This project describes a portion of a long-term study of the behavioral ecology of sea otters. Sub-studies of this project include the development of an individual recognition program for sea otters, the construction of male sea otter activity and energy budgets, and the assessment of male sea otter territory quality. The Sea Otter Nose Matching Program, or "SONMaP", was developed to identify individual sea otters in Simpson Bay, Prince William Sound, Alaska, using a blotch-pattern recognition algorithm based on the shape and location of nose scars. The performance of the SONMaP program was tested using images of otters collected during the 2002-03 field seasons, and previously matched by visually comparing every image in a catalog of 1,638 animals. In 48.9% of the visually matched images, the program accurately selected the correct image in the first 10% of the catalog. Individual follows and instantaneous sampling were used during the summers of 2004-06, to observe male sea otter behavior. Six behaviors (foraging, grooming, interacting with other otters, patrolling, resting, and surface swimming) were observed during four time periods (dawn, day, dusk, night) to create 24-hr activity budgets. Male sea otters spent 27% of their time resting, 26% swimming, 19% grooming, 14% foraging, 9% patrolling and 5% interacting with other otters. Field Metabolic Rate (FMR) was estimated by combining the energetic costs for foraging, grooming, resting, and swimming behaviors of captive otters from Yeates et al. (2007) with these activity budgets. "Swimming" accounted for the greatest percentage (43%) of energy expended each day followed by grooming (23%), resting (15%), feeding (13%) and other (5%). With a peak summer sea otter density of 5.6 otters km-2, the low percentage of time spent foraging indicates that Simpson Bay is below equilibrium density. Territory quality was assessed for male sea otters using four attributes: territory size, shoreline enclosure, accessibility, and number of females observed feeding in each territory. Each attribute was coded with a score of 0-2, and total quality scores ranged from 0.14-1.96 (0.9 + 0.61 SD). High quality territories had large areas, moderate shoreline enclosure, high accessibility, and many foraging females

This project describes a portion of a long-term study of the behavioral ecology of sea otters. Sub-studies of this project include the development of an individual recognition program for sea otters, the construction of male sea otter activity and energy budgets, and the assessment of male sea otter territory quality. The Sea Otter Nose Matching Program, or "SONMaP", was developed to identify individual sea otters in Simpson Bay, Prince William Sound, Alaska, using a blotch-pattern recognition algorithm based on the shape and location of nose scars. The performance of the SONMaP program was tested using images of otters collected during the 2002-03 field seasons, and previously matched by visually comparing every image in a catalog of 1,638 animals. In 48.9% of the visually matched images, the program accurately selected the correct image in the first 10% of the catalog. Individual follows and instantaneous sampling were used during the summers of 2004-06, to observe male sea otter behavior. Six behaviors (foraging, grooming, interacting with other otters, patrolling, resting, and surface swimming) were observed during four time periods (dawn, day, dusk, night) to create 24-hr activity budgets. Male sea otters spent 27% of their time resting, 26% swimming, 19% grooming, 14% foraging, 9% patrolling and 5% interacting with other otters. Field Metabolic Rate (FMR) was estimated by combining the energetic costs for foraging, grooming, resting, and swimming behaviors of captive otters from Yeates et al. (2007) with these activity budgets. "Swimming" accounted for the greatest percentage (43%) of energy expended each day followed by grooming (23%), resting (15%), feeding (13%) and other (5%). With a peak summer sea otter density of 5.6 otters km-2, the low percentage of time spent foraging indicates that Simpson Bay is below equilibrium density. Territory quality was assessed for male sea otters using four attributes: territory size, shoreline enclosure, accessibility, and number of females observed feeding in each territory. Each attribute was coded with a score of 0-2, and total quality scores ranged from 0.14-1.96 (0.9 + 0.61 SD). High quality territories had large areas, moderate shoreline enclosure, high accessibility, and many foraging females.

Sea otter (Enhydra lutris kenyoni) foraging behavior and prey preference (2001-2004) and the behavior and activity budgets of females with dependent pups (2005-2010) were studied during the summer (June-August) in Simpson Bay, Prince William Sound, Alaska. Unlike most previous studies of sea otters which were conducted in coastal areas with a rocky benthos and kelp canopy, the benthic habitat in this study was primarily soft sediment (mud or mixed mud and gravel) with no canopy-forming kelps. Foraging behavior and prey preference. A total of 1,816 foraging dives from 211 bouts were recorded. 87% of foraging dives were successful, and 44% of the prey was identified: 75% clams, 9% Pacific blue mussels, 6% crabs, 2% scallops and a variety of other invertebrates. Significantly more prey items/area were brought up from mixed mud/gravel than mud (p-value

Habitat associations of sea otters during resting and feeding were investigated in Simpson Bay, Prince William Sound, Alaska during the summer months of 2001-2003. Sea otter locations collected during boat surveys were overlaid on bathymetry and sediment maps and water depth, sediment type, distance from shore, and position in the bay (peripheral vs. central) was determined for each. Logistic regression analysis was used to determine whether sea otter habitat use was non-random according to any of these habitat variables. Water depth was the most significant habitat association for feeding behavior, with the majority of feeding dives occurring in shallow water less than 20m deep. Position in the bay was the most significant habitat association for resting behavior, with more otters resting in the center of the bay. In addition, digital images taken of the sea otters during the boat surveys of 2002 and 2003 were used to examine the potential of using nose scars to photo-identify individual sea otters. Both male and female sea otters bore nose scars. Forty-five percent of all individuals encountered were considered identifiable from nose scars and a total of 114 individuals were identified. This compares favorably with the results of photo-identification studies of other marine mammals, suggesting that photo-identification may be a useful tool for the individual identification of sea otters as well.