Assessment of seasonal and individual Steller sea lion body condition and population trends

The polar regions cover areas of intense biological interest. The southern circumpolar seas have been fairly untouched by commercial enterprises and remain one of the few ecosystems subjected to comparatively little impact from human activities. Conversely, arctic regions around and including the Bering Sea comprise delicate ecosystems threatened by profound regime shifts. The Bering Sea region represents one of the biologically and economically most important ecosystems in the United States, providing over 5% of fish and shellfish catches in a multi-billion dollar industry. In a troubling development, most apex predators in this ecosystem have exhibited dramatic population declines over the past three decades. Steller sea lions, as one such species have declined to less than 15% of peak population levels and are currently listed as endangered in the western portion of their range (along the Aleutian Islands and in the Bering Sea). Northern fur seals, harbor seals and several seabird species have exhibited less dramatic but nonetheless severe declines. Extensive removal of fish biomass through commercial trawling has been hypothesized as one possible factor involved in the decline of Aleutian and Bering Sea pinnipeds. Despite years of intense research efforts by many agencies and institutions, no conclusive data exists to shed light on the hypothesized link between commercial fisheries, nutritional stress and reduced reproductive output of pinnipeds, or to allow for analysis of proximate mechanisms linking hypothesized cause and effect. Significant fisheries management decisions are being made under scarcity of adequate data. This lack of vital data on polar pinnipeds and seabirds encompasses some of the most basic life-history information:

  • Year-round population census figures of sufficient spatial and temporal resolution, including details on the age structures of populations.
  • Body mass and body condition estimates, both in form of longitudinal data from individual animals and cross-sectional data for meta populations.
  • Year-round detailed foraging behavior data of sufficient temporal and spatial resolution to accurately assess fisheries interactions.

Several reasons can be listed for this lack of conclusive data. The species of interest reside in very remote and inaccessible locations in predominantly extreme environments. They include some of the most difficult marine mammal and seabird species to work with, partly on account of their extreme shyness and sensitivity to disturbances. Rookeries and haulouts are difficult to approach, let alone land on, frequently impossible on a repeated basis. Most observations have been limited to the reproductive season during local summer.

Present State of Technology

Traditionally, two types of telemetry approaches have been used on polar pinniped and seabird species. Aerial photography has been used in arctic regions for most pinniped stock assessments and population monitoring. In remote island areas with frequent dense cloud covers, such an approach is extremely costly and dangerous while delivering data of limited accuracy. The reduced accuracy is a result of the two most common problems in aerial or remote imaging census operations: redundant animal counting from overlapping images, and animals being obscured from given perspectives. Frequently only one or two assessments can be done per year.

To address these shortcomings, we have pursued several innovations in telemetry of seals and sea lions.  In our Life History Transmitter project we have developed new transmitters to allow remote monitoring of individual animals over their entire life.  In the SLiDAP technical development project, we pursued technology to remotely monitor seals and sea lions at their rookeries and haul-outs.  The combination of these approaches will allow us to collect a majority of the vital data described above.

The SLiDAP project has two components, the technical development component and the research component.

The SLiDAP Technical Development Project

This portion of the project has been completed. The goal of the SLiDAP technical development project was the design and implementation of a local area imaging network for polar regions that is remotely accessible via satellite high-speed data link. The SLiDAP network is described in:

Plankis, B., M. Horning, N. Ponto and L. Brown. 2007. Designing a dependable and fault-tolerant semiautonomous distributed cotrol data collection network with opportunistic hierarchy. IEEE Journal of Oceanic Engineering. 32(2): 400-407. 

The primary purpose of this imaging network is the performance of close-range 3-D photogrammetry for the remote determination of accurate spatial dimensions. By incorporating 3-D photogrammetry into the imaging system, we are transforming remote, close-range imaging from a simple observational tool into a sophisticated quantitative tool for the accurate assessment of biological and physical systems in extreme environments. In a novel approach, we are using remote 3-D photogrammetry to significantly increase temporal resolution and numerical accuracy of remote census operations.  This will determine the age structure within pinniped rookeries through measurements of animals' length and use photogrammetric volume determinations as estimators of body mass. The 3-D photogrammetric techniques have been validated by our laboratories as described in:

 Waite, J., W. Schrader, J. Mellish and M. Horning. 2007. Three-dimensional photogrammetry as a tool for estimating morphometrics and body mass of Steller sea lions (Eumetopias jubatus). Canadian Journal of Fiheries & Aquatic Sciences. 64: 296-303.

