SEX-SPECIFIC AGGRESSIVE DECISION-MAKING IN THE AFRICAN CICHLID MELANOCHROMIS AURATUS
Kamela De Stamey
A Thesis
Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of
MASTER OF SCIENCE
August 2014
Committee:
Moira van Staaden, Advisor
Daniel Wiegmann
Sheryl Coombs © 2014
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All Rights Reserved iii ABSTRACT
Moira van Staaden, Advisor
Effective fighting strategies are essential to successfully navigate competitive social interactions. Probing the fighting ability of opponents requires that individuals employ assessment behaviors so that appropriate decisions about fighting strategies can be made.
Inherent properties, such as sex and body size, have the potential to influence tactical fighting choices. African cichlids are well known for their hyper-aggressive nature and make ideal models for probing the underlying factors that impact decision-making during aggressive encounters.
Here, an ethogram was constructed comprising seventeen behaviors to probe the sex- and size- related differences in the fighting decisions of same-sex pairs of Melanochromis auratus, a highly territorial Malawian cichlid. A modified Mirror Image Stimulation (MMIS) test was developed that utilized mirrors with curved surfaces to query sex-dependent strategies based on altered apparent opponent size. Differential behavior based on the sex of the fish was also observed in staged encounters of size-matched dyads. Males showed little progressive assessment behavior and instead engaged in immediate and intense fighting, whereas females exhibit longer latencies to engage opponents and prolonged assessment phases. The sexes also exhibited distinct, but different, size-dependent strategies. During MMIS, males bit and displayed at higher rates towards larger mirror-image opponents, while female responses were more circumspect.
Comparisons of MMIS and size-matched encounters indicate that live opponents elicit more aggression from larger males than do flat mirror images. We conclude that male M. auratus do not conform to expectations based on typical progressive opponent assessment, but rather escalate to full-contact, high-intensity attacking very rapidly. iv
I dedicate this to my parents Kevin and Debi Stamey for the unfailing love and support
throughout my academic career. v ACKNOWLEDGMENTS
Firstly, I would like to thank my graduate advisor Dr. Moira van Staaden for her continual support, advice, and constructive feedback throughout the entire course of this project.
I would also like to thank Robert Huber for his insightful assessment and critical evaluation at every stage. In addition, his substantial statistical and technical contribution, specifically with the development of tracking software, was an invaluable part of my study.
I would also like to mention special gratitude to all the members of the van Staaden
(Sarah Jenevieve Jackson and Jessica LaHurd) and Huber (Udita Datta and Rohan Bhimani) labs for their feedback, manuscript review and, most importantly, for their continual support and encouragement. Thanks are also extended to my committee members, Dan Wiegmann and Sheryl
Coombs, for their critique and feedback of my experimental design, notably for Dr. Wiegmanns’ expert statistical advise.
Special thanks to Joe Coleman for the extensive time he took from his own thesis work to assist me in writing code for my statistical analysis. I thank Steve Queen for constructing all experimental arenas and the BGSU Stats Department for the free statistical support service they offer graduate students.
Lastly, I thank my family and friends for their loving support, practical advice, and unconditional encouragement, without which this work would not have been possible. vi
TABLE OF CONTENTS
Page
INTRODUCTION………………………………………………………………………..... 1
MATERIALS AND METHODS ...... 5
Test subjects and Housing ...... 5
Behavioral Analysis and Score ...... 5
Aggressive Dyadic Interactions ...... 6
Experimental Arena ...... 6
Testing Procedures ...... 6
Modified Mirror Image Stimulation ...... 7
Experimental Arena ...... 7
Testing Procedures ...... 7
Statistical Analysis ...... 8
Size-matched Dyads ...... 8
Modified Mirror Image Stimulation ...... 9
Comparisons of Flat Mirror Images to Size-matched Opponents ...... 10
RESULTS ………………………...... 11
Behavioral Observations………………………………………………………………..11
Sex-Specific Differences in Size-matched Dyadic Contests ………………………… 11
Size-Dependent Differences in Fighting Behavior ...... 13
Altering Opponent Size...... 13
Comparing Responses to Mirror Images and Live Opponents ...... 14
Body Size Alters Fighting Towards Flat Mirror Images ...... 15 vii
DISCUSSION ...... 16
Sex-Specific Fighting Strategies ...... 16
Size-Specific Fighting Strategies ...... 17
Sequential Assessment is Sex-Dependent ...... 18
Modifying Opponent Size with MMIS Alters Decision-Making ...... 18
Differential Response Based on Opponent Type ...... 21
Conclusions ...... 22
REFERENCES……………………………………………………………………………… 23
APPENDIX …………………………………………………………… ...... 48 viii
LIST OF TABLES
Table Page
1 Ethogram ...... 34
2 Replicated Goodness of Fit (G-statistic) for differences in the frequency of Attack,
Assessment, and Non-aggressive behaviors for males and females ...... 35
3 Behavioral frequency. A summary of the overall frequencies for each type of behavior (N
= 17) exhibited by males and females during size-matched dyads ...... 35
4 Principle Components Analysis ...... 37
5 Male Transition Matrix ...... 38
6 Partial correlation matrix that shows behavioral associations to Body Size in size-
matched dyads ...... 40
7 Partial correlation matrix that shows associations between Body Size and the frequency
of individual fighting behaviors in size-matched dyads ...... 41
8 MMIS. Behavioral Frequency ...... 42
9 MMIS: ANOVA ...... 43
10 Test Effects of the ANOVA (Table 9) ...... 43
11 MMIS: MANOVA ...... 43
12 Replicated Goodness of Fit (G-statistic) for opponent type ...... 45
13 Partial correlation matrix that shows behavioral associations to Body Size in MMIS trials
for males and females ...... 46
14 Partial correlation matrix that shows associations between Body Size and the frequency
of individual fighting behaviors in (a) females and (b) males facing flat mirror images 47 ix
LIST OF FIGURES Figure Page
1 Oblique view of experimental arena for MMIS ...... 33
2 Percentage of Behaviors: Size-matched dyads ...... 36
3 Flow chart of male Transition Matrix ...... 39
4 S-Shape Display exhibited by female M. auratus ...... 43
5 Canonical Centroid Plot ...... 44
6 Percentage of Behaviors for Opponent Type ...... 48
1
INTRODUCTION
Fighting in fishes relies heavily on informative cues that aid in aggressive decision- making. East African cichlids, well-known for their hyper-aggressive nature and tendency to engage in intense fighting behavior, make ideal models for probing the factors that are influential in aggressive decision-making. Malawi cichlids share a high degree of genomic similarity (more than laboratory strains of Danio rerio; Loh et al. 2008), yet boast of nearly 1000 species that display wide ranges of morphological, ecological, and behavioral distinction, resulting in a radiation unmatched among vertebrate taxa (Kocher 2004; van Doorn et al. 2004; Kanyumba et al. 2012; Sluis et al. 2013). Geographic restriction to relatively shallow coastal waters has promoted the formation of dense, multi-species communities among Malawi cichlids, increasing the rates of social encounters and possibly contributing to the high degree of territoriality and extreme aggressiveness characteristic of the taxon (Genner and Tuner 2005).
