Three-dimensional reconstruction of the fast-start swimming kinematics of densely schooling fish

The role of hydrodynamics in collective motions of fish schools and bioinspired underwater robots

Collective behaviour defines the lives of many animal species on the Earth. Underwater swarms span several orders of magnitude in size, from coral larvae and krill to tunas and dolphins. Agent-based algorithms have modelled collective movements of animal groups by use of social forces, which approximate the behaviour of individual animals. But details of how swarming individuals interact with the fluid environment are often under-examined. How do fluid forces shape aquatic swarms? How do fish use their flow-sensing capabilities to coordinate with their schooling mates? We propose viewing underwater collective behaviour from the framework of fluid stigmergy, which considers both physical interactions and information transfer in fluid environments. Understanding the role of hydrodynamics in aquatic collectives requires multi-disciplinary efforts across fluid mechanics, biology and biomimetic robotics. To facilitate future collaborations, we synthesize key studies in these fields.

Recent Advancements in Deep Learning Frameworks for Precision Fish Farming Opportunities, Challenges, and Applications

The growth of the fish is influenced by a variety of scientific factors. So, profit can be easily achieved by using some clever techniques, for example, maintaining the correct pH level along with the dissolved oxygen (DO) level and temperature, as well as turbidity for good growth of fish. Fully grown fish are generally sold at a good price because price of fish in the market is governed by weight as well as size of nurtured fish. Artificial intelligence (AI)-based systems may be created to regulate key water quality factors including salinity, dissolved oxygen, pH, and temperature. The software programme operates on an application server and is connected to multiparameter water quality meters in this system. This study examines smart fish farming methods that show how complicated science and technology may be simplified for use in seafood production. This research focuses on the use of artificial intelligence in fish culture in this setting. The technical specifics of DL approaches used in smart fish farming which includes data and algorithms as well as performance was also examined. In a nutshell, our goal is to provide academics and practitioners with a better understanding of the current state of the art in DL implementation in aquaculture, which will help them deploy smart fish farming applications as well their benefits.

Combining stereo‐video monitoring and physiological trials to estimate reef fish metabolic demands in the wild

Organismal metabolic rates (MRs) are the basis of energy and nutrient fluxes through ecosystems. In the marine realm, fishes are some of the most prominent consumers. However, their metabolic demand in the wild (field MR [FMR]) is poorly documented, because it is challenging to measure directly. Here, we introduce a novel approach to estimating the component of FMR associated with voluntary activity (i.e., the field active MR [AMRfield]). Our approach combines laboratory‐based respirometry, swimming speeds, and field‐based stereo‐video systems to estimate the activity of individuals. We exemplify our approach by focusing on six coral reef fish species, for which we quantified standard MR and maximum MR (SMR and MMR, respectively) in the laboratory, and body sizes and swimming speeds in the field. Based on the relationships between MR, body size, and swimming speeds, we estimate that the activity scope (i.e., the ratio between AMRfield and SMR) varies from 1.2 to 3.2 across species and body sizes. Furthermore, we illustrate that the scaling exponent for AMRfield varies across species and can substantially exceed the widely assumed value of 0.75 for SMR. Finally, by scaling organismal AMRfield estimates to the assemblage level, we show the potential effect of this variability on community metabolic demand. Our approach may improve our ability to estimate elemental fluxes mediated by a critically important group of aquatic animals through a non‐destructive, widely applicable technique.

