Variance Components in the Estimation of Potential Egg Deposition of Sockeye Salmon Escapements

1969 ◽  
Vol 26 (3) ◽  
pp. 655-670 ◽  
Author(s):  
Ole A. Mathisen ◽  
Tor Gunnerød
Keyword(s):  
Variance Components ◽  
Variance Component ◽  
Sockeye Salmon ◽  
Bristol Bay ◽  
Egg Deposition ◽  
Average Fecundity

The magnitude of the variance components in the estimation of the potential egg deposition of sockeye salmon escapements to the Kvichak District, Bristol Bay, Alaska, was determined from data collected from 1957 to 1966. The greatest variance component was caused by estimation of the escapement followed by the variance due to estimation of the ratio of females in the escapement. Estimation of the average fecundity added the least variance.

Density, climate, and the processes of prespawning mortality and egg retention in Pacific salmon (Oncorhynchus spp.)

2007 ◽  
Vol 64 (3) ◽  
pp. 574-582 ◽  
Author(s):  
T P Quinn ◽  
D M Eggers ◽  
J H Clark ◽  
H B Rich, Jr.
Keyword(s):  
Sockeye Salmon ◽  
Pacific Salmon ◽  
River System ◽  
Retention Rates ◽  
Bristol Bay ◽  
Egg Retention ◽  
Limited Sampling ◽  
Egg Deposition ◽  
Two Factors

In 2004 and 2005, exceptionally large runs of sockeye salmon (Oncorhynchus nerka) to the Alagnak River system in Bristol Bay, Alaska, coincided with weak runs to the nearby Kvichak River system. Restricted fishing to protect the Kvichak populations resulted in densities on the Alagnak River system's spawning grounds that were 11.5-fold (in 2004) and 9.0-fold (in 2005) above the long-term (1956–2003) average. Carcass sampling indicated that 23% (2004) and 44% (2005) of the potential egg deposition was lost to prespawning mortality or incomplete spawning in the Alagnak populations. Much lower levels of egg retentions were observed in spawning populations in the Kvichak River and Wood River systems, where the runs did not appreciably exceed the escapement goals, indicating that density-dependent spawning failure may have occurred. However, in 2005, significantly higher egg retention rates were observed in the Alagnak River system despite slightly lower densities than in 2004, indicating that environmental processes (probably low river levels and high temperatures) influenced prespawning mortality as well. More limited sampling in 2006 revealed only 3% egg retention in one of the Alagnak populations, but the combination of lower density and cooler conditions did not allow us to determine the relative contributions of these two factors to spawning failure.

scholarly journals Genomic prediction with non-additive effects in beef cattle: stability of variance component and genetic effect estimates against population size

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Akio Onogi ◽  
Toshio Watanabe ◽  
Atsushi Ogino ◽  
Kazuhito Kurogi ◽  
Kenji Togashi
Keyword(s):  
Population Size ◽  
Genomic Prediction ◽  
Variance Components ◽  
Variance Component ◽  
Predictive Accuracy ◽  
Genetic Effect ◽  
Genetic Effects ◽  
Additive Effects ◽  
Additive Variance ◽  
Additive Genetic Effects

Abstract Background Genomic prediction is now an essential technology for genetic improvement in animal and plant breeding. Whereas emphasis has been placed on predicting the breeding values, the prediction of non-additive genetic effects has also been of interest. In this study, we assessed the potential of genomic prediction using non-additive effects for phenotypic prediction in Japanese Black, a beef cattle breed. In addition, we examined the stability of variance component and genetic effect estimates against population size by subsampling with different sample sizes. Results Records of six carcass traits, namely, carcass weight, rib eye area, rib thickness, subcutaneous fat thickness, yield rate and beef marbling score, for 9850 animals were used for analyses. As the non-additive genetic effects, dominance, additive-by-additive, additive-by-dominance and dominance-by-dominance effects were considered. The covariance structures of these genetic effects were defined using genome-wide SNPs. Using single-trait animal models with different combinations of genetic effects, it was found that 12.6–19.5 % of phenotypic variance were occupied by the additive-by-additive variance, whereas little dominance variance was observed. In cross-validation, adding the additive-by-additive effects had little influence on predictive accuracy and bias. Subsampling analyses showed that estimation of the additive-by-additive effects was highly variable when phenotypes were not available. On the other hand, the estimates of the additive-by-additive variance components were less affected by reduction of the population size. Conclusions The six carcass traits of Japanese Black cattle showed moderate or relatively high levels of additive-by-additive variance components, although incorporating the additive-by-additive effects did not improve the predictive accuracy. Subsampling analysis suggested that estimation of the additive-by-additive effects was highly reliant on the phenotypic values of the animals to be estimated, as supported by low off-diagonal values of the relationship matrix. On the other hand, estimates of the additive-by-additive variance components were relatively stable against reduction of the population size compared with the estimates of the corresponding genetic effects.

scholarly journals On the Best Quadratic Minimum Bias Non-Negative Estimator of a Two-Variance Component Model

2011 ◽  
Vol 1 (3) ◽  
pp. 280-285 ◽  
Author(s):  
Lars Sjöberg
Keyword(s):  
Variance Components ◽  
Variance Component ◽  
Component Model ◽  
Variance Component Model ◽  
Minimum Bias ◽  
Unbiased Estimators ◽  
Independent Observations ◽  
Special Case

On the Best Quadratic Minimum Bias Non-Negative Estimator of a Two-Variance Component ModelVariance components (VCs) in linear adjustment models are usually successfully computed by unbiased estimators. However, for many unbiased VC techniques estimated variance components might be negative, a result that cannot be tolerated by the user. This is, for example, the case with the simple additive VC model aσ2/1 + bσ2/2 with known coefficients a and b, where either of the unbiasedly estimated variance components σ2/1 + σ2/2 may frequently come out negative. This fact calls for so-called non-negative VC estimators. Here the Best Quadratic Minimum Bias Non-negative Estimator (BQMBNE) of a two-variance component model is derived. A special case with independent observations is explicitly presented.

