Background:
Reference points are used in fisheries management to represent desired and undesired stock and fishery states, and provide a means by which to evaluate the status of fish stocks. Biomass and fishing reference points are also often used as operational control points to trigger changes in the management measures (e.g., fishing rate) in response to changes in the stock. Reference points are key components of the precautionary approach (PA), which is considered a cornerstone for sustainable fisheries management. PA reference points are usually estimated from models taking into account historical fish population dynamics and their response to fishing mediated by environmental conditions and the life-history characteristics of the stock. These reference points are mostly estimated to be static characterizations of a stock’s productivity assuming equilibrium dynamics (hereafter referred to as static reference points). However, in reality, it is well known that a stock’s distribution and productivity vary in time both randomly and often with trends (Karp et al. 2019), sometimes even showing regime-like characteristics. This means that management decisions based on such static reference points may not reflect the productivity of a stock in the future, especially as climate change is already impacting environmental conditions, primary productivity, and distributions of fish stocks (Lotze et al. 2019). This may affect the risk of management decisions that are either 1) unsustainable or 2) overly cautious with foregone yield, because of the mismatch between actual productivity and the productivity inherent in a static PA framework.

Challenges:
Time-varying (non-stationary) reference points are points that can change according to the “prevailing” environmental conditions. For example, time-varying reference points can be calculated by incorporating environmental covariates into models and projections (a “mechanistic approach” including dynamic B0, moving windows or the STARs approaches to calculating reference points (Punt et al. 2014). However, there are several challenges with this approach: 1) ecosystem regimes or prevailing conditions are difficult to define and detect, 2) the environmental mechanisms are often elusive and tend to change over time, 3) forecasting environmental conditions could be highly uncertain, and 4) inclusion of such methods may not lead to substantially better management outcomes. Another option is to use static reference points in harvest strategies that are then evaluated for robustness to time-varying productivity by accounting for possible broad scenarios of future dynamics (an “empirical approach”; Punt et al. 2014). This approach does not require identifying, understanding, or projecting explicit mechanisms affecting fish population dynamics, thereby avoiding the above-mentioned challenges associated with time-varying reference points. However, implementation of such reference points in harvest strategies may lead to over-exploitation/under-exploitation in periods with poor/good environmental conditions, resulting in sub-optimal harvesting in fisheries (Rindorf et al. 2017). Limitations of the use of both time varying and static reference points in harvest strategies suggest the choice of reference points should be evaluated in the context of specific fisheries and ecosystems, and some general and practical guidance on how to make such choices is warranted (e.g. Holt & Michielsens 2019).

Two-parts Workshop Format:
The workshop has two parts:
1. Part 1 is an online workshop featuring keynote talks followed by discussions.
2. Part 2 is an in-person workshop focusing on actual practices of defining and/or changing reference points in case studies, identify research gaps, and develop general guidance or
recommendation of best practices.