Name: using the fishsim animation toolchain to investigate fish behavior: a case study on mate-choice copying in sailfin mollies
Uploaded: 2018-11-08T13:00:00.000+00:00
Duration: 10 min 50 s
Description: Watch this Scientific Journal Video about Using the FishSim Animation Toolchain to Investigate Fish Behavior: A Case Study on Mate-Choice Copying In Sailfin Mollies at JoVE.com

This work was supported by the Deutsche Forschungsgemeinschaft DFG (WI 1531/12-1 to KW and SG and KU 689/11-1 to KDK, KM and JMH). We sincerely thank the DAAD RISE Germany program for providing and organizing an undergraduate research internship between SG and DB (Funding-ID: 57346313). We are grateful to Mitacs for funding DB with a RISE-Globalink Research Internship Award (FR21213). We kindly thank Aaron Berard for inviting us to introduce FishSim to the JoVE readership and Alisha DSouza as well as three anonymous reviewers for their valuable comments on a previous version of the manuscript.

The authors have nothing to disclose.

The gravid spot in sailfin molly females was previously described to serve as a means of fertility advertisement towards conspecific males59,60. Whether a gravid spot may also provide information to conspecific females in the context of mate choice had not been tested so far. In the present case study, we investigated the potential role of a gravid spot as a source of public information for observing conspecific females in the context of MCC. Our study shows that the gravid spot seems to not be a sign of model female quality for live focal females when deciding to copy the mate choice of a virtual model female for a virtual male. Focal females copied the choice of a virtual model female for a prior non-preferred virtual male regardless of whether the model female had a gravid spot or not. We found no difference in copying scores nor the number of mate-choice reversals between the two treatments, indicating that the copying effect was also equally strong whether the model female had a gravid spot or not. When no public information was provided in the control (no model female present), focal females were consistent in their mate choice. This supports that the observed change of preference within treatments can be explained by the presence of the virtual model female only, providing sufficient public information for copying the mate choice of others.
Even though the general presence and extent of the gravid spot are considered to be linked to the female reproductive cycle, with the spot being largest prior to parturition and smallest or absent after giving birth60, systematic visual observations of the development of gravid spots in individual females are still missing. Moreover, variation in gravid spot size can be high between individual females with spots also being completely absent in mature, gravid females60. Even though sailfin molly females are most receptive short after parturition59,76, they are able to store sperm for several months57. Therefore, females should always be choosy for the best quality mate. With regards to our case study on MCC and the tested hypotheses, we conclude that a gravid spot may not be a valid indicator of model female quality to observing conspecific females. Information on the reproductive state of a model female that an observing female might possibly gain seems to not be important in the decision to copy her choice or not, at least among sailfin mollies.
Notably, our study demonstrates a highly standardized procedure for visual manipulation of public information provided in MCC experiments by using computer animated fish. In contrast to an earlier study by Benson77, who injected live fish with tattoo ink to manipulate gravid spots, our method provides a completely non-invasive alternative for visual manipulation. We described in detail the procedure on how to create and animate virtual sailfin mollies in FishSim. We further showed how computer animation can be used to adopt the experimental procedure of a classic MCC experiment with virtual fish for the presentation towards live test fish in a binary choice situation.
Following the protocol, we identify several critical steps that need specific attention to ensure the correct handling of our toolchain and the success of the experiment. Since computer animations are created and presented using computers and display devices such as computer monitors, the technical equipment should always be good enough to ensure a smooth processing of the general workflow and, most importantly, the playback of the animation (steps 2, 3, and 5). When using two or more monitors for presentation of stimuli, their technical specifications should be identical. When using our software, the set monitor resolution should always be that of the presentation monitors (see step 1.2.1.). Setting the scene (step 1.2.) as well as the design (steps 1.3. and 1.4.) and animation (step 2) of virtual stimuli should always be done on a monitor later used for stimulus presentation during experiments to ensure the correct dimensions.
In this protocol, we concentrate on the necessary steps to create one set of fish stimuli (steps 1.3. and 1.4.) for the use in one trial of a treatment (step 5). Here, we would like to point out that it is important to create several different fish stimuli and/or animations to account for pseudoreplication15,78,79 which affects the possible interpretation of the data obtained during experiments. With our toolchain, it is easy to create various fish stimuli offering possibilities to use a unique set of stimuli for each experimental trial. Overall the total number of stimuli needed depends on the intended sample size for each treatment (see &#34;Representative results&#34; section for information on our case study).
With our toolchain, we wanted to provide a fast and easy-to-create animation process by using a video game controller (step 2). Thereby, the general swimming behavior of the virtual fish is automatically generated, based on videos of swimming live sailfin mollies80. Swimming behavior (including movement of fins and gonopodium) is, therefore, tuned to the use with virtual stimuli of sailfin mollies in particular and live-bearing fish in general. Apart from live-bearing fish, an additional template for a three-spined stickleback provides additional functions for species-specific movement, such as raising/lowering of dorsal and ventral spines.
Animation functions currently provided by our toolchain might not be sufficient for every behavioral pattern and fish species. This, however, is up to the user and depends on the tested research question. Further, animation with FishSteering (step 2) needs a little practice beforehand to get accustomed to the functions of the gaming controller. Therefore, the animation process is probably the most time-consuming step of the protocol. A controller of a different brand may be used here but the functionality might not be that smooth and the button functions (as given in the user manual) may be different or completely absent. During the animation process, only one feature of a virtual stimulus (e.g., position, fins, gonopodium) can be animated at a time. First, the swimming movement (position) and afterwards additional features (e.g., fins) may be added independently. We recommend saving each step separately. This offers the advantage that the user has the possibility to come back to an earlier version of the animation to change a specific feature, for example keeping the swimming path constant but changing the dorsal fin movement compared to a previous version. Especially when animating more than one fish (step 2.2.), the order in which fish stimuli are animated is very important and needs to be determined beforehand. Here, it might be helpful to refer to the biology of the tested species. In our case study, we simulated the courtship behavior of sailfin mollies in which a male is generally following a female81. Hence, we first created the swimming path of the virtual female and added the path for the virtual male by following the female.
When running the experimental procedure (step 5) the timing is crucial for the success of the experiment. The times/durations we referred to in the protocol (step 5) derived from previous studies with sailfin mollies. They should be regarded as suggestions and are not obligated for the general success of the experimental but should, nevertheless, be tightly followed during the procedure. Acclimatization time may vary between fish species and even individuals and should generally be as long as the focal fish needs to explore the whole test tank and acclimate to its new surroundings. We determined the appropriate pause duration length in training runs of the experimental procedure. The pause should be at least as long as the time needed for catching the fish with the cylinder, as well as walking to and from the test tank and operational computer to release the fish from the cylinder. Here, times possibly vary depending on the specific experimental situation in each lab and the tested fish species. In any case, the experimenter may individually change times/durations either by setting a different time in FishPlayer (see step 3.1. 3.) or by creating animation sequences with a different length (see step 2.1).
The experimenter can improve the measuring of association time for each mate-choice test by implementing an automated tracking system, though it needs to be capable of tracking in real-time. Here, we also want to point out that there is no possibility of having a blind observer and, hence, blind analysis when following the procedure for testing MCC. Since the experimenter cannot know which virtual male stimulus will be preferred by the focal female prior to testing, he or she needs to be aware of the focal fish&#39;s choice to rearrange the order of animation sequences accordingly (see steps 3.2 and 5.10).
The protocol we describe here is specific to our study design on MCC in sailfin mollies. However, the toolchain can also be used in combination with other experimental designs with up to four monitors for presentation. In general, computer animation tools offer a wide variety of solutions to study various questions on fish behavior like mate choice, shoaling decisions or predator-prey detection, using artificial visual stimuli. General technical and conceptual considerations for the use of computer animation in animal behavior research should be carefully evaluated before using it in experiments2,15. Most important for the decision whether computer animation approaches can be implemented in research regards the visual capabilities of the tested fish species and whether it responds naturally towards virtual stimuli presented on monitor screens. Especially, when testing the effect of color aspects, it should be noted that monitor screens only depict colors as RGB values and that this might impede or limit research possibilities, although RGB color output may indeed be adjusted82. For some fish species, a limitation might certainly be that monitors do not emit UV wavelengths or that, on the other hand, certain monitor types are highly polarized which might be a limitation with fish being sensitive to polarized light for example in questions of mate choice83. Therefore, a validation for the effectiveness of presented stimuli as computer animations is necessary before testing any hypotheses2,12,15,84,85.
In the future, new developments in animal tracking and action recognition might make it possible to create interactive virtual stimuli that react in real-time towards live fish and simulate corresponding behavior to massively increase realism for observing fish86. Thanks to the modularity of the underlying ROS, external devices such as cameras may be integrated into the toolchain, provided that the user has adequate programming skills. A first successful attempt showed that FishSim can generally be used to simulate interactive virtual fish stimuli by extension of a 3D real-time tracking system87,88,89. During the science communication event &#34;Molly knows best&#34; (https://virtualfishproject.wixsite.com/em2016-fisch-orakel), we were able to demonstrate that virtual fish can be programmed to follow live focal fish on screen and perform courtship behavior according to a predefined algorithm. Further, such real-time tracking systems could be used to measure association time automatically to enhance experimental procedure. This feature is not yet included in the current version of FishSim but is subject to future development.
In conclusion, the use of computer animation in animal behavior research is a promising approach when conventional methods would require invasive treatment of live animals to manipulate the expression of a visual trait or behavioral pattern. Manipulating computer animations allows for a high degree of control and standardization compared to using live test fish, especially, since it also offers solutions to manipulate behavior which is very limited or even impossible in live fish. Further, in line with the 3Rs-principle and similar guidelines for the use of animals in research and teaching90,91, this technique bears the potential to &#39;reduce&#39; and &#39;replace&#39; live test animals as well as to &#39;refine&#39; experimental procedures in research.

