Turbulence triggers vigorous swimming but hinders motion strategy in planktonic copepods

Learning to swim efficiently in a nonuniform flow field

Microswimmers can acquire information on the surrounding fluid by sensing mechanical queues. They can then navigate in response to these signals. We analyze this navigation by combining deep reinforcement learning with direct numerical simulations to resolve the hydrodynamics. We study how local and nonlocal information can be used to train a swimmer to achieve particular swimming tasks in a nonuniform flow field, in particular, a zigzag shear flow. The swimming tasks are (1) learning how to swim in the vorticity direction, (2) learning how to swim in the shear-gradient direction, and (3) learning how to swim in the shear-flow direction. We find that access to laboratory frame information on the swimmer's instantaneous orientation is all that is required in order to reach the optimal policy for tasks (1) and (2). However, information on both the translational and rotational velocities seems to be required to accomplish task (3). Inspired by biological microorganisms, we also consider the case where the swimmers sense local information, i.e., surface hydrodynamic forces, together with a signal direction. This might correspond to gravity or, for microorganisms with light sensors, a light source. In this case, we show that the swimmer can reach a comparable level of performance to that of a swimmer with access to laboratory frame variables. We also analyze the role of different swimming modes, i.e., pusher, puller, and neutral.

Experimental investigation of preferential concentration in zooplankton swimming in turbulence

Turbulence can cause particles to accumulate within specific regions of the flow. One mechanism responsible for this phenomenon, called preferential concentration, consists in particle-fluid interactions yielding inhomogeneous spatial distribution of particles into clusters or depleted regions due to density difference or finite-size effects. In the case of living particles such as plankton, clustering may also originate from their motility or from their behavioral response to turbulent forcing. Preferential concentration of plankton has attracted much attention, because it is a key determinant of encounter rates and therefore relevant for a wide range of ecological processes. However, most studies have focused on microscopic cells, and consequently the case of larger organisms remains poorly studied. Here, we use high-performance particle tracking and three-dimensional Voronoï analysis to test for the emergence of clustering in the spatial distribution of calanoid copepods, the most important metazoans in the oceans in terms of biomass. We found that neither inertia nor motility resulted in significant departure from a random Poisson process over a range of turbulence intensity from very strong to moderate. However, we observed weak clustering in calm water, which may originate from hydrodynamic and olfactory interactions between organisms. Our results improve our understanding of fluid-particle interactions in the zooplankton and have important implications for the modeling of their encounter rates in turbulence.

Responding to the signal and the noise: behavior of planktonic gastropod larvae in turbulence

Swimming organisms may actively adjust their behavior in response to the flow around them. Ocean flows are typically turbulent, and characterized by chaotic velocity fluctuations. While some studies have observed planktonic larvae altering their behavior in response to turbulence, it is not always clear whether a plankter is responding to an individual turbulent fluctuation or to the time-averaged flow. To distinguish between these two paradigms, we conducted laboratory experiments with larvae in turbulence. We observed veliger larvae of the gastropod Crepidula fornicata in a jet-stirred turbulence tank while simultaneously measuring two-components of the fluid and larval velocity. Larvae were studied at two different stages of development, early-stage and late-stage, and their behavior was analyzed in response to different characteristics of turbulence: acceleration, dissipation, and vorticity. Our analysis considered both the effects of the time-averaged flow and the instantaneous flow around the larvae. Overall, we found that both stages of larvae increased their upward swimming speeds in response to increasing turbulence. However, we found that the early-stage larvae tended to respond to the time-averaged flow whereas the late-stage larvae tended to respond to the instantaneous flow around them. These observations indicate that larvae can integrate flow information over time and that their behavioral responses to turbulence can depend on both their present and past flow environments.

Response of the copepod Acartia tonsa to the hydrodynamic cues of small-scale, dissipative eddies in turbulence