Dominating lengthscales of zebrafish collective behaviour

Collective behaviour in living systems is observed across many scales, from bacteria to insects, to fish shoals. Zebrafish have emerged as a model system amenable to laboratory study. Here we report a three-dimensional study of the collective dynamics of fifty zebrafish. We observed the emergence of collective behaviour changing between ordered to randomised, upon adaptation to new environmental conditions. We quantify the spatial and temporal correlation functions of the fish and identify two length scales, the persistence length and the nearest neighbour distance, that capture the essence of the behavioural changes. The ratio of the two length scales correlates robustly with the polarisation of collective motion that we explain with a reductionist model of self-propelled particles with alignment interactions.

epiTracker: A Framework for Highly Reliable Particle Tracking for the Quantitative Analysis of Fish Movements in Tanks

Behavioral analysis of moving animals relies on a faithful recording and track analysis to extract relevant parameters of movement. To study group behavior and social interactions, often simultaneous analyses of individuals are required. To detect social interactions, for example to identify the leader of a group as opposed to followers, one needs an error-free segmentation of individual tracks throughout time. While automated tracking algorithms exist that are quick and easy to use, inevitable errors will occur during tracking. To solve this problem, we introduce a robust algorithm called epiTracker for segmentation and tracking of multiple animals in two-dimensional (2D) videos along with an easy-to-use correction method that allows one to obtain error-free segmentation. We have implemented two graphical user interfaces to allow user-friendly control of the functions. Using six labeled 2D datasets, the effort to obtain accurate labels is quantified and compared to alternative available software solutions. Both the labeled datasets and the software are publicly available.

Superfetation reduces the negative effects of pregnancy on the fast-start escape performance in live-bearing fish

Superfetation, the ability to simultaneously carry multiple litters of different developmental stages in utero, is a reproductive strategy that evolved repeatedly in viviparous animal lineages. The evolution of superfetation is hypothesized to reduce the reproductive burden and, consequently, improve the locomotor performance of the female during pregnancy. Here, we apply new computer-vision-based techniques to study changes in body shape and three-dimensional fast-start escape performance during pregnancy in three live-bearing fishes (family Poeciliidae) that exhibit different levels of superfetation. We found that superfetation correlates with a reduced abdominal distension and a more slender female body shape just before parturition. We further found that body slenderness positively correlates with maximal speeds, curvature amplitude and curvature rate, implying that superfetation improves the fast-start escape performance. Collectively, our study suggests that superfetation may have evolved in performance-demanding (e.g. high flow or high predation) environments to reduce the locomotor cost of pregnancy.

The zebrafish subcortical social brain as a model for studying social behavior disorders

Social behaviors are essential for the survival and reproduction of social species. Many, if not most, neuropsychiatric disorders in humans are either associated with underlying social deficits or are accompanied by social dysfunctions. Traditionally, rodent models have been used to model these behavioral impairments. However, rodent assays are often difficult to scale up and adapt to high-throughput formats, which severely limits their use for systems-level science. In recent years, an increasing number of studies have used zebrafish (Danio rerio) as a model system to study social behavior. These studies have demonstrated clear potential in overcoming some of the limitations of rodent models. In this Review, we explore the evolutionary conservation of a subcortical social brain between teleosts and mammals as the biological basis for using zebrafish to model human social behavior disorders, while summarizing relevant experimental tools and assays. We then discuss the recent advances gleaned from zebrafish social behavior assays, the applications of these assays to studying related disorders, and the opportunities and challenges that lie ahead.

Reorientation and propulsion in fast-starting zebrafish larvae: an inverse dynamics analysis

Most fish species use fast starts to escape from predators. Zebrafish larvae perform effective fast starts immediately after hatching. They use a C-start, where the body curls into a C-shape, and then unfolds to accelerate. These escape responses need to fulfil a number of functional demands, under the constraints of the fluid environment and the larva's body shape. Primarily, the larvae need to generate sufficient escape speed in a wide range of possible directions, in a short-enough time. In this study, we examined how the larvae meet these demands. We filmed fast starts of zebrafish larvae with a unique five-camera setup with high spatiotemporal resolution. From these videos, we reconstructed the 3D swimming motion with an automated method and from these data calculated resultant hydrodynamic forces and, for the first time, 3D torques. We show that zebrafish larvae reorient mostly in the first stage of the start by producing a strong yaw torque, often without using the pectoral fins. This reorientation is expressed as the body angle, a measure that represents the rotation of the complete body, rather than the commonly used head angle. The fish accelerates its centre of mass mostly in stage 2 by generating a considerable force peak while the fish 'unfolds'. The escape direction of the fish correlates strongly with the amount of body curvature in stage 1, while the escape speed correlates strongly with the duration of the start. This may allow the fish to independently control the direction and speed of the escape.