Recently, utilizing modern techniques for the creation of artificial stimuli, such as computer animations and virtual reality, has garnered popularity in research1. These methods provide several advantages compared to classic experimental approaches with live stimulus animals1,2. Computer animation enables non-invasive manipulation of the appearance (size, color) and behavior of virtual stimulus animals used in experiments. For example, the surgical removal of the sword in male green swordtails (Xiphophorus helleri) to test mate preferences in females3 was rendered unnecessary by using computer animation in a later study on this species4. Furthermore, computer animations can create phenotypes that are only rarely encountered in nature5. Morphological features of virtual animals may even be altered beyond the natural range of that species4. Particularly, the possible systematic manipulation of behavior is one major advantage of computer animation, since it is almost impossible with live animals6,7.
Various techniques exist to date for creating computer animations. Simple two-dimensional (2D) animations typically derive from a picture of a stimulus moving in only two dimensions and can be created with common software like MS PowerPoint8 or Adobe After Effects9. Three-dimensional (3D) animations, which require more sophisticated 3D graphics modelling software, enable the stimulus to be moved in three-dimensions, increasing possibilities for realistic and complex physical movement6,7,10,11,12. Even virtual reality designs that simulate a 3D environment where live animals navigate have been used13,14. In a recent review Chouinard-Thuly et al. 2 discuss these techniques one by one and highlight advantages and disadvantages on their implementation in research, which notably depends on the scope of the study and the visual capacities of the test animal (see &#8220;Discussion&#8221;). Additionally, Powell and Rosenthal15 give advice on appropriate experimental design and what questions may be addressed by employing artificial stimuli in animal behavior research.
Since creating computer animation may be difficult and time consuming, the need for software to facilitate and standardize the process of animation design arose. In this study, we introduce the free and open-source FishSim Animation Toolchain16 (short: FishSim; https://bitbucket.org/EZLS/fish_animation_toolchain/), a multidisciplinary approach combining biology and computer science to address these needs. Similar to the earlier published tool anyFish17,18, the development of the toolchain followed the goal to provide researchers with an easy-to-use method for implementing animated 3D stimuli in experiments with fish. Our software consists of a set of tools that can be used to: (1) create 3D virtual fish (FishCreator), (2) animate the swimming paths of the virtual fish with a video game controller (FishSteering), and (3) organize and present prerecorded animations on monitors to live focal fish (FishPlayer). Our toolchain provides various features that are especially useful for testing in a binary choice situation but also applicable to other experimental designs. Moreover, the possible animation of two or more virtual fish enables the simulation of shoaling or courtship. Animations are not bound to a specific stimulus but may be replayed with other stimuli making it possible to change the appearance of a stimulus but keep its behavior constant. The open-source nature of the toolchain, as well as the fact that it is based on the robot operation system ROS (www.ros.org), provide high modularity of the system and offer nearly endless possibilities to include external feedback devices (as the controller or a tracking system) and to adapt the toolchain to one&#8217;s own needs in research. In addition to the sailfin molly, four other species are currently usable: the Atlantic molly Poecilia mexicana, the guppy Poecilia reticulata, the three-spined stickleback Gasterosteus aculeatus and a cichlid Haplochromis spp. New species can be created in a 3D graphics modelling tool (e.g., Blender, www.blender.org). To exemplify the workflow with FishSim and to provide a protocol on how to conduct a mate-choice copying experiment with computer animation, we performed a case study with sailfin mollies.
Mate choice is one of the most important decisions animals make in their life history. Animals have evolved different strategies for finding the best mating partners. They may rely on personal information when evaluating potential mating partners independently, possibly according to predetermined genetic preferences for a certain phenotypic trait19, 20. However, they may also observe the mate choice of conspecifics and thereby utilize public information21. If the observer then decides to choose the same mate (or the same phenotype) as the observed conspecific &#8212; the &#8220;model&#8221; &#8212; chosen previously, this is termed mate-choice copying (hereafter abbreviated as MCC)22,23. Mate-choice copying is a form of social learning and, hence, a non-independent mate-choice strategy24, which has been observed in both vertebrates25,26,27,28,29 and invertebrates30,31,32. So far, MCC was predominantly studied in fish and is found both under laboratory conditions33,34,35,36,37,38 and in the wild39,40,41,42. Mate-choice copying is especially valuable for an individual if two or more potential mating partners are apparently similar in quality, and a &#8220;good&#8221; mate choice &#8212; in terms of maximizing fitness &#8212; is difficult to make43. The quality of a model female herself can affect whether focal females copy her choice or not44,45,46,47. Respectively, &#8220;good&#8221; or &#8220;bad&#8221; model female quality has been attributed to her being more or less experienced in mate choice, for example with regard to size and age44,45,46, or by her being a conspecific or a heterospecific47. In sailfin mollies that copy the mate choice of conspecifics39,48,49,50,51, it was found that focal females even copy the rejection of a male52. Since MCC is considered to play an important role in the evolution of phenotypic traits as well as speciation and hybridization21,23,53,54, the consequences of copying a &#8220;false&#8221; choice may be tremendous in reducing the fitness of the copier55. If an individual decides to copy the choice of another individual, it is important to evaluate if the observed model is a reliable source of information, i.e., that the model itself is making a &#8220;good&#8221; choice due to him or her being well experienced in mate choice. Here the question arises: what visual features may characterize a reliable model to copy from in sailfin molly females?
A distinct visual feature in female sailfin mollies and other Poeciliids is the gravid spot (also known as &#8216;anal spot&#8217;, &#8216;brood patch&#8217; or &#8216;pregnancy spot&#8217;). This darkly pigmented area in their anal region derives from melanization of the tissue lining the ovarian sac56. The size and presence of the gravid spot are variable across conspecific females and may further individually change during the progression of ovarian cycles56,57. Gravid spots may serve to attract males and facilitate gonopodial orientation for internal insemination58 or as a means of advertising fertility59,60. Considering the link between the gravid spot and a female&#8217;s reproductive status, we predicted that the gravid spot serves as a sign of model female quality by providing information on her current reproductive state to observing focal females. We investigated two alternate hypotheses. First, if the gravid spot is a general sign for maturity, as predicted by Farr and Travis59, it denotes a presumably reliable and experienced model compared to an immature model (without the spot). Here, focal females are more likely to copy the choice of a model with a spot but not that of a model without a spot. Second, if the gravid spot marks non-receptivity due to already developing broods, as predicted by Sumner et al.60, the model is presumably less reliable since non-receptive females would be considered less choosy. In this case, focal females will not copy their choice but that of models without spot. So far, the role of the gravid spot for MCC in sailfin molly females has never been tested, nor experimentally manipulated.
We used FishSim to perform an MCC experiment by presenting virtual stimulus males and virtual model females on computer monitors instead of using live stimulus and model fish as used in the classic experimental procedure49,50,51,61. The general usability of our software has previously been validated for testing hypotheses about mate choice in sailfin mollies12. Here, we tested whether the absence or presence of a gravid spot in virtual model females affects the mate choice of observing live focal females. We first let focal females acclimate to the test tank (Figure 1.1) and let them choose between two different virtual stimulus males in a first mate-choice test (Figure 1.2). Afterwards, during the observation period, the prior non-preferred virtual male was presented together with a virtual model female (Figure 1.3). In a subsequent second mate-choice test, focal females chose again between the same males (Figure 1.4). We analyzed whether focal females had copied the mate choice of the observed model female by comparing her mate-choice decision in the first and second mate-choice test. We performed two different experimental treatments in which we visually manipulated the quality of the virtual model female. During the observation period, we either presented the prior non-preferred virtual male (1) together with a virtual model female with a gravid spot (&#8220;spot&#8221; treatment); or (2) together with a virtual model female without a gravid spot (&#8220;no spot&#8221; treatment). Additionally, in a control without any model female, we tested whether focal females chose consistently when no public information was provided.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/58435/58435fig1.jpg" /> 
Figure 1. General overview of the most important experimental steps for a MCC experiment using virtual fish stimuli. (1) Acclimatization period. (2) First mate-choice test: live focal female chooses between virtual stimulus males. (3) Observation period: focal female watches the prior non-preferred male together with a virtual model female with gravid spot. (4) Second mate-choice test: the focal female again chooses between virtual stimulus males. In this example, she copies the choice of the model. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58435/58435fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

