scholarly journals Analysis of juvenile North Atlantic albacore (Thunnus alalunga) catch per unit effort by surface gears in relation to environmental variables

2005 ◽  
Vol 62 (7) ◽  
pp. 1475-1482 ◽  
Author(s):  
Nicolas Goñi ◽  
Haritz Arrizabalaga
Keyword(s):  
North Atlantic ◽  
Environmental Variables ◽  
Negative Relationship ◽  
Generalized Least Squares ◽  
Catch Per Unit Effort ◽  
Seasonal Thermocline ◽  
Unit Effort ◽  
Negative Effect ◽  
Thunnus Alalunga ◽  
Age Structured

Abstract The relationship between the catch per unit effort (cpue) of trolling and baitboat fisheries targeting juvenile North Atlantic albacore (Thunnus alalunga, Bonnaterre, 1788) and several environmental variables was studied. A multiple linear regression and a generalized least squares model (GLS) showed a significant negative relationship between age 2 albacore trolling and baitboat cpue, and the average agitation of the sea and the duration of insolation. No clear relationship was found between the juvenile albacore cpue and sea surface temperature, precipitation, and NAO or Gulf Stream Index. Underlying processes that could explain the negative effect of agitation and insolation are discussed, especially relating to the habitat of age 2 albacore above the seasonal thermocline. Results highlight the necessity of considering environmental variables in the standardization of albacore cpue series used for calibrating age-structured stock assessments.

Are Age-Structured Models Appropriate for Catch-Effort Data?

1985 ◽  
Vol 42 (6) ◽  
pp. 1066-1072 ◽  
Author(s):  
Donald Ludwig ◽  
Carl J. Walters
Keyword(s):  
Simulated Data ◽  
Fishing Effort ◽  
Production Model ◽  
Model Structure ◽  
Catch Per Unit Effort ◽  
Unit Effort ◽  
Production Models ◽  
Stock Assessments ◽  
Age Structured ◽  
Age Structured Model

Simulated data have been used to evaluate the performance of schemes for estimating optimum fishing effort using a simple stock-production model and R. B. Deriso's age-structured model Even when the data are generated using Deriso's model, the simpler production model generally gives as good or better estimates for the optimal effort. The only exception to this result is when data are provided with unrealistically large contrasts in effort and catch per unit effort over time. The implication of these findings is that simple production models should often be used in stock assessments based on catch/effort data, even when more realistic and structurally correct models are available to the analyst; the best choice depends on how much contrast has occurred in the historical effort and catch per unit effort data, rather than on prior knowledge about which model structure is biologically more realistic.

scholarly journals Catch per unit effort-environmental variables relations in the fishery of white shrimp (<i>Litopenaeus schmitti</i>) from the Gulf of Venezuela

2013 ◽  
Vol 04 (06) ◽  
pp. 83-90 ◽  
Author(s):  
Ángel Antonio Díaz Lugo ◽  
Orlando José Ferrer Montaño ◽  
Rodolfo Álvarez ◽  
Luis González ◽  
Jesús Méndez ◽  
...  
Keyword(s):  
Environmental Variables ◽  
White Shrimp ◽  
Catch Per Unit Effort ◽  
Unit Effort

scholarly journals Canopy cover negatively affects arboreal ant species richness in a tropical open habitat

2016 ◽  
Vol 76 (4) ◽  
pp. 864-870 ◽  
Author(s):  
A. C. M. Queiroz ◽  
C. R. Ribas
Keyword(s):  
Species Richness ◽  
Environmental Variables ◽  
Negative Relationship ◽  
Canopy Cover ◽  
Tree Height ◽  
Generalist Species ◽  
Arboreal Ants ◽  
Negative Effect ◽  
Vegetation Characteristics ◽  
Set Up

Abstract We tested the hypothesis of a negative relationship between vegetation characteristics and ant species richness in a Brazilian open vegetation habitat, called candeial. We set up arboreal pitfalls to sample arboreal ants and measured the following environmental variables, which were used as surrogate of environmental heterogeneity: tree richness, tree density, tree height, circumference at the base of the plants, and canopy cover. Only canopy cover had a negative effect on the arboreal ant species richness. Vegetation characteristics and plant species composition are probably homogeneous in candeial, which explains the lack of relationship between other environmental variables and ant richness. Open vegetation habitats harbor a large number of opportunistic and generalist species, besides specialist ants from habitats with high temperatures. An increase in canopy cover decreases sunlight incidence and may cause local microclimatic differences, which negatively affect the species richness of specialist ants from open areas. Canopy cover regulates the richness of arboreal ants in open areas, since only few ant species are able to colonize sites with dense vegetation; most species are present in sites with high temperature and luminosity. Within open vegetation habitats the relationship between vegetation characteristics and species richness seems to be the opposite from closed vegetation areas, like forests.

scholarly journals Electrofishing eel, salmon and trout: impact of waveform and frequency on capture-per-unit-effort and spinal damage