The SLiDAP Research Project

We are refining the photogrammetric remote estimation of body mass and condition of Steller sea lions using wild animals temporarily held at the Alaska Sea Life Center. We will install remote SLiDAP systems at multiple locations in Alaska and along the Pacific Northwest coast. We will use these SLiDAP systems to collect detailed, year-round census data. We will estimate by 3-D photogrammetry the body mass and condition trends at monitoring locations, both cross-sectional and longitudinal, throughout the year. This project is led by the Pinniped Ecology Applied Research Laboratory, in cooperation with the National Marine Mammal Laboratory (NMML) and the Alaska Sea Life Center (ASLC), bringing together leading academic research and marine resource management laboratories, as well as the industry leaders in telemetry and photogrammetry. Our development and research efforts are designed to enhance basic biological research as well as marine ecosystem management.

The SLiDAP Project has received support from:

The National Science Foundation
NOAA’s National Marine Fisheries Service
The Alaska SeaLife Center

This research is carried out under NMFS Permit numbers 881-1668 and 1034-1887.

The concept of remote three-dimensional (3-D) close range soft copy photogrammetry via the SLiDAP system:

The SLiDAP system is a semi-autonomous remote imaging network accessible via satellite data link. Each installation consists of a network of imaging stations capable of providing multiple high-resolution, time-synchronous digital still images form different perspectives of specific objects of interest within a set viewing area. These images are automatically taken and then sent to the home lab for subsequent analysis. Using off-the-shelf, commercially available software, spatially referenced virtual object models are constructed, from which accurate spatial measurements can be derived.

This schematic shows the SLiDAP system in concept. The schematic depicts a coastal rookery of seals or sea lions. Five imaging stations, comprising boxes with built-in cameras and solar panel power supplies, are arranged around the rookery with the cameras pointing at the rookery. The schematic also shows an orbiting satellite linking one of the five stations to the home lab. The five imaging stations are connected to each other via wireless network.

The primary functions the SLiDAP system is designed to perform are:

  1. Accurate year-round age-specific counts of sea lions at remote locations, up to several times per day. Age structure information will be based on volume estimates collected from individual animals.
  2. Repeated, accurate body mass estimates of individual sea lions based on three-dimensional photogrammetry. Body mass estimates will be used for long-term monitoring of mass trends of individually recognizable or tagged sea lions. Body mass trends will be analyzed for annual and ontogenetic changes, as well as changes across major fishing episodes.
  3. Repeated estimates of body condition trends based on photogrammetrically derived morphometric measurements.
  4. Once implantable, archival tags become available, use multiple SLiDAP systems to automatically download data from RAT-Link equipped mobile data recording tags.

Key system design criteria center around extreme ruggedness, highest reliability with minimal service requirements, low temperature capability, complete independence from any local power and communications infrastructure, rapid system deployment capability and very low environmental impact.

Local area coverage for the SLiDAP system wLAN can be set up for ¼ sq. km, but can be extended with modifications to cover larger circular areas or several km of coastline. Such extended areas may however impose certain restrictions on photogrammetric accuracy. Two separate satellite data links can be integrated into the SLiDAP system. Global coverage is provided through an INMARSAT remote system, for which access extends from the equator to 78 degrees latitude north and south. This covers most Antarctic coastlines and sub-Antarctic islands of interest for biological studies, as well as most arctic locations of biological interest: all of Alaska including the Aleutian Islands, Pribilof Islands in the Bering sea, most of the Canadian arctic and Greenland, all of Siberia and its coastline, as well as both magnetic poles. The northernmost portion of Greenland, Ellesmere Island, most of the arctic winter sea-ice cap and the core of the Antarctic continent are excluded. VSAT systems provide higher data throughput rates at substantially lower operating costs, but have more restricted coverage and higher power consumption rates. SLiDAP systems can be configured with one or two satellite links of each system.

The SLiDAP system is designed to operate in extreme environments, down to a lower temperature limit of -25 degrees C in initial the first development stage. At later stages operations down to -40 degrees ambient will be feasible. The imaging system has initially been designed for the visible spectrum, with low light level capability for dusk and dawn operations.

For details on the SLiDAP system design and the application of 3-D photogrammetry, see these two publications:

Plankis, B., M. Horning, N. Ponto and L. Brown. 2007. Designing a dependable and fault-tolerant semiautonomous distributed cotrol data collection network with opportunistic hierarchy. IEEE Journal of Oceanic Engineering. 32(2): 400-407. 

