Journal articles: 'Animal behaviour modelling'

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Sumpter, David J. T., Richard P. Mann, and Andrea Perna. "The modelling cycle for collective animal behaviour." Interface Focus 2, no. 6 (August 15, 2012): 764–73. http://dx.doi.org/10.1098/rsfs.2012.0031.

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Collective animal behaviour is the study of how interactions between individuals produce group level patterns, and why these interactions have evolved. This study has proved itself uniquely interdisciplinary, involving physicists, mathematicians, engineers as well as biologists. Almost all experimental work in this area is related directly or indirectly to mathematical models, with regular movement back and forth between models, experimental data and statistical fitting. In this paper, we describe how the modelling cycle works in the study of collective animal behaviour. We classify studies as addressing questions at different levels or linking different levels, i.e. as local, local to global, global to local or global. We also describe three distinct approaches—theory-driven, data-driven and model selection—to these questions. We show, with reference to our own research on species across different taxa, how we move between these different levels of description and how these various approaches can be applied to link levels together.

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Matetić, Maja, Slobodan Ribarić, and Ivo Ipšić. "Qualitative Modelling and Analysis of Animal Behaviour." Applied Intelligence 21, no. 1 (July 2004): 25–44. http://dx.doi.org/10.1023/b:apin.0000027765.12621.6f.

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Mäekivi, Nelly. "Modelling Ex Situ Animal Behaviour and Communication." Biosemiotics 9, no. 2 (May 10, 2016): 207–26. http://dx.doi.org/10.1007/s12304-016-9264-5.

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Smouse, Peter E., Stefano Focardi, Paul R. Moorcroft, John G. Kie, James D. Forester, and Juan M. Morales. "Stochastic modelling of animal movement." Philosophical Transactions of the Royal Society B: Biological Sciences 365, no. 1550 (July 27, 2010): 2201–11. http://dx.doi.org/10.1098/rstb.2010.0078.

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Modern animal movement modelling derives from two traditions. Lagrangian models, based on random walk behaviour, are useful for multi-step trajectories of single animals. Continuous Eulerian models describe expected behaviour, averaged over stochastic realizations, and are usefully applied to ensembles of individuals. We illustrate three modern research arenas. (i) Models of home-range formation describe the process of an animal ‘settling down’, accomplished by including one or more focal points that attract the animal's movements. (ii) Memory-based models are used to predict how accumulated experience translates into biased movement choices, employing reinforced random walk behaviour, with previous visitation increasing or decreasing the probability of repetition. (iii) Lévy movement involves a step-length distribution that is over-dispersed, relative to standard probability distributions, and adaptive in exploring new environments or searching for rare targets. Each of these modelling arenas implies more detail in the movement pattern than general models of movement can accommodate, but realistic empiric evaluation of their predictions requires dense locational data, both in time and space, only available with modern GPS telemetry.

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Ravignani, Andrea, and Koen de Reus. "Modelling Animal Interactive Rhythms in Communication." Evolutionary Bioinformatics 15 (January 2019): 117693431882355. http://dx.doi.org/10.1177/1176934318823558.

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Time is one crucial dimension conveying information in animal communication. Evolution has shaped animals’ nervous systems to produce signals with temporal properties fitting their socio-ecological niches. Many quantitative models of mechanisms underlying rhythmic behaviour exist, spanning insects, crustaceans, birds, amphibians, and mammals. However, these computational and mathematical models are often presented in isolation. Here, we provide an overview of the main mathematical models employed in the study of animal rhythmic communication among conspecifics. After presenting basic definitions and mathematical formalisms, we discuss each individual model. These computational models are then compared using simulated data to uncover similarities and key differences in the underlying mechanisms found across species. Our review of the empirical literature is admittedly limited. We stress the need of using comparative computer simulations – both before and after animal experiments – to better understand animal timing in interaction. We hope this article will serve as a potential first step towards a common computational framework to describe temporal interactions in animals, including humans.

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Taylor, R. A. J., Marc Mangel, and Colin W. Clark. "Dynamic Modelling in Behaviour Ecology." Journal of Animal Ecology 59, no. 3 (October 1990): 1200. http://dx.doi.org/10.2307/5050.

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Ruxton, Graeme D., John D. Armstrong, and Stuart Humphries. "Modelling territorial behaviour of animals in variable environments." Animal Behaviour 58, no. 1 (July 1999): 113–20. http://dx.doi.org/10.1006/anbe.1999.1114.

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Clark, Colin W. "Modelling the behaviour of fishers and fishes." ICES Journal of Marine Science 75, no. 3 (December 9, 2017): 932–40. http://dx.doi.org/10.1093/icesjms/fsx212.

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Abstract I describe my personal evolution as a modeller of behaviour, both human and (non-human) animal behaviour, using dynamic state-variable models. At first I worked in renewable resource Economics, especially the economics of marine fisheries where I collaborated extensively with Gordon R. Munro. Subsequently, in collaboration with Marc Mangel (and many field biologists) I worked in Behavioural Ecology. Mathematical models have played a major role in both of these subjects, but until recently mostly static models were used, on the grounds that dynamic (not to mention stochastic) models were too difficult to work with. I express the hope that our use of relatively simple (but not too simple) dynamic models has established the fact that such models can be extremely helpful, perhaps essential, in understanding many aspects of behaviour.

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Browne, K. A., M. N. Tamburri, and R. K. Zimmer-Faust. "Modelling quantitative structure-activity relationships between animal behaviour and environmental signal molecules." Journal of Experimental Biology 201, no. 2 (January 15, 1998): 245–58. http://dx.doi.org/10.1242/jeb.201.2.245.

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Quantitative structure-activity relationships (QSARs) between the physicochemical properties of environmental signal molecules and animal behaviour have been determined. Past work has shown that oyster and barnacle larval settlement and mud crab abdominal pumping (for larval dispersal) are stimulated by small peptide cues. In all the peptides examined that were active at ecologically relevant concentrations, arginine or lysine was found at the carboxy terminus, but the amino acids found at preceding positions were highly variable. We used the multivariate partial least squares algorithm to relate composite properties for the hydrophilicity, size and charge of each amino acid and the sequence position to oyster, barnacle and crab behaviour patterns. From the information in these QSAR models, the apparent variability in amino acid sequences eliciting behavioural responses was explained in each case, and more potent peptide analogues are hypothesized on the basis of untested amino acid sequences. Remarkably, these peptide signals are all structurally related to the carboxy-terminal sequence of mammalian C5a anaphylatoxin, a potent white blood cell chemoattractant. Even more striking is the fact that these different animal species should rely on apparently similar environmental signal molecules when residing within a common habitat (southeastern US estuaries). Through the physicochemical properties of amino acids, the current QSAR models clearly differentiate between the optimal sequences for eliciting oyster, barnacle and mud crab behaviour. Thus, QSARs provide a novel and powerful method not only for relating the physicochemical properties of molecules to animal behaviour but also for differentiating responses to chemicals by individuals of different species.

