Behavioral responses across a mosaic of ecosystem states restructure a sea otter-urchin trophic cascade

Abstract

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.

Keywords: community regulation; ecosystem functioning; species interactions; stability; trophic cascade.

Fig. 1.

Temporal dynamics of sea otters, kelp, sea urchins, and Pycnopodia. (Left) Annual changes in sea otter abundance in the Monterey study region (A) and relative density of kelp stipes (B), exposed sea urchins (C), and Pycnopodia (D). The trend line in A is corrected for observer error and fit with a Bayesian state-space model (SI Appendix, Supplementary Methods) to the time series of raw survey counts of independent sea otters. B–D represent annual mean observed densities fit with a cubic spline (λ = 0.05). Each shaded region across A–D represents the 95% credible interval. (Right) A conceptual illustration of the dynamics that initiated the formation of the mosaic of remnant kelp forests interspersed with sea urchin barrens. See SI Appendix, Supplementary Methods for expanded time series analyses. We used published data for A from the US Geological Survey (available at https://doi.org/10.3133/ds1097) and subtidal data for B–D from the Partnership for Interdisciplinary Studies of Coastal Oceans subtidal surveys (available at https://doi.org/10.6085/AA/PISCO_SUBTIDAL.151.2).

Fig. 2.

Sea urchin foraging behavior (exposed, concealed) and condition (gonad index) as a function of kelp density. (A) Residuals from a linear regression on the log-transformed proportion of exposed urchins (to account for urchin density) fit with a negative exponential decay function with kelp stipe density. (B) The relationship between mean gonad index (per square meter) and the proportion of exposed sea urchins. The gray shaded area represents the 95% confidence of fit.

Fig. 3.

Gonad index of sea urchins in focal patches where sea otters were actively foraging on sea urchins (orange circles) and reference sites (green circles) where otters were not foraging on sea urchins. Also depicted is the density of urchins and kelp at each patch.

Fig. 4.

Probability of sea otter focal patch selection by urchin gonad index. Model predicted foraging preference (with 95% CIs shaded in green) using the localized mean urchin gonad index (mean gonad index/square meter). Probability values (green line) are translated from the logit-transformed logged odds. The red dashed line indicates the 50% transition threshold.