When used in an ethological context, ‘aggression’ refers to behaviors that are associated with attacking or the threat of attacking (Francis 1988). Competitive interactions for resources excite fighting behavior and territorial skirmishes among neighboring cichlid species (Archer
1988; Kohda 1998; Maynard-Smith and Harper 2003; Genner and Turner 2005), and successful acquisition depends directly on the effectiveness of the competitive strategies chosen. Poor tactical fighting proves markedly expensive given the high degree of metabolic expenditure (i.e. oxygen and caloric consumption; Mann et al. 2001; Ros et al. 2006; Copeland et al. 2011), risk of bodily harm (scale and fin damage), and the forfeiture of the contested resource. Thus, adopting effective fighting strategies is critical to increasing fitness, and will, therefore, be subject to selection (Rutte et al. 2006). 2
The modalities recruited by cichlids to modulate these competitive strategies vary depending on environment, social context, or life history of a given species (Genner and Turner
2005; Verbeek et al. 2007). Multi-modal signaling plays a critical role in optimizing the effectiveness of competition by facilitating the communication of aggressiveness, while minimizing bodily injury from physical contact (Maynard Smith and Harper 2003; van Staaden and Smith 2011). Nonetheless, cichlids rely heavily on visual signaling to convey aggressive state (Seehausen and Schluter 2004; Dijkstra et al. 2006; Pauers et al. 2008), and less so on chemical (Maruska and Fernald 2011) or mechanosensory cues (Simoes et al. 2008). The ability to estimate opponent fighting ability based on visual information is thus central to making informed decisions about the method, or prudency, of further engagement.
The Sequential Assessment Model (SAM) provides a robust theoretical framework for understanding how differential fighting is employed in response to opponent ability, and has been observed in cichlids (Enquist et al. 1990). Unlike traditional game theory models (Maynard
Smith and Price 1973), SAM assumes that fighting ability is rarely equivalent between opponents (van Rhijn and Vodegel 1980) and predicts that low-cost signaling that provide minimal accuracy will be employed earlier in a fight to estimate opponent fighting ability.
Assessment with progressively more costly behaviors may continue if information about opponent ability is insufficient to gauge the likelihood of success (van Staaden et al. 2011).
Depending on the Resource Holding Potential (RHP) of an opponent, the combined sets of attributes that an individual brings to a fight, cichlids may choose to employ different assessment tactics based on body size (Keeley and Grant 1993), previous experience (Kasumovic et al. 2010;
Dijkstra et al. 2012), or prior residency (Parker 1974). Body size has emerged as one of the most critical elements for accurate visual assessment and indicators of success (Enquist and Jakobsson 3
1986; Enquist et al 1987; Hsu et al. 2008). In convict cichlids, there is an inverse relationship between the degree of phenotypic asymmetry of two contestants and the amount of time they engage in fighting (Enquist et al. 1990). Small body size asymmetries are generally insufficient to permit accurate prediction of success, and contestants must spend more time evaluating their opponents (Leiser et al 2004; Enquist et. al. 1990, Taylor and Elwood 2003). In contrast, when asymmetries are greater than 40%, little escalation occurs and contests are rapidly resolved
(Enquist and Jakobsson 1986).
The majority of SAM studies assume uniformity of fighting strategy among contestants and focus exclusively on the characterization of male-male competition. Reports of female aggressive behavior are common (Johnson 1988; Archer 1988; Cunningham and Birkead 1998;
Arnott and Elwood 2009), but few studies have explored the existence of fighting tactics equivalent to male counterparts. While many studies have demonstrated that males and females draw from a similar behavioral repertoire (Neil 1984; Holder et al. 1991; Draud et al. 2004;
Arnott and Elwood 2009, Reddon et al. 2011; Reddon et al. 2013; see Magurran and Garcia 2000 for review), whether or not there are biologically meaningful differences in the decision-making of male and female cichlids remains unclear (Hammerstein and Riechert 1988).
Aggressive decision-making has been measured in multiple ways (Rowland 1998), including the well-established Mirror Image Stimulation (MIS) method that uses flat mirrors to induce behavioral responses. Here we develop a modified version of Mirror Image Stimulation
(MMIS) incorporating additional concave and convex mirrors, to evaluate decision-making with respect to opponents of various sizes. We combine this novel MMIS method with size-matched encounters of live opponents in order to obtain a broad understanding of factors influential in aggressive decision-making. 4
Specifically, the study aims to (i) identify key sex- and size-specific differences in aggressive decision-making among size-matched pairs of adult Melanochromis auratus, (ii) investigate how tactical fighting is altered when opponent size is manipulated via MMIS, and, lastly, (iii) assess the efficacy of mirror use to assay aggressive decision-making by comparing responses from flat mirror images to those exhibited towards live opponents.
5
MATERIALS AND METHODS
Test subjects and Housing
Captive-bred juvenile Melanochromis auratus (Boulenger 1897) were obtained from a commercial supplier and raised to maturity in the lab. M. auratus is a small (4-9cm), sexually dimorphic, highly aggressive Malawi cichlid that maintains large, coastal territories positioned along rocky-outcrops (Markert et al. 1999). Their range is extensive, spanning from the southwestern to the southernmost portion of the lake, usually not exceeding depths of 10 meters
(Ribbink et al. 1983).
Fish were housed under a light:dark cycle of 12:12 hours and water temperature was maintained at 25oC ± 2oC. Feeding was administered daily ad libitum using high protein formula
Ocean Nutrition Veggie Flakes. Because of the aggressive nature of the species, individuals were housed separately. However, since complete social isolation may inflate aggressiveness (Earley et al. 2006), we chose to use mesh partitions to sub-divide 20-gallon aquaria into 3 single- occupancy compartments, thus preventing physical contact but permitting chemical and visual interaction. Small-gravel substrate provided ample digging opportunity and a small terra cotta pot was placed in each compartment to serve as shelter. Maintenance and experimental procedures were conducted in accordance with protocol #11-002 from the Animal Care and Use
Committee of Bowling Green State University.
Behavioral Analysis and Scoring
In a preliminary study, extended encounters were staged between same-sex, size-matched
M. auratus pairs and the video-recordings analyzed to establish a detailed ethogram for aggression in this taxon. All behavioral events throughout the pilot and experimental trials were 6 scored by a single observer using JWatcher behavioral software (Blumstein and Daniel 2007). To ensure consistency and repeatability of behavioral descriptions (i) additional observers were recruited to score portions of randomly selected contests, and (ii) several early encounters were scored by the primary observer multiple times until scoring reliability reached at least 90%. All trials were scored blind to preclude experimenter bias.
Aggressive Dyadic Interactions
Experimental Arena
The experimental arena was constructed of non-reflective, acrylic plexiglass (25cm x
25cm x 16cm) with one panel being clear to facilitate observation. White plastic was attached to the outside of each of the non-reflective panels to limit extraneous external visual stimuli. A
Sony HDR-HC9 MiniDV HD Camcorder positioned in front of the viewing panel recorded the interactions. Water conditions and temperature in the experimental arena were similar to that of holding tanks and all trials were conducted under ambient lighting.
Testing Procedures
Adult M. auratus (female = 5; male = 8) fought size-matched (within 10% wet body weight) opponents of the same sex. None of the animals had prior fighting experience and all pairs were unique. Rivals were separated during a 15-minute acclimation period by an opaque plastic barrier that prevented physical and visual contact. Once the opaque barrier was raised, video recording was initiated and continued for a trial duration of 7 minutes maximum. During this time contestants were continuously monitored on a screen situated behind a curtain to ensure that fighting did not escalate to levels where severe physical damage was sustained. Trials were terminated when an individual retreated, when there was a break in interactions between opponents for 60 seconds, or when aggression by one individual was judged to inflict severe 7 bodily damage on the opponent. All individuals were returned to their home enclosures immediately following testing.
