Factors influencing three-spined stickleback Gasterosteus aculeatus (Linnaeus 1758) catch per unit effort

2015 ◽  
Vol 31 (5) ◽  
pp. 905-908 ◽  
Author(s):  
J. Merilä
Keyword(s):  
Gasterosteus Aculeatus ◽  
Catch Per Unit Effort ◽  
Factors Influencing ◽  
Unit Effort

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.

Modelling catch per unit effort of the Black Volta near the Bui dam in Ghana

2016 ◽  
Vol 55 (2) ◽  
pp. 126-133
Author(s):  
Elliot H. Alhassan ◽  
Patrick K. Ofori-Danson ◽  
Francis K. E. Nunoo
Keyword(s):  
Catch Per Unit Effort ◽  
Unit Effort

Predation by southern sea lions (Otaria flavescens) on artisanal fishing catches in Uruguay

2002 ◽  
Vol 53 (8) ◽  
pp. 1161 ◽  
Author(s):  
Diana Szteren ◽  
Enrique Páez
Keyword(s):  
Significant Relationship ◽  
Shallow Waters ◽  
Fishing Gear ◽  
Artisanal Fishery ◽  
Artisanal Fishing ◽  
Catch Per Unit Effort ◽  
Sea Lion ◽  
Otaria Flavescens ◽  
Sea Lions ◽  
Unit Effort

Southern sea lions (Otaria flavescens) forage in coastal fishery grounds in shallow waters, where they interact with coastal fishing activities. The main objective of this research was to evaluate the predation of southern sea lions on artisanal fishery catches and thus determine whether interactions with sea lions affected catches. Between July 1997 and March 1998, we observed 53 fishing events onboard artisanal fishing boats in four localities. The presence and number of sea lions around the boat and the numbers of each fish species consumed by sea lions were recorded by an onboard observer. To estimate the damage caused by sea lions to fishery catches, we considered two scenarios, a conservative scenario and a maximized scenario. Predation on catches was observed in 50.9% of all the fishing events and up to four sea lions were sighted in 67.9% of fishing events. Considering a conservative scenario, predation varied from 0.8 to 9.1% of the catch per unit effort (CPUE) depending on the location. Considering the maximized scenario, predation varied from 3.4 to 46.2%. However, no significant relationship was found between CPUE and the number of sea lions in any locality or with either type of fishing gear. Furthermore, CPUE did not differ in the presence or absence of sea lion interactions and predation per unit effort did not vary between localities or seasons. It was concluded that neither the presence of sea lions nor the damage they cause were responsible for variations in CPUE.

Wind-Aided Recruitment of Canadian Arctic Cisco (Coregonus autumnalis) into Alaskan Waters

1988 ◽  
Vol 45 (5) ◽  
pp. 906-910 ◽  
Author(s):  
Robert G. Fechhelm ◽  
David B. Fissel
Keyword(s):  
Time Series ◽  
Canadian Arctic ◽  
Wind Data ◽  
Commercial Fishery ◽  
Catch Per Unit Effort ◽  
Longshore Currents ◽  
Unit Effort ◽  
Colville River ◽  
Young Of The Year ◽  
Mackenzie River

Summer wind data collected at Barter Island, Alaska, were compared with commercial fishery catches of arctic cisco (Coregonus autumnalis) at the Colville River, Alaska, for the period 1967–85. There was a significant (p = 0.036) association between yearly catch-per-unit-effort and the percent of easterly winds after adjusting for a 5-yr differential in the two time series. Results suggest that young-of-the-year fish which spawn in Canada's Mackenzie River are aided in their westward dispersal into Alaskan waters via wind-driven longshore currents. The greater the prevalence of easterly winds (westerly currents), the greater the recruitment. Increased recruitment manifests itself as an increase in Alaskan commercial fishery catch some 5-yr later when fish have grown to a size that renders them susceptible to commercial nets.

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