al., 1998), reproductive pattern and fecundity

(Coleman et al., 1996; Koenig et al., 1996), color variation and behavior (Gilmore and

Jones, 1992), habitat preference (Hart, 2002), fishing mortality (Lindberg and Loftin,

1998), and interactions between conspecifics and other species (Loren Kellogg,

University of Florida, unpublished data). Lindberg and Loftin (1998) noted variation in

summer growth and condition measures of gag in relation to aggregation density on

experimental reef arrays varying in patch size and spacing. Based on a bioenergetic

approach, Lindberg et al. (2002) concluded that consumption rates and the prey fish

availability in the summer did not explain all of the variation in the growth of gag. They

suggested that density‐dependent energy expenditure, through swimming activity,

could be an alternative explanation for the growth differences (Lindberg et al., 2002).

This density‐dependent energy expenditure could be estimated using activity budgets of

gag, calculated by summing the energy costs of specific activities observed on a daily

basis. To date, however, these components required to estimate energy costs due to

activity have not been investigated for gag.

Seasonal temperature changes are important to examine in gag grouper at the

subadult stage because, unlike many migratory species, gag remain resident on “home”

reefs for an average of 9.8 months, with a range of 5 days to 2.6 years (Lindberg and

Loftin, 1998). This exposes these fish to temperature fluctuations where they must either

14 conform, with commensurate changes in metabolic rate and activity, or metabolically

compensate in some metabolic pathway or enzyme isoform to regulate their metabolic

rate (Clarke, 1993; Johnston et al., 1994; Hochachka and Somero, 2002). These two

strategies have been noted in other fish and invertebrate species (Hochacka and Somero,

2002). Vetter (1982) noted alternative strategies for two estuarine seatrout species,

Cynoscion nebulosus, through metabolic temperature compensation, and C. arenarius,

through behavioral temperature compensation. Currently, only sparse incidental and

anecdotal evidence is available for gag at cold temperatures. For example, it has been

noted that in early winter they can be hand‐caught by divers on shallow reefs (pers.

obs.) but later in the winter they are actively swimming and avoid divers (Douglas

Weaver, University of Florida, pers. comm.).

Objectives

Metabolic responses to seasonal temperature changes are unknown for gag, and

presently, respirometry studies are lacking for any grouper species. Estimates of

energetic costs associated with activity are essential for bioenergetic modeling, but

remain elusive for these top‐level predators. The goal of this study was to develop a

quantitative model of oxygen consumption as a function of swimming speed and

temperature for gag grouper in order to estimate the amount of energy required for

locomotion and energy available for metabolic scope. This included estimating the

energy expenditure due to both standard (Mr) and active (Mr + Ma) aerobic metabolism

in gag. The specific objectives were

• To measure and model oxygen consumption in gag grouper over a representative range of body sizes, swimming speeds, and seasonal temperatures observed in the eastern Gulf of Mexico using a modified‐Blazka respirometer and Rice’s (1981) general multivariate formula (Eq. 1‐4)

• To use the resulting model from Eq. 1‐4 to estimate performance measures of gag, . including standard oxygen consumption rate ( O SMR ), critical swimming speed . V 2 (Ucrit), maximum oxygen consumption rate (VO2 max ), and metabolic scope

• To determine if gag are metabolic conformers or compensators while inhabiting shallow reefs in the eastern Gulf of Mexico.

The initial hypothesis was that oxygen consumption rate, and therefore metabolic rate of

gag grouper is directly related to environmental temperatures and will exhibit a

consistent Q10 value for oxygen consumption rate when tested over the temperature

interval encountered in the northeastern Gulf of Mexico. This latter portion of the

hypothesis relating to Q10 is an inherent assumption used in applying the complete Rice

(1981) model.

CHAPTER 2 METHODS

Design of the Blazka Respirometer

The respirometer used the Blazka et al. (1960) concept of compact, concentric tubes; but was modified by the use of an outer shell that was rectangular with curved ends and utilizing a flat floor and lid (Fig. 2‐1) for support of the swimming section and the convenience of a flat sealing surface. The swimming section of the respirometer was constructed of a 30.5‐cm diameter translucent fiberglass tube that was 94 cm in length, grafted to 30.5‐cm diameter PVC drainpipe (Fig. 2‐1A). Plastic coated metal grids (2.5 X

2.5 cm) were installed at both ends of the swimming section to prevent escape of the fish. A 74 ft‐pound thrust, 24 volt trolling motor (Minn Kota Riptide Rt74, Mankato,

MN) was used to move the water and was powered by two 12 volt, deep‐cycle batteries connected in series to a 24 volt, 10 amp battery charger (Schumacher SE 70MA, Mount

Prospect, IL). The motor was mounted in front of the swimming section (Fig. 2‐1A) to a

60 cm section of 30.5‐cm diameter PVC pipe, providing for removal and installation of the swimming section without the motor assembly. Flow inside the swimming section was modified from circular to turbulent with the use of a 6‐bladed straightening vane constructed of 3‐mm PVC with vane widths of 14 cm (Fig. 2‐1A). Video of the flow characteristics of the empty flume with streamers attached to the front grid revealed a

16 17 slightly turbulent flow as recommended by Brett (1995) to lessen boundary layer effects

in the swimming section and promote a dynamic swimming environment for the fish.

Many respirometry studies calibrate the water speed of an empty flume and then

use the equations from Bell and Terhune (1971) to correct for the change in water

velocity experienced by the fish due to blocking effect, or the theoretical change in flume

water velocity from partial blocking of the channel of water flow, due to fish size (i.e.,

Smith and Newcomb, 1970; Cech, 1990; Sepulveda et al, 2003). This method has

potential drawbacks because it assumes the fish is a rigid cylinder and therefore both the

body hydrodynamics and swimming motion of the fish are not taken into account. This

study used an electronic flow meter (Marsh McBirney Flowmate 2000, Frederick, MD),

with the probe affixed to the center of the flume by use of a 10‐mm PVC pipe extending

from the top of the swimming section. This allowed for measurement of the relative

water velocity experienced by each fish at the rear and center of the respirometer

swimming section during the actual swimming trials. The maximum sustained water

flow velocity of the respirometer was 80 cm s‐1 and the resolution of the flow meter was

(± 1 cm s‐1).

The outer shell of the respirometer was rectangular and constructed of 13‐mm

(1/2”) marine grade plywood with 5‐cm X 5‐cm wood reinforcements. Insulation board

(19 mm thick) was affixed to the interior and covered with 3‐mm tempered hardboard,

also used in construction of the curved ends. Layers of fiberglass were applied to the

inner shell and the outer plywood. All surfaces were sanded and a coat of non‐toxic

epoxy paint was applied. The respirometer was allowed to “cure” for several weeks and

18 was then run as a flow‐through freshwater system for one week before any trials. The

inner dimensions of the respirometer were 39 cm X 182 cm, with a volume of 257 L. This

volume was selected empirically so that the respirometer could accommodate gag of

various sizes, yet still allow measurable decreases in dissolved oxygen consumption

over a 30‐min swimming trial.

The lid of the respirometer (Fig. 2‐1B) was constructed of 6.4 mm (3/8”) acrylic

with two 13‐mm acrylic perpendicular support strips and 25‐mm X 25‐mm aluminum

“L” stock around the perimeter, affixed with silicone glue for support. The lid was

sealed using EPDM rubber gasket material and affixed to the respirometer shell by ¼”

stainless wing nuts and bolts. A vent was cut into the lid 2/3 across to purge bubbles

trapped in the respirometer. When all bubbles were vented, this slit was sealed using a

rectangular piece of acrylic and a 3‐mm neoprene seal affixed with ¼” stainless wing

nuts and bolts.