<table><tbody><tr><td>&lt;strong&gt;Hardware&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>2x 19&quot; Belinea LCD displays</td><td>Belinea GmbH, Germany</td><td>Model 1970 S1-P</td><td>1280 x 1024 pixels resolution</td></tr><tr><td>1x 24&quot; Fujitsu LCD display</td><td>Fujitsu Technology Solutions GmbH, Germany</td><td>Model B24-8 TS Pro</td><td>1920 x 1080 pixels resolution</td></tr><tr><td>Computer</td><td></td><td></td><td>Intel Core 2 Quad CPU Q9400 @ 2.66GHz x 4, GeForce GTX 750 Ti/PCIe/SSE2, 7.8 GiB memory, 64-bit, 1TB; keyboard and mouse</td></tr><tr><td>SONY Playstation 3 Wireless Controller</td><td>Sony Computer Entertainment Inc., Japan</td><td>Model No. CECHZC2E</td><td>USB-cable for connection to computer</td></tr><tr><td>Glass aquarium</td><td></td><td></td><td>100 cm x 40 cm x 40 cm (L x H x W)</td></tr><tr><td>Plexiglass cylinder</td><td>custom-made</td><td></td><td>49.5 cm height, 0.5 cm thickness, 12 cm diameter; eight small holes (approx. 5 mm diameter) drillt close to the end of the cylinder lower the amount of water disturbance while releasing the fish</td></tr><tr><td>Gravel</td><td></td><td></td><td></td></tr><tr><td>2x OSRAM L58W/965</td><td>OSRAM GmbH, Germany</td><td></td><td>Illumination of the experimental setup</td></tr><tr><td>2x Stopwatches</td><td></td><td></td><td></td></tr><tr><td>&lt;strong&gt;Name&lt;/strong&gt;</td><td>&lt;strong&gt;Company&lt;/strong&gt;</td><td>&lt;strong&gt;Catalog Number&lt;/strong&gt;</td><td>&lt;strong&gt;Comments&lt;/strong&gt;</td></tr><tr><td>&lt;strong&gt;Software&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>ubuntu 16.04 LTS</td><td></td><td></td><td>Computer operating system; Download from: https://www.ubuntu.com/</td></tr><tr><td>&lt;em&gt;FishSim&lt;/em&gt; Animation Toolchain v.0.9</td><td></td><td></td><td>Software download and user manual (PDF) from: https://bitbucket.org/EZLS/fish_animation_toolchain</td></tr><tr><td>GIMP Gnu Image Manipulation Program (version 2.8.22)</td><td></td><td></td><td>Download from: https://www.gimp.org/</td></tr></tbody></table>

using the fishsim animation toolchain to investigate fish behavior: a case study on mate-choice copying in sailfin mollies

