2.1 Visual foraging observations
We observed sea otter foraging behavior from May to August 2018 on the
western side and neighboring islands of POW. Sampling was stratified by
time since recolonization, based on US Fish and Wildlife Service (USFWS)
aerial surveys. Three periods were denoted from the surveys: zone 1
(> 30 years present), zone 2 (< 30 years and
> 15 years present), and zone 3 (< 15 years and
> 7 years present) (Fig. 1). In each zone, a minimum of 300
foraging dives were recorded. Because zone 2 makes up a majority of POW,
most foraging dives occurred in this zone.
Foraging observations were made from shore to assess sea otter diet
composition. Questar telescopes (50X) were used to follow individual sea
otters for one foraging bout (up to 20 dives per sea otter). The
observer recorded the following foraging metrics: prey item (to species
level when possible), prey size (based on an estimated sea otter paw
width of 5 cm and categorized into < ⅓ of the paw,
> ⅓ and < ⅔ of the paw, or the whole paw), the
proportion of the prey item consumed, GPS location (approximated based
on GPS location of the telescope and distance/bearing to the sea otter),
prey handling time (defined as the amount of time the sea otter spent
manipulating and eating the prey), time spent diving, and total time
spent at the surface. The following sea otter metrics were also recorded
for each foraging bout: sex, reproductive status, and age class. Males
were identified by the presence of a penile bulge, whereas females were
identified if there was a clear lack of penile bulge, or if they had a
pup. If sex was not confirmed, nor pup was observed, the sex was
categorized as “unknown.” When possible, age class was determined as
adult or juvenile by visual assessment of size and amount of grizzled
fur .
We calculated the caloric intake for sea otters based on visual foraging
observations using the Sea Otter Foraging Analysis (SOFA) program, which
is based in Matlab (MathWorks) and maintained by the USGS Alaska Science
Center in Anchorage, AK. SOFA uses a Monte Carlo-based simulation to
account for unknown prey items and potential sampling bias. SOFA is a
Bayesian model that provides the estimated biomass for individual prey
types across time since recolonization, reproductive status, and sex.
All SOFA outputs are reported as means with standard deviation. The
consumption rates for each prey species were assigned for each foraging
bout using the estimated prey size relative to a sea otter paw width.
Prey diversity for each region was calculated using the Shannon-Wiener
Index . Success rate, which is defined as the percentage of dives in a
bout where the sea otter came up with food, was calculated for each sea
otter metric.