Segmentation of Laterally Symmetric Overlapping Objects: Application to Images of Collective Animal Behavior

Video analysis is currently the main non-intrusive method for the study of collective behavior. However, 3D-to-2D projection leads to overlapping of observed objects. The situation is further complicated by the absence of stall shapes for the majority of living objects. Fortunately, living objects often possess a certain symmetry which was used as a basis for morphological fingerprinting. This technique allowed us to record forms of symmetrical objects in a pose-invariant way. When combined with image skeletonization, this gives a robust, nonlinear, optimization-free, and fast method for detection of overlapping objects, even without any rigid pattern. This novel method was verified on fish (European bass, Dicentrarchus labrax, and tiger barbs, Puntius tetrazona) swimming in a reasonably small tank, which forced them to exhibit a large variety of shapes. Compared with manual detection, the correct number of objects was determined for up to almost 90 % of overlaps, and the mean Dice-Sørensen coefficient was around 0.83 . This implies that this method is feasible in real-life applications such as toxicity testing.

Target tracking and 3D trajectory acquisition of cabbage butterfly (P. rapae) based on the KCF-BS algorithm

Insect behaviour is an important research topic in plant protection. To study insect behaviour accurately, it is necessary to observe and record their flight trajectory quantitatively and precisely in three dimensions (3D). The goal of this research was to analyse frames extracted from videos using Kernelized Correlation Filters (KCF) and Background Subtraction (BS) (KCF-BS) to plot the 3D trajectory of cabbage butterfly (P. rapae). Considering the experimental environment with a wind tunnel, a quadrature binocular vision insect video capture system was designed and applied in this study. The KCF-BS algorithm was used to track the butterfly in video frames and obtain coordinates of the target centroid in two videos. Finally the 3D trajectory was calculated according to the matching relationship in the corresponding frames of two angles in the video. To verify the validity of the KCF-BS algorithm, Compressive Tracking (CT) and Spatio-Temporal Context Learning (STC) algorithms were performed. The results revealed that the KCF-BS tracking algorithm performed more favourably than CT and STC in terms of accuracy and robustness.

The effects of lateral line ablation and regeneration in schooling giant danios

Fish use multiple sensory systems, including vision and their lateral line system, to maintain position and speed within a school. Although previous studies have shown that ablating the lateral line alters schooling behavior, no one has examined how the behavior recovers as the sensory system regenerates. We studied how schooling behavior changes in giant danios, Devario aequipinnatus, when their lateral line system is chemically ablated and after the sensory hair cells regenerate. We found that fish could school normally immediately after chemical ablation, but that they had trouble schooling 1-2 weeks after the chemical treatment, when the hair cells had fully regenerated. We filmed groups of giant danios with two high-speed cameras and reconstructed the three-dimensional positions of each fish within a group. One fish in the school was treated with gentamycin to ablate all hair cells. Both types of neuromasts (canal and superficial) were completely ablated after treatment, but fully regenerated after 1 week. We quantified the structure of the school using nearest neighbor distance, bearing, elevation, and the cross-correlation of velocity between each pair of fish. Treated fish maintained a normal position within the school immediately after the lateral line ablation, but could not school normally 1 or 2 weeks after treatment, even though the neuromasts had fully regenerated. By 4-8 weeks post-treatment, the treated fish could again school normally. These results demonstrate that the behavioral recovery after lateral line ablation is a longer process than the regeneration of the hair cells themselves.