Dissolved oxygen was measured with a Clark polarographic oxygen electrode

(Microelectrodes Inc., Bedford, NH). This was connected to a meter, A/D interface

(Strathkelvin 928, Glasgow, UK), and connected to a personal computer for data logging

(once per 3 seconds [20 Hz]). This unit lacked temperature compensation, so minor

temperature fluctuations were monitored with a thermocouple and meter (Physitemp

BAT‐12, Clifton, NJ) and corrected manually. Temperature control (± 0.3°C) was

achieved by insulation, the thermal inertia of the large water volume, as well as a heat

exchanger circuit within the respirometer consisting of thin‐walled aluminum tubing

(13‐mm outside diameter). Water for the respirometer was supplied via a 190‐L

19 insulated reservoir for temperature control before flowing through a 25‐μm canister

filter and ultraviolet sterilizer.

Collection and Maintenance of Gag

Gag ranging in size from 420 to 620 mm total length (TL) (0.797 to 3.167 kg) were

captured over artificial reefs at ~13 m depth in the eastern Gulf of Mexico, periodically

from August 2003 to April 2004. Fish were collected using baited hook and line,

snagged with bare treble hook or caught by a handheld lobster net while on SCUBA. All

fish were brought to the surface slowly and, once on the boat, their gas bladders were

vented using a hypodermic needle to reduce problems associated with barotrauma

(Parrish and Moffitt, 1993; Florida Sea Grant, 2001). The fish were transported to the

University of Florida, Fisheries and Aquatic Sciences Aquatic Facility in Gainesville,

Florida, using 114‐L insulated coolers with seawater and compressed oxygen aeration.

All gag were given a 10‐min freshwater dip to reduce ectoparasites (Spotte, 1992)

before introduction into a 3,600‐L recirculating seawater system consisting of large

sump, head tank, five 570‐L and two 680‐L circular tanks. All tanks were covered with

opaque corrugated plastic to reduce evaporative water loss and shield the grouper from

visual stressors. Sections of PVC drainpipe of 20‐ and 30‐cm diameter were placed into

each tank for refuge and to reduce holding stress. Gag were housed two to four fish per

tank in keeping with the natural aggregating behavior of the species (Parrish, 1987).

Large and/or aggressive gag were housed separately as needed. Lighting consisted of

overhead fluorescent lights with the cycle fixed at the summer photoperiod of 13.5:10.5 h

(light:dark). A small incandescent lamp (40 W) was automatically turned on in the room

20 for 15 min at each end of the light cycle to alleviate any startle responses. Temperature

control was achieved by manipulation of ambient air temperature with an air

conditioner unit, as well as the use of a ¾ hp water chiller unit.

Filtration in the recirculating seawater system consisted of an 800‐μm mesh catch

bag upon entry to the sump followed by a large propeller‐washed bead filter (PBF3

Aquaculture Systems Technologies, Jefferson, LA) and large fluidized bed sand filter

(Quicksand FB89, Gainesville, FL) connected in parallel. Water parameters were

maintained within acceptable limits for marine fish, with pH between 8.0 and 8.2,

dissolved oxygen >80% saturation and > 6 mg/L, salinity between 31 and 36 ppt (33 to 35

ppt during swimming trials), ammonia <0.05 ppm, nitrite <0.2 ppm, and nitrate <50 ppm

(Spotte, 1992). This was done by monthly water changes of 1200 L, or 30% of the system’s capacity, with sand‐filtered seawater transported from the Whitney Marine

Laboratory (Marineland, Florida). Periodic addition of sodium bicarbonate and

dolomite powder helped to control the alkalinity and pH between experiments.

Gag generally took 1 to 2 weeks to start feeding voluntarily and were offered a

ration of 2 to 4% body weight every other day, based on preliminary consumption

estimates for gag in the wild (Lindberg et al., 2002). Ration consisted of pieces or whole

scaled sardines (Harengula jaguana), Spanish sardines (Sardinella aurita), or threadfin shad

(Dorosoma petenense). Actual feeding rates varied with the appetite of the gag, which

increased with temperature, and gag fed approximately once per week at 15°C, once

every 3 to 4 days at 22°C and once every other day at 30°C. However, all fish fed

sufficiently to maintain their weight throughout the experiment (i.e., ± 8% of their

21 original weight). All fish were anesthetized with 150 mg/L tricaine methanosulfate

(MS222), weighed (to the nearest gram), measured for maximum total length (TL) (to the

nearest mm), and injected with a sterilized Passive Integrated Transponder (PIT) tag in

the coelomic cavity for subsequent individual identification. Health of the gag was maintained by periodic treatment of abrasions and scrapes using Animax antibiotic

ointment (Pharmaderm Animal Health., Melville, NY) when required, especially the

eyes, which were particularly susceptible to infection after netting.

Experimental Protocols

Fish were acclimated to three sequential temperature treatments of 15, 22, and

30°C. These temperatures were selected because they respectively represent winter,

spring/fall and summer temperatures in the eastern Gulf of Mexico at 13 m water depth,

where gag were captured (Fig. 2‐2, E. Phlips, unpublished data). Temperature was

changed in increments of 1°C per day until the target temperature was reached,

followed by a 2‐week acclimation period before any respirometer trials (Fry, 1971; Cech,

1990).

The average period of fasting used in this study was 48 h ± 4.4, with a range of 36

to 84 h to ensure that gag had evacuated any previous meal from their gut tract. Ideally,

all gag should have been fasted for equal time periods, but a few gag were fasted as long

as 84 h because all fish from one tank were tested before moving to another. This was

necessary because gag that were disturbed with a net would not feed for several days

afterwards. The maximum fast duration in this study was 84 h, far below the 144 h

cautioned by Brett (1995).

Fish were randomly selected without replacement for each swimming trial. Each

fish was netted, placed in the respirometer swimming section (Fig. 2‐1), and allowed to

acclimate overnight at a low rate of flow (10 to 12 cm s‐1). This was the lowest rate that caused gag to orient to the flow in the swimming section. During this time, the

respirometer was run as a flow‐through system connected to the entire 3600‐L

recirculating system. In the morning, before each respirometry trial, the respirometer lid

was washed with a dilute soap solution, and rinsed with freshwater to prevent bubble

adhesion. The lid was then affixed to the respirometer and any trapped bubbles vented.

A black plastic partition was installed between the respirometer and the rest of the room

to reduce possible disturbance by external stimuli. A small incandescent lamp (40 W)

with a diffuser, and a video camera, were mounted directly over the swimming section.

The lamp provided an even light environment for the fish and reduced shadows on the

video. The video camera was placed directly over and perpendicular to the swimming

section to observe and record gag swimming behavior. Gag were left undisturbed for 1

h after setup, during which salinity and initial temperature were recorded and the

oxygen electrode was calibrated.

Calibration of the electrode to zero oxygen consisted of equilibration for 10 min in

a 500‐mL beaker filled with filtered seawater and compressed nitrogen bubbled through

an air stone. Calibration to 100% air saturation consisted of equilibration of the

electrode for 10 min in a 1000‐mL beaker filled with filtered seawater with gently

bubbled room air and a slowly moving stir bar. Calibration temperature was

maintained within ± 0.1°C of the respirometer temperature by monitoring with a

23 thermocouple and meter (Physitemp BAT‐12, Clifton, NJ) and adjusting a temperature‐

controlled water bath as needed. Values for air saturated seawater were determined

with equations from Benson and Krause (1984).

The range of swimming speeds for testing gag were determined in preliminary

trials at 30°C, where responses of swimming gag ranged from just oriented to flow

(positive rheotaxis) at 10 to12 cm s‐1 to labored or burst swimming at speeds from 65 to

80 cm s‐1. At each temperature treatment (15, 22, 30°C), each fish was subjected to the

same basic protocol. Swimming trials consisted of six successive 30 min bouts of 10, 20,

35, 50, 65 and 80 cm s‐1. A 20 min period at 12 to15 cm s‐1 was allowed between speeds ≥

20 cm s‐1 to allow for replenishment of oxygen in the respirometer and control of water

temperature. For fish > 2.5 kg, 100% saturation levels in the respirometer were achieved

during the rest period with the addition of compressed oxygen through a carbon

micropore stone placed in the reservoir. The speed following rest periods was slowly

increased over 2‐3 min to allow the fish time to adjust swimming gait to the new speed.

During the 15°C temperature trials, the water velocity was reduced from 65 cm s‐1 to a

maximum speed of 60 cm s‐1 because initial fish could not swim at 65 cm s‐1.

