Sharoni Shafir

Bio: Sharoni Shafir is an academic researcher from Hebrew University of Jerusalem. The author has contributed to research in topics: Honey bee & Nectar. The author has an hindex of 32, co-authored 85 publications receiving 4616 citations. Previous affiliations of Sharoni Shafir include Stanford University & University of Florida.

Predicting Risk-Sensitivity in Humans and Lower Animals: Risk as Variance or Coefficient of Variation

Abstract: In this paper, we examine the determinants of risk-sensitivity exhibited by humans and other animals. Our dependent measure is the proportion of respondents who choose a sure option over a risky option with equal expected value. We present a meta-analysis of human risk-preference data and compare it to the results of a similar meta-analysis of animal data by Shafir (2000). Both sets of data show that the coefficient of variation (CV), a relative measure of risk per unit of return, significantly predicts choices across a broad range of decision situations. In those situations where the CV can be compared to outcome variance, a more traditional (absolute) measure of risk, the CV outperforms variance as a predictor of risk sensitivity. This is especially true when decision makers (humans, or animals foraging for food) acquire information about choice outcomes and their variability experientially and over time, as demonstrated in an experiment in which we attempted to put students into a risky learning and decision making situation comparable to the experiential information acquisition in risky foraging choice tasks in animal experiments.

Predicting risk sensitivity in humans and lower animals: risk as variance or coefficient of variation.

Abstract: This article examines the statistical determinants of risk preference. In a meta-analysis of animal risk preference (foraging birds and insects), the coefficient of variation (CV), a measure of risk per unit of return, predicts choices far better than outcome variance, the risk measure of normative models. In a meta-analysis of human risk preference, the superiority of the CV over variance in predicting risk taking is not as strong. Two experiments show that people’s risk sensitivity becomes strongly proportional to the CV when they learn about choice alternatives like other animals, by experiential sampling over time. Experience-based choices differ from choices when outcomes and probabilities are numerically described. Zipf’s law as an ecological regularity and Weber’s law as a psychological regularity may give rise to the CV as a measure of risk. Decision making under risk and uncertainty is a topic of research in disciplines as diverse as psychology, economics, zoology, and entomology. Both the animal and the human risky choice literatures have proposed models that either predict choices in a deterministic fashion or predict risk sensitivity (i.e., the probability of choosing a riskier or less risky option) in a stochastic fashion. Theories of human risky choice include the prescriptive expected utility model (von Neumann & Morgenstern, 1947) or the risk– return models used to price risky options in finance (Markowitz, 1959). A prominent descriptive model is prospect theory (Kahneman & Tversky, 1979). In the animal literature, theories about risky foraging gave rise to the energy budget rule (Caraco, 1980; Stephens, 1981), a special case of a general class of normative models called risk sensitivity theories that construe risk sensitivity as the response of organisms whose goal is the maximization of Darwinian fitness in stochastic environments. Similar to prospect theory for human risky choice, the energy budget rule predicts risk aversion when animals are not in danger of starvation (domain of gains) but risk seeking when there is such a risk (domain of losses). Although different in many respects, these models all assume that the likelihood of choosing a risky option is affected by the variability of the option’s possible outcomes. The measure of variability used in these models is usually the variance of outcomes around the option’s expected value. The capital-assetpricing model in finance, for example, equates risk with variance and predicts that people’s willingness to pay for risky options with equal expected value is a decreasing function of the options’ outcome variance (Sharpe, 1964). The energy budget rule, as another example, predicts that—among options with equal expected energy intake—animals will prefer foraging options with smaller variance when the expected energy intake exceeds the caloric needs of the animal but will prefer options with greater variance when the expected energy intake is less than that required for survival because increases in outcome variance (holding expected value constant) are associated with a greater chance of obtaining the caloric intake required for survival.

Causes and consequences of sea urchin abundance and diversity in Kenyan coral reef lagoons.