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Larson, Stephen D., Padraig Gleeson, and André E. X. Brown. "Connectome to behaviour: modelling Caenorhabditis elegans at cellular resolution." Philosophical Transactions of the Royal Society B: Biological Sciences 373, no. 1758 (September 10, 2018): 20170366. http://dx.doi.org/10.1098/rstb.2017.0366.

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It has been 30 years since the ‘mind of the worm’ was published in Philosophical Transactions B (White et al . 1986 Phil. Trans. R. Soc. Lond. B 314 , 1–340). Predicting Caenorhabditis elegans ' behaviour from its wiring diagram has been an enduring challenge since then. This special theme issue of Philosophical Transactions B combines research from neuroscientists, physicists, mathematicians and engineers to discuss advances in neural activity imaging, behaviour quantification and multiscale simulations, and how they are bringing the goal of whole-animal modelling at cellular resolution within reach. This article is part of a discussion meeting issue ‘Connectome to behaviour: modelling C. elegans at cellular resolution’.

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Bauer, S. A., D. L. Pearl, K. E. Leslie, J. Fournier, and P. V. Turner. "Causes of obesity in captive cynomolgus macaques: influence of body condition, social and management factors on behaviour around feeding." Laboratory Animals 46, no. 3 (July 2012): 193–99. http://dx.doi.org/10.1258/la.2012.011120.

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Similar to other primate species, captive cynomolgus macaques ( Macaca fascicularis) are prone to becoming overweight. The relationship between body condition and feeding behaviour in group-housed animals has not been reported. This study evaluated the effect of daily feeding routines on behaviour patterns in cynomolgus macaques to determine whether overweight macaques displayed different behaviours and activity levels. In this prospective observational study, 16 macaques ( m = 4, f = 12) from four separate troops ( n = 4 per troop) were selected from a colony of 165 animals. Observational data were collected over six months during morning and afternoon feedings by scan sampling. Behaviours of interest included foraging, eating, aggressive and positive social interactions, inactivity and physical activities. Multivariable mixed logistic regression modelling was used for data analysis. Results indicated that overweight animals were more likely to be inactive, dominant animals had increased probabilities of eating compared with non-dominants, and aggressive behaviours were more likely to occur in the morning and before feeding, suggesting feeding anticipation. Positive social interaction before feeding was seen and may be a strategy used to avoid aggressive encounters around food resources. Individual animal caregivers had an unintentional impact on behaviour, as decreased eating and an increase in inactivity were noted when certain individuals fed animals. These findings illustrate the complexities of feeding group-housed cynomolgus macaques to avoid overweight body condition. Feeding routines may require more care and attention to distribute food in a way that ensures equitable food intake among troop animals, while not disturbing group cohesion.

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del Mar Delgado, Maria, Maria Miranda, Silvia J. Alvarez, Eliezer Gurarie, William F. Fagan, Vincenzo Penteriani, Agustina di Virgilio, and Juan Manuel Morales. "The importance of individual variation in the dynamics of animal collective movements." Philosophical Transactions of the Royal Society B: Biological Sciences 373, no. 1746 (March 26, 2018): 20170008. http://dx.doi.org/10.1098/rstb.2017.0008.

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Animal collective movements are a key example of a system that links two clearly defined levels of organization: the individual and the group. Most models investigating collective movements have generated coherent collective behaviours without the inclusion of individual variability. However, new individual-based models, together with emerging empirical information, emphasize that within-group heterogeneity may strongly influence collective movement behaviour. Here we (i) review the empirical evidence for individual variation in animal collective movements, (ii) explore how theoretical investigations have represented individual heterogeneity when modelling collective movements and (iii) present a model to show how within-group heterogeneity influences the collective properties of a group. Our review underscores the need to consider variability at the level of the individual to improve our understanding of how individual decision rules lead to emergent movement patterns, and also to yield better quantitative predictions of collective behaviour. This article is part of the theme issue ‘Collective movement ecology’.

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Sridhar, Vivek Hari, Dominique G. Roche, and Simon Gingins. "Tracktor: Image‐based automated tracking of animal movement and behaviour." Methods in Ecology and Evolution 10, no. 6 (March 5, 2019): 815–20. http://dx.doi.org/10.1111/2041-210x.13166.

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Chakravarty, Pritish, Gabriele Cozzi, Arpat Ozgul, and Kamiar Aminian. "A novel biomechanical approach for animal behaviour recognition using accelerometers." Methods in Ecology and Evolution 10, no. 6 (April 2, 2019): 802–14. http://dx.doi.org/10.1111/2041-210x.13172.

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Asher, Lucy, Lisa M. Collins, Angel Ortiz-Pelaez, Julian A. Drewe, Christine J. Nicol, and Dirk U. Pfeiffer. "Recent advances in the analysis of behavioural organization and interpretation as indicators of animal welfare." Journal of The Royal Society Interface 6, no. 41 (September 9, 2009): 1103–19. http://dx.doi.org/10.1098/rsif.2009.0221.

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While the incorporation of mathematical and engineering methods has greatly advanced in other areas of the life sciences, they have been under-utilized in the field of animal welfare. Exceptions are beginning to emerge and share a common motivation to quantify ‘hidden’ aspects in the structure of the behaviour of an individual, or group of animals. Such analyses have the potential to quantify behavioural markers of pain and stress and quantify abnormal behaviour objectively. This review seeks to explore the scope of such analytical methods as behavioural indicators of welfare. We outline four classes of analyses that can be used to quantify aspects of behavioural organization. The underlying principles, possible applications and limitations are described for: fractal analysis, temporal methods, social network analysis, and agent-based modelling and simulation. We hope to encourage further application of analyses of behavioural organization by highlighting potential applications in the assessment of animal welfare, and increasing awareness of the scope for the development of new mathematical methods in this area.

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Smith, Amy, Sarah C. Avitabile, and Steven W. J. Leonard. "Less fuel for the fire: malleefowl (Leipoa ocellata) nesting activity affects fuel loads and fire behaviour." Wildlife Research 43, no. 8 (2016): 640. http://dx.doi.org/10.1071/wr16127.