Water velocity measurements were recorded every 10 s during the first ~5 min of

each speed trial, with the median of 20 successive measurements calculated as the true

speed. Water velocity was rechecked at the end of each trial to ensure it had been

maintained throughout. The oxygen electrode was recalibrated at each rest period to

control for probe and temperature drift. Each swimming trial was concluded when 30

min of swimming was completed at each speed or the fish was no longer able to swim

24 against the water current (i.e., fish positioned itself on the back grid of the swimming

section). At 30°C and a salinity of 35 ppt, the dissolved oxygen saturation level was 6.25 . ‐1 mgO2 L , andVO2 measurements were therefore concluded when the level dropped

below 5 mg L‐1 (80% saturation). However, each fish was allowed to complete the trial

(30 min) while the respirometer valves were opened to allow flushing of the

respirometer with saturated water. Beamish (1970) noted no difference in largemouth

bass oxygen consumption rates or maximum sustained speeds at 70% saturation at 30

and 34°C.

Preliminary regressions of biological oxygen demand (BOD) as a function of water

speed at 30°C showed that there was no significant relationship between speed and the

recorded BOD (p=0.524; r2= 0.053). Therefore, at the end of each day a blank run was

completed at 20 cm s‐1 for all temperatures to account for biological oxygen demand

(BOD). Regardless of the BOD level, the respirometer was drained of saltwater and

rinsed with freshwater daily. At 30°C, the respirometer and reservoir was drained and

cleaned with household bleach (5% NaOCl) daily to minimize the BOD. The bleach was

then neutralized with an equal (100 g/L) solution of sodium thiosulfate (NaHSO2) and

freshwater. . ‐1 Oxygen consumption rate (VO2 ) in mgO2 h was calculated at each water velocity

by linear regression from a portion of the swimming trial where the fish was swimming

in a consistent manner for 15 min. Biological oxygen demand was measured from blank

runs immediately after the fish was removed from the respirometer after each day and . was calculated in the same way as the fish VO2 measures. The BOD rate was subtracted

25 from the calculated oxygen consumption rate, for each speed in the trial. Biological

oxygen demand rates were undetectable at 15°C, and averaged 12.58 ± 0.61 (± 1SE) and

16.62 ± 0.85 mgO2 h‐1 at 22 and 30°C, respectively. These values represented 14% and . ‐1 16% of the VO2 for the smallest gag (~0.8 kg) at the lowest speed (10 cm s ) and 1.7% and . 1.4% of the VO2 for the largest gag (~3.1 kg) at the highest speed, for 22 and 30°C,

respectively. For an average size gag of 1.8 kg, the BOD values equated to 7 and 8.5% of . . the total VO2 at 22 and 30°C. To calculate accurate VO2 measures in relation to body mass,

as well as to verify that gag were maintaining their weight over the study period, all gag

were anesthetized with MS‐222 after swimming trials, weighed to the nearest gram on a

digital scale (Ohaus IP15KS, Pine Brook, NJ), and measured for maximum TL (nearest

mm).

Statistical Analysis

A total of 18 gag grouper were used in the swimming trials with each temperature

treatment using 13 fish over the size range. Nine fish were repeated through all

temperatures, three fish were repeated at two temperatures, and six fish were used at

only one temperature. Differences in the mean weight of the fish used in each

temperature treatment were tested using a one‐factor analysis of variance (ANOVA).

As a standard first step to observe general trends and variation in the data, oxygen

consumption measured in mgO2 h‐1 was scaled on a per kg basis (as mgO2 kg‐1hr‐1),

linearized, and corrected for heterogeneity by the natural logarithm transformation, and

regressed as a function of swimming speed. Analysis of covariance (ANCOVA) was

26 applied to the scaled data to compare oxygen consumption among temperature

treatments for significant difference in elevations and intercepts.

A multivariate mixed‐effects model (Proc Mixed in SAS, Littel et al., 2000) was

used to analyze and apply Rice’s (1981) model (Eq.1‐4) to the entire, pooled data set.

This model allowed for the computation of the coefficients for body size (b), swimming

speed (g), and temperature (m). While the Proc Mixed procedure had similar uses to a

general linear model (Littel et al., 2000), it also allowed for analysis of repeated measures

with unequal cell sizes. Proc Mixed also allowed for analysis of the effects of repeated

speed trials on the same fish, via a covariance factor in the residual error structure. Data . ‐1 for VO2 (mgO2 h ) and body mass (kg) were transformed using natural logarithm

transformations in order to linearize the data and meet the model assumption of

normality in the residual distribution (Littel et al., 2000).

The residual error was modeled with an autoregressive covariance structure

[ar(1)] (Littel et al., 2000). The ar(1) type error covariance structure applied the

assumption that the residual error of closer measures of oxygen consumption due to

speed treatments for a fish, on a given day, were more correlated than the residual error

of measures further apart (i.e., 10 and 20 cm s‐1 versus 10 and 50 cm s‐1). To utilize this

correlated error structure, the order of swim trial within a day was transformed to a

categorical variable (i.e., 1 to 6). The fit of the corrected error residual structure to the

normal distribution was tested visually with normal plots, as well as the Shapiro‐Wilk

statistic.

Three multiparameter linear models (Eq. 2‐1 to 2‐3) were applied to the pooled,

repeated measures data to test for significant effect of each variable as well as interaction

(SAS Proc Mixed, Littel et al., 2000) . ln(VO2 ) = a + b ln(B) + gS + mT + ε* (2‐1) . ln(VO2 ) = a + b ln(B) + gS + mT + (S * T) + ε* (2‐2) . ln(VO2 ) = a + b ln(B) + gS + mT + [ln(B) * S] + ε* (2‐3)

where: T = categorical temperature treatment, as 15, 22 or 30°C; ln(B) = log body mass; S

= swimming speed; a = a constant; b, g and m = coefficients; (S * T) = the interaction term

between swimming speed and temperature; [ln(B) * S] = the interaction term between

log body mass and swimming speed; and ε* = the error with a correlated covariance

structure.

Three mass‐independent models (one for each temperature treatment) were . ‐1 calculated by dividing the VO2 data (mgO2 h ) by body mass raised to the common mass

specific exponent (b) from Eqns. (2‐1 to 2‐3). This calculation accounted for most of the

variation due to body size and therefore allowed further comparison of gag performance

measures in relation to temperature and swimming speed on a mass‐independent basis.

The effect of temperature treatment on gag was assessed by computing critical . . swimming speed (Ucrit), standard (VO2 SMR ) and maximum (VO2 max ) mass‐independent . . oxygen consumption rates, and Q10 values for VO2 SMR and VO2 max at each temperature

treatment. Critical swimming speed in absolute (cm s‐1) and scaled (bl s‐1) terms was

calculated for each fish using Eq. 1‐2. These values were then averaged for all fish in . each temperature treatment. Standard metabolic rate (VO2 SMR ) or the theoretical oxygen

28 consumption rate of a fish at zero activity, was calculated at each temperature by . extrapolation to the y‐intercept, to predict mass‐independent VO2 at zero swimming

velocity. Average mass‐independent, routine activity rates were calculated as oxygen

consumption at the lowest water flow tested (10 cm s‐1). This speed was the lowest that

would cause positive rheotaxis of gag in the flume and appeared similar to a typical

hovering behavior that is observed in gag on experimental reefs in the northeastern Gulf . of Mexico. Maximum predicted oxygen consumption rate (VO2 max ) at each temperature was calculated using the mass‐independent model at mean Ucrit. Metabolic scope was . ‐b ‐1 calculated by subtracting mass‐independent VO2 SMR (mgO2 kg hr ) from mass‐ . independent VO2 max . The effect of temperature treatment was assessed by calculating a . . Q10 value for VO2 SMR and VO2 max between each temperature treatment (15 to 22 and 22 to

30°C), and for the whole test range of 15 to 30°C, using Eq. 1‐3. All tests of significance

were at α ≤ 0.05.

