Habitat Features Predict Carrying Capacity of a Recovering Marine Carnivore |
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Authors: | M. Tim Tinker Julie L. Yee Kristin L. Laidre Brian B. Hatfield Michael D. Harris Joseph A. Tomoleoni Tom W. Bell Emily Saarman Lilian P. Carswell A. Keith Miles |
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Affiliation: | 1. U.S. Geological Survey, Western Ecological Research Center, Santa Cruz Field Station, 2885 Mission Street, Santa Cruz, CA, 95060 USA;2. Polar Science Center, Applied Physics Laboratory, University of Washington, 1013 NE 40th Street, Seattle, WA, 98105 USA;3. California Department of Fish and Wildlife, Office of Spill Prevention and Response—Veterinary Services, 1385 Main Street, Morro Bay, CA, 93442 USA;4. Earth Research Institute, University of California, Santa Barbara, Santa Barbara, California, 93106 USA;5. Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO), Long Marine Laboratory, 115 McAllister Way, University of California, Santa Cruz, CA, 95060 USA;6. U.S. Fish and Wildlife Service, Ventura, CA, 93003 USA;7. U.S. Geological Survey, Western Ecological Research Center, 3020 State University Drive, Sacramento, CA, 95819 USA |
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Abstract: | 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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Keywords: | Bayesian state-space model density dependence Enhydra lutris habitat quality optimal sustainable population population abundance sea otter |
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