Sea otter carrying capacity in a soft- and mixed-sediment benthic habitat

Abstract

Identifying factors that influence animal population density can provide insight into why it varies spatially and temporally and when a recovering population has reached an equilibrium density because of food resources (i.e., carrying capacity K). Although food availability is widely recognized as an important extrinsic factor limiting sea otter (Enhydra lutris) population density, can we determine when a population has reached K based on population size and prey availability? The goal of this study was to estimate K for Simpson Bay, Alaska by measuring the abundance of edible bivalves, the primary prey for sea otters for over 40 years. We then compared prey abundance and estimated replacement rate (i.e., the mean age of bivalves predated by sea otters) to estimated annual prey consumption based on the mean population density for the past 18 years. On average, 110 adult sea otters (5.2 km−2) have occupied Simpson Bay annually since 2001 consuming an estimated 176,660 kg of bivalves. The total biomass (standing stock) of the major bivalves (predominately butter clams and stained macomas) was 785,730 kg, so adult sea otters consumed about 22% annually. Given the stable abundance of sea otters over the past 18 years and evidence of sustainable prey replacement, sea otters in Simpson Bay appear to be at K. Understanding which factors regulate population density may be one of the most challenging ecological questions and require long-term monitoring for complete resolution. We suggest that studies such as this, when applied to a variety of littoral habitats occupied by sea otters, complement approaches that use proxies for prey availability to assess K. Future research should focus on a few sites, which are representative of the variety of littoral habitats occupied by sea otters around the North Pacific Rim. From those sites, we may learn how the balance among intrinsic and extrinsic factors affects regional sea otter population density. In addition, this approach provides a mechanistic assessment of K, which will better inform probabilistic inferences for sea otter population trends and help resource managers anticipate potential conflicts and tailor management strategies to benefit a wide range of recovering predators, such as the sea otter.