Figure 2‐1. Modified‐Blazka respirometer used to measure oxygen consumption of gag grouper: A) insulated outer shell, interior, and swimming section for the fish, with a total volume of 257 L. B) acrylic lid showing the aluminum perimeter, perpendicular acrylic stiffeners, and bubble vent. The respirometer was capable of maximum sustained speeds of 80 cm s‐1.

40.0

Summer 30.0 Spring Fall

20.0 Temperature (°C)

10.0 Winter Winter

0.0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Figure 2‐2. Mean and range of monthly water temperature in the northeastern Gulf of Mexico during 1996 to 2001, at a depth of 13 m, off the mouth of the Suwannee River

CHAPTER 3 RESULTS

Oxygen Consumption at Temperature and Swimming Speed . At all temperature treatments, VO2 increased exponentially with swimming speed . ‐1 ‐1 (Fig. 3‐1). Absolute VO2 ranged from 55.5 mgO2 h for a 0.93 kg gag at 10 cm s and 15°C, to 956.8 mgO2 h‐1 for a 3.15 kg gag at 80 cm s‐1 and 30°C. Least squares regressions . ‐1 ‐1 applied to natural logarithm transformed, scaled VO2 (mgO2 kg hr ) versus swimming speed (cm s‐1) data provided good fits, with r2 values of 0.76, 0.82 and 0.86 for 15, 22, and . 30°C, respectively (Fig. 3‐1). Initial regressions of ln(VO2 ) as a function of swimming speed were more similar between 15 and 22°C than between 22 and 30°C treatments

(Fig. 3‐1). The slopes of these relationships did not differ significantly (ANCOVA: F=

1.76; p = 0.187), but did have different intercepts (F = 14.18; p = 0.0003). Similarly, slopes for the regressions for the 22 and 30°C relationships were not significantly different

(ANCOVA: F = 3.62; p = 0.059), allowing for tests of intercepts, which were significantly different between 22 and 30°C (F = 80.17; p = 0.0001).

Swimming Performance

In general, gag swam well in the respirometer and maintained a positive rheotaxis during testing. Gag avoided having their caudal fin in contact with the rear grating and this helped to maintain their position in the forward part of the flume. Gag exhibited an affinity for the sides of the flume at low speeds and many required 2 to 3 min at the

31 32

beginning of the speed trials to assume a normal swimming posture. All gag were able

to attain greater swimming speeds with increasing temperature, and larger fish

generally attained higher absolute speeds than smaller ones. However, for any of the

temperature treatments, this latter trend of greater swimming speed with increasing fish

size was not significant (all p > 0.300). Only three large fish were able to complete the 60

cm s‐1 trial at 15°C, one of which swam at 80 cm s‐1. At 22°C, nine fish were able to

complete the trial at 65 cm s‐1, however only one completed an 80 cm s‐1 trial. At 30°C, all gag completed a 65 cm s‐1 trial, and ten completed the 80 cm s‐1 trial. However, one trial

was excluded from Ucrit calculations due to an artificially low final swimming speed

resulting from battery failure.

The maximum sustainable swimming speed (Ucrit) calculated for 15 and 22°C

treatments averaged 1.02 ± 0.15 body lengths per second (bl s‐1) (± 1SE) and 1.29 bl s‐1 ±

0.21, respectively (Table 3‐1). At 30°C, many fish completed the 30 min trial at 80 cm s‐1.

However, three gag failed at this speed and several others were swimming erratically at

the end. Due to these observations, and the impossibility of greater test speeds in the

respirometer, 80 cm s‐1 or 1.48 bl s‐1 ± 0.07 was assigned as Ucrit for the 30°C treatment

and may be a slight underestimate.

Multivariate Model Derivation

The multivariate, linear model (Eq. 2‐2) with autoregressive error covariance

structure met the assumption of normality (Kolmogorov‐Smirnov: p > 0.081) and

provided the best fit to the data R2 = 0.93). The intercepts were significantly different . due to temperature (p < 0.001). Swimming speed (S) had a significant effect on ln(VO2 ),

with a significant interaction effect between swimmng speed and temperature (p < . 0.001). Body mass (B) also had a significant effect on ln(VO2 ) (p < 0.001). The effect was independent of speed and temperature and the coefficient b was estimated as 0.718 ±

0.040 (± 1SE). An interaction between ln(B) and S was not significant in the model (p =

0.210). Due to the significant interaction between swimming speed and temperature, three separate temperature‐dependent equations were used to describe the relationship . between VO2 as a function of swimming speed and body mass . 2 T = 15° C ln(VO2 ) = 3.8182 + 0.0268(S) + 0.718ln(B) R = 0.90 (3‐1) . 2 T = 22° C ln(VO2 ) = 4.1008 + 0.0231(S) + 0.718ln(B) R = 0.94 (3‐2) . 2 T = 30° C ln(VO2 ) = 4.5747 + 0.0185(S) + 0.718ln(B) R = 0.93 (3‐3)

Oxygen consumption was then scaled relative to the allometric relationship of . 0.718 ‐0.718 ‐1 B , yielding mass‐independent VO2 (mgO2 kg h ) for each fish. These data were then plotted as a function of swimming speed at the three temperatures (Fig. 3‐1),

resulting in exponential equations . 0.0264(S) 2 T = 15°C VO2 = 46.57e r = 0.84 (3‐4) . 0.0231(S) 2 T = 22°C VO2 = 59.18e r = 0.90 (3‐5) . 0.0188(S) 2 T = 30°C VO2 = 95.56e r = 0.91 (3‐6)

These mass‐independent relationships provided a better fit to the data in

comparison to scaling on a per‐kg basis and allowed for a more effective analysis

regarding the effects of swimming speed and temperature across the size range of gag . tested. A graph of the relationship of mass‐independent VO2 SMR , metabolic scope and . VO2 max depicted the dramatic increases commensurate with temperature (Fig. 3‐2). The

. . maximum predicted mass‐independent VO2 at Ucrit (VO2 max ) for gag was calculated from

Eq. (3‐4 to 3‐6) as 194.79 ± 31.10, 282.24 ± 33.97 and 429.99 ± 41.95 mgO2 kg‐0.718 h‐1 for 15, . 22, and 30°C, respectively. Mass‐independent VO2 SMR calculated from the intercepts of

Eq. (3‐4 to 3‐6) was 46.57 ± 1.06, 59.18 ± 1.04 and 95.56 ± 1.03mgO2 kg‐0.718 h‐1. By difference, mass‐independent metabolic scope was then calculated as 148.22, 223.06, and

334.43 mgO2 kg‐0.718 h‐1 for 15, 22, and 30°C, respectively (Fig. 3‐2). Average observed . minimum (routine) VO2 (the lowest oxygen consumption rate recorded in this study when the fish was not actively swimming but just exhibiting positive rheotaxis) was calculated using a body mass coefficient of 0.718 to yield mean, mass‐independent values of 58.9 ± 1.6, 79.5 ± 2.8, and 118.9 ± 4.5 mgO2 kg‐0.718 h‐1 over 15, 22, and 30°C, respectively (Table 3‐1). . Calculated Q10 values for VO2 SMR differed between the temperature ranges of 15 to

22°C and 22 to 30°C, and were 1.32 and 1.80, respectively. The Q10 for the entire . temperature range of 15 to 30°C was 1.65. For VO2 max , Q10 values were quite similar at

1.74, 1.78, and 1.76 for ranges 15 to 22, 22 to 30, and 15 to 30°C, respectively. Mean weight of gag tested was not significantly different among temperature treatments

(ANOVA: F= 0.10, p = 0.89) (Table 3‐1). Temperature within each speed treatment varied

± 0.3°C, and at most, ± 1.2°C throughout each day. Mean temperature treatment values were 14.9°C ± 0.03, 22.2°C ± 0.03; and 30.4°C ± 0.03.

