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The biology and oceanography of Atla...
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Teo, Steven Lip Heng.
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The biology and oceanography of Atlantic bluefin tuna on their breeding grounds.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
The biology and oceanography of Atlantic bluefin tuna on their breeding grounds./
作者:
Teo, Steven Lip Heng.
面頁冊數:
238 p.
附註:
Source: Dissertation Abstracts International, Volume: 67-09, Section: B, page: 4905.
Contained By:
Dissertation Abstracts International67-09B.
標題:
Biology, Ecology. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3235365
ISBN:
9780542896026
The biology and oceanography of Atlantic bluefin tuna on their breeding grounds.
Teo, Steven Lip Heng.
The biology and oceanography of Atlantic bluefin tuna on their breeding grounds.
- 238 p.
Source: Dissertation Abstracts International, Volume: 67-09, Section: B, page: 4905.
Thesis (Ph.D.)--Stanford University, 2006.
Electronic tags and remote-sensing data were used to examine the biology, migrations, and oceanography of Atlantic bluefin tuna (ABFT), Thynnus thunnus, on their breeding grounds in the Gulf of Mexico (GOM). The ABFT's geolocations were determined using an algorithm developed to calculate light-level longitudes and sea surface temperature (SST) based latitudes. Double-tagging experiments with blue and salmon sharks, and ABFT demonstrated that light-level longitudes had root mean square errors (RMSEs) of 0.55--1.30°, while SST latitudes had RMSEs of 0.90--1.89°.
ISBN: 9780542896026Subjects--Topical Terms:
1017726
Biology, Ecology.
The biology and oceanography of Atlantic bluefin tuna on their breeding grounds.
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Electronic tags and remote-sensing data were used to examine the biology, migrations, and oceanography of Atlantic bluefin tuna (ABFT), Thynnus thunnus, on their breeding grounds in the Gulf of Mexico (GOM). The ABFT's geolocations were determined using an algorithm developed to calculate light-level longitudes and sea surface temperature (SST) based latitudes. Double-tagging experiments with blue and salmon sharks, and ABFT demonstrated that light-level longitudes had root mean square errors (RMSEs) of 0.55--1.30°, while SST latitudes had RMSEs of 0.90--1.89°.
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Movement patterns, diving behavior, and thermal biology of ABFT changed significantly on their breeding grounds. The ABFT experienced significantly warmer mean SSTs within the GOM (26.4 +/- 1.6 °C) than outside (20.2 +/- 1.9 °C). As ABFT entered and exited the GOM, they exhibited daily maximum depths of 568 +/- 50 and 580 +/- 144 m respectively, and directed movement paths. Breeding phase ABFT exhibited significantly shallower daily maximum depths (203 +/- 76 m), shallow oscillatory nighttime dives, and significantly more residential movement paths. Heat transfer coefficients of ABFT increased at high temperatures and were significantly higher in the nighttime breeding phase. These results indicate electronic tags can be used to define spawning time and location.
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Habitat use patterns of breeding ABFT were significantly affected by bathymetry, SST, eddy kinetic energy (EIRE), sea surface height anomaly (SSHA), and surface chlorophyll concentration. Breeding ABFT preferred areas on the continental slope (>200m), with SSTs from 24--29°C and low surface chlorophyll concentrations (0.11 to 0.15 mg m-3). The ABFT also preferred areas with moderate EIRE (266 to 422 cm2 s-2) and negative SSHA, indicating a preference for cyclonic mesoscale eddies. These results can be used to predict the breeding areas of ABFT and improve the capacity for managers and fishers to discern how best to lower interaction probability and aid population recovery.
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A novel method was developed to estimate in situ chlorophyll concentrations from light-level and pressure data from archival tags. Tag deployments at 14 oceanographic stations indicated that the RMSE between tag-estimated and filtered water chlorophyll concentrations was 0.088 mg m-3. Most chlorophyll maxima depths (82.4%) concentrations (91.8%) estimated from archival tags deployed on Pacific bluefin tuna were within the 95% confidence intervals of the World Ocean Database.
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