Over the last decade, employing computer animations for animal behavior research has increased due to its ability to non-invasively manipulate the appearance and behavior of visual stimuli, compared to manipulating live animals. Here, we present the FishSim Animation Toolchain, a software framework developed to provide researchers with an easy-to-use method for implementing 3D computer animations in behavioral experiments with fish. The toolchain offers templates to create virtual 3D stimuli of five different fish species. Stimuli are customizable in both appearance and size, based on photographs taken of live fish. Multiple stimuli can be animated by recording swimming paths in a virtual environment using a video game controller. To increase standardization of the simulated behavior, the prerecorded swimming path may be replayed with different stimuli. Multiple animations can later be organized into playlists and presented on monitors during experiments with live fish.
In a case study with sailfin mollies (Poecilia latipinna), we provide a protocol on how to conduct a mate-choice copying experiment with FishSim. We utilized this method to create and animate virtual males and virtual model females, and then presented these to live focal females in a binary choice experiment. Our results demonstrate that computer animation may be used to simulate virtual fish in a mate-choice copying experiment to investigate the role of female gravid spots as an indication of quality for a model female in mate-choice copying.
Applying this method is not limited to mate-choice copying experiments but can be used in various experimental designs. Still, its usability depends on the visual capabilities of the study species and first needs validation. Overall, computer animations offer a high degree of control and standardization in experiments and bear the potential to &#39;reduce&#39; and &#39;replace&#39; live stimulus animals as well as to &#39;refine&#39; experimental procedures.

