Recent work has revealed the importance of contemporary evolution for shaping ecological outcomes. In particular, rapid evolutionary divergence between populations has been shown to impact the ecology of populations, communities, and ecosystems. While studies have focused largely on the role of adaptive divergence in generating ecologically-important variation among populations, much less is known about the role of gene flow in shaping ecological outcomes. After divergence, populations may continue to interact through gene flow, which may influence evolutionary and ecological processes. Here we investigate the role of gene flow in shaping the contemporary evolution and ecology of recently diverged populations of anadromous steelhead / resident rainbow trout (Oncorhynchus mykiss). Results show that resident rainbow trout introduced above waterfalls have diverged evolutionarily from downstream anadromous steelhead, which were the source of introductions. However, the movement of fish from above to below the waterfalls has facilitated gene flow, which has reshaped genetic and phenotypic variation in the anadromous source population. In particular, gene flow has led to an increased frequency of residency, which in turn has altered population density, size-structure, and sex ratio. This result establishes gene flow as a contemporary evolutionary process that can have important ecological outcomes. From a management perspective, anadromous steelhead are generally regarded as a higher conservation priority than resident rainbow trout, even when found within the same watershed. Our results show that anadromous and resident O. mykiss populations may be connected via gene flow, with important ecological consequences. Such eco-evolutionary processes should be considered when managing recently diverged populations connected by gene flow.

Our study used a historical translocation of anadromous O. mykiss above waterfalls on two tributaries of a coastal California watershed as the experimental basis for studying the effects of genetic divergence and one-way gene flow on a founding population. We integrated historical records and paired surveys above and below barriers on two tributaries to explore how variation in downstream dispersal and gene flow influence the distribution of genotypes, phenotypes, and population density and size structure. We sampled O. mykiss at a number of study sites distributed across the watershed, resulting in the datasets described in the following sections.

Genetic Data

We used single nucleotide polymorphism (SNP) data at both neutral and adaptive loci to analyze patterns of population differentiation and gene flow.

Caudal fin tissue samples were extracted in 96-well plates using the DNeasy Blood and Tissue Kit following the manufacturer's specifications with the BioRobot 3000 (Qiagen Inc. Gaithersburg, MD, USA). Individuals were genotyped using a 95-SNP panel developed for performing genetic stock identification and parentage-based analysis in O. mykiss, following the methods of Abadía-Cardoso et al. (2011, 2013) and Pearse and Garza (2015). Two negative controls were included in each array, and genotypes were called using SNP Genotyping Analysis Software (Fluidigm, South San Francisco, CA, USA). Additionally, a Y chromosome-linked sex identification assay was used to categorize individuals as male or female (Brunelli et al., 2008).

Mark/Recapture Data

We used mark-recapture data, including a mixture of physical capture and PIT tag antenna detection data, to monitor fish movement and explore movement patterns for genotyped fish. 

The initial marking of individuals occurred at each of the nine study sites, such that all captured individuals ≥ 65 mm FL were issued a 12 mm passive integrated transponder (PIT) tag (Oregon RFID Inc., Portland, OR, USA) via intraperitoneal injection. Recapture information was generated year-round through a variety of life cycle monitoring efforts, including passive detection events at two stationary PIT tag antenna arrays; electrofishing surveys, estuary/lagoon seining, and downstream migrant trapping. We recorded the geographic location of each observation, and for physical recaptures, we re-measured the individual for FL and mass. Additionally, we used data generated at two stationary PIT tag antenna arrays to infer the emigration of individuals out of the watershed.

Our data set includes all fish that were (1) first captured and PIT tagged at one of our 8 study sites located in the upper watershed (i.e., above the confluence of Big Creek and the Mainstem) during our 2017-19 field seasons, and (2) genotyped for Omy05 and genetic sex. We used recapture histories to identify “migrants”—defined as individuals whose final encounter occurred in the lower watershed. Fish that were (1) detected repeatedly in the lower watershed for a period of > 2 weeks (i.e., “milling”), or (2) at large for > 1.5 years between initial and final encounter (i.e., “too old”) were not considered migrants.

Demographic Data

We used population survey data to estimate density and population size structure over three consecutive years (2017–2019). Sampling took place within a two-week window during low (base) flow conditions (August/September) to minimize the potential for individuals to disperse among sampling sites. Environmental and hydrological conditions remained fairly constant throughout each annual sampling period. During each fish sampling event, we installed block nets (6 mm mesh) at the upstream and downstream ends of the site and collected fish from the area between the nets using a backpack electrofisher (Model LR-24; Smith-Root Inc., Vancouver, WA, USA). To quantify fish abundance and size distribution at each site, we employed multiple-pass depletion (removal) methods, completing three passes of equal effort by time in most cases. However, additional passes were completed when cumulative catch increased by more than 50% between the previous two passes. Following capture, we anesthetized O. mykiss with tricaine methanesulphonate (MS-222; Western Chemical Inc., Ferndale, WA, USA), measured for fork length (FL; ± 1.0 mm) and wet mass (± 0.1 g).