Risks and benefits of catching pretty good yield in multispecies mixed fisheries

Multispecies mixed fisheries catch ecologically interacting species with the same gears at the same time. We used an ensemble of size-based multispecies models to investigate the effects of different rates of fishing mortality (F) and fleet configurations on yield, biomass, risk of collapse and community structure. Maximum sustainable yield (MSY) and FMSY for 21 modelled species’ populations in the North Sea were defined at the Nash equilibrium, where any independent change in F for any species would not increase that species’ MSY. Fishing mortality ranges leading to “Pretty Good Yield” (F-PGY), by species, were defined as ranges yielding ≥0.95 × MSY. Weight and value of yield from the entire fishery increased marginally when all species were fished at the upper end of F-PGY ranges rather than at FMSY, but risk of species’ collapse and missing community targets also increased substantially. All risks fell markedly when fishing at the lower end of F-PGY ranges, but with small impacts on total fishery yield or value. While fishing anywhere within F-PGY ranges gives managers flexibility to manage trade-offs in multispecies mixed fisheries, our results suggest high long-term yields and disproportionately lower risks of stock collapse are achieved when F ≤ FMSY for all component stocks

The use of a length-structured multispecies model fitted directly to data in near-real time as a viable tool for advice

Fish communities are multispecies assemblages, so ideally multispecies models should be used directly for assessing this resource. However, progress in this direction has been slow, partly because these models are often more complex and take longer to fit, rendering them too slow to demonstrate near-real-time utility, and thus creating a perception that they are opaque to stakeholders. In this study we implemented a multispecies assessment for the Irish Sea, fitting a model of eight key stocks directly to catch and survey data. Two novel features of our approach allowed the multispecies model to be fitted within a few hours. Firstly, by using size-based theory and life-history invariants to specify many of the required properties of stocks, we reduced the number of general parameters that needed to be fitted directly to a more manageable 25. Secondly, by using state-of-the-art fitting methods, we found acceptable solutions quickly enough to provide assessments within the timescale of an advisory meeting. The outcomes were compared with the standard single species assessments of the same eight species. Model fits were generally good for either catch or at least one of the surveys, but not for all data sources at the same time, illustrating the challenges of fitting multiple stocks to different data sources simultaneously. Estimates of SSB and F agreed qualitatively with the assessments for most stocks with the exception of whiting. Estimates of natural mortality showed modest year to year variability, suggesting that single species assessments may be appropriate for short term tactical management. This method shows great promise for making multispecies assessments as a complement to existing assessments because of the rapid turnaround time and ability to respond at meetings to the requests of stakeholders. In addition, because these models avoid our current dependence on existing single species models they can be used to provide boundary conditions in natural mortality for standard assessment models and check for internal consistency in the assessment process. Furthermore, they are easily accessible because they are based upon freely available code

Assessing the utility of fisheries-dependent data to support mixed fisheries management: a spatiotemporal simulation framework

Fishers exploit populations that are heterogeneously distributed in space and time without full knowledge of species distributions and with fishing gear that is not fully selective. The ability to change catch composition is limited by species mix at a particular location and time and the capture characteristics of the fishing gear. Models capturing the dynamics of the fisheries (‘fleet dynamics’ models) are often simplistic due to a lack of knowledge of the processes driving these catches, which occur both at large and small scales. We develop a simulation framework to investigate the importance of scaling on the interactions between fish populations and fisheries dynamics. The framework provides i) a realistic but tractable biological model of fish populations in space and time, including daily population processes (mortality, growth and recruitment) and population movement implemented as a combination of diffusive density-dependent processes and migrations; and, ii) a realistic fishing simulation model to capture how fishers may exploit heterogeneously distributed fish populations with different values and uncertain knowledge about the underlying spatial processes. We generate a model system where we investigate the consequences of scaling and data aggregation and validate this simulated data against data collected on fisheries operating in the Celtic Sea. The simulation allows a more in-depth understanding of factors important when using fisheries-dependent data to develop spatial management measures, from the micro- to the large-scale and individual to population processes, not otherwise possible due to the limitations in ‘real-world’ spatiotemporal data on fish distributions

A multi-stock harvest control rule based on "pretty good yield" ranges to support mixed-fisheries management

