Plasticity of Visual Acuity in Cichlids with Changes in Habitat and Social Complexity

Author: Elizabeth Lee Higgins

Persistent link: http://hdl.handle.net/2345/416

This work is posted on eScholarship@BC, Boston College University Libraries.

Boston College Electronic Thesis or Dissertation, 2006

Elizabeth Higgins

Senior thesis submitted in partial fulfillment of the requirements of the College of Arts and Sciences Honors Program

Advisors: Dr. Daniel Kirschner, Boston College Biology Department Dr. Caroly Shumway, New England Aquarium

Boston College 2006 1

Plasticity of visual acuity in cichlids with changes in habitat and social complexity

Abstract Species-specific differences in visual acuity have been demonstrated across species of cichlids differing in social and habitat complexity. What is the role of plasticity? A visual acuity assay on two species of fish reared in different habitat and social complexity was used to study brain plasticity in Xenotilapia flavipinnis and Asprotilapia leptura juveniles. The X. flavipinnis lives in sandy habitats and schools as juveniles. These fry were raised in an impoverished social environment in one case and an enriched habitat environment in another. The A. leptura lives in rocky habitats naturally. These fry were raised in an impoverished habitat environment. All conditions were compared to control groups with natural social and habitat conditions. I found that a change in social complexity had a plastic effect on visual acuity but a change in habitat complexity in both cases did not.

Introduction

Environmental and social pressures drive the evolution of sensory systems (Ryan and Rand, 1993; Striedter, 2005). Many studies have correlated sensory specializations, including within the visual system, with ecological differences across different vertebrate taxa (Healy and Guilford, 1990; Higgs and Fiuman 1998; Lisney and Collin, 2006;

Marshall and Vorobyev, 2003; Stoddard, 1999). Species-specific differences in visual acuity have been shown in closely related Tanganyikan cichlids, with visual acuity increasing as either habitat or social complexity increases (Dobberfuhl, Ullmann, and

Shumway, 2005). The factors responsible for the differences between species as well as the rapid speciation of African cichlids are uncertain. The possibility of plasticity and the factors that influence plasticity may play a key role in shaping sensory systems in cichlids.

Both environmental and social complexity have been shown to cause plastic changes in brain structure and function. Many vertebrate studies, specifically on birds, fish, and mammals, have shown experience-dependent plasticity in sensory areas, the 2 hippocampus, and on learning and memory in developing animals and adults (e.g., Daw,

2004; Cancedda et al., 2004; Shumway et al., 1999, 2005; Rosenzweig & Bennett, 1996;

Clayton, 1994). Experience may be necessary for full growth of brain and behavioral potential in songbirds (Clayton and Krebs, 1994; Healy and Krebs, 1993). The survival of new neurons in the forebrain in adult songbirds is affected by social complexity

(Lipkind et al., 2002). Fish may be more plastic than other vertebrate classes, exhibiting neurogenesis throughout life in numerous brain regions (Zupanc et al., 2005). Rearing fish in social isolation affects neurogenesis (Castellano et al., 2005) and tectal spine density (Coss & Globus, 1978). Hatchery rearing of salmon and other salmonid fishes in an impoverished environment compared to wild habitats has been shown to cause changes in brain structure and function (Marchetti and Nevitt, 2003; Kihslinger and

Nevitt, 2005). Variations in the rearing environment within the first three weeks of life in salmon can cause volumetric changes in the brain that are usually attributed to generations of selection (Kihslinger and Nevitt, 2005). Changes in habitat also influence rates of cell proliferation (Lema, Hodges, Marchetti, and Nevitt, 2005). Social environment affects neuron proliferation in a stimulus- and site-specific manner in adult female prairie voles (Fowler, Liu, Ouimet, and Wang, 2002). Genetic work has also been done in mammals to explore mechanisms for brain plasticity. Repeated expression of

Immediate Early Genes in response to an altered environment demonstrate a fast genetic mechanism for retinal plasticity in mammals (Pinaud and Tremere, 2005). In rats, as well as other mammalian species, maternal behavior produces epigenetic stable alterations of

DNA expression in their offspring. This gene-environment interaction provides a 3 mechanism for long term effects of ‘environmental programming’ on gene expression and function (Champagne and Curley, 2005; Weaver, et al., 2004).

Cichlids are a good model for studying the effects of changes in habitat and social complexity. Cichlid phenotypic plasticity has been demonstrated for social behavior and brain structure and function, visual behavior and retinal structure, and feeding morphology (Insel & Fernald, 2004; Hofmann & Fernald, 2001; Kröger et al., 2001,

2003; Liem & Osse, 1975; Meyer 1989), and has been suggested as a cause of adaptive radiation (Bell and Travis, 2005). Cichlids have undergone rapid speciation within the great lakes of Africa, with a calculated 250 species in Lake Tanganyika alone (Poll, 1986;

Turner et al., 2001). Many closely related species differ in only one aspect of life, such as breeding behavior or habitat, making them ideal for studying evolutionary pressures.