Abstract: Large differences in community structure of sea urchins and finfish have been observed in Kenyan reef lagoons. Differences have been attributed to removal of finfish predators through human fishing activities. This study attempted to determine (i) the major sea urchin finfish predators, (ii) the effect of predation on sea-urchin community structure, and (iii) the possible effect of sea urchin increases and finfish decreases on the lagoonal substrate. Six reefs, two protected and four unprotected, were compared for differences in finfish abundance, sea urchin abundance and diversity and substrate cover, diversity and complexity. Comparisons between protected and unprotected reefs indicated that finfish populations were ca. 4 x denser in protected than unprotected reefs. Sea urchin populations were >100 x denser and predation rates on a sea urchin, Echinometra mathaei, were 4 x lower in unprotected than in protected reefs. The balistidae (triggerfish) was the single sea-urchin finfish predator family which had a higher population density in protected than in unprotected reefs. Balistid density was positively correlated with predation rates on tethered E. mathaei (r=0.88; p<0.025) and negatively correlated with total sea-urchin density (r=-0.89; p<0.025) on the six reefs. We conclude from observations that the balistids Balistaphus undulatus and Rhinecanthus aculeatus are the dominant sea-urchin predators. The sea-urchin assemblage had its greatest diversity and species richness at intermediate predation rates and low to intermediate sea-urchin densities. At low predation rates and high sea-urchin density E. mathaei dominated the assemblage's species composition. Preferential predation on the competitive dominant maintains the assemblage's diversity, supporting the compensatory mortality hypothesis (Connell 1978) of coral reef diversity. Protected reefs had greater cover of hard coral, calcareous and coralline algae, and greater substrate diversity and topographic complexity than unprotected reefs which had greater algal turf and sponge cover. Coral cover and topographic complexity were negatively correlated with total sea urchin density. Although experimentation is lacking, these substrate changes may be due to the switch from finfish to sea-urchins as consumers which results from overfishing of finfish. Removal of top invertebrate-eating carnivores appears to have cascading effects on the entire coral reef ecosystem.

Context-dependent violations of rational choice in honeybees (Apis mellifera) and gray jays (Perisoreus canadensis)

Abstract: Contrary to the theory of rational choice, adding an alternative to a set of available options often affects people's judgement of the preexisting options. Here, we show that honeybees (Apis mellifera) and gray jays (Perisoreus canadensis) are also influenced by the addition of an option to a choice set (i.e., by a change in local context). Like humans, our subjects violated basic properties of rational choice. Their relative preference between two original options changed with the introduction of a third, relatively unattractive option. Such context-dependent choice violates the constant-ratio rule. Our subjects increased their relative preference for the more similar of two alternatives, contrary to the similarity hypothesis. The jays also increased their absolute preference for the more similar of two alternatives, in violation of regularity. Thus, the principle of irrelevant alternatives, which assumes that preference between options does not depend on the presence or absence of other options, is violated not only by humans, but also by an invertebrate and a nonhuman vertebrate. These findings contradict the view that nonhuman animals should be immune to such psychological effects and that they should conform with normative accounts, such as rationality or optimal-foraging theory, because their decision-making processes are evolutionarily adaptive. We discuss the potential generality of context-dependent effects and suggest that such effects should be incorporated into decision-making models in behavioral ecology.

IAPV, a bee-affecting virus associated with Colony Collapse Disorder can be silenced by dsRNA ingestion.

Abstract: Colony Collapse Disorder (CCD) has been associated with Israeli acute paralysis virus (IAPV). CCD poses a serious threat to apiculture and agriculture as a whole, due to the consequent inability to provide the necessary amount of bees for pollination of critical crops. Here we report on RNAi-silencing of IAPV infection by feeding bees with double-stranded RNA, as an efficient and feasible way of controlling this viral disease. The association of CCD with IAPV is discussed, as well as the potential of controlling CCD.

An Introduction to Genetic Algorithms

Abstract: From the Publisher: "This is the best general book on Genetic Algorithms written to date. It covers background, history, and motivation; it selects important, informative examples of applications and discusses the use of Genetic Algorithms in scientific models; and it gives a good account of the status of the theory of Genetic Algorithms. Best of all the book presents its material in clear, straightforward, felicitous prose, accessible to anyone with a college-level scientific background. If you want a broad, solid understanding of Genetic Algorithms -- where they came from, what's being done with them, and where they are going -- this is the book. -- John H. Holland, Professor, Computer Science and Engineering, and Professor of Psychology, The University of Michigan; External Professor, the Santa Fe Institute. Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics -- particularly in machine learning, scientific modeling, and artificial life -- and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.