Waite, J., W. Schrader, J. Mellish and M. Horning. 2007. Three-dimensional photogrammetry as a tool for estimating morphometrics and body mass of Steller sea lions (Eumetopias jubatus). Canadian Journal of Fiheries & Aquatic Sciences. 64: 296-303.

Specific objectives of the NSF funded SLiDAP development 

  1. Develop, build and test a remotely accessible, low impact, highly reliable local area imaging network suitable for obtaining accurate, 3-D close-range photogrammetric measurements.
  2. Adapt existing close-range photogrammetry software for use as a quantitative tool when integrated into the remote imaging network.
  3. Specifically adapt the use of 3-D photogrammetry to perform accurate census operations, and to remotely estimate individual body masses in pinnipeds.
  4. In a second software development stage, enhance the 3-D photogrammetry system through automatic image analysis for semi-automated census operations.
  5. Develop open design specifications for a bi-directional radio data link between roving archival tags and remote data collection stations for future universal system compatibility.

Specific objectives of the SSLRI/NOAA funded physiological validation study of 3-D photogrammetry at the ASLC

  1. Define the accuracy of body mass calculations based on relationships derived from morphometric measures and 3-D photogrammetry.
  2. Assess the validity and accuracy of estimating body condition using 3-D photogrammetry.
  3. Assess the comparability of body condition estimates using 3-D photogrammetry with existing methods of measurement (i.e., morphometrics, isotope dilution, ultrasound blubber depth and BIA).
  4. Determine patterns of blubber mobilization (i.e., selective regional lipid mobilization) under fasting conditions.
  5. Determine trends of fatty acid mobilization (i.e., selective regional fatty acid mobilization) under fasting conditions.

Specific objectives of the SSLRI/NOAA funded remote monitoring of Steller sea lions in the Gulf of Alaska and  Aleutian Islands via SLiDAP

  1. Obtain year-round frequent, accurate census data from selected study sites.
  2. Assess seasonal variations in haul-out patterns and age structures of selected study rookeries.
  3. Estimate longitudinal, seasonal body mass trends for clearly recognizable individuals at selected study sites, as well as cross-sectional trends for all unmarked animals.
  4. Estimate longitudinal, seasonal body condition trends for clearly recognizable individuals at selected study sites, as well as cross-sectional trends for all unmarked animals.
  5. Assess the relationship between observed trends in body mass and condition, and reported environmental parameters.

The specific hypotheses we will test, within the scope of the biological application of the SLiDAP system, are listed as null-hypotheses

  1. There is no regional difference in lipid mobilization during fasting. Unlike phocid seals, lipid depots are comparably sparse and are not distributed evenly throughout the body of otariid seals. Instead, there are regions that tend to have a greater percentage of the total lipid stored, such as the neck region. As a result, we expect selective mobilization of energy stores from larger lipid depots, either as a function of absolute energy availability or perhaps to maintain a critical threshold of blubber for insulatory purposes at more vulnerable sites of the body. If a significant site-specific selective mobilization is detected, this will have important implications for the accurate estimation of body mass and body condition using morphometric parameters and 3-D photogrammetry.
  2. There is no selective fatty acid mobilization during fasting. Blubber tissue can be analyzed for its constituent fatty acids, which can be a reflection of the diet of the animal. However, in this instance, blubber fatty acids can also be used as a measure of selective lipid mobilization or preferential fatty acid removal from the blubber layer for energetic purposes during times of negative energy balance. Using fatty acid analysis at several sites of the body during an experimental fast, we will be able to determine regional differences, or a lack thereof, in fatty acid metabolism. This study will further allow an examination of potential physiological implications of selective fatty acid depletion for a nutritionally challenged individual. We will determine the accuracy of body condition predicted from body mass and total body water, estimated by three-dimensional photogrammetry using a combination of isotope dilution, BIA and blubber-scan methods for reference.
  3. Longitudinal and cross-sectional body mass values obtained in the rookeries observed via the SLiDAP systems do not exhibit significant seasonal variation.
  4. Longitudinal and cross-sectional body condition does not exhibit significant seasonal variation.
  5. Body mass and body condition trends (if observed) are not related to reported prey biomass removal values and other environmental parameters.
  6. There is no seasonal variation in numbers of individuals hauled out, as observed via the SLiDAP systems.
  7. There is no seasonal variation in the distribution of age classes present in monitored sites.