Modified Mirror Image Stimulation
Experimental Arena
The experimental arena (Figure 1) was constructed of white, opaque acrylic measuring 28.5 x 32 x 38.5 cm. Three mirrors (concave, convex, and flat; 10 cm diameter) were mounted separately onto opaque acrylic panels that were positioned securely into tracks created from narrow strips attached 12.2 cm apart along the back wall of the tank. Mirrors were centered 7 cm from the bottom of the tank and water level was maintained at a depth of 18-20 cm to completely submerge the mirrors. An additional removable, acrylic panel the width of the arena, served to conceal the mirrors during acclimation. Water quality and temperature were similar to that of the holding tanks. Fish movements were monitored using ObjectTracker, a freeware program developed by R. Huber and available at
Testing Procedures
All three mirror types were presented simultaneously to the focal animal in different spatial locations (left, middle, right). There were six possible mirror configurations to which the fish could be exposed and each test subject was exposed to every possible configuration within a trial. The order was randomized such that no two fish received the same presentation order of mirror configurations. Absolute size of the reflected image depended on mirror type and proximity to the mirror surface. 8
At the beginning of each experiment, fish were restricted to the front half of the arena, shielded from mirror exposure by an opaque removable panel. Following acclimation for 15 minutes, the panel was lifted, exposing the individual to the first mirror configuration. After 7 minutes of recording, the panel was replaced for a period of two minutes while the mirror positions were reconfigured. After two minutes, the panel was removed, allowing the fish to interact with the second mirror configuration, and recording resumed. This procedure was repeated until all six mirror combinations were used, resulting in a cumulative trial duration of
52 minutes. A total of 22 trials were conducted (female = 15; male = 7)
Statistical Analysis
JMP 11.1statistical software package, public domain Java Applets (available at http://caspar.bgsu.edu/~software/Java/), and Python script were employed for all statistical analyses.
Sized-matched Dyads
Frequencies of observed behaviors were standardized due to heteroscedasticity.
Replicated Goodness of Fit (RGOF; Sokal and Rohlf 1995) compared frequencies of behaviors between males and females. Post hoc Freeman-Tukey analysis using Java Applets was used to look at cell-wise deviations that contributed to significance.
Likelihood ratio tests (chi square, X2) using behavioral transition matrices were performed to investigate inherent behavioral patterning among size-matched opponents. Limited sampling and lack of normality necessitated the use of randomization tests as an alternative method for significance testing. Transition matrices were constructed separately for males and females. A transition was said to have occurred when a behavior ended (row) and another began
(column), which included transitions into the same behavior. Each transition type (i.e. each cell 9 in the matrix) had an expected frequency derived by dividing the column totals by the number of behavioral categories. Using the observed and expected frequencies for each transition type, a X2 statistic was computed. To compute the test statistic, randomization was used to generate new matrices. Column totals were redistributed among the rows and a new table-wide X2 was computed for new each matrix generated. After 10,000 randomizations, the cumulative distribution of X2 created a probability density function for each sex and P values were calculated from the proportion of X2 statistics that were greater than the X2 obtained from the observed frequencies.
Similar randomization methods were employed post hoc to determine which transition types were responsible for table-wide significance. Column totals were randomly redistributed among the rows for each column. Instead of computing X2 for every cell, summing, and randomization occurring table-wide, single X2 were computed for each cell and 10,000 replications were done within each column, thereby generating probability density functions for each of the three columns (i.e. each behavior transitioned into). The observed X2 for each transition type (i.e. cell) was compared to the generated distribution for each column, obtaining cell-wise probability values. In essence this method allowed us to discover the probability of each behavior (row) transitioning into another (column).
Principle Components Analysis (Varimax rotation) was applied to detect clustering of behaviors in males and in females. It was also used to obtain a composite measure of body size using standard length (mm) and wet body weight (g). Correlation matrices for both sexes were created using frequencies and body size values (ranked). Analysis of variance was used to analyze the effect of sex on the duration of each behavior separately.
Modified Mirror Image Stimulation 10
Similar to size-matched dyads, behavioral observations for MMIS treatments were standardized. ANOVAs were conducted to test for the effect of mirror type (concave, convex, flat), mirror position (left, middle, right), and sex on the frequency of individual behaviors.
Multivariate analysis (MANOVA) was conducted globally on all behaviors, to detect correlations among behaviors and how they are influenced by sex and mirror type.
Comparisons of Flat Mirror Images To Size-Matched Opponents
In order to determine the effectiveness of mirror use, responses to size-matched, live opponents were compared to those elicited by flat mirror images. Replicated Goodness of Fit
(RGOF) were employed on the frequency of behaviors to determine the degree of similarity between responses. Correlation matrices were additionally constructed using the ranked values for body size to uncover size-dependent trends in fighting behavior unique to each sex. 11
RESULTS
Behavioral Observations
A total of 591 behavioral events (female = 197; male = 394) were observed from size- matched dyads and categorized into seventeen named behaviors that together comprised the ethogram outlined in Table 1. All behaviors were exhibited by both sexes, though not by every individual. While most behaviors have been previously described in other cichlid aggression studies (Enquist et al.1990; Koops and Grant 1992; Neat 1998), we did characterize four that had not been previously defined: t-stand display, swimming over opponents, darting away from opponents, and hovering near opponents. Both males and females exhibited t-stand displays in between bouts of intense fighting, but this did not appear instrumental in inflicting injury to opponents. Instead, individuals would align perpendicularly, with one individual positioning its head near the pelvic fins of the rival, and hold the position for several seconds. Attempting to swim over or dart away from an opponent were two other behaviors also observed during fighting bouts. darting occurred when an individual quickly retreated but immediately returned to reengage in fighting; this was relatively infrequent in either sex. Hovering laterally (or frontally) was done near an opponent or at a distance and never involved the extension of caudal or anal fins (distinguishing it from lateral or frontal displays).
Sex-Specific Differences in Size-matched Dyadic Contests
Overall, males were more active in dyadic encounters than females, displaying greater mean number of behavioral acts (N=49.25 vs 39.4) as well as higher absolute frequencies in 11 of 17 behavioral categories (Table 3). However, there was no substantial difference in the standardized duration of any particular behavior (see APPENDIX for individual ANOVAs). 12
Specific behaviors that were relevant to male and female fighting strategies were identified using Principle Components Analysis (Tables 4a and b). Three factors accounted for over 90% of the variation in either sex. PC 1 (Eigenvalue = 3.52) explained >45% of the variation in males and included three contact behaviors (biting, tail beating, and pushing) and one non-contact behavior (t-stand). Displays and hovers loaded secondarily onto PCA 2
(Eigenvalue = 1.73; 24% variance). Females exhibited nearly the opposite behavioral trends.
Display and hovers, along with tail beating constituted PCA 1 (Eigenvalue = 3.22; variance explained = 42%); while, biting, pushing, and swimming over an opponent loaded onto PCA 2
(Eigenvalue = 2.86; 40% variance). Circling was not displayed by any of the females tested, though females have been observed to exhibit the behavior (personal observations). In males, circling was combined with biting for statistical analysis.