7 . 2 30 °C ln( V O 2 ) = 0.0189(S) + 4.3926 r = 0.86

. 2 22 °C ln( V O 2 ) = 0.0220(S) + 3.9692 r = 0.82

. 2 15 °C ln( V O 2 )= 0.0247(S) + 3.7215 r = 0.76 ) 6 -1 hr -1 kg 2 5 2 O . V

ln( ) (mgO ) ln( 4

3 0 102030405060708090 SwimmingSwimming speedSpeed (cm/s)cm s-1

Figure 3‐1. Relationship of ln scaled oxygen consumption as a function of swimming speed, and temperature in gag grouper, displaying the non‐uniform effects of warm and cold acclimation temperatures.

500

. 0.0188(S) 2 450 30 °C VO2 = 95.56e r = 0.91 . 0.0231(S) 2 22 °C VO2 = 59.18e r = 0.90

400 . 0.0264(S) 2 15 °C VO 2 = 46.57e r = 0.84

) 350 -1 hr 300 -0.718 kg

2 250

200 2 O . V

(mgO 150

100

0 0 102030405060708090 SwimmingSwimming Speed speed (cm/s)cm s-1

Figure 3‐2. Mass‐independent oxygen consumption as an exponential function of swimming speed and mean critical swimming speed (drop lines) for gag grouper at three acclimation temperatures.

500

450

400 )

-1 350

hr x . ma 300 2 -0.718 VO kg

2 250

200

2 Metabolic O

. 150 V (mgO Scope 100

50 . SMR 0 VO2 15 °C 22 °C 30 °C Temperature

Figure 3‐3. Effect of acclimation temperature on mass‐independent maximum oxygen consumption metabolic scope and standard oxygen consumption of gag grouper.

Table 3‐1. Average gag grouper sizes, oxygen consumption rates, and critical swimming speeds at three acclimation temperatures. Acclimation temperature 15°C 22°C 30°C Gag grouper Sample size 13 13 13 Total length (mm) 537 (22) 533 (23) 551 (22) Wet weight (kg) 1.900 (0.231) 1.798 (0.244) 1.943 (0.213) Oxygen consumption (mgO2 kg‐0.718 h‐1) . Standard ( VO2 SMR) 46.57 (1.06) 59.18 (1.04) 95.56 (1.03) Routine (10 cm s‐1) 58.9 (1.5) 79.5 (2.9) 118.9 (4.5) . Maximum (VO2 max) 194.79 (31.10) 282.24 (33.97) 429.99 (41.95) Critical swimming speed Absolute (cm s‐1) 54 (2) 68 (3) 80a Relative (bl s‐1) 1.02 (0.04) 1.29 (0.06) 1.48a (0.07) a n = 12; Highest speed tested and may therefore be an underestimate Standard errors are given in parentheses.

CHAPTER 4 DISCUSSION

Comparisons of Aerobic Metabolism and Performance

The present study is the first to measure aerobic metabolism via oxygen consumption rate in gag grouper and, to my knowledge, any grouper species. Few examples in the literature have addressed metabolism of warm‐temperate or sub‐ tropical marine fish species and these studies have tended to focus on smaller‐sized individuals (Brett, 1964; Beamish, 1970; Tolley and Torres, 2002). The present study on gag grouper used relatively large fish and individuals over a size range encountered on shallow reefs in the Gulf of Mexico, where gag spend a good portion of their life span

(Coleman et al., 1996; Lindberg and Loftin, 1998).

The interaction of temperature and swimming speed and the unequal Q10 values . for VO2 SMR for gag at 15 to 22°C (Q10=1.32) versus 22 to 30°C (Q10=1.80) prevented the estimation of the temperature coefficient (m), formulation of one overall model (Rice’s

1981 model, Eq. 1‐4), and led to the rejection of the hypothesis that gag metabolic rate exhibits a consistent Q10 throughout the range of seasonal temperatures in the northeastern Gulf of Mexico. However, the resulting three temperature‐specific models . 2 (Eq. 3‐4 to 3‐6) did explain a large amount of the variation (R = 0.90 to 0.94) in VO2 (mgO2 h‐1) due to body mass and swimming speed. In addition, the coefficients for body mass

(0.718) and swimming speed (0.0185 to 0.0268) both lay close to values reported in the

39 40

literature for other fish species, such as largemouth bass, sockeye salmon, and aholehole,

which range from 0.65 to 1.05 for body mass (Rice, 1981; Brett, 1995) and 0.0196 to 0.030

for swimming speed (Rice, 1981).

The observed increases in Ucrit (Fig. 3‐2) commensurate with temperature

increases, followed trends reported in the literature (Beamish, 1970; Rome et al., 1990;

Brett, 1995) and the highest average Ucrit of 1.48 bl s‐1 was within the range reported for

other predatory marine species of similar size. For example, adult sockeye salmon (2 to

3 kg) tested with a mobile respirometer by Lee et al. (2003) had Ucrit values of 1.68 to 2.17

bl s‐1 at 10 to 22°C. These are higher than the maximum Ucrit for gag, but this is to be

expected as gag are typically demersal predators whereas the sockeye salmon in Lee et

al.’s study were actively migrating upriver. Another large predator, the scalloped

hammerhead shark (Sphyrna lewini), had Ucrit levels of 1.17 bl s‐1 at 24°C (Lowe, 1996),

slightly lower than the Ucrit of 1.29 at 22°C for gag. By definition, Ucrit is not the fastest speed attainable by a fish but rather the maximum speed that can be aerobically

maintained over prolonged activities, such as foraging and migration (Fry, 1971; Brett,

1995). Therefore, the Ucrit reported for gag at each temperature in this study should be a

good predictor of the maximum temperature‐specific, aerobic swimming rate for gag in

the northeastern Gulf of Mexico. . The maximum and standard VO2 and resulting metabolic scope, increased

substantially over the temperature range tested but were low for gag in comparison to

other fishes such as yellowfin tuna (Dewar and Graham, 1994) and sockeye salmon (Lee

et al., 2003). The marked difference in peaks of metabolic scope when comparing

similarly‐sized gag at 30°C, European seabass at 20°C (Claireaux and Largardere, 1999)

and sockeye salmon at 15°C (Brett, 1964), across similar temperature ranges, represent

the effects of fish adapted to different temperature regimes (Hochachka and Somero,

2002). Peak metabolic scope was determined by Fry (1971) to be a good indicator of

optimal performance temperature in ectotherms and it appears that this is ≥ 30°C for gag

grouper.

The metabolic response to temperature, and general position in the trophic

structure, are very similar for gag grouper and largemouth bass (the present study and

Beamish, 1970). In some areas of their distribution, the seasonal temperature regime is . also similar (Rice, 1981). Beamish (1970) noted an increase in VO2 of largemouth bass up

to 30°C and a sharp decrease thereafter. Although this potential decrease has yet to be

determined for gag, it will obviously occur at a temperature ≥ 30°C and therefore

appears to be following a trend similar to largemouth bass. It is interesting to note,

however, that temperatures above 30°C are not commonly recorded at 13 m water depth

in the northeastern Gulf of Mexico where gag reside (Fig. 2‐2).

The increasing and relatively large metabolic scope for gag at 30°C (Fig. 3‐3)

indicates that gag are performing best at summer temperatures. This should also

translate to increased growth of gag during the summer and evidence for this trend can

be seen in the high growth rates of post‐settlement juveniles in seagrass beds (Keener et

al., 1988), high growth rates of gag captured in the summer on shallow reefs in the Gulf

of Mexico (Lindberg et al., 2002), and large visceral fat stores of captured gag on shallow

reefs in the early fall months (D. Murie, University of Florida, unpublished data).

Metabolic Temperature Compensation . The Q10 values for gag at VO2 SMR were within the range of 1.5 to 3.2 reported for

various fish species (Beamish,1970; Rice, 1981; Dewar and Graham, 1994; Brett, 1995),

but the overall Q10 value of 1.65 for 15 to 30°C for gag did not adequately predict the . effect of the temperature intervals on VO2 . In particular, it appeared that gag increased

their standard metabolic rate at low temperature compared to what is expected in a

typical pokilothermic animal (i.e., a consistent Q10 of 2 to 3 over the temperature range) . (Schmidt Neilson, 1990; Jobling, 1994; McNab, 2002). However, the Q10 values for VO2 max showed a more consistent trend (1.74 to 1.78) and appeared more temperature‐ . dependent when compared with VO2 SMR measures.