Also, there have been many instances of evolutionary parallelism between the lakes

(Sugawara et al, 2005), suggesting that there must be some similar forces acting on these fish that cause them to undergo phenotypic change eventually resulting in speciation. The speed of evolution of the species in a lake depends upon the plasticity of the species involved, the biological and physical pressures exerted on them, and the length of time these pressures have been acting upon the animals (Axelrod and Burgess, 1988).

Variation among several species of cichlids has been found in their visual systems in opsin gene expression, allowing them to tune their visual systems to their specific photic environment (Parry et al., 2005; Spady et al. 2005). It has also been shown in cichlids that different photic and spectral environments induce neural plasticity in the retina and behavioral changes in response to stimuli, demonstrating plasticity in the brain through environmental cues (Kröger, Knoblauch, and Wagner, 2003). 4

I explored whether changes in physical and social environment affected visual

behavior in cichlids. Specifically, two species of Tanganyikan cichlid, Xenotilapia

flavipinnis and Asprotilapia leptura, were reared under different levels of habitat complexity; Xenotilapia flavipinnis was also reared under different levels of social complexity to quantify the change in the visual abilities caused by changes in environment. These closely related species are members of the Ectodini clade, a monophyletic tribe endemic to Lake Tanganyika. The two species are sister species

(Kobmüller et al. 2004). They share the same social behavior (biparental mouthbrooders), but differ in habitat structure; Xenotilapia flavipinnis prefers sandy substrates and Asprotilapia leptura prefers rocky habitats. I compared normal visual ability to that of fish reared with an impoverished habitat complexity, an enriched habitat complexity, and an impoverished social complexity. Visual abilities were measured by determining the visual acuity, or the reciprocal of resolving power, defined as either the minimum angle formed by the eye by two objects that appear separate (Douglas and

Hawrynshyn, 1990) or the minimum angle that a stimulus can project onto the eye and still be detected (Neave, 1984). Visual acuity was analyzed by measuring both the optomotor (Neave, 1984; Pankhurst, 1994; Rahmann, Jeserich, and Zeutzius, 1979) and optokinetic response (Carvalho, Nolte, and Tillitt, 2002; Clark, 1981).

Materials and Methods (adapted from Dobberfuhl, Ullmann, and Shumway, 2005)

Experimental Subjects

The Xenotilapia flavipinnis subjects were two broods of lab-born progeny from one breeding pair. They were removed from their parents’ home tank when they no 5

longer had an external yolk sac. They were placed into three separate groups, each with

different habitat and social conditions. The fish were run in trials when they were three to

four months old; the groups were the same standard lengths at the time of testing. The

subjects for the lens diameter measurements originated from one of the two broods used,

with an additional third brood from the same parents. The diameters of the lenses, fixed

in 4% paraformaldehyde, were measured from a digital picture using ImagePro software.

The diameters were corrected for shrinkage, using a value of 10% (Miller, Crowder, &

Rice, 1993; Neave, 1984). The Asprotilapia leptura subjects were lab-born progeny of

one breeding pair from the same brood. They were placed in two groups with different

habitat conditions. All research reported in this article was performed under the auspices

of the New England Aquarium’s Animal Care and Use Committee.

Home Tanks

The fry were maintained in aquaria under conditions mimicking their natural

environment (temperature, light levels and spectrum, and pH). The Xenotilapia

flavipinnis fry were separated into three groups. The control group consisted of ten fry in one five gallon tank with a natural sandy substrate (normal social and normal habitat complexity). The rock group consisted ten fry in one five gallon tank fry with a rocky substrate (normal social, but enriched habitat complexity). The isolates consisted of ten tanks with natural sandy substrates, each with one fish (normal habitat but impoverish social complexity). The individuals in the sand and rock groups were all from the same brood; the isolates were from a second brood. The fry in the rock and sand groups were individually identified by their lengths measured at the start of each trial. All tanks had 6 the same volume (7695 cm3). The Asprotilapia leptura fry were separated into two groups. The control rock group consisted of one tank section with a group of four fry with a rocky substrate (normal habitat complexity). The sand group consisted of one tank section with a group of three fry with a sandy substrate (impoverished habitat complexity). These two tank sections had the same volume. All tanks were covered on all sides with opaque white covering and were adapted with a filtration and heating system contained in a blocked off compartment that allowed for no extra visual stimulation. The fry were all fed a diet of live brine shrimp and placed on a 12 hour light- dark cycle.

