DOI: 10.5061/dryad.6wwpzgn4h
title: Multifaceted framework for defining conservation units: An example from Atlantic salmon (Salmo salar) in Canada

description: Conservation units represent important components of intraspecific
 diversity that can aid in prioritizing and protecting at-risk populations,
 while also safeguarding unique diversity that can contribute to species
 resilience. In Canada, identification and assessments of conservation
 units are done by the Committee on the Status of Endangered Wildlife in
 Canada (COSEWIC). COSEWIC can recognize conservation units below the
 species level (termed “designatable units”; DUs) if the unit has
 attributes that make it both discrete and evolutionarily significant.
 There are various ways in which a DU can meet the criteria of discreteness
 and significance, and increasing access to “big data” is providing
 unprecedented information that can directly inform both criteria.
 Specifically, the incorporation of genomic data for an increasing number
 of non-model species is informing more COSEWIC assessments; thus, a
 repeatable, robust framework is needed for integrating these data into DU
 characterization. Here, we develop a framework that uses a multifaceted,
 weight-of-evidence approach to incorporate multiple data types, including
 genetic and genomic data, to inform COSEWIC DUs. We apply this framework
 to delineate DUs of Atlantic salmon (Salmo salar, L.), an economically,
 culturally, and ecologically significant species that is also
 characterized by complex hierarchical population structure. Specifically,
 we focus on an in-depth example of how our approach was applied to a
 previously data-limited region of northern Canada that was defined by a
 single large DU. Application of our framework with newly available genetic
 and genomic data led to subdividing this DU into three new DUs. Although
 our approach was developed to meet the criteria of COSEWIC, it is widely
 applicable given the similarities in the definitions of a conservation
 unit.
description: Genomic data here includes data used for Labrador, Canada, in the
 main analysis of the paper. Genomic data from a 220,000 SNP array (see
 Barson et al., 2015) developed using a targeted,
 biallelic SNP Affymetrix Axiom array by the Centre for Integrative
 Genetics (CIGENE, Ås, Norway) were compiled for populations of Atlantic
 salmon. Genotyping was performed using the Affymetrix Axiom array protocol
 (Thermo Fisher Scientific), with raw data processed using the Axiom
 Analysis Suite (AAS) software based on the manufacturer's best
 practices protocol. AAS assigns all SNP assays into different categories
 based on clustering patterns, and only SNPs that were classified as high
 quality were used for subsequent analyses. SNPs were filtered using PLINK
 v1.9 (Purcell et al., 2007) for minor allele frequency
 (MAF) of 0.05.
description: # Multifaceted framework for defining conservation units: An example from
 Atlantic salmon (*Salmo salar*) in Canada
 [https://doi.org/10.5061/dryad.6wwpzgn4h](https://doi.org/10.5061/dryad.6wwpzgn4h) ## Description of the data and file structure Data are in plink format (.fam, .bim, .bed), see plink website for full details of formatting [https://www.cog-genomics.org/plink/1.9/formats](https://www.cog-genomics.org/plink/1.9/formats) ### Files and variables #### File: Labrador\_220K\_maf005.fam **Description:** plink .fam file for SNP dataset, which includes ID and population information #### File: Labrador\_220K\_maf005.bed **Description:** plink .bed file for SNP dataset, which includes genotype data #### File: Labrador\_220K\_maf005.bim **Description:** plink .bim file for SNP dataset, which includes all SNP position information (map) ## Code/software Codes used for the manuscript are provided at: [https://github.com/SarahLehnert/Salmon_DUs](https://github.com/SarahLehnert/Salmon_DUs) ## Access information Other publicly accessible locations of the data: * These data are compiled from previously published sources as indicated. Data used here were accessed from previous publications, and these included the 101 microsatellite dataset (Sylvester et al., [2018](https://onlinelibrary.wiley.com/doi/10.1111/eva.13587#eva13587-bib-0087)), 96 SNP dataset (Bradbury et al., [2021](https://onlinelibrary.wiley.com/doi/10.1111/eva.13587#eva13587-bib-0009)), and 220K SNP dataset (Lehnert et al., [2023](https://onlinelibrary.wiley.com/doi/10.1111/eva.13587#eva13587-bib-0054)). Data was derived from the following sources: * Bradbury, I. R., Lehnert, S. J., Messmer, A. M., Duffy, S. J., Verspoor, E., Kess, T., Gilbey, J., Wennevik, V., Robertson, M. J., Chaput, G., Sheehan, T. F., Bentzen, P., Dempson, J. B., & Reddin, D. G. (2021). Range-wide genetic assignment confirms long-distance oceanic migration in Atlantic salmon over half a century. *ICES Journal of Marine Science*, 78, 1434–1443. * Lehnert, S. J., Bradbury, I. R., April, J., Wringe, B. F., Van Wyngaarden, M., & Bentzen, P. (2023). Pre-COSEWIC Review of Anadromous Atlantic Salmon (*Salmo salar*) in Canada, Part 1: Designatable Units. DFO Canadian Science Advisory Secretariat, Res. Doc. 2023/026. * Sylvester, E. V., Beiko, R. G., Bentzen, P., Paterson, I. G., Horne, J. B., Watson, B., Lehnert, S. J., Duffy, S., Clement, M., Robertson, M. J., & Bradbury, I. R. (2018). Environmental extremes drive population structure at the northern range limit of Atlantic salmon in North America. *Molecular Ecology*, 27, 4026–4040.