We need to talk about the role of zooplankton in marine food webs.

Zooplankton are the key intermediary between primary production and the fish community and a cornerstone of marine food webs, but they are often poorly represented in models that tend to focus on fish, charismatic top predators, or ocean biogeochemistry. In this study, we use an intermediate complexity end-to-end food web model of the North Sea with explicit two-way coupling of zooplankton to phytoplankton and higher trophic levels to ask whether this matters. We vary the metabolic rate of omnivorous zooplankton (OZ) as a proxy for uncertainties in our understanding and modeling of zooplankton form and function, and moving beyond previous studies we look at the impacts on the food web in concert with climate warming and fishing. We consider impacts on food web state and time to recover the relevant unfished state after fishing ceases. We also consider potential impacts on pelagic and demersal fishing fleets if we assume that they are constrained by the requirement to allow recovery to an unfished state within a certain period of time as a way of ensuring consistency with Good Environmental Status as required by EU and UK legislation. We find that all three aspects considered are highly sensitive to changes in the treatment of zooplankton, with impacts being larger than for warming of 2 or 4°C across most food web functional groups, particularly for apex predators. We call for a programme of research aimed at improving our understanding of zooplankton ecology and its relationship to the wider food web, and we recommend that improved representations of zooplankton are incorporated in future modeling studies as a priority.

Emerging issues in fisheries science by fisheries scientists.

The current epoch in fisheries science has been driven by continual advances in laboratory techniques and  increasingly sophisticated approaches to analysing datasets. We now have the scientific knowledge and tools to proactively identify obstacles to the sustainable management of marine resources. However, in addition to technological advances, there are predicted global environmental changes, each with inherent implications for fisheries. The 2023 symposium of the Fisheries Society of the British Isles called for "open and constructive knowledge exchange between scientists, stakeholders, managers and policymakers" (https://fsbi.org.uk/symposium-2023/), a nexus of collaborative groups best placed to identify issues and solutions. Arguably, the Centre of Environment, Aquaculture and Fisheries Science (Cefas) and their Scientific Advice for Fisheries Management (SAFM) Team sit at the centre of such a network. SAFM regularly engages with managers and stakeholders, undertakes scientific research, provides fisheries advice to the UK government, and are leading experts within the International Council for the Exploration of the Sea (ICES). As such, this paper is an opinion piece, linked to individual authors specialisms, that aims to highlight emerging issues affecting fisheries and suggest where research efforts could be focused that contribute to sustainable fisheries.

LeMaRns: A Length-based Multi-species analysis by numerical simulation in R.

Fish stocks interact through predation and competition for resources, yet stocks are typically managed independently on a stock-by-stock basis. The need to take account of multi-species interactions is widely acknowledged. However, examples of the application of multi-species models to support management decisions are limited as they are often seen as too complex and lacking transparency. Thus there is a need for simple and transparent methods to address stock interactions in a way that supports managers. Here we introduce LeMaRns, a new R-package of a general length-structured fish community model, LeMans, that characterises fishing using fleets that can have different gears and species catch preferences. We describe the model, package implementation, and give three examples of use: determination of multi-species reference points; modelling of mixed-fishery interactions; and examination of the response of community indicators to dynamical changes in fleet effort within a mixed-fishery. LeMaRns offers a diverse array of options for parameterisation. This, along with the speed, comprehensive documentation, and open source nature of the package makes LeMans newly accessible, transparent, and easy to use, which we hope will lead to increased uptake by the fisheries management community.

What is multispecies MSY? A worked example from the North Sea.

The concept of an optimum yield at intermediate levels of fishing (the so called maximum sustainable yield or MSY) has been with us since the 1930s and is now enshrined in legislation as a key objective of fisheries management. The concept seems intuitively reasonable and is readily applicable to a single stock treated in isolation and assuming a constant environment. However, translating this concept into a mixed and multispecies fishery, where there are complex trade-offs between fleets and stocks and in general no simple optimum solution, has been problematic. Here I introduce a framework for thinking about multispecies MSY in terms of an integrated risk of stock depletion and expected long-term yield. Within this framework I consider the performance of a set of simple harvest control rules based upon a single-limit fishing mortality rate (F) which is common to all stocks and a target biomass which is a set fraction of a stock's virgin biomass. Using a multispecies management strategy evaluation, I compare expected outcomes for a set of these harvest control rules with alternative scenarios, in which each stock has its own F based on the assessment process. I find that the simple framework can produce outcomes that are similar to those from the more sophisticated estimates of F. I therefore conclude that achieving multispecies MSY may depend more upon setting reasonable biomass targets and faithfully applying a harvest control rule approach rather than determining the best possible Fs for each stock.

Evaluation and management implications of uncertainty in a multispecies size-structured model of population and community responses to fishing.

Implementation of an ecosystem approach to fisheries requires advice on trade-offs among fished species and between fisheries yields and biodiversity or food web properties. However, the lack of explicit representation, analysis and consideration of uncertainty in most multispecies models has limited their application in analyses that could support management advice.We assessed the consequences of parameter uncertainty by developing 78 125 multispecies size-structured fish community models, with all combinations of parameters drawn from ranges that spanned parameter values estimated from data and literature. This unfiltered ensemble was reduced to 188 plausible models, the filtered ensemble (FE), by screening outputs against fish abundance data and ecological principles such as requiring species' persistence.Effects of parameter uncertainty on estimates of single-species management reference points for fishing mortality (FMSY, fishing mortality rate providing MSY, the maximum sustainable yield) and biomass (BMSY, biomass at MSY) were evaluated by calculating probability distributions of estimated reference points with the FE. There was a 50% probability that multispecies FMSY could be estimated to within ±25% of its actual value, and a 50% probability that BMSY could be estimated to within ±40% of its actual value.Signal-to-noise ratio was assessed for four community indicators when mortality rates were reduced from current rates to FMSY. The slope of the community size spectrum showed the greatest signal-to-noise ratio, indicating that it would be the most responsive indicator to the change in fishing mortality F. Further, the power of an ongoing international monitoring survey to detect predicted responses of size spectrum slope was higher than for other size-based metrics.Synthesis and applications: Application of the ensemble model approach allows explicit representation of parameter uncertainty and supports advice and management by (i) providing uncertainty intervals for management reference points, (ii) estimating working values of reference points that achieve a defined reduction in risk of not breaching the true reference point, (iii) estimating the responsiveness of population, community, food web and biodiversity indicators to changes in F, (iv) assessing the performance of indicators and monitoring programmes and (v) identifying priorities for data collection and changes to model structure to reduce uncertainty.