Animating Predator and Prey Fish Interactions

Schooling behavior is one of the most salient social and group activities among fish. They form schools for social reasons like foraging, mating and escaping from predators. Animating a school of fish is difficult because they are large in number, often swim in distinctive patterns that is they take the shape of long thin lines, squares, ovals or amoeboid and exhibit complex coordinated patterns especially when they are attacked by a predator. Previous work in computer graphics has not provided satisfactory models to simulate the many distinctive interactions between a school of prey fish and their predator, how does a predator pick its target? and how does a school of fish react to such attacks? This dissertation presents a method to simulate interactions between prey fish and predator fish in the 3D world based on the biological research findings. Firstly, a model is described by representing a school of fish as a complex network information flow with structural properties. Using this model, a predator fish targeting isolated peripheral fish is simulated. Secondly, the escape behavior state machine model and escape maneuvers exhibited by fish schools are described. The escape maneuvers include compact, avoid, fast avoid, skitter, fountain, flash, ball, split, join, herd, vacuole, and hourglass are identified in the biological studies. This proposed escape behavior animation model can free an animator from dealing with the low-level animations but instead, control the fish behavior on a higher level by modifying a state machine and a small set of system parameters. With the state machine and relatively few system parameters, the proposed system is stable, predictable, and easy to tune, which represent important properties for animators to control the outcome. This system is developed in Unity (3D). In addition, a plug-in is also developed for full-fledged graphics tool Blender software to simulate escape maneuvers. The animator has to simply select escape maneuvers, adjust parameters and work on animating predator using keyframe method. It does not deal with the state machine model. The proposed model is useful not only in generating group behaviors but also in scientific visualization tool for studying fish behavior

Animating the Carbon Cycle

This a post-print, author-produced version of an article accepted for publication in Ecosystems. Copyright © 2013 Springer Science+Business Media New York. The final publication is available at Springer via http://dx.doi.org/10.1007/s10021-013-9715-7Understanding the biogeochemical processes regulating carbon cycling is central to mitigating atmospheric CO2 emissions. The role of living organisms has been accounted for, but the focus has traditionally been on contributions of plants and microbes. We develop the case that fully “animating” the carbon cycle requires broader consideration of the functional role of animals in mediating biogeochemical processes and quantification of their effects on carbon storage and exchange among terrestrial and aquatic reservoirs and the atmosphere. To encourage more hypothesis-driven experimental research that quantifies animal effects we discuss the mechanisms by which animals may affect carbon exchanges and storage within and among ecosystems and the atmosphere. We illustrate how those mechanisms lead to multiplier effects whose magnitudes may rival those of more traditional carbon storage and exchange rate estimates currently used in the carbon budget. Many animal species are already directly managed. Thus improved quantitative understanding of their influence on carbon budgets may create opportunity for management and policy to identify and implement new options for mitigating CO2 release at regional scales.US National Science FoundationNERCBBSRCNippon Foundatio

Goliath's humanimal body:Masculinity, ethnicity, and animal imagery in 1 Samuel 17

In 1 Samuel 17, Goliath is described using animal imagery, depicted like a sea creature, a lion and bear, a dog, and scavengers’ prey. I argue that these images present Goliath as not fully human, and contribute to the construction of his masculinity and ethnicity. This article traces the trajectory here: masculinity is established then undermined; the foreigner encroaches then is expelled. Goliath is introduced as a hypermasculine ultrapredator. Akin to a sea monster from the chaotic beyond, he has an exoskeleton of fish-scale armour (17:5). David then likens him to lions and bears (17:34-37), imperial symbols for fearsome foreign nations. David, though, can grasp their beards (overturning their masculinity) and slay them. Goliath perceives David to be treating him like a scavenging dog (17:43)—a dishonourable creature encroaching where it does not belong. Consequently, the opponents threaten to give the other’s flesh to the birds and beasts (17:44, 46). Their bodies’ masculine wholeness is disarticulated by scavengers and expelled from society

Whales as marine ecosystem engineers

Baleen and sperm whales, known collectively as the great whales, include the largest animals in the history of life on Earth. With high metabolic demands and large populations, whales probably had a strong influence on marine ecosystems before the advent of industrial whaling: as consumers of fish and invertebrates; as prey to other large-bodied predators; as reservoirs of and vertical and horizontal vectors for nutrients; and as detrital sources of energy and habitat in the deep sea. The decline in great whale numbers, estimated to be at least 66% and perhaps as high as 90%, has likely altered the structure and function of the oceans, but recovery is possible and in many cases is already underway. Future changes in the structure and function of the world\u27s oceans can be expected with the restoration of great whale populations

Analytical detection of stationary and dynamic patterns in a prey-predator model with reproductive Allee effect in prey growth

