Describing Fine‐Scale Patterns of Genetic Structure and Introgression of Redband Trout in a Complex River System

Abstract

The conservation status of Redband Trout Oncorhynchus mykiss gairdneri has been an increasing concern of fish managers. Effective fish management first requires an understanding of the spatial distribution of distinct populations and the processes influencing gene flow. We performed a genetic analysis of Redband Trout from the Deschutes River basin in central Oregon to discern population genetic structure and the genetic impacts of an extensive hatchery stocking program and several potential barriers to dispersal. Conducting surveys in lateral habitats, we sampled over 1,400 young‐of‐the‐year Redband Trout and genotyped them at a panel of 269 SNPs using genotyping‐in‐thousands by sequencing. We found that within this section of the Deschutes River basin there were multiple distinct genetic groups of Redband Trout, with an irrigation diversion dam and only one of eight waterfalls in the study area acting as complete barriers to gene flow. Within these distinct genetic groups there was a strong signal of isolation by distance. Despite the extensive stocking of large numbers out‐of‐basin hatchery Rainbow Trout Oncorhynchus mykiss, our results indicated that introgression of wild fish occurred only with a locally derived hatchery strain of Redband Trout. Hatchery influence was greatest in Fall River and in neighboring portions of the Deschutes River. The combination of spatially explicit sampling in lateral habitat with genotyping via high‐throughput sequencing provided an effective sampling design for this large river and its tributaries. Such an approach may be useful elsewhere for identifying genetic management units of Redband Trout and other widespread freshwater fishes.

Genetic analysis of red deer (Cervus elaphus) administrative management units in a human-dominated landscape

“…R I/E > 1 would indicate that the rate of immigration in a population is higher than the emigration rate and vice versa for R I/E < 1. Finally, we note that the results of the divMigrate analysis do not necessarily represent actual migration but rather estimate the probability of the exchange of genes between two sampling locations (Marrotte et al 2017;Bohling et al 2019). Further, relative migration rates are estimated across all pairs of included populations and do not account for spatial context or distance between them.…”

“…Most of the AMUs with lower mean rates of immigration as compared to emigration rates (Table 3) are characterized by either small population sizes, low densities, or higher levels of isolation, suggesting that they probably received fewer genes from other populations in the past. Relative to the other populations they are therefore more likely to send out individuals (Bohling et al 2019). Genetic similarity, for example due to historical reasons, will also lead to positive values of inferred migration.…”

Urbanization reduces gene flow but not genetic diversity of stream salamander populations in the New York City metropolitan area

“…When dispersal distance spatially limits species, populations geographically farther apart will have greater genetic differentiation between them, a pattern known as isolation‐by‐distance (IBD; Wright, 1943). Alternatively, urban habitat degradation in the terrestrial landscape caused by roadways (Fenderson et al., 2014; Serieys, Lea, Pollinger, Riley, & Wayne, 2015), buildings (Beninde, Veith, & Hochkirch, 2015), loss of green space (Spear, Peterson, Matocq, & Storfer, 2005), or dams (Bohling, Starcevich, Von Bargen, & Bailey, 2019) may produce nonpermeable barriers restricting gene flow between populations (isolation‐by‐barrier; IBB; Smouse, Long, & Sokal, 1986). Both IBD and IBB ultimately shape patterns of genetic variation within and between populations.…”