Following the protocol, we used FishSim to create computer animations of virtual sailfin molly males and females. We further used the toolchain to present animations to live focal females in a binary choice situation to perform an MCC experiment according to the experimental procedure described in Figure 1 and step 5 of the protocol.
In order to determine whether focal females copied the choice of the virtual model female, we measured a focal female&#39;s association time for each male within the first and second mate-choice test during the experiments. Several parameters are typically analyzed using association time obtained in the first and the second mate-choice test for each treatment and the control for choice consistency. How the data are being analyzed is not bound to a specific statistical test but can be done in various ways (e.g., parametric/nonparametric tests, repeated measures ANOVA, statistical models) and may depend on the final data structure. For our data analysis, we used R 3.2.262. We uploaded the raw data we obtained in our experiment as well as the R-code we used for our analysis to Figshare (doi: 10.6084/m9.figshare.6792347).
In the current study, we created 15 different virtual model females with a gravid spot for Treatment 1 and identical 15 model females without a spot for Treatment 2. All model females had a virtual standard length (SL) of 50 mm. The relative gravid spot area was 4.7% of the total body surface (excluding fins; as measured with ImageJ v1.51j8) for all females in Treatment 1. Further, we created 30 different virtual stimulus males presented during mate-choice tests, allowing for 15 unique male stimuli pairings. Stimulus males had a virtual SL between 41-45 mm. We performed 15 trials for each treatment and the control for choice consistency. We tested a total number of 55 live focal females descendant from wild sailfin mollies caught on Mustang Island near Corpus Christi, TX, USA in 2014. All focal females were mature adults and were only tested once. Two females had to be excluded due to technical problems during testing. One female was excluded due to stress since she did not acclimate to the test situation and was too afraid to enter either choice zone. The control for side bias in focal fish (protocol step 6.3) required that we further exclude seven females from the final analysis due to their side bias in the first mate-choice test. Altogether, we analyzed a total of n = 15 focal females for each treatment and the control. Focal females had a mean SL of 32 &#177; 5 mm in Treatment 1, 33 &#177; 5 mm in Treatment 2 and 33 &#177; 3 mm in the control for choice consistency. We compared the standard length (SL) of focal females across treatments and the control using a Kruskal Wallis rank sum test for independent data revealing that SL did not differ between treatments and the control (Kruskal Wallis rank sum test: n = 45, df = 2, &#967;2 = 0.329, p = 0.848).
The most important parameter measured in an MCC experiment is the focal female&#39;s association time for each male (protocol step 6.1). Association time is an indirect measure of female mate preference in fish63,64,65,66 and a well-established measure to determine mate choice in sailfin mollies when no direct contact is provided12,48,61,67,68. For each treatment and the control, we first used association time to analyze whether the choosing motivation differed between mate-choice tests. Choosing motivation is defined as the total time a focal female spent in both choice zones within a mate-choice test. However, a change in choosing motivation does not necessarily reflect a change in preference for either male. If choosing motivation is significantly different between the two mate-choice tests it is obligatory to use preference scores instead of absolute association time, for further analysis to ensure comparability within and between treatments (see protocol step 6.2). In our study, choosing motivation of focal females before and after observation of a virtual model female sexually interacting with a male did not differ in Treatment 1 (Wilcoxon signed rank test: n = 15, V = 44, p = 0.379) and in the control for choice consistency (Wilcoxon signed rank test: n = 15, V = 42, p = 0.33). However, choosing motivation was significantly higher after observation of a virtual model female without gravid spot sexually interacting with a male in Treatment 2 (Wilcoxon signed rank test: n = 15, V = 22, p = 0.03).
The most important determinant of whether MCC occurred is a significant increase in time spent/preference scores for the prior non-preferred male from the first to the second mate-choice test22. Transferred to a natural situation, an increase in time spent with the prior non-preferred male, consequently increases the probability that a female will mate with that male. Therefore, the main analysis compared either the absolute times or the preference scores for the prior non-preferred male between the two mate-choice tests. This analysis has to be done for each treatment and the control separately. Since in our study, choosing motivation differed in Treatment 2, we used preference scores for the initially non-preferred stimulus male, instead of absolute association time, to determine whether these scores changed between the first and second mate-choice test when public information was provided, compared to the control treatment in which public information was absent.
For this, we fit a linear mixed effect (LME) model with the lme function from the &#39;nlme&#39; package69 with preference score for the prior non-preferred male (pref_NP) as the dependent variable. We included mate-choice test (Mtest: M1, M2) and treatment (treatment: spot, no spot, control) as fixed factors as well as focal female&#39;s standard length (SL) as a covariate. To account for the repeated measures design, focal female identity (ID) was included as a random factor. We were especially interested in whether the effect of mate-choice test was different among treatments; therefore, we included an interaction between mate-choice test and the treatment in our model. We conducted two orthogonal comparisons for &#34;treatment&#34; using the function contrasts70. We set the contrasts of the model (1) to compare the control against the mean of all treatments in which any virtual model female was presented during observation [control &#62;&#62;&#160;(spot, no spot)], and (2) to compare the treatment showing a virtual model female with spot against that without a spot (spot &#62;&#62;&#160;no spot). A plot of the standardized residuals of a factor against the fitted values revealed heteroscedasticity of the residual variances for &#34;Mtest&#34;. Therefore, we included a weights function using the varIdent class of the lme function to allow for different variances for each level of &#34;Mtest&#34;71,72. We used the R package &#39;phia&#39;73 for a post hoc analysis with Holm-Bonferroni correction of significant interaction terms. We inspected model assumptions (Q/Q-plots, residuals, residuals against fitted values) for all models visually74. We further compared the distribution of the residuals against a normal distribution using Shapiro-Wilk normality tests. The given p-values were considered significant if p &#8804; 0.05.
The results of this analysis are given in Figure 7A and Tables 1 and 2. We found a significant interaction between M2 and the contrast &#34;[control &#62;&#62;&#160;(spot, no spot)]&#34; for preference scores of the prior non-preferred male (LME: df = 42, t = -2.74, p = 0.009). However, preference scores were not affected by focal female SL. Further post hoc analysis of the interaction term revealed a significant difference of preference scores of the prior non-preferred male in M2 in Treatment 1 (spot: df = 1, &#967;2 = 30.986, p &#60; 0.001) and Treatment 2 (no spot: df = 1, &#967;2 = 19.957, p &#60; 0.001) but not for the control (&#967;2-test: df = 1, &#967;2 = 2.747, p = 0.097). Here, our results demonstrate that, as predicted for MCC, preference scores for the prior non-preferred virtual male significantly increased from M1 to M2 after focal females had been presented with the simulated mate choice of a virtual model female. We found this effect in both treatments but not in the control for choice consistency. Instead, in the control where no model female was present during the observation period, focal females were consistent in their mate choice for a male.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Factors</td>
			<td>Lower</td>
			<td>Estimate</td>
			<td>Upper</td>
			<td>SE</td>
			<td>df</td>
			<td>t-value</td>
			<td>p-value</td>
		</tr>
		<tr>
			<td>(Intercept)</td>
			<td>0.046</td>
			<td>0.339</td>
			<td>0.632</td>
			<td>0.145</td>
			<td>42</td>
			<td>2,336</td>
			<td>0.024</td>
		</tr>
		<tr>
			<td>M2</td>
			<td>0.207</td>
			<td>0.296</td>
			<td>0.384</td>
			<td>0.044</td>
			<td>42</td>
			<td>6.750</td>
			<td>&#60; 0.001</td>
		</tr>
		<tr>
			<td>Control &#8594; (spot, no spot)</td>
			<td>-0.041</td>
			<td>-0.012</td>
			<td>0.017</td>
			<td>0.014</td>
			<td>41</td>
			<td>-0.852</td>
			<td>0.4</td>
		</tr>
		<tr>
			<td>Spot &#8594; no spot</td>
			<td>-0.093</td>
			<td>-0.043</td>
			<td>0.008</td>
			<td>0.025</td>
			<td>41</td>
			<td>-1,715</td>
			<td>0.094</td>
		</tr>
		<tr>
			<td>SL</td>
			<td>-0.012</td>
			<td>-0.003</td>
			<td>0.006</td>
			<td>0.004</td>
			<td>41</td>
			<td>-0.747</td>
			<td>0.459</td>
		</tr>
		<tr>
			<td>M2 x [control &#8594; (spot, no spot)]</td>
			<td>-0.148</td>
			<td>-0.085</td>
			<td>-0.023</td>
			<td>0.031</td>
			<td>42</td>
			<td>-2,743</td>
			<td>0.009</td>
		</tr>
		<tr>
			<td>M2 x (spot &#8594; no spot)</td>
			<td>-0.067</td>
			<td>0.042</td>
			<td>0.15</td>
			<td>0.054</td>
			<td>42</td>
			<td>0.777</td>
			<td>0.441</td>
		</tr>
	</tbody>
</table>
Table 1. LME estimates for effects on preference scores for the prior non-preferred virtual male. Preference score for the prior non-preferred virtual male stimulus was the dependent variable throughout. Given are estimates &#177; standard error and lower/upper confidence intervals, degrees of freedom, t-values and p-values for each fixed factor. Intercept estimates represent the grand mean of all treatments. Orthogonal comparisons of treatments are given. If treatments are combined in parentheses, mean values of these treatments are used in the comparisons. The intercept reference category for factor &#34;M2&#34; is &#34;M1&#34;. Significant p-values (p &#60; 0.05) are printed in bold. M1 = first mate-choice test, M2 = second mate-choice test, SL = standard length of focal females. 90 observations with n = 15 focal females per treatment.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Random factor</td>
			<td>Variance</td>
			<td>SD</td>
		</tr>
		<tr>
			<td>ID ((Intercept))</td>
			<td>1.464x10-10</td>
			<td>1.21x10-5</td>
		</tr>
		<tr>
			<td>Residual</td>
			<td>1.859x10-2</td>
			<td>0.1364</td>
		</tr>
	</tbody>
</table>
Table 2. LME variance components for focal female ID. Variance and standard deviation for the random effect &#34;focal female ID&#34; and the residuals are given.
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/58435/58435fig7.jpg" /> 
Figure 7: Results of the virtual MCC experiment manipulating model female quality by the visual absence or presence of a gravid spot. (A) Preference scores for the (prior) non-preferred virtual stimulus male in M1 and M2 for both treatments and the control. (B) Change of preference from M1 to M2 (copying score) for the prior non-preferred virtual male in the treatments and in the control. The dotted line depicts no change in preference, positive values show an increase in preference and negative values show a decrease in preference. Grey dots in A and B depict raw data of each focal female. (C) Number of mate-choice reversals in M2 for each treatment and the control. M1 = first mate-choice test, M2 = second mate-choice test, ns = not significant, * = p &#60; 0.05, ** = p &#60; 0.01, *** = p &#60; 0.001. N = 15 for both treatments and the control. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58435/58435fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
To obtain additional information about whether a copying effect might be more or less strong depending on the respective treatment, a comparison between copying scores and the number of mate-choice reversals between the different treatments and the control was conducted. Therefore, we further analyzed whether copying scores for the prior non-preferred male were different across treatments. The copying score for a male describes the change in female preference for a male from the first to the second mate-choice test. The copying score is defined by the preference score of a male in the second mate-choice test minus the score of that same male in the first mate-choice test. Copying scores range between -1 and +1 and can either be positive or negative values in which negative values describe a decrease in preference and positive values an increase in preference for that male. Here, we fit an LME with copying score (copy_NP) as the dependent variable, treatment as a fixed factor, focal female SL as a covariate and focal female&#39;s spot area as a random factor. Here, we conducted the same two orthogonal comparisons for &#34;treatment&#34; as described above.
As we show in Figure 7B and Tables 3 and 4, we found a significantly higher copying score for the prior non-preferred male in treatments with a virtual model female compared to the control (LME: df = 20, t = -2.833, p = 0.01) but no significant difference between treatments (LME: df = 20, t = 0.618, p = 0.544). Copying scores were not affected by focal female SL.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Fixed factors</td>
			<td>Lower</td>
			<td>Estimate</td>
			<td>Upper</td>
			<td>SE</td>
			<td>df</td>
			<td>t-value</td>
			<td>p-value</td>
		</tr>
		<tr>
			<td>(Intercept)</td>
			<td>-0.889</td>
			<td>-0.081</td>
			<td>0.727</td>
			<td>0.389</td>
			<td>21</td>
			<td>-0.208</td>
			<td>0.837</td>
		</tr>
		<tr>
			<td>Control &#8594; (spot, no spot)</td>
			<td>-0.153</td>
			<td>-0.088</td>
			<td>-0.023</td>
			<td>0.031</td>
			<td>20</td>
			<td>-2.833</td>
			<td>0.01</td>
		</tr>
		<tr>
			<td>Spot &#8594; no spot</td>
			<td>-0.079</td>
			<td>0.033</td>
			<td>0.146</td>
			<td>0.054</td>
			<td>20</td>
			<td>0.618</td>
			<td>0.544</td>
		</tr>
		<tr>
			<td>SL</td>
			<td>-0.013</td>
			<td>0.011</td>
			<td>0.035</td>
			<td>0.011</td>
			<td>20</td>
			<td>0.991</td>
			<td>0.333</td>
		</tr>
	</tbody>
</table>
Table 3. LME estimates for effects on copying scores for the prior non-preferred virtual male. Copying score for the prior non-preferred virtual male stimulus was the dependent variable throughout. Given are estimates &#177; standard error and lower/upper confidence intervals, degrees of freedom, t-values and p-values for each fixed factor. Intercept estimates represent the grand mean of all treatments. Orthogonal comparisons of treatments are given. If treatments are combined in parentheses, mean values of these treatments are used in the comparisons. Significant p-values (p &#8804; 0.05) are printed in bold. SL = standard length of focal females. 45 observations with n = 15 focal females per treatment.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Random factor</td>
			<td>Variance</td>
			<td>SD</td>
		</tr>
		<tr>
			<td>spot_area ((Intercept))</td>
			<td>0.028</td>
			<td>0.166</td>
		</tr>
		<tr>
			<td>Residual</td>
			<td>0.075</td>
			<td>0.275</td>
		</tr>
	</tbody>
</table>
Table 4. LME variance components for focal female spot area. Variance and standard deviation for the random effect &#34;spot_area&#34; and the residuals are given.
Additionally, we tested whether the number of focal females that reversed their initial mate preference in M2 differed across treatments. Mate-choice reversal is defined as whether there is a change in the preference for a male (from less than 50% to more than 50% of the time in both choice zones) from the first to the second mate-choice test. Mate-choice reversal is counted as a &#34;Yes&#34; (preference for a male has changed) or a &#34;No&#34; (preference for a male did not change). Here, we performed a post hoc pairwise G-test using the R package &#39;RVAideMemoire&#39;75 with correction for multiple testing. As we show in Figure 7C, eleven out of 15 focal females reversed their mate choice in Treatment 1 and ten females reversed their mate choice in Treatment 2. On the other hand, only two reversals were observed in the control. Thereby, the number of focal females that reversed their initial mate choice in favor of the prior non-preferred male in M2 was significantly larger in both treatments compared to the control (post hoc pairwise G-test: Spot vs. control, p = 0.002; no spot vs. control, p = 0.003) but not significantly different between Treatments 1 and 2 (Post-hoc pairwise G-test: spot vs. no spot, p = 0.69).

