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NATURAL HISTORY AND FACTORS INFLUENCING POPULATION
STRUCTURE IN THE BANDED CORAL SHRIMP (Stenopus hispidus)
BRANDON R. CHOCKLEY
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
Brandon R. Chockley
To my Mother, Father, and Fiance for your constant loving support and general curiosity
throughout this process.
I would like to thank my advisor, C. St. Mary, for her insight, guidance, and
contribution to many aspects of this research, as well as numerous reviews of this
manuscript. Experimental design, analyses, and interpretation of results were greatly
motivated by discussions with my committee, C. St. Mary, C. Osenberg, and W.
Lindberg, and members of the St. Mary-Osenberg lab group, particularly J. Wilson and L.
Vigliola. I would like to thank C. St. Mary and B. Bolker for their guidance in the
modeling procedures. I am grateful to C. St. Mary, C. Osenberg, and C. Watson for the
use of their equipment for field and laboratory work both in the Florida Keys and at the
University of Florida, and to Ken Nedimyer (Sea Life Inc.) for collecting shrimp for my
experiments. In addition, I would like to thank J. Wilson, T. Adam, E. Hauck, and L.
Vigliola for their help with conducting this research. I am also grateful to H. Chockley,
L. Chockley, and S. Chockley for their constant support and reassurance. Parts of the
work for this manuscript were funded by the University of Florida (Grinter Fellowship),
PADI Project AWARE, and National Sea Grant (funding to C. Osenberg, C. St. Mary,
and B. Bolker).
TABLE OF CONTENTS
A C K N O W L E D G M E N T S ................................................................................................. iv
LIST OF TABLES .............. ....................... .... ...... ........ vii
LIST OF FIGURES ........................ ................. .. .. .. ................. viii
A B S T R A C T ............................................ ... ......... ................................... x
1 SIZE AT SETTLEMENT, GROWTH, AND FECUNDITY OF THE BANDED
CORAL SHRIMP, Stenopus hispidus, IN THE UPPER FLORIDA KEYS ......................1
In tro du ctio n ...................................... .................................................... 1
M e th o d s ........................................................................................................................... 4
Size at Settlement ........................................ ........... 4
M o lt In te rv al .......................................................................... 6
G ro w th ........................................................ ........ ...... 7
Relative Fecundity ......................................... .............. .. 10
R e su lts ............................................................................................ 1 1
Size at Settlem ent............................. .............. 11
M olt Interval ........................................ 12
G ro w th ................................................................ 12
R elative F ecundity ..................................................... .............. 13
D iscu ssio n ..................................................... 14
Size at Settlem ent............................. .............. 14
M olt Interval ........................................ 15
G ro w th ................................................................ 1 6
R elative F ecundity ..................................................... .............. 18
Conclusion ......................................... 18
2 EFFECTS OF SETTLEMENT, POST-SETTLEMENT MORTALITY, AND
GROWTH, ON THE POPULATION SIZE-STRUCTURE OF THE BANDED CORAL
SHRIMP, Stenopus hispidus, IN THE UPPER FLORIDA KEYS ....................................28
Introduction....................... ............... ..... ............. 28
M eth o d s ........................................................... 3 1
Population Structure................................... 31
L arval Settlem ent ................. ........ .......... .............................. ........... .. 32
Post-settlement Mortality and Movement............... .................................. 33
Growth ............ ............................... ............... 36
R e su lts ....................................................................... 3 8
P opu nation Stru ctu re ............................ .............. ... ................ .... ................ 3 8
L arval Settlem ent .............. .. ....... ......... ..................... ........ ...... .......... .. 39
Post-Settlem ent M ortality and M ovem ent .......................................................... 39
Growth ............ ............................... ............... 41
D iscu ssio n ..................................................................................... 4 2
Conclusion ............................................ 46
L IST O F R E F E R E N C E S ........................................................................ .. ....................59
B IO G R A PH IC A L SK E T C H ...................................................................... ..................65
LIST OF TABLES
1-1. Details of sites used in the growth tagging study. .............................................. 20
2-1. Details of sites used in population size-structure study...........................................47
2-2. Details of sites used in post-settlement mortality tagging study. ...........................48
2-3. Parameter estimates and test statistics from linear regression models to estimate the
growth increment for shrimp from the inshore and offshore region, as in Equation
2.2............... ........................................... ......... 49
LIST OF FIGURES
1-1. Linear regression (solid line) of mean molt interval (days) on body size (mm TL) of
all S. hispidus. ................................................... .................. .................. ........... 21
1-2. Estimated weekly molting probability as a function of shrimp size (mm TL) based
on survivorship analysis (exponential model).. ....................................... ........ 22
1-3. Polynomial regression (solid line) of growth increment (mm) on pre-molt length
(mm TL) of S. hispidus ........................................................23
1-4. Mean (dots) and standard deviations (error bars) of length (mm TL) at post-
settlement age (weeks) resulting from 100 simulations of the growth model ......24
1-5. Relationship between female length (mm TL) and egg mass volume (mm3) in S.
hisp idus (n= 4 1).. ......................................................................25
1-6. Relationship between female length (mm TL) and egg number (eggs/brood) in S.
hisp idus (n= 4 1).. ......................................................................26
1-7. Relationship between female length (mm TL) and female wet body mass (g) in S.
hispidus from Zhang et al. (1998) (closed circles) and present study (open
circles)..................................... .................. ........ ....... ........... 27
2-1. Box plots of total length (mm) for all sites surveyed in each of 2001 and 2002.......50
2-2. Mean (+SE) number of settlers to inshore and offshore artificial reefs in each often
w eek ly su rv ey s................................................ ................ 5 1
2-3. Survivorship curves of five size-classes of S. hispidus for 2001 and 2002 and all
sites com b in ed .............................................................................. ............... 52
2-4. Survival of small and large, tethered and un-tethered individuals in the laboratory
control tether experim ent.. .............. .......... ........................... ........................... 53
2-5. Survivorship of small and large, inshore and offshore tethered individuals in the
field tether experim ent.. ................................................. ............... ................. 54
2-6. Mean abundance (number/3.14m2) of predators in each of the clusters generated by
a k-m eans clustering analysis.......................................... ........................... 55
2-7. Adjusted mean (+ SE) growth increment for inshore and offshore populations of S.
hispidus from A N C O V A ........................................ ........................................ 56
2-8. Linear regression of mean pre-molt length (mm) on mean growth increment (mm)
for inshore and offshore populations of S. hispidus..............................................57
2-9. Mean and standard deviations (error bars) of shrimp length (mm TL) at post-
settlement age for inshore (closed circles) and offshore (open circles) regions....58
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
NATURAL HISTORY AND FACTORS INFLUENCING POPULATION
STRUCTURE IN THE BANDED CORAL SHRIMP (Stenopus hispidus)
Brandon R. Chockley
Chair: Colette St. Mary
Major Department: Zoology
Understanding natural history and population dynamics of marine organisms is
imperative for their management and conservation. My research documents important
life history parameters of the banded coral shrimp (Stenopus hispidus), a popular marine
ornamental shrimp, as well as estimates effects of several factors on the population
structure in the Upper Florida Keys. Among the life history parameters described are 1)
size at settlement, 2) molt interval, 3) growth, and 4) relative fecundity. Variation in the
size at settlement of S. hispidus in the Upper Florida Keys was much smaller than that
found in previous studies from other parts of the world. This suggests that there is large-
scale spatial variation in the size at settlement of S. hispidus. In a laboratory study, molt
interval increased as shrimp body size increased. I estimated weekly molting probability
and growth increment per molt under natural conditions, for various sized individuals,
with a field tagging study. These data were then incorporated into a crustacean growth
model, which included discontinuous growth and natural variability in size at settlement
and growth increment, to describe expected patterns of S. hispidus growth. This model
also allowed for the estimation of post-settlement age of S. hispidus in the Upper Florida
Keys. Finally, I described the relationships among female body size and egg mass
volume and egg number, and found that both relationships were significantly positive.
In the summer of 2002, I conduced studies that estimated to what degree 1) settlement,
2) post-settlement mortality and movement, and 3) growth contributed to the variable
size-structure of S. hispidus populations in the Upper Florida Keys. Smaller typically
immature shrimp dominated offshore reefs in the Upper Florida Keys, while larger
mature shrimp dominated inshore reefs. I showed, using artificial reefs, that settlement to
the offshore region was much higher than that to the inshore region. Using an extensive
tagging study, I documented size-selective mortality, which was consistent between the
two regions. Smaller individuals experienced much higher rates of mortality than did
larger individuals. Post-settlement movement was found to be minimal, with no evidence
of long distance movement between regions. Finally, growth in the offshore region was
slower than that in the inshore region. These results indicate that the offshore region may
be dominated by smaller shrimp because settlers rarely reach larger sizes, due to lower
growth rates and increased periods of vulnerability to high mortality (possibly due to
predation). Therefore, the variable size-structure of S. hispidus in the Upper Florida Keys
is probably due to the differential growth rates between the two habitats.
SIZE AT SETTLEMENT, GROWTH, AND FECUNDITY OF THE BANDED CORAL
SHRIMP, Stenopus hispidus, IN THE UPPER FLORIDA KEYS
Understanding life history of marine organisms is imperative for their management
and conservation. Only when demographic features such as growth rates, size at
maturity, and fecundity are better understood can reliable management practices be
implemented. This is especially true in harvested species. One fishery in need of data is
that of marine ornamentals, fishes and invertebrates that are harvested for the aquarium
trade. It is estimated that the global trade of ornamentals and associated accessories is in
excess of $7 billion/year (Andrews 1990). Current opinion is that 90% of freshwater
ornamentals can be captive-bred (Andrews 1990). However, Wilson et al. (2001) report
that approximately 98% of all marine species are still taken from wild populations, based
on an estimate provided by Martin Moe from Green Turtle Publications. It is estimated
that over 3000 species of marine fishes and invertebrates are collected from natural
habitats for the marine aquarium trade (Fletcher et al. 1995). The harvest of marine
ornamentals is still increasing, even with documented declines in local fish abundance
and habitat quality (Andrews 1990, Fletcher et al. 1995, Tissot and Hallacher 1999).