This study quantifies the behavioral response of a marine copepod (Acartia tonsa) to individual, small-scale, dissipative vortices that are ubiquitous in turbulence. Vortex structures were created in the laboratory using a physical model of a Burgers vortex with characteristics corresponding to typical dissipative vortices that copepods are likely to encounter in the turbulent cascade. To examine the directional response of copepods, vortices were generated with the vortex axis aligned in either the horizontal or vertical direction. Tomographic particle image velocimetry was used to measure the volumetric velocity field of the vortex. Three-dimensional copepod trajectories were digitally reconstructed and overlaid on the vortex flow field to quantify A. tonsa's swimming kinematics relative to the velocity field and to provide insight into the copepod behavioral response to hydrodynamic cues. The data show significant changes in swimming kinematics and an increase in relative swimming velocity and hop frequency with increasing vortex strength. Furthermore, in moderate-to-strong vortices, A. tonsa moved at elevated speed in the same direction as the swirling flow and followed spiral trajectories around the vortex, which would retain the copepod within the feature and increase encounter rates with other similarly behaving Acartia While changes in swimming kinematics depended on vortex intensity, orientation of the vortex axis showed minimal significant effect. Hop and escape jump densities were largest in the vortex core, which is spatially coincident with the peak in vorticity, suggesting that vorticity is the hydrodynamic cue that evokes these behaviors.

Efficient mate finding in planktonic copepods swimming in turbulence

Zooplankton live in dynamic environments where turbulence may challenge their limited swimming abilities. How this interferes with fundamental behavioral processes remains elusive. We reconstruct simultaneously the trajectories of flow tracers and calanoid copepods and we quantify their ability to find mates when ambient flow imposes physical constrains on their motion and impairs their olfactory orientation. We show that copepods achieve high encounter rates in turbulence due to the contribution of advection and vigorous swimming. Males further convert encounters within the perception radius to contacts and then to mating via directed motion toward nearby organisms within the short time frame of the encounter. Inertial effects do not result in preferential concentration, reducing the geometric collision kernel to the clearance rate, which we model accurately by superposing turbulent velocity and organism motion. This behavioral and physical coupling mechanism may account for the ability of copepods to reproduce in turbulent environments.

Machine learning strategies for path-planning microswimmers in turbulent flows

We develop an adversarial-reinforcement learning scheme for microswimmers in statistically homogeneous and isotropic turbulent fluid flows, in both two and three dimensions. We show that this scheme allows microswimmers to find nontrivial paths, which enable them to reach a target on average in less time than a naïve microswimmer, which tries, at any instant of time and at a given position in space, to swim in the direction of the target. We use pseudospectral direct numerical simulations of the two- and three-dimensional (incompressible) Navier-Stokes equations to obtain the turbulent flows. We then introduce passive microswimmers that try to swim along a given direction in these flows; the microswimmers do not affect the flow, but they are advected by it. Two nondimensional control parameters play important roles in our learning scheme: (a) the ratio V[over ̃]_{s} of the microswimmer's bare velocity V_{s} and the root-mean-square (rms) velocity u_{rms} of the turbulent fluid and (b) the product B[over ̃] of the microswimmer-response time B and the rms vorticity ω_{rms} of the fluid. We show that the average time required for the microswimmers to reach the target, by using our adversarial-reinforcement learning scheme, eventually reduces below the average time taken by microswimmers that follow the naïve strategy.

Reverse engineering field-derived vertical distribution profiles to infer larval swimming behaviors

Biophysical models are well-used tools for predicting the dispersal of marine larvae. Larval behavior has been shown to influence dispersal, but how to incorporate behavior effectively within dispersal models remains a challenge. Mechanisms of behavior are often derived from laboratory-based studies and therefore, may not reflect behavior in situ. Here, using state-of-the-art models, we explore the movements that larvae must undertake to achieve the vertical distribution patterns observed in nature. Results suggest that behaviors are not consistent with those described under the tidally synchronized vertical migration (TVM) hypothesis. Instead, we show (i) a need for swimming speed and direction to vary over the tidal cycle and (ii) that, in some instances, larval swimming cannot explain observed vertical patterns. We argue that current methods of behavioral parameterization are limited in their capacity to replicate in situ observations of vertical distribution, which may cause dispersal error to propagate over time, due to advective differences over depth and demonstrate an alternative to laboratory-based behavioral parameterization that encompasses the range of environmental cues that may be acting on planktic organisms.