Watch this Scientific Journal Video about Using the FishSim Animation Toolchain to Investigate Fish Behavior: A Case Study on Mate-Choice Copying In Sailfin Mollies at JoVE.com

Using the FishSim Animation Toolchain to Investigate Fish Behavior: A Case Study on Mate-Choice Copying In Sailfin Mollies

Using the novel FishSim Animation Toolchain, we present a protocol for non-invasive visual manipulation of public information in the context of mate-choice copying in sailfin mollies. FishSim Animation Toolchain provides an easy-to-use framework for the design, animation and presentation of computer-animated fish stimuli for behavioral experiments with live test fish.

Using the FishSim Animation Toolchain to Investigate Fish Behavior: A Case Study on Mate-Choice Copying In Sailfin Mollies

Over the last decade, employing computer animations for animal behavior research has increased due to its ability to non-invasively manipulate the ...

using-fishsim-animation-toolchain-to-investigate-fish-behavior-case

Nanyang Technological University

Research

JoVE Journal

Behavior

10.7K Views.  University of Siegen. Deze methode kan helpen om belangrijke vragen te beantwoorden in het bestuderen van visgedrag vooral op het gebied van partner keuze en hier om de fascinerende strategie van mate-choice kopiëren te bestuderen. Het belangrijkste voordeel van onze techniek is dat we totale controle hebben over het uiterlijk en het gedrag van de visstimuli die we gebruiken om levende vissen te presenteren tijdens experimenten. Visuele demonstratie van deze methode is van cruciaal belang omdat de verschillende s...

Video: Using the FishSim Animation Toolchain to Investigate Fish Behavior: A Case Study on Mate-Choice Copying In Sailfin Mollies

Automated Interactive Video Playback for Studies of Animal Communication

Video playback is a widely-used technique for the controlled manipulation and presentation of visual signals in animal communication. In particular, parameter-based computer animation offers the opportunity to independently manipulate any number of behavioral, morphological, or spectral characteristics in the context of realistic, moving images of animals on screen. A major limitation of conventional playback, however, is that the visual stimulus lacks the ability to interact with the live animal. Borrowing from video-game technology, we have created an automated, interactive system for video playback that controls animations in response to real-time signals from a video tracking system. We demonstrated this method by conducting mate-choice trials on female swordtail fish, Xiphophorus birchmanni. Females were given a simultaneous choice between a courting male conspecific and a courting male heterospecific (X. malinche) on opposite sides of an aquarium. The virtual male stimulus was programmed to track the horizontal position of the female, as courting males do in the wild. Mate-choice trials on wild-caught X. birchmanni females were used to validate the prototype's ability to effectively generate a realistic visual stimulus.

Video playback is a widely used technique in animal behavior. We created and evaluated a program that applies rules-based, interactive playback of 3-D computer animations in response to real-time, automated data on subject behavior.

Video playback is a widely-used technique for the controlled manipulation and presentation of visual signals in animal communication. In particular, ...