Significant sex-specific differences were found in the frequency of fighting behaviors
(Table 2; RGOF G=58.90), though substantial variability among individuals was also observed for each sex (Table 2; RGOF within males=83.16; within females=114.62). For statistical purposes, behaviors were combined on the basis of proximity to opponents. Males attacked
(contact behaviors) nearly three times more often than did females (Figure 2; N=324 vs 103), the later opting for mostly assessment (non-contact behaviors; N=71) or non-aggressive activities
(non-opponent directed behaviors; N=23). There was no indication that the individuals who initiated fights also won them (Fisher’s Exact Test: Left tail, P=0.68; Right tail, P=0.75). Six of the thirteen contests were draws (female=2; male=4); whereas five ended with one opponent retreating immediately (<1min; female=3; male=2).
Randomization tests on transition matrices also revealed significant structural organization to male (X2=469.218, P= 0.0478), but not female (X2= 107.803, P=0.803), 13 competitive interactions. Post hoc cell-wise analysis (Table 5; Figure 3) uncovered significant tendencies for males to transition frequently (80%) into high intensity fighting behavior. Attack- to-attack (p<<0.001 was the most common transition type for males, though escalations from assessment (p<<0.001) or non-aggressive states (p<<0.001) into attack behavior were also significant.
Size-Dependent Differences in Fighting Behavior
Relationships of each behavior to body size are summarized in correlation matrices
(Tables 6 and 7). There were robust positive associations between body size and the use of attack behavior in both sexes. Smaller females were more likely to engage in non-contact behavior, unlike males, who showed no such tendencies. Instead, smaller, rather than larger, males showed increased rates of chasing size-matched opponents.
Altering Opponent Size
MMIS trials were scored using the same ethogram used for size-matched dyads with two modifications. Circling, pushing, and swimming over an opponent were excluded from analysis due to the physical limitations inherent to fighting mirror images. S-shape display and charging were uniquely exhibited towards mirrored opponents and added to MMIS analyses (Table 8).
Analysis of variance showed a significant effect of apparent opponent size on the time spent interacting with mirrored images in both sexes (Table 9). Higher interaction duration with larger apparent opponents was observed, compared to smaller or same-sized ones (Table 10).
There was no interaction between sex and mirror type (p=0.554), as both males and females shared similar behavioral preferences with respect to the larger mirror image. 14
Mirror type also showed a significant effect on the frequency of eight of the eleven behaviors observed by either sex (APPENDIX 2 for Analysis of variance), whereas the effect of mirror position was negligible and excluded from subsequent analyses.
Male and female responses to mirror images were generally similar (Table 11;
MANOVA Wilk’s; NumDF = 24; DenDF = 758; P = 0.357; Appendix 3 for Eigenvalues), but distinguishing trends were observed. Of the eleven behavioral measures, all but two proved important in differentiating male and female strategic decision-making.
Differences in fighting behavior between males and females can be visualized with a canonical centroid plot (Figure 5), which summarizes the direction and extent of behavioral differences associated with apparent opponent size. Males and females showed similar responses towards small and like-sized reflections, but deviations with respect to apparent larger opponents. Frontal hovers were negatively correlated with frontal and lateral displays and biting, which males distinctly targeted at larger mirror images. Female behavior towards larger opponents was negatively related to that of males, females opting for frontal hovering and swimming. Lateral behavior by males in the form of hovers and displays was inversely related to charging, which was distinctive of smaller and same-sized opponents. Males were more actively aggressive (charging) towards flat mirror images, whereas females reserved most active aggression (tail beating) for convex images. Thus, we interpret Canonical 1 as representing a more reactive strategy by males and Canonical 2 as the less volatile strategy of females.
Comparative Responses to Mirror Images and Live Opponents
In both the MMIS and size-matched dyads, individuals displayed substantial variability in the frequency of attack, assessment, and non-aggressive behaviors (Table 12; flat mirror images
G = 906.62; size-matched live opponents G = 434.74). There were also significant differences in 15 the frequency of responses (df = 4; G = 353.34) based on opponent type. Freeman-Tukey was applied post hoc and showed that live, size-matched opponents elicited more attacking, than assessment or non-aggressive behaviors (Figure 6). In contrast, individuals showed a decreased rate of attacking towards flat mirror images and an increase in assessment and non-aggressive behaviors.
Body Size Alters Fighting Towards Flat Mirror Images
Similar to correlation matrices of sized-matched dyads, larger males had distinct biases for particular behaviors (Table 13b). Unlike size-matched dyads, however, this bias weighed heavily towards attacking. Larger males tended to engage in biting, charging, and s-shape behavior more frequently than smaller males, who showed equally strong preferences to explore flat mirror surfaces (Table 14 b). There was also a weaker positive correlation in larger males to hover, rather than display. Female decision-making showed no substantial correlation with body size (Table 14a).
16
DISCUSSION
Understanding the underlying factors that direct aggressive decision-making is essential to increasing our knowledge of the behavioral complexities of African cichlids during competitive social interactions. Using a highly territorial, rock-dwelling cichlid, Melanochromis auratus, our study supports the existence of intersexual differences in the expression of overt aggression that may also be influenced by body size. When fighting size-matched opponents, male M. auratus were unexpectedly characterized by intense and rapid escalation into fighting, rather than by the progressive assessment strategies previously established in other cichlid taxa.
We also were able to demonstrate the usefulness of modifying standard mirror image stimulation methods for measuring aggressive responses that are contingent upon opponent size. In light of accepted game theory models that predict differential behavior towards opponents of varying sizes, the responses towards different mirror types during MMIS was surprisingly similar to what would be expected in natural fighting when faced with opponents of larger or smaller size.
Sex-Specific Fighting Strategies
Sex-specific fighting was observed in both MMIS and size-matched dyads. While male and female fighting strategies employed similar types of behavior, each sex showed distinct reliance on certain behaviors above others. Males emerged clearly as the more aggressive sex. When faced with size-matched opponents, they responded with close-contact Attack behaviors (viz., tail-beating, biting, circling, pushing, and swimming over) three times more frequently than did females. Females, in contrast, primarily opted for assessment behaviors (displays and hovers;
Figure 2; Table 3 and 4).
These results are consistent with previous findings in both social and non-social cichlid species that indicate males will attack and display more frequently than females do when 17 presented with opponents or novel stimuli (Archard and Braithwaite 2011; Hick et al. 2014).
Sex-specific differences have likewise been reported in the group-living South American cichlid
Amatilania (Cichliasoma) nigrofasciata (Barlow 1976), where females, rather than males show increased rates of biting and frontal displays (a precursor to attack behavior; Cole et al. 1980;
Arnott and Elwood 2009). Other studies, however, indicate an absence of sex-dependent aggressive strategies (Reddon et al. 2011; Reddon et al. 2013). In these cases, fights were staged between randomly selected pairs of subordinate individuals (about half of which had prior exposure to experimental testing) taken from mixed-sex groups where dominance relationships were already established, making contests asymmetric with respect to prior experience, social status, and body size.