Biomechanics of swimming in developing larval fish

Most larvae of bony fish are able to swim almost immediately after hatching. Their locomotory system supports several vital functions: fish larvae make fast manoeuvres to escape from predators, aim accurately during suction feeding and may migrate towards suitable future habitats. Owing to their small size and low swimming speed, larval fish operate in the intermediate hydrodynamic regime, which connects the viscous and inertial flow regimes. They experience relatively strong viscous effects at low swimming speeds, and relatively strong inertial effects at their highest speeds. As the larvae grow and increase swimming speed, a shift occurs towards the inertial flow regime. To compensate for size-related limitations on swimming speed, fish larvae exploit high tail beat frequencies at their highest speeds, made possible by their low body inertia and fast neuromuscular system. The shifts in flow regime and body inertia lead to changing functional demands on the locomotory system during larval growth. To reach the reproductive adult stage, the developing larvae need to adjust to and perform the functions necessary for survival. Just after hatching, many fish larvae rely on yolk and need to develop their feeding systems before the yolk is exhausted. Furthermore, the larvae need to develop and continuously adjust their sensory, neural and muscular systems to catch prey and avoid predation. This Review discusses the hydrodynamics of swimming in the intermediate flow regime, the changing functional demands on the locomotory system of the growing and developing larval fish, and the solutions that have evolved to accommodate these demands.

Three-dimensional analysis of the fast-start escape response of the least killifish, Heterandria formosa

Fish make C-starts to evade predator strikes. Double-bend (DB) C-starts consist of three stages: Stage 1, in which the fish rapidly bends into a C-shape; Stage 2, in which the fish bends in the opposite direction; and a variable Stage 3. In single-bend (SB) C-starts, the fish immediately straightens after Stage 1. Despite fish moving in 3D space, fast-start responses of adult fish have mainly been studied in a horizontal plane. Using automated 3D tracking of multi-camera high-speed video sequences, we show that both SB and DB fast-starts by adult female least killifish (Heterandria formosa) often contain a significant vertical velocity component, and large changes in pitch (DB: up to 43 deg) and roll (DB: up to 77 deg) angles. Upwards and downwards elevation changes are correlated with changes in pitch angle of the head; movement in the horizontal plane is correlated with changes in yaw angle of the head. With respect to the stimulus, escape heading correlates with the elevation of the fish at the onset of motion. Irrespective of the initial orientation, fish can escape in any horizontal direction. In many cases, the centre of mass barely accelerates during Stage 1. However, it does accelerate in the final direction of the escape in other instances, indicating that Stage 1 can serve a propulsive role in addition to its preparatory role for Stage 2. Our findings highlight the importance of large-scale 3D analyses of fast-start manoeuvres of adult fish in uncovering the versatility of fish escape repertoire.

Feature point based 3D tracking of multiple fish from multi-view images

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly.

Multiple fish tracking with an NACA airfoil model for collective behavior analysis

We propose a visual tracking method with an NACA airfoil model for dense fish schools in which occlusions occur frequently. Although much progress has been made for tracking multiple objects, it remains a challenging task to track individuals due to factors such as occlusion and target appearance variation. In this paper, we first introduce a NACA airfoil model as a deformable appearance model of fish. For occluded fish, we estimate their positions, angles, and postures with template matching and simulated annealing algorithms to effectively optimize their parameters. To improve performance of tracking, we repeatedly track fish with the parameter estimation algorithm forwards and backwards. We prepared two real fish scenes in which the average number of fish is over 25 in each frame and multiple fish superimpose over 50 times. Experimental results for the scenes show that fish are practically tracked with our method compared to a tracking method based on a mixture particle filter. Over 75 % of fish in each scene have been tracked throughout the scene, and the average difference is less than 4 % of the mean body length of the school.

An effective and robust method for tracking multiple fish in video image based on fish head detection

Background

Fish tracking is an important step for video based analysis of fish behavior. Due to severe body deformation and mutual occlusion of multiple swimming fish, accurate and robust fish tracking from video image sequence is a highly challenging problem. The current tracking methods based on motion information are not accurate and robust enough to track the waving body and handle occlusion. In order to better overcome these problems, we propose a multiple fish tracking method based on fish head detection.