In 1998, the trade of invertebrates for aquariums was valued at $30 million in the
United States alone, and virtually all of the invertebrates in the aquarium trade are marine
species (Larkin and Degner 2001). Among the marine invertebrates collected for the
aquarium trade are the cleaner shrimps, consisting of over 18 species (Fletcher et al.
1995). It has been hypothesized that the harvest of cleaner shrimps from the natural
environment for the aquarium trade can result in a decline in the local fish population,
therefore having broader implications for the ornamental trade and reef communities
(Fletcher et al. 1995).
One of the most popular cleaner shrimps in the marine ornamental trade is the banded
coral shrimp, Stenopus hispidus (Olivier) (Zhang et al. 1998). Stenopus hispidus is a
reef-associated cleaner shrimp (Decapoda: Stenopodidae) with a worldwide distribution.
It is known to remove and consume ectoparasites, injured or dead tissues, and excess
food particles from fishes (Limbaugh et al. 1961, Johnson 1977). As adults, S. hispidus
are found in crevices or overhangs in reefs at depths ranging from <1 to 210 meters and
are thought to move over an extremely limited area (<1 m2) with males exhibiting
territorial behavior within this area (Limbaugh et al. 1961, Stolen 1964, Young 1979,
Fletcher et al. 1995).
Adults are typically found in reproductive pairs (Limbaugh et al. 1961, Johnson 1969,
Young 1979). It is believed that juveniles form pairs and then grow up together
(Limbaugh et al. 1961). Females reach sexual maturity at -30 mm TL (Stolen 1964).
Unlike many other cleaner shrimps that exhibit simultaneous hermaphroditism, S.
hispidus shows no signs of hermaphroditism (Fletcher et al. 1995). Mating usually
occurs within 12-48 hours of a female molt and can be broken into five discrete steps: 1)
antennule contact (10 minutes-6 hours), 2) erection of female body, 3) grasping, 4)
copulation (10 seconds), and 5) spawning (Zhang et al. 1998). Spawning typically begins
within 15-25 minutes of copulation and lasts approximately 10 minutes, during which the
female deposits a blue-green egg mass on the swimmerets under the abdomen (Limbaugh
et al. 1961, Zhang et al. 1998).
After spawning, eggs progress from heavily pigmented towards transparency, where
darkly pigmented eyespots begin to appear. Larvae typically hatch within 16 days of
fertilization at 280C (Young 1979). Like many other members of the family
Stenopodidae, newly hatched S. hispidus larvae go through nine larval stages before
settling to the benthos (Gurney and Lebour 1941). However, compared to most
Stenopodids, S. hispidus has a long larval duration (at least 123 days) and has shown the
ability to delay metamorphosis up to as many as 210 days, until suitable nutritional or
environmental conditions are encountered (Gurney and Lebour 1941, Williamson 1976,
Fletcher et al. 1995). Because of its long larval duration and potential to delay
metamorphosis, little progress has been made in the culture of S. hispidus in the
laboratory, unlike many other species of cleaner shrimps (Zhang et al. 1997).
Although much is known about S. hispidus, several key factors of its life history are
still unknown. From a management perspective, perhaps the most important aspect of S.
hispidus biology is its growth rate. For most marine fisheries, estimates of species'
growth rates is one of the most essential elements in population modeling when trying to
provide estimates of sustainable harvests (Chen and Kennelly 1999). Although
determining growth rates for fishes is straightforward, measuring growth in crustaceans is
more difficult, due primarily to the loss of all hard parts upon molting and the
discontinuous nature of crustacean growth (McCaughran and Powell 1977, Annala and
Bycroft 1988, Chen and Kennelly 1999).
The overall objective of this chapter is to provide additional life history information
which will aid in the management ofS. hispidus, including estimates of 1) size at
settlement, 2) molt interval across the range of sizes, 3) relative fecundity and egg
number, and 4) estimates of S. hispidus growth based on data from a detailed tagging
study, which allowed for the estimation of weekly molting probability and growth
increment per molt of S. hispidus under natural conditions. These data were then
incorporated into a crustacean model (Chen and Kennelly 1999) to describe expected
patterns of S. hispidus growth.
Size at Settlement
Light traps and artificial settlement substrates. To quantify size at settlement of S.
hispidus I deployed larval light traps and artificial settlement substrates in several
locations in the Upper Florida Keys. Light traps were variations on the design of Meekan
et al. (2001). Traps consisted of a single chamber made of clear acrylic. In the center of
the chamber was a suspended dive light (Princeton Tech IMPACT) attached to a 50 cm
clear plastic tube with a mirror on the opposite end to prevent light loss through the
bottom of the traps. A single "funnel" (10.16 cm diameter) made of clear soda bottles
(Sponaugle and Cowan 1996) was imbedded into each side of the trap, to allow
photopositive organisms to enter. Once deployed, the light traps operated continuously
for approximately 120 hours. Floats were attached to the top of each trap to make them
positively buoyant and traps were suspended 2 m above the surface of the reef by
mooring them to two, 2.37 L concrete weights.
Artificial settlement substrates were slight variations on the design of van Montfrans
et al. (1995). As with those of van Montfrans et al. (1995), substrates consisted of a
plastic fibrous material, approximately 1.9 cm thick typically used as an air-conditioner
filter (surface area = 0.26 m2) formed around a cylinder of PVC pipe. However, the PVC
pipe used in this study was 10.16 cm in diameter and 50.8 cm long. Substrates were
secured to PVC cylinders by large rubber bands. Cylinders were equipped with internal
flotation and capped at each end. The substrates were suspended vertically 2 m from the
surface of the reef by mooring them to two 0.95 L concrete weights.
Previous studies with light traps indicate that marine invertebrate post-larvae are most
abundant between the 3rd quarter and new moon phases of the lunar cycle (Reyns and
Sponaugle 1999, Meekan et al. 2001). Therefore, traps were deployed each night
beginning two nights prior to the new moon and ending two nights after new moon in
May and June of 2002. Four replicate light traps and four replicate settlement substrates
were deployed in both offshore and inshore reefs in the Upper Florida Keys. Traps and
substrates were recovered and redeployed daily during the collection periods. Upon
recovery, trap contents were emptied into 0.85 mm mesh sieves and preserved in 95%
EtOH. Processing of substrate collections consisted of removing and replacing each filter
with a new, clean filter. Old filters were placed into individual plastic bags for later
rinsing with freshwater. This water was then sieved (0.85 mm mesh) for organisms,
which were preserved in EtOH (van Montfrans et al. 1995).
Artificial reefs. Artificial reefs were also used to quantify size at settlement. On June
19, 2002, 87 small (<1 m2) artificial reefs, each consisting of five limestone rocks from a
local quarry, were deployed in a linear array (5 meters apart), approximately five meters
from a natural contiguous reef, in the Upper Florida Keys. From July 25 to August 3,
2002, each reef was surveyed daily and emptied of all fishes and invertebrates (including
S. hispidus) using Eugenol (an anesthetic, also known as clove oil). All S. hispidus
collected from these reefs were then measured (mm TL).
Surveys. A previous study by Gurney and Lebour (1941) provided descriptions and
sketches of S. hispidus post larvae. One distinguishing characteristic among these post
larvae is the presence of red on the body and legs in less distinguishable bands than that
of adults. I observed similar color patterns among small S. hispidus in the Upper Florida
Keys. Because this color pattern matched that described by Gurney and Lebour (1941), I
assumed these shrimp had recently settled. Therefore, I conducted extensive surveys for
S. hispidus of this color pattern among several reefs in the Upper Florida Keys. All
shrimp encountered were collected and measured (mm TL) underwater and released.
Data analysis. A pooled mean size was calculated from all measured individuals
from all three studies. I checked for possible outliers, individuals greater than three
standard deviations from this mean, and then removed them. After removing outliers, a
mean size at settlement was calculated from all remaining individuals.
Twenty-seven shrimp, of various sizes, were purchased from a collector operating in
the Upper Florida Keys (Sea Life Inc.) and maintained in a closed-system aquarium at the
University of Florida, Department of Zoology from March 12 to May 3, 2002. Shrimp
were housed in individual 2L containers that constantly received recycled water from a
drip-bar located above each container. Water temperature fluctuated between 24 and
260C and salinity was kept between 35-39 ppt. All shrimp were fed quartered silversides
once every three days. Upon introduction to the aquaria, all shrimp were measured (mm
TL), sexed, and tagged. Daily inspections for molting events were then conducted for 52
The criteria used to sex individuals were revised from those given by Stolen (1964)
and Johnson (1969): (1) if a single, median spine was found on the ventral surface of the
abdominal segments of a shrimp >30 mm TL, it was assumed to be a male; (2) If a
shrimp >30 mm TL lacked spines, it was called a female; (3) If a shrimp carried a blue-
green egg mass on the ventral surface of the abdomen or had a blue-green mass beneath
the dorsal surface of the carapace, it was assumed to be female; (4) All individuals <30
mm TL (which typically have an abdominal spine) were categorized as unknown sex,
unless criteria 3 was met.
