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Methods for Identifying Species Complexes Using a Novel Suite of Multivariate Approaches and Multiple Data Sources: a Case Study with Gulf of Alaska Rockfish

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Methods for Identifying Species Complexes Using a Novel Suite of Multivariate Approaches and Multiple Data Sources: a Case Study with Gulf of Alaska Rockfish fmars-08-663375 August 10, 2021 Time: 11:40 # 1 ORIGINAL RESEARCH published: 11 August 2021 doi: 10.3389/fmars.2021.663375 Methods for Identifying Species Complexes Using a Novel Suite of Multivariate Approaches and Multiple Data Sources: A Case Study With Gulf of Alaska Rockfish Kristen L. Omori1*, Cindy A. Tribuzio2, Elizabeth A. Babcock3 and John M. Hoenig1 1 Department of Fisheries Science, Virginia Institute of Marine Science, William & Mary, Gloucester Point, VA, United States, 2 Auke Bay Laboratories, Alaska Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Juneau, AK, United States, 3 Department of Marine Biology and Ecology, Rosenstiel School of Marine and Atmospheric Sciences, University of Miami, Miami, FL, United States International and national laws governing the management of living marine resources generally require specification of harvest limits. To assist with the management of Edited by: data-limited species, stocks are often grouped into complexes and assessed and Natalie Anne Dowling, managed as a single unit. The species that comprise a complex should have similar Oceans and Atmosphere (CSIRO), Australia life history, susceptibility to the fishing gear, and spatial distribution, such that common Reviewed by: management measures will likely lead to sustainable harvest of all species in the José Lino Vieira De Oliveira Costa, complex. However, forming complexes to meet these standards is difficult due to the University of Lisbon, Portugal Lyall Bellquist, lack of basic biological or fisheries data to inform estimates of biological vulnerability The Nature Conservancy, and fishery susceptibility. A variety of cluster and ordination techniques are applied to United States bycatch rockfish species in the Gulf of Alaska (GOA) as a case study to demonstrate *Correspondence: how groupings may differ based on the multivariate techniques used and the availability Kristen L. Omori [email protected] and reliability of life history, fishery independent survey, and fishery catch data. For GOA rockfish, our results demonstrate that fishing gear primarily defined differences in species Specialty section: composition, and we suggest that these species be grouped by susceptibility to the This article was submitted to Marine Ecosystem Ecology, main fishing gears while monitoring those species with high vulnerabilities to overfishing. a section of the journal Current GOA rockfish complex delineations (i.e., Other Rockfish and Demersal Shelf Frontiers in Marine Science Rockfish) are consistent with the results of this study, but should be expanded across the Received: 02 February 2021 Accepted: 16 July 2021 entire GOA. Differences observed across species groupings for the variety of data types Published: 11 August 2021 and multivariate approaches utilized demonstrate the importance of exploring a diversity Citation: of methods. As best practice in identifying species complexes, we suggest using a Omori KL, Tribuzio CA, productivity-susceptibility analysis or expert judgment to begin groupings. Then a variety Babcock EA and Hoenig JM (2021) Methods for Identifying Species of multivariate techniques and data sources should be used to identify complexes, Complexes Using a Novel Suite while balancing an appropriate number of manageable groups. Thus, optimal species of Multivariate Approaches and Multiple Data Sources: A Case complex groupings should be determined by commonality and consistency among a Study With Gulf of Alaska Rockfish. variety of multivariate methods and datasets. Front. Mar. Sci. 8:663375. doi: 10.3389/fmars.2021.663375 Keywords: stock complex, species assemblage, cluster analysis, ordination analysis, data-limited fisheries Frontiers in Marine Science| www.frontiersin.org 1 August 2021| Volume 8| Article 663375 fmars-08-663375 August 10, 2021 Time: 11:40 # 2 Omori et al. Multivariate Approaches for Species Complexes INTRODUCTION remains a difficult scientific problem. No single method has proven robust for all species complex grouping approaches, and The requirement to implement catch limits for data-limited and often development of species complexes relies on a combination previously unassessed stocks resulting from recent international of qualitative (i.e., expert judgement) and quantitative measures. policies, such as the Magnuson-Stevens Reauthorization Act Productivity-susceptibility analysis (PSA) has been proposed of 2006 (MSRA, 2007) and Common Fisheries Policy (CFP, as a tool for grouping data-limited species based primarily 2013), presents scientific and management challenges for regional on expert