Results

The shape and gray scale characteristics of the fish image are employed to locate the fish head position. For each detected fish head, we utilize the gray distribution of the head region to estimate the fish head direction. Both the position and direction information from fish detection are then combined to build a cost function of fish swimming. Based on the cost function, global optimization method can be applied to associate the target between consecutive frames. Results show that our method can accurately detect the position and direction information of fish head, and has a good tracking performance for dozens of fish.

Conclusion

The proposed method can successfully obtain the motion trajectories for dozens of fish so as to provide more precise data to accommodate systematic analysis of fish behavior.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1138-y) contains supplementary material, which is available to authorized users.

Automated Planar Tracking the Waving Bodies of Multiple Zebrafish Swimming in Shallow Water

Zebrafish (Danio rerio) is one of the most widely used model organisms in collective behavior research. Multi-object tracking with high speed camera is currently the most feasible way to accurately measure their motion states for quantitative study of their collective behavior. However, due to difficulties such as their similar appearance, complex body deformation and frequent occlusions, it is a big challenge for an automated system to be able to reliably track the body geometry of each individual fish. To accomplish this task, we propose a novel fish body model that uses a chain of rectangles to represent fish body. Then in detection stage, the point of maximum curvature along fish boundary is detected and set as fish nose point. Afterwards, in tracking stage, we firstly apply Kalman filter to track fish head, then use rectangle chain fitting to fit fish body, which at the same time further judge the head tracking results and remove the incorrect ones. At last, a tracklets relinking stage further solves trajectory fragmentation due to occlusion. Experiment results show that the proposed tracking system can track a group of zebrafish with their body geometry accurately even when occlusion occurs from time to time.

Turbulence triggers vigorous swimming but hinders motion strategy in planktonic copepods

Calanoid copepods represent a major component of the plankton community. These small animals reside in constantly flowing environments. Given the fundamental role of behaviour in their ecology, it is especially relevant to know how copepods perform in turbulent flows. By means of three-dimensional particle tracking velocimetry, we reconstructed the trajectories of hundreds of adult Eurytemora affinis swimming freely under realistic intensities of homogeneous turbulence. We demonstrate that swimming contributes substantially to the dynamics of copepods even when turbulence is significant. We show that the contribution of behaviour to the overall dynamics gradually reduces with turbulence intensity but regains significance at moderate intensity, allowing copepods to maintain a certain velocity relative to the flow. These results suggest that E. affinis has evolved an adaptive behavioural mechanism to retain swimming efficiency in turbulent flows. They suggest the ability of some copepods to respond to the hydrodynamic features of the surrounding flow. Such ability may improve survival and mating performance in complex and dynamic environments. However, moderate levels of turbulence cancelled gender-specific differences in the degree of space occupation and innate movement strategies. Our results suggest that the broadly accepted mate-searching strategies based on trajectory complexity and movement patterns are inefficient in energetic environments.

Automated Reconstruction of Three-Dimensional Fish Motion, Forces, and Torques

Fish can move freely through the water column and make complex three-dimensional motions to explore their environment, escape or feed. Nevertheless, the majority of swimming studies is currently limited to two-dimensional analyses. Accurate experimental quantification of changes in body shape, position and orientation (swimming kinematics) in three dimensions is therefore essential to advance biomechanical research of fish swimming. Here, we present a validated method that automatically tracks a swimming fish in three dimensions from multi-camera high-speed video. We use an optimisation procedure to fit a parameterised, morphology-based fish model to each set of video images. This results in a time sequence of position, orientation and body curvature. We post-process this data to derive additional kinematic parameters (e.g. velocities, accelerations) and propose an inverse-dynamics method to compute the resultant forces and torques during swimming. The presented method for quantifying 3D fish motion paves the way for future analyses of swimming biomechanics.