Neuroscience

Basic Methods for the Study of Reproductive Ecology of Fish in Aquaria

Captive-rearing observations are valuable for revealing aspects of fish behavior and ecology when continuous field investigations are impossible. Here, a series of basic techniques are described to enable observations of the reproductive behavior of a wild-caught gobiid fish, as a model, kept in an aquarium. The method focuses on three steps: collection, transport, and observations of reproductive ecology of a substrate spawner. Essential aspects of live fish collection and transport are (1) preventing injury to the fish, and (2) careful acclimation to the aquarium. Preventing harm through injuries such as scratches or a sudden change of water pressure is imperative when collecting live fish, as any physical damage is likely to negatively affect the survival and later behavior of the fish. Careful acclimation to aquaria decreases the incidence death and mitigates the shock of transport. Observations during captive rearing include (1) the identification of individual fish and (2) monitoring spawned eggs without negative effects to the fish or eggs, thereby enabling detailed investigation of the study species' reproductive ecology. The subcutaneous injection of a visible implant elastomer (VIE) tag is a precise method for the subsequent identification of individual fish, and it can be used with a wide size range of fish, with minimal influence on their survival and behavior. If the study species is a substrate spawner that deposits adhesive eggs, an artificial nest site constructed from polyvinyl chloride (PVC) pipe with the addition of a removable waterproof sheet will facilitate counting and monitoring the eggs, lessening the investigator's influence on the nest-holding and egg-guarding behavior of the fish. Although this basic method entails techniques that are seldom mentioned in detail in research articles, they are fundamental for undertaking experiments that require the captive rearing of a wild fish.

A series of basic methods to enable the study of the reproductive ecology of fish kept in aquaria are described. These are useful protocols for collecting fish using SCUBA, transporting live fish, and observing the reproductive behavior of wild-caught fish kept in aquaria.

Captive-rearing observations are valuable for revealing aspects of fish behavior and ecology when continuous field investigations are impossible. Here, a ...

Individual Culturing of Tigriopus Copepods and Quantitative Analysis of Their Mate-guarding Behavior

Copepods of the genus Tigriopus, which are common zooplankton in rocky tide pools, show precopulatory mate-guarding behavior where a male clasps a potential mate to form a pair. While this phenomenon has attracted interest of researchers, methods for its analysis have not been well described. Here we describe procedures for: 1) individual culturing and staging of Tigriopus juveniles and adults, and 2) video-based analysis of their mate-guarding behavior. The culturing method enables experimental control of paring experience of animals as well as the ability to track their development before behavioral tests. The analysis method allows quantitative evaluation of several aspects of the mate-guarding behavior, including capturing attempts by males and swimming trajectory of mate-guarding pairs. Although these methods were originally established for ethological studies on Tigriopus, with proper modifications they can also be applied to studies of other zooplankton in different research fields, such as physiology, toxicology, and ecological genetics.

Individual Culturing of Tigriopus Copepods and Quantitative Analysis of Their Mate-guarding Behavior

Mate-guarding behavior plays an important role in reproduction of intertidal copepods of the genus Tigriopus. However, methods for studying this behavior have not been well described. Here we describe methods for: 1) individual culture of virgin Tigriopus animals, and 2) quantitative analysis of their mate-guarding behavior.

Copepods of the genus Tigriopus, which are common zooplankton in rocky tide pools, show precopulatory mate-guarding behavior where a male clasps a ...

Environment

Behavioral Tracking and Neuromast Imaging of Mexican Cavefish

Cave-dwelling animals have evolved a series of morphological and behavioral traits to adapt to their perpetually dark and food-sparse environments. Among these traits, foraging behavior is one of the useful windows into functional advantages of behavioral trait evolution. Presented herein are updated methods for analyzing vibration attraction behavior (VAB: an adaptive foraging behavior) and imaging of associated mechanosensors of cave-adapted tetra, Astyanax mexicanus. In addition, methods are presented for high-throughput tracking of a series of additional cavefish behaviors including hyperactivity and sleep-loss. Cavefish also show asociality, repetitive behavior and higher anxiety. Therefore, cavefish serve as an animal model for evolved behaviors. These methods use free-software and custom-made scripts that can be applied to other types of behavior. These methods provide practical and cost-effective alternatives to commercially available tracking software.

Here, we present methods for high-throughput study of a series of the Mexican cavefish behaviors and vital staining of a mechanosensory system. These methods use free-software and custom-made scripts, providing a practical and cost-effective method for the studies of behaviors.

Cave-dwelling animals have evolved a series of morphological and behavioral traits to adapt to their perpetually dark and food-sparse environments. Among ...

Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions

Collective animal behavior arises from individual motivations and social interactions that are critical for individual fitness. Fish have long inspired investigations into collective motion, specifically, their ability to integrate environmental and social information across ecological contexts. This demonstration illustrates techniques used for quantifying behavioral responses of fish, in this case, Golden Shiner (Notemigonus crysoleucas), to visual stimuli using computer visualization and digital image analysis. Recent advancements in computer visualization allow for empirical testing in the lab where visual features can be controlled and finely manipulated to isolate the mechanisms of social interactions. The purpose of this method is to isolate visual features that can influence the directional decisions of the individual, whether solitary or with groups. This protocol provides specifics on the physical Y-maze domain, recording equipment, settings and calibrations of the projector and animation, experimental steps and data analyses. These techniques demonstrate that computer animation can elicit biologically-meaningful responses. Moreover, the techniques are easily adaptable to test alternative hypotheses, domains, and species for a broad range of experimental applications. The use of virtual stimuli allows for the reduction and replacement of the number of live animals required, and consequently reduces laboratory overhead.
This demonstration tests the hypothesis that small relative differences in the movement speeds (2 body lengths per second) of virtual conspecifics will improve the speed and accuracy with which shiners follow the directional cues provided by the virtual silhouettes. Results show that shiners directional decisions are significantly affected by increases in the speed of the visual cues, even in the presence of background noise (67% image coherency). In the absence of any motion cues, subjects chose their directions at random. The relationship between decision speed and cue speed was variable and increases in cue speed had a modestly disproportionate influence on directional accuracy.

Here, we present a protocol to demonstrate a behavioral assay that quantifies how alternative visual features, such as motion cues, influence directional decisions in fish. Representative data are presented on the speed and accuracy where Golden Shiner (Notemigonus crysoleucas) follow virtual fish movements.

Collective animal behavior arises from individual motivations and social interactions that are critical for individual fitness. Fish have long inspired ...

Swimming Performance Assessment in Fishes

Swimming performance tests of fish have been integral to studies of muscle energetics, swimming mechanics, gas exchange, cardiac physiology, disease, pollution, hypoxia and temperature. This paper describes a flexible protocol to assess fish swimming performance using equipment in which water velocity can be controlled. The protocol involves one to several stepped increases in flow speed that are intended to cause fish to fatigue. Step speeds and their duration can be set to capture swimming abilities of different physiological and ecological relevance. Most frequently step size is set to determine critical swimming velocity (Ucrit), which is intended to capture maximum sustained swimming ability. Traditionally this test has consisted of approximately ten steps each of 20 min duration. However, steps of shorter duration (e.g. 1 min) are increasingly being utilized to capture acceleration ability or burst swimming performance. Regardless of step size, swimming tests can be repeated over time to gauge individual variation and recovery ability. Endpoints related to swimming such as measures of metabolic rate, fin use, ventilation rate, and of behavior, such as the distance between schooling fish, are often included before, during and after swimming tests. Given the diversity of fish species, the number of unexplored research questions, and the importance of many species to global ecology and economic health, studies of fish swimming performance will remain popular and invaluable for the foreseeable future.