Tagging consisted of an injection of non-toxic, acrylic paint just beneath the dorsal
surface of the second-to-last abdominal segment with a 30 gauge, 1.27 cm hypodermic
needle and 1 mL syringe. A similar method was used with juvenile and adults of a
popular food shrimp (Panaeus vannamei) and found to result in 99.9% and 100% tag
retention, respectively, after undergoing as many as 23 molts (Godin et al. 1995).
Upon molting, each shrimp was re-measured. Molt interval (i.e., the time between
two successive molts) was calculated for each individual, as well as a mean interval for
those individuals that molted more than once during the study. A linear regression model
was fit to describe the relationship between molt interval and shrimp body size. Mean
molt intervals for females and males were compared with a t-test.
To quantify growth rates of S. hispidus, a large scale tagging study was conducted in
three inshore and three offshore sites in the Upper Florida Keys, from May 14 to July 31,
2002. The offshore sites consisted of three sections of contiguous reef. The inshore reefs
were part of a series of small patch reefs found in shallower water interspersed with beds
of sea grass (Thalassia testudinum). Further details of these sites are presented in Table
Quantifying growth in crustaceans is difficult because of their loss of all hard parts as
a result of molting. This problem can be overcome through the use of internal tags that
identify individuals and indicate if an individual has molted (Ennis 1972, Taylor and
Hoenig 1990, Godin et al. 1995, Chen and Kennelly 1999).
All shrimp in each site were tagged underwater (see procedure above), measured (mm
TL), and sexed (see criteria above). A total of six colors were used (black, green, blue,
red, orange, and yellow) and distance between two shrimp with the same color was
maximized and greater than their estimated home range (-1 m2) (Limbaugh et al, 1961,
Stolen 1964, Young 1979), so that individuals could be distinguished. I also ablated the
left exopod of each shrimp. Upon subsequent molting, the ablated exopod is replaced
with a new exopod, therefore indicating that a tagged shrimp had molted (Linnane and
Mercer 1998). This technique was verified for S. hispidus in the molt interval lab study
All holes where shrimp were found were marked with numbered flagging tape tied to
a weight and mapped to PVC paper for use underwater. I then conducted extensive
weekly surveys of each study site. In these surveys, I 1) recorded presence/absence of
previously tagged shrimp, 2) tagged, measured, and sexed any new shrimp, and 3) re-
measured and re-clipped any individuals who were missing their molt indicators. Each
week, prior to surveying, the maps of each site were updated with the locations of newly
tagged shrimp in order to assure all tagged individuals were included in the surveys.
Based on the results from the molt interval study (see Results) and previously published
data (Johnson 1977), this study ran for 70 days, in order to maximize the probability of an
individual molting twice in the duration of the study.
Time to each molt (weeks) as well as growth increments (i.e., change in length after a
single molt) were measured for all tagged shrimp that were observed to molt in the
tagging study. Using shrimp that molted more than once, the weekly probability of
molting was estimated. Due to the relationship between shrimp size (mm TL) and molt
interval (days) from the molt interval study (see Results), I expected shrimp of different
sizes to have different molt intervals (weeks) in the tagging study. Therefore, I
conducted a survivorship analysis (exponential model) to estimate the time to molt (Tm;
weeks) as a function of shrimp size (s) as
Tm = e(a bs) 1.1
where a and b are fitted parameters (Allison 1995). Therefore, the weekly probability,
Pr(m), of a shrimp molting was estimated as
Pr(m)= 1/e(a+ bs). 1.2
This weekly probability of molting, Pr(m), was then incorporated into a crustacean
growth model (detailed below).
The relationship between growth increment and pre-molt size was estimated using
polynomial regression (Sokal and Rohlf 1996). The best-fit model for this relationship
was used to provide estimates of growth increment for a given pre-molt size, also to be
used in the crustacean growth model (detailed below). Additionally, deviations from this
predicted growth increment (Gd) were calculated, to provide estimates of variation in
growth. These deviations were also incorporated into the growth model.
I modeled S. hispidus growth through the application of an approach first used by
Chen and Kennelly (1999), referred to as the probabilistic stepwise growth curves
(PSGC) approach. This approach generates a distribution of growth curves that mimic a
discontinuous pattern of growth while incorporating intrinsic variation in the data. A
simulation of a population of shrimp was generated using the following sequence of
steps: (1) a size at settlement, L1, was chosen from the observed distribution of settler
sizes (see Results); (2) for each subsequent week an individual molted with probability Pi
(Equation 1.2); (3) if no molting occurred, then the same process was repeated for the
next week; (4) if the individual did molt then its new size was determined as L2 = L1 +
AL + Gd, where AL is the predicted growth increment (Equation 1.3) and Gd is a random
deviation from this predicted increment. This process (steps 2-4) was repeated for 100
shrimp for 100 weeks, in order to obtain a distribution of growth curves. Mean size (+
standard deviation) at age was estimated from this distribution of growth curves, in order
to describe growth of the average shrimp. This growth model was constructed to provide
an estimate of growth for an average shrimp and, therefore, all differences in size
structure among the sites used in this study (see Chapter 2) were ignored and all shrimp
were treated as if from a single population.
In May 2001, 33 gravid females were collected from various locations in the Upper
Florida Keys. Additionally, in July 2002, eight gravid females were purchased from a
local collector working in the Upper Florida Keys (Sea Life Inc.). Upon
collection/purchase, females were measured (mm TL) and weighed (in 2001 only). Three
dimensions of the egg masses were measured, mass length (1m), mass width (wm), and
mass height (hm), and egg mass volume (Vm) was estimated as 47i(lm*wm*hm/8).
Samples of the eggs were collected (-20 eggs per female) and preserved in 10%
buffered formalin (2001) or 95% EtOH (2002). Ten eggs from each female were
randomly selected and the diameter of each egg was measured (mm) with a dissecting
microscope integrated with an image analysis program (Image Pro Plus). Mean egg
diameter (de) was estimated for each female, and mean egg volume (Ve), for each female
was calculated as 7r(de3)/6 (Zhang et al. 1998). Finally, egg number (Ne) was estimated as
Because these measurements (female length, female mass, Vm, and Ne) were assumed
to be allometric, they were log-transformed (base 10) and fit with linear regression
models to investigate the relationships between logio(female length) and logio(wet body
mass), logio(Vm), and logio(Ne), respectively (LaBarbera 1989).
To investigate possible influences of the egg preservation method or the effect of
female length on egg size, a two-way ANCOVA was conducted to estimate the effect of
logio(female length), preservation method, and their interaction on logio(de).
Size at Settlement
Both larval light traps and artificial settlement substrates were unsuccessful in
collecting S. hispidus larvae. However, a total of 14 individuals were collected from the
artificial reef (n=7) and survey studies (n=7). The average ( SD) TL of these individuals
was 17.61 2.84 mm. One individual was considered an outlier (27 mm TL). When this
outlier was excluded, mean ( SD) TL of settlers was 16.88 0.89 mm, with individuals
ranging from 14.8-18.4 mm TL.
There were a total of 23 individuals used in this study. Of these, 14 had multiple
molts, so the molt intervals were averaged for each individual. Virtually no growth was
observed for individuals in this laboratory study. The overall mean standardd error)
intermolt duration was 23.18 1.65 days. The molt interval was positively related to
shrimp length (Linear regression: bse=0.60 0.09, p<0.0001, r2=0.6931; Figure 1-1).
There was no significant difference in the molt interval between males and females
(t12=0.019, p=0.9851). Mean (SE) molt interval for females was 25.07 2.52 days
(n=7), whereas that for males was 25.0 2.65 days (n=7). In addition, all ablated
exopods were replaced upon subsequent molts, as well as 100% retention of internal tags.
Fifty-five of the 83 tagged shrimp were observed to molt over the course of the 10
week study, and 44 of these shrimp molted more than once. This resulted in 98
measurements of growth increments and 44 measurements of molt interval. In one case,
a shrimp was not sampled for several weeks and later re-sighted having molted; this
individual was excluded from the analysis.
Survivorship analysis revealed a significant effect of shrimp size (mm TL) on time to
molt (weeks) (Wald's Chi-square: X2=6.03, p=0.0140). Estimates for the fitted
parameters, a and b (SE), were as follows: a = -0.29300.4980 and b = 0.03330.0136
(to be used in Equation 1.2). The estimated weekly probability of molting decreased
rapidly as shrimp size increased (Figure 1-2).
The mean growth increment ( SE) was 1.64 0.23 mm, ranging from -4.2 to 7.9
mm, and varied substantially among individuals with different pre-molt sizes. The
relationship between pre-molt size and growth increment was hump shaped, and best
described by a quadratic model:
ALi = a + b(Li) + c(Li)2 + ;i, 1.3
where AL is the growth increment after a molt, Li is the pre-molt size, and si is an error
term (Polynomial Regression: F2,95=8.72, p=0.0003; Figure 1-3), compared to a linear
(Linear Regression: F1,96=8.31, p=0.0049) and cubic model (Polynomial Regression:
F3,94=5.76, p=0.0012). The quadratic model provided parameter estimates ( SE) of a=-
2.5265 2.05, b=0.32 0.13, and c=-0.0051 0.002 (Figure 1-3). However, growth was
highly variable, with pre-molt size accounting for only 15.5% of the variance in growth.
Growth simulations showed that size increased rapidly during the first 40 weeks,
gradually slowing, and essentially stopping after approximately 60 weeks (1.15 years).
Shrimp reached maximum size (-53 mm TL) by approximately 62 weeks (1.19 years)
(Figure 1-4). Variation in size at age increased as age increased until about 35 weeks
(0.67 year), when it began to decrease slightly.
