Density and Distribution of Young Sockeye Salmon (Oncorhynchus nerka) throughout a Multibasin Lake System

1958 ◽  
Vol 15 (5) ◽  
pp. 961-982 ◽  
Author(s):  
W. E. Johnson
Keyword(s):  
Population Density ◽  
Sockeye Salmon ◽  
Oncorhynchus Nerka ◽  
Catch Per Unit Effort ◽  
Lake System ◽  
Unit Effort ◽  
Limited Dispersal ◽  
Discrete Populations

Estimates of density (based on catch per unit effort with tow nets) of fingerling sockeye salmon populations in a large (174 sq. mile) multibasin lake system were carried out during 1955, 1956 and 1957. Density and distribution of fingerling sockeye throughout the lake system are related to density and distribution of the spawning parent populations. Discrete populations associated with discrete basins point to a limited dispersal as a result of the multibasin nature of the lake system. In one example, higher population density appears to result in greater dispersal.

The Relation of Lake Population Density to Size of Young Sockeye Salmon (Oncorhynchus nerka)

1944 ◽  
Vol 6c (3) ◽  
pp. 267-280 ◽  
Author(s):  
R. E. Foerster
Keyword(s):  
Population Density ◽  
Sockeye Salmon ◽  
Oncorhynchus Nerka ◽  
Inverse Correlation ◽  
Fish Populations ◽  
Production Level ◽  
Natural Conditions ◽  
Significant Inverse Correlation ◽  
Appreciable Increase

For Cultus lake, B.C., data concerning relative numbers of young sockeye inhabiting the lake each year were obtained from the count of seaward migrants. From samples of the latter the sizes of the migrants were determined. For all years, 1927–1937, a statistically significant inverse correlation of −0.815 existed between extent of lake population and size of migrants. Under natural conditions the lake's sockeye productivity seems limited, probably due to limited plankton crop, and the sockeye values obtained in each year are compared to a production level of 6,000–8,000 kg. Experiments in reducing predaceous fish populations indicate appreciable increase in sockeye production.

Identification of Sockeye Salmon (Oncorhynchus nerka) Stocks in the Stikine River Based on Egg Size Measurements

1985 ◽  
Vol 42 (11) ◽  
pp. 1696-1701 ◽  
Author(s):  
P. C. Craig
Keyword(s):  
Body Weight ◽  
Egg Size ◽  
Sockeye Salmon ◽  
Pattern Analysis ◽  
Oncorhynchus Nerka ◽  
Egg Mass ◽  
Stock Identification ◽  
Mass Measurements ◽  
Lake System ◽  
Identification Method

The Stikine River in southeastern Alaska supports two principal stocks of sockeye salmon (Oncorhynchus nerka). An expedient means of separating these stocks when they enter freshwater is by egg size and egg mass measurements. Eggs of sockeye that spawn in the Tahltan Lake system are smaller than sockeye spawning elsewhere in the Stikine drainage, a difference supported by an independent stock identification method (scale pattern analysis). Tahltan females have only slightly developed ovaries (1–3% of body weight) and small eggs (2.0–3.5 mm) when they enter freshwater; they enter the river earlier (2–3 wk) and travel farther upstream to spawn than non-Tahltan sockeye. The latter group has more developed ovaries (5–16% of body weight) and larger eggs (3.5–6.2 mm) when they enter the river. Thus, an assessment of egg sizes of sockeye caught in the river can provide on-site information about stock composition and run timing. These data and escapement counts at Tahltan Lake indicate that the total escapement to the Stikine in 1983 was 61 000 to 71 000 sockeye of which 45–53% were Tahltan stock and 47–55% spawned eleswhere in the drainage.