Size–Specific Fighting Strategies
Decisions about the frequency and duration of aggressive encounters have been shown to be influenced by body size of the aggressing fish (Enquist and Jakobsson 1986; Nelissen 1992;
Turner 1992; Neat 1998; but see Enquist et al. 1990 for opposing view). Results from both
MMIS and size-matched contests indicate that body size influences how often fighting behaviors are displayed, but not how long individuals chose to employ them. When fighting size-matched live opponents, larger males showed increased aggression compared to females and smaller males (Table 6 and 7). Similarly, when interacting with flat mirrors that produce images of equal-sized opponents, larger males behaved more aggressively than did smaller males. Only a single non-aggressive behavior (darting) was positively correlated with increases in size. This is likely because during high intense fighting bouts, individuals often darted away quickly from live opponents, but return immediately to reengage. Displaying and tail beating showed negative correlations with body size in females, unlike males. 18
In at least one case, smaller males have been reported as being more aggressive than larger males, not less as we observed. Leiser et al. (2004) showed distinct differences in both the early assessment phases and escalated fighting behavior from large and small size-matched fighting pairs of convict cichlids. While the overall use of behaviors was similar between small and large dyads, smaller males tended to utilize tail beating, biting, and chasing earlier in a fight sequence than did larger males, who employed lateral displaying for longer periods of time and progressed through escalation at slower rates. In contrast, males in the current study did not follow this inverted trend, rather larger males were more likely to engage in intense fighting behavior, not smaller males.
Sequential Assessment Is Sex-Dependent
Sequential assessment has been well established in several cichlid taxa (Enquist et al.
1990; Koops and Grant 1992; Keeley and Grant 1993). Contests are characterized by distinct
“phases” that begin with assessment behaviors, such as displays, then progress into more intense tail beating, and, finally, culminate with biting or mouth wrestling, until one opponent retreats.
In the present study, males, but not females, showed tendencies to structure fighting behavior, but did not progress sequentially through increasing states of aggressiveness (Table 5; Figure 3).
Instead, they exhibited consistent and rapid escalation into high intensity attacking, as indicated by the over-abundance of attack-to-attack transitions in size-matched dyads. These unexpected trends demonstrate that, not only will male M. auratus escalate faster, but that they will remain in higher aggressive states longer than would be predicted by traditional sequential assessment models.
Modifying Opponent Size With MMIS Alters Decision-Making 19
The MMIS detected differential behavior based on opponent size in males and females.
Both sexes chose to spend more time interacting with the larger apparent opponents (concave mirror), relative to opponents of smaller (convex mirror) or equal (flat mirror) size, and we were able to identify key sex-specific behaviors based on perceived opponent size (Table 11; Figure
5). M. auratus females showed limited fighting behavior towards larger opponents and mostly hovered near or explored mirror surfaces. However, in males, larger apparent opponents elicited more bites and aggressive displays. This is consistent with observations by Neat (1998) who noted that small males tended to direct biting towards larger rivals, rather than the converse, but if opponents were of equal size, absolute body size did not influence overall biting frequency.
SAM models predict that when faced with rivals of greater body size, smaller individuals will rely heavily on assessment strategies and delay attacking. Males showed strong tendencies to display aggressively at larger apparent opponents; while, biting was of secondary importance
(Table 11; Figure 4). Aggressively attacking with charging and tail beating was reserved for smaller or equal-sized opponents. S-shape display (Figure 4) was also mostly exhibited towards smaller or equal-sized opponents. While not an attack behavior per se, contortions into the distinct “S” shape have been previously associated with preparations to strike (Myrberg 1995;
Schriefer and Hale 2004). Draud (2004) found that when there were large asymmetries in male- male contests, smaller males would display more towards larger contestants whereas larger rivals would frequently chase smaller contestants. Males in the current study behaved likewise.
Similarly, in the MMIS, larger apparent opponents (concave mirror) received more displays from
‘smaller’ males; while opponents of smaller (convex mirror) and equal-size (flat mirror) were attacked with charging and tail beating by ‘larger’ or ‘similar-sized’ rivals respectively.
Contrary to trends associated with live opponents, in MMIS fights, biting was preferentially 20 targeted at larger apparent opponents. This may be an artifact of the ‘unnatural’ feedback provided by MMIS, causing the focal animal to behave more aggressively than they would in a natural fight. Image distortion due to curvature of the mirror surface is also a potential confounding variable. At a distance of 1 cm away from the surface of a concave mirror, objects were magnified approximately 7%; however, moving 5 cm away increased magnification nearly
90%. Therefore, responses to images produced by concave mirrors may be influenced by the variability of magnification as a product of distance, as well as whether the image remains upright or inverted, depending on the precise location of the individual relative to the focal point of the mirror (Gallup 1968). Most behaviors, and all attack behaviors, however, were exhibited less than half a body length from the mirror surface and far from the point of inversion (focal length = 15 cm). Thus, image distortion or inversion is very unlikely to have influenced aggressive responses. The clear behavioral distinctions based on apparent opponent size indicate that the minimal visual distortion that did occur played little or no role in altering behavior.
Alternatively, we speculate that surface curvature may enhance the effectiveness of hydrodynamic feedback from concave mirrors. tail beating communicates aggressiveness by directing pulses of water at the body surface of rivals, who detect the hydrodynamic force of the tail beat with flow-sensing receptors along its lateral line (Enquist et al. 1990). When this behavior is instead directed at a concave mirror, the inward sloping curvature of the mirror surface acts like a parabolic reflector that focuses the reflected water back in a more targeted, compressed fashion compared to the dispersed reflection of the convex or flat mirrors. The focused reflection may, therefore, mimic the stronger tail beating responses reciprocated by larger opponents in natural fighting. 21
Draud (2004) found that size-dependent strategies only existed in male contestants and suggested that female fish do not conform to SAM predictions, but instead relied on the value placed on the contested resource (Resource Payoff Value, RPV). Unlike their male counterparts, females in the present study gave no indication of sequential assessment in size-matched dyadic interactions. We did, however, observe differential behavior in females as opponent size was altered. Although responses were similar to that of males, when interacting with smaller or same- sized rivals, increases in apparent opponent size were accompanied by increased latencies for females to engage. Although sample size limitations preclude firm conclusions, the differential response to opponent images of varying size by females in MMIS trials does suggest that reliance on the Resource Holding Potential (RHP) of a rival as a decision-maker may be more important than previously thought.
Differential Response Based on Opponent Type
Opponent type impacted the fighting strategy of M. auratus. Attacking behavior was targeted at size-match live opponents, while individuals were more likely to assess or behave non-aggressively towards mirror images. Differences of this nature have led to criticism of mirror assays to measure aggression (Gallup 1968). Behavioral synchronization with mirror images may lead to abnormal activity, such as hyper-aggression, and has been observed previously in other taxa (Betta splendens Baenninger 1966; Rivulus marmoratus Earley 2000).
Conversely, based on substantial increase in egr-1 and c-fos expression in the dorsomedial telencephalon (homologous to the amygdala in human brains), Desjardins and Fernald (2010) claim that the ‘unnatural’ feedback from mirror image opponents induces fear. However, the fact that multiple fish species exhibit mirror entrainment behavior makes Desjardins and Fernald’s interpretation difficult to accept. The use of mirrors to assay aggression clearly has limitations, 22 such as the lack of chemical (Maruska and Fernald 2011) or auditory (Bertucci 2010) cues that are associated with aggressive signaling. Other methods, such as models (Beeching 1995; Earley
2000) or video images (Rowland et al. 1994; Fleishman and Endler 2000; Verbeek et al. 2007) have been employed in lieu of MIS to induce aggressive behavioral responses in fishes, but fail to provide a demonstrably superior alternative. The differential behavior observed by individuals in the current study towards rivals of different sizes indicates that MMIS methods can provide an informative method for testing aggression in fish.