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Context Fire is an important driver of species distributions globally. At the same time, biota also influence fire regimes. Animal activities that modify fuel characteristics may influence fire regimes and hence ecosystem function. However, apart from herbivory, animal effects on fuels and fire behaviour have rarely been studied. Aims We examined the effect of nest building by malleefowl (Leipoa ocellata) on litter fuel loads and fire behaviour in the fire-prone, semiarid mallee ecosystem of south-eastern Australia. Malleefowl nests consist of mounds constructed by raking large amounts of leaf litter from the surrounding area. Mound-building activity is likely to affect fuel loads and potentially affect fire behaviour in this environment. Methods Litter cover and mass were compared between paired mound and non-mound sites. Fire behaviour modelling was used to determine whether differences in fuel load were likely to translate into differences in fire behaviour. Additionally, in an area recently burnt by wildfire, the minimum diameter of burnt stems was compared between mound and non-mound sites to determine the effects of malleefowl activity on fire intensity. Key results Malleefowl nesting activity reduced litter fuel loads around mounds. Fire behaviour modelling and post-fire minimum stem diameter measurements showed this led to reduced fire intensity around mounds, even under extreme fire weather conditions. Conclusions The likelihood and intensity of fire is reduced around active malleefowl mounds. Malleefowl nesting contributes to more heterogeneous burn patterns in mallee vegetation. This in turn may contribute to the formation of fire refuges. Implications Few studies have examined the effects of animal activities on fire. This study demonstrates that non-trophic interactions of fauna with fuels may influence fire regimes. Species that reduce or disrupt the continuity or connectivity of fuels could have similar effects to malleefowl in fire-prone regions. Further examination of the interactions of animals and fire regimes will contribute to a better understanding and conservation management of fire-prone ecosystems.

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van Beek, Johannes H. G. M., Anne-Christin Hauschild, Hannes Hettling, and Thomas W. Binsl. "Robust modelling, measurement and analysis of human and animal metabolic systems." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367, no. 1895 (May 28, 2009): 1971–92. http://dx.doi.org/10.1098/rsta.2008.0305.

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Modelling human and animal metabolism is impeded by the lack of accurate quantitative parameters and the large number of biochemical reactions. This problem may be tackled by: (i) study of modules of the network independently; (ii) ensemble simulations to explore many plausible parameter combinations; (iii) analysis of ‘sloppy’ parameter behaviour, revealing interdependent parameter combinations with little influence; (iv) multiscale analysis that combines molecular and whole network data; and (v) measuring metabolic flux (rate of flow) in vivo via stable isotope labelling. For the latter method, carbon transition networks were modelled with systems of ordinary differential equations, but we show that coloured Petri nets provide a more intuitive graphical approach. Analysis of parameter sensitivities shows that only a few parameter combinations have a large effect on predictions. Model analysis of high-energy phosphate transport indicates that membrane permeability, inaccurately known at the organellar level, can be well determined from whole-organ responses. Ensemble simulations that take into account the imprecision of measured molecular parameters contradict the popular hypothesis that high-energy phosphate transport in heart muscle is mostly by phosphocreatine. Combining modular, multiscale, ensemble and sloppy modelling approaches with in vivo flux measurements may prove indispensable for the modelling of the large human metabolic system.

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Dingemanse, Niels J., and Max Wolf. "Recent models for adaptive personality differences: a review." Philosophical Transactions of the Royal Society B: Biological Sciences 365, no. 1560 (December 27, 2010): 3947–58. http://dx.doi.org/10.1098/rstb.2010.0221.

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In this paper we review recent models that provide adaptive explanations for animal personalities: individual differences in behaviour (or suites of correlated behaviours) that are consistent over time or contexts. We start by briefly discussing patterns of variation in behaviour that have been documented in natural populations. In the main part of the paper we discuss models for personality differences that (i) explain animal personalities as adaptive behavioural responses to differences in state, (ii) investigate how feedbacks between state and behaviour can stabilize initial differences among individuals and (iii) provide adaptive explanations for animal personalities that are not based on state differences. Throughout, we focus on two basic questions. First, what is the basic conceptual idea underlying the model? Second, what are the key assumptions and predictions of the model? We conclude by discussing empirical features of personalities that have not yet been addressed by formal modelling. While this paper is primarily intended to guide empiricists through current adaptive theory, thereby stimulating empirical tests of these models, we hope it also inspires theoreticians to address aspects of personalities that have received little attention up to now.

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Budaev, Sergey, Tore S. Kristiansen, Jarl Giske, and Sigrunn Eliassen. "Computational animal welfare: towards cognitive architecture models of animal sentience, emotion and wellbeing." Royal Society Open Science 7, no. 12 (December 2020): 201886. http://dx.doi.org/10.1098/rsos.201886.

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To understand animal wellbeing, we need to consider subjective phenomena and sentience. This is challenging, since these properties are private and cannot be observed directly. Certain motivations, emotions and related internal states can be inferred in animals through experiments that involve choice, learning, generalization and decision-making. Yet, even though there is significant progress in elucidating the neurobiology of human consciousness, animal consciousness is still a mystery. We propose that computational animal welfare science emerges at the intersection of animal behaviour, welfare and computational cognition. By using ideas from cognitive science, we develop a functional and generic definition of subjective phenomena as any process or state of the organism that exists from the first-person perspective and cannot be isolated from the animal subject. We then outline a general cognitive architecture to model simple forms of subjective processes and sentience. This includes evolutionary adaptation which contains top-down attention modulation, predictive processing and subjective simulation by re-entrant (recursive) computations. Thereafter, we show how this approach uses major characteristics of the subjective experience: elementary self-awareness, global workspace and qualia with unity and continuity. This provides a formal framework for process-based modelling of animal needs, subjective states, sentience and wellbeing.

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Davison, C., J. M. Bowen, C. Michie, J. A. Rooke, N. Jonsson, I. Andonovic, C. Tachtatzis, M. Gilroy, and C.-A. Duthie. "Predicting feed intake using modelling based on feeding behaviour in finishing beef steers." Animal 15, no. 7 (July 2021): 100231. http://dx.doi.org/10.1016/j.animal.2021.100231.

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Dalziel, Benjamin D., Mael Le Corre, Steeve D. Côté, and Stephen P. Ellner. "Detecting collective behaviour in animal relocation data, with application to migrating caribou." Methods in Ecology and Evolution 7, no. 1 (August 22, 2015): 30–41. http://dx.doi.org/10.1111/2041-210x.12437.

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Silva, Manuel F., J. A. Tenreiro Machado, and António M. Lopes. "Modelling and simulation of artificial locomotion systems." Robotica 23, no. 5 (August 23, 2005): 595–606. http://dx.doi.org/10.1017/s0263574704001195.

