DOI: 10.5061/dryad.80gb5mkqc
title: Morphometric trait measurements of Arctic char in foothill lakes of arctic Alaska

description: Polymorphism facilitates coexistence of divergent morphs (e.g.,
 phenotypes) of the same species by minimizing intraspecific competition,
 especially when resources are limiting. Arctic char (Salvelinus sp.) are a
 Holarctic fish often forming morphologically, and sometimes genetically,
 divergent morphs. In this study, we assessed the morphological and genetic
 diversity and divergence of 263 individuals from seven populations of
 arctic char with varying length-frequency distributions across two
 distinct groups of lakes in northern Alaska. Despite close geographic
 proximity, each lake group occurs on landscapes with different glacial
 ages and surface water connectivity, and thus were likely colonized by
 fishes at different times. Across lakes, a continuum of physical (e.g.,
 lake area, maximum depth) and biological characteristics (e.g., primary
 productivity, fish density) exists, likely contributing to characteristics
 of present-day char populations. Although some lakes exhibit bimodal size
 distributions, using model-based clustering of morphometric traits
 corrected for allometry, we did not detect morphological differences
 within and across char populations. Genomic analyses using 15,934 SNPs
 obtained from genotyping-by-sequencing demonstrated differences among lake
 groups related to historical biogeography, but within lake groups and
 within individual lakes, genetic differentiation was not related to total
 body length. We used PERMANOVA to identify environmental and biological
 factors related to observed char size structure. Significant predictors
 included water transparency (i.e., a primary productivity proxy), char
 density (fish·ha-1), and lake group. Larger char occurred in lakes with
 greater primary production and lower char densities, suggesting less
 intraspecific competition and resource limitation. Thus, char populations
 in more productive and connected lakes may prove more stable to
 environmental changes, relative to food-limited and closed lakes, if lake
 productivity increases concomitantly. Our findings provide some of the
 first descriptions of genomic characteristics of char populations in
 arctic Alaska, and offer important consideration for the persistence of
 these populations for subsistence and conservation.
description: We sampled arctic char in 2016
 (May-Sept) and 2017 (May) via gill nets and hook-and-line sampling. We
 used eight panel, experimental benthic gill nets (gill net mesh size range
 = 18 – 64 mm; Lester et al. 2009) set perpendicular to shore on the lake
 bottom, which extended from the littoral zone to bottom depths in open
 water areas, and checked nets every half hour to minimize mortalities. We
 conducted hook-and-line sampling alone through the ice (May) and
 concurrently with gill nets during open water periods. We used a mix of
 hook-and-line methods (e.g., lure size), in addition to experimental gill
 nets, to sample char across sizes classes. We sampled all lakes at similar
 time periods and used same sampling methods at each lake. Therefore, we
 are confident we sampled across all fish greater than approximately 115 mm
 (but see Finstad and Berg 2004).. For example, hook-and-line sampling was
 conducted both littoral and in open water habitats throughout the water
 column. For each arctic char captured, we measured, weighed, and then
 photo-documented the fish on a grid board for later trait measurement. We
 placed each fish flat, oriented head to the left, and photographed the
 fish from approximately 60 cm directly above the fish prior to releasing
 the char. We subsequently used photos to make
 morphometric measurements (mm) including: snout length (SL), eye width
 (EW), maxilla length (ML), head depth (HD), head length (HL), body depth
 posterior (BDP), body depth anterior (BDA), post pelvic fin length (PPF)
 and caudal peduncle depth (CP), using the software program ImageJ (e.g.,
 Skoglund et al., 2015; Figure 2). To account for allometric size
 differences, we first log-transformed measurements to reduce heterogeneity
 in variance, and then size-adjusted our measurement using an allometric
 growth formula (e.g., Senar et al., 1994):   <i>log</i><sup><i>10</i></sup><i>Y</i><sub><i>i</i></sub><i>= </i><i>log</i><sup><i>10</i></sup><i>M</i><sub><i>i</i></sub><i>+b(</i><i>log</i><sup><i>10</i></sup><i>L</i><sub><i>m</i></sub><i>- </i><i>log</i><sup><i>10</i></sup><i>L</i><sub><i>i</i></sub><i>)</i>   where <i>Y<sub>i</sub></i> is the size-adjusted trait value, <i>M<sub>i</sub></i> is the measured trait value, <i>L<sub>i</sub></i><sub> </sub>is the measured total length,<i> b</i> is the slope of the log-transformed measured trait (<i>log<sup>10</sup>M<sub>i</sub></i>) against log-transformed total length (<i>log<sup>10</sup>L<sub>i</sub></i>), and <i>L<sub>m</sub></i> is the mean total length for all fish (e.g., all char for comparisons across lakes, all char within a lake for within lake comparisons).