Classical experiments on honey bee time-memory showed that foragers trained to collect food at a fixed time of day return the following day with a remarkable degree of time-accuracy. A series of field experiments revealed that not all foragers return to a food source on unrewarded test days. Rather, there exist two subgroups: \"persistent\" foragers reconnoiter the source; \"reticent\" foragers wait in the hive for confirmation of source availability. A forager's probability of being persistent is dependent both on the amount of experience it has had at the source and the environmental conditions present, but the probability is surprisingly high (0.4-0.9). Agent-based simulation of foraging behavior indicated these high levels of persistence represent an energetically optimal strategy, which is likely a compromise solution to an ever-changing environment. Time-memory, with its accompanying anticipation, enables foragers to improve time-accuracy, quickly reactivating the foraging group to more efficiently exploit a food source.
","abstract_html":"<p>Classical experiments on honey bee time-memory showed that foragers trained to collect food at a fixed time of day return the following day with a remarkable degree of time-accuracy. A series of field experiments revealed that not all foragers return to a food source on unrewarded test days. Rather, there exist two subgroups: "persistent" foragers reconnoiter the source; "reticent" foragers wait in the hive for confirmation of source availability. A forager's probability of being persistent is dependent both on the amount of experience it has had at the source and the environmental conditions present, but the probability is surprisingly high (0.4-0.9). Agent-based simulation of foraging behavior indicated these high levels of persistence represent an energetically optimal strategy, which is likely a compromise solution to an ever-changing environment. Time-memory, with its accompanying anticipation, enables foragers to improve time-accuracy, quickly reactivating the foraging group to more efficiently exploit a food source.</p>","abstract_has_math":false,"creators":["Van Nest, Byron N."],"institution":null,"degree_name":"MS (Master of Science)","degree_level":"Thesis - restricted","degree_discipline":"Biology","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010-05-08T07:00:00Z","date_published":"2010-05-08T07:00:00Z","updated_at":"2026-07-24T02:20:42Z","subjects":["agent-based model","social insects","food-anticipatory activity","foraging","Apis mellifera","time-memory","Behavior and Ethology","Ecology and Evolutionary Biology","Entomology","Life Sciences"],"languages":[],"rights":["Copyright by the authors."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dc.etsu.edu/etd/1709","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Van Nest, Byron N."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2010-05-08T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Biology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - restricted"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS (Master of Science)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["agent-based model","social insects","food-anticipatory activity","foraging","Apis mellifera","time-memory","Behavior and Ethology","Ecology and Evolutionary Biology","Entomology","Life Sciences"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Copyright by the authors."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dc.etsu.edu/context/etd/article/3064/viewcontent/VanNestB041510f.pdf","https://dc.etsu.edu/etd/1709"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Classical experiments on honey bee time-memory showed that foragers trained to collect food at a fixed time of day return the following day with a remarkable degree of time-accuracy. A series of field experiments revealed that not all foragers return to a food source on unrewarded test days. Rather, there exist two subgroups: \"persistent\" foragers reconnoiter the source; \"reticent\" foragers wait in the hive for confirmation of source availability. A forager's probability of being persistent is dependent both on the amount of experience it has had at the source and the environmental conditions present, but the probability is surprisingly high (0.4-0.9). Agent-based simulation of foraging behavior indicated these high levels of persistence represent an energetically optimal strategy, which is likely a compromise solution to an ever-changing environment. Time-memory, with its accompanying anticipation, enables foragers to improve time-accuracy, quickly reactivating the foraging group to more efficiently exploit a food source.
"]},{"key":"dc:title","label":"Title","values":["Time-Memory Behavior Yields Energetically Optimal Foraging Strategy in Honey Bees."]}]}],"canonical_facts":{"dc:creator":["Van Nest, Byron N."],"dc:date.issued":["2010-05-08T07:00:00Z"],"dc:description.abstract":["Classical experiments on honey bee time-memory showed that foragers trained to collect food at a fixed time of day return the following day with a remarkable degree of time-accuracy. A series of field experiments revealed that not all foragers return to a food source on unrewarded test days. Rather, there exist two subgroups: \"persistent\" foragers reconnoiter the source; \"reticent\" foragers wait in the hive for confirmation of source availability. A forager's probability of being persistent is dependent both on the amount of experience it has had at the source and the environmental conditions present, but the probability is surprisingly high (0.4-0.9). Agent-based simulation of foraging behavior indicated these high levels of persistence represent an energetically optimal strategy, which is likely a compromise solution to an ever-changing environment. Time-memory, with its accompanying anticipation, enables foragers to improve time-accuracy, quickly reactivating the foraging group to more efficiently exploit a food source.
"],"dc:identifier":["https://dc.etsu.edu/context/etd/article/3064/viewcontent/VanNestB041510f.pdf","https://dc.etsu.edu/etd/1709"],"dc:rights":["Copyright by the authors."],"dc:subject":["agent-based model","social insects","food-anticipatory activity","foraging","Apis mellifera","time-memory","Behavior and Ethology","Ecology and Evolutionary Biology","Entomology","Life Sciences"],"dc:title":["Time-Memory Behavior Yields Energetically Optimal Foraging Strategy in Honey Bees."],"thesis:degree_discipline":["Biology"],"thesis:degree_level":["Thesis - restricted"],"thesis:degree_name":["MS (Master of Science)"]},"updated_at":"2026-07-24T02:20:42Z"}