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This paper describes a simulation model for a multi-legged locomotion system with joints at the legs having viscous friction, flexibility and backlash. For that objective the robot prescribed motion is characterized in terms of several locomotion variables. Moreover, the robot body is divided into several segments in order to emulate the behaviour of an animal spine. The foot-ground interaction is modelled through a non-linear spring-dashpot system whose parameters are extracted from the studies on soil mechanics. To conclude, the performance of the developed simulation model is evaluated through a set of experiments while the robot leg joints are controlled using fractional order algorithms.

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Bernardi, Sara, and Marco Scianna. "An agent-based approach for modelling collective dynamics in animal groups distinguishing individual speed and orientation." Philosophical Transactions of the Royal Society B: Biological Sciences 375, no. 1807 (July 27, 2020): 20190383. http://dx.doi.org/10.1098/rstb.2019.0383.

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Collective dynamics in animal groups is a challenging theme for the modelling community, being treated with a wide range of approaches. This topic is here tackled by a discrete model. Entering in more details, each agent, represented by a material point, is assumed to move following a first-order Newtonian law, which distinguishes speed and orientation. In particular, the latter results from the balance of a given set of behavioural stimuli, each of them defined by a direction and a weight, that quantifies its relative importance. A constraint on the sum of the weights then avoids implausible simultaneous maximization/minimization of all movement traits. Our framework is based on a minimal set of rules and parameters and is able to capture and classify a number of collective group dynamics emerging from different individual preferred behaviour, which possibly includes attractive, repulsive and alignment stimuli. In the case of a system of animals subjected only to the first two behavioural inputs, we also show how analytical arguments allow us to a priori relate the equilibrium interparticle spacing to critical model coefficients. Our approach is then extended to account for the presence of predators with different hunting strategies, which impact on the behaviour of a prey population. Hints for model refinement and applications are finally given in the conclusive part of the article. This article is part of the theme issue ‘Multi-scale analysis and modelling of collective migration in biological systems’.

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Everitt, Barry J., Chiara Giuliano, and David Belin. "Addictive behaviour in experimental animals: prospects for translation." Philosophical Transactions of the Royal Society B: Biological Sciences 373, no. 1742 (January 29, 2018): 20170027. http://dx.doi.org/10.1098/rstb.2017.0027.

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Since the introduction of intravenous drug self-administration methodology over 50 years ago, experimental investigation of addictive behaviour has delivered an enormous body of data on the neural, psychological and molecular mechanisms of drug reward and reinforcement and the neuroadaptations to chronic use. Whether or not these behavioural and molecular studies are viewed as modelling the underpinnings of addiction in humans, the discussion presented here highlights two areas—the impact of drug-associated conditioned stimuli—or drug cues—on drug seeking and relapse, and compulsive cocaine seeking. The degree to which these findings translate to the clinical state of addiction is considered in terms of the underlying neural circuitry and also the ways in which this understanding has helped develop new treatments for addiction. The psychological and neural mechanisms underlying drug memory reconsolidation and extinction established in animal experiments show particular promise in delivering new treatments for relapse prevention to the clinic.This article is part of a discussion meeting issue ‘Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists'.

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Laan, Andres, Marta Iglesias-Julios, and Gonzalo G. de Polavieja. "Zebrafish aggression on the sub-second time scale: evidence for mutual motor coordination and multi-functional attack manoeuvres." Royal Society Open Science 5, no. 8 (August 2018): 180679. http://dx.doi.org/10.1098/rsos.180679.

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Most animals fight by repeating complex stereotypic behaviours, yet the internal structure of these behaviours has rarely been dissected in detail. We characterized the internal structure of fighting behaviours by developing a machine learning pipeline that measures and classifies the behaviour of individual unmarked animals on a sub-second time scale. This allowed us to quantify several previously hidden features of zebrafish fighting strategies. We found strong correlations between the velocity of the attacker and the defender, indicating a dynamic matching of approach and avoidance efforts. While velocity matching was ubiquitous, the spatial dynamics of attacks showed phase-specific differences. Contest-phase attacks were characterized by a paradoxical sideways attraction of the retreating animal towards the attacker, suggesting that the defender combines avoidance manoeuvres with display-like manoeuvres. Post-resolution attacks lacked display-like features and the defender was avoidance focused. From the perspective of the winner, game-theory modelling further suggested that highly energetically costly post-resolution attacks occurred because the winner was trying to increase its relative dominance over the loser. Overall, the rich structure of zebrafish motor coordination during fighting indicates a greater complexity and layering of strategies than has previously been recognized.

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Nuppenau, E. A. "Farm Behaviour and Incentives for Animal Welfare: On Stimulating Interest in Cow Life Expectancy by Industry Attentiveness." Journal of Food Research 7, no. 4 (May 23, 2018): 55. http://dx.doi.org/10.5539/jfr.v7n4p55.

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This contribution deals primarily with a new concept derived from institutional economics, to improve animal health (eventually welfare, depending on the use of synonyms and actually measured as cow life expectancy, i.e. in figures: number of lactations). Based on consumer willingness to pay, it investigates a potential collaboration between a dairy industry whose aim is to diversify products and some farmers whose intention is to request compensation for a change of practices. For finding practical attributes for health, we have a focus on practices promoting numbers of lactations, currently at a low level in conventional farming. We distinguish farm types by strategies asking why most farms are primarily aiming at maximal efficiency (feeding concentrates for high milk yields and having no grazing). Vice versa: this has raised public concern because (with big herds, high milk yields and minimal lactations) farmers seem to stress animal welfare. We assume WTP exists for an improvement in animal health (though diffuse so far). I.e. on the one hand as a symptom of crisis, successes for gestation are low (almost half compared to those of farms “caring” for animals). On the other hand better practice can be financed if targeted by WTP. Further assumptions are: even the industry may admit problems with animal health, and within consumers’ and citizens’ circles, there is an increasing awareness and that WTP (finance) may enable private solutions. WTP could be used for those farmers doing better on animal welfare; but so far, markets have failed. We are confronted with different strategic behaviour of farmers (by sectors) whose commencing points (as observation and deliberation) must be a willingness to change practices. A starting point should be insight into behaviour(al) change and willingness to increase animal health (gestation), yet based on compensation. Compensation can be used to get more farmers interested in animal health, but it must be differentiated according to actions for improvement. In an institutional economics analysis of animal welfare, we will work out a concept of optimal compensation, preferably achieving cooperation between a dairy industry and willing farmers to lodge payments received from consumers. It means working on participation of actors in product diversification (milk identified by different sources) and transfer of money to those farmers who are actually working for animal health concerns. The paper further addresses selection of farms which manage to achieve set health goals and assure confirmation of achievements in increasing health. The goal is to increase the number of lactations. By utilizing contracted numbers of lactations as the basis for modelling a quantitative criterion which adequately shall reflect aspects of working for animal health (such as feeding practices, grazing, better husbandry (space and straw), caring (stress recovery), etc., is worked out and animal welfare shall improve.

