Genotyping-in-Thousands by sequencing panel development and application to inform kokanee salmon (Oncorhynchus nerka) fisheries management at multiple scales

The ability to differentiate life history variants is vital for estimating fisheries management parameters, yet traditional survey methods can be inaccurate in mixed-stock fisheries. Such is the case for kokanee, the freshwater resident form of sockeye salmon (Oncorhynchus nerka), which exhibits various reproductive ecotypes (stream-, shore-, deep-spawning) that co-occur with each other and/or anadromous O. nerka in some systems across their pan-Pacific distribution. Here, we developed a multi-purpose Genotyping-in-Thousands by sequencing (GT-seq) panel of 288 targeted single nucleotide polymorphisms (SNPs) to enable accurate kokanee stock identification by geographic basin, migratory form, and reproductive ecotype across British Columbia, Canada. The GT-seq panel exhibited high self-assignment accuracy (93.3%) and perfect assignment of individuals not included in the baseline to their geographic basin, migratory form, and reproductive ecotype of origin. The GT-seq panel was subsequently applied to Wood Lake, a valuable mixed-stock fishery, revealing high concordance (>98%) with previous assignments to ecotype using microsatellites and TaqMan® SNP genotyping assays, while improving resolution, extending a long-term time-series, and demonstrating the scalability of this approach for this system and others.

Evaluating Tag-Reliant Harvest Estimators in Chinook Salmon Mixed-Stock Fisheries Using Simulations

Management of mixed-stock Chinook salmon fisheries requires balancing fishery access and conservation of vulnerable stocks. Although accurate, timely estimates of stock-specific harvest are crucial in achieving competing objectives, limited numbers of stock assignments (e.g., tag recoveries) can diminish the utility of estimates. We used a flexible simulation approach, applied to both a theoretical and real-world fishery case study, to compare the performance of competing monitoring alternatives and estimators for harvest. We sought to improve accuracy for point estimates of harvest and harvest trajectories over time. Bayesian models provided similarly accurate point estimates to existing models at high levels of data aggregation, generally improved estimates of harvest trajectories at intermediate aggregation, and reliable estimates of uncertainty. Incorporation of time-lagged prior information inconsistently improved estimates of harvest trajectories. Among monitoring alternatives yielding equal increases (33%) in CWT recoveries, increasing tagging rates resulted in the greatest decrease in estimate uncertainty for target stocks (37.5 to 45.3%). Variable performances of mixed-stock harvest estimators suggest their use should considered on a stock- and fishery-specific basis, potentially using a simulation-based approach.

Mixed stock analysis of genetic compositions of lake sturgeon (Acipenser fulvescens) mixtures in Lake Michigan: hierarchical spatial heterogeneity and evidence of improving recruitment in Wisconsin spawning populations

Information regarding site occupancy of fish that migrate long distances during non-spawning periods together with estimates of recruitment trends for individual populations can be informative for management, especially when individuals from different spawning populations intermix and are sampled/harvested together. Tendencies for individuals from different populations to preferentially occupy specific regions increases vulnerability to anthropogenic and natural disturbances. Using mixed stock analysis (MSA), we estimated population-specific occupancy of lake sturgeon in open-water and nearshore regions of Lake Michigan across a hierarchy of spatial scales. Open-water mixture composition differed between Lake Michigan’s eastern and western basins. Significant heterogeneity in habitat occupancy was also observed at microgeographic scales throughout open-water regions of Green Bay, indicating non-random occupancy to regions proximal to natal streams. Estimates of relative recruitment levels determined from MSA extensions indicated increasing recruitment trends for spawning populations associated with Wisconsin tributaries (Oconto/Peshtigo, Fox, and Menominee Rivers). Our lake sturgeon results demonstrate the utility of genetic data for informing management efforts for spatially-structured, highly migratory species. Similar analyses could prove beneficial for species with similar characteristics.

KURS RUPIAH, INDEKS NIKKEI 225, BI RATE, DAN PENGARUHNYA TERHADAP STOCK EXCHANGE INDEKS HARGA SAHAM GABUNGAN (IHSG) PERIODE TAHUN 2018-2020

Gross Domestic Product (GDP) growth is a constructive indicator and vice versa. A rise in GDP affects the buying power of citizens positively. It will therefore raise demand for the commodity. A surge in the market for goods raises the firm's earnings and may also increase the stock price. The analysis was designed to examine the impact on composite stock price index using data from time series from January 2018 to December 2020 of Rupiah Exchange rate, Nikkei 225 Index, and BI Rate. Multiple linear regression is used in the mixed Stock Price Index scheme to identify the relevant influence of BI on the Rupiah and Nikkei 225. The test results show that the BI rate has a significant positive effect on the Rupiah exchange rate for the composite stock pricing index. Meanwhile, the Nikkei 225 Index has no impact on the Composite Stock Price Index.

Large inter-stock differences in catch size-at-age of mature Atlantic salmon observed by using genetic individual origin assignment from catch data

Genetic individual assignment of river stock of origin of mixed stock catch fish offers a tool to analyze size differences among river stocks. Data on the genetically identified river stock of origin of individual fish from commercial mixed stock catches were used to compare the catch size-at-age of mature Atlantic salmon catch fish (Salmo salar) from different rivers in the Baltic Sea. In this application of genetic mixed stock modeling, individual assignments of the river stock of origin were analyzed together with length- and weight-at-age data for individual catch fish. The use of four genetic stock identification based methods was compared for defining the length distributions of caught mature salmon in different river stocks. The catch data included information on maturing salmon in the northern Baltic Sea over the years 2000–2013. DNA microsatellite data on 17 loci and information on the smoltification age were used to assign spawners to their stock of origin. All of the compared methods for using probabilistic stock of origin data in our case yielded very similar estimates of the final mean length distributions of the stocks. The Bayesian mixture model yielded slightly more conservative estimates than the direct probability method, threshold method, or the modified probability method. The catch size between spawners of a same sex and age from river stocks differed significantly and the differences were large. The mean catch weight of 1-sea-winter old mature males in different rivers varied from 1.9 kg to 2.9 kg, from 5.1 kg to 7.5 kg for 2-sea-winter old males, from 5.0 kg to 7.2 kg for 2-sea-winter old females, and from 8.2 kg to 10.8 kg for 3-sea-winter-old females. The mean size of caught wild salmon spawners in each year-class was on average smaller than that of the hatchery-reared and sea ranched stocks.