Conclusions
Both sex and body size have the capacity to influence aggressive decision making during symmetric contests in Melanochromis auratus. We conclude that by manipulating perception of opponent size, differential aggressive responses in accordance with the prediction of SAM can be induced, demonstrating the efficacy of the novel modified MIS approach. Despite the fact that
M. auratus behaves more aggressively towards flat mirror images than towards live opponents, mirror use remains a powerful ethological tool in aggression studies, especially if modified methods are employed. 23
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FIGURES AND TABLES
Figure 1. Oblique view of experimental arena for MMIS. Mirrors panels slide into tracks along the back wall. Acrylic partitions separate mirrors and a removable, opaque panel (not shown) shielded test subjects from mirrors prior to testing. SONY digital camera positioned towards the front panel of the arena (not shown).
34
Table 1. Ethogram. Behaviors (N=17) are categorized as attack, assessment, or non-aggressive, based on proximity to opponent. Attacking consisted of behaviors where opponents inflicted injury or made contact. Assessment behaviors were within half a body length, but generally did not involve contact between rivals. Non-Aggressive behaviors were any behavior that was not directly targeted at the opponent. The ethogram was used to score size-matched dyads and was modified for MMIS scoring.
Behavior Description Attack Behaviors Behaviors involving physical contact with the opponent Biting Bout of bites made in rapid succession Circling Rotation either clockwise or counterclockwise in the head-to-tail position Over Movement over the top of an opponent Tail Beat Tail motions (slaps) that forcefully direct water towards the lateral line of an opponent Chasing Rapid pursuit of rival Mouth Wrestling Locking onto the mouthparts of a rival Push Displacing an opponent Assessment Behaviors Non-contact interactive behavior Lateral Display Left- or right-orientation that is relatively parallel to opponent Anal or pelvic fins visible. Caudal fins usually perpendicular to the body Frontal Display Oriented frontally relative to opponent. Anal or pelvic fins visible. Caudal fins usually perpendicular to the body Lateral Hover Contestant in a left- or right-oriented position and laterally to the opponent. No anal or pelvic fins visible Frontal Hover Oriented frontally relative to opponent. Anal or pelvic fins not visible. T-stand Stationary hovering perpendicular to rival with the head position near the anal fins, forming a “T” shape Non-Aggressive Behaviors Submissive or non-interactive behaviors Explore Swimming along a surface Swim General movement around the tank Retreat contestant repeatedly swims away from rival Dart A quick, jerky movement away from opponent, but not a retreat
35
Table 2. Replicated Goodness of Fit (G-statistic) for differences in the frequency of attack, assessment, and non-aggressive behaviors for males and females. Rows 1 and 2 indicate the variability in the frequency of attack, assessment, and non-aggressive behaviors within all males (N=8) and within all females (N=5). The variability between the gender groups (all males vs all females) is reported in Row 3. Because the expected frequencies used to calculate the G-statistic were obtained by finding the total for each behavioral category by the total for all behaviors exhibited by each sex, the pooled G-statistic was zero.
Pooled Heterogeneity P value Male 0 83.159 >0.001 Female 0 114.623 >0.001 Between 0 58.902 >0.001
Table 3. Behavioral frequency. A summary of the overall frequencies for each type of behavior (N = 17) exhibited by males and females during size-matched dyads.
Behavior Female Male Approach 2 4 Bite 11 84 Dart 3 7 Explore 3 6 Chase 0 2 Over 31 36 Push 59 160 Retreat 3 3 Swim 12 6 Tail beat 1 21 T-stand 1 5 Mouth Wrestle 1 1 Circle 0 20 Frontal Display 1 0 Lateral Display 51 10 Frontal Hover 2 1 Lateral Hover 16 28 Total 197 394
36
** ** **
**
Figure 2. Percentage of Behaviors: Size-matched dyads. The percentage for seven select behaviors are graphed for males (blue) and females (red). Percentages were based on the total number of behaviors exhibited for males (N=394) and females (N=197); while post hoc Freeman-Tukey Deviates determined which behaviors were exhibited significantly more or less when compared to the other sex (delineated by asterisks). 37
Table 4. Principle Components Analysis. This was done to find groupings of related behaviors in (a) females and (b) males. Varimax rotation was done on Principle Components and the rotated loading factors reported below. Sign indicates the direction of correlation.
Behavior PCA 1 PCA 2 PCA 3 Bite -0.139 0.987 -0.082 Tail beat 0.969 -0.038 -0.242 T-stand -0.021 -0.206 0.978 Over -0.156 0.980 -0.115 Push 0.197 0.966 -0.165 Display 0.987 -0.136 0.087 Hover 0.995 0.059 0.080 Variance 2.99 2.93 1.08 EigenVal 3.22 2.86 0.91 Percent 42.67% 41.91% 15.39% Cumulative% 42.67% 84.57% 99.97%
(b) Behavior PCA 1 PCA 2 PCA 3 Bite 0.985 -0.019 0.167 Tail beat 0.941 0.099 -0.289 T-stand 0.698 -0.173 0.592 Over 0.059 0.024 0.972 Push 0.910 0.123 0.369 Display 0.156 0.905 0.252 Hover -0.081 0.902 -0.270 Variance 3.21 1.69 1.68 EigenVal 3.52 1.73 1.32 Percent 45.79% 24.13% 23.98% Cumulative% 45.79% 69.392% 93.91%
38
Table 5. Male Transition Matrix. This reports the number of each transition type (bolded). Rows represented transitioned out of; while columns represented behaviors transitioned into (Example: attack-to-assessment = 19). Chi square statistic (X2) was calculated post hoc via randomization methods and P values identify which transition types were significant compared to others (delineated by asterisks). Dunn-sidak correction was used due to multiple comparisons (P > 0.00568).
Attack Assessment Non-Aggression Attack N 290 19 15 X2 306.704 2.769 2.108 p <<0.001** 0.010 0.080 Assessment N 26 11 7 X2 62.259 0.308 1.075 p <<0.001** 0.770 0.390 Non-Aggression N 8 9 9 X2 92.593 1.230 0.172 p <<0.001** 0.310 0.870
39
Figure 3. Flow chart of male Transition Matrix. This was constructed from values in Table 5, depicts the transitional structure of male fighting. Significant transitions (red) were mostly in the direction of attacking behavior. Dunn-sidak correction was used due to multiple comparisons (α > 0.00568). 40
Table 6. Partial correlation matrix that shows behavioral associations to Body Size in size- matched dyads. The frequency of attack, assessment, and non-aggressive behaviors in (a) females and (b) males (N = 13) were correlated to body size. Correlation values close to 1 indicate strong correlations with increased Body Size (ranked) and non-positive correlation values indicate negative relationships between behaviors.
(a) Behavior Correlation value Attack 0.588 Assessment -0.657 Non-Aggressive -0.362
(b) Behavior Correlation value Attack 0.723 Assessment 0.113 Non-Aggressive 0.400
41
Table 7. Partial correlation matrix that shows associations between Body Size and the frequency of individual fighting behaviors in size-matched dyads The body size of (a) females and (b) males was correlated to body size in size-matched dyads (N = 13). All hovers, and all displays were combined. mouth wrestling was displayed only once for each sex and not included.