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Eckard, R. J., V. O. Snow, I. R. Johnson, and A. D. Moore. "The challenges and opportunities when integrating animal models into grazing system models for evaluating productivity and environmental impact." Animal Production Science 54, no. 12 (2014): 1896. http://dx.doi.org/10.1071/an14551.

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The intensification of livestock production has highlighted the importance of balancing production and the environmental impact in grazing systems. With the advent of more distributed computing power we have seen more complex models being developed, capable of simulating most aspects of a livestock production system. Where the modelling objective includes prediction of both productivity and environmental impacts, it is imperative to include appropriate consideration of the grazing animal in the simulation. This raises numerous challenges with respect to environmental impact modelling, including explicit treatment of nutrients in dung and urine, the prediction of grazing behaviour, dry matter intake and associated enteric methane loss. This paper discusses these challenges and opportunities when integrating animal models into grazing system models for evaluating productivity and environmental impact.

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Jauhiainen, L., and H. T. Korhonen. "Optimal behaviour sampling and autocorrelation curve: modelling data of farmed foxes." acta ethologica 8, no. 1 (February 26, 2005): 13–21. http://dx.doi.org/10.1007/s10211-004-0105-1.

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Deutsch, Andreas, Peter Friedl, Luigi Preziosi, and Guy Theraulaz. "Multi-scale analysis and modelling of collective migration in biological systems." Philosophical Transactions of the Royal Society B: Biological Sciences 375, no. 1807 (July 27, 2020): 20190377. http://dx.doi.org/10.1098/rstb.2019.0377.

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Collective migration has become a paradigm for emergent behaviour in systems of moving and interacting individual units resulting in coherent motion. In biology, these units are cells or organisms. Collective cell migration is important in embryonic development, where it underlies tissue and organ formation, as well as pathological processes, such as cancer invasion and metastasis. In animal groups, collective movements may enhance individuals' decisions and facilitate navigation through complex environments and access to food resources. Mathematical models can extract unifying principles behind the diverse manifestations of collective migration. In biology, with a few exceptions, collective migration typically occurs at a ‘mesoscopic scale’ where the number of units ranges from only a few dozen to a few thousands, in contrast to the large systems treated by statistical mechanics. Recent developments in multi-scale analysis have allowed linkage of mesoscopic to micro- and macroscopic scales, and for different biological systems. The articles in this theme issue on ‘Multi-scale analysis and modelling of collective migration’ compile a range of mathematical modelling ideas and multi-scale methods for the analysis of collective migration. These approaches (i) uncover new unifying organization principles of collective behaviour, (ii) shed light on the transition from single to collective migration, and (iii) allow us to define similarities and differences of collective behaviour in groups of cells and organisms. As a common theme, self-organized collective migration is the result of ecological and evolutionary constraints both at the cell and organismic levels. Thereby, the rules governing physiological collective behaviours also underlie pathological processes, albeit with different upstream inputs and consequences for the group. This article is part of the theme issue ‘Multi-scale analysis and modelling of collective migration in biological systems’.

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Cocker, Paul J., and Catharine A. Winstanley. "Towards a Better Understanding of Disordered Gambling: Efficacy of Animal Paradigms in Modelling Aspects of Gambling Behaviour." Current Addiction Reports 2, no. 3 (July 5, 2015): 240–48. http://dx.doi.org/10.1007/s40429-015-0065-8.

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Crompton, Robin Huw, William I. Sellers, and Susannah K. S. Thorpe. "Arboreality, terrestriality and bipedalism." Philosophical Transactions of the Royal Society B: Biological Sciences 365, no. 1556 (October 27, 2010): 3301–14. http://dx.doi.org/10.1098/rstb.2010.0035.

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The full publication of Ardipithecus ramidus has particular importance for the origins of hominin bipedality, and strengthens the growing case for an arboreal origin. Palaeontological techniques however inevitably concentrate on details of fragmentary postcranial bones and can benefit from a whole-animal perspective. This can be provided by field studies of locomotor behaviour, which provide a real-world perspective of adaptive context, against which conclusions drawn from palaeontology and comparative osteology may be assessed and honed. Increasingly sophisticated dynamic modelling techniques, validated against experimental data for living animals, offer a different perspective where evolutionary and virtual ablation experiments, impossible for living mammals, may be run in silico , and these can analyse not only the interactions and behaviour of rigid segments but increasingly the effects of compliance, which are of crucial importance in guiding the evolution of an arboreally derived lineage.

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Bestley, Sophie, Ian D. Jonsen, Mark A. Hindell, Christophe Guinet, and Jean-Benoît Charrassin. "Integrative modelling of animal movement: incorporating in situ habitat and behavioural information for a migratory marine predator." Proceedings of the Royal Society B: Biological Sciences 280, no. 1750 (January 7, 2013): 20122262. http://dx.doi.org/10.1098/rspb.2012.2262.

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A fundamental goal in animal ecology is to quantify how environmental (and other) factors influence individual movement, as this is key to understanding responsiveness of populations to future change. However, quantitative interpretation of individual-based telemetry data is hampered by the complexity of, and error within, these multi-dimensional data. Here, we present an integrative hierarchical Bayesian state-space modelling approach where, for the first time, the mechanistic process model for the movement state of animals directly incorporates both environmental and other behavioural information, and observation and process model parameters are estimated within a single model. When applied to a migratory marine predator, the southern elephant seal ( Mirounga leonina ), we find the switch from directed to resident movement state was associated with colder water temperatures, relatively short dive bottom time and rapid descent rates. The approach presented here can have widespread utility for quantifying movement–behaviour (diving or other)–environment relationships across species and systems.

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Vargas-Villamil, L. M., and L. O. Tedeschi. "Potential integration of multi-fitting, inverse problem and mechanistic modelling approaches to applied research in animal science: a review." Animal Production Science 54, no. 12 (2014): 1905. http://dx.doi.org/10.1071/an14568.

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Modern researchers working in applied animal science systems have faced issues with modelling huge quantities of data. Modelling approaches that have previously been used to model biological systems are having problems to adapt to increased number of publications and research. So as to develop new approaches that have the potential to deal with these fast-changing complex conditions, it is relevant to review modern modelling approaches that have been used successfully in other fields. Therefore, this paper reviews the potential capacity of new integrated applied animal-science approaches to discriminate parameters, interpret data and understand biological processes. The analysis shows that the principal challenge is handling ill-conditioned complex models, but an integrated approach can obtain meaningful information from complementary data that cannot be obtained from present applied animal-science approaches. Furthermore, it is shown that parameter sloppiness and data complementarity are key concepts during system behaviour restrictions and parameter discrimination. Additionally, model evaluation and implementation of the potential integrated approach are reviewed. Finally, the objective of an integral approach is discussed. Our conclusion is that these approaches have the potential to be used to deepen the understanding of applied animal systems, and that exist enough developed resources and methodologies to deal with the huge quantities of data associated with this science.