The lives of the majority of fish are predicated on swimming. This protocol describes techniques for capturing a range of swimming modes available to individual and schooling fish, and includes metrics associated with swimming physiology and behaviour.

Swimming performance tests of fish have been integral to studies of muscle energetics, swimming mechanics, gas exchange, cardiac physiology, disease, ...

Biology

Assays to Detect UV-reflecting Structures and Determine their Importance in Mate Preference using the Sailfin Molly Poecilia latipinna

Many organisms use cues and signals beyond human sensitivity during social interactions. It is important to take into account how organisms perceive their worlds when trying to understand their behavior and ecology. Sensitivity to the ultraviolet spectrum (UV; 300 - 400 nm) is found across multiple genera of birds, fish, reptiles, amphibians, and even mammals. This protocol describes a technique for examining organisms for the presence of UV-reflecting structures and a method for testing whether these cues are used as social signals in the context of mate choice. A spectrophotometer is used to detect the presence of UV reflectance and variation in reflective intensity between individuals and sexes. An example of this technique is presented in which a dichotomous mate choice test exposes sexually receptive individuals to opposite sex individuals whose visual appearance can be manipulated by filters that either transmit full spectrum or block UV wavelengths. This system allowed for the determination that female, but not male, sailfin mollies (Poecilia latipinna) were using UV markings as part of their mating decisions. These types of studies serve to expand our knowledge of the range of organisms that utilize UV and provide insight into how UV plays a role in their lives.

Assays to Detect UV-reflecting Structures and Determine their Importance in Mate Preference using the Sailfin Molly Poecilia latipinna

This protocol outlines the use of spectrophotometry to detect ultraviolet-reflecting structures on organisms (in this example, the sailfin molly Poecilia latipinna) and describes dichotomous choice tests for fish that allow inferences to be made on the role of ultraviolet cues during mate selection.

Many organisms use cues and signals beyond human sensitivity during social interactions. It is important to take into account how organisms perceive their ...

Boldness, Aggression, and Shoaling Assays for Zebrafish Behavioral Syndromes

A behavioral syndrome exists when specific behaviors interact under different contexts. Zebrafish have been test subjects in recent studies and it is important to standardize protocols to ensure proper analyses and interpretations. In our previous studies, we have measured boldness by monitoring a series of behaviors (time near surface, latency in transitions, number of transitions, and darts) in a 1.5 L trapezoidal tank. Likewise, we quantified aggression by observing bites, lateral displays, darts, and time near an inclined mirror in a rectangular 19 L tank. By dividing a 76 L tank into thirds, we also examined shoaling preferences. The shoaling assay is a highly customizable assay and can be tailored for specific hypotheses. However, protocols for this assay also must be standardized, yet flexible enough for customization. In previous studies, end chambers were either empty, contained 5 or 10 zebrafish, or 5 pearl danios (D. albolineatus). In the following manuscript, we present a detailed protocol and representative data that accompany successful applications of the protocol, which will allow for replication of behavioral syndrome experiments.

This manuscript describes the setup, implementation, and analysis of boldness, aggression, and shoaling in zebrafish and testing for the presence of a behavioral syndrome. A standardized approach for behavioral quantification will allow for easier comparison across studies. Modifications to this protocol are possible as each assay can be run individually.

A behavioral syndrome exists when specific behaviors interact under different contexts. Zebrafish have been test subjects in recent studies and it is ...

Medicine

Assessment of Swim Endurance and Swim Behavior in Adult Zebrafish

Due to their renowned regenerative capacity, adult zebrafish are a premier vertebrate model to interrogate mechanisms of innate spinal cord regeneration. Following complete transection of their spinal cord, zebrafish extend glial and axonal bridges across severed tissue, regenerate neurons proximal to the lesion, and regain their swim capacities within 8 weeks of injury. Recovery of swim function is thus a central readout for functional spinal cord repair. Here, we describe a set of behavioral assays to quantify zebrafish motor capacity inside an enclosed swim tunnel. The goal of these methods is to provide quantifiable measurements of swim endurance and swim behavior in adult zebrafish. For swim endurance, zebrafish are subjected to a constantly increasing water current velocity until exhaustion, and time at exhaustion is reported. For swim behavior assessment, zebrafish are subjected to low current velocities and swim videos are captured with a dorsal view of the fish. Percent activity, burst frequency, and time spent against the water current provide quantifiable readouts of swim behavior. We quantified swim endurance and swim behavior in wild-type zebrafish before injury and after spinal cord transection. We found that zebrafish lose swim function after spinal cord transection and gradually regain that capacity between 2 and 6 weeks post-injury. The methods described in this study could be applied to neurobehavioral, musculoskeletal, skeletal muscle regeneration, and neural regeneration studies in adult zebrafish.

Capable of functional recovery after spinal cord injury, adult zebrafish is a premier model system to elucidate innate mechanisms of neural regeneration. Here, we describe swim endurance and swim behavior assays as functional readouts of spinal cord regeneration.

Due to their renowned regenerative capacity, adult zebrafish are a premier vertebrate model to interrogate mechanisms of innate spinal cord regeneration. ...

Silencing the Spark: CRISPR/Cas9 Genome Editing in Weakly Electric Fish

Electroreception and electrogenesis have changed in the evolutionary history of vertebrates. There is a striking degree of convergence in these independently derived phenotypes, which share a common genetic architecture. This is perhaps best exemplified by the numerous convergent features of gymnotiforms and mormyrids, two species-rich teleost clades that produce and detect weak electric fields and are called weakly electric fish. In the 50 years since the discovery that weakly electric fish use electricity to sense their surroundings and communicate, a growing community of scientists has gained tremendous insights into evolution of development, systems and circuits neuroscience, cellular physiology, ecology, evolutionary biology, and behavior. More recently, there has been a proliferation of genomic resources for electric fish. Use of these resources has already facilitated important insights with regards to the connection between genotype and phenotype in these species. A major obstacle to integrating genomics data with phenotypic data of weakly electric fish is a present lack of functional genomics tools. We report here a full protocol for performing CRISPR/Cas9 mutagenesis that utilizes endogenous DNA repair mechanisms in weakly electric fish. We demonstrate that this protocol is equally effective in both the mormyrid species Brienomyrus brachyistius and the gymnotiform Brachyhypopomus gauderio by using CRISPR/Cas9 to target indels and point mutations in the first exon of the sodium channel gene scn4aa. Using this protocol, embryos from both species were obtained and genotyped to confirm that the predicted mutations in the first exon of the sodium channel scn4aa were present. The knock-out success phenotype was confirmed with recordings showing reduced electric organ discharge amplitudes when compared to uninjected size-matched controls.

Here, a protocol is presented to produce and rear CRISPR/Cas9 genome knockout electric fish. Outlined in detail are the required molecular biology, breeding, and husbandry requirements for both a gymnotiform and a mormyrid, and injection techniques to produce Cas9-induced indel F0 larvae.

Using the FishSim Animation Toolchain to Investigate Fish Behavior: A Case Study on Mate-Choice Copying In Sailfin Mollies

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