How much is too much? Defining bycatch reference points for harbour porpoises in a European context

Incidental catches in fisheries (bycatch) continue to present a conservation threat for many marine top predator species globally. Over the past 30 years, several countries have introduced the notion of reference points to manage this threat. Those points define bycatch levels that cannot be sustained by management units or populations of sensitive species. Reaching a reference point is supposed to trigger clearly defined management actions aiming to reduce bycatch to sustainable levels. Reference points are defined precisely and are underpinned by rigorous technical approaches to estimate them. The regulatory context is complex in European waters with both national and EU level objectives, as well as additional multilateral commitments, which do not always align. Here, we use a well-studied management unit of harbour porpoise (Phocoena phocoena) in the Western Baltic to assess how the different objectives that apply to define bycatch reference points in our seas might become conflicting. At first, we define a range of scenarios for bycatch management based on these multiple objectives. To estimate these scenarios, we use a procedure developed as an extension of the Catch Limit Algorithm from the International Whaling Commission. Specifically, we use an aggregated population model to estimate the current population depletion rate based on time series of abundance and bycatch estimates for 2010-2022. We then apply an age-class demographic model to estimate the likely current age-sex structure of the population subjected to bycatch. We finally use this tuned age-class demographic model, based on the current depletion rate, to forecast the behaviour of the population subjected to bycatch over the time horizon(s) specified by the management scenario(s) and estimate the corresponding value of each reference point. This procedure relies on a series of assumptions made about bycatch estimation and demography. We test the sensitivity of outcomes, as well as the goodness-of-fit of the forecasting models to these assumptions. We use this large set of simulations to show that both bycatch estimation procedures and demographic assumptions have a large effect on outcomes and that both must be improved to retrieve precise bycatch reference points for this population.