January 2008

A paper describing technical aspects of the SLiDAP remote imaging network has been published:

  • Plankis, B.J., M. Horning, N. Ponto and L.K. Brown. 2007. Designing a dependable and fault tolerant semi-autonomous distributed control data collection network with opportunistic hierarchy. IEEE Journal of Oceanic Engineering. 32(20): 400-407.

Summer 2007  

The following paper describes the application of 3-D Photogrammetry for estimating body mass in sea lions:

  • Waite, J., W. Schrader, J. Mellish and M. Horning. 2007. Three-dimensional photogrammetry as a tool for estimating morphometrics and body mass of Steller sea lions (Eumetopias jubatus). Canadian Journal of Fisheries & Aquatic Sciences. 64: 296-303.

The following paper describes seasonal morphometric changes in blubber of seals and sea lions:

  • Mellish, J., M. Horning and A.E. York. 2007. Seasonal and spatial blubber-depth changes in captive harbor seals (Phoca vitulina) and Steller’s sea lions (Eumetopias jubatus). Journal of Mammalogy. 88(2): 408-414.

April 2005

Brian and Markus just returned from a service visit to the Seward SLiDAP installation. We expanded the system with further components. The system is continuing to operate as planned. Below, Brian is trying to listen to the camera shutter release of one station, and another one caught the moment.

We will be giving the following presentation at the Biologging 2 conference, related to the SLiDAP and LHX projects:

  • Autonomic Computing in Bio-logging.
    Horning, M., B. Plankis and R. Hill.
    Biologging 2 Conference, St. Andrews, U.K., June 13-16 2005.

January 2005

In December 2004 we completed the installation of the first Alaskan SLiDAP system at the Seward Marine Center (UAF) and began remote operations. Even though further components will be added to this system in the near future, the system is operational, and has been up and running since December.

Here are some images of this system:

 Here you can see elements of the first system set up in an ice covered parking lot of the Seward Marine Center (UAF), adjacent to the Alaska Sea Life Center (background). Three twin sets of 130 W solar panels are mounted on support racks. In the foreground, another bare support rack can be seen. In the background is the large satellite dish for the VSAT system. Behind one panel set one of the imaging stations can be recognized as a black box atop a 5'3" dia pole. At the bottom of the pole a battery box can be seen that houses the battery and charge regulator.




 This image shows one imaging station as a large black box atop a 3" diameter steel pole. Power cables lead to the battery box at the foot of the pole. This box houses a spill-proof absorbed glass matt (AGM) battery and a charge regulator.

 This is a closeup of the viewport of one camera box. The viewport consists of a straight, optically rectified glass pane of 10" by 14". The glass is 6mm thick, tempered and has a special coating. The box is waterproof. Inside one can just make out the front of the camera lens, and some of the electronic components of the station.

 This is the back of the large VSAT satellite dish. The dish is of an offset design, meaning that even though the dish is vertical, or appears to be pointing horizontal, it is actually pointing about 20 degrees above the horizon, towards a geostationary satellite.

October 2004

We have begun with the preparation of the first Alaska installation of a SLiDAP system for test purposes, at the Seward Marine Center of the School of Fisheries and Ocean Sciences at the University of Alaska Fairbanks.

Many thanks for the kind support offered by the Seward Marine Center, and in particular by Mike Banas, Rawlins, and Tom Smith.

November 2003

We have installed the first outdoor imaging station at our neighboring compound of the National Marine Fisheries Service in Galveston, TX for testing purposes. This outdoor station is operating well and talking to other test stations located inside our laboratory. Many thanks to Lynda, Niko and Brian for their incredibly hard and excellent work to get this station off the ground and running!

December 2001

We have completed the selection of COTS (Consumer-off-the-shelf) components to be used for SLiDAP, in conjunction with our own developments of hardware and software. We may periodically revise these selections.

The SLiDAP project funding agencies, collaborators and contractors:

National Science Foundation, Office of Polar Programs
The Steller Sea Lion Research Initiative of the National Marine Fisheries Service (NOAA)
The Texas Institute of Oceanography (cost share participation)

The SLiDAP project is carried out in cooperation with the National Marine Mammal Laboratory (NMML) and the Alaska Sea Life Center.

Field testing of the first SLiDAP system is conducted with the kind support of the Seward Marine Center of the School of Fisheries and Ocean Sciences of the University of Alaska Fairbanks.

