Ecosystem management (EM) suffers from linguistic uncertainty surrounding the definition of “EM” and how it can be operationalized. Using fisheries management as an example, we clarify how EM exists in different paradigms along a continuum, starting with a single-species focus and building towards a more systemic and multi-sector perspective. Focusing on the specification of biological and other systemic reference points (SRPs) used in each paradigm and its related regulatory and governance structures, we compare and contrast similarities among these paradigms. We find that although EM is a hierarchical continuum, similar SRPs can be used throughout the continuum, but the scope of these reference points are broader at higher levels of management. This work interprets the current state of the conversation, and may help to clarify the levels of how EM is applied now and how it can be applied in the future, further advancing its implementation.

No abstract

No abstract

Ecological forecasts are potentially of great value for managing fisheries and for stakeholders dependent on their long-term sustainability. Yet most forecasting approaches are data-intensive, requiring information not just on the focal species, but also on ecological interactions and the physical environment. Empirical dynamic modeling (EDM) is an equation-free approach to forecasting species’ abundance using only data on past abundance, but the time series required for this approach must be long enough to reconstruct the dynamics of the system. This requirement is rarely met, especially for long-lived species. Here we used simulations and empirical data to demonstrate that incorporating time series from multiple age classes can improve our ability to forecast abundance compared to a single age class and/or index of total abundance. Including data from multiple age classes produced the greatest gains in forecast accuracy when time series were the shortest. Overall, our results show that the incorporation of age-structure should allow EDM to be applied to many species for which relatively short time series would have previously been a limiting factor.