New Zealand Journal of Zoology ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/tnzz20 Genetic stock structure of New Zealand fish and the use of genomics in fisheries management: an overview and outlook Yvan Papa , Tom Oosting , Noemie Valenza-Troubat , Maren Wellenreuther & Peter A. Ritchie To cite this article: Yvan Papa , Tom Oosting , Noemie Valenza-Troubat , Maren Wellenreuther & Peter A. Ritchie (2020): Genetic stock structure of New Zealand fish and the use of genomics in fisheries management: an overview and outlook, New Zealand Journal of Zoology, DOI: 10.1080/03014223.2020.1788612 To link to this article: https://doi.org/10.1080/03014223.2020.1788612 View supplementary material Published online: 13 Jul 2020. Submit your article to this journal Article views: 157 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=tnzz20 NEW ZEALAND JOURNAL OF ZOOLOGY https://doi.org/10.1080/03014223.2020.1788612 REVIEW ARTICLE Genetic stock structure of New Zealand fish and the use of genomics in fisheries management: an overview and outlook Yvan Papa a, Tom Oosting a, Noemie Valenza-Troubat a,b, Maren Wellenreuther b,c and Peter A. Ritchie a aSchool of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand; bNew Zealand Institute for Plant and Food Research Ltd, Nelson, New Zealand; cSchool of Biological Sciences, University of Auckland, Auckland, New Zealand ABSTRACT ARTICLE HISTORY Sustainable management of wild fisheries requires accurate Received 18 February 2020 delineation of reproductively isolated stocks to avoid depletion of Accepted 24 June 2020 a commercially and ecologically important resource. However, HANDLING EDITOR there is still a lack of reliable information on stock structure for Jonathan Banks most fishery species in New Zealand. DNA markers can assist in the delineation of stocks, but they also can provide significant KEYWORDS insights into other areas related to the genetic diversity and the Climate change; response to pressures. In this review, we first provide a detailed conservation; fishing-induced summary of the population genetic studies of New Zealand fish evolution; genetic diversity; species, with a particular focus on hoki, orange roughy, snapper, genome-wide sequencing; ling, and blue cod. We find that genetic data is uniformly lacking population structure; review; for most species. We then discuss how the global shift from low teleost resolution markers to genomics in fisheries genetics has far reaching consequences for the sustainable management of our aquatic resources, by allowing us to address multiple important pressures that wild fisheries are currently facing, and we introduce some of these briefly. We conclude by emphasising the need for a more systematic and holistic approach for the use of genomics in New Zealand fisheries management, so that the best evidence is available to inform the decisions of policy makers. Introduction The New Zealand Exclusive Economic Zone (EEZ, Figure 1) covers more than 4,000,000 km2 of ocean and is one of the 10 largest EEZ in the world (Migiro 2018). Wild capture fisheries in the New Zealand EEZ are made up of more than 100 species, and around 600,000 tonnes are harvested annually. In an effort to ensure sustainable utilisation of this resource, spatial, temporal, and size limits are set using a Quota Management System that divides New Zealand waters into Quota Management Areas. Currently, 98 species or groups of species of fishes, invertebrates, and seaweeds are managed as one or more stocks under the Quota Management System (Fisheries New Zealand 2019a). Each stock has an annual Total Allowable Catch, which is supposed to be the upper limit of biomass that can be removed without overfishing the stock. Sustainable catch limits, which Total CONTACT Yvan Papa [email protected] Supplemental data for this article can be accessed https://doi.org/10.1080/03014223.2020.1788612. This article has been corrected with minor changes. These changes do not impact the academic content of the article. © 2020 The Royal Society of New Zealand 2 Y. PAPA ET AL. Figure 1. Sampling localities for fish population genetic studies in New Zealand. The dashed line shows the boundary of the New Zealand Exclusive Economic Zone (EEZ), and the continuous line is the 1000 m bathymetric contour, which is the approximate edge of the continental shelf. New Zealand is bathed from the west by water masses of different temperatures: the warm Subtropical Inflow and the cold Subantarctic Inflow. The warm Tasman Front and Subtropical Front are associated with the main flowing surface currents that might influence fish dispersal around New Zealand. The Subtropical Front separates the warmer northern waters from the colder