SLiDAP project principal investigator: Markus Horning
Co-principal investigator of the biological applications of SLiDAP: Jo-Ann Mellish (ASLC)
Co-investigators: Tom Loughlin, Tom Gelatt (NMML/NMFS)

Project contractors and consultants:
Ashford Technical Software
EOS Systems Inc.
Wildlife Computers

Selected literature relevant to the primary biological objectives of the SLiDAP Project

  1. Arnould, J.P.Y. 1995. Body condition and body-composition in female Antarctic fur seals (Arctocephalus gazella). Marine Mammal Science. 11: 301-313.
  2. Arnould, J.P.Y., S.P. Luque,, C. Guinet,, D,P. Costa,, J. Kingston and S.A. Shaffer. 2004. The comparative energetics and growth strategies of sympatric Antarctic and subantarctic fur seal pups at Iles Crozet. J. Exp. Biol. 206: 4497-4506.
  3. Baker, J.D., C.W. Fowler and G.A. Antonelis. 1994. Mass change in fasting immature northern fur seals. Can. J. Zool. 72: 326-329.
  4. Beauplet, G., C. Guinet, and J.P.Y. Arnould. 2003. Body Composition Changes, Metabolic Fuel Use, and Energy Expenditure during Extended Fasting in Subantarctic Fur Seal (Arctocephalus tropicalis) Pups at Amsterdam Island. Physiol. Biochem. Zool. 76: 262-270.
  5. Beauplet, G., L. Dubroca, C. Guinet, Y. Cherel, W. Dabin and M. Hindell. 2004. Foraging ecology of subantarctic fur seals Arctocephalus tropicalis breeding on Amsterdam Island: seasonal changes in relation to maternal characteristics and pup growth. Mar. Ecol. Prog. Ser. 273: 211-225.
  6. Bossart, G.D., T.H. Reidarson, L.A. Dierauf, and D.A. Duffield. 2001. Clinical Pathology. In: Dierauf, L.A., Gulland, F.A. (Eds.), Handbook of marine mammal medicine. CRC press, New York, pp. 383 - 436.
  7. Bowen, W.D., C.A. Beck and S.J. Iverson. 1999. Bioelectrical impedance analysis as a means of estimating total body water in grey seals. Canadian Journal of Zoology. 77: 418-422.
  8. Bowen, W.D., D.J. Boness and S.J. Iverson. 1998. Estimation of total body water in harbor seals: How useful is bioelectric impedance analysis? Marine Mammal Science. 14: 765-777.
  9. Bowen, W.D. and S.J. Iverson. 1998. Estimation of total body water in pinnipeds using hydrogen-isotope dilution. Physiological Zoology. 71: 329-332.
  10. Boyd, I.L. and C.D. Duck. 1991. Mass changes and metabolism in territorial male Antarctic fur seals (Arctocephalus gazella). Physiol. Zool. 64: 375 - 392.
  11. Bradshaw, C.J.A., L.S. Davis, C. Lalas and R.G. Harcourt. 2000. Geographic and temporal variation in the condition of pups in the New Zealand fur seal (Arctocephalus forsteri): evidence for density dependence and differences in the marine environment. Journal of Zoology. 252: 41-51.
  12. BSERP. 1998. DRAFT Bering Sea Ecosystem Research Plan. NOAA, USDOI, ADF&G.
  13. Calkins, D.G., E.F. Becker and K.W. Pitcher. 1998. Reduced body size of female Steller sea lions from a declining population in the Gulf of Alaska. Marine Mammal Science. 14(2): 232-244.
  14. Castellini, M.A. 2001. Using bio-electrical impedance to measure the body composition of seals and sea lions. FASEB: Experimental Biology 2001 at Orlando, FL, USA.
  15. Castellini, M.A. and D.G. Calkins. 1993. Mass estimates using body morphology in Steller sea lions. Marine Mammal Science. 9: 48-54.
  16. Castellini, M.A. and L.D. Rea. 1992. The biochemistry of natural fasting at its limits. Experientia. 48: 575-582.
  17. Cherel, Y., J.-P. Robin, A. Heitz, C. Calgari and Y. LeMaho. 1992. Relationships between lipid availability and protein utilization during prolonged fasting. J. Comp. Physiol. B. 162: 305-313.