judgment (Patrick et al., 2010; Cope et al., fishery management entities. Managing an aggregation of fish 2011). A PSA bins information (i.e., life history values and stocks or species as a single unit is one approach utilized by impact by fisheries indicators) in productivity or susceptibility fisheries managers in an attempt to comply with international categories based on expert judgement. The rankings within and federal laws (Jiao et al., 2009), reduce the number of each category are calculated into an overall vulnerability score, required stock assessments (Koutsidi et al., 2016), and create which is thereby used to summarize species into groups. manageable harvest regulations. These aggregations, also known However, PSA may not be as useful when forming complexes as stock or species complexes, are often determined by similarity with closely related species with poor quality data, because in life history characteristics, vulnerability to the fishery, and vulnerability rankings are likely to be too similar despite geographic distributions (USOFR, 2009). Multiple stocks of a having the possibility of scoring differently in the susceptibility single species being managed together are likely to have strong categories. For example, Cope et al.(2011) determined that similarities in life history and susceptibility, whereas complexes vulnerability rankings from a PSA could not alone be used to consisting of multiple species have more diverging characteristics establish complexes for rockfish species in the United States in productivity (i.e., life history traits), behavior, and habitat West Coast groundfish fishery. A hierarchical tiered approach preference. Species in a complex are typically caught in a was implemented by applying clustering analyses first using multispecies fishery and often lack adequate data for a single ecological distribution (i.e., depth and latitude), followed by using species assessment (USOFR, 2009). the vulnerability scores. Yet, the use of expert judgment for Assigning species to complexes can be a difficult, but scoring vulnerability was considered problematic for species with critical task for implementing sustainable management of such poor quality data. data-limited species. Complexes are often formed using a Alternately, multivariate techniques (e.g., cluster analyses and combination of life history traits, trophic roles, and fishing ordination methods) are a quantitative tool used for identifying pressure (Shertzer and Williams, 2008). However, rarely is the similarities among species when adequate species-specific data full extent of this information available to adequately determine are available. Of the few quantitative studies that have developed the appropriateness of a complex grouping, and there can species complexes, the combination of expert judgment and be a mismatch in groupings when using life history traits multiple data sources or multivariate approaches (or both) have compared to fishery susceptibility (i.e., species caught together typically been used to assign species to appropriate groups. by the same gear types). Grouping species based on life history For example, both ordination and clustering methods can be characteristics, which represent the population’s productivity, used to examine species assemblages using one data source is important because species with similar growth and maturity (e.g., Lee and Sampson, 2000; Williams and Ralston., 2002), often demonstrate similar responses to fishing pressure (e.g., or multiple data sources with each dataset being analyzed Farmer et al., 2016; DeMartini, 2019). From a management separately, summarized and compared to determine species perspective, grouping by susceptibility to fishing gear (e.g., groupings (e.g., Shertzer and Williams, 2008; Pennino et al., multispecies fisheries) is often simpler than grouping by life 2016). Other studies have developed methods to quantitatively history traits, because management by gear type is less easily synthesize findings of species co-occurrence when using multiple enforceable for complexes harvested by a variety of gears. Yet, datasets. For example, Farmer et al.(2016) combined analysis the potential for disproportionate impacts on the species within of multiple catch data matrices along with a life history matrix the complex exists when complexes are formed using gear to assign species to complexes by amalgamating the results susceptibility and when selectivity or availability differs by species from individual hierarchical cluster analyses into a weighted (DeMartini, 2019). mean cluster association index. However, the weighted mean Aggregating species exclusively based on either life history or cluster association index depended on each cluster analyses fishery traits can lead to unsuitable groupings. For example, a from each data source to produce clear, sensible results (i.e., complex formed on fishing vulnerability may group species with no chaining,
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