This apparent compensatory effect on SMR at lower temperature (conservation of

metabolic rate; Hochachka and Somero, 2002) could be due to the increases in the

amounts of certain specific enzymes or the transcription of a more temperature‐

independent enzyme isoform at lower temperatures (Hochachka and Somero, 2002).

Alternatively, increases of mitochondrial density (Hochachka and Somero, 2002) and

muscle contractile properties in the goldfish, Cyprinus carpio (Johnston et al., 1990) have

been noted as a compensatory mechanism during colder seasons. In terms of modeling

this effect, Claireaux et al. (2000) and Claireaux and Legardere (1999) were able to fit an . asymptotic function to cod (Gadus morhua) and European sea bass VO2 SMR data, which

followed a trend of unequal Q10 values. This approach could potentially replace the ‘m’

coefficient for temperature in the Rice (1981) model. However, data from more

temperature treatments would be necessary to use this approach for gag, especially at

temperatures greater than 30°C.

Temperature and photoperiod have been investigated as cues for metabolic

compensation in fish. Although temperature is commonly indicated as the driving force

behind changes in metabolic rate of aquatic ectotherms, other factors are confounding

(Clarke, 1993). Some factors that have been correlated with changes in metabolic rates of

fish are seasonal fluctuations of rainfall, food availability, and gonadal development . (Evans, 1984). Independent effects on VO2 due to photoperiod have been noted in

pumpkinseed (Lepomis gibbosus) (Evans, 1984) and muskellunge (Esox masquinongy)

(Chipps et al., 2000). In pumpkinseed, increasing photoperiod caused a commensurate . increase in VO2 , but did not change the magnitude of the response with regard to

temperature change (i.e., same Q10 values per interval).

A fixed summer photoperiod was utilized in the present study to test the effect of

temperature without the potential confounding effect of photoperiod. The effect of

reducing the light phase of the photoperiod in gag, as would occur during the winter, . might shift the total response in VO2 but, following the results of Evans (1984), might not

affect the relative change in response at each temperature (i.e., resulting in the same Q10 values). The results from the present study may indicate that gag have some

compensatory mechanism to control standard metabolic rate in relation to temperature,

especially when encountering low temperature. However, this effect is unseen in the . VO2 max values, which have consistent Q10 values between 15 to 22°C and 22 to 30°C. The

present study did not address the effect of photoperiod alone or the seasonal

44 combinations of photoperiod and temperature, and future studies should be performed altering photoperiod and/or temperature to determine their effects on metabolic rate of gag. The selected photoperiod in the present study is mostly beneficial for the modeling of summer metabolic rates, when the majority of gag growth is observed (Collins et al.,

1998; Lindberg et al., 2002). . The increased similarity of the 15 and 22°C versus the 22 and 30°C VO2 measurements at 20 to 50 cm s‐1 could indicate some type of compensatory mechanism in gag to increase metabolism at lower temperatures (Fig. 3‐2). However, conflicting behavioral evidence has been observed in the early winter, when gag have been hand‐ captured or snagged by hook‐and‐line while remaining motionless inside structure at temperatures near 15°C. The feeding rates of captive gag in this study were also greatly reduced at the winter temperature. Weaver (1998) also noted that gag were motionless at temperatures <15°C, but upon later inspection of the captured specimens he found that they had ingested large prey items. This indicates that gag are at least somewhat active at winter temperatures. Full acclimatization of gag to the initial cold winter temperatures, which arrive as cold fronts, may require several weeks in the Gulf of

Mexico. Further studies using temperatures below 15°C may be informative, but it may ultimately be necessary to determine the lower lethal temperature for gag and investigate the lower extreme of this possible metabolic compensation.

Spotted seatrout (Cynoscion nebulosus) co‐occur with juvenile gag over seagrass beds in Florida and Vetter (1982) showed that spotted seatrout exhibit a similar trend in . VO2 SMR compared to gag over similar temperatures (Fig. 4‐1). However, another co‐

. occurring fish, the sand seatrout (C. arenarius) showed a trend of VO2 SMR falling to lower levels (~25 mgO2 kg‐1 h‐1 ) at 15°C. Standard metabolism for C. nebulosus was estimated

at 50 mgO2 kg‐1 h‐1 for 15°C and 124 mgO2 kg‐1 h‐1 at 30°C. For gag these values were 45

and 97 mgO2 kg‐1 h‐1 at 15 and 30°C, respectively. The sand seatrout was therefore

considered by Vetter (1982) to be a temperature conformer while the spotted seatrout

was considered to be a metabolic compensator. Differences in the metabolic

temperature response of these two seatrout species may relate to their behavioral

differences in relation to seasonal temperature extremes in the shallow waters of the

Gulf of Mexico. The sand seatrout migrates out into deeper Gulf of Mexico waters to

escape cold temperatures in the winter while spotted seatrout remain resident inshore.

The similarity of behavior between spotted seatrout and gag, and similar . responses in VO2 SMR at temperature, lend support for metabolic temperature

compensation in gag. This may explain how gag endure the extreme temperature

fluctuations of the Gulf of Mexico while remaining resident on relatively shallow‐water

reefs for several years (Koenig et al., 1996; Lindberg and Loftin, 1998). Metabolic

compensation at low temperatures would also allow them to remain active to some

degree (i.e., for foraging) during the winter.

Utility of the Models

To demonstrate the utility of the temperature‐specific oxygen consumption

models derived in this study, the energetic costs incurred by gag for two major activities

were estimated: 1) swimming costs of offshore movements; and 2) metabolic costs due to

annual temperature cycle.

Costs Associated with Offshore Movements

Gag maturing in the Gulf of Mexico move to spawning sites on the shelf edge, reportedly close to the Florida Middle Ground and Madison‐Swanson marine reserves

(Koenig et al., 1996). From the experimental reefs where the study gag were captured, a fish would have to swim ~125 km to reach the general spawning area. In addition, since actively spawning gag are captured during Febuary through April (Coleman et al., 1996;

Collins et al., 1998) this movement likely takes place during the early spring. Although gag may move from shallow reefs to spawning grounds through cooler water temperatures, calculations using 22°C serve as an example of how the generated equations could be used to predict the costs of swimming and standard metabolism in gag grouper. In addition, all gag used in the respirometry study were non‐reproductive females and therefore any costs associated with gonadal tissue maturation have not been included in the energetic cost estimates. In particular, respirometry of females with maturing gonads would be informative, but logistically very difficult unless a portable respirometer could be carried on an offshore vessel.

Minimum cost of transport in aquatic organisms, or the minimum energy required to transport a unit of mass 1 km (Schmidt‐Nielsen, 1972), has an associated least‐cost velocity (Uopt) that predicts the most efficient swimming speed for a fish. Optimal swimming velocity has been previously determined for estuarine species at 28°C and 20 to 30 ppt, including spotted seatrout, red drum (Sciaenops ocellatus), sheepshead

(Archosargus probatocephalus), and striped burrfish (Chilomycterus schoepfi) (Wakeman and

Wohlschlag, 1982). At an average size of ~30 cm body length, the Uopt for these species

ranged from a high of 3.6 km h‐1 for sheepshead to a low of 1.8 km h‐1 for striped burrfish. The greater values for Uopt for sheepshead indicated more efficient swimming

compared to the burrfish, probably based on fundamental differences in their body

shapes (compressed versus ostraciform body shape, respectively). In general, Uopt

increases as fish size increases, and also increases as temperature increases (Wakeman

and Wohlschlag, 1982).

