DOI: 10.5061/dryad.wdbrv15z2
title: Mixed-stock analysis reveals long-distance movements and few populations with large harvest contributions in lake-migratory brook trout

description: Effective fishery management relies on knowing the relative contributions
 of distinct populations to mixed-stock harvests. Mixed-stock analyses
 increasingly adopt single-nucleotide polymorphism (SNP) panels but could
 make better use of precise spatial information to improve understanding of
 population distributions, movements, and structure. Together with local
 partners, we collected and georeferenced 1051 samples of lake-migratory
 brook trout between 2020-2022 from three large lakes in Quebec
 (Mistassini, Mistasiniishish, Waconichi). We then used a GT-seq
 (Genotyping-in-Thousands by sequencing) SNP panel to infer population
 genetic structure and determine spatial harvest contributions of
 genetically distinct populations. Our results revealed population
 structure in two of three study lakes, with few populations (n = 1-2)
 contributing the majority (&gt; 80%) of mixed-stock harvest in each
 lake. We also detected extensive movements of brook trout within and
 between lakes, spatial segregation of populations in one lake, and an
 unknown (unsampled) population in another lake. Our results illustrate the
 precision afforded by combining GT-seq and georeferencing of samples to
 generate insights into the ecology and genetics of migratory fishes,
 thereby facilitating local decision-making for sustainable fisheries.
description: # Mixed-stock analysis reveals long-distance movements and few populations
 with large harvest contributions in lake-migratory brook trout
 [https://doi.org/10.5061/dryad.wdbrv15z2](https://doi.org/10.5061/dryad.wdbrv15z2) ## Description of the data and file structure This compressed folder contains all input data as well as scripts/code required to generate outputs from that data. The data is organized in folders, and each folder is named after its related analysis (e.g., the folder "CPUE" contains all data and code associated with catch-per-unit-effort analyses discussed in our research article "Mixed-stock analysis reveals long-distance movements and few populations with large harvest contributions in lake-migratory brook trout"). ### Files and variables #### Folder: CPUE **Description:** Contains two sub-folders: mistassini_rivers_cpue & mixed-stock_fishery_cpue. Each folder contains an R file to run the respective analyses (e.g., R file "annual_mixed_stock_fishery_cpue_analysis" contains the code required to run linear regression on the catch-per-unit-effort data of the three study lakes). Raw input files for each analysis are contained in the same location as the R files. **.csv file: mistassini_rivers_cpue_raw** *population_year*: Name of source population followed by the time period in brackets (). *CPUE*: raw catch-per-unit-effort calculated as the number of fish caught per angler per 8-hour fishing day. **R file: mistassini_sources_cpue_visualization** Script that requires R to run. Uses mistassini_rivers_cpue_raw as input data and generates a box plot for visualization. **.csv files: albanel_cpue, mistassini_cpue, waconichi_cpue** *year*: year the data was collected *CPUE*: annual catch-per-unit-effort calculated as the number of fish caught per angler per 8-hour fishing day. **R file: annual_mixed_stock_fishery_cpue_analysis** Script that requires R to run. Uses albanel_cpue, mistassini_cpue, and waconichi_cpue as input data to run a linear regression on each lake's CPUE over time. #### Folder: Rubias **Description:** Contains one R file: mixed_stock_assignments; and one .txt file: dataR_source_and_mixed_stock. This R file contains scripts to run mixed-stock assignment analyses. **.txt file: dataR_source_and_mixed_stock** *sample_type*: type of collected sample (reference or mixture). Reference samples are collected from spawning individuals in their source rivers, and mixture samples are collected from mixed-stock individuals in the lakes. *repunit*: reporting unit of the individual. For mixture individuals, this field is null because their source population is unknown. *collection*: river or lake in which the sample was collected. *indiv*: individual fish identification. *LG01_100261162_1 to LG42_1816745_1.1*: Alleles of loci included in the SNP panel. Each field contains a single letter: A, C, T, or G (or NA for null fields). The letter corresponds to the sequenced nucleotide at a given allele of a given locus for a given individual. **R file: mixed_stock_assignment** A script that requires R to run. Uses dataR_source_and_mixed_stock as input data to run mixed-stock analyses and assign mixture individuals to their population of origin based on the allele frequencies of the reference samples. #### Folder: snpR\_for\_PCA\_and\_Fst **Description:** Contains one R markdown file: snpr_analyses; and two .txt files: 5sources_brooktrout_data & 6sources_brooktrout_data. The R markdown file contains scripts to run population structure analyses. **.txt file: 5sources_brooktrout_data** *indiv*: individual fish identification. *pop*: population of origin. For spawning