{"@context":"http://iiif.io/api/presentation/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/manifest.json","@type":"sc:Manifest","label":"Quantitative foraging ecology of terns at Great Gull Island, New York: Theory, models, and remote sensing of collective behavior in a dynamic habitat","metadata":[{"label":"dc.description.sponsorship","value":"This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree."},{"label":"dc.format","value":"Monograph"},{"label":"dc.format.medium","value":"Electronic Resource"},{"label":"dc.identifier.uri","value":"http://hdl.handle.net/11401/78261"},{"label":"dc.language.iso","value":"en_US"},{"label":"dcterms.abstract","value":"Most seabirds forage for prey whose distributions are patchy and unpredictable, and their strategies for locating food have long interested ecologists. Recent studies using individual telemetry have yielded many insights, but our understanding is still limited: simultaneous measurements of prey and predator distributions are rare, and tracking tags can be deployed on only small numbers of animals at once. I addressed these challenges using a marine radar deployed at a breeding colony of common and roseate terns (Sterna hirundo and S. dougallii) on Great Gull Island, New York, in 2014 and 2015. I calibrated the radar, enabling measurements of tern radar cross-sections, which in turn allowed the number of birds in a flock to be estimated remotely by echo integration. The distribution of feeding flocks around the colony was mapped by radar, and the terns' prey and tidal currents were measured using acoustic instruments on small boats. These high-resolution data let me identify and model the terns' important foraging habitat: where tidal currents accelerated and diverged over shallow topography. I also developed methods to identify and track individual terns in the radar data. Analysis of hundreds of thousands of tern tracks showed the terns' directions of departure and return from the colony shifted between days, weeks, and years. By analyzing the relative timing of outbound and inbound traffic, distant foraging areas could be tentatively identified; these generally agreed with the habitat model's predictions. Finally, several mechanisms for information transfer between foraging terns were investigated. I showed theoretically that one of these behaviors, trail following, should provide more accurate guidance to food patches. This prediction was confirmed in an individual-based simulation model, and evidence for trail following was found in the flight patterns of the terns. These findings may have conservation value, for instance in planning human activities such as offshore wind energy installations to avoid harm to terns. They also open exciting new possibilities for studies linking the behaviors of individual seabirds to the dynamic distribution of their populations as a whole."},{"label":"dcterms.available","value":"2018-06-21T13:38:46Z"},{"label":"dcterms.contributor","value":"Larkin, Ronald P"},{"label":"dcterms.creator","value":"Urmy, Samuel Stetson"},{"label":"dcterms.dateAccepted","value":"2018-06-21T13:38:46Z"},{"label":"dcterms.dateSubmitted","value":"2018-06-21T13:38:46Z"},{"label":"dcterms.description","value":"Department of Marine and Atmospheric Science"},{"label":"dcterms.extent","value":"172 pg."},{"label":"dcterms.format","value":"Application/PDF"},{"label":"dcterms.identifier","value":"http://hdl.handle.net/11401/78261"},{"label":"dcterms.issued","value":"2017-12-01"},{"label":"dcterms.language","value":"en_US"},{"label":"dcterms.provenance","value":"Made available in DSpace on 2018-06-21T13:38:46Z (GMT). No. of bitstreams: 1\nUrmy_grad.sunysb_0771E_13521.pdf: 15187582 bytes, checksum: 3ee1ce8f47b4b3bddd796dcc4337636a (MD5)\n  Previous issue date:   12"},{"label":"dcterms.subject","value":"Ecology"},{"label":"dcterms.title","value":"Quantitative foraging ecology of terns at Great Gull Island, New York: Theory, models, and remote sensing of collective behavior in a dynamic habitat"},{"label":"dcterms.type","value":"Dissertation"},{"label":"dc.type","value":"Dissertation"}],"description":"This manifest was generated dynamically","viewingDirection":"left-to-right","sequences":[{"@type":"sc:Sequence","canvases":[{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json","@type":"sc:Canvas","label":"Page 1","height":1650,"width":1275,"images":[{"@type":"oa:Annotation","motivation":"sc:painting","resource":{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/11%2F67%2F97%2F116797867167149762094515847861955075905/full/full/0/default.jpg","@type":"dctypes:Image","format":"image/jpeg","height":1650,"width":1275,"service":{"@context":"http://iiif.io/api/image/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/11%2F67%2F97%2F116797867167149762094515847861955075905","profile":"http://iiif.io/api/image/2/level2.json"}},"on":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json"}]}]}]}