Allee effect in population dynamics has a major impact in suppressing the paradox of enrichment through global bifurcation, and it can generate highly complex dynamics. The influence of the reproductive Allee effect, incorporated in the prey's growth rate of a prey-predator model with Beddington-DeAngelis functional response, is investigated here. Preliminary local and global bifurcations are identified of the temporal model. Existence and non-existence of heterogeneous steady-state solutions of the spatio-temporal system are established for suitable ranges of parameter values. The spatio-temporal model satisfies Turing instability conditions, but numerical investigation reveals that the heterogeneous patterns corresponding to unstable Turing eigen modes acts as a transitory pattern. Inclusion of the reproductive Allee effect in the prey population has a destabilising effect on the coexistence equilibrium. For a range of parameter values, various branches of stationary solutions including mode-dependent Turing solutions and localized pattern solutions are identified using numerical bifurcation technique. The model is also capable to produce some complex dynamic patterns such as travelling wave, moving pulse solution, and spatio-temporal chaos for certain range of parameters and diffusivity along with appropriate choice of initial conditions Judicious choices of parametrization for the Beddington-DeAngelis functional response help us to infer about the resulting patterns for similar prey-predator models with Holling type-II functional response and ratio-dependent functional response

Cognitive Modeling for Computer Animation: A Comparative Review

Cognitive modeling is a provocative new paradigm that paves the way towards intelligent graphical characters by providing them with logic and reasoning skills. Cognitively empowered self-animating characters will see in the near future a widespread use in the interactive game, multimedia, virtual reality and production animation industries. This review covers three recently-published papers from the field of cognitive modeling for computer animation. The approaches and techniques employed are very different. The cognition model in the first paper is built on top of Soar, which is intended as a general cognitive architecture for developing systems that exhibit intelligent behaviors. The second paper uses an active plan tree and a plan library to achieve the fast and robust reactivity to the environment changes. The third paper, based on an AI formalism known as the situation calculus, develops a cognitive modeling language called CML and uses it to specify a behavior outline or sketch plan to direct the characters in terms of goals. Instead of presenting each paper in isolation then comparatively analyzing them, we take a top-down approach by first classifying the field into three different categories and then attempting to put each paper into a proper category. Hopefully in this way it can provide a more cohesive, systematic view of cognitive modeling approaches employed in computer animation

Marine reserves can mitigate and promote adaptation to climate change

Strong decreases in greenhouse gas emissions are required to meet the reduction trajectory resolved within the 2015 Paris Agreement. However, even these decreases will not avert serious stress and damage to life on Earth, and additional steps are needed to boost the resilience of ecosystems, safeguard their wildlife, and protect their capacity to supply vital goods and services. We discuss how well-managed marine reserves may help marine ecosystems and people adapt to five prominent impacts of climate change: acidification, sea-level rise, intensification of storms, shifts in species distribution, and decreased productivity and oxygen availability, as well as their cumulative effects. We explore the role of managed ecosystems in mitigating climate change by promoting carbon sequestration and storage and by buffering against uncertainty in management, environmental fluctuations, directional change, and extreme events. We highlight both strengths and limitations and conclude that marine reserves are a viable low-tech, cost-effective adaptation strategy that would yield multiple cobenefits from local to global scales, improving the outlook for the environment and people into the future

Chimera States in Ecological Network Under Weighted Mean-Field Dispersal of Species

In ecological landscapes, species tend to migrate between nearby patches in search of a better survivability condition. By this dispersal process, they form connectivity between the patches and thereby may develop various correlated or partially correlated population dynamics among species living in the patches. We explore various possible emergent collective population patterns using a simple ecological network model of all-to-all connected patches where we use a particular type of dispersal process that is controlled by a weighted mean-field diffusion to include the failed migration between the interacting patches. We represent the population dynamics of both the predator and prey in each patch by a modified Rosenzweig-MacArthur (mRM) model that incorporates an additional effect of habitat complexity. Our theoretical investigations on the network dynamics, using numerical and to some extent, analytical techniques, show various complex patterns, namely, 2-cluster, 3-cluster and multicluster states, and chimera states, besides synchrony (1-cluster) and homogeneous steady states (HSS) in a migrating metapopulation. An important observation is that addition of habitat complexity in the Rosenzweig-MacArthur (RM) model makes qualitative changes in the collective behaviors. Especially to mention that it shrinks the region of synchrony and broadens the region of HSS, in parameter space and, thereby leads to better survival probabilities and increased population persistence in a natural ecosystem

Introductory Life Science Mathematics and Quantitative Neuroscience Courses

We describe two sets of courses designed to enhance the mathematical, statistical, and computational training of life science undergraduates at Emory College. The first course is an introductory sequence in differential and integral calculus, modeling with differential equations, probability, and inferential statistics. The second is an upper-division course in computational neuroscience. We provide a description of each course, detailed syllabi, examples of content, and a brief discussion of the main issues encountered in developing and offering the courses