Behavioral Acuity

The square-wave stimulus consisted of black and white stripes of equal width on the internal side of a drum. For the Asprotilapia leptura, the set up for adult fish explained in Dobberfuhl, et al. (2005) was used. The drum (280mm diameter × 215mm height) completely covered the experimental tank horizontally and extended 38mm beyond the tank vertically. A plastic divider was used to raise the bottom of the chamber by 8cm, so that the stimulus filled the fish’s entire visual field. The cylindrical experimental tank was made of plastic and had a diameter of 280mm. For the Xenotilapia flavipinnis, a new set up, specifically sized for juveniles, was created. The drum (height =

100mm; diameter = 110mm) completely covered the experimental tank horizontally and extended above and below the grating. The cylindrical experimental tank was made of clear cast acrylic with an opaque bottom with an inner diameter of 75mm, a wall width of

3mm, and a water depth of 30mm. The tank was suspended into the grating drum. The 7 stimulus filled the fish’s entire visual field. We printed nine different grating cycles (i.e. both the black and white lines) with a total width of 10.22, 5.1, 4.24, 3.44, 2.56, 1.96,

1.28, 0.92, and 0.64mm, at a resolution of 1200 dpi. A gray grating (50% gray) was used in control trials. Each stimulus was rotated at 4 rpm by a variable speed reversible DC motor. At this low speed, the flicker fusion threshold was not exceeded (Carvalho et al.,

2002). Two full spectrum light bulbs (mimicking field conditions) were suspended over the experimental arena on either side of a digital video camera directly above the experimental tank. Ceiling fluorescent illumination was maintained to reduce shadows.

The combined lights provided an average peak illumination of 0.082 µmoes/m2/s

(calibrated with an EPP200 light meter [StellarNet, Tampa, FL] and measured daily with a Luna-Pro light meter [Gossen, Nürnberg, Germany]) at the water surface.

Trials were run between the times of 8:00 and 18:00, with room illumination of the home tanks beginning at 6:00. At the start of each trial, the fish was placed in a small plastic holding container with a white background and a centimeter scale bar to restrict their movement. A digital photo was taken. Measurements of each fish were taken from the photo using ImagePro, in order to identify the fish and measure standard length.

After the photo was taken, the fish was placed into the experimental tank, which was filled with water from the fish’s home tank (temperatures between 25°C and 27°C). Prior to testing, subjects were acclimated for 10 minutes in the experimental tank surrounded by the grating. The direction of the grating was randomly determined at the beginning of each experiment. Three trials were run for each grating size, with each trial lasting 2 minutes, followed by a 3 minute break. Each trial was videotaped from above (Sony

Digital 8 Handycam) and observed on a TV monitor. At the end of each experiment, the 8 experimental tank was emptied and wiped clean with alcohol, to eliminate any possible odor confounds.

Visual acuity of the fish was determined by using a combination of both optomotor and optokinetic responses. A positive response consisted of either a combination of smooth tracking eye movements followed by reset saccades (Easter Jr. and Nicola, 1996) and/or locomotory following of the moving stripes (Pankhurst, 1994).

As defined by Dobberfuhl et al. (2005), the criteria for a positive response was half a rotation of swimming with the grating, one full pivot with the grating, or two sets of smooth tracking eye movements synchronized with the speed and direction of the grating.

A set of eye movements was defined as a “follow-reset-follow” motion of both eyes in accordance with the grating direction done three times consecutively. After the experiments, scoring was completed by a blind observer who did not know the grating size or fish identity.

Data Analysis

The spatial frequency of a given grating, measured in cycles/degree, was calculated as the inverse of the visual angle (degrees) generated by that grating cycle for each group. The spatial frequencies were compared by calculating the mean response at the point of the average response of the last four gratings where the response dropped from 100% to 0% (43% for comparing the control group and the rock group; 37% for comparing the control group and the isolates) from logarithmic regressions of the respective individual spatial frequency curves. 9

Minimal separable angle (MSA) is the threshold for resolving two lines. MSA is

0.5W calculated with the equation α = 2arctan( RD ) , where W is the mean of the smallest stripe width that could be resolved, and RD is the mean reactive distance for that group

(Breck and Gitter, 1983). The RD for each group was measured from a subsample of three random individuals (50% of the control and rock group, 75% of the isolates). One trial was randomly selected out of the three videotaped trials/grating for two gratings that had 100% response (10.11 and 2.56). At each grating size, we measured the RD from the middle of the eyes (assuming foveal attention to the grating) to the edge of the tank for five frames captured every 20 seconds. PhotoDV (Digital Origin, Mountain View, CA) was used to convert the videotape to stills and the images were measured on the computer screen with calipers to determine the distance. After adding the distance between the tank and the grating, the mean for each fish at each grating was determined. A t-test showed no significant difference between the RD of the control group and the rock group, so the groups were pooled and a mean of their RDs was used. Similarly, the control group and the isolates did not significantly differ, so they were pooled and a mean of their RDs was used in comparing those groups. These RD means were used in calculating individual and mean MSA for each group and also the spatial frequencies for each group. The control group was compared to the rock group and the isolates separately.