There was no effect of preservation method on loglo(ed) (ANCOVA: F1,37=0.83,
p=0.3669). Therefore, all females were included in the regression analyses. Averaged
across the entire sample, female length (TL) was 46.80 0.91 mm (n=41), wet body
mass was 3.01 0.28 g (n=33), egg mass volume was 292.48 37.98 mm3 (n=41), egg
diameter was 0.617 + 0.014 mm (n=41), egg volume was 0.131 0.009 mm3 (n=41), and
EN was 2,557 337 eggs/brood (n=41) ( SE). Most of these variables covaried
positively with one another. Logio(wet body mass) was significantly related to
loglo(female length) (Linear Regression: aSE=-6.08 0.30, bSE=3.89 0.18,
F1,31=474.28, p<0.0001, n=33, r2=0.94). Given the high association of these two
variables, I focused on relationships with TL, although they can be readily converted to
wet body mass.
As loglo(female length) increased, logio(Vm) increased (Linear Regression: aSE=-
4.99 + 1.10, bSE=4.40 0.66, F1,39=44.42, p<0.0001, n=41, r2=0.53; Figure 1-5) and
logio(Ne) increased (Linear Regression: aSE=-4.21 1.29, bSE=4.48 0.78,
F1,39=33.41, p<0.0001, n=41, r2=0.46; Figure 1-6). There was no significant relationship
between logio(de) and loglo(female length) (ANCOVA: logio(female length), F1,37=0.70,
p=0.4073; interaction, F1,37=0.83, p=0.3670).
Size at Settlement
Previous estimates of size at settlement for S. hispidus are highly variable, ranging
from last larval stage measurements of 21-31 mm to post larva measuring 10-31 mm
(Gurney and Lebour 1941, Williamson 1976, Fletcher et al. 1995). A portion of the
substantial difference in last and post larval length can be attributed to the rostrum of the
last larval stage, accounting for as much as 31% of its total body length (Gurney and
Lebour 1941). It has been hypothesized that it may be possible for larvae in the last stage
to change to another practically identical larval stage and continue to grow to a larger
size, due to extended periods of feeding in the water column (Gurney and Lebour 1941,
Zhang et al 1998). With the presence of delayed metamorphosis in S. hispidus (Fletcher
et al. 1995), this hypothesis may be supported, thus possibly contributing to the high
variability in the measurements of last larval size. All individuals encountered in this
study were of the post larval stage and within the size range of those described in Gurney
and Lebour (1941) and Williamson (1976). However, the variation in the size of
individuals from this study was much smaller than those from Gurney and Lebour (1941)
and Williamson (1976). This may be due to differences in environmental factors such as
temperature or depth in the regions studied. Gurney and Lebour (1941) only collected
individuals from Bermuda, sometimes at great depths (300 m), while Williamson (1976)
collected individuals from the Indian Ocean. This suggests that there may be extensive
spatial variation in the size at settlement of S. hispidus. However, Gurney and Lebour
(1941) and Williamson (1976) only vaguely describe those shrimp that they considered
post-larvae and, therefore, it is possible that they included larger juveniles. Further
studies are needed to describe spatial variation in S. hispidus size at settlement.
Previously, the only published data on molt interval of S. hispidus was for mature
females. The results from this study indicate that younger smaller shrimp molt more
frequently than larger older individuals. This relationship has also been documented in
other crustacean species (Tremblay and Eagles 1997, Chen and Kennelly 1999, Comeau
and Savoie 2001). This shift in molt interval may be due to the onset of sexual maturity,
and, in females, the brooding of eggs. Because molting and brood development are
related in S. hispidus, the increased molt interval may be required to assure sufficient
time for embryo development (16 days) and oocyte maturation. What maintains male
molting frequency is unknown at this point. Since male molt interval is not different
from that of females, it is possible that the cycle of female molts is what maintains male
The time period between molts was estimated as the time between tagging with the
molt indicator and the time at which the exopod was replaced. This estimation assumes
that shrimp molted just once before being re-measured and re-tagged. This assumption
may introduce additional error in modeling the weekly probability of molting. However,
the molt interval study (Figure 1.1) indicated that the minimum time interval between
successive molts was 9 days. Therefore, surveys were conducted at weekly intervals in
order to minimize this error.
The relationship between growth increment and pre-molt size indicated that smaller
shrimp have smaller growth increments, which then increase until approximately the size
at maturity (30 mm TL) when they gradually begin to decrease again (Figure 1.3). Given
that larger shrimp tend to molt less frequently and their growth increment begins to
decline, it is apparent that growth rates tend to decline as shrimp size increases. This is
supported by the growth curves generated by the PSGC approach.
Similar to Chen and Kennelly (1999), pre-molt size only accounted for 15.5% of the
variation in growth increment. It is apparent that other external factors may influence
growth increment. Both abiotic and biotic factors, including temperature, depth, and food
supply, may also be influencing growth increments (Annala and Bycroft 1988, Chen and
Kennelly 1999, Hartnoll 2001). Further studies are needed to identify the effects of these
factors and to potentially model growth of individuals from different habitats separately
(see Chapter 2).
The growth curves generated in this study indicate that the average female reaches
sexual maturity (30 mm TL) 4 weeks after settlement. Variation in mean size seemed to
decrease by approximately 50 weeks, at about 50 mm TL. This is probably due to a
decreased growth increment at this size (Figure 1.3). Finally, it is worth noting that this
model is based on growth data taken during the summer. Therefore, the growth rates
generated by this study may be an overestimation of annualized growth, due to the
warmer temperatures in the summer months. Also, since there were differences in the
size-structure of the populations used in this study, I re-constructed this model for each
population (inshore and offshore) based on their growth increments (see Chapter 2).
Since the tagging study used all sized individuals in the prediction of growth
increments and each run started with a settler, the mean growth curve (Figure 1.4) is
based on true post-settlement age, and thus, provided a means of ageing S. hispidus.
Previously, the most reliable method for ageing crustaceans was through the
measurement of the concentration of lipofuscin deposits, irregular yellow-fluorescing
granules found in the post-mitotic tissues of senescing animals (Sheehey et al. 1994).
However, this method is only possible in species that can be reared in the laboratory, in
order to use known-aged individuals to devise a statistical model that predicts age from
lipofuscin concentration (Sheehey 1990, Sheehey et al. 1994). Sheehey et al, (1994)
concluded that lipofuscin concentration was more accurate in predicting crayfish age than
a model using body size measurements. However, the model that Sheehey et al. (1994)
used in predicting age from body size measurements was a von Bertalanffy growth
model. The von Bertalanffy growth model is commonly used in describing fish growth,
which is assumed to be continuous (Chen and Kennelly 1999), whereas crustacean
growth is discontinuous. Since the PSGC approach produces growth curves that mimic
discontinuous growth and incorporates intrinsic variation, it may provide a more realistic
means with which to age crustaceans than the von Bertalanffy model. Therefore, the
PSGC approach may provide comparable estimates of age as a model predicting age from
lipofuscin concentration. Further studies are needed to test this assumption.
The positive, linear relationship between female wet body weight and total length is
consistent with observations made for S. hispidus (Zhang et al. 1998). However, the
slope produced by this study (bSE=3.89 0.18) was significantly different (t53=-64.74,
p<0.0001) from that of Zhang et al. (1998) (bSE=3.12 0.14; Figure 1-7) (Zar 1996).
This may be due to different sized females used in each study. For example, as
mentioned earlier, the mean female mass for this study was 3.01 g, whereas that for
Zhang et al. (1998) was 1.40 g.
This study shows that total length is a good predictor of fecundity, also consistent with
previous observations (Zhang et al. 1998). However, loglo(Vm) seems to be a better
measure of relative fecundity than logio(Ne), when regressed against logio(female length).
One explanation for this may be variation in measuring egg diameters (critical for egg
number estimations), since not all eggs were perfectly spherical. This argument is
supported by the non-significant effect of logio(female length) on logio(de). Further
studies are needed to identify the true size at sexual maturity for both males and females,
possibly through the use of histology.
The results of these studies begin to provide valuable information for the possible
future management of S. hispidus for the marine ornamental trade. I provide a method
for ageing S. hispidus, and possibly other crustacean species, without the need of
successful larviculture. In addition, I provide an easily attainable measurement of
relative fecundity (Vm) with minimal disturbance. With additional research, particularly
to investigate: 1) the influence of environmental factors on S. hispidus growth, 2)
estimation of the true size at maturity, and 3) physical and environmental factors that
contribute to population dynamics and demographics, managers can begin to develop
management plans based on its life history.
Table 1-1. Details of sites used in the growth
Site Depth Distance Reef type Coordinates
(m) from shore
Davis Deep 14.6 7.60 contiguous 240 55.461'N, 800 30.019'W
Crocker Deep 14.6 7.02 contiguous 24 54.279'N, 800 31.681'W
Crocker Shallow 6.71 6.69 contiguous 240 54.454'N, 800 31.672'W
Rock 1 3.05 1.63 patch 240 56.548'N, 800 33.666'W
Rock 2 3.66 1.60 patch 240 56.991'N, 800 33.157'W
Rock 3 5.79 2.04 patch 240 57.256'N, 800 32.774'W
D = 0.6001L 2.3815
r = 0.6931
Linear Regression (all points)
15 20 25 30 35 40 45 50 55
Figure 1-1. Linear regression (solid line) of mean molt interval (days) on body size (mm
TL) of all S. hispidus. Closed squares represent individuals of unknown sex, open circles
are females, and closed circles are males. Di is the molt interval and Li is initial length.