Sockeye salmon cycles in the Kvichak River, Bristol Bay, Alaska

1981 ◽  
Vol 21 (2) ◽  
pp. 1207-1213
Author(s):  
Ole A. Mathisen ◽  
Patrick H. Poe
Keyword(s):  
Sockeye Salmon ◽  
Bristol Bay

Secondary sexual characters, energy use, senescence, and the cost of reproduction in sockeye salmon

1999 ◽  
Vol 77 (11) ◽  
pp. 1663-1675 ◽  
Author(s):  
Andrew P Hendry ◽  
Ole K Berg
Keyword(s):  
Egg Production ◽  
Sockeye Salmon ◽  
Energy Use ◽  
Relative Size ◽  
Cost Of Reproduction ◽  
Bristol Bay ◽  
Secondary Sexual Characters ◽  
In The Wild ◽  
The Cost ◽  
Secondary Sexual

Reproductive development and energy stores were characterized for sockeye salmon (Oncorhynchus nerka) maturing in the wild (Pick Creek, Bristol Bay, Alaska). Between freshwater entry and the start of spawning, ovaries increased in mass by 87.1% and secondary sexual characters increased in linear dimension by 13.0-47.4%. Between the start of spawning and death, secondary sexual characters decreased in relative size by 3.3-12.7%. Mass-specific somatic energy declined from freshwater entry (6.7% fat, 20.6% protein, 6.6 kJ·g-1) to the start of spawning (1.6% fat, 18.0% protein, 4.5 kJ·g-1) and finally to death (0.1% fat, 14.4% protein, 2.9 kJ·g-1). Stored fat appeared to be used primarily for upriver migration and egg production, whereas stored protein appeared to be used primarily for the development of secondary sexual characters and metabolism during spawning. Most development of secondary sexual characters occurred late in maturation, perhaps to forestall deterioration of muscle tissue. Relative to populations with long freshwater migrations, Bristol Bay sockeye salmon stored less fat before entering fresh water and used less fat before death. The total energy cost of reproduction (freshwater entry until death, including gonad investment) was 74.1% for females and 66.1% for males, higher than levels typically reported for iteroparous salmonids.

Selective predation by brown bears (Ursus arctos) foraging on spawning sockeye salmon (Oncorhynchus nerka)

2000 ◽  
Vol 78 (6) ◽  
pp. 974-981 ◽  
Author(s):  
Gregory T Ruggerone ◽  
Renn Hanson ◽  
Donald E Rogers
Keyword(s):  
Sockeye Salmon ◽  
Ursus Arctos ◽  
Oncorhynchus Nerka ◽  
The Body ◽  
Upstream Migration ◽  
Selective Predation ◽  
Bristol Bay ◽  
Brown Bears ◽  
Risk Of Predation ◽  
Salmon Population

Selective predation by and predation rates of brown bears (Ursus arctos) foraging on spawning sockeye salmon (Oncorhynchus nerka) in a small shallow creek in the Wood River lake system near Bristol Bay, Alaska, were quantified during 1986 and 1990–1992. Bears killed a high proportion of spawning salmon when few salmon entered the creek (92% of 505 fish) and a much smaller proportion when the spawning population reached a historical high (16% of 15 631 fish). Selective predation on salmon that differed in length, sex, and spawning condition was measured by tagging salmon at the mouth of the creek immediately prior to upstream migration and then recovering dead tagged fish during daily surveys of the entire creek. The relative frequencies of large, medium-sized, and small salmon killed by bears indicated that the risk of predation was more than 150% greater for large than for small salmon. A higher proportion of the male salmon population was killed and a greater proportion of male bodies were consumed than female salmon. Selectivity for male salmon increased as the spawning season progressed, possibly because male salmon weakened earlier and lived longer in a weakened state than female salmon. Male salmon were attacked mostly along the dorsal hump area, whereas female salmon tended to be attacked along the abdomen, where eggs could be exposed. Bears selectively killed female salmon prior to spawning during 1 of the 3 years, but only 6.1–7.8% of the female spawning populations were killed prior to spawning. These data support the hypothesis that selective predation by bears may influence the body morphology of spawning salmon.

scholarly journals Trends and Factors Influencing the Length, Compensatory Growth, and Size-Selective Mortality of Juvenile Bristol Bay, Alaska, Sockeye Salmon at Sea

2016 ◽  
Vol 8 (1) ◽  
pp. 315-333 ◽  
Author(s):  
Ellen M. Yasumiishi ◽  
Ed V. Farley ◽  
Gregory T. Ruggerone ◽  
Beverly A. Agler ◽  
Lorna I. Wilson
Keyword(s):  
Sockeye Salmon ◽  
Compensatory Growth ◽  
Selective Mortality ◽  
Bristol Bay ◽  
Factors Influencing
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