All measures of variability reported herein are standard error (SE). Statistical significance for measures of spatial frequency and MSA were determined with two-tailed t-test assuming equal variance. Statistical significance for regression analyses is described below in the results section. 10

Results

Plastic Effect of a Change in Social Complexity

There was a notable plastic difference with a change in social complexity. Social isolation led to a reduced visual acuity in Xenotilapia flavipinnis. The isolates had a significantly lower mean spatial frequency compared to the control group at the 37% point (Figure 1; n = 4, 6 respectively). At this point, the isolates had a spatial frequency

(1.60 cycles/degree) 32% smaller than the control group (2.44 cycles/degree). A two- tailed t-test showed that the spatial frequency of the isolates was significantly smaller (p

= 0.048). Observed differences were greater at higher spatial frequencies. The minimal separable angle (MSA) for the isolates (47.83 ± 4.54 min) was 53% larger than that of the control group (31.17 ±5.01 min) (Figure 2). A two-tailed t-test showed that the control group had a significantly smaller MSA than the isolates (p = 0.050).

100% Isolates )

% 80% Sand Group ( e s n

o 60% p s e R

e 40% g a r e v

A 20%

0% 0.1 1 10 Spatial Frequency (cycles/degree)

Figure 1. Effect of a decrease in social complexity on spatial frequency in X. flavipinnis. Error bars represent standard error. The dashed line represents the 37% response level. At this level, the control (sand) group detected a significantly higher spatial frequency than the social impoverished isolates (sand group: n = 6; isolates: n = 4). 11

140 120 ) s 100 e t

u * n

i 80 m ( 60 A S

M 40 20 0 Sand Group Isolates Social Complexity

Figure 2. Effect of a decrease in social complexity on mean minimum separable angle (MSA) in X. flavipinnis. Error bars represent standard error. The control (sand) group perceived a significantly smaller MSA than the isolates (sand group: n = 6, isolates: n = 4; *p = 0.050).

Plastic Effect of a Change in Habitat Complextiy

For Xenotilapia flavipinnis, I found no significant effect on visual acuity with an

increase in habitat complexity (Figure 3; n = 6). At the 43% point (which was the average

response over the last four grating sizes), the control group had a spatial frequency of

2.09 cycles/degree and the rock group had a spatial frequency of 2.03 cycles/degree. A

two-tailed t-test showed no significant difference between the two groups (p = 0.78).

Comparison of the mean MSA values (Figure 4) with a two-tailed t-test showed no

significant difference between the groups (p = 0.90). The mean MSA for the control

group was 33.68 ± 5.41 min and for the rock group was 32.52 ± 7.71 min. 12

Similarly, the spatial frequency comparison between the control (rock) group and

the impoverished condition (sand) for Asprotilapia leptura showed no significant effect

on visual acuity with a decrease in habitat complexity (Figure 5; n = 4 and 3

respectively). At the 50% point, the control group had a spatial frequency of 0.5497

cycles/degree and the sand group had a spatial frequency of 0.6366 cycles/degree. A

two-tailed t-test showed no significant difference between the groups (p = 0.82). There was also no significant difference in the mean MSA values for the two groups (p = 0.72); the control group had an MSA of 99.50 ± 17.48 min and the sand group had an MSA of

91.18 ± 8.18 min (Figure 6).

100% Rock

80% Sand ) % ( e

s 60% n o p s e

R 40% e g a r e

v 20% A

0% 0.1 1 10 Spatial Frequency (cycles/degree)

Figure 3. Effect of an increase in habitat complexity on spatial frequency in Xenotilapia flavipinnis. Error bars represent standard error. The dashed line represents the 43% response level. There was no significant difference in the spatial frequencies detected by each group (control (sand) group: n = 6; rock group: n = 6). 13

140 120 ) s 100 e t u n i 80 NS m ( 60 A S

M 40 20 0 Sand Rock Habitat Complexity

Figure 4. Effect of an increase in habitat complexity on mean minimum separable angle (MSA) in X. flavipinnis. Error bars represent standard error. The control (sand) group perceived a similar MSA to the rock group (sand group: n = 6; rock group: n = 6).

100 sand

) rock

% 80 ( e s n

o 60 p s e R

e 40 g a r e v

A 20

0 0.1 1 10 Spatial frequency (cycles/degree)

Figure 5. Effect of a decrease in habitat complexity on spatial frequency in Asprotilapia leptura. Error bars represent standard error. The dashed line represents the 50% response level. There was no significant difference in the spatial frequencies detected by each group (control (rock) group: n = 4; sand group: n = 3). 14

140 NS 120 ) s 100 e t u n

i 80 m ( 60 A S

M 40 20 0 Sand Rock Habitat Complexity

Figure 6. Effect of a decrease in habitat complexity on mean minimum separable angle (MSA) in A. leptura. Error bars represent standard error. The control (rock) group perceived a similar MSA to the sand group (rock group: n = 4; sand group: n = 3).