Effect of acute ethanol administration on zebrafish tail-beat motion

Zebrafish is becoming a species of choice in neurobiological and behavioral studies of alcohol-related disorders. In these efforts, the activity of adult zebrafish is typically quantified using indirect activity measures that are either scored manually or identified automatically from the fish trajectory. The analysis of such activity measures has produced important insight into the effect of acute ethanol exposure on individual and social behavior of this vertebrate species. Here, we leverage a recently developed tracking algorithm that reconstructs fish body shape to investigate the effect of acute ethanol administration on zebrafish tail-beat motion in terms of amplitude and frequency. Our results demonstrate a significant effect of ethanol on the tail-beat amplitude as well as the tail-beat frequency, both of which were found to robustly decrease for high ethanol concentrations. Such a direct measurement of zebrafish motor functions is in agreement with evidence based on indirect activity measures, offering a complementary perspective in behavioral screening.

Refraction corrected calibration for aquatic locomotion research: application of Snell's law improves spatial accuracy

Images of underwater objects are distorted by refraction at the water-glass-air interfaces and these distortions can lead to substantial errors when reconstructing the objects' position and shape. So far, aquatic locomotion studies have minimized refraction in their experimental setups and used the direct linear transform algorithm (DLT) to reconstruct position information, which does not model refraction explicitly. Here we present a refraction corrected ray-tracing algorithm (RCRT) that reconstructs position information using Snell's law. We validated this reconstruction by calculating 3D reconstruction error-the difference between actual and reconstructed position of a marker. We found that reconstruction error is small (typically less than 1%). Compared with the DLT algorithm, the RCRT has overall lower reconstruction errors, especially outside the calibration volume, and errors are essentially insensitive to camera position and orientation and the number and position of the calibration points. To demonstrate the effectiveness of the RCRT, we tracked an anatomical marker on a seahorse recorded with four cameras to reconstruct the swimming trajectory for six different camera configurations. The RCRT algorithm is accurate and robust and it allows cameras to be oriented at large angles of incidence and facilitates the development of accurate tracking algorithms to quantify aquatic manoeuvers.

Automatically detect and track multiple fish swimming in shallow water with frequent occlusion

Due to its universality, swarm behavior in nature attracts much attention of scientists from many fields. Fish schools are examples of biological communities that demonstrate swarm behavior. The detection and tracking of fish in a school are of important significance for the quantitative research on swarm behavior. However, different from other biological communities, there are three problems in the detection and tracking of fish school, that is, variable appearances, complex motion and frequent occlusion. To solve these problems, we propose an effective method of fish detection and tracking. In this method, first, the fish head region is positioned through extremum detection and ellipse fitting; second, The Kalman filtering and feature matching are used to track the target in complex motion; finally, according to the feature information obtained by the detection and tracking, the tracking problems caused by frequent occlusion are processed through trajectory linking. We apply this method to track swimming fish school of different densities. The experimental results show that the proposed method is both accurate and reliable.

Automated image-based tracking and its application in ecology

The behavior of individuals determines the strength and outcome of ecological interactions, which drive population, community, and ecosystem organization. Bio-logging, such as telemetry and animal-borne imaging, provides essential individual viewpoints, tracks, and life histories, but requires capture of individuals and is often impractical to scale. Recent developments in automated image-based tracking offers opportunities to remotely quantify and understand individual behavior at scales and resolutions not previously possible, providing an essential supplement to other tracking methodologies in ecology. Automated image-based tracking should continue to advance the field of ecology by enabling better understanding of the linkages between individual and higher-level ecological processes, via high-throughput quantitative analysis of complex ecological patterns and processes across scales, including analysis of environmental drivers.

The effects of flow on schooling Devario aequipinnatus: school structure, startle response and information transmission

To assess how flow affects school structure and threat detection, startle response rates of solitary and small groups of giant danio Devario aequipinnatus to visual looming stimuli were compared in flow and no-flow conditions. The instantaneous position and heading of each D. aequipinnatus was extracted from high-speed videos. Behavioural results indicate that (1) school structure is altered in flow such that D. aequipinnatus orient upstream while spanning out in a crosswise direction, (2) the probability of at least one D. aequipinnatus detecting the visual looming stimulus is higher in flow than no flow for both solitary D. aequipinnatus and groups of eight D. aequipinnatus; however, (3) the probability of three or more individuals responding is higher in no flow than in flow. These results indicate a higher probability of stimulus detection in flow but a higher probability of internal transmission of information in no flow. Finally, results were well predicted by a computational model of collective fright response that included the probability of direct detection (based on signal detection theory) and indirect detection (i.e. via interactions between group members) of threatening stimuli. This model provides a new theoretical framework for analysing the collective transfer of information among groups of fishes and other organisms.