polar water masses of the Subantarctic Inflow at the Subtropical Convergence (STC, dotted line). South of New Zealand and the Campbell Plateau is the deeper Subantarctic Front and associated cold Antarctic Circumpolar Current. (Currents based on a map from the National Institute of Water and Atmospheric Research). NEW ZEALAND JOURNAL OF ZOOLOGY 3 Allowable Catch are based on, are traditionally set using the results of stock assessments when such data are available (Beddington et al. 2007; Gibbs 2008). Properly identifying the boundaries of fisheries stocks is crucial because it is a necessary parameter in any stock assessment model (Begg et al. 1999; Waples et al. 2008; Cadrin et al. 2014a). Moreover, discrepancies between biological populations and management units can result in overex- ploitation of stocks (Reiss et al. 2009; Benestan 2019) and lack of knowledge of biological spatial structure has already resulted in important fisheries collapses (Cadrin 2020). Overfishing of the infamous Atlantic northern cod in the late 1980s, depletion of small spawning areas of Atlantic herring in the Northwest Atlantic, and overexploitation of crustacean fisheries in the Gulf of Alaska, which all led to dramatic fisheries collapses, have all been attributed, at least partially, to mismatches between the spatial management or assessment units and the actual population structure (Orensanz et al. 1998; Smedbol and Stephenson 2001). In spite of those potential issues, the current lack of knowledge of fisheries biological stock boundaries in New Zealand makes it impossible to know with certainty if they are matched with their assessment and management stock bound- aries. Current stock hypotheses that are reported from New Zealand fisheries assessment literature (i.e. Fisheries New Zealand 2018) are either inexistent or are based on various types of observations and scientific data, often sparse, and rarely match the Quota Man- agement Areas (Table S1). The value of genetics in fisheries stock delineation and fisheries management Over the last decade there have been increasing efforts to use a holistic approach to delin- eate fish stocks, by combining the results obtained from multiple methods such as physical tagging, morphometrics, parasites as biological tags, life history data (growth, age compo- sition, reproduction, and distribution), otolith chemistry, and genetics (Abaunza et al. 2008; Espeland et al. 2008; Baldwin et al. 2012; Tanner et al. 2014; Zemeckis et al. 2014; Cadrin et al. 2014b; Izzo et al. 2017; Corrigan et al. 2018). The rationale is that these methods capture evidence from different biological processes which can operate over different temporal and spatial scales. As an example, differences in levels of metal ions and trace elements accumulated in otoliths during time spent at a particular locality can be used to infer residency or migratory events on an ecological time scale (months– a few decades). Otolith microchemistry markers thus provide direct measures of what an individual has done and where it has been. In contrast, genetic loci are markers that can be used to estimate levels of connectivity at evolutionary time scales (decades–thou- sands of years). The latter utilises a sample of characters that remain permanent in indi- viduals and are partially passed down from one generation to the next (Tanner et al. 2016). These markers are indirect because they measure the consequences of what other individ- uals (the ancestors) have done and where they have been. Information from genetic markers is said to provide the most definitive inference of reproductive isolation (Cadrin 2020), although it is important to take into account the intrinsic characteristics of the markers studied, i.e. the mutation rate and the vulnerability to natural selection, in order to interpret results properly. Using genetic markers either as a standalone method or as part of an integrative approach has led to numerous advances towards establishing the levels of connectivity and structure of fisheries stocks. Recent examples include the discovery of four 4 Y. PAPA ET AL. reproductively isolated stocks of beaked redfish in the North Atlantic (Cadrin et al. 2010), three stocks of Atlantic cod that reproduce at different times of year on the East Coast of North America (Kovach et al. 2010), five global populations of silky sharks based on mito- chondrial DNA control region sequences (Clarke et al. 2015), significant genetic popu- lation structure among Greenland lumpfish (Garcia-Mayoral et al. 2016) and Greenland halibut (Westgaard et al. 2017), two mitochondrial lineages of night sharks in the West Atlantic (Domingues et al. 2019), and two genetic stocks of Australasian snapper