Every form of behavior is shaped by trial and error. Such stepwise adaptation can occur through individual learning or through natural selection, the basis of evolution. Since the work of Maynard Smith and others, it has been realized how game theory can model this process. Evolutionary game theory replaces the static solutions of classical game theory by a dynamical approach centered not on the concept of rational players but on the population dynamics of behavioral programs. In this book the authors investigate the nonlinear dynamics of the self-regulation of social and economic behavior, and of the closely related interactions among species in ecological communities. Replicator equations describe how successful strategies spread and thereby create new conditions that can alter the basis of their success, i.e., to enable us to understand the strategic and genetic foundations of the endless chronicle of invasions and extinctions that punctuate evolution. In short, evolutionary game theory describes when to escalate a conflict, how to elicit cooperation, why to expect a balance of the sexes, and how to understand natural selection in mathematical terms.

 Comprehensive treatment of ecological and game theoretic dynamics
 Invasion dynamics and permanence as key concepts
 Explanation in terms of games of things like competition between species

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Evolutionary games and population dynamics

Fast and frugal heuristics - simple rules for making decisions with realistic mental resources - are presented here. These heuristics can enable both living organisms and artificial systems to make smart choices, classifications, and predictions by employing bounded rationality. But when and how can such fast and frugal heuristics work? What heuristics are in the mind's adaptive toolbox, and what building blocks compose them? Can judgments based simply on a single reason be as accurate as those based on many reasons? Could less knowledge even lead to systematically better predictions than more knowledge? This book explores these questions by developing computational models of heuristics and testing them through experiments and analysis. It shows how fast and frugal heuristics can yield adaptive decisions in situations as varied as choosing a mate, dividing resources among offspring, predicting high school drop-out rates, and playing the stock market.

Simple Heuristics That Make Us Smart

Current methods of evaluating wildlife habitat for management purposes can be arranged in a hierarchy of increasing generality. The most general level is evaluation of wildlife habitat for entire com- munities on the basis of inferences drawn from vegetational structure. At the base of the hierarchy the high resolution studies, upon which accuracy at the higher hierarchical levels depends, usually assume that habitat quality for a species is positively correlated with the density of the species. If habitat quality for a wildlife species is a measure of the importance of habitat type in maintaining a particular species, habitat quality should be defined in terms of the survival and production characteristics, as well as the density, of the species occupying that habitat. Situations in which habitat quality thus defined is not expected to be positively correlated with density are described, along with the species and environmental characteristics that are most likely to produce these situations. Examples drawn from the literature in which density and habitat quality are not positively correlated are described. The positive correlation of density with habitat quality in specific instances cannot be assumed without supporting demographic data. J. WILDL. MANAGE. 47(4):893-901 The foundation of any wildlife habitat management plan is the ability to assess habitat quality accurately. Without this key ingredient, the effort put into care- fully prepared objectives and elegant cat- egorizations of habitat types is largely wasted. Yet biologists often dwell on ob- jectives and categories while treating lightly the assumptions implicit in their assessments of habitat quality. For in- stance, they seldom question the assump- tion that the density of a species in a hab- itat is a direct measure of the quality of that habitat. Perhaps this is because any more accurate investigation of habitat quality to truly reflect the importance of that habitat in maintaining wildlife species populations must be intensive, often at the expense of the broader information base that could be achieved by simple surveys. Such surveys are a particularly common means of evaluating nongame wildlife habitat. The objectives of this paper are to pro- vide some examples of situations in which this correlation does not hold, and to make predictions regarding species and envi- ronmental types for which the density- habitat quality relationship is likely to be decoupled. In such cases, management policies based directly on species abun- dance may be misleading and these errors may be amplified when management ap- proaches are restricted to the higher levels of the hierarchy. This paper is dedicated to the late 0. C. Wallmo, who was always eager to dis- cuss ideas and whose refusal to be any- thing but completely honest in evaluating his own ideas, objectives, and research ideas, as well as those of others, set an example for us to follow.

http://floridarivers.ifas.ufl.edu/ecological stats/2008/van horne 1983.pdf

Density as a misleading indicator of habitat quality

Movement of individual organisms is fundamental to life, quilting our planet in a rich tapestry of phenomena with diverse implications for ecosystems and humans. Movement research is both plentiful and insightful, and recent methodological advances facilitate obtaining a detailed view of individual movement. Yet, we lack a general unifying paradigm, derived from first principles, which can place movement studies within a common context and advance the development of a mature scientific discipline. This introductory article to the Movement Ecology Special Feature proposes a paradigm that integrates conceptual, theoretical, methodological, and empirical frameworks for studying movement of all organisms, from microbes to trees to elephants. We introduce a conceptual framework depicting the interplay among four basic mechanistic components of organismal movement: the internal state (why move?), motion (how to move?), and navigation (when and where to move?) capacities of the individual and the external factors affecting movement. We demonstrate how the proposed framework aids the study of various taxa and movement types; promotes the formulation of hypotheses about movement; and complements existing biomechanical, cognitive, random, and optimality paradigms of movement. The proposed framework integrates eclectic research on movement into a structured paradigm and aims at providing a basis for hypothesis generation and a vehicle facilitating the understanding of the causes, mechanisms, and spatiotemporal patterns of movement and their role in various ecological and evolutionary processes. "Now we must consider in general the common reason for moving with any movement whatever." (Aristotle, De Motu Animalium, 4th century B.C.).

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A movement ecology paradigm for unifying organismal movement research

Predators and food are the keys to understanding fish shoals; synchronised co-operation defeats predators, and optimal food gathering in shoals reflects a shifting balance between joining, competing in, or leaving the group In the wild, predators may arrive while shoaling fish are feeding, and so vigilance is a crucial behaviour Once detected, predator defence takes precedence over feeding, since an animal’s life is worth more than today’s dinner

Functions of Shoaling Behaviour in Teleosts

This example is provided so that non-theorists may see actual applications of the theory previously described. The Dickcissel sex ratio is employed as an indirect index of suitability. A sex ratio index was found to be correlated positively with density. This is consistent with the hypothesis that territorial behavior in the males of this species limits their density. This study provides a valid example of how the problem can be approached and offers a first step in the eventual identification of the role of territorial behavior in the habitat distribution of a common species.

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On territorial behavior and other factors influencing habitat distribution in birds

/pdf/on-territorial-behavior-and-other-factors-influencing-2j03gxcqng.pdf

James Stevan Calver

Papers

On territorial behavior and other factors influencing habitat distribution in birds

On territorial behavior and other factors influencing habitat distribution in birds: II. Sex ratio variation in the Dickcissel (Spiza americana Gmel)