An Estimation of Carrying Capacity for Sea Otters along the California Coast Paper by K. L. Laidre, R. J. Jameson, D. P. DeMaster. 2001. Marine Mammal Science, 17(2): 294-309. Presented by Patrick Mehran Jadali, Geography, Geo370, Monday March 1, 2010

Problem and Hypothesis Problem: In 1977, the California Sea Otter was listed as “threatened” by the US Endangered Species Act due to small population size, human disturbance, and pollution. These factors have reduced the carrying capacity for sea otters along the coastline. They need updated data to better manage sea otter populations. Hypothesis: Through using GIS, a new and updated carrying capacity will be obtained to better manage sea otters along the coastline over traditional methods.

Methods, data & test: Site: Sea otter locations along the California Coast (out to 40 m) The study used GIS to estimate the habitat available to sea otters (carrying capacity). Habitat quality was measured by aerial surveys of the coastline. GIS software projected the data into the Albers Equal Area projection to look at data. Calculated density estimates by diving the sum of the counts by the total area of the habitat type.

Results The estimated mean number of sea otters that may be supported by the marine environment at a depth of 40 m (for rocky, sandy, and mixed habitats) in California was 15,941. GIS-based approach calculated 7,569 km2 habitant area for sea otters compared to 7,802 km2 vs. older methods. Primary problem with old methods was a lack of reference points beyond the zero depth contour and trouble with estimation.

Conclusions GIS based method produced different and more accurate area estimates. GIS eliminated a lot of error due to lack of coastline reference points. Densities of sea otters are similar in areas with similar habitat types. Criticisms: The use of the Albers Equal Area Projection did not preserve scale and shape. They should have also looked at other projections. Also, the authors did not really take into account environmental factors that would affect their data collection (erosion, climate change, etc).