Bee declines driven by combined stress from parasites, pesticides, and lack of flowers

Abstract: Bees are subject to numerous pressures in the modern world. The abundance and diversity of flowers has declined, bees are chronically exposed to cocktails of agrochemicals, and they are simultaneously exposed to novel parasites accidentally spread by humans. Climate change is likely to exacerbate these problems in the future. Stressors do not act in isolation; for example pesticide exposure can impair both detoxification mechanisms and immune responses, rendering bees more susceptible to parasites. It seems certain that chronic exposure to multiple, interacting stressors is driving honey bee colony losses and declines of wild pollinators, but such interactions are not addressed by current regulatory procedures and studying these interactions experimentally poses a major challenge. In the meantime, taking steps to reduce stress on bees would seem prudent; incorporating flower-rich habitat into farmland, reducing pesticide use through adopting more sustainable farming methods, and enforcing effective quarantine measures on bee movements are all practical measures that should be adopted. Effective monitoring of wild pollinator populations is urgently needed to inform management strategies into the future.

Response diversity, ecosystem change, and resilience

Abstract: Biological diversity appears to enhance the resilience of desirable ecosystem states, which is required to secure the production of essential ecosystem services. The diversity of responses to environmental change among species contributing to the same ecosystem function, which we call response diversity, is critical to resilience. Response diversity is particularly important for ecosystem renewal and reorganization following change. Here we present examples of response diversity from both terrestrial and aquatic ecosystems and across temporal and spatial scales. Response diversity provides adaptive capacity in a world of complex systems, uncertainty, and human-dominated environments. We should pay special attention to response diversity when planning ecosystem management and restoration, since it may contribute considerably to the resilience of desired ecosystem states against disturbance, mismanagement, and degradation.

The effects of fishing on marine ecosystems

Abstract: We review the effects of fishing on benthic fauna, habitat, diversity, community structure and trophic interactions in tropical, temperate and polar marine environments and consider whether it is possible to predict or manage fishing-induced changes in marine ecosystems Such considerations are timely given the disillusionment with some fishery management strategies and that policy makers need a scientific basis for deciding whether they should respond to social, economic and political demands for instituting or preventing ecosystem-based management Fishing has significant direct and indirect effects on habitat, and on the diversity, structure and productivity of benthic communities These effects are most readily identified and last longest in those areas that experience infrequent natural disturbance The initiation of fishing in an unfished system leads to dramatic changes in fish community structure As fishing intensity increases the additional effects are more difficult to detect Fishing has accelerated and magnified natural declines in the abundance of many forage fishes and this has lead to reduced reproductive success and abundance in birds and marine mammals However, such donor-controlled dynamics are less apparent in food webs where fishes are the top predators since their feeding strategies are rather more plastic than those of most birds and mammals Fishers tend to target species in sequence as a fishery develops and this leads to changes in the composition of the fished communities with time The dramatic and apparently compensatory shifts in the biomass of different species in many fished ecosystems have often been driven by environmental change rather than the indirect effects of fishing Indeed, in most pelagic systems, species replacements would have occurred, albeit less rapidly, in the absence of fishing pressure In those cases when predator or prey species fill a key role, fishing can have dramatic indirect effects on community structure Thus fishing has shifted some coral reef ecosystems to alternate stable states because there is tight predator–prey coupling between invertebrate feeding fishes and sea urchins Fishing has reduced, and locally extirpated, populations of predatory fishes These reductions do not have a consistent effect on the abundance and diversity of their prey: environmental processes control prey populations in some systems, whereas top-down processes are more important in others By-catch which is discarded during fishing activities may sustain populations of scavenging species, particularly seabirds We conclude by identifying the circumstances in which new research is needed to guide managers and stress the importance of unfished control sites for studies of fishing effects We discuss the advantages and disadvantages of closed area management (marine reserves) and the conditions under which such management is likely to provide benefits for the fishery or ecosystem

Individual-based modeling and ecology

Abstract: Individual-based modeling is a new, exciting discipline that allows ecologists to explore, using computer simulations, how properties of populations and ecosystems might evolve from the characteristics and behaviors of individual organisms. Individual-based Modeling and Ecology, written by Volker Grimm and Steven F. Railsback, gives an excellent introduction and overview of this field. It should be read by everyone interested in individual-based modeling, and especially by anyone contemplating developing, or being involved with a group developing, an individualbased model.