Sedentary behavior as a factor in determining lateral line contributions to rheotaxis

Rheotaxis is a robust, multisensory behavior with many potential benefits for fish and other aquatic animals. Visual (optic flow) cues appear to be sufficient for rheotaxis, but other sensory cues can clearly compensate for the loss of vision. The role of various non-visual sensory systems, in particularly the flow-sensing lateral line, is poorly understood-largely due to widely varying methods and sensory conditions for studying rheotaxis. Here, we examine how sedentary behavior under visually deprived conditions affects the relative importance of lateral line cues in two species: one that is normally sedentary (the three-lined corydoras, Corydoras trilineatus) and one that normally swims continuously along the substrate (the blind cavefish, Astyanax mexicanus). No effect of lateral line disruption on rheotactic performance was found in blind cavefish, which were significantly more mobile than three-lined corydoras. By contrast, rheotaxis was significantly impaired at low, but not high, flow speeds in lateral-line deprived corydoras. In addition, lateral line enabled corydoras were characterized by decreased mobility and increased rheotactic performance relative to lateral line deprived fish. Taken together, these results suggest that sedentary behavior is an important factor in promoting reliance on lateral line cues.

Behavioral responses of the estuarine calanoid copepod Eurytemora affinis to sub-lethal concentrations of waterborne pollutants

Estuarine waters contain a variety of chemicals which affect to various extents the behavior of aquatic organisms. Little is known, however, on the behavioral response of copepods. The present study shows the results of laboratory experiments investigating the immediate effects of sub-lethal concentrations of three commonly found contaminants on the three-dimensional swimming behavior of the estuarine calanoid copepod Eurytemora affinis. Nonylphenol at 2 μg L⁻¹, cadmium at 45 n gL⁻¹ and a mixture of low to medium molecular weight polycyclic aromatic hydrocarbons at 40 ng L⁻¹ all affected the swimming behavior of E. affinis adults, increasing both swimming speed and activity. In most cases, effects were observable within 30 min of exposure and persisted or faded during a period of depuration in uncontaminated water of similar duration. In ovigerous females exposed to Cd and PAHs, effects appeared to be more pronounced during the depuration period, suggesting that carrying ovisacs may impair recovery. We quantified differences in the distribution of swimming speed values by considering the relative frequencies of periods of break, slow and fast swimming and we observed a trend toward faster movements in the presence of pollutants. The degree of trajectory complexity, estimated through their fractal dimension, was unaffected by pollutants. Since both narcotic and non-narcotic pollutants induced hyperactivity, our results suggest that changes in behavior after a short-term exposure may be independent of the general mode of action of the chemicals. The increase in speed and activity resembles an escape reaction permitting copepods to evade stressful conditions. Overall, these results indicate that environment-relevant concentrations of pollutants can induce rapid changes in copepod behavior. Since behavioral processes represent a fundamental element in the ecology of copepods, our results raise concern about the effects of background levels of pollution on a major component of the plankton community. The long-term response of copepods to waterborne pollutants, their synergistic effects and their interactions with other environmental factors need further investigation.