Pore-Scale Hydrodynamics in a Progressively Bioclogged Three-Dimensional Porous Medium: 3-D Particle Tracking Experiments and Stochastic Transport Modeling

Biofilms are ubiquitous bacterial communities that grow in various porous media including soils, trickling, and sand filters. In these environments, they play a central role in services ranging from degradation of pollutants to water purification. Biofilms dynamically change the pore structure of the medium through selective clogging of pores, a process known as bioclogging. This affects how solutes are transported and spread through the porous matrix, but the temporal changes to transport behavior during bioclogging are not well understood. To address this uncertainty, we experimentally study the hydrodynamic changes of a transparent 3-D porous medium as it experiences progressive bioclogging. Statistical analyses of the system's hydrodynamics at four time points of bioclogging (0, 24, 36, and 48 h in the exponential growth phase) reveal exponential increases in both average and variance of the flow velocity, as well as its correlation length. Measurements for spreading, as mean-squared displacements, are found to be non-Fickian and more intensely superdiffusive with progressive bioclogging, indicating the formation of preferential flow pathways and stagnation zones. A gamma distribution describes well the Lagrangian velocity distributions and provides parameters that quantify changes to the flow, which evolves from a parallel pore arrangement under unclogged conditions, toward a more serial arrangement with increasing clogging. Exponentially evolving hydrodynamic metrics agree with an exponential bacterial growth phase and are used to parameterize a correlated continuous time random walk model with a stochastic velocity relaxation. The model accurately reproduces transport observations and can be used to resolve transport behavior at intermediate time points within the exponential growth phase considered.

Zooplankton can actively adjust their motility to turbulent flow

Calanoid copepods are among the most abundant metazoans in the ocean and constitute a vital trophic link within marine food webs. They possess relatively narrow swimming capabilities, yet are capable of significant self-locomotion under strong hydrodynamic conditions. Here we provide evidence for an active adaptation that allows these small organisms to adjust their motility in response to background flow. We track simultaneously and in three dimensions the motion of flow tracers and planktonic copepods swimming freely at several intensities of quasi-homogeneous, isotropic turbulence. We show that copepods synchronize the frequency of their relocation jumps with the frequency of small-scale turbulence by performing frequent relocation jumps of low amplitude that seem unrelated to localized hydrodynamic signals. We develop a model of plankton motion in turbulence that shows excellent quantitative agreement with our measurements when turbulence is significant. We find that, compared with passive tracers, active motion enhances the diffusion of organisms at low turbulence intensity whereas it dampens diffusion at higher turbulence levels. The existence of frequent jumps in a motion that is otherwise dominated by turbulent transport allows for the possibility of active locomotion and hence to transition from being passively advected to being capable of controlling diffusion. This behavioral response provides zooplankton with the capability to retain the benefits of self-locomotion despite turbulence advection and may help these organisms to actively control their distribution in dynamic environments. Our study reveals an active adaptation that carries strong fitness advantages and provides a realistic model of plankton motion in turbulence.

Short-term exposure to gold nanoparticle suspension impairs swimming behavior in a widespread calanoid copepod

Calanoid copepods play an important role in the functioning of marine and brackish ecosystems. Information is scarce on the behavioral toxicity of engineered nanoparticles to these abundant planktonic organisms. We assessed the effects of short-term exposure to nonfunctionalized gold nanoparticles on the swimming behavior of the widespread estuarine copepod Eurytemora affinis. By means of three-dimensional particle tracking velocimetry, we reconstructed the trajectories of males, ovigerous and non-ovigerous females. We quantified changes in their swimming activity and in the kinematics and geometrical properties of their motion, three important descriptors of the motility patterns of zooplankters. In females, exposure to gold nanoparticles in suspension (11.4 μg L^-1) for 30 min caused depressed activity and lower velocity and acceleration, whereas the same exposure caused minimal effects in males. This response differs clearly from the hyperactive behavior that is commonly observed in zooplankters exposed to pollutants, and from the generally lower sensitivity of female copepods to toxicants. Accumulation of gold nanoparticles on the external appendages was not observed, precluding mechanical effects. Only very few nanoparticles appeared sporadically in the inner part of the gut in some samples, either as aggregates or as isolated nanoparticles, which does not suggest systemic toxicity resulting from pronounced ingestion. Hence, the precise mechanisms underlying the behavioral toxicity observed here remain to be elucidated. These results demonstrate that gold nanoparticles can induce marked behavioral alterations at very low concentration and short exposure duration. They illustrate the applicability of swimming behavior as a suitable and sensitive endpoint for investigating the toxicity of nanomaterials present in estuarine and marine environments. Changes in swimming behavior may impair the ability of planktonic copepods to interact with their environment and with other organisms, with possible impacts on population dynamics and community structure.