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Browning, Ella, Mark Bolton, Ellie Owen, Akiko Shoji, Tim Guilford, and Robin Freeman. "Predicting animal behaviour using deep learning: GPS data alone accurately predict diving in seabirds." Methods in Ecology and Evolution 9, no. 3 (November 20, 2017): 681–92. http://dx.doi.org/10.1111/2041-210x.12926.

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de Vries, Han, and Jacobus C. Biesmeijer. "Modelling collective foraging by means of individual behaviour rules in honey-bees." Behavioral Ecology and Sociobiology 44, no. 2 (November 18, 1998): 109–24. http://dx.doi.org/10.1007/s002650050522.

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Larom, D., M. Garstang, K. Payne, R. Raspet, and M. Lindeque. "The influence of surface atmospheric conditions on the range and area reached by animal vocalizations." Journal of Experimental Biology 200, no. 3 (February 1, 1997): 421–31. http://dx.doi.org/10.1242/jeb.200.3.421.

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Low-level vertical changes in temperature and wind exert powerful and predictable influences on the area ensonified by animal vocalizations. Computer modelling of low-frequency sound propagation in measured atmospheric conditions predicts that the calls of the savanna elephant at these frequencies can have ranges exceeding 10 km and that the calls will be highly directional in the presence of wind shear. Calling area is maximized under temperature inversions with low wind speeds. Calling area changes substantially over 24 h periods; on any given day, the calling area undergoes an expansion and contraction which may be as large as one order of magnitude. This cycle is modulated by topography, regional weather patterns, seasonality and possibly by climate variation. Similar influences affect the somewhat higher-frequency calls of lions and may be a selective pressure towards their crepuscular and nocturnal calling behaviour. Coyotes and wolves, which also live in areas with strong and prevalent nocturnal temperature inversions, show similar calling patterns, maximizing their chances of being heard over the longest possible distances. The pronounced dawn and evening vocalization peaks in other animals including birds, frogs and insects may reflect the same influences in combination with other factors which selectively limit high-frequency sound propagation. Atmospheric conditions therefore need to be taken into account in many field studies of animal behaviour. A simplified method for estimating sound propagation during field studies is presented.

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KING, J. R., and J. M. OLIVER. "Thin-film modelling of poroviscous free surface flows." European Journal of Applied Mathematics 16, no. 4 (August 2005): 519–53. http://dx.doi.org/10.1017/s095679250500584x.

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Thin-film models for the flow of a low reduced-Reynolds-number poroviscous droplet over a planar substrate are developed. One of the formulations is used to develop a minimal model for active animal cell motion in which the microscopic mechanisms of polymerisation and depolymerisation near the outer cell periphery are modelled by specifying the rate of mass transfer between the phases at the contact-line in terms of the velocity of the latter. An asymptotic analysis in the limit corresponding to strong cell-substrate adhesion is shown to lead to a novel class of multi-valued contact-line laws, a qualitative analysis of which leads in two dimensions to some intriguing behaviour, including (i) periodic contraction and expansion (pulsation), (ii) steady propagation at a contant speed, (iii) an unsteady combination of pulsation and propagation, and (iv) a bistable regime in which both non-motile and motile solutions are admissible, each of them being stable to sufficiently small perturbations, but with sufficiently large perturbations being able to ‘prod’ a stationary cell into motion or halt a moving one; these qualitative predictions are where possible compared with experiment. The contact-line behaviour is likely to be highly sensitive to environmental signals; the formulation may, therefore, provide a useful ‘minimal’ modelling framework for investigation of chemotactic effects at the cell scale. The corresponding extensional flow formulations are also noted.

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Webb, J. N., T. Székely, A. I. Houston, and J. M. McNamara. "A theoretical analysis of the energetic costs and consequences of parental care decisions." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 357, no. 1419 (March 29, 2002): 331–40. http://dx.doi.org/10.1098/rstb.2001.0934.

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Should a parent care for its young or abandon them before they reach independence? We consider parental care behaviour as an adaptive decision, involving trade–offs between current and future reproduction. The condition of the parent is expected to influence these trade–offs. Using a dynamic programming model we explore how changes in the levels of energetic reserves, and time in the season, determine changes in parental care decisions. The novel feature of our model is that we have included the possibility of remating within the current breeding season in a consistent manner by explicitly modelling the behaviour of unmated animals. We show that there may be several fluctuations in the average duration of care during the breeding season. We also show that, because of the dependence of parental care behaviour on both the condition of the parent and time during the breeding season, changing some of the costs of care may increase the duration of care during one part of the season and decrease it at another. The model also shows that the conditions prevailing for animals with dependent offspring can affect the way in which an unmated animal behaves. For example, the behaviour of unmated animals may change to compensate (partly) for increases in the costs of raising offspring, which are produced at a later date (for example, by increasing the duration of foraging between breeding attempts). Overall, the model provides a good framework for understanding how various ecological and life–history variables should influence parental care behaviour during a breeding season.

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MARION, G., L. A. SMITH, D. L. SWAIN, R. S. DAVIDSON, and M. R. HUTCHINGS. "Agent-based modelling of foraging behaviour: the impact of spatial heterogeneity on disease risks from faeces in grazing systems." Journal of Agricultural Science 146, no. 5 (September 9, 2008): 507–20. http://dx.doi.org/10.1017/s0021859608008022.

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SUMMARYMany of the most pervasive disease challenges to livestock are transmitted via oral contact with faeces (or by faecal–aerosol) and the current paper focuses on how disease risk may depend on: spatial heterogeneity, animal searching behaviour, different grazing systems and faecal deposition patterns including those representative of livestock and a range of wildlife. A spatially explicit agent-based model was developed to describe the impact of empirically observed foraging and avoidance behaviours on the risk of disease presented by investigative and grazing contact with both livestock and wildlife faeces. To highlight the role of spatial heterogeneity on disease risks an analogous deterministic model, which ignores spatial heterogeneity and searching behaviour, was compared with the spatially explicit agent-based model. The models were applied to assess disease risks in temperate grazing systems. The results suggest that spatial heterogeneity is crucial in defining the disease risks to which individuals are exposed even at relatively small scales. Interestingly, however, although sensitive to other aspects of behaviour such as faecal avoidance, it was observed that disease risk is insensitive to search distance for typical domestic livestock restricted to small field plots. In contrast disease risk is highly sensitive to distributions of faecal contamination, in that contacts with highly clumped distributions of wildlife contamination are rare in comparison to those with more dispersed contamination. Finally it is argued that the model is a suitable framework to study the relative inter- and intra-specific disease risks posed to livestock under different realistic management regimes.