Relationship Between Lens Size and Standard Length

There is a significant positive correlation between lens diameter and standard length (measured from the tip of the mouth to the caudal peduncle) in these juvenile

Xenotilapia flavipinnis (Figure 7; r2 = 0.952, p < 0.0001). The range of lengths of the fish used in all parts of this experiment was 17mm to 33mm. Note that over the course of the experiment, the lengths of the fish increased, but at each grating size, both conditions were compared only when there was no significant difference in size among the subjects of each group. 15

1.3 1.2 ) m

m 1.1 ( r e t 1 e m a i 0.9 d s n

e 0.8 L 0.7 0.6 10 15 20 25 30 Length (mm)

Figure 7. The relationship between lens size and standard length. Lens size is significantly correlated with standard length of the Xenotilapia flavipinnis juveniles (p < 0.0001).

Discussion

Juvenile Size and/or Behavior Affects Visual Acuity

Fish eyes grow constantly throughout life. As a result, previous studies have shown a significant positive correlation between lens size and standard length of fish

(Carvalho et al., 2002; Dobberfuhl, Ullmann, & Shumway, 2005; Pankhurst, Pankhurst &

Montgomery, 1993). However, at least in adult fish, lens diameter did not have a significant effect on MSA (Dobberfuhl et al., 2005). A comparison of MSA to lens diameter was not possible in this study because the subjects could not be euthanized, as they are to be followed over a longer period of time. As found in Dobberfuhl et al.

(2005) in adult cichlids, there was a similar correlation with lens diameter compared to size in juveniles. However, in comparing the results from that paper with the present 16 study, juvenile Xenotilapia flavipinnis perceived a MSA (31.17 ± 5.01 min) 1/3 that of an adult (111.2 ± 15.4 min). Conversely, Asprotilapia leptura showed a 50% decrease in

MSA perceived from juvenile (99.50 ± 17.48 min) to adult (42.6 ± 6.65 min). The latter result is to be expected, as theoretically visual acuity increases as the fish grows, due to increase in lens size. Visual acuity reaches an asymptote in adults, as cone density is inversely related to standard length and will outweigh the increase in lens size (Breck and

Gitter, 1983; Carvalho et al., 2002; Pankhurst et al., 1993).

What might be a possible explanation for the decline in the visual abilities of adult

Xenotilapia flavipinnis? A decrease in the size of the optic tectum has been observed in five species of shark as the fishes advanced from juvenile to adult. It is thought that this decrease is due to an ontogenic shift in habitat and/or diet and feeding strategy. The sharks use shallow nursery areas where young sharks develop and would be exposed to a greater range of wavelengths and rely more heavily on visual cues than adults. There are also reported shifts in predation techniques and prey during shark development (Lisney and Collin, 2005). It is possible that the Xenotilapia flavipinnis fry were exposed to more light than the adults in the previous study or that there is a similar ontogenic shift due to a change in diet size (the juveniles were fed tiny brine shrimp and the adults had been fed larger ColorBits (Tetra)). It is possible that there is a similar pattern in Asprotilapia leptura; however, the fry in this study may have been deprived of light as they were able to hide under the rock provided in their substrate (this was fixed for the rearing of the rock group in the Xenotilapia flavipinnis). It is also possible in Xenotilapia flavipinnis that a change in social complexity from juveniles to adults causes a decrease in visual acuity, as the schools of fry break into monogamous pairs at reproductive maturity (~1 17 year). It may be that the brain is still plastic after the age of one year in this case and more trials should be run at this age (or length, if sexual maturity is based on size).

Sociality is Key in Shaping Visual Abilities

This study shows that only a change in the social complexity had a significant effect on visual acuity, at least at four months. There was a significant decrease in visual acuity in the isolates which suggests that, as a juvenile, social contact is an important factor in brain development. This agrees with what was observed in adults (Dobberfuhl et al., 2005), as visual acuity increased from the monogamous Xenotilapia flavipinnis to the polygamous Enantiopus melanogenys.

Together, these two studies suggest that sociality may be the driving force behind evolution in cichlids. In other words, an increase in visual abilities due to increased social complexity in group size may allow for a more complex habitat, and not the other way around. A change in social complexity within a species was the only way a change in visual acuity could be elicited, as a change in habitat complexity had no effect in two species, at least at the young age of four months. Complicating this hypothesis, however, is the fact that monogamous Xenotilapia flavippinis has a larger forebrain than polygamous Enantiopus melanogenys (Pollen et al., 2006). It must be noted that measuring social complexity is difficult, as we do not fully know the parameters. Such factors as breeding behavior, whether it be monogamous pairs or polygamous leks, predation avoidance strategies, size of behavioral repertoire of social interactions, amount and type of conspecific and nonspecific interaction, and group size could all have different effects on plasticity in brain structure and function. Certainly, more studies must 18 be done in order to quantify the importance of each characteristic in social complexity.

