Fine Scale Foraging Behavior of Gray Whales in Relation to Prey Fields and Vessel Disturbance Along the Oregon Coast Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/tb09jb334

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  • The desire to understand the spatial and temporal drivers of animal behavior and distribution relative to scale is central to movement ecology. Optimal foraging theory states that a predator should continue exploiting a patch until it is no longer profitable to do so. As human developments increasingly encroach on the marine environment, understanding how anthropogenic interactions affect predator searching and foraging behaviors is key to minimizing disturbance. In 2015 and 2016, two studies were conducted to assess how gray whale behavior state changes (1) relative to static and dynamic environmental cues, and (2) relative to vessel interactions. The first study was addressed through the non-invasive documentation of gray whale movements (n = 76 tracks) using shore-based theodolites for eight weeks from July-August 2016, in Port Orford, Oregon, USA. When conditions allowed, a research kayak was concurrently navigated to 18 sampling stations in two comparative study sites (Mill Rocks and Tichenor Cove) within the study area. Go-Pro cameras were used to record zooplankton relative density in the water column (n=198 casts), and zooplankton net tows (n=107) were used to assess community structure. Video stills were scored for quality and relative density of zooplankton, and averaged through the water column to provide a daily density estimate of zooplankton density for each station. Whale behaviors were categorized into search, forage, and transit using the Residence in Space and Time (RST) method; behavior state was then assessed relative to static and dynamic variables at multiple scales. Despite being only one kilometer apart, there were significant spatio-temporal differences in the community assemblages of zooplankton between the two study areas, and whales demonstrated scale-dependent habitat selection relative to predictable static features (kelp) and dynamic prey availability. In Tichenor Cove, mysids (Holmesimysis sculpta), a known regional gray whale prey item, dominated the community, yet whales spent little time foraging here. Whales preferentially foraged in Mill Rocks where a combination of mysids and gammarid amphipods, previously undocumented as gray whale prey in Oregon, were prevalent. The second study occurred in the summer of 2015, and tracked whales and vessels using non-invasive, shore based theodolite and photo ID techniques. Two sites with differing levels of vessel traffic, Boiler Bay and Port Orford, were monitored for 4 weeks each. Whale focal follows were again analyzed with RST to assess behavior state changes relative to location, individual, and vessel presence, type, and distance to whale. There were significant differences in population level gray whale activity budgets between control and impact conditions, and between study sites. No significant difference in individual response to vessels disturbance was found. Taken together, the results of these two studies show that gray whales maximize energy gain through predictable, successful foraging. In the absence of vessels, foraging gray whales use information from a static feature and prey availability at a fine scale (<0.5 km) and larger regional scale (1-2 km), but searching behavior may be influenced by these features in a scale-dependent manner. When a vessel is present, disturbance appears to be tolerated as long as the foraging is profitable. Multi-faceted studies such as these advance the knowledge of which factors inform fine scale predator decision making in an increasingly anthropogenically impacted environment and have the potential to inform local management and conservation efforts.
  • The desire to understand the spatial and temporal drivers of animal behavior and distribution relative to scale is central to movement ecology. Optimal foraging theory states that a predator should continue exploiting a patch until it is no longer profitable to do so. As human developments increasingly encroach on the marine environment
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  • description.provenance : Rejected by Julie Kurtz(julie.kurtz@oregonstate.edu), reason: Hi Florence, I need to reject your thesis because of the page numbering. You thesis starts on page 12 and the introduction should start on page 1. Also the last few pages do not have pages numbers. The pretext pages are correct without page numbers. Everything else looks good. Once revised, log back into ScholarsArchive and go to the upload page. Replace the attached file with the revised PDF and resubmit. Thanks, Julie on 2017-06-25T00:32:12Z (GMT)
  • description.provenance : Submitted by Florence Sullivan (vantuldf@oregonstate.edu) on 2017-06-16T09:33:15Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: bb87e2fb4674c76d0d2e9ed07fbb9c86 (MD5) SullivanFlorenceA2017.pdf: 1636545 bytes, checksum: 5eecc8e494c8efdbf2c00599f8a7be56 (MD5)
  • description.provenance : Made available in DSpace on 2017-06-28T20:59:50Z (GMT). No. of bitstreams: 2 license_rdf: 1223 bytes, checksum: d127a3413712d6c6e962d5d436c463fc (MD5) SullivanFlorenceA2017_v2.pdf: 1013838 bytes, checksum: 2d250b646299d9f90d7328fcef672619 (MD5) Previous issue date: 2017-06-02
  • description.provenance : Submitted by Florence Sullivan (vantuldf@oregonstate.edu) on 2017-06-27T06:11:53Z No. of bitstreams: 2 license_rdf: 1223 bytes, checksum: d127a3413712d6c6e962d5d436c463fc (MD5) SullivanFlorenceA2017_v2.pdf: 1013838 bytes, checksum: 2d250b646299d9f90d7328fcef672619 (MD5)
  • description.provenance : Approved for entry into archive by Steven Van Tuyl(steve.vantuyl@oregonstate.edu) on 2017-06-28T20:59:50Z (GMT) No. of bitstreams: 2 license_rdf: 1223 bytes, checksum: d127a3413712d6c6e962d5d436c463fc (MD5) SullivanFlorenceA2017_v2.pdf: 1013838 bytes, checksum: 2d250b646299d9f90d7328fcef672619 (MD5)
  • description.provenance : Approved for entry into archive by Julie Kurtz(julie.kurtz@oregonstate.edu) on 2017-06-27T21:18:14Z (GMT) No. of bitstreams: 2 license_rdf: 1223 bytes, checksum: d127a3413712d6c6e962d5d436c463fc (MD5) SullivanFlorenceA2017_v2.pdf: 1013838 bytes, checksum: 2d250b646299d9f90d7328fcef672619 (MD5)

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