Aggressive behavior Correlation Value Approach -0.318 Dart 0.780 Explore 0.106 Chase 0.000 Over 0.704 Push 0.500 Retreat -0.637 Swim -0.571 Tail beat -0.650 T-stand 0.000 Display -0.684 Hover -0.560 Bite 0.730
(b) Aggressive behavior Correlation Value Approach -0.075 Dart 0.626 Explore 0.170 Chase -0.674 Over 0.308 Push 0.720 Retreat -0.064 Swim 0.252 Tail beat 0.621 T-stand 0.601 Display 0.100 Hover 0.108 Bite 0.713
42
Table 8. MMIS. Behavioral Frequency. The behavior of (a) females (N=15) and (b) males (N=7) towards each mirror type (concave, convex, flat) compiled into a frequency table.
(a) Behavior Concave Convex Flat Charge 13 72 48 Bite 210 629 579 Tail beat 4 67 39 Lateral Display 402 383 335 Lateral Hover 885 410 487 Frontal Hover 118 20 53 Frontal Display 37 6 11 S-shape Display 34 61 59 Jump 13 1 3 Swim 14 3 15 Explore 1045 682 671 Total 2775 2334 2300
(b) Behavior Concave Convex Flat Charge 12 33 44 Bite 348 313 334 Tail beat 0 5 1 Lateral Display 499 278 239 Lateral Hover 497 250 222 Frontal Hover 26 6 12 Frontal Display 54 16 16 S-shape Display 21 15 17 Jump 5 0 2 Swim 10 10 12 Explore 570 323 287 Total 2042 1249 1186
43
Figure 4. S-shape display exhibited by female M. auratus. Here the body is contorted on the horizontal plane in a distinct “S” shape.
Table 9. MMIS: ANOVA. This tested the effect opponent size (mirror type) and sex had on the amount of time fish spent interacting with mirrors during MMIS.
Source DF Sum of Squares Mean Square F Ratio Prob > F Model 5 2.24693E+11 44938508490 5.262742935 0.000109 Error 390 3.33021E+12 8538989847
C. Total 395 3.5549E+12
Table 10. Table 10. Test Effects of the ANOVA (Table 9). This shows a significant effect of mirror type on time spent interacting with a larger mirror images (Tukey HSD), but not an effect of sex or an interaction.
Source Nparm DF Sum of Squares F Ratio Prob > F Sex 1 1 3E+09 0.351524 0.553595 Type 2 2 1.87E+11 10.93042 2.41E-05** Sex*Type 2 2 2.97E+08 0.017364 0.982787
44
Table 11. . MMIS: MANOVA. This investigated the sex-specific trends in behavior (frequency standardized) towards larger (concave), smaller (convex), or similarly-sized (flat) opponents.
Test Value Exact F NumDF DenDF Prob>F F Test 1.20289 0.8592 7 5 0.5883
Figure 5. Canonical Centroid Plot (see APPENDIX 3 for centroid values). Original variables are plotted as vectors along canonical axes and extend outward in a direction that imparts correlation. Directional movement of vectors away from the grand mean indicate their ability to distinguish the putative opponent-based strategies of each sex. Vectors aligned in the same directions share positive correlations; while, vectors aligned in the opposing direction share negative correlations. Uncorrelated vectors are plotted orthogonally. Circles represent groupings of data points around a multivariate mean with a 95% confidence interval. Thus, variations in circle size indicate variations in sample size (small circle indicates a larger sample size). The placement of these circles is determined by the degree of effectiveness from each behavior.
45
Table 12. Replicated Goodness of Fit (G-statistic) for opponent type. Rows 1 and 2 indicate the variability in the frequency of attack, assessment, and non-aggressive behaviors within all individuals in interacting with flat mirrors (N = 17) and within all individuals fighting a size- matched opponent (N = 11). The variability between the two groups (flat mirror vs live opponent) is reported in Row 3. Because the expected frequencies used to calculate the G- statistic were obtained by finding the total for each behavioral category by the total for all behaviors exhibited by each sex, the pooled G-statistic was zero in all cases.
Pooled Heterogeneity P value Flat Mirror 0 906.62 >0.001 Live Opponent 0 434.74 >0.001 Between 0 353.46 >0.001 46
Table 13. Replicated Goodness of Fit (G-statistic) for opponent type. Rows 1 and 2 indicate the variability in the frequency of attack, assessment, and non-aggressive behaviors within all individuals in interacting with flat mirrors (N = 17) and within all individuals fighting a size- matched opponent (N = 11). The variability between the two groups (flat mirror vs live opponent) is reported in Row 3. Because the expected frequencies used to calculate the G- statistic were obtained by finding the total for each behavioral category by the total for all behaviors exhibited by each sex, the pooled G-statistic was zero in all cases.
(a) Aggressiveness Correlation value Attack -0.305 Assessment -0.265 Non-Aggressive -0.036
(b) Aggressiveness Correlation value Attack 0.804 Assessment 0.446 Non-Aggressive -0.497
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Table 14. Partial correlation matrix that shows associations between Body Size and the frequency of individual fighting behaviors in (a) females and (b) males facing flat mirror images.
Behavior Correlation value Display 0.156 Hover -0.386 Charge -0.142 Explore 0.017 Jump -0.089 Swim 0.132 Tail beat -0.499 S-Shape -0.043 Bite -0.173
(b) Behavior Correlation value Display 0.206 Hover 0.588 Charge 0.465 Explore -0.604 Jump -0.265 Swim 0.305 Tail beat 0.314 S-Shape 0.854 Bite 0.837
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Figure 6. Percentage of Behaviors for Opponent type. Total number of behaviors ellicted to Flat mirror images (N = 3410) and Live opponents (N = 902) were used to calculate percentages for each behavioral category. 49
APPENDIX
Appendix 1 . Univariate analysis (ANOVA) on the standardized duration of individual behaviors during size matched dyads. This was done to detect the effect of sex on the duration of behaviors. All displays and all hovers were combined. Biting included instances of circling. Mouth wrestling and chasing were excluded due to very low incident rate.
Behavior DF Sum of Squares Mean Square F Ratio Prob > F Bite Sex 1 1.4288 1.4288 1.4868 0.2482 Error 11 10.5712 0.9610 Total 12 12
Display Sex 1 2.8160 2.8160 3.3728 0.0934 Error 11 9.1840 0.8349 Total 12 12
Hover Sex 1 0.3433 0.3433 0.3239 0.5807 Error 11 11.6567 1.0597 Total 12 12
Swim Sex 1 0.3546 0.3546 0.3349 0.5744 Error 11 11.6454 1.0587 Total 12 12
Tail beat Sex 1 0.9119 0.9119 0.9046 0.3620 Error 11 11.0881 1.0080 Total 12 12
T-stand Sex 1 0.5002 0.5002 0.4785 0.5034 Error 11 11.4998 1.0454 Total 12 12
Over Sex 1 0.0155 0.0155 0.0142 0.9071 Error 11 11.9845 1.0895 Total 12 12
Push Sex 1 0.1845 0.1845 0.1717 0.6866
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Error 11 11.8155 1.0741 Total 12
Explore Sex 1 0.2077 0.2077 0.1937 0.6684 Error 11 11.7923 1.0720 Total 12 12
Approach Sex 1 0.0727 0.0727 0.0671 0.8004 Error 11 11.9273 1.0843 Total 12 12
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Appendix 2. Univariate analysis (ANOVA) investigated the effect sex, mirror position (left, middle, right), mirror type (concave, convex, and flat), and their interactions had on the standardized frequency of 12 behaviors (including Time Spent; ms) for MMIS trial. Asterisks denote significance.