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Craft, Meggan E. "Infectious disease transmission and contact networks in wildlife and livestock." Philosophical Transactions of the Royal Society B: Biological Sciences 370, no. 1669 (May 26, 2015): 20140107. http://dx.doi.org/10.1098/rstb.2014.0107.

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The use of social and contact networks to answer basic and applied questions about infectious disease transmission in wildlife and livestock is receiving increased attention. Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade networks. Network modelling is a flexible tool used to capture the heterogeneous contacts of a population in order to test hypotheses about the mechanisms of disease transmission, simulate and predict disease spread, and test disease control strategies. This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or using contact data. This paper describes the rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations; discusses the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks; and highlights knowledge gaps in how to collect and analyse contact data. Opportunities for the future include increased attention to experiments, pathogen genetic markers and novel computational tools.

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Pérez-Escudero, Alfonso, and Gonzalo G. de Polavieja. "Adversity magnifies the importance of social information in decision-making." Journal of The Royal Society Interface 14, no. 136 (November 2017): 20170748. http://dx.doi.org/10.1098/rsif.2017.0748.

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Decision-making theories explain animal behaviour, including human behaviour, as a response to estimations about the environment. In the case of collective behaviour, they have given quantitative predictions of how animals follow the majority option. However, they have so far failed to explain that in some species and contexts social cohesion increases when conditions become more adverse (i.e. individuals choose the majority option with higher probability when the estimated quality of all available options decreases). We have found that this failure is due to modelling simplifications that aided analysis, like low levels of stochasticity or the assumption that only one choice is the correct one. We provide a more general but simple geometric framework to describe optimal or suboptimal decisions in collectives that gives insight into three different mechanisms behind this effect. The three mechanisms have in common that the private information acts as a gain factor to social information: a decrease in the privately estimated quality of all available options increases the impact of social information, even when social information itself remains unchanged. This increase in the importance of social information makes it more likely that agents will follow the majority option. We show that these results quantitatively explain collective behaviour in fish and experiments of social influence in humans.

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GILBERT, W. H., B. N. HÄSLER, and J. RUSHTON. "Influences of farmer and veterinarian behaviour on emerging disease surveillance in England and Wales." Epidemiology and Infection 142, no. 1 (March 26, 2013): 172–86. http://dx.doi.org/10.1017/s0950268813000484.

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SUMMARYSurveillance for new and re-emerging animal diseases in England and Wales is based on post-mortem and syndromic analysis of laboratory data collated in a central database by the Animal Health and Veterinary Laboratories Agency (AHVLA), with the aim of providing early warning of disease events prior to clinical diagnosis. Understanding the drivers for participation in such systems is critical to the success of attempts to improve surveillance sensitivity. The aim of this study was to investigate the decision-making process governing the submission of biological samples on which this surveillance system is based by use of questionnaires. Data extracted were used to structure and parameterize scenario trees modelling the probability of generating an entry in the surveillance database. The mean probability for database entry per case ranged from 0·085 for neurological disorders to 0·25 for enteric disease. These findings illustrate the importance of on-farm decision making to the generation of surveillance data.

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Swain, D. L., M. A. Friend, G. J. Bishop-Hurley, R. N. Handcock, and T. Wark. "Tracking livestock using global positioning systems - are we still lost?" Animal Production Science 51, no. 3 (2011): 167. http://dx.doi.org/10.1071/an10255.

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Since the late 1980s, satellite-based global positioning systems (GPS) have provided unique and novel data that have been used to track animal movement. Tracking animals with GPS can provide useful information, but the cost of the technology often limits experimental replication. Limitations on the number of devices available to monitor the behaviour of animals, in combination with technical constraints, can weaken the statistical power of experiments and create significant experimental design challenges. The present paper provides a review and synthesis of using GPS for livestock-based studies and suggests some future research directions. Wildlife ecologists working in extensive landscapes have pioneered the use of GPS-based devices for tracking animals. Wildlife researchers have focussed efforts on quantifying and addressing issues associated with technology limitations, including spatial accuracy, rate of data collection, battery life and environmental factors causing loss of data. It is therefore not surprising that there has been a significant number of methodological papers published in the literature that have considered technical developments of GPS-based animal tracking. Livestock scientists have used GPS data to inform them about behavioural differences in free-grazing experiments. With a shift in focus from the environment to the animal comes the challenge of ensuring independence of the experimental unit. Social facilitation challenges independence of the individual in a group. The use of spatial modelling methods to process GPS data provides an opportunity to determine the degree of independence of data collected from an individual animal within behavioural-based studies. By using location and movement information derived from GPS data, researchers have been able to determine the environmental impact of grazing animals as well as assessing animal responses to management activities or environmental perturbations. Combining satellite-derived remote-sensing data with GPS-derived landscape preference indices provides a further opportunity to identify landscape avoidance and selection behaviours. As spatial livestock monitoring tools become more widely used, there will be a greater need to ensure the data and associated processing methods are able to answer a broader range of questions. Experimental design and analytical techniques need to be given more attention if GPS technology is to provide answers to questions associated with free-grazing animals.

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Blaauboer, Bas J. "The Necessity of Biokinetic Information in the Interpretation of In Vitro Toxicity Data." Alternatives to Laboratory Animals 30, no. 2_suppl (December 2002): 85–91. http://dx.doi.org/10.1177/026119290203002s13.

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Data derived from in vitro toxicity studies are not directly applicable in an assessment of the toxicity of compounds in intact organisms. The major limitation is the lack of knowledge of biokinetic behaviour in vivo. Since the toxicity of a compound will be determined by the critical concentration (or other dose metric) of the critical compound (or a metabolite thereof) at the critical site of toxic action, biokinetic behaviour must be taken into account. Possibilities of biokinetic modelling on the basis of in vitro and other non-animal data are discussed, and the application of the results in hazard and risk-assessment schedules is considered.

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Hogan, Jerry. "Causation: the study of behavioural mechanisms." Animal Biology 55, no. 4 (2005): 323–41. http://dx.doi.org/10.1163/157075605774840969.

