Brian B. Hatfield

INCORPORATING DIVERSE DATA AND REALISTIC COMPLEXITY INTO DEMOGRAPHIC ESTIMATION PROCEDURES FOR SEA OTTERS

Reliable information on historical and current population dynamics is central to understanding patterns of growth and decline in animal populations. We developed a maximum likelihood-based analysis to estimate spatial and temporal trends in age/sex-specific survival rates for the threatened southern sea otter (Enhydra lutris nereis), using annual population censuses and the age structure of salvaged carcass collections. We evaluated a wide range of possible spatial and temporal effects and used model averaging to incorporate model uncertainty into the resulting estimates of key vital rates and their variances. We compared these results to current demographic parameters estimated in a telemetry-based study conducted between 2001 and 2004. These results show that survival has decreased substantially from the early 1990s to the present and is generally lowest in the north-central portion of the populations range. The greatest temporal decrease in survival was for adult females, and variation in the survival of this age/sex class is primarily responsible for regulating population growth and driving population trends. Our results can be used to focus future research on southern sea otters by highlighting the life history stages and mortality factors most relevant to conservation. More broadly, we have illustrated how the powerful and relatively straightforward tools of information-theoretic-based model fitting can be used to sort through and parameterize quite complex demographic modeling frameworks.

A protozoal-associated epizootic impacting marine wildlife: Mass-mortality of southern sea otters (Enhydra lutris nereis) due to Sarcocystis neurona infection

During April 2004, 40 sick and dead southern sea otters (Enhydra lutris nereis) were recovered over 18km of coastline near Morro Bay, California. This event represented the single largest monthly spike in mortality ever recorded during 30 years of southern sea otter stranding data collection. Because of the point-source nature of the event and clinical signs consistent with severe, acute neurological disease, exposure to a chemical or marine toxin was initially considered. However, detailed postmortem examinations revealed lesions consistent with an infectious etiology, and further investigation confirmed the protozoan parasite Sarcocystis neurona as the underlying cause. Tissues from 94% of examined otters were PCR-positive for S. neurona, based on DNA amplification and sequencing at the ITS-1 locus, and 100% of tested animals (n=14) had elevated IgM and IgG titers to S. neurona. Evidence to support the point-source character of this event include the striking spatial and temporal clustering of cases and detection of high concentrations of anti-S. neurona IgM in serum of stranded animals. Concurrent exposure to the marine biotoxin domoic acid may have enhanced susceptibility of affected otters to S. neurona and exacerbated the neurological signs exhibited by stranded animals. Other factors that may have contributed to the severity of this epizootic include a large rainstorm that preceded the event and an abundance of razor clams near local beaches, attracting numerous otters close to shore within the affected area. This is the first report of a localized epizootic in marine wildlife caused by apicomplexan protozoa.

A multi-decade time series of kelp forest community structure at San Nicolas Island, California (USA)

Abstract San Nicolas Island is surrounded by broad areas of shallow subtidal habitat, characterized by dynamic kelp forest communities that undergo dramatic and abrupt shifts in community composition. Although these reefs are fished, the physical isolation of the island means that they receive less impact from human activities than most reefs in Southern California, making San Nicolas an ideal place to evaluate alternative theories about the dynamics of these communities. Here we present monitoring data from seven sampling stations surrounding the island, including data on fish, invertebrate, and algal abundance. These data are unusual among subtidal monitoring data sets in that they combine relatively frequent sampling (twice per year) with an exceptionally long time series (since 1980). Other outstanding qualities of the data set are the high taxonomic resolution captured and the monitoring of permanent quadrats and swaths where the history of the community structure at specific locations has been recor...