Microcosm experimental evidence that habitat orientation affects phytoplankton-zooplankton dynamics

Although spatial ecology has achieved a great success in the passing decades, the importance of habitat orientation has not been well studied, especially for its effects on prey-predator dynamics. Here, we examined the responses of zooplankton activity and grazing rate to habitat orientation and their consequences on the stability of phytoplankton-zooplankton system in a two-factor factorial experiment involving habitat orientation (three levels; small, medium, and large base area, respectively) and habitat size (64 ml and 512 ml) using two algal-grazer systems (Chlorella pyrenoidosa-Daphnia magna and C. pyrenoidosa- Moina micrura). In both systems, grazer density increased with increasing base area for a given chamber volume and with increasing chamber volume for a given orientation in the first 6 days, followed by a dramatic decrease, which corresponded to increasing the amplitude of density fluctuations in both zooplankton and phytoplankton species. Such an algal-grazer dynamics could be accounted for by the greater average swimming ability and grazing rate observed in large-based and large-volumed chambers. Our results demonstrate that habitat orientation affects the zooplankton behavior and population dynamics of both zooplankton and phytoplankton species, which further influences the stability of phytoplankton-zooplankton systems.

Flow Navigation by Smart Microswimmers via Reinforcement Learning

Smart active particles can acquire some limited knowledge of the fluid environment from simple mechanical cues and exert a control on their preferred steering direction. Their goal is to learn the best way to navigate by exploiting the underlying flow whenever possible. As an example, we focus our attention on smart gravitactic swimmers. These are active particles whose task is to reach the highest altitude within some time horizon, given the constraints enforced by fluid mechanics. By means of numerical experiments, we show that swimmers indeed learn nearly optimal strategies just by experience. A reinforcement learning algorithm allows particles to learn effective strategies even in difficult situations when, in the absence of control, they would end up being trapped by flow structures. These strategies are highly nontrivial and cannot be easily guessed in advance. This Letter illustrates the potential of reinforcement learning algorithms to model adaptive behavior in complex flows and paves the way towards the engineering of smart microswimmers that solve difficult navigation problems.

Effects of experimental long-term CO2 exposure on Daphnia magna (Straus 1820): From physiological effects to ecological consequences

The carbon capture and storage (CCS) technologies that were proposed to mitigate environmental problems arising from anthropogenic CO2 emissions, also have potential environmental risks. An eventual CCS leak might induce very low pH values in the aquatic system. Due to the lack of knowledge of long-term CO2 exposures with very low pH values, this study aims to know the effects and consequences of such a situation for zooplankton, using the Daphnia magna experimental model. A CO2 injection system was used to provide the experimental condition. A twenty-one days experiment with control and low pH treatment (pH = 7) replicates was carried out under light and temperature-controlled conditions. Survival, individual growth, RNA:DNA ratio, and neonates production were analysed during the aforementioned period. No differences on survival (except last day), individual growth and RNA:DNA ratio were observed between both control and low pH treatments. However, clear differences were detected in neonates production and, consequently, in population growth rates and secondary production. The observed differences could be related with an energy allocation strategy to ensure individual survival but would have ecological consequences affecting higher trophic levels.

Lagrangian model of copepod dynamics: Clustering by escape jumps in turbulence

Planktonic copepods are small crustaceans that have the ability to swim by quick powerful jumps. Such an aptness is used to escape from high shear regions, which may be caused either by flow perturbations, produced by a large predator (i.e., fish larvae), or by the inherent highly turbulent dynamics of the ocean. Through a combined experimental and numerical study, we investigate the impact of jumping behavior on the small-scale patchiness of copepods in a turbulent environment. Recorded velocity tracks of copepods displaying escape response jumps in still water are here used to define and tune a Lagrangian copepod (LC) model. The model is further employed to simulate the behavior of thousands of copepods in a fully developed hydrodynamic turbulent flow obtained by direct numerical simulation of the Navier-Stokes equations. First, we show that the LC velocity statistics is in qualitative agreement with available experimental observations of copepods in turbulence. Second, we quantify the clustering of LC, via the fractal dimension D_{2}. We show that D_{2} can be as low as ∼2.3 and that it critically depends on the shear-rate sensitivity of the proposed LC model, in particular it exhibits a minimum in a narrow range of shear-rate values. We further investigate the effect of jump intensity, jump orientation, and geometrical aspect ratio of the copepods on the small-scale spatial distribution. At last, possible ecological implications of the observed clustering on encounter rates and mating success are discussed.