  18. Costa, D.P. 1991. Reproductive and foraging energetics of pinnipeds: Implications for life history patterns. In: Renouf, D. (Ed.), Behaviour of Pinnipeds. Chapman and Hall, London, pp. 300-344.
  19. Costa, D.P. and C.L. Ortiz. 1982. Blood chemistry homeostasis during prolonged fasting in the northern elephant seal. Am. J. Physiol. 242: R591-R595.
  20. Costa, D.P. and T.M. Williams. 1999. Marine mammal energetics. In: Reynolds III, J.E., Rommel, S.A. (Eds.), Biology of Marine Mammals, Smithsonian Institution Press, Washington, DC.
  21. Fery, F., L. Plat, C. Melot and E.O. Balasse. 1996. Role of fat-derived substrates in the regulation of gluconeogenesis during fasting. Am. J. Physiol. 270: E822-E830.
  22. Fritz, L.W. and R.C. Ferrero. 1998. Options in Steller sea lion recovery and groundfish fishery management. Biosphere Conservation. 1(1): 7-19.
  23. Fritz, L.W., R.C. Ferrero and R.J. Berg. 1995. The threatened status of Steller Sea Lions, Eumetopias jubatus, under the endangered species act: Effects on Alaska Groundfish Fisheries Management. Marine Fisheries Review. 57(2):14-27.
  24. Golet, G.H. and D.B. Irons. 1999. Raising young reduces body condition and fat stores in black-legged kittiwakes. Oecologia. 120: 530-538.
  25. Goodman, M.N., B. Lowell, E. Belur and N.B. Ruderman. 1984. Sites of protein conservation and loss during starvation: influence of adiposity. Am. J. Physiol. 246: E383-E390.
  26. Guinet, C., N, Servera, S. Mangin, J.Y. Georges and A. Lacroix, 2004. Change in plasma cortisol and metabolites during attendance period ashore in fasting lactating subantarctic fur seals. Comp. Biochem. Physiol. A. 137: 523-531.
  27. Horning, M. and R.W. Davis. 1996. Report on Workshop: Juvenile Development in Otariids, held at the International Symposium on Otariid Reproductive Strategies and Conservation, Washington D.C., April 12-16 1996, 5 pp.
  28. Horning, M. and F. Trillmich. 1997. Development of Hemoglobin, Hematocrit and Erythrocyte Values in Galápagos Fur Seals. Marine Mammal Science. 13(1): 100-113.
  29. Horning, M. and F. Trillmich. 1997. Ontogeny of diving behaviour in the Galapagos fur seal. Behaviour. 134: 1211-1257.
  30. Horning, M. and F. Trillmich. 1999. Lunar cycles in die prey migrations exert stronger effect on diving juveniles than adult Galapagos fur seals. Proc. Roy. Soc. Lond. B. 266: 1127-1132.
  31. Houser, D.S. and D.P. Costa. 2001. Protein catabolism in suckling and fasting northern elephant seal pups (Mirounga angustirostris). J. Comp. Physiol. B. 171: 635-642.
  32. Jakob, E.M., S.D. Marshall and G.W. Uetz. 1996. Estimating fitness: a comparison of body condition indices. Oikos. 77: 61-67.
  33. Loughlin, T.R. 1998. The Steller sea lion: A declining species. Biosphere Conservation. 1(2): 91-98.
  34. Mellish, J.E., S.J. Iverson and W.D. Bowen. 1999. Variation in milk production and lactation performance in grey seals and consequences for pup growth and weaning characteristics. Physiol. Biochem. Zool. 72: 677-690.
  35. Mellish, J.E. and S.J. Iverson. 2001. Blood metabolites as indicators of nutrient utilization in fasting, lactating phocid seals: does depletion of nutrient reserves terminate lactation? Can. J. Zool. 79: 303-311.
  36. Mellish, J.E. and T.R. Loughlin. 2003. Lipoprotein lipase in lactating and neonatal northern fur seals: exploring physiological management of energetic conflicts. Comp. Biochem. Physiol. A. 134: 147-156.
