Consumer and predator foraging behavior can impart profound trait-mediated constraints on community regulation that scale up to influence the structure and stability of ecosystems. Here, we demonstrate how the behavioral response of an apex predator to changes in prey behavior and condition can dramatically alter the role and relative contribution of top-down forcing, depending on the spatial organization of ecosystem states. In 2014, a rapid and dramatic decline in the abundance of a mesopredator (Pycnopodia helianthoides) and primary producer (Macrocystis pyrifera) coincided with a fundamental change in purple sea urchin (Strongylocentrotus purpuratus) foraging behavior and condition, resulting in a spatial mosaic of kelp forests interspersed with patches of sea urchin barrens. We show that this mosaic of adjacent alternative ecosystem states led to an increase in the number of sea otters (Enhydra lutris nereis) specializing on urchin prey, a population-level increase in urchin consumption, and an increase in sea otter survivorship. We further show that the spatial distribution of sea otter foraging efforts for urchin prey was not directly linked to high prey density but rather was predicted by the distribution of energetically profitable prey. Therefore, we infer that spatially explicit sea otter foraging enhances the resistance of remnant forests to overgrazing but does not directly contribute to the resilience (recovery) of forests. These results highlight the role of consumer and predator trait-mediated responses to resource mosaics that are common throughout natural ecosystems and enhance understanding of reciprocal feedbacks between top-down and bottom-up forcing on the regional stability of ecosystems.

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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.