Steller’s Sea Cow and Kelp Forest Regeneration in the North Pacific

Modern ecosystems are almost universally degraded relative to their past counterparts, from the Pleistocene to the present day. Thus, modern ecosystems may serve as poor guides to conservation actions. Conservation paleobiology is well-suited to address this challenge through enhanced understanding of systems dynamics during past periods of greater species and functional diversity, abundances, and resilience. However, past and present ecosystem dynamics must be integrated to model the future impacts of conservation actions. Here we propose a three-step, Past-Present-Future (PPF) methodology rooted in mathematical modeling. First, construct a model of primary species and interactions of the present-day ecosystem, including biotic and abiotic components. Second, integrate historical and/or paleontological data into the model to investigate past states and processes of the ecosystem, with an emphasis on critical elements (e.g., ecological engineer species) that are no longer present. Third, integrate analyses from the first two steps to predict putative future dynamics and states, and use these to make testable predictions regarding specific conservation interventions. We illustrate this approach with a study investigating impacts of the now-extinct Steller’s sea cow on north Pacific giant kelp forests. The model indicates that the historical system was distinct from the modern, with differing abundances of giant kelp and understory algae. Furthermore, the familiar kelp-dominated state is metastable, capable of rapid transitions to an urchin-dominated state if perturbed by extreme hydrodynamic events, disease-driven reductions of seastar predation, or disease coupled to extreme warming events. We explore the possibility of increasing the resilience of modern forests by artificially recreating at least some of the ecological impacts of sea cows, accounting for metabolic requirements, estimates of abundance based on recent analyses of ancient DNA, and trophic impact.