A Hawk-Dove game in kleptoparasitic populations

Kleptoparasitism, the parasitism by theft, is a widespread biological phenomenon. In this paper we extend earlier models to investigate a population of conspecifics involved in foraging and, potentially, kleptoparasitism. We assume that the population is composed of two types of individuals, Hawks and Doves. The types differ according to their strategic choices when faced with an opportunity to steal and to resist a challenge. Hawks use every opportunity to steal and they resist all challenges. Doves never resist and never steal. The fitness of each type of individual depends upon various natural parameters, for example food density, the handling time of a food item, density of the population, as well as the duration of potential fights over the food. We find the Evolutionarily Stable States (ESSs) for all arameter combinations and show that there are three possible ESSs, pure Hawks, pure Doves, and a mixed population of Hawks and Doves. We show that for any set of parameter values there is exactly one ESS. We further investigate the relationship between our findings and the classical Hawk-Dove game as defined in Maynard Smith 1982. We also show how our model extends the classical on

vol 1 no 1_information page

This page provides some basic journal information (the constitution of the international editorial board of the journal, the identity of itsl publisher, its emphasis, coverage and orientation, etc.)

MS-175: Kate Burr Whiting Travel Journal

This collection consists one of one 177 page travel journal, with 136 images included. A letter from 1928 is also included with the journal. The photographs document all the places Kate Burr Whiting traveled around the world. Special Collections and College Archives Finding Aids are discovery tools used to describe and provide access to our holdings. Finding aids include historical and biographical information about each collection in addition to inventories of their content. More information about our collections can be found on our website http://www.gettysburg.edu/special_collections/collections/.https://cupola.gettysburg.edu/findingaidsall/1144/thumbnail.jp

Extension Education: How do we learn best?

Due to the rise of new educational methods, one may begin to wonder, what is the best way to learn information? Can these new methods truly replace traditional methods? This experiment evaluated the effectiveness of an infographic to a text based on amount of information retained and personal preference. This study also examines if professional status has an effect on information retention. In order to answer these questions, subjects were given a copy of an infographic and a journal article covering the same information. The subjects were then given 5 minutes to look over both materials and to answer four comprehensive questions. After completing this portion, the subjects were then asked to complete a survey analyzing the effectiveness of the methods and their personal preferences. The results yielded that an infographic is a better than a journal article for distributing information to both students and extension personnel

Construction of a Pragmatic Base Line for Journal Classifications and Maps Based on Aggregated Journal-Journal Citation Relations

A number of journal classification systems have been developed in bibliometrics since the launch of the Citation Indices by the Institute of Scientific Information (ISI) in the 1960s. These systems are used to normalize citation counts with respect to field-specific citation patterns. The best known system is the so-called "Web-of-Science Subject Categories" (WCs). In other systems papers are classified by algorithmic solutions. Using the Journal Citation Reports 2014 of the Science Citation Index and the Social Science Citation Index (n of journals = 11,149), we examine options for developing a new system based on journal classifications into subject categories using aggregated journal-journal citation data. Combining routines in VOSviewer and Pajek, a tree-like classification is developed. At each level one can generate a map of science for all the journals subsumed under a category. Nine major fields are distinguished at the top level. Further decomposition of the social sciences is pursued for the sake of example with a focus on journals in information science (LIS) and science studies (STS). The new classification system improves on alternative options by avoiding the problem of randomness in each run that has made algorithmic solutions hitherto irreproducible. Limitations of the new system are discussed (e.g. the classification of multi-disciplinary journals). The system's usefulness for field-normalization in bibliometrics should be explored in future studies.Comment: accepted for publication in the Journal of Informetrics, 20 July 201