Multifractal anisotropic swimming: the optimal foraging behaviour of grouper larvae

It was hypothesized that the Malabar grouper Ephinephelus malabaricus larvae have developed search patterns adapted to the distribution of their prey to maximise their net energy intake per unit time. Analysis of the swimming behaviour of E. malabaricus larvae in both the presence and absence of Artemia sp. nauplii is presented to test this hypothesis. A method derived from turbulence studies (the moment function of the displacements) was used to characterize the behaviour. The results revealed that larval swimming pattern was multifractal (intermittent and long-range-correlated) and isotropic (i.e. uniform in all directions) in the presence of prey, but multifractal and anisotropic (i.e. more frequent long displacement on the vertical axis) in the absence of prey. It is suggested that the search behaviour observed in the absence of prey is an adaptive response to prey distribution pattern, which is often characterised by multifractality and anisotropy (i.e. larger patches on the horizontal axes). In the presence of prey, E. malabaricus shifted to intensive search behaviour. Other possible contributors to the observed patterns are discussed. It is concluded that multifractality and anisotropy of swimming patterns observed in the experiment are mainly explained in an optimal foraging theory framework.

Lipid nanocapsules for behavioural testing in aquatic toxicology: Time-response of Eurytemora affinis to environmental concentrations of PAHs and PCB

The increasing interest for behavioural investigations in aquatic toxicology has heightened the need for developing tools that allow realistic exposure conditions and provide robust quantitative data. Calanoid copepods dominate the zooplankton community in marine and brackish environments. These small organisms have emerged as attractive models because of the sensitivity of their behaviour to important environmental parameters and the significance of self-induced motion in their ecology. Estuarine copepods are particularly relevant in this context because of their incessant exposure to high levels of pollution. We used lipid nanocapsules to deliver sub-lethal concentrations of PAHs (pyrene, phenanthrene and fluoranthene) and PCB 153 into the digestive track of males and females Eurytemora affinis. This novel approach enabled us to achieve both contact and trophic exposure without using phytoplankton, and to expose copepods to small hydrophobic molecules without using organic solvent. We reconstructed the motion of many copepods swimming simultaneously by means of three-dimensional particle tracking velocimetry. We quantified the combined effects of contact and trophic toxicity by comparing the kinematic and diffusive properties of their motion immediately and after 3h and 24h of exposure. Despite the lack of toxicity of their excipients, both empty and loaded capsules increased swimming activity and velocity immediately after exposure. Laser microscopy imaging shows adhesion of nanocapsules on the exoskeleton of the animals, suggesting contact toxicity. The behavioural response resembles an escape reaction allowing copepods to escape stressful conditions. The contact toxicity of empty capsules and pollutants appeared to be additive and nanocapsules loaded with PCB caused the greatest effects. We observed a progressive accumulation of capsules in the digestive track of the animals after 3h and 24h of exposure, which suggests an increasing contribution of systemic toxicity. Nanocapsules filled with PAHs caused a smaller response compared to empty capsules, which we attribute to the narcotic properties of these toxicants. The sharp decrease in velocity after 24h of exposure to capsules loaded with PCB suggests physiological incapacitation following systemic toxicity. Clear differences are visible between genders in their response to empty and loaded capsules, for all exposure durations. Females appear to be less sensitive than males, suggesting different tolerance to stress conditions. Our results confirm the feasibility of using lipid nanocapsules to identify pollutant-induced behavioural alteration in the plankton. They also add new insights into the contact and systemic toxicity of common pollutants. We expect that our results will assist and evoke further research to develop suitable nanocarrier systems for behavioural testing.

Characterization of intermittency in zooplankton behaviour in turbulence

We consider Lagrangian velocity differences of zooplankters swimming in still water and in turbulence. Using cumulants, we quantify the intermittency properties of their motion recorded using three-dimensional particle tracking velocimetry. Copepods swimming in still water display an intermittent behaviour characterized by a high probability of small velocity increments, and by stretched exponential tails. Low values arise from their steady cruising behaviour while heavy tails result from frequent relocation jumps. In turbulence, we show that at short time scales, the intermittency signature of active copepods clearly differs from that of the underlying flow, and reflects the frequent relocation jumps displayed by these small animals. Despite these differences, we show that copepods swimming in still and turbulent flow belong to the same intermittency class that can be modelled by a log-stable model with non-analytical cumulant generating function. Intermittency in swimming behaviour and relocation jumps may enable copepods to display oriented, collective motion under strong hydrodynamic conditions and thus, may contribute to the formation of zooplankton patches in energetic environments.