Test fishery indices for sockeye salmon (Oncorhynchus nerka) as affected by age composition and environmental variables

2004 ◽  
Vol 61 (1) ◽  
pp. 80-92 ◽  
Author(s):  
Lucy Flynn ◽  
Ray Hilborn
Keyword(s):  
Sockeye Salmon ◽  
Oncorhynchus Nerka ◽  
Average Error ◽  
Fishing Gear ◽  
Migration Route ◽  
Catch Per Unit Effort ◽  
Age Classes ◽  
Age Composition ◽  
Fishery Data ◽  
Average Body

In this paper, we explore sources of variability in test fishing indices for sockeye salmon (Oncorhynchus nerka) and illustrate potential solutions. For our analysis, we use the Port Moller test fishery in Bristol Bay, Alaska. The traditional model used to forecast run size using Port Moller test fishery data is based on a simple linear regression of total returns to the fishing districts against the cumulative test fishery catch-per-unit-effort (CPUE) index on a given date. We show that much of the inaccuracy of recent forecasts based on test fishery indices is due to the variable age composition of sockeye runs and the unequal vulnerability of respective age classes to the test fishing gear. We also illustrate solutions to the problems presented by variability in migration route and variability in return timing. In warmer years, we found that there was an increase in effective vulnerability to the test fishing gear and that the strength of this relationship increased linearly with the average body length of age classes. Retrospective analysis shows that correcting for age composition, migration route, and timing provides an in-season index of abundance with an average error of 6.7 million fish or 21%, compared with 33% for previous models.

On the Distribution of Young Sockeye Salmon (Oncorhynchus nerka) in Babine and Nilkitkwa Lakes, B.C.

1956 ◽  
Vol 13 (5) ◽  
pp. 695-708 ◽  
Author(s):  
W. E. Johnson
Keyword(s):  
Sockeye Salmon ◽  
Oncorhynchus Nerka ◽  
Fishing Effort ◽  
Lake Area ◽  
Parent Population ◽  
Unequal Distribution ◽  
The North ◽  
Limited Dispersal ◽  
Mean Size ◽  
Skeena River

Babine Lake and connected Nilkitkwa Lake, a total lake area of 174 square miles, provide nursery facilities for progeny of the largest sockeye salmon run to the Skeena River in northern British Columbia.Based on catch per unit of fishing effort, tow-net collections in August and October, 1955, indicate that at least 67%, and possibly as much as 88%, of the total age 0 sockeye population of these lakes (estimated as 50 to 60 million) was concentrated in Nilkitkwa Lake and the North Arm of Babine Lake: that is, in 11.4% of the total lake area. Mean size of young sockeye in these areas of concentration was much smaller than in the sparsely populated remainder of Babine Lake.This unequal distribution of young sockeye, and resulting inefficient utilization of the lake nursery facilities, is apparently a result of the distribution of the spawning parent population and a limited dispersal of young sockeye from their points of entrance into the lake as fry.

Qarun Lake fisheries; Fishing gears, Species composition and Catch per unit effort

2014 ◽  
Vol 18 (2) ◽  
pp. 39-49
Author(s):  
Sabry El-Serafy ◽  
Alaa El-Haweet ◽  
Azza El-Ganiny ◽  
Alaa El-Far
Keyword(s):  
Species Composition ◽  
Catch Per Unit Effort ◽  
Unit Effort ◽  
Fishing Gears ◽  
Lake Fisheries

scholarly journals Modeling of Lake Malombe Annual Fish Landings and Catch per Unit Effort (CPUE)

Forecasting ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 39-55
Author(s):  
Rodgers Makwinja ◽  
Seyoum Mengistou ◽  
Emmanuel Kaunda ◽  
Tena Alemiew ◽  
Titus Bandulo Phiri ◽  
...  
Keyword(s):  
Time Series ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Efficiency Coefficient ◽  
Arima Models ◽  
Catch Per Unit Effort ◽  
Annual Fish ◽  
Unit Effort ◽  
The Mean