Behavior DF Sum of Squares F Ratio Prob > F
Time Spent Sex 1 0.333 0.353 0.553 Position 2 5.670 3.006 0.051
Sex*Position 2 2.246 1.191 0.305
Type 2 20.688 10.966 <0.0001**
Sex*Type 2 0.033 0.017 0.983
Position*Type 4 0.519 0.138 0.968
Sex*Position*Type 4 1.432 0.379 0.823
Explore Sex 1 0.263 0.278 0.598 Position 2 2.545 1.343 0.262
Sex*Position 2 0.362 0.191 0.826
Type 2 27.265 14.392 <0.0001**
Sex*Type 2 1.329 0.702 0.497
Position*Type 4 0.957 0.253 0.908
Sex*Position*Type 4 0.194 0.051 0.995
Charge Sex 1 2.332 1.992 0.159 Position 2 6.215 2.655 0.072
Sex*Position 2 6.299 2.691 0.069
Type 2 15.081 6.442 0.0018**
Sex*Type 2 2.510 1.072 0.343
Position*Type 4 3.177 0.678 0.607
Sex*Position*Type 4 2.661 0.568 0.686
Frontal Display Sex 1 22.379 17.576 <0.0001** Position 2 0.998 0.392 0.676
Sex*Position 2 1.744 0.685 0.505
Type 2 31.913 12.532 <0.0001**
Sex*Type 2 7.436 2.920 0.055
Position*Type 4 11.905 2.338 0.055
Sex*Position*Type 4 13.058 2.564 0.038
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Jump Sex 1 0.042 0.055 0.815 Position 2 0.816 0.530 0.589
Sex*Position 2 0.182 0.118 0.889
Type 2 8.727 5.670 0.0037**
Sex*Type 2 0.208 0.135 0.874
Position*Type 4 5.642 1.833 0.122
Sex*Position*Type 4 1.926 0.626 0.644
Swim Sex 1 5.335 6.412 0.0117* Position 2 1.452 0.873 0.419
Sex*Position 2 0.665 0.400 0.671
Type 2 1.652 0.993 0.372
Sex*Type 2 0.763 0.459 0.633
Position*Type 4 9.768 2.935 0.0207*
Sex*Position*Type 4 4.605 1.384 0.239
Tail beat Sex 1 3.422 4.281 0.0392* Position 2 3.450 2.159 0.117
Sex*Position 2 4.830 3.022 0.0499*
Type 2 2.955 1.849 0.159
Sex*Type 2 1.520 0.951 0.387
Position*Type 4 1.812 0.567 0.687
Sex*Position*Type 4 3.024 0.946 0.437
Frontal Hover Sex 1 4.074 3.731 0.054 Position 2 2.238 1.025 0.360
Sex*Position 2 1.559 0.714 0.490
Type 2 13.488 6.177 0.0023**
Sex*Type 2 2.035 0.932 0.395
Position*Type 4 2.381 0.545 0.703
Sex*Position*Type 4 0.764 0.175 0.951
S-shape Display Sex 1 0.874 1.068 0.302 Position 2 2.806 1.714 0.182
Sex*Position 2 0.752 0.459 0.632
Type 2 0.254 0.155 0.856
Sex*Type 2 1.473 0.900 0.407
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Position*Type 4 0.650 0.199 0.939
Sex*Position*Type 4 0.861 0.263 0.902
Bite Sex 1 5.761 5.090 0.025 Position 2 2.515 1.111 0.330
Sex*Position 2 5.241 2.315 0.100
Type 2 2.635 1.164 0.313
Sex*Type 2 4.657 2.057 0.129
Position*Type 4 0.936 0.207 0.935
Sex*Position*Type 4 1.047 0.231 0.921
Lateral Display Sex 1 24.260 20.112 <0.0001** Position 2 0.458 0.190 0.827
Sex*Position 2 4.880 2.023 0.134
Type 2 14.100 5.844 0.0032**
Sex*Type 2 9.728 4.032 0.0185*
Position*Type 4 4.162 0.863 0.487
Sex*Position*Type 4 2.215 0.459 0.766
Lateral Hover Sex 1 24.260 20.112 <0.0001** Position 2 0.458 0.190 0.827
Sex*Position 2 4.880 2.023 0.134
Type 2 14.100 5.844 0.0032**
Sex*Type 2 9.728 4.032 0.0185*
Position*Type 4 4.162 0.863 0.487
Sex*Position*Type 4 2.215 0.459 0.766
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Appendix 3. Centroid values from Canonical Centroid Plot (Figure 3). This shows how behaviors are related to each other and how the frequency is influenced by mirror type and sex of the fish. Vales that near each other show close correlations. Signs denote the direction of correlation.
Behavior Type Canonical 1 Canonical 2 Grand 0.153 -0.006 TimeSpent -0.681 -0.221 Explore 0.402 -0.403 Charge -1.654 -3.761 Frontal Display 2.440 -0.894 Jump -0.371 -0.478 Swim -1.144 1.528 Tail beat 0.462 -2.749 Frontal Hover -2.164 1.365 sShape 0.340 0.104 Bite 1.461 -0.088 Lateral Display 1.128 0.912 Lateral Hover 1.016 1.445 Female -0.001 -0.038 Male 0.483 0.064 Concave 0.418 0.442 Convex 0.265 -0.252 Flat 0.039 -0.152 F,conc -0.185 0.404 F,conv 0.179 -0.447 F,flat 0.002 -0.072 M,conc 1.022 0.480 M,conv 0.352 -0.057 M,flat 0.076 -0.233
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Office of Research Compliance 309A University Hall Bowling Green, OH 43403-0183 Phone: (419) 372-7716 Fax: (419) 372-6916 E-mail: [email protected]
February 11, 2011 Dr. Moira van Staaden Biological Sciences Bowling Green State University
Re: IACUC Protocol 11-002
Title: Behavior and Sensory Systems of Cichlid Fishes
Dear Dr. van Staaden:
On February 7, 2011 the above referenced protocol received final approval after review of the requested modifications by Designated Member Review. The modifications have been incorporated into the official copy of your protocol (see modifications below).
This approval expires on February 6, 2012, by which time renewal must be requested if you wish to continue work on the protocol. The Office of Research Compliance will send notification reminding you of the need for renewal in advance of that date.
Please have all members of your research team read the approved version of the protocol. Please also remember to keep a copy of the approved protocol in the animal facility room(s) in which your animals are housed and in any associated procedure rooms (contact the UAF staff for assistance in this regard).
Please consult with the staff of the Animal Facility about your requirements to get started on this project. Good luck with your project.
Hillary Harms, Ph.D. IACUC Administrator 61
Incorporated Modifications:
1. The complete protocol application was resubmitted. 2. In item 12, the pH levels were specified for each species of fish.