  37. Mellish, J.E., P.A. Tuomi and M. Horning. 2004. Assesment of ultrasound imaging as a noninvasive measure of blubber thickness in pinnipeds. J. Zoo Wild. Med. 35: 116-118.
  38. Merrick, R.L. and T.R. Loughlin. 1997. Foraging behavior of adult female and young-of-the-year Steller sea lions in Alaskan waters. Can. J. Zool. 75: 776-786.
  39. Noren, D. and M. Mangel. 2004. Energy reserve allocation in fasting northern elephant seal pups: inter-relationships between body condition and fasting duration. Funct. Ecol. 18: 233-242.
  40. Øritsland, N.A., A.J. Påsche, N.H. Markussen, and K. Ronald. 1985. Weight loss and catabolic adaptations to starvation in grey seal pups. Comparative Biochemistry and Physiology A. 82: 931-933.
  41. Owen, O.E., K.J. Smalley, D.A. D’Alessio, M.A. Mozzoli and E.K. Dawson. 1998. Protein, fat, and carbohydrate requirements during starvation: anaplerosis and cataplerosis. Am. J. Clin. Nutr. 68: 12-34.
  42. Pitcher, K.W., D.G. Calkins and G.W. Pendleton. 2000. Steller sea lion body condition indices. Marine Mammal Science. 16: 427-436
  43. Rea, L.D., D.A.S. Rosen and A.W. Trites. 1998. Blood chemistry and body mass changes during fasting in juvenile Steller sea lions (Eumetopias jubatus). Proc. Comp. Nutr. Soc. 2: 174-178.
  44. Rea, L.D., D.A.S. Rosen and A.W. Trites. 2000. Metabolic response to fasting in 6-week-old Steler sea lion pups (Eumetopias jubatus). Can. J. Zool. 78: 890-894.
  45. Richards, M.K., G.E. Keyo and B.M. Popkin. 2000. Waist-to-hip ratio is linked with malnutrition in young children. FASEB Journal 14: A39.
  46. Rosen, D.A.S. and A.W. Trites. 2002. Changes in metabolism in response to fasting and food restriction in the Steller sea lion (Eumetopias jubatus). Comp. Biochem. Physiol. B. 132: 389-399.
  47. Ryg, M., T.G. Smith and N.A. Øritsland. 1990. Seasonal changes in body mass and body composition of ringed seals (Phoca hispida) on Svalbard. Canadian Journal of Zoology. 68: 470-478.
  48. Schumacher, J. 2000. Regime shift theory: A review of changing environmental conditions in the Bering Sea. Proceedings 5th North Pacific Rim Fisheries Conference, Dec 1-3 1999. 19pp.
  49. Slip, D.J., H.R. Burton and N.J. Gales. 1992. Determining blubber mass in the southern elephant seal, Mirounga leonina, by ultrasonic and isotopic techniques. Australian Journal of Zoology. 40: 143-152.
  50. Springer, A., K. Bailey, D. Bowen, I. Boyd, J. Estes, S. Iverson and J. Piatt. 1999. Steller sea lion Feeding Ecology Workshop Review. Seattle, WA, Feb 11-12, 1999: 40pp
  51. Thompson, J.R. and G. Wu. 1991. The effect of ketone bodies on nitrogen metabolism in skeletal muscle. Comp. Biochem. Physiol. B. 100: 209-216.
  52. Trillmich, F. and K. Ono. 1991. Pinnipeds and El Nino: Responses to Environmental Stress. Springer Verlag, Heidelberg.
  53. Waite, J.N.. 2000. Three-dimensional photogrammetry as a tool for assessing morphometrics and estimating body mass of Steller sea lions. M.S. thesis. Texas A&M University. 69 pp.
  54. Waite, J.N. and M. Horning. 2000. 3D photogrammetry as a tool for assessing morphometrics and estimating body mass of Steller sea lions (Eumetopias jubatus). FASEB: Experimental Biology 2000 at San Diego, CA, USA.
  55. Williams, T.M., D. Boness, D. Bowen, I. Boyd, D. Croll, M. Horning, S. Iverson, D. Calkins and A. Didier. 1999. Steller sea lion Physiology Workshop Review. Seattle, WA, Feb 8-10, 1999:34pp.
  56. York, A., 1994. The population dynamics of Northern Sea Lions 1975-1985. Mar. Mam. Sci. 10: 38-51.