Forecasting, using time series data, has become the most relevant and effective tool for fisheries stock assessment. Autoregressive integrated moving average (ARIMA) modeling has been commonly used to predict the general trend for fish landings with increased reliability and precision. In this paper, ARIMA models were applied to predict Lake Malombe annual fish landings and catch per unit effort (CPUE). The annual fish landings and CPUE trends were first observed and both were non-stationary. The first-order differencing was applied to transform the non-stationary data into stationary. Autocorrelation functions (AC), partial autocorrelation function (PAC), Akaike information criterion (AIC), Bayesian information criterion (BIC), square root of the mean square error (RMSE), the mean absolute error (MAE), percentage standard error of prediction (SEP), average relative variance (ARV), Gaussian maximum likelihood estimation (GMLE) algorithm, efficiency coefficient (E2), coefficient of determination (R2), and persistent index (PI) were estimated, which led to the identification and construction of ARIMA models, suitable in explaining the time series and forecasting. According to the measures of forecasting accuracy, the best forecasting models for fish landings and CPUE were ARIMA (0,1,1) and ARIMA (0,1,0). These models had the lowest values AIC, BIC, RMSE, MAE, SEP, ARV. The models further displayed the highest values of GMLE, PI, R2, and E2. The “auto. arima ()” command in R version 3.6.3 further displayed ARIMA (0,1,1) and ARIMA (0,1,0) as the best. The selected models satisfactorily forecasted the fish landings of 2725.243 metric tons and CPUE of 0.097 kg/h by 2024.

Environmental drivers of golden tilefish ( Lopholatilus chamaeleonticeps ) commercial landings and catch‐per‐unit‐effort

2021 ◽  
Author(s):  
Geneviève Nesslage ◽  
Vyacheslav Lyubchich ◽  
Paul Nitschke ◽  
Erik Williams ◽  
Churchill Grimes ◽  
...  
Keyword(s):  
Environmental Drivers ◽  
Catch Per Unit Effort ◽  
Unit Effort

Ecological and environmental factors affecting the foraging activity of the White-bellied Heron Ardea insignis (Hume, 1878) in Bhutan

2021 ◽  
pp. 1-18
Author(s):  
PEMA KHANDU ◽  
GEORGE A. GALE ◽  
SARA BUMRUNGSRI
Keyword(s):  
Relative Abundance ◽  
Habitat Restoration ◽  
Prey Species ◽  
Catch Per Unit Effort ◽  
Factors Affecting ◽  
Prey Biomass ◽  
Gravel Mining ◽  
Unit Effort ◽  
Prey Preferences ◽  
The Government

Summary White-bellied Heron Ardea insignis (WBH) is critically endangered, but we lack data on many aspects of its basic ecology and threats to the species are not clearly understood. The goal of this study was to analyse WBH foraging microhabitat selection, foraging behaviour, and prey preferences in two river basins (Punatsangchhu and Mangdechhu) in Bhutan which are likely home to one of the largest remaining populations of WBH. We also explored the relationship between the relative abundance of the WBH and prey biomass catch per unit effort within four foraging river microhabitats (pool, pond, riffle and run). Prey species were sampled in 13 different 100-m thalweg lengths of the rivers using cast nets and electrofishing gear. Riffles and pools were the most commonly used microhabitats; relative abundance was the highest in riffles. The relative abundance of WBH and prey biomass catch per unit effort (CPUE) also showed a weak but significant positive correlation (rs = 0.22). The highest biomass CPUE was observed in riffles while the lowest was found in the ponds. From the 97 prey items caught by the WBH, 95% of the prey were fish. The WBH mainly exploited three genera of fish (Garra, Salmo, and Schizothorax) of which Schizothorax (64%) was the most frequently consumed. This study provides evidence in support of further protection of critical riverine habitat and fish resources for this heron. Regular monitoring of sand and gravel mining, curbing illegal fishing, habitat restoration/mitigation, and developing sustainable alternatives for local people should be urgently implemented by the government and other relevant agencies. Further study is also required for understanding the seasonal variation and abundance of its prey species in their prime habitats along the Punatsangchhu and Mangdechhu basins.

Sign in / Sign up

Export Citation Format

Share Document