Sample sizes are as follows: unknown, n=9; female, n=7; male, n=7.
p = 0.0140
0 0.5 -
10 15 20 25 30 35 40 45 50 55 60 65
Length (mm TL)
Figure 1-2. Estimated weekly molting probability as a function of shrimp size (mm TL)
based on survivorship analysis (exponential model). Parameter estimates for a and b
(Equation 1.2) are provided above, where Pr(m) is the estimated weekly molting
probability and s is shrimp length (mm TL) (n=44).
Ginc = -2.5265 + 0.32Li 0.0051(Li)2
* 0 0
I I I I I I I I I
15 20 25 30 35 40 45 50 55 60
Pre-molt Length (mm)
Figure 1-3. Polynomial regression (solid line) of growth increment (mm) on pre-molt
length (mm TL) of S. hispidus. Parameter estimates for a, b, and c (Equation 1.3) are
provided in the above regression equation, where Ginc is the growth increment and Li is
the pre-molt length (n=98).
0 Og *
0 10 20 30 40 50 60 70 80 90 100
Post-settlement Age (weeks)
Figure 1-4. Mean (dots) and standard deviations (error bars) of length (mm TL) at post-
settlement age (weeks) resulting from 100 simulations of the growth model.
log,,(Vm)= -4.99 + 4.4010og,,, !im.klI length)
R2 = 0.53
Figure 1-5. Relationship between female length (mm TL) and egg mass volume (mm3) in
S. hispidus (n=41). Equation and regression line (solid line) represent linear regression of
logio(female length) (mm TL) on logio(Vm) (mm3) where Vm is egg mass volume.
logl0(Ne) = -4.21 + 4.481og,,,! i~ .ik. length)
II I I
30 40 50 60
Figure 1-6. Relationship between female length (mm TL) and egg number (eggs/brood)
in S. hispidus (n=41). Equation and regression line (solid line) correspond to linear
regression of logio(female length) (mm TL) on logio(Ne) (eggs/brood) where Ne is egg
0 0 0
4 O O
0.8 0 */ Zhang et al. 1998
Zhang et al. 1998 Linear Regression
0.6 / O Present Study
S-- Present Study Linear Regression
0.4 1 1
30 40 50 60
Figure 1-7. Relationship between female length (mm TL) and female wet body mass (g)
in S. hispidus from Zhang et al. (1998) (closed circles) and present study (open circles).
Dotted line represents regression of logio(female length) on logio(female mass) from
Zhang et al. (1998), solid line represents that of present study. Sample sizes are as
follows: Zhang et al. (1998), n=24; Present Study, n=33.
EFFECTS OF SETTLEMENT, POST-SETTLEMENT MORTALITY, AND GROWTH,
ON THE POPULATION SIZE-STRUCTURE OF THE BANDED CORAL SHRIMP,
Stenopus hispidus, IN THE UPPER FLORIDA KEYS
Spatial variation in population structure among marine invertebrate populations has
been well documented (von Montfrans et al. 1995, Miron et al. 1999, Pascual et al. 2001).
Typically, studies of this variation focus on one phenomenon (e.g., settlement, growth,
movement, or post-settlement mortality). However, the structure of marine invertebrate
populations probably does not depend on any one process alone, but rather on several
processes acting together.
Population structure is often linked to the settlement rates and larval supply to a
habitat (Minchinton and Scheibling 1991). For instance, it has been argued that the
number of larvae settling to a habitat determines the number of older individuals found in
that habitat (Sale 1991). However, concentrating on settlement by itself may cause one to
dismiss other processes that are equally likely to affect population structure, such as post-
settlement survival, movement, or growth. If spatial variation in post-settlement
mortality exists between two habitats that receive equal levels of settlement, the two
habitats will not be structured similarly (Rochette and Dill 2000, Pascual et al. 2001).
Furthermore, if one fails to detect a relationship between adult numbers and settlement,
post-settlement movement or mortality may contribute to this lack of correlation
(Robertson 1988). Most studies that identify post-settlement mortality as the primary
factor contributing to populations often fail to quantify post-settlement movement (but
see Frederick 1997) and thus confound these two processes.
Finally, differential growth rates between habitats may contribute to differences in
population structure. Kube et al. (1996) found that the growth rates of two species of
marine bivalve were considerably lower in a brackish sublittoral zone of the Southern
Baltic Sea, compared to growth rates from a full marine environment. Another
environmental factor to which differential growth rates are often attributed is
temperature, especially in crustaceans (Hartnoll 2001). Clearly, two habitats that share
similar settlement, post-settlement mortality, and movement rates, but differ in
temperature, possibly due to depth, might be expected to differ in population structure as
These processes can also interact to affect the population structure of an organism.
For example, in a species of fish in which size-selective mortality was present, Werner et
al. (1983) found that smaller fish underwent lower growth rates in the presence of a
predator, due to behavioral responses. In fish, it has been hypothesized that lower growth
rates, coupled with size-selective mortality, could prolong the period of increased
vulnerability to predators (Leggett and DeBlois 1994), increase mortality (Werner et al.
1983), and/or increase the amount of time it takes for an individual to reach a size-refugia
and sexual maturity (Miller et al. 1988, Bailey and Houde 1989, Werner et al. 1983).
Thus, differential growth rates between habitats, whether through differential food
availability, temperature, or behavioral responses to predation can give rise to spatial
variation in population size-structure between the habitats.
Understanding which processes affect the population structures of marine organisms,
and to what degree, is critical for understanding the dynamics of these systems. With a
better understanding of the population dynamics of these organisms, management
practices can be tailored for particular areas or habitats. One fishery in need of
information for the development of management practices is the marine ornamental trade.
The marine ornamental trade is growing at a high rate, with documented declines in local
fish abundances and habitat quality, due to current practices (Tissot and Hallacher 1999).
Over 18 species of cleaner shrimps are collected for marine aquaria (Fletcher et al.
1995). In addition to concern about over-harvesting and harvest effects on habitat
quality, it has been hypothesized that the removal of cleaner shrimps might also lead to
declines in the local fish populations (e.g., via increased local fish diseases) (Fletcher et
al. 1995, Zhang et al. 1997), therefore having broader implications for the ornamental
trade and reef communities.
One of the most popular cleaner shrimps in the marine ornamental trade is the banded
coral shrimp, Stenopus hispidus (Olivier, 1811) (Zhang et al. 1998). Stenopus hispidus is
a reef associated cleaner shrimp (Decapoda: Stenopodidae) with a worldwide
distribution. As adults, S. hispidus are found in crevices or overhangs in reefs at depths
ranging from <1 to 210 meters and are extremely limited in post-settlement dispersal (<1
m2) with males exhibiting territorial behavior within this area (Limbaugh et al. 1961,
Stolen 1964, Young 1979, Fletcher et al. 1995). Adults are typically found in
reproductive pairs (Limbaugh et al. 1961, Johnson 1969, Young 1979), possibly formed
as juveniles (Limbaugh et al. 1961). After a molt, the female typically mates with her
long-term mate, and a mass of blue-green eggs is deposited on the swimmerets (Zhang et
al. 1998). As the larvae develop, the blue-green eggs begin to lose this pigmentation and
darkly pigmented eyespots begin to appear. Hatching typically occurs within 16 days of
spawning (Young 1979). Stenopus hispidus larvae have a highly variable larval duration
(17-30 weeks) and are capable of delaying metamorphosis until suitable habitat is
encountered (Fletcher et al. 1995). It is still unknown what settlement cues S. hispidus
The overall objective of this chapter is to 1) compare the size-structure of populations
of S. hispidus in different habitats and 2) examine the mechanisms that produce spatial
variation in population size-structure. In particular, I examine i) settlement, ii) post-
settlement movement and mortality, and iii) growth rates in inshore and offshore habitats
of the Upper Florida Keys.
During the summers of 2001 and 2002 (May-August), I conducted surveys in both
inshore and offshore regions of the Upper Florida Keys (Table 2-1) to quantify spatial
and temporal variation in S. hispidus abundance and size-frequency distributions. The
surveys consisted of thoroughly searching each reef and surrounding rocks for S.
hispidus. Every shrimp encountered was collected, measured (mm TL), and sexed (male,
female, and unknown) underwater, and released. Sex was assigned using a modification
of criteria given by Stolen (1964) and Johnson (1969): (1) if a single, median spine was
found on the ventral surface of the abdominal segments of a shrimp >30 mm TL, it was
assumed to be a male; (2) If a shrimp >30 mm TL lacked spines, it was called a female;
(3) If a shrimp carried a blue-green egg mass on the ventral surface of the abdomen or
had a blue-green mass beneath the dorsal surface of the carapace, it was assumed to be
female; (4) All individuals <30 mm TL (which typically have an abdominal spine) were
categorized as unknown sex, unless criteria 3 was met.
For all reefs that were surveyed in both 2001 and 2002 (three inshore and two
offshore), I evaluated the effects of region, site, year, and their interactions on shrimp
total length (log-transformed) using a nested-ANOVA model with site nested within
region. In the case of a significant year effect in this analysis, separate nested-ANOVA
models were run for each year, testing for region and site effects, again with site nested
within region. All sites for a given year (2001: five sites, 2002: 10 sites) were included in
these analyses, including those that were not surveyed both years. In the case when a
significant site effect was found, post-hoc comparisons of means were conducted to see
which sites differed within and between regions (Younger 1998).
To quantify spatial variation in settlement of S. hispidus in the Upper Florida Keys, I
used artificial reefs that were cleared of all fishes and invertebrates on a weekly basis. In
the summer of 2001, two arrays of five artificial reefs were deployed in each of the
inshore and offshore regions. All artificial reefs consisted of small boulders of limestone,
taken from a single quarry in Miami, Florida. Reefs were deployed within a few days of
one another, in June 2001, and were approximately 1 m2 in basal area. In the summer of
2002 (May-July), I conducted 10 weekly surveys and collections from each artificial reef.
