Probabilistic models of individual and collective animal behavior

Recent developments in automated tracking allow uninterrupted, high-resolution recording of animal trajectories, sometimes coupled with the identification of stereotyped changes of body pose or other behaviors of interest. Analysis and interpretation of such data represents a challenge: the timing of animal behaviors may be stochastic and modulated by kinematic variables, by the interaction with the environment or with the conspecifics within the animal group, and dependent on internal cognitive or behavioral state of the individual. Existing models for collective motion typically fail to incorporate the discrete, stochastic, and internal-state-dependent aspects of behavior, while models focusing on individual animal behavior typically ignore the spatial aspects of the problem. Here we propose a probabilistic modeling framework to address this gap. Each animal can switch stochastically between different behavioral states, with each state resulting in a possibly different law of motion through space. Switching rates for behavioral transitions can depend in a very general way, which we seek to identify from data, on the effects of the environment as well as the interaction between the animals. We represent the switching dynamics as a Generalized Linear Model and show that: (i) forward simulation of multiple interacting animals is possible using a variant of the Gillespie's Stochastic Simulation Algorithm; (ii) formulated properly, the maximum likelihood inference of switching rate functions is tractably solvable by gradient descent; (iii) model selection can be used to identify factors that modulate behavioral state switching and to appropriately adjust model complexity to data. To illustrate our framework, we apply it to two synthetic models of animal motion and to real zebrafish tracking data.Comment: 26 pages, 11 figure

The influences of basic physical properties of clayey silt and silty sand on its laboratory electrical resistivity value in loose and dense conditions

Non-destructive test which refers to electrical resistivity method is recently popular in engineering, environmental, archaeological and mining studies. Based on the previous studies, the results on electrical resistivity interpretation were often debated due to lack of clarification and evidences in quantitative perspective. Traditionally, most of the previous result interpretations were depending on qualitative point of view which is risky to produce unreliable outcomes. In order to minimise those problems, this study has performed a laboratory experiment on soil box electrical resistivity test which was supported by an additional basic physical properties of soil test like particle size distribution test (d), moisture content test (w), density test (ρbulk) and Atterberg limit test (LL, PL and PI). The test was performed to establish a series of electrical resistivity value (ERV) with different quantity of water content for clayey silt and silty sand in loose and dense condition. Apparently, the soil resistivity value was different under loose (L) and dense (C) conditions with moisture content and density variations (silty SAND = ERVLoose: 600 - 7300 Ωm & ERVDense: 490 - 7900 Ωm while Clayey SILT = ERVLoose: 13 - 7700 Ωm & ERVDense: 14 - 8400 Ωm) due to several factors. Moreover, correlation of moisture content (w) and density (ρbulk) due to the ERV was established as follows; Silty SAND: w(L) = 638.8ρ-0.418, w(D) = 1397.1ρ-0.574, ρBulk(L) = 2.6188e-6E-05ρ, ρBulk(D) = 4.099ρ-0.07 while Clayey SILT: w(L) = 109.98ρ-0.268, w(D) = 121.88ρ-0.363, ρBulk(L) = -0.111ln(ρ) + 1.7605, ρBulk(D) = 2.5991ρ-0.037 with determination coefficients, R2 that varied from 0.5643 – 0.8927. This study was successfully demonstrated that the consistency of ERV was greatly influenced by the variation of soil basic physical properties (d, w, ρBulk, LL, PL and PI). Finally, the reliability of the ERV result interpretation can be enhanced due to its ability to produce a meaningful outcome based on supported data from basic geotechnical properties

Numerical simulation of water flow around a rigid fishing net

This paper is devoted to the simulation of the flow around and inside a rigid axisymmetric net. We describe first how experimental data have been obtained. We show in detail the modelization. The model is based on a Reynolds Averaged Navier-Stokes turbulence model penalized by a term based on the Brinkman law. At the out-boundary of the computational box, we have used a "ghost" boundary condition. We show that the corresponding variational problem has a solution. Then the numerical scheme is given and the paper finishes with numerical simulations compared with the experimental data.Comment: 39 page

Informative and misinformative interactions in a school of fish

It is generally accepted that, when moving in groups, animals process information to coordinate their motion. Recent studies have begun to apply rigorous methods based on Information Theory to quantify such distributed computation. Following this perspective, we use transfer entropy to quantify dynamic information flows locally in space and time across a school of fish during directional changes around a circular tank, i.e. U-turns. This analysis reveals peaks in information flows during collective U-turns and identifies two different flows: an informative flow (positive transfer entropy) based on fish that have already turned about fish that are turning, and a misinformative flow (negative transfer entropy) based on fish that have not turned yet about fish that are turning. We also reveal that the information flows are related to relative position and alignment between fish, and identify spatial patterns of information and misinformation cascades. This study offers several methodological contributions and we expect further application of these methodologies to reveal intricacies of self-organisation in other animal groups and active matter in general

Modelling and experimental investigation of carangiform locomotion for control

We propose a model for planar carangiform swimming based on conservative equations for the interaction of a rigid body and an incompressible fluid. We account for the generation of thrust due to vortex shedding through controlled coupling terms. We investigate the correct form of this coupling experimentally with a robotic propulsor, comparing its observed behavior to that predicted by unsteady hydrodynamics. Our analysis of thrust generation by an oscillating hydrofoil allows us to characterize and evaluate certain families of gaits. Our final swimming model takes the form of a control-affine nonlinear system

Anti-androgens act jointly in suppressing spiggin concentrations in androgen-primed female three-spined sticklebacks - Prediction of combined effects by concentration addition

This is the post-print version of the final paper published in Aquatic Toxicology. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Increasing attention is being directed at the role played by anti-androgenic chemicals in endocrine disruption of wildlife within the aquatic environment. The co-occurrence of multiple contaminants with anti-androgenic activity highlights a need for the predictive assessment of combined effects, but information about anti-androgen mixture effects on wildlife is lacking. This study evaluated the suitability of the androgenised female stickleback screen (AFSS), in which inhibition of androgen-induced spiggin production provides a quantitative assessment of anti-androgenic activity, for predicting the effect of a four component mixture of anti-androgens. The anti-androgenic activity of four known anti-androgens (vinclozolin, fenitrothion, flutamide, linuron) was evaluated from individual concentration-response data and used to design a mixture containing each chemical at equipotent concentrations. Across a 100-fold concentration range, a concentration addition approach was used to predict the response of fish to the mixture. Two studies were conducted independently at each of two laboratories. By using a novel method to adjust for differences between nominal and measured concentrations, good agreement was obtained between the actual outcome of the mixture exposure and the predicted outcome. This demonstrated for the first time that androgen receptor antagonists act in concert in an additive fashion in fish and that existing mixture methodology is effective in predicting the outcome, based on concentration-response data for individual chemicals. The sensitivity range of the AFSS assay lies within the range of anti-androgenicity reported in rivers across many locations internationally. The approach taken in our study lays the foundations for understanding how androgen receptor antagonists work together in fish and is essential in informing risk assessment methods for complex anti-androgenic mixtures in the aquatic environment.European Commission and Natural Environment Research Council