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Jeffrey B. Olsen

Publications and source records attributed to Jeffrey B. Olsen.

3 recordsLinked to original sources

Potential of environmental DNA to evaluate Northern pike ( Esox lucius ) eradication efforts: An experimental test and case study

Determining the success of invasive species eradication efforts is challenging because populations at very low abundance are difficult to detect. Environmental DNA (eDNA) sampling has recently emerged as a powerful tool for detecting rare aquatic animals; however, detectable fragments of DNA can persist over time despite absence of the targeted taxa and can therefore complicate eDNA sampling after an eradication event. This complication is a large concern for fish eradication efforts in lakes since killed fish can sink to the bottom and slowly decay. DNA released from these carcasses may remain detectable for long periods. Here, we evaluated the efficacy of eDNA sampling to detect invasive Northern pike ( Esox lucius ) following piscicide eradication efforts in southcentral Alaskan lakes. We used field observations and experiments to test the sensitivity of our Northern pike eDNA assay and to evaluate the persistence of detectable DNA emitted from Northern pike carcasses. We then used eDNA sampling and traditional sampling (i.e., gillnets) to test for presence of Northern pike in four lakes subjected to a piscicide-treatment designed to eradicate this species. We found that our assay could detect an abundant, free-roaming population of Northern pike and could also detect low-densities of Northern pike held in cages. For these caged Northern pike, probability of detection decreased with distance from the cage. We then stocked three lakes with Northern pike carcasses and collected eDNA samples 7, 35 and 70 days post-stocking. We detected DNA at 7 and 35 days, but not at 70 days. Finally, we collected eDNA samples ~ 230 days after four lakes were subjected to piscicide-treatments and detected Northern pike DNA in 3 of 179 samples, with a single detection at each of three lakes, though we did not catch any Northern pike in gillnets. Taken together, we found that eDNA can help to inform eradication efforts if used in conjunction with multiple lines of inquiry and sampling is delayed long enough to allow full degradation of DNA in the water.

PLoS ONE

Population genetic structure of Santa Ynez rainbow trout – 2001 based on microsatellite and mtDNA analyses

Microsatellite allelic and mitochondrial DNA (mtDNA) haplotype diversity are analyzed in eight rainbow trout ( Oncorhynchus mykiss ) collections: two from tributaries flowing into the upper Santa Ynez River watershed at Gibraltar Reservoir (Camuesa and Gidney creeks); three from tributaries between Gibraltar and Jameson reservoirs (Fox, Blue Canyon, and Alder creeks); one from a tributary above Jameson Reservoir (Juncal Creek); Jameson Reservoir; and one from the mainstem Santa Ynez River above the Jameson Reservoir. Both analyses reveal a high degree of population structure. Thirteen microsatellite loci are amplified from 376 fish. Population pairwise comparisons show significant differences in allelic frequency among all populations with the exception of Juncal Creek and Jameson Reservoir (p = 0.4). Pairwise F st values range from 0.001 (Juncal Creek and Jameson Reservoir) to 0.17 (Camuesa and Juncal creeks) with an overall value of 0.021. Regression analyses (Slatkin 1993) supports an isolation-bydistance model in the five populations below Jameson Reservoir (intercept = 1.187, slope = -0.41, r2 = 0.67). A neighbor-joining bootstrap value of 100% (based on 2000 replicate trees) separates the populations sampled above and below Juncal Dam. Composite haplotypes from 321 fish generated using mtDNA sequence data (Dloop) reveal four previously described haplotypes (MYS1, MYS3, MYS5 and MYS8; Nielsen et al. 1994a), and one (MYS5) was found in all populations. Mean haplotype diversity is 0.48. Pairwise F st values from mtDNA range from -0.019 to 0.530 (0.177 over all populations) and are larger than those for microsatellites in 26 of 28 pairwise comparisons. In addition, the mtDNA and microsatellites provide contrasting evidence of the relationship of Fox and Alder creeks to the other six populations. Discrepancies between the two markers are likely due to the unique properties of the two marker types and their value in revealing historic (mtDNA) versus contemporary (microsatellites) genetic relationships. The contrasting results may indicate how relationships among the upper Santa Ynez River populations have changed since the installation of Juncal Dam. Comparisons of mtDNA haplotype frequencies from fish collected for this study with samples analyzed previously in JLN’s laboratory (1993) reveal significant differences in mtDNA haplotypes for Fox and Alder creeks. In the 2001 samples from this study, there is a loss of three haplotypes despite larger sample sizes. AMOVA analysis of what we term “upper” (Alder, Fox, Blue Canyon, Camuesa, Gidney creeks and the upper Santa Ynez mainstem) and “lower” (Hilton, Salsipuedes and the lower mainstem Santa Ynez River) Santa Ynez River populations (1993-2001) reveal that 11% of the variance in haplotypes is found between the upper and lower drainage. A comparison of the mtDNA data from this study with those available for southern California coastal and California hatchery O. mykiss populations yields F st values of 0.15 and 0.47, respectively. Differentiation of mtDNA haplotypes for population pairs of Santa Ynez River and hatchery fish show no significant differentiation between wild and at least one hatchery strain in Cachuma Reservoir, Hilton Creek, and the Lower Santa Ynez River.

California

Temporal variation in phenotypic and genotypic traits in two sockeye salmon populations, Tustumena Lake, Alaska

Sockeye salmon Oncorhynchus nerka in two tributary streams (about 20 km apart) of the same lake were compared for temporal variation in phenotypic (length, depth adjusted for length) and genotypic (six microsatellite loci) traits. Peak run time (July 16 versus 11 August) and run duration (43 versus 26 d) differed between streams. Populations were sampled twice, including an overlapping point in time. Divergence at microsatellite loci followed a temporal cline: Population sample groups collected at the same time were not different ( F ST = 0), whereas those most separated in time were different ( F ST = 0.011, P = 0.001). Although contemporaneous sample groups did not differ significantly in microsatellite genotypes ( F ST = 0), phenotypic traits did differ significantly (MANOVA, P < 0.001). Fish from the larger stream were larger; fish from the smaller stream were smaller, suggesting differential fitness related to size. Results indicate run time differences among and within sockeye salmon populations may strongly influence levels of gene flow.

Alaska