JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. Submitted January 5, 2013; Accepted April 11, 2013; Electronically published July 12, 2013 abstract: The metabolic costs of animal movement have been studied extensively under laboratory conditions, although frequently these are a poor approximation of the costs of operating in the natural, heterogeneous environment. Construction of "energy landscapes," which relate animal locality to the cost of transport, can clarify whether, to what extent, and how movement properties are attributable to environmental heterogeneity. Although behavioral responses to aspects of the energy landscape are well documented in some fields (notably, the selection of tailwinds by aerial migrants) and scales (typically large), the principles of the energy landscape extend across habitat types and spatial scales. We provide a brief synthesis of the mechanisms by which environmentally driven changes in the cost of transport can modulate the behavioral ecology of animal movement in different media, develop example cost functions for movement in heterogeneous environments, present methods for visualizing these energy landscapes, and derive specific predictions of expected outcomes from individual-to population-and species-level processes. Animals modulate a suite of movement parameters (e.g., route, speed, timing of movement, and tortuosity) in relation to the energy landscape, with the nature of their response being related to the energy savings available. Overall, variation in movement costs influences the quality of habitat patches and causes nonrandom movement of individuals between them. This can provide spatial and/or temporal structure to a range of population-and specieslevel processes, ultimately including gene flow. Advances in animalattached technology and geographic information systems are opening up new avenues for measuring and mapping energy landscapes that are likely to provide new insight into their influence in animal ecology.

Locomotion is one of the major energetic costs faced by animals and various strategies have evolved to reduce its cost. Birds use interspersed periods of flapping and gliding to reduce the mechanical requirements of level flight while undergoing cyclical changes in flight altitude, known as undulating flight. Here we equipped free-ranging marine vertebrates with accelerometers and demonstrate that gait patterns resembling undulating flight occur in four marine vertebrate species comprising sharks and pinnipeds. Both sharks and pinnipeds display intermittent gliding interspersed with powered locomotion. We suggest, that the convergent use of similar gait patterns by distinct groups of animals points to universal physical and physiological principles that operate beyond taxonomic limits and shape common solutions to increase energetic efficiency. Energetically expensive large-scale migrations performed by many vertebrates provide common selection pressure for efficient locomotion, with potential for the convergence of locomotory strategies by a wide variety of species.

Devices attached to flying birds can hugely enhance our understanding of their behavioural ecology for periods when they cannot be observed directly. For this, scientists routinely attach units to either birds' backs or their tails. However, inappropriate payload distribution is critical in aircraft and, since birds and planes are subject to the same laws of physics during flight, we considered aircraft aerodynamic constraints to explain flight patterns displayed by northern gannets Sula bassana equipped with (small ca. 14 g) tail- and back-mounted accelerometers and (larger ca. 30 g) tail-mounted GPS units. Tail-mounted GPS-fitted birds showed significantly higher cumulative numbers of flap-glide cycles and a higher pitch angle of the tail than accelerometer-equipped birds, indicating problems with balancing inappropriately placed weights with knock-on consequences relating to energy expenditure. These problems can be addressed by carefully choosing where to place tags on birds according to the mass of the tags and the lifestyle of the subject species.

Assessment of animal internal “state” – which includes hormonal, disease, nutritional, and emotional states – is normally considered the province of laboratory work, since its determination in animals in the wild is considered more difficult. However, we show that accelerometers attached externally to animals as diverse as elephants, cockroaches, and humans display consistent signal differences in micro‐movement that are indicative of internal state. Originally used to elucidate the behavior of wild animals, accelerometers also have great potential for highlighting animal actions, which are considered as responses stemming from the interplay between internal state and external environment. Advances in accelerometry may help wildlife managers understand how internal state is linked to behavior and movement, and thus clarify issues ranging from how animals cope with the presence of newly constructed roads to how diseased animals might change movement patterns and therefore modulate disease spread.

In recent years, a collection of new techniques which deal with video as input data, emerged in computer graphics and visualization. In this survey, we report the state of the art in video‐based graphics and video visualization. We provide a review of techniques for making photo‐realistic or artistic computer‐generated imagery from videos, as well as methods for creating summary and/or abstract visual representations to reveal important features and events in videos. We provide a new taxonomy to categorize the concepts and techniques in this newly emerged body of knowledge. To support this review, we also give a concise overview of the major advances in automated video analysis, as some techniques in this field (e.g. feature extraction, detection, tracking and so on) have been featured in video‐based modelling and rendering pipelines for graphics and visualization.

A new area of biological research is identifying and grouping patterns of behaviour in wild animals by analysing data obtained through the attachment of tri-axial accelerometers. As these recording devices become smaller and less expensive their use has increased. Currently acceleration data are visualised as 2D time series plots, and analyses are based on summary statistics and the application of Fourier transforms. We develop alternate visualisations of this data so as to analyse, explore and present new patterns of animal behaviour. Our visualisations include interactive spherical scatterplots, spherical histograms, clustering methods, and feature-based state diagrams of the data. We study the application of these visualisation methods to accelerometry data from animal movement. The reaction of biologists to these visualisations is also reported.

Fig. 1. A smooth graph representation of a labeled biological time-series. Each ring represents a state, and the edges between states visualize the state transitions. This graph uses smooth curves to explicitly visualize third order transitions, so that each curved edge represents a unique sequence of four successive states. The orange node is part of a selection set, and all transitions matching the current selection are highlighted in orange.Abstract-In this paper, we present a new visual way of exploring state sequences in large observational time-series. A key advantage of our method is that it can directly visualize higher-order state transitions. A standard first order state transition is a sequence of two states that are linked by a transition. A higher-order state transition is a sequence of three or more states where the sequence of participating states are linked together by consecutive first order state transitions. Our method extends the current state-graph exploration methods by employing a two dimensional graph, in which higher-order state transitions are visualized as curved lines. All transitions are bundled into thick splines, so that the thickness of an edge represents the frequency of instances. The bundling between two states takes into account the state transitions before and after the transition. This is done in such a way that it forms a continuous representation in which any subsequence of the timeseries is represented by a continuous smooth line. The edge bundles in these graphs can be explored interactively through our incremental selection algorithm. We demonstrate our method with an application in exploring labeled time-series data from a biological survey, where a clustering has assigned a single label to the data at each time-point. In these sequences, a large number of cyclic patterns occur, which in turn are linked to specific activities. We demonstrate how our method helps to find these cycles, and how the interactive selection process helps to find and investigate activities.

We present a feasibility study on using video visualization to aid snooker skill training. By involving the coaches and players in the loop of intelligent reasoning, our approach addresses the difficulties of automated semantic reasoning, while benefiting from mature video processing techniques. This work was conducted in conjunction with a snooker club and a sports scientist. In particular, we utilized the principal design of the VideoPerpetuoGram (VPG) to convey spatiotemporal information to the viewers through static visualization, removing the burden of repeated video viewing. We extended the VPG design to accommodate the need for depicting multiple video streams and respective temporal attribute fields, including silhouette extrusion, spatial attributes, and non-spatial attributes. Our results and evaluation have shown that video visualization can provide snooker coaching with visually quantifiable and comparable summary records, and is thus a cost-effective means for assessing skill levels and monitoring progress objectively and consistently.