Elsevier

Marine Policy

Volume 116, June 2020, 103511
Marine Policy

Hotspot mapping in the Celtic Sea: An interactive tool using multinational data to optimise fishing practices

https://doi.org/10.1016/j.marpol.2019.103511Get rights and content

Abstract

As a result of the introduction of the Landing Obligation in European fisheries there is a need to equip industry with the tools and knowledge to avoid unwanted catches. Optimising fishing practices in terms of time and location fished have been acknowledged as being important in modulating catch composition. Mapping techniques used to identify and manage the spatio-temporal nature of bycatch, however, remain underutilized. Data collected on board commercial fishing vessels by observers provides an important source of information on the component of catches discarded. Using a unique dataset, combining observer data for Irish, French and British vessels operating in the Celtic Sea between 2010 and 2015, maps were developed to identify where catches of quota restricted species or under minimum conservation reference size (MCRS) fish were consistent through time. Different catch metrics, based on CPUE and proportion of species in the catch, were compared as a basis for the maps. Our results indicate that it is possible to target above MCRS catches whilst avoiding below MCRS catches of the same species. Quota restricted species such as haddock can also be avoided whilst targeting other commercially exploited species including whiting. To allow all the information produced to be easily interpreted, the maps have been incorporated into a user-friendly app, to better inform decision making and potentially increase fishing opportunities under the Landing Obligation.

Introduction

The reduction of discards and unwanted catch in European fisheries was identified as one of the main objectives of the EU Common Fisheries Policy reforms in 2013, resulting in the introduction of the Landing Obligation (LO), whereby discarding of quota species in European fisheries will be prohibited by 2019 [1,2]. Implementation of the LO presents major challenges especially for mixed fisheries [3]. Whilst improvements in gear selectivity can help in reducing unwanted catches there remains a need to avoid areas with an abundance of unwanted catch if this legislation is to be adhered to [[4], [5], [6], [7]]. Altering fishing practices in terms of time and location of fishing has, therefore, been acknowledged as being important in optimising catch composition and extending fishing opportunities [4,[8], [9], [10]].

For fishermen to effectively target their fishing practices it is vital that industry stakeholders are provided with as much information about the distribution of fish as possible. Survey data collected from research vessels, observer data collected from commercial fishing vessels and catch information from logbooks or electronic monitoring technology coupled with VMS (vessel monitoring systems) data can be used to produce maps that identify species hotspots [[11], [12], [13], [14]]. The inclusion of discards in such data sources provides more precise estimates of catch than just using landings data alone [15]. Maps produced from observer data could, therefore, provide a real insight into the spatial distribution of all species caught by commercial vessels. Fishing suitability and bycatch hotspot maps have indeed been developed using fisheries data and statistical modelling techniques to assist in forecasting fish distributions and to provide insight into regional discarding issues in locations including; the Canadian Arctic, Danish waters, the Spanish Mediterranean and the northwest Atlantic [4,[16], [17], [18]]. Whilst such advanced spatial analysis techniques and methods used to identify and manage the spatio-temporal nature of bycatch have been developed in a number of global fisheries they generally remain underutilized by industry [16,19]. In addition to developing such maps there is a need to ensure the resultant outputs are presented in an easily digestible and accessible format. Further, it is essential that spatial analysis and mapping are based on as much suitable data as possible. Whilst observer data does provide information on the whole catch and not just the component later landed there are problems associated with discard sampling from observers, including low sampling frequency and irregular sampling design [20].

The Celtic Sea is an area on the western edge of Europe extending from the western Channel, south of England up around the west coast of Ireland, across the continental shelf to the west of Scotland. The Celtic Sea is an extensively fished ecosystem, providing valuable fisheries for several species, which often co-occur within a mixed species assemblage [21]. Due to its geographical location this area supports a number of international fleets including those from Ireland, France, and the UK. Whilst individual EU member states are required to collect fisheries data as part of the EU data collection framework (Council regulation (EC) No 199/2008) there is no obligation to share this data directly with other EU member states. Sharing and compiling data, especially that collected by observers, can increase sampling frequency and coverage and assist in overcoming some of the issues associated with the sparse nature of observer data. Further, the mixed nature of demersal fisheries in this area and their complex spatial structure [12] make the Celtic Sea an ideal area to make use of such a data sharing exercise to help better identify spatial patterns in fish distributions.

A unique tri-national dataset was created by combining observer data from Irish, French and British vessels operating in the Celtic Sea for the first time. This dataset was then used to identify areas where catches of species subject to TAC (total allowable catch), for both the above and below minimum conservation reference size (MCRS) components of the catch, were consistent over time. This use of consistent patterns in the catch, rather than simply calculating mean values from observer data over multiple years, is a novel way of approaching hotspot mapping. The resultant maps can be used to identify hotspots of catches that fishermen may want to better target or avoid to optimise catches under the landing obligation. Further to the development of this methodology an interactive app was developed so that fishermen can extract tailored information, ultimately helping to inform where to fish to reduce bycatch and reduce the risk of choke events [22]. If this approach does prove useful to them, it may also increase their motivation to share their own data and potentially increase the accuracy and/or increase the temporal resolution of the results.

Section snippets

Data

Data collected by onboard observers working on Irish, British and French demersal vessels operating in the Celtic Sea between 2010 and 2015 were used in the analyses. Data were collected by each member state as part of the EU data collection framework (Council regulation (EC) No 199/2008). The exact structure of each nation's observer programme does vary with the selection of vessels being stratified by gear type for the British fleet, by metier in France and stratified by area of operation

Results

The hotspot maps, an example of which can be seen in Fig. 2, have been created for the above and below MCRS component of the catch for all demersal species subject to a TAC. To better focus comparison and analysis of the results this paper will focus on three key species; haddock, whiting and cod. Both haddock and whiting have been recognised as “choke” species [40] in the Celtic Sea with the perception from multiple member states that catches for these species exceed TAC [41]. Further current

Discussion

Hotspot mapping provides useful information to allow the optimisation of fishing activity to better target certain species whilst avoiding unwanted and quota restricted catch. Observer data, collected from commercial fishing vessels, provides an ideal basis for such maps as these data include the discarded component of catches, in addition to landings. The sparse coverage of observer data and limited sampling of commercial vessels can present problems when trying to identify patterns in fish

Declarations of interest

None.

Acknowledgements

This work has been funded by the European Union’s Horizon 2020 research and innovation programme under Grant Agreement DiscardLess No 633680.

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