Collections consisted of removing all fishes and invertebrates using Eugenol (an
anesthetic, also known as clove oil), and preserving them in 95% EtOH for later
identification and measuring.
To check for possible outliers (i.e., migrants) among the settlers collected, I used
estimates of size at settlement of S. hispidus from a separate study (see Chapter 1). This
process involved estimating a mean size at settlement, and removing all individuals who
were greater than three standard deviations from this mean. Individuals collected in this
study that were larger than that upper limit (26.11 mm TL) were considered migrants and
removed from the analysis. No migrants were found in this study.
Counts of shrimp collected, for each array of reefs on each collection day, were
square-root-transformed and analyzed with a repeated measures ANOVA, to test for the
effect of site, transect (nested within site), and week (the repeated factor) on the number
of settlers in each region.
Post-settlement Mortality and Movement
Tagging study. To quantify spatial and temporal variation in natural post-settlement
mortality rates of S. hispidus, I conducted a tagging study at three inshore and two
offshore sites in the Upper Florida Keys during the summers of 2001 (July-August) and
2002 (May-July). These sites were among the same sites used in the growth study from
Chapter 1, and the population structure study above (Table 2-2).
Shrimp in each site were tagged (Chapter 1; Godin et al. 1996), measured (mm TL),
and sexed. To keep track of individuals, a total of six colors were used (black, green,
blue, red, orange, and yellow) and distance between two shrimp with the same color was
maximized and always greater then their estimated home range (-1 m) (Limbaugh et al,
1961, Stolen 1964, Young 1979). Holes where shrimp were found were marked with
numbered flagging tape tied to a weight and mapped onto PVC paper for use underwater.
I then conducted extensive weekly surveys of each study site. In these surveys, I: 1)
recorded presence/absence of previously tagged shrimp, 2) tagged, measured, and sexed
any newly encountered shrimp, and 3) in 2001, measured the distance moved (when an
individual moved from its original site). Each week, prior to surveying, the maps of each
site were updated with the locations of newly tagged and relocated shrimp in order to
assure all tagged individuals were included in the surveys.
Since each shrimp was individually tagged, the time to disappearance of an individual
was known. These times were analyzed using a survivorship analysis (Cox' Proportional
Hazards Model), which allows for the estimation of the effects of covariates in shrimp
disappearance (Barbaeau et al. 1994, Allison 1995). Because of the small home range
reported for this species, I assumed that disappearances were the result of mortality rather
than movement. To eliminate tagging induced mortality from estimates of mortality, I
excluded all shrimp that died within the first week of tagging. Covariates considered in
the survival analysis included shrimp size (mm TL), region (inshore or offshore), site
(five sites used in the study), and year (2001 or 2002). I report significant effects in the
model as well as estimates of the hazard ratio, which can be converted to estimate the
percent change in survivorship for each one-unit increase of quantitative covariates (i.e.,
body size) as
Pr(s) = 100*(-h), 2.1
where h is the hazard ratio (Allison 1995).
I compared distances that shrimp moved in inshore vs. offshore sites using a t-test.
Analyses were based on mean movement distances (per week) for each shrimp. Analyses
were repeated after excluding all weekly movement of 0 m. Finally, I compared the
proportion of movements (>0 m) from the two regions through the use of a Chi-square
Tethering experiments. To further investigate spatial variation in predation and size-
selective mortality, I conducted a tethering experiment from August 5-8, 2002, using the
five sites from the tagging study. In previous studies, I found that translocating shrimp,
without tethering, resulted in the disappearance of all individuals within 24 hours, due to
unknown causes. Therefore, tethering was necessary for this study, to assure no
translocation-induced movement. All naturally occurring shrimp were removed from the
study sites prior to experimentation. Seventy shrimp were purchased from a local
collector operating in the Upper Florida Keys (Sea Life Inc.). None of these shrimp were
collected in any of the study sites. Shrimp were sexed, measured, and separated into two
size categories; small: <30 mm TL and large: >40 mm TL. Each shrimp was tethered to
an 85 g weight with a 250 mm length of 2.72 kg test monofilament line by securing a
loop of the monofilament line to the carapace with a drop of cyanoacrylate glue (Pile et
al. 1996, Acosta and Butler 1999). Tethered shrimp were then held in a closed aquarium
system, in individual containers, until deployment the next day. A total of 40 shrimp
were randomly assigned to the offshore region (10 of each size category in each of 2
sites) and 30 to the inshore region (4-6 of each size category in each of 3 sites).
Experimental shrimp were placed into holes where a shrimp had previously been
encountered. As with the tagging study, a survivorship analysis (Cox Proportional
Hazards Model) was used to test for the effects of region (inshore or offshore), site (five
reefs used in study), and size category (small or large) on survival.
Typically, tethering studies include a caged treatment of tethered individuals in the
field to control for potential tethering effects (Peterson and Black 1994, Rochette and Dill
2000). However, caging tethered shrimp in the wild was not possible. Therefore, a
separate lab experiment was conducted to assess the tether effect (Pile et al. 1996). Forty
shrimp were purchased from the same local collector. Shrimp were measured and placed
into one of the two size categories (as above). Ten shrimp of each size category were
then randomly assigned a treatment, un-tethered or tethered (as described above although
with 100 mm tethers). Shrimp were then randomly assigned to a holding tank (in
individual containers) and monitored for a week for mortality and molting activity.
Survivorship analysis (Cox Proportional Hazards Model) was used to test for the effects
of tethering (tethered or non-tethered), size category (small or large), and tank (tank 1 or
tank 2) on the survivorship of individuals.
Predator abundance. To characterize variation in predator abundance in the two
regions, I surveyed each of the five sites by counting all possible predators (including
invertebrates) within a 1 m radius of each marked hole from the tagging study. Fish
predators surveyed were among the following families: Haemulidae, Lutjanidae,
Serranidae, Scorpiaenidae, Tetraodontidae, Synodontidae, Kyphosidae, Pomacentridae,
Labridae, and Sciaenidae. The only invertebrate predators encountered were mantis
shrimps (Order: Stomatopoda). The abundance of each predator from each hole was
square-root-transformed and analyzed with a k-means cluster analysis (STATISTICA
1999) to see if the clusters generated corresponded to the designated regions. Two
clusters were generated in this analysis.
Tagging study. The 2002 tagging study was modified to compare shrimp growth
between the inshore and offshore regions. The left exopod of each shrimp's uropod was
clipped. Since all hard parts are replaced at molting (Chapter 1; Linnane and Mercer
1998), I could identify tagged shrimp that had molted by the presence of the left exopod.
All tagged shrimp with an intact left exopod were re-measured and re-clipped.
A mean pre-molt length (mm) and mean growth increment (mm) was calculated for
each individual that was observed to molt during the course of this study. One individual
was missed and later rediscovered. Since the number of molting events that occurred in
this interval could not be assigned, the growth increment associated with this interval was
excluded from the analysis. A two-way ANCOVA tested for the effects of region and
mean pre-molt length on mean growth increment. In the case that mean pre-molt length
was found to significantly effect mean growth increment, separate linear regression
analyses for each region were conducted to describe this relationship.
As mentioned earlier, temperature has been known to affect crustacean growth,
typically causing faster growth at higher temperatures (Hartnoll 2001). Because the
inshore and offshore regions used in this growth study differed in depth, and temperature
is generally negatively correlated with depth (Lee et al. 1992), I measured bottom
temperature in each of the two regions, several times throughout the summer. Mean
temperatures were calculated for each region and compared with a t-test.
Growth model. Once growth in each region was evaluated in the above study, I
applied a crustacean growth model (Chapter 1; Chen and Kennelly 1999) in order to
model the growth of shrimp in each region. To do this, I used the same distribution of
settlers when choosing a start size, as well as the same weekly probability of molting
(Pr(m)) as described in Chapter 1 (Equation 1.2; Figure 1-2). However, the estimated
growth increment for a given pre-molt size was based on the linear regression analyses
conducted to describe the relationship between mean pre-molt length and mean growth
increment for each region. Therefore, the equations for estimated growth increment for
each region were
ALi = a + b(Li) + Si, 2.2
where ALi is the growth increment after a molt, Li is the pre-molt size, a and b are
parameter estimates provided by the linear regression models of each region, and si is an
error term. As in Chapter 1, deviations (Gd) from the predicted growth increment for
each region were calculated, to provide estimates of variation in growth. These
deviations were also incorporated into the growth models. Using the same sequence of
steps as in Chapter 1, I applied this growth model to each region for 100 individuals for
100 weeks each. Mean size (+ standard deviation) at age was estimated from the
distribution of growth curves for each region, in order to compare the growth trajectories
between the two regions.
A total of 261 shrimp were measured among the sites surveyed in both in 2001 and
2002. Region (Nested ANOVA: F1,251=317.62, p<0.0001) and year (Nested ANOVA:
F1,251=13.90, p=0.0002) had significant effects on shrimp size, although there was no
effect of site or any of the interactions (Nested ANOVA: all F<1.94, all p>0.1325). The
year effect was strong in the offshore region but no so much in the inshore region (Figure
2-1). Overall, shrimp inshore were approximately 18 mm larger than those offshore.
Due to the significant year effect, and differences in the sites sampled in 2001 vs.
2002, each year was analyzed separately. In 2001, the five sites yielded 111 shrimp.