Selected technical and engineering literature related to the development of the SLiDAP system:

  1. Arlat, J., A. Costes, Y. Crouzet, J.C. Laprie and D. Powell. 1993. Fault Injection and Dependability Evaluation of Fault-Tolerant Systems. IEEE Transactions on Computers. 42(8): 913-923.
  2. Avizienis, A. 1995. Dependable Computing Depends on Structured Fault Tolerance. Proc. 6th International Symposium on Software Reliability Engineering, pp. 158-168.
  3. Bastani, F.B. and I.L. Yen. 1993. Inherent fault tolerance in decentralized process-control systems. Proc. International Symposium on Autonomous Decentralized Systems, pp. 267-274.
  4. Bondavalli, A., A. Fantechi, D. Latella and L. Simoncini. 2001. Design Validation of Embedded Dependable Systems. IEEE Micro. 21: 52-62.
  5. Clark, J.A. and D.K. Pradhan. 1995. Fault injections: a method for validating computer system dependability. IEEE Computer. 28: 47-56.
  6. Elias, M. 2000. Development of a Low Cost, Fault Tolerant, and Highly Reliable Command and Data Handling Computer. Proc. 19th Digital Avionics System Conferences, vol. 2, pp. 8B4/1-8B4/8.
  7. Grossman, J.P. 2004. Analytically Modeling a Fault-Tolerant Messaging Protocol. IEEE Trans. Comp. 53: 870-878.
  8. Harris, I.G. 2003. Fault Models and Test Generation for Hardware-Software Covalidation. IEEE Design & Test of Computers. July-August: 40-47.
  9. IBM. Autonomic Computing: IBM's Perspective on the State of Information Technology.
  10. Johnson, B. 1989. Design and Analysis of Fault-Tolerant Digital System. Addison Wesley.
  11. Kephart, J.O. and D.M. Chess. 2003. The Vision of Autonomic Computing. Computer. 36: 41-50.
  12. Lala, P. 1985. Fault-Tolerant and Fault-Testable Hardware Design, Prentice Hall.
  13. Lala, J.H. and R.E. Harper. 1994. Architectural principles for Safety-Critical Real-Time Applications. Proceedings of the IEEE. 82: 25-40.
  14. Mahmood, A. and E.J. McCluskey. 1988. Concurrent Error Detection Using Watchdog Processors. IEEE Trans. Comp. 37: 160-174.
  15. McCabe, J.D. 2003. Network Analysis, Architecture, and Design, 2nd Ed. Elsevier Science.
  16. McCluskey, E.J. and S. Bozorgui-Nesbat. 1981. Design for Autonomous Test. IEEE Trans Circuits Systems. CAS-28: 1070-1079.
  17. Mitra, S., R. Saxena and E.J. McCluskey. 2002. A Design Diversity Metric and Analysis of Redundant Systems. IEEE Trans. Comp. 51: 498-510.
  18. Mitra, S., N.R. Saxena and E.J. McCluskey. 2004. Efficient Design Diversity Estimation for Combinational Circuits. IEEE Trans. Comp. 53: 1483-1492.
  19. Mitra, S., W.J. Huang, N.R. Saxena, S.Y. Yu and E.J. McCluskey. 2004. Reconfigurable Architecture for Autonomous Self-Repair. IEEE Design Test Comp. May-June: 228-240.
  20. Powell, D., J. Arlat, L. Beus-Dukic, A. Bondavalli, P. Coppola, A. Fantechi, E. Jenn, C. Rabejac and A. Wellings. 1999. A Generic Upgradable Architecture for Real-Time Dependable Systems. IEEE Trans Parall. Distrib Sys. 10: 580-599.
  21. Pradhan, D.K. .1996. Fault-Tolerant Computer System Design, Prentice Hall.
  22. Prasad, V.B. 1989. Fault tolerant digital systems. IEEE Potentials. 8: 17-21.
  23. Rouff, C. and W. Trutzkowski. 2001. A process for introducing agent technology into Space missions. IEEE Proceedings of the 2001 Aerospace Conference. 6: 2743-2750.
  24. Schill, A. 1990. Dependability in distributed applications-approaches and issues. Proc Workshop on Real Time, pp. 170-177
  25. Sievers, M. 1996. Fault-Tolerance: A Methodology for Implementing Highly Dependable Systems. 15th AIAA/IEEE Digital Avionics Systems Conference, pp. 465-470.
  26. Sterritt, R. and D. Bustard. 2003. Towards an Autonomic Computing Environment. Proc 14th International Workshop on Database and Expert Systems Applications, pp. 694-698.
  27. Trutzkowski, W., M. Hinchey, J. Rash and C. Rouff. 2004. NASA's Swarm Missions: The Challenge of Building Autonomous Software. IT Professional. 6: 47-52.
  28. White, S.R., J.E. Hanson, I. Whalley, D.M. Chess and J.O. Kephart. 2004. An Architectural Approach to Autonomic Computing. IEEE Proceedings of the International Conference on Autonomic Computing. 2: 2-9.
  29. Wolfe, A. 1995. A Case Study in Low-Power System-Level Design. IEEE.
  30. Wolf, W. 2002. What is Embedded Computing? Computer. January: 136-137.
  31. Yakovlev, A., S. Furber, R. Krenz and A. Bystrov. 2004. Design and Analysis of a Self-Timed Duplex Communication System. IEEE Trans Comp. 53: 98-814.