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 population's 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.
During April, 2004, 40 sick and dead southern sea otters (Enhydra lutris nereis) were recovered over 18 km 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.
Although southern sea otters (Enhydra lutris nereis) are not considered prey for white sharks (Carcharodon carcharias), sharks do nonetheless bite sea otters. We analyzed spatial and temporal trends in shark bites on sea otters in California, assessing the frequency of shark bite wounds in 1,870 carcasses collected since 1985. The proportion of stranded sea otters having shark bites has increased sharply since 2003, and white shark bites now account for >50% of recovered carcasses. The trend was most pronounced in the southern part of the range, from Estero Bay to Point Conception, where shark bite frequency has increased eightfold. Seasonal trends were also evident: most shark‐bitten carcasses are recovered in late summer and fall; however, the period of elevated shark bite frequency has lengthened. The causes of these trends are unclear, but possible contributing factors include increased white shark abundance and/or changes in white shark behavior and distribution. In particular, the spatiotemporal patterns of shark‐bitten sea otters match increases in pinniped populations, and the increased availability of marine mammal prey for white sharks may have led to more sharks spending more time in nearshore waters utilized by both sea otters and pinnipeds.
Elevated mortality appears to be the main reason for both sluggish growth and periods of decline in the threatened California sea otter population. We assessed causes of mortality from salvage records of 3,105 beach‐cast carcasses recovered from 1968 through 1999, contrasting two periods of growth with two periods of decline. Overall, an estimated 40%‐60% of the deaths were not recovered and 70% of the recovered carcasses died from unknown causes. Nonetheless, several common patterns were evident in the salvage records during the periods of population decline. These included greater percentages of (1) prime age animals (3–10 yr), (2) carcasses killed by great white shark attacks, (3) carcasses recovered in spring and summer, and (4) carcasses for which the cause of death was unknown. Neither sex composition nor the proportion of carcasses dying of infectious disease varied consistently between periods of population increase and decline. The population decline from 1976 to 1984 was likely due to incidental mortality in a set‐net fishery, and the decline from 1995 to 1999 may be related to a developing live‐fish fishery. Long‐term trends unrelated to periods of growth and decline included a decrease in per capita pup production and mass/length ratios of adult carcasses over the 31‐yr study. The generally high proportion of deaths from infectious disease suggests that this factor has contributed to the chronically sluggish growth rate of the California sea otter population.
The recovery of large carnivore species from over‐exploitation can have socioecological effects; thus, reliable estimates of potential abundance and distribution represent a valuable tool for developing management objectives and recovery criteria. For sea otters (Enhydra lutris), as with many apex predators, equilibrium abundance is not constant across space but rather varies as a function of local habitat quality and resource dynamics, thereby complicating the extrapolation of carrying capacity (K) from one location to another. To overcome this challenge, we developed a state‐space model of density‐dependent population dynamics in southern sea otters (E. l. nereis), in which K is estimated as a continuously varying function of a suite of physical, biotic, and oceanographic variables, all described at fine spatial scales. We used a theta‐logistic process model that included environmental stochasticity and allowed for density‐independent mortality associated with shark bites. We used Bayesian methods to fit the model to time series of survey data, augmented by auxiliary data on cause of death in stranded otters. Our model results showed that the expected density at K for a given area can be predicted based on local bathymetry (depth and distance from shore), benthic substrate composition (rocky vs. soft sediments), presence of kelp canopy, net primary productivity, and whether or not the area is inside an estuary. In addition to density‐dependent reductions in growth, increased levels of shark‐bite mortality over the last decade have also acted to limit population expansion. We used the functional relationships between habitat variables and equilibrium density to project estimated values of K for the entire historical range of southern sea otters in California, USA, accounting for spatial variation in habitat quality. Our results suggest that California could eventually support 17,226 otters (95% CrI = 9,739–30,087). We also used the fitted model to compute candidate values of optimal sustainable population abundance (OSP) for all of California and for regions within California. We employed a simulation‐based approach to determine the abundance associated with the maximum net productivity level (MNPL) and propose that the upper quartile of the distribution of MNPL estimates (accounting for parameter uncertainty) represents an appropriate threshold value for OSP. Based on this analysis, we suggest a candidate value for OSP (for all of California) of 10,236, which represents 59.4% of projected K. © 2021 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.
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