individuals, this field contains the name of one of five known source populations (named after the river in which they spawn). For mixed-stock individuals, this field contains the name of the lake in which they were sampled. *LG01_100261162_1 to LG42_1816745_1*: Loci included in the SNP panel. Each field contains a pair of the following letters: A, C, T, or G (or NN for null fields). The letters correspond to the sequenced nucleotides at both alleles of a given locus for a given individual. **.txt file: 6sources_brooktrout_data** *indiv*: individual fish identification. *pop*: population of origin. For spawning individuals, this field contains the name of one of six source populations (five known populations named after the river in which they spawn, and a putative sixth population detected through structure and mixed-stock analyses; see our research article "Mixed-stock analysis reveals long-distance movements and few populations with large harvest contributions in lake-migratory brook trout"). For mixed-stock individuals, this field contains the name of the lake in which they were sampled. *LG01_100261162_1 to LG42_1816745_1*: Loci included in the SNP panel. Each field contains a pair of the following letters: A, C, T, or G (or NN for null fields). The letters correspond to the sequenced nucleotides at both alleles of a given locus for a given individual. **R markdown file: snpr_analyses** A script that requires R to run. Uses 5sources_brooktrout_data or 6sources_brooktrout_data  as input data to run population structure analyses via Principal Component Analysis, as well as calculate pairwise fixation index (Fst), expected heterozygosity (He), observed heterozygosity (Ho), Wright’s inbreeding coefficient (Fis), and the number of private alleles of all source populations. Step-by-step comments are included in the code to guide the user through the analysis. #### Folder: STRUCTURE\_6sources **Description:** Contains one R file: 6sources_STRUCTURE_analysis; one .txt file: labels_pop_all; and one sub-folder: STRUCTURE_runs. The R file contains scripts to generate and analyze STRUCTURE plots for the 6-source dataset, using the raw STRUCTURE runs contained in the STRUCTURE_runs subfolder.  **.txt file: labels_pop_all** *pop*: population of origin. This list is used by the R script to label and group individuals by population for visualization in STRUCTURE plots. **R file: 6sources_STRUCTURE_analysis** A script that requires R to run. Uses the files contained in the sub-folder STRUCTURE_runs to generate STRUCTURE plots and results of individual assignment to population clusters. **Sub-folder: STRUCTURE_runs** Contains 35 files corresponding to 35 runs on the program STRUCTURE.  *k1_run_1 to k7_run_35*: Individual runs for K = 1 to K = 7 (i.e., from one population cluster to seven population clusters used by the program to assign individuals based on relatedness from allele frequencies). Each K was run five times for robustness, for a total of 35 runs from K = 1 to K = 7. #### Folder: Temporal\_comparison\_MANOVA **Description:** Contains one R file: temporal_comparison; and two .csv files: 2021_vs_2022 & historical_vs_contemporary. The R file contains the code to run MANOVA tests for stability in the spatial distribution of Mistassini Lake's populations over time. Raw input files are contained in the same location as the R file. **.csv file: 2021_vs_2022** *sector*: spatial sector of Mistassini Lake (see our research article "Mixed-stock analysis reveals long-distance movements and few populations with large harvest contributions in lake-migratory brook trout" for details on the lake's division into nine sectors). *year*: sampling year. *RUP_prop*: proportion of individuals originating from Rupert River found in a given sector of the lake. *inflows_prop*: proportion of individuals originating from the inflow rivers (Cheno and Papas) found in a given sector of the lake. **.csv file: historical_vs_contemporary** *sector*: spatial sector of Mistassini Lake (see our research article "Mixed-stock analysis reveals long-distance movements and few populations with large harvest contributions in lake-migratory brook trout" for details on the lake's division into nine sectors). *year*: historical or contemporary time period. Historical time period corresponds to "year00to01" (i.e., 2000 to 2001), and contemporary time period corresponds to "year21to22" (i.e., 2021 to 2022). *RUP_prop*: proportion of individuals originating from Rupert River found in a given sector of the lake. *inflows_prop*: proportion of individuals originating from the inflow rivers (Cheno and Papas) found in a given sector of the lake. **R file: temporal_comparison** Script that requires R to run. Uses 2021_vs_2022 and historical_vs_contemporary as input data to run MANOVAs testing for the effects of sector and time on the population proportions found within Mistassini Lake. ## Code/software R or RStudio (preferred) is required to view and run the scripts contained in this dataset. The raw data files (.csv or .txt) can be viewed with any text reader. The required packages will all get installed and loaded when the scripts are run.