For example, plasticity in breeding behavior could be examined through cross-fostering experiments of two species with different breeding strategies.

There was no significant effect on visual acuity produced by either an enrichment of habitat complexity, as in the case of the Xenotilapia flavipinnis, or an impoverishment of habitat complexity, as in the case of the Asprotilapia leptura. This finding suggests that habitat complexity does not influence the plasticity of the juvenile cichlids in regards to visual acuity, at least at four months of age. As with an increase in social complexity in cichlids mentioned above, Dobberfuhl et al. (2005) also reported an increase in visual acuity with an increase in habitat complexity. There was a significant difference between

Xenotilapia flavipinnis and Asprotilapia leptura, and also between Xenotilapia spiloptera

(intermediate habitat complexity) and Asprotilapia leptura. However, there was no difference between the sand and intermediate habitat species. It was noted previously that the difference in visual acuity might be observed after a longer period of development, as Nevitt et al. did not find developmental differences in the telencephalon until after one year. It is also possible that the difference observed as adults is a consequence of increased spatial behavior, i.e. more movement in and around obstacles in their habitat.

There were a few complications worth noting that may confound the results.

First, although all groups started with ten animals, the ns for all of the animals tested were small, due to mortalities that naturally occur during development. Perhaps a larger group size would show plasticity differences under the different habitat conditions.

Certainly, the adult individual variability was large enough that ns of 10-15 were 19 necessary (Dobberfuhl et al., 2005). Another complication was that not all of the fish were reduced to zero response even at the smallest grating size. However, it was actually physically impossible to print a smaller size grating than the 0.64mm grating cycle with the printers available. The fish most likely would have had zero response at the next grating size down but there was no way to quantify that. Another issue may have been the behavior of the isolates. The isolates’ tanks were devoid of any stimulation except for light. This appeared to cause them to be very skittish at the slightest disturbance

(including simply removing the lid to feed them). They constantly tried to jump out of their home tanks, as well as the experimental tank. It seemed any stimulation at all stressed them out, which may have provided for the significantly lower response.

Another consideration would be the complexity of the rocky environments. In the initial experiments with the Asprotilapia leptura, the rocky environment contained one fake rock formation that allowed the fish to swim under. It was observed that they spent most of their time hiding under it and therefore, were not exposed to as much light as the other condition. The rock was changed in the next experiments with Xenotilapia flavipinnis to a simple bulge of a rock that the fish could not swim under or be shaded in any way by it.

However, the rock, before growing any algae, was a similar color to the sandy substrate and did not seem to provide this group of fish with any more stimulation than the simple sand habitat. This is probably the reason that the comparisons were so close in both cases, and with an improved plan for increasing habitat complexity, there might be a change in visual acuity in those fishes. With additional experiments taking into consideration the complications above and over a longer period of time, this study could 20 really reveal to what extent the visual ability attributed to habitat and social factors is evolutionarily “hard-wired” or experience dependent.

Acknowledgements

I would like to express my deepest gratitude to my advisor at the New England

Aquarium, Dr. Caroly Shumway, for her knowledge and continual encouragement over the past three years that has inspired me to research cichlid visual acuity and take the next step with my own research in plasticity. I would also like to thank her for providing the lab facilities and fish necessary for my work. Dr. Daniel Kirschner also deserves much gratitude for his advice on writing my senior thesis this year. A special thanks to Justin

Scace for making sure my fish were well cared for, and supporting me and giving me feedback on ideas throughout my project, and to Adam Dobberfuhl for originally training me in visual acuity assays in the beginning. I would also like to thank Margaret Bell,

Lindsay Bryan, and Lindsey Hemphill for helping run trials when time was tight and scoring the trials blind. 21

Works Cited

Axelrod, H.R. and Burgess, W.E. (1988). African Cichlids of Lakes Malawi and Tanganyika. (pp. 32) Neptune City, NJ: T.F.H.

Bell, M.A., and Travis, M.P. (2005). Hybridization, transgressive segregation, genetic covariation, and adaptive radiation. Trends in Ecology and Evolution, 20, 358-361.

Breck, J.E., and Gitter, M.J. (1983). Effect of fish size on the reactive distance of bluegill sunfish (Lepomis macrochirus). Canadian Journal of Fisheries and Aquatic Science, 40, 162-167.

Brichard, P. (1989). Xenotilapia. In Pierre Brichard’s book of cichlids and all the other fishes of Lake Tanganyika. (pp. 432). Neptune City, NJ: T.F.H.

Cancedda, L., E. Putignano, A. Sale, A. Viegi, Berardi, N., and L. Maffei (2004) Acceleration of visual system development by environmental enrichment. Journal of Neuroscience, 24(20): 4840-4848.