Advice for commercially exploited fish stocks is usually given on a stock-by-stock basis. In light of the ecosystem-based fisheries management, the need to move towards a holistic approach has been largely acknowledged. In addition, the discard bans in some countries requires consistent catch advice among stocks to mitigate choke species limiting fisheries activity. In this context, in 2015, the European Commission proposed the use of fishing mortality ranges around fishing mortality targets to give flexibility to the catch advice system and improve the use of fishing opportunities in mixed-fisheries. We present a multi-stock harvest control rule (HCR) that uses single stock assessment results and fishing mortality ranges to generate a consistent catch advice among stocks. We tested the performance of the HCR in two different case studies. An artificial case study with three stocks exploited simultaneously by a single fleet and the demersal mixed-fishery operating in Bay of Biscay and Celtic Sea. The HCR produced consistent catch advice among stocks when there was only a single fleet exploiting them. Even more, the HCR removed the impact of the discard ban. However, in a multi-fleet framework the performance of the HCR varied depending on the characteristics of the fleets

Commentary: Combining ecosystem and single-species modeling to provide ecosystem-based fisheries management advice within current management systems

A Commentary on: 'Combining Ecosystem and Single-Species Modeling to Provide Ecosystem-Based Fisheries Management Advice Within Current Management Systems' by Howell, D., Schueller, A. M., Bentley, J. W., Buchheister, A., Chagaris, D., Cieri, M., Drew, K., Lundy, M. G., Pedreschi, D., Reid, D. G., and Townsend, H. (2021). Front. Mar. Sci. 7:607831. doi: 10.3389/fmars.2020.60783

Effort reduction and the large fish indicator: Spatial trends reveal positive impacts of recent European fleet reduction schemes

The large fish indicator (LFI), or ‘proportion of fish greater than 40 cm length in bottom trawl surveys,’ is a frequently debated indicator of Good Environmental Status in European regional seas. How does the LFI respond to changes in fishing pressure? This question is addressed here through analysis of fine-scale spatial trends in the LFI within the North Sea, compared between two periods of contrasting fisheries management: 1983–1999 and 2000–2012, respectively, before and after the onset of the European Union's fleet reduction scheme. Over the entire period, the LFI has decreased in large parts of the North Sea. However, most of the decline was from 1983–1999; since 2000 the LFI has improved in much of the North Sea, especially in UK waters. Comparison with international effort data shows that those western areas where the LFI has improved correspond with regions where otter trawl effort has decreased since 2000 (and previously was highest in the 1990s), and also with decreases in beam trawl effort. This study provides strong support that recent European effort reduction schemes are now beginning to result in an improved ecosystem state as indicated by the regional-scale improvement in the LFI

Synthesizing empirical and modelling studies to predict past and future primary production in the North Sea

Understanding change at the base of the marine foodwebs is fundamental to understanding how climate change can impact fisheries. However, there is a shortage of empirical measurements of primary productivity, and models estimates often disagree with each other by an order of magnitude or more. In this study we incorporate information from empirical studies and a suite of Earth system models statistically downscaled using an ensemble model to produce estimates of North Sea primary production with robust quantification of uncertainties under two different climate scenarios. The results give a synthesised estimate of primary production that can feed into regional fisheries models. We found that Earth system models describe the dynamics of primary production in the North Sea poorly, and therefore the effects of climate change on future primary production are uncertain. The methods demonstrated here can be applied to other geographical locations and are not limited in application to primary production

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 multispecies 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

Spatial separation of catches in highly mixed fisheries

Abstract Mixed fisheries are the dominant type of fishery worldwide. Overexploitation in mixed fisheries occurs when catches continue for available quota species while low quota species are discarded. As EU fisheries management moves to count all fish caught against quota (the “landing obligation”), the challenge is to catch available quota within new constraints, else lose productivity. A mechanism for decoupling exploitation of species caught together is spatial targeting, which remains challenging due to complex fishery and population dynamics. How far spatial targeting can go to practically separate species is often unknown and anecdotal. We develop a dimension-reduction framework based on joint dynamic species distribution modelling to understand how spatial community and fishery dynamics interact to determine species and size composition. In application to the highly mixed fisheries of the Celtic Sea, clear common spatial patterns emerge for three distinct assemblages. While distribution varies interannually, the same species are consistently found in higher densities together, with more subtle differences within assemblages, where spatial separation may not be practically possible. We highlight the importance of dimension reduction techniques to focus management discussion on axes of maximal separation and identify spatiotemporal modelling as a scientific necessity to address the challenges of managing mixed fisheries