This cost of transport for gag at 22°C was calculated by transforming mass‐

independent oxygen consumption values derived in Eq. 3‐5 from mgO2 kg‐0.718 h‐1 to

mgO2 kg‐0.718 cm‐1, and interatively determining the minimum value in the relationship

between oxygen consumption (energy per unit distance) as a function of swimming

speed (Videler, 1993). This optimal swimming speed was calculated from the data in

this study as 43 cm s‐1 (1.54 km hr‐1) for a 3.5 kg (650 mm TL) gag at 22°C. In a field

telemetry study, gag returned to home reefs from up to 3 km away after tagging and

release at a swimming rate of 35 cm s‐1 (1.26 km hr‐1) (Brian Keil, University of Florida,

pers. comm.). The calculated Uopt value of 1.54 km hr‐1 was therefore lower for gag than

previously examined estuarine fishes, but reasonable for gag based on an approximate

field estimate. This lower Uopt value for gag could also be attributed to a lower test

temperature (22°C versus 28°C), and the larger body size of gag (65 cm TL) compared to

the average 30‐cm body size of the estuarine fishes tested by Wakeman and Wohlschlag

(1982).

Under the assumption of a gag traveling a distance of 125 km at a temperature of

22°C, with further assumptions that fish are swimming at or near an optimal rate

between 35 to 43 cm s‐1 (1.26 to 1.54 km hr‐1), and they do not feed while in transit (hence

SDA=0), then a 3.5 kg (650 mm) female gag would require 100 h (~4 days) of continuous

swimming to reach the proposed spawning area. The combined cost of active

metabolism (standard metabolic rate and swimming) for this travel can be calculated using Eq. 3‐2, where: a = 4.1008; g = 0.0231; b = 0.718; and with S = 35 to 43 cm s‐1 and B =

3.5 kg . ln(VO2 ) = 4.1008 + (0.0231 S) + 0.718 ln(3.5) (4‐1) . ‐1 ‐1 ‐1 ‐1 which yields ln(VO2 ) = 333.2 mgO2 h .for 35 cm s and 400.8 mgO2 h for 43 cm s . For

100 h of travel time, this extrapolates to a range of 33,320 to 40,080 mgO2 h‐1. Applying

an oxycalorific conversion for O2 used in metabolism of 0.0136 kJ per mgO2 (or 0.00323

kcal per mgO2) (Lucas, 1992), yields energetic costs of 453 to 545 kJ (108 to 129 kcal).

Given that lipid contains approximately 35.5 kJ/g (8.48 kcal/g) (Lucas, 1992), 12.8 to

15.4 g of dry weight lipid would have to be metabolized over this distance, given

constant swimming at 35 cm s‐1 and no feeding. For a 3.5 kg gag this amount of lipid

would represent less than 1% of its body weight, and is available as visceral fat deposits

in a gag in the late fall (November) (D. Murie, University of Florida, unpublished data).

This example serves to demonstrate that the costs of swimming in offshore movements

to spawning grounds may be relatively small for gag. Even if these values are under‐

estimates of actual field costs for offshore movements (Brett, 1995), a value 3 X as large is

still a relatively small cost to a 3.5 kg gag and could result in a net weight gain if feeding

were included. These calculations lend support to the idea that gag could swim directly

49 from shallow reefs to spawning grounds without the need to forage, and still retain much of their stored energy for gonadal growth and spawning related expenditures.

Costs Associated with Annual Metabolic Rates

Maintenance costs for gag grouper, based on their standard metabolic rate, along with routine and maximal rates, vary across the seasonal temperature cycle that these fish experience while on relatively shallow‐water reefs in the Gulf of Mexico (Fig. 2‐2).

Although a broad size range of gag grouper occur on these reefs, fish of a mean body mass of ~1.8 kg are common (D. Murie, unpublished data). Therefore, Eq. (3‐1 to 3‐3) were solved using a 1.8 kg body mass and three activities (at swimming speeds)

• Standard metabolic rate at 0 cm s‐1

• Routine metabolic rate or ‘hovering’ (oriented to flow) at 10 cm s‐1, a behavior commonly observed for gag in the field (pers. obs.)

• Temperature‐specific critical swimming speeds, for estimates of maximum aerobic capacity at temperature.

The nine resulting values (three speeds at each of three temperatures) were then converted from mgO2 h‐1 to kJ d‐1 using an oxycalorific coefficient of 1 mgO2 = 0.0136 kJ

(0.00323 kcal) (Lucas, 1992) for a fish with a piscivorous diet, and multiplying by 24 h.

Polynomial equations were then fitted to the data to allow for interpolation across the temperature range (Fig. 4‐2). These equations were then used to calculate annual energy expenditure (kJ and kcal) of a 1.8 kg gag over the monthly temperature regime encountered at a ~13 m water depth in the Gulf of Mexico (Fig. 2‐2), yielding values presented in Table 4‐1. As expected based on metabolic scope (Fig. 3‐3) and the potential metabolic compensation observed in gag at lower temperatures (Fig. 4‐1), the

50 maximum oxygen consumption rate in the summer (e.g., August) was 4.5 times the

SMR, as compared to only 3.8 times the SMR in the winter (e.g., January) (Table 4‐1).

This higher metabolic scope associated with elevated temperatures occurs for an extended period from May through September.

The energy costs associated with maintenance, routine activity, and maximum metabolic rate were also calculated for the months of July through October, since most of the growth in gag grouper is assumed to occur during this time and preliminary food consumption estimates were also available for gag during this part of the year (Lindberg et al., 2002). The water temperatures during this period ranged between 23.4 and 29.9°C

(Fig. 2‐2), and the energy expenditure was calculated on an average daily basis as 41.1,

53.6, and 190.8 kJ d‐1 (9.8, 12.8 and 45.6 kcal d‐1) for SMR, routine, and maximum aerobic activities, respectively (Table 4‐1). A field‐estimated consumption rate for gag on experimental reefs in the Gulf of Mexico was 1.2 to 1.8% body mass per day (Lindberg et al., 2002). The caloric content of a mixed pelagic baitfish diet was estimated as 1.114 kcal g‐1 wet mass (Lindberg et al., 2002) and equated to a daily consumption estimate of 21.6 to 32.4 g wet mass or 24.1 to 36.1 kcal d‐1 for a 1.8 kg gag grouper.

The values for standard and routine aerobic energy expenditure generated in the present study predict a lower requirement than estimates of field consumption rates from Lindberg at al. (2002). However, the values calculated in this study based on oxygen consumption measurements represent the net energy requirements and do not include other components of the bioenergetic equation. For instance, not all of the gross energy obtained by consuming baitfish is available to gag grouper for metabolic

51 expenditure, since some components (and hence energy) of the baitfish is lost through fecal and urinary wastes. If it is assumed that approximately 80% of the gross energy consumed is available as net energy for maintenance, activity, and growth in piscivores

(Brett and Groves, 1979), such as gag during the summer (Lindberg et al., 2002), then gross energy consumption values estimated for gag would be equivalent to 19.2 to 28.9 kcal d‐1 net energy. This range is of similar magnitude to energetic costs estimated for

SMR and routine metabolic rate for the same time period (Table 4‐1).

Factors Affecting Respirometry Studies

The use of an overnight acclimation period in this study reduced the variation and total metabolic rate in gag at the lowest swimming speed, compared with preliminary studies at 30°C. This acclimation period has been disregarded or deemed impossible in respirometry studies of some species (see Tolley and Torres, 2002; Sepulveda at al., 2003) but may have a substantial effect on the lowest rates recorded, leading to an over‐ . estimate of VO2 SMR (Holker, 2003). The acclimation period in this study was potentially hindered by the respirometer lid being installed 1 h before testing. This was required to counteract the large amount of bubbles and proteins that would accumulate on the lid . overnight. Although the lid installation was a potential source of elevated VO2 , gag would typically return to their previous hovering behavior within a few minutes of lid and partition installation. Recordings over 1 h at the lowest test velocity in several fish . revealed no change in VO2 when comparing two sequential 30‐min periods.

Background oxygen consumption measures (BOD) were relatively high for the smallest fish in this study. However, for the average‐sized gag of ~1.8 kg, the BOD was

. 8.5% of VO2 , well within the limits reported by Sepulveda et al. (2003) (6 to 14%) and

Holker (2003) (10 to 20%). Gag were observed to produce a considerable amount of

mucus, especially when netted or after feeding. Even with a protein fractionator and

pre‐filtration of the water before entry into the respirometer, and skimming of the

respirometer with a small hand net after placement of gag in the respirometer, this extra

nutrient source probably contributed to the background oxygen consumption levels,

especially at higher temperatures. In the future, I would suggest using a smaller water

volume in the respirometer, which would increase the dissolved oxygen drop in relation . to the BOD, as well as more water filtration measures, to reduce the error in VO2 measurement of smaller gag.