Regions differed significantly in shrimp body size (Nested ANOVA: F1,106=146.97,
p<0.0001), but there was no significant variation among sites (Nested ANOVA:
F3,106=1.55, p=0.2057; Figure 2-1). In 2002, the 10 sites yielded 236 shrimp. There were
significant differences among regions (Nested ANOVA: F1,226=178.29, p<0.0001) and
among sites within regions (Nested ANOVA: F8,226=2.97, p=0.0035; Figure 2-1). Also in
2002, among the three sites that had both shallow and deep areas surveyed, only one
(Crocker) exhibited a significant difference in mean shrimp size between the two depths
(p=0.0392), where the mean ( standard error) total length in the deeper area was
19.971.03 mm and that for the shallow area was 22.281.05 mm (Figure 2-1).
One shrimp was collected from the inshore artificial reefs, whereas 43 were collected
offshore. Using the criteria outlined above, no migrants were found in either region. The
average size ( SE) of all the settlers collected was 17.380.19 mm TL (range: 14.0-20.8
mm). There were significantly more settlers offshore than inshore (Repeated measures
ANOVA: F1,2=64.08, p=0.0152) but the number of settlers was unaffected by week and
transect within region (Repeated Measures ANOVA: all F<1.81, all p>0.1) (Figure 2-2).
Post-Settlement Mortality and Movement
Tagging experiment. To evaluate the patterns of mortality that were observed in the
tagging study, a full survivorship model was considered that included effects of region,
site, year, and shrimp size. Only the effect of shrimp size on survival was significant
(Wald's Chi-square: X2=12.18, p=0.0005), so the model was simplified to include only
shrimp size. This simplified model provided a more precise estimate of the hazard ratio.
Smaller shrimp had much lower survivorship than larger shrimp (Figure 2-3).
Specifically, for each 1mm increase in total length, the probability of survival increased
by 5.8% (Equation 2.1).
Overall, shrimp in both regions moved similarly (t57=1.599, p=0.115) with an average
(+ SE) displacement of 0.340.10 m (range: 0-9.33 m). With Om movements eliminated,
shrimp still moved similarly between the regions: 1.180.35 m (Range: 0.20-9.33 m)
pooled across regions. Finally, there was no significant difference in the proportion of
movements (>Om) between the inshore and offshore regions (X2=3.50, df=l, p>0.05).
The results from the tethering experiments identified no effects of tethering or body
size and no regional or site-specific difference in survival. In the laboratory control
experiment there were no differences in the survivorship of the tethered or un-tethered
individuals (Wald's Chi-square: X2=0.3099, df=l, p=0.5777). In addition, neither body
size (Wald's Chi-square: X2=1.23, df=l, p=0.2670) nor tank (Wald's Chi-square:
X2=1.5481, df=l, p=0.2134) affected shrimp survival (Figure 2-4). Similarly, in the field
experiment, neither shrimp size nor region significantly affected survivorship (Wald's
Chi-square: X2=0.4622, df=2, p=0.7936; Figure 2-5).
Predator abundance. In all, 94 holes were surveyed for this study and 24 predator
species identified. Sixty-six of these holes were surveyed in the offshore region and 28
from the inshore region. Overall, the two clusters generated by the k-means clustering
analysis did separate the holes from the two regions. Cluster 1 (inshore) consisted of 19
of the surveyed holes, all of which were found inshore. Only eight predator species were
found in this cluster, which was dominated by three predator species: 1) Haemulon
plumieri, 2) Anisotremus virginicus, and 3) Haemulonparra (descending order of mean
abundance; Figure 2-6). Cluster 2 (offshore) consisted of 75 surveyed holes, all 66 from
the offshore region and 9 from inshore. This cluster was not dominated by any one
predator in particular, but instead was made up of low abundances of all the predators
surveyed (except Kyphosus sectatrix and Lutjanus apodus; Figure 2-6).
Tagging study. Fifty-five shrimp molted during the course of this study. Both region
(ANCOVA: F1,52=14.05, p=0.0004) and mean pre-molt length (ANCOVA: F1,52=18.72,
p<0.0001) had significant effects on mean growth increment. The least-squares means (+
SE) for the growth increment in the two regions were 3.180.52 mm inshore and
0.270.39 mm offshore (Figure 2-7). There was no significant relationship between
mean pre-molt length and mean growth increment in the offshore region (Linear
Regression: F1,31=0.48, p=0.4942; Table 2-3; Figure 2-8). However, in the inshore
region, there was a significant negative relationship between mean pre-molt length and
mean growth increment (Linear Regression: F1,20=30.71, p<0.0001; Table 2-3; Figure 2-
The mean bottom temperatures differed significantly between the two regions
(t27=2.77, p=0.0101). Overall, the mean temperature (SE) of the inshore region was
27.640.320C, whereas that for the offshore region was 26.480.270C.
Growth model. The linear regression models to describe the relationship between
mean pre-molt length and mean growth increment for each region provided estimates of a
and b for Equation 2.2 (Table 2-3). With these parameter estimates, the growth models
revealed that the expected growth trajectories for the two regions differed substantially
(Figure 2-9). Consistently, the shrimp in the inshore region reached particular sizes
approximately four times faster than those in the offshore region. For example, the
inshore shrimp reached sexual maturity (approximately 30 mm TL) in approximately 4
weeks (post-settlement), whereas those offshore did not reach sexual maturity until
approximately 16 weeks (post-settlement).
The significant spatial variation in S. hispidus size structure is consistent with
observations made by local collectors in the Upper Florida Keys (Ken Nedimyer,
personal communication). Generally, this difference must stem from regional differences
in settlement and/or subsequent survivorship, movement, or growth.
Often, observed spatial variation in settlement is attributed to oceanographic processes
(Sponaugle and Cowen 1996, Balch and Scheibling 2000). Here I have shown significant
and temporally consistent differences in the supply of settlers to the inshore and offshore
regions. This difference may be due to oceanographic processes. In mid-late April, a
cold cyclonic gyre forms seaward of the middle and lower Keys, where the Florida
Current shifts from an eastward to northward flow (Lee et al. 1992). Prevailing easterly
winds circulate over this gyre and cause a convergence of Ekman flow, which facilitates
an inshore transport of pelagic larvae from the Florida Current to the fringing reefs (Lee
et al. 1992, Ogden 1997). This inshore transport of larvae to the fringing reefs could
cause larvae to reach the offshore study sites before those inshore, thus potentially
depleting larval supply to the inshore region. Other studies have identified tidal currents
and wind stress as factors influencing larval settlement (Sponaugle and Cowen 1996,
Paula et al. 2001). Further studies are needed to quantify the effects of tidal currents and
wind stress to the settlement of organisms in the Upper Florida Keys.
Spatial variation in settlement has also been attributed to larval habitat selection
(Miron et al. 1999, Paula et al. 2001). In addition, several studies have found that the
larvae of many marine organisms prefer to settle to habitats where conspecifics are found
(Sweatman 1985, Raimondi 1988, Sweatman and St. John 1990, Wellington 1992). As
mentioned earlier, it is unknown what settlement cues S. hispidus may be using. It is
possible that S. hispidus larvae may be using chemical cues from conspecifics on the
reefs as settlement cues. The offshore reefs were observed to have higher abundances of
S. hispidus, and therefore, may contribute higher amounts of a chemical settlement cue.
However, further studies are needed to identify precisely what cues S. hispidus larvae are
using for settlement.
The tagging study documented significant size-selective mortality in S. hispidus, in the
Upper Florida Keys. Furthermore, the pattern of size-specific mortality did not differ
between sites or regions. Smaller individuals have much higher mortality rates than do
larger individuals. These results are consistent with other studies in which size-selective
mortality has been observed in marine invertebrates (Barbeau et al. 1994, review in
Peterson and Black 1994, Pile et al. 1996, Moksnes et al. 1998). However, such studies
typically used tethering as a means of investigating differential mortality rates between
different sized individuals. Tethering studies are used to study potential predation rates
because investigators are concerned with post-settlement movement, which may be
confused with mortality.
Consistent with previous studies, the movement results from the present study indicate
that S. hispidus is extremely limited in post-settlement dispersal. Furthermore, the
majority of the post-settlement movements recorded were by larger inshore shrimp.
Since mostly larger shrimp were moving, one would suspect that the estimates of their
mortality might be inflated, not that of the smaller individuals. Thus, the higher mortality
rates of smaller individuals were likely not due to movement. Also, no tagged
individuals were encountered in regions where they were not expected, in either year. In
fact, five tagged individuals from the 2001 study were found in the same location at the
beginning of the 2002 study, approximately eight months later. These observations
suggest that there is no evidence for long distance movement between habitats.
Therefore, it is safe to assume that the size-selective mortality identified in the tagging
study is actual, and not simply an artifact of the study.
Also, during the tagging study, I observed several instances when a mature individual
(usually male) would move back and forth between rocks up to nine meters away, to be
found with different individuals of the opposite sex. This suggests that S. hispidus,
although pair bonded, may not be completely monogamous.
Despite strong evidence for size-selective mortality in the tagging study, there seems
to be no evidence of it from the tethering study. However, these results may be
inconclusive because of inherent difficulties with this experiment. Although tethering did
not seem to effect survivorship in the control, additional stresses or biases, inherent of the
field experiment, may have caused increased mortality in the field study. These stresses
and biases include: 1) drastic temperature increases associated with introducing shrimp to
sites, 2) depleted oxygen concentration in holding containers as the day went on, and 3)
predators taking notice to divers putting shrimp down. Survivorship fell drastically in the
first day but seemed to slow down by day two, where it became somewhat stable to the
end of the experiment (Figure 2-5). This is evidence for an increase in mortality due to
the experimental manipulation itself.
Based on the predator surveys, it is clear that the regions differ substantially in the
assemblage of potential predators. There is no information available about the feeding
rates of any of these species on S. hispidus. I did, however, see some of the predator
species feeding on S. hispidus in the context of the tethering study and population
structure surveys (e.g., Haemulonplumieri, Ephinephelus cruentatus, and Stomatopoda).