The spatiotemporal dynamics of rheotactic behavior depends on flow speed and available sensory information

Rheotaxis is a robust, multisensory behavior with many potential benefits for fish and other aquatic organisms. Visual (optic flow) cues appear to be sufficient for rheotaxis, but other sensory cues can clearly compensate for the loss of vision. Nevertheless, the nature of multisensory interactions and the relative contributions of different senses under varying conditions are poorly understood - largely because there is so little description of the actual behavior. Here, we examined the effects of different flow speeds and different sensory conditions on the spatiotemporal dynamics of rheotaxis. Although the overall ability of giant danio (Devario aequipinnatus) to head upstream is largely unaffected by either unimodal or bimodal deprivation of visual and/or lateral line senses, the spatiotemporal form of the behavior is altered in subtle ways. When deprived of vision, fish move further upstream, but the angular accuracy of the upstream heading is reduced. In addition, visually deprived fish exhibit left/right sweeping movements near the upstream barrier at low flow speeds. Sweeping movements are abolished when these fish are additionally deprived of lateral line information. These results indicate that fish adopt different sensorimotor strategies to compensate for the loss of one or more senses and that the nature of multisensory interactions is a complex function of flow speed.

Closed-loop control of zebrafish response using a bioinspired robotic-fish in a preference test

In this paper, we study the response of zebrafish to a robotic-fish whose morphology and colour pattern are inspired by zebrafish. Experiments are conducted in a three-chambered instrumented water tank where a robotic-fish is juxtaposed with an empty compartment, and the preference of live subjects is scored as the mean time spent in the vicinity of the tank's two lateral sides. The tail-beating of the robotic-fish is controlled in real-time based on feedback from fish motion to explore a spectrum of closed-loop systems, including proportional and integral controllers. Closed-loop control systems are complemented by open-loop strategies, wherein the tail-beat of the robotic-fish is independent of the fish motion. The preference space and the locomotory patterns of fish for each experimental condition are analysed and compared to understand the influence of real-time closed-loop control on zebrafish response. The results of this study show that zebrafish respond differently to the pattern of tail-beating motion executed by the robotic-fish. Specifically, the preference and behaviour of zebrafish depend on whether the robotic-fish tail-beating frequency is controlled as a function of fish motion and how such closed-loop control is implemented.

Mosquitofish (Gambusia affinis) preference and behavioral response to animated images of conspecifics altered in their color, aspect ratio, and swimming depth

Mosquitofish (Gambusia affinis) is an example of a freshwater fish species whose remarkable diffusion outside its native range has led to it being placed on the list of the world's hundred worst invasive alien species (International Union for Conservation of Nature). Here, we investigate mosquitofish shoaling tendency using a dichotomous choice test in which computer-animated images of their conspecifics are altered in color, aspect ratio, and swimming level in the water column. Pairs of virtual stimuli are systematically presented to focal subjects to evaluate their attractiveness and the effect on fish behavior. Mosquitofish respond differentially to some of these stimuli showing preference for conspecifics with enhanced yellow pigmentation while exhibiting highly varying locomotory patterns. Our results suggest that computer-animated images can be used to understand the factors that regulate the social dynamics of shoals of Gambusia affinis. Such knowledge may inform the design of control plans and open new avenues in conservation and protection of endangered animal species.

Three-dimensional tracking and behaviour monitoring of multiple fruit flies

The increasing interest in the investigation of social behaviours of a group of animals has heightened the need for developing tools that provide robust quantitative data. Drosophila melanogaster has emerged as an attractive model for behavioural analysis; however, there are still limited ways to monitor fly behaviour in a quantitative manner. To study social behaviour of a group of flies, acquiring the position of each individual over time is crucial. There are several studies that have tried to solve this problem and make this data acquisition automated. However, none of these studies has addressed the problem of keeping track of flies for a long period of time in three-dimensional space. Recently, we have developed an approach that enables us to detect and keep track of multiple flies in a three-dimensional arena for a long period of time, using multiple synchronized and calibrated cameras. After detecting flies in each view, correspondence between views is established using a novel approach we call the 'sequential Hungarian algorithm'. Subsequently, the three-dimensional positions of flies in space are reconstructed. We use the Hungarian algorithm and Kalman filter together for data association and tracking. We evaluated rigorously the system's performance for tracking and behaviour detection in multiple experiments, using from one to seven flies. Overall, this system presents a powerful new method for studying complex social interactions in a three-dimensional environment.