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AbstractThis paper describes current work on the causal analysis of behaviour systems. It is noted that while causal work investigating the neural, hormonal, and genetic bases of behaviour is flourishing, work being conducted at a strictly behavioural level of analysis has declined greatly over the past 40 years. Nonetheless, most recent research on animal cognition and applied ethology is still being carried out at a behavioural level of analysis and examples of both types of research are presented: memory mechanisms of food-storing birds and decisions of spider-eating jumping spiders, as well as feather pecking in fowl and animal welfare issues, are all briefly discussed. Finally, I discuss the similarities between neural network modelling and early ethological models of motivation, and then show how a modern version of Lorenz's model of motivation can account for current research findings on dustbathing in chickens and sleep in humans. I conclude that valuable information can still be obtained by research at a behavioural level of analysis.

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Lewis, C. R. G., and J. J. McGlone. "Modelling feeding behaviour, rate of feed passage and daily feeding cycles, as possible causes of fatigued pigs." Animal 2, no. 4 (2008): 600–605. http://dx.doi.org/10.1017/s1751731108001766.

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Grøn, Ole. "The spatio-temporal dynamics of resources in ‘wild’ prehistoric landscapes." Samara Journal of Science 7, no. 4 (November 30, 2018): 161–67. http://dx.doi.org/10.17816/snv201874202.

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Based on archaeological and ethnoarchaeological data, this paper discusses the spatio-temporal dynamics of the resources in wild prehistoric landscapes, i.e. landscapes not subjected to techniques related to modern mono-cultural agriculture but potentially managed in other ways. The prevailing assumption in the archaeological environments engaged in modelling of Stone Age settlement positions is, that the resources in such landscapes are rather stable and evenly distributed. Such a concept was, however, abandoned in landscape ecology in the mid-1990s because it did not match the observed environmental reality, and replaced with much more mathematically complex models accepting that the different species (plants as well as animals) tend to appear in highly dynamic patches. Updating both the archaeological debate and research initiatives related to modelling of Stone Age habitation areas is therefore long overdue. A central point in this respect is whether the dynamic spatio-temporal behaviour of the resources in these landscapes is so complex that its reconstruction in specific micro-areas, and thereby a precise modelling of potential Stone Age settlement areas, is impossible. The fact, that human cultural groups opposite animal and plant societies often can be observed to behave different in similar environmental situations due to that they have developed different strategies and traditions, does not leave much hope.

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Goodall, Victoria L., Sam M. Ferreira, Paul J. Funston, and Nkabeng Maruping-Mzileni. "Uncovering hidden states in African lion movement data using hidden Markov models." Wildlife Research 46, no. 4 (2019): 296. http://dx.doi.org/10.1071/wr18004.

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Context Direct observations of animals are the most reliable way to define their behavioural characteristics; however, to obtain these observations is costly and often logistically challenging. GPS tracking allows finer-scale interpretation of animal responses by measuring movement patterns; however, the true behaviour of the animal during the period of observation is seldom known. Aims The aim of our research was to draw behavioural inferences for a lioness with a hidden Markov model and to validate the predicted latent-state sequence with field observations of the lion pride. Methods We used hidden Markov models to model the movement of a lioness in the Kruger National Park, South Africa. A three-state log-normal model was selected as the most suitable model. The model outputs are related to collected data by using an observational model, such as, for example, a distribution for the average movement rate and/or direction of movement that depends on the underlying model states that are taken to represent behavioural states of the animal. These inferred behavioural states are validated against direct observation of the pride’s behaviour. Key results Average movement rate provided a useful alternative for the application of hidden Markov models to irregularly spaced GPS locations. The movement model predicted resting as the dominant activity throughout the day, with a peak in the afternoon. The local-movement state occurred consistently throughout the day, with a decreased proportion during the afternoon, when more resting takes place, and an increase towards the early evening. The relocating state had three peaks, namely, during mid-morning, early evening and about midnight. Because of the differences in timing of the direct observations and the GPS locations, we had to compare point observations of the true behaviour with an interval prediction of the modelled behavioural state. In 75% of the cases, the model-predicted behaviour and the field-observed behaviour overlapped. Conclusions Our data suggest that the hidden Markov modelling approach is successful at predicting a realistic behaviour of lions on the basis of the GPS location coordinates and the average movement rate between locations. The present study provided a unique opportunity to uncover the hidden states and compare the true behaviour with the inferred behaviour from the predicted state sequence. Implications Our results illustrated the potential of using hidden Markov models with movement rate as an input to understand carnivore behavioural patterns that could inform conservation management practices.

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Jhawar, Jitesh, and Vishwesha Guttal. "Noise-induced effects in collective dynamics and inferring local interactions from data." Philosophical Transactions of the Royal Society B: Biological Sciences 375, no. 1807 (July 27, 2020): 20190381. http://dx.doi.org/10.1098/rstb.2019.0381.

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In animal groups, individual decisions are best characterized by probabilistic rules. Furthermore, animals of many species live in small groups. Probabilistic interactions among small numbers of individuals lead to a so-called intrinsic noise at the group level. Theory predicts that the strength of intrinsic noise is not a constant but often depends on the collective state of the group; hence, it is also called a state-dependent noise or a multiplicative noise . Surprisingly, such noise may produce collective order. However, only a few empirical studies on collective behaviour have paid attention to such effects owing to the lack of methods that enable us to connect data with theory. Here, we demonstrate a method to characterize the role of stochasticity directly from high-resolution time-series data of collective dynamics. We do this by employing two well-studied individual-based toy models of collective behaviour. We argue that the group-level noise may encode important information about the underlying processes at the individual scale. In summary, we describe a method that enables us to establish connections between empirical data of animal (or cellular) collectives and the phenomenon of noise-induced states, a field that is otherwise largely limited to the theoretical literature. This article is part of the theme issue ‘Multi-scale analysis and modelling of collective migration in biological systems’.

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Vernon, Matthew C., and Matt J. Keeling. "Representing the UK's cattle herd as static and dynamic networks." Proceedings of the Royal Society B: Biological Sciences 276, no. 1656 (October 14, 2008): 469–76. http://dx.doi.org/10.1098/rspb.2008.1009.

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Network models are increasingly being used to understand the spread of diseases through sparsely connected populations, with particular interest in the impact of animal movements upon the dynamics of infectious diseases. Detailed data collected by the UK government on the movement of cattle may be represented as a network, where animal holdings are nodes, and an edge is drawn between nodes where a movement of animals has occurred. These network representations may vary from a simple static representation, to a more complex, fully dynamic one where daily movements are explicitly captured. Using stochastic disease simulations, a wide range of network representations of the UK cattle herd are compared. We find that the simpler static network representations are often deficient when compared with a fully dynamic representation, and should therefore be used only with caution in epidemiological modelling. In particular, due to temporal structures within the dynamic network, static networks consistently fail to capture the predicted epidemic behaviour associated with dynamic networks even when parameterized to match early growth rates.

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Journal articles on the topic 'Animal behaviour modelling'

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