Further studies are needed to categorize actual S. hispidus predators and characterize
feeding rates, in order to better define and compare the predator assemblages between the
The significant difference in bottom temperature between the inshore and offshore
region may contribute to the differential growth rates between the two regions. However,
the two regions only differed by 1.16C. Although previous studies have documented a
significant change in growth from small temperature differences (Wyban et al. 1995,
reviewed in Hartnoll 2001), it is difficult to ascertain whether the temperature difference
between the inshore and offshore regions was large enough to cause the difference in
growth between the two regions. In order to do this, further studies are needed to
quantify the effect of temperature on the growth of S. hispidus of different sizes
In addition to temperature, food availability has been shown to affect the growth rates
of crustaceans. Specifically, a reduction in food supply causes a reduction in growth
rates, through an extension of molt interval and/or a reduction in growth increment
(reviewed in Hartnoll 2001). Observations of the inshore and offshore habitats indicate
that there may be a difference in food availability between the two. There seems to be a
much higher concentration of algae and other plant material in the inshore regions, thus
potential higher productivity in this habitat. In addition to cleaning fishes of parasites, S.
hispidus are most likely opportunistic feeders, picking food particles from the reefs and
possibly grazing on algae. Therefore, it may be that the higher growth rate in the inshore
region was due to increased food availability in that region.
This study has shown: 1) more larvae settle in the offshore region than the inshore
region, 2) there is strong evidence of size-selective mortality that does not differ between
the two regions, and 3) offshore shrimp grow approximately four times slower than their
inshore counterparts. With these results it is possible to imagine a scenario that would
explain the differences in S. hispidus population structure between inshore and offshore
regions of the Upper Florida Keys. It is probable that the offshore population is
dominated by smaller individuals because settlers never reach larger sizes, due to lower
growth and increased periods of vulnerability to high predation. In contrast, although
settlement inshore is much lower, settlers are able to reach larger sizes and, therefore,
escape mortality more quickly, due to their higher growth.
Table 2-1. Details of sites used in population size-structure study. Site codes (in parentheses) for each site correspond to those used in
Site Depth (m) Distance from Reef type Coordinates Year(s)
shore (km) surveyed
Alligator Deep (AD)
Alligator Shallow (AS)
Davis Deep (DD)
Davis Shallow (DS)
Crocker Deep (CD)
Crocker Shallow (CS)
Rock 1 (R1)
Rock 2 (R2)
Rock 3 (R3)
Shrimp Rock 1 (SR1)
contiguous and patch
240 50.526'N, 800 37.464'W
240 51.221'N, 800 36.823'W
240 55.461'N, 800 30.019'W
240 55.029'N, 800 30.614'W
240 54.279'N, 800 31.681'W
240 54.454'N, 800 31.672'W
240 56.548'N, 800 33.666'W
240 56.991'N, 800 33.157'W
240 57.258'N, 800 32.774'W
240 56.909'N, 800 33.251'W
2001 and 2002
2001 and 2002
2001 and 2002
2001 and 2002
2001 and 2002
Table 2-2. Details of sites used in post-settlement mortality tagging study.
Site Depth Distance Reef type Coordinates
(m) from shore
Davis Deep 14.6 7.60 contiguous 240 55.461'N, 800 30.019'W
Crocker Deep 14.6 7.02 contiguous 240 54.279'N, 800 31.681'W
Rock 1 3.05 1.63 patch 240 56.548'N, 800 33.666'W
Rock 2 3.66 1.60 patch 240 56.991'N, 800 33.157'W
Rock 3 5.79 2.04 patch 240 57.256'N, 800 32.774'W
Table 2-3. Parameter estimates and test statistics from linear regression models to
estimate the growth increment for shrimp from the inshore and offshore region, as in
Equation 2.2. Graphical representations for these parameter estimates can be seen in
Region Parameter Estimates Test Statistics
a + SE b + SE F-value dfn,d Pr > F r2
Inshore 8.32 + 1.25 -0.153 + 0.027 30.71 1,20 <0.0001 0.61
Offshore 2.42 + 1.60 -0.047 0.067 0.48 1,31 0.4942 0.02
0 5 10 15 20 25 30 35 40 45 50 55 60
0 5 10 15 20 25 30 35 40 45 50 55 60 65
Figure 2-1. Box plots of total length (mm) for all sites surveyed in each of 2001 and
2002. Shaded boxes represent inshore sites, white boxes represent offshore sites. Site
symbols correspond to those presented in Table 2.1. Boxes contain 50% of the sample
values (1st sample quartile-3r sample quartile). The two whiskers extend within a range
of 1.5 times the interquartile range. Dots represent outliers. A vertical line in each box
represents the median of each sample. Sample sizes are as follows: 2001 CD, n=43; 2001
DD, n=38; 2001 R2, n=12; 2001 R1, n=10; 2001 R3, n=8; 2002 CD, n=74; 2002 CS,
n=29; 2002 DD, n=44; 2002 DS, n=14; 2002 AD, n=9; 2002 AS, n=20; 2002 R1, n=9;
2002 R3, n=14; 2002 SR1, n=14; 2002 R2, n=9.
Sc -5- Inshore
0 1 2 3 4 5 6 7 8 9 10
Figure 2-2. Mean (+SE) number of settlers to inshore and offshore artificial reefs in each
often weekly surveys.
1.0 O4 '
S.7 50-60mm TL
-- 40-50mm TL
S0.6 30-40mm TL
1-D- 20-30mm TL
o 0.5 10-20mmTL
0 10 20 30 40 50 60 70 80 90
Figure 2-3. Survivorship curves of five size-classes of S. hispidus for 2001 and 2002 and
all sites combined. Note that 10-20mm individuals have different survivorship than those
of 20-30mm and 30-40mm, which have different survivorship than those of 40-50mm
and 50-60mm TL. Sample sizes are as follows: 50-60mm, n=23; 40-50mm, n=16; 30-
40mm, 20; 20-30mm, n=53; 10-20mm, n=37.
0.8 ......... ::: ::::: ::: :::::::::: :::: ... ::::
--- Large, not tethered
0.2 .. .. Small, not tethered
--- Large, tethered
0.1 ..... Large, not tethered
0 1 2 3 4 5 6 7 8
Figure 2-4. Survival of small and large, tethered and un-tethered individuals in the
laboratory control tether experiment. There is no difference in survivorship in any of the
four treatments. Sample sizes are 10 for all treatments.
0.7 Small, inshore
S..... Small, offshore
0.6 -- Large, inshore
S*..**. Large, offshore
0 1 E" . .  . . . . a 1
0.1 ''.'^Ol------- --------D
0 1 2 3 4 5
Figure 2-5. Survivorship of small and large, inshore and offshore tethered individuals in
the field tether experiment. There is no difference in survivorship between any of the
four treatments. Sample sizes are as follows: small inshore, n=13; small offshore, n=12;
large inshore, n=15; large offshore, n=19.
0- r, r- n -m 1 r- 1 IL .-. n .-. 1-1
'/ 0 % % 0$
Figure 2-6. Mean abundance (number/3.14m2) of predators in each of the clusters generated by a k-means clustering analysis.
Figure 2-7. Adjusted mean (+ SE) growth increment for inshore and offshore
populations of S. hispidus from ANCOVA. Sample sizes are as follows: inshore, n=22;
E 4 0 0 0
E o 0o
So o o
E ...... .......
0 -2 -
-4 -- Inshore Linear Regression
0 O Offshore
....... Offshore Linear Regression
-6 I I
10 20 30 40 50 60
Pre-molt length (mm)
Figure 2-8. Linear regression of mean pre-molt length (mm) on mean growth increment
(mm) for inshore and offshore populations of S. hispidus. Sample sizes are as follows:
inshore, n=22; offshore, n=33. Parameter estimates for regression lines can be found in
S' ||e Inshore
30 O Offshore
0 10 20 30 40 50 60 70 80 90 100
Post-settlement Age (weeks)
Figure 2-9. Mean and standard deviations (error bars) of shrimp length (mm TL) at post-
settlement age for inshore (closed circles) and offshore (open circles) regions. These
means and standard deviations result from 100 simulations of the crustacean growth
model for each region. Note the only overlap in the standard deviations of the two
populations is for the first 2 weeks and last 13 weeks, post-settlement.
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Brandon Rae Chockley was born on May 4, 1978, at Andrews Air Force Base, MD.
He received his Bachelor of Science in marine biology from Auburn University in
Auburn, Alabama, in Spring 2000. During his last year at Auburn University, he was an
undergraduate teaching assistant for two general biology classes (Principles of Biology
and Animal Biology). Brandon completed an independent research project under the
supervision of Dr. Jon Armbruster, in which he described a new species of armored
catfish (Panaque change) from eastern Peru. Partial funding for this project came from
an Auburn University Undergraduate Research Award that Brandon received in June
1999. The manuscript from this project has recently been published.
Prior to Brandon's graduate career at the University of Florida, he worked as a
laboratory and field teaching assistant at the Oregon Institute of Marine Biology
(University of Oregon) for the Invertebrate Zoology class. He began attending the
University of Florida for his Master of Science in zoology in the fall of 2000, in Dr.
Colette St. Mary's lab. While at the University of Florida, he has been a teaching
assistant (Principles of Biology and General Ecology) and a research assistant (under Dr.
Craig Osenberg). Brandon started the fieldwork for his master's research in the Florida
Keys in the summer of 2001 and continued in the summer of 2002. Brandon has received
funding from the University of Florida (Grinter Fellowship, 2000-2002) and PADI
Project AWARE (2002) for his master's research.