The Blazka‐respirometer in this study provided excellent temperature control (±

0.3°C) of the testing environment either comparable to, or better than, other studies,

such as Tolley and Torres (2002) and Sepulveda et al. (2003) (both ± 1.0°C) and Holker

(2003) (± 0.2°C). No temperature correction measures were needed below 50 cm s‐1, and

at or above 50 cm s‐1, the heat production from the trolling motor and friction at high

water velocity was controlled adequately by the chiller unit and heat exchanger.

The potential for correlation between successive swimming speeds was also

addressed in this study. In forced swimming experiments, the accepted protocol has

been to sequentially increase speed over time (Brett, 1995). This appears beneficial, since . any accumulated oxygen debt would be pooled in the increasingly large VO2 at high

swimming velocities, resulting in a relatively smaller error in measurement of aerobic . . VO2 . A model incorporating some correlation of VO2 measurements among sequential

speed treatments could account for some of this residual variation. In this study, a

model with an auto‐regressive error structure provided a better fit to the data than . standard uncorrelated error and therefore provided evidence for an effect on VO2

measures due to the order of the speed trials.

General Conclusions . In summary, metabolic scope for activity as measured by VO2 substantially . increases in the summer months for gag. Similar responses of VO2 SMR to low temperature for spotted seatrout and gag provide evidence for metabolic temperature compensation . in gag. Standard metabolic rate and VO2 max are lower in gag, on a per kg basis, than fast

swimming species such as salmon and tuna, while comparisons with more typically

demersal species, such as largemouth bass and European seabass, show similarity.

Models derived for oxygen consumption due to swimming speed, body size and

temperature have utility in modeling movements and activity budgets of gag. Further

experiments are recommended to determine the upper and lower lethal temperature

limits of gag, as well as the effect of photoperiod on their metabolic rates. The results

from this study indicate that the effect of body mass is independent of swimming speed

and temperature, while an interaction between swimming speed and temperature

prevented the development of a single generalized model for gag.

The results of this study can be incorporated with existing energetic data on

consumption and growth to further parameterize the bioenergetic model for gag

grouper. Since spacial structuring of life stages occurs in gag, and only pre‐reproductive

female gag are captured on the shallow‐experimental reefs in the northeastern Gulf of

Mexico (Lindberg and Loftin, 1998; and also verified with all subjects in this study), the

variable for gonadal growth (Gp) can be removed from Eq. 1‐1, vastly simplifying the

overall bioenergetic model. A fully parameterized bioenergetics model has the potential

to significantly advance our understanding of the energy allocation and growth of gag

grouper in the fluctuating shallow‐reef environment of the Gulf of Mexico.

While this is the first study to report metabolic measurements of grouper, the

results may not be broadly applicable to gag everywhere because all of the fish used in

the present study were subadult females collected from relatively shallow water (~13 m

depth) off the west‐central coast of Florida. Gag also exhibit spatially structured life stages as do many other fish species. Current information on the differences in energy

requirements of different life stages for species other than salmonids is lacking.

Inferences about whole populations of gag will be aided by the results of this study

however, habitat and temperature regime differences that these populations experience might alter their energy requirements and therefore would require verification.

175 sand seatrout

150

spotted 125 seatrout

)

-1 100 h

-1 gag g k 2 O g

m 75 (

r sm 2 . VO 50

0 10 15 20 25 30 Temperature (°C)

Figure 4‐1. Standard oxygen consumption as a function of temperature for gag (this study) compared to spotted seatrout, a metabolic compensator, and sand seatrout, a metabolic conformer (modified from Vetter, 1982).

Serie 250 s4 60

Poly.Max y = 0.1045x2 + 2.7359x + 32.368 (Seri es2) 2 Poly.Routine y = 0.1258x - 3.5375x + 54.402 50 200 (Seri es3) 2 Poly.SMR y = 0.078x - 1.8794x + 33.35 (' )

40 ) ) -1 -1 150

100 Energy used (kJ d used (kJ Energy

20 d used (kcal Energy

50 10

0 0 10 15 20 25 30 35 Temperature (°C)

Figure 4‐2. Predicted daily metabolic expenditure (in kJ and kcal) for a 1.8 kg gag grouper at temperatures encountered in the northeastern Gulf of Mexico. The curves for standard (SMR) and maximum (Max) metabolic rate bound the predicted energy use of a 1.8 kg gag. The curve for the routine metabolic rate is the predicted energy expenditure used in the typical hovering behavior of gag observed on the reefs.

Table 4‐1. Annual and summer energy expenditure for gag grouper for standard, routine, and maximum aerobic oxygen consumption rates modeled in this study. Energy Expenditure (kJ) Total Month SMR Routine Maximum Hours Annual Jan 744 677.7 920.0 2576.8 Feb 696 665.1 862.5 2989.5 Mar 744 860.6 1089.9 4229.3 Apr 720 838.8 1062.2 4124.2 May 744 1141.9 1468.9 5472.7 Jun 720 1275.0 1662.4 5917.8 Jul 744 1419.1 1864.1 6461.4 Aug 744 1477.9 1949.4 6655.5 Sep 720 1230.5 1598.8 5760.8 Oct 744 974.3 1238.6 4780.6 Nov 720 816.9 1034.6 4006.3 Dec 744 724.7 933.7 3330.2

Total (kJ) 12102.5 15685.2 56305.2 (kcal) 2891.2 3747.1 13450.8 Summer Jul 744 1419.1 1864.1 6461.4 Aug 744 1477.9 1949.4 6655.5 Sep 720 1230.5 1598.8 5760.8 Oct 744 974.3 1238.6 4780.6

Total (kJ) 1275.5 1662.8 5914.6 (kcal) 304.7 397.2 1412.9

Daily (kJ) 41.1 53.6 190.8 (kcal) 9.8 12.8 45.6

LIST OF REFERENCES

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BIOGRAPHICAL SKETCH

The author was born in Ft. Worth, Texas in 1970. Throughout his childhood he was constantly fascinated by the animals he encountered. In high school he was introduced to ecological concepts during trips to the Cayman Islands, Texas coast, Big

Thicket, and Big Bend National Park. All of the systems were interesting to him, but it was the marine environment that he loved. He soon became a certified SCUBA diver and was constantly exploring aquatic environments.

His first experience with higher education was disenchanting. His initial instructors did not seem to hold an interest in the science that they were teaching. After a few semesters, he decided to pursue other interests and held several professions while living in several cities. In 1998, he decided to go back to school and worked while paying his own way through college. During that time, he found professors who shared his love for science. In 2001, he graduated from the University of Texas at Austin with a

Bachelor of Science degree in ecology, evolution, and behavior. After graduation, he worked at the US Geological Survey investigating water quality issues and assessing fish and invertebrate populations in Texas rivers.

As a graduate student in the Department of Fisheries and Aquatic Sciences at the

University of Florida, he was able to explore the marine environment that he loves, and to learn about gag grouper. At Fisheries, he served in several capacities: collecting

65 66 grouper and other fish specimens, for several ongoing studies in the eastern Gulf of

Mexico; and as a teaching assistant in the Biology of Fishes course. He also helped maintain departmental boats and collecting equipment. In this study, he was instrumental in designing and constructing a 1000 gallon recirculating seawater system to house large grouper. He also spent 4 months designing and constructing the respirometer described in this study, which will continue to be used in metabolic studies on gag and other fish species. In his spare time, he taught SCUBA diving at the

University Academic Diving Program; and is presently a teaching assistant for the

Biological Sciences program.

In the future, he plans to investigate the reproductive physiology of groupers for a doctoral degree; and hopes to one day conduct research and convey his knowledge to other students, as a professor at a university. As a final note to anyone who bothers to read this sketch, it is never too late to follow your dreams.