Carvalho, P.S.M., Nolte, D.B., and Tillitt, D.E. (2002). Ontogenetic improvement of visual function in the medaka Oryzias latipes based on an optomotor testing system for larval and adult fish. Animal Behavior, 64, 1-10.

Champagne, F.A., Curley, J.P. (2005). How social experiences influence the brain. Current Opinion in Neurobiology, 15, 704-709.

Clark, D.T. (1981). Visual responses in developing zebrafish (Brachydanio rerio). Unpublished doctoral thesis, University of Oregon.

Clayton, N.S. (1994) The role of age and experience in the behavioral development of food-storing and retrieval in marsh tits, Parus palustris. Animal Behavior, 47(6): 1435-1444.

Clayton, N.S. and Krebs, J.R. (1994) Hippocampal growth and attrition in birds affected by experience. Proc. Natl. Acad. Sci. USA, 91, 7410-7414.

Daw, N.W. (2004) Mechanisms of plasticity in the visual cortex. In: The visual neurosciences, Chalupa, L.M. and J.S. Werner (eds.), MIT Press, Cambridge, MA, pp. 126-145.

Dobberfuhl, A.P., Ullmann, J.F.P, and Shumway, C. A. (2005) Visual Acuity, Environmental Complexity, and Social Organization in African Cichlid Fishes. Behavioral Neuroscience, 119, 1648-1655.

Douglas, R.H. and Hawrynshyn, C.C. (1990). Behavioral studies of fish vision: An analysis of visual capabilities, In R.H. Douglas and M.B.A. Djamgoz (Eds.), The visual system of fish (pp. 373-417). London: Chapman and Hall.

Easter Jr., S.S., and Nicola, G.N. (1996). The development of vision in the zebrafish (Danio rerio). Developmental Biology, 180, 646-663.

Fowler, C.D., Liu, Y., Ouimet, C., Wang, Z. (2002). The Effects of Social Evironment of Adult Neurogenesis in the Female Prarie Vole. Journal of Neurobiology, 51, 115-128.

Healy, S., and Guilford, T. (1990) Olfactory-bulb size and nocurnality in birds. Evolution, 44, 339-346.

Healy, S.D. and Krebs, J.R. (1993) Development of hippocampal specialization in a food- storing bird. Behav. Brain Res., 53, 127-130.

Higgs, D.M. and Fuiman, L.A. (1998). Associations between sensory development and ecology in three species of clupeoid fish. Copeia, 1, 133-144.

Hofmann H.A., and R.D. Fernald (2001). Review: What cichlids tell us about the social regulation of brain and behavior. Journal of Aquariculture and Aquatic Science, 9, 1- 15.

Insel, T. R. and R. D. Fernald (2004) How the brain processes social information: searching for the social brain. Annual Review of Neuroscience, 27, 697-722.

Kihslinger, R.L. and Nevitt, G.A. (2005). Early rearing environment impacts cerebellar growth in juvenile salmon. Journal of Experimental Biology, 209, 504-509.

Koblmüller, S., Salzburger, W. and Sturmbauer, C. (2004). Evolutionary relationships in the sand-dwelling cichlid lineage of Lake Tanganyika suggest multiple colonization of rocky habitats and convergent origin of biparental mouthbrooding. Journal of Molecular Evolution, 58, 79-96.

Kröger, R.H.H., Braun, S.C., and Wagner, H.-J. (2001). Rearing in different photic and spectral environments modifies spectral responses of cone horizontal cells in adult fish retina. Visual Neuroscience, 18, 857-864.

Kröger, R.H.H, Knoblauch, B., Wagner, H.-J. (2003). Rearing in different photic and spectral environments changes the optomotor response to chromatic stimuli in the chichlid fish Aequidens pulcher. Journal of Experimental Biology, 206, 1643-1648.

Lema, S.C., Hodges, M.J., Marchetti, M.P., Nevitt, G.A. (2005). Proliferation zones in the salmon telencephalon and evidence for environmental influence on proliferation rate. Comparative Biochemistry and Physiology, 141, 327-335.

Liem, K.F., and J.W.M. Osse (1975) Biological versatility, evolution, and food resource exploitation in African cichlid fishes. American Zoology, 15, 427-454.

Lipkind, D., Nottebohm, F., Rado, R., Barnea, A. (2002). Social change affects the survival of new neurons in the forebrain of adult songbirds. Behavioral Brain Research, 133, 31-43.

Lisney, T.J., Collin, S.P. (2006) Brian morphology in large pelagic fishes: a comparison between sharks and teleosts. Journal of Fish Biology, 68, 1-23.

Lisney, T.J., Collin, S.P. (2005). Volmetric Analysis of sensory brain areas indicates ontogenetic shifts in the relative importance of sensory systems in carcharihid and sphyrnid sharks. Submitted in: The Proceedings of the 7th Indo-Pacific Fish Conference.