2020 ◽  
pp. 42
Author(s):  
Gaétan Pottier ◽  
Marie Nevoux ◽  
Frédéric Marchand
Keyword(s):  
Direct Current ◽  
Environmental Variables ◽  
Spinal Column ◽  
European Eel ◽  
Catch Per Unit Effort ◽  
Non Invasive ◽  
Unit Effort ◽  
Invasive Method ◽  
Pulsed Direct Current ◽  
Spinal Damage

Performing fish survey protocols with different electrofishing equipment and settings can lead to difficulties in comparing the data obtained. In this study, we captured two fish taxa (i.e. the European eel and salmonids: Atlantic salmon and brown trout) in the field using four models of electrofishers that provided different waveforms: direct current (DC), pulsed direct current (PDC) and pulsed exponential current (PEC). This study aimed to assess effects of using different waveforms and frequencies, while considering environmental variables, on i) attraction, represented by occurrence and catch-per-unit-effort (CPUE) of fishes, and ii) spinal damage, based on ultrasound of the spinal column. For all species, DC and PDC yielded equivalent occurrences and CPUEs, regardless of the frequency. In contrast, PEC induced a significant decrease in occurrences and CPUEs of both eels and salmonids. The percentage of injured fishes increased as the frequency or length of the salmonids increased while waveform had no effect. Ultrasound was determined to be a good non-invasive method to detect injuries in fishes.

Detecting and forecasting complex nonlinear dynamics in spatially structured catch-per-unit-effort time series for North Pacific albacore (Thunnus alalunga)

2011 ◽  
Vol 68 (3) ◽  
pp. 400-412 ◽  
Author(s):  
Sarah M. Glaser ◽  
Hao Ye ◽  
Mark Maunder ◽  
Alec MacCall ◽  
Michael Fogarty ◽  
...  
Keyword(s):  
Nonlinear Dynamics ◽  
Time Series ◽  
North Pacific ◽  
Stock Assessment ◽  
North Pacific Ocean ◽  
Catch Per Unit Effort ◽  
Data Set ◽  
Unit Effort ◽  
Thunnus Alalunga ◽  
Low Dimensional

The presence of complex, nonlinear dynamics in fish populations, and uncertainty in the structure (functional form) of those dynamics, pose challenges to the accuracy of forecasts produced by traditional stock assessment models. We describe two nonlinear forecasting models that test for the hallmarks of complex behavior, avoid problems of structural uncertainty, and produce good forecasts of catch-per-unit-effort (CPUE) time series in both standardized and nominal (unprocessed) form. We analyze a spatially extensive, 40-year-long data set of annual CPUE time series of North Pacific albacore ( Thunnus alalunga ) from 1° × 1° cells from the eastern North Pacific Ocean. The use of spatially structured data in compositing techniques improves out-of-sample forecasts of CPUE and overcomes difficulties commonly encountered when using short, incomplete time series. These CPUE series display low-dimensional, nonlinear structure and significant predictability. Such characteristics have important implications for industry efficiency in terms of future planning and can inform formal stock assessments used for the management of fisheries.

scholarly journals Sustainable wildlife extraction and the impacts of socio-economic change among the Kukama-Kukamilla people of the Pacaya-Samiria National Reserve, Peru

Oryx ◽  
2018 ◽  
Vol 54 (2) ◽  
pp. 260-269 ◽  
Author(s):  
Maire Kirkland ◽  
Cristina Eisenberg ◽  
Andy Bicerra ◽  
Richard E. Bodmer ◽  
Pedro Mayor ◽  
...  
Keyword(s):  
Population Growth ◽  
Human Population ◽  
Negative Relationship ◽  
Indigenous Populations ◽  
Catch Per Unit Effort ◽  
Structured Interviews ◽  
Game Species ◽  
Human Population Growth ◽  
Unit Effort ◽  
Hunting And Fishing

AbstractThroughout the tropics, hunting and fishing are critical livelihood activities for many Indigenous peoples. However, these practices may not be sustainable following recent socio-economic changes in Indigenous populations. To understand how human population growth and increased market integration affect hunting and fishing patterns, we conducted semi-structured interviews in five Kukama-Kukamilla communities living along the boundary of the Pacaya-Samiria National Reserve, in the Peruvian Amazon. Extrapolated annual harvest rates of fish and game species by these communities amounted to 1,740 t and 4,275 individuals (67 t), respectively. At least 23 fish and 27 game species were harvested. We found a positive correlation between village size and annual community-level harvest rates of fish and a negative relationship between market exposure and mean per-capita harvest rates of fish. Catch-per-unit-effort (CPUE) analyses indicated local depletion of fish populations around larger, more commercial communities. Catch-per-unit-effort of fish was lower in more commercial communities and fishers from the largest village travelled further into the Reserve, where CPUE was higher. We found no effect of village size or market exposure on harvest rates or CPUE of game species. However, larger, more commercial communities targeted larger, economically valuable species. This study provides evidence that human population growth and market-driven hunting and fishing pose a growing threat to wildlife and Indigenous livelihoods through increased harvest rates and selective harvesting of species vulnerable to exploitation.

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.

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