Short-Term Activity Cycles in Leptothorax Ants
{'Code': '08090200', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
{'SignBlockName': 'Fred Stollnitz', 'PO_EMAI': None, 'PO_PHON': None}
A fundamental problem in the study of behavior is the emergence                 of complexity of social behavior from the behavior of individuals               within the social unit.  If the characteristics of a social group               can be accounted for by the summed actions of individuals, then                 social behavior is a resultant of individual behavior.  If the                  characteristics of a group are not simply due to the summed                     actions of individuals, then social behavior has an emergent                    property.                                                                                                                                                       Social insects are well known to have attributes of the colony                  that are not present among the individuals comprising the colony.               The activity of a colony is basic to all its other behavior.  Dr.               Cole has discovered that activity within nests of a species of                  ant, Leptothorax allardycei, has short-term cycles, with pulses                 of activity occurring at intervals of approximately 20 minutes.                 Individual, isolated ants do not show this regularity of                        activity, but the periodicity emerges as more and more ants are                 added to the aggregate.                                                                                                                                         The purpose of this research project is to analyze the production               of periodicity in colonies from the behavior and movement                       patterns of individual ants.  Dr. Cole will develop a computer                  model of the movement patterns of individual ants, including                    their velocity of movement, turning angles, and position within                 the nest that they occupy.  This information will be combined                   with information on their response to encounters with other ants,               the effect of an encounter on the probability of subsequent                     activity by an individual ant, and mutual synchronization of                    activity to produce a computer model of the activity of a colony.               This model will be tested by direct manipulation of the activity                of colonies through the use of alarm pheromones.                                                                                                                Dr. Cole's research is an important step toward gaining an                      understanding of the mechanisms by which the individuals within a               social unit produce social phenomena.  Until we understand the                  mechanisms of social interaction, it will remain impossible to                  predict the consequences of group living and the effects of                     natural selection on social behavior.
{'FirstName': 'Blaine', 'LastName': 'Cole', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Blaine J Cole', 'EmailAddress': 'BCOLE@UH.EDU', 'NSF_ID': '000409176', 'StartDate': '09/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Virginia Main Campus', 'CityName': 'CHARLOTTESVILLE', 'ZipCode': '229034833', 'PhoneNumber': '4349244270', 'StreetAddress': '1001 EMMET ST N', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'VA05', 'ORG_UEI_NUM': 'JJG6HU8PA4S5', 'ORG_LGL_BUS_NAME': 'RECTOR & VISITORS OF THE UNIVERSITY OF VIRGINIA', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '1160', 'Text': 'IBN ANIMAL BEHAVIOR'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8808973.xml'}