Marchetti, M.P., Nevitt, G.A. (2003). Effects of hatchery rearing on brain structures of rainbow trout, Oncorhynus mykiss. Environmental Biology of Fishes, 66, 9-14.

Marshall, T.J., and Vorobyev, M. (2003). The design of color signals and color vision in fishes. In S.P. Collin and N. J. Marshall (Eds.), Sensory processing in aquatic environments (pp. 194-222). New York: Springer-Verlag.

Meyer, A. (1989) Ecological and evolutionary consequences of the trophic polymorphism in Cichlasoma-sitrinellum pisces Cichlidae. Biological Journal of the Linnean Society, 39, 279-300.

Miller, T.J., Crowder, L.B., & Rice, J.A. (1993). Ontogenetic changes in behavioural and histological measures of visual acuity in three species of fish. Environmental Biology of Fishes, 37, 1-8.

Neave, D.A. (1984) The development of visual acuity in larval plaice (Pleuronectes platessa L.) and turbot (Scopthalmus maximus L.). Journal of Experimental Marine Biology and Ecology, 78, 167-175.

Pankhurst, P.M. (1994). Age-related changes in the visual acuity of larvae of New Zealand snapper, Pagrus auratus. Journal of the Marine Biological Association of the United Kingdom, 74, 337-349.

Pankhurst, P.M., Pankhurst, N.W., and Montgomery, J.C. (1993). Comparison of behavioral and morphological measures of visual acuity during ontogeny in a teleost fish, Forsterygion varium, Tripterygiidae (Forster, 1801). Brain, Behavior and Evolution, 48, 178-188.

Parry, J.W.L., Carleton, K.L., Spady, T., Carboo, A., Hunt, D.M., and Bowmaker, J.K. (2005) Mix and match color vision: Tuning spectral sensitivity by differential opsin gene expression in Lake Malawi cichlids. Current Biology, 15, 1734-1739. 24

Poll, M. (1986). Classification des Cichlidae du lac Tanganyika: Tribus, Genre et Especes. Mem. Classe. Sci. Acad. Roy. Belg. 5, 5-163.

Pollen, A.A., Dobberfuhl, A.P., Igulu, M.M., Scace, J., Renn, S.C.P., Shumway, C.A., and Hofmann, H.A. (2006). Environmental Complexity and Social Organization Sculpt the Brain in Lake Tanganyikan Cichlid Fish.

Rahmann, H., Jeserich, G. and Zeutzius, I. (1979). Ontogeny of visual acuity of rainbow trout under normal conditions and light deprivation. Behaviour, 68, 315-322.

Rosenzweig M.R. and E.L. Bennett (1996) Psychobiology of plasticity: effects of training and experience on brain and behavior. Behavioral Brain Research, 78(1), 57-65.

Ryan, M.J., and Rand, A.S. (1993). Sexual selection and signal evolution: The ghost of biases past. Philosophical Transactions of the Royal Society B, 340, 187-195.

Shumway, C.A. (2006). NSF grant proposal.

Shumway, C.A., H. Hofmann, R. Wakafumbe, D. Sorocco, and L. Kaufman (1999). Is Social Behavior Related to Habitat Complexity in Tanganyikan Cichlids? Abstract presented at Gordon Research Conference on Neuroethology: Behavior, Evolution, and Neurobiology. Oxford, England.

Spady, T.C., Seehausen, O., Loew, E.R., Jordan, R.C., Kocher, T.D., and Carleton, K.L. (2005). Adaptive molecular evolution in the opsin genes of rapidly speciating cichlid species. Mol. Biol. Evol., 22, 1412-1422.

Stoddard, P.K. (1999, July 15). Predation enhances complexity in the evolution of electric fish signals. Nature, 400, 254-256.

Striedter, G.F. (2005). Evolutionary changes in brain region and size. In Principles of brain evolution (pp. 137-175). Sunderland, MA: Sinauer Associates.

Sugawara, T., Terai, Y., Imai, H., Turner, G.F., Koblmuller, S., Sturmbauer, C., Shichida, Y. and Okada, N. (2005). Parallelism of amino acid changes at the RH1 affecting spectral sensitivity among deep-water cichlids from Lakes Tanganyika and Malawi. PNAS, 102, 5448-5453.

Turner, G.F., Seehausen, O., Knight K.E., Allender, C.J., and Robinson, R.L. (2001) How many species of cichlid fishes are there in African Lakes? Journal of Molecular Ecology, 10, 793-806.

Zupanc, G.K.H., Hinsch, K., and Gage, F.H. (2005). Proliferation, Migration, Neuronal Differentiation, and Long-Term Survival of New Cells in the Adult Zebrafish Brain. Journal of Comparative Neurology, 488, 290-319.