Fisheries management based on gear selectivity of a tropical reservoir, Lake Nasser, Egypt

El-Far, Alaa M.; Aly, Walid; El-Haweet, Alaa Eldin; Nasr-Allah, A.M.; Charo‐Karisa, Harrison

doi:10.1016/j.ejar.2020.02.004

Cited by 14 publications

(11 citation statements)

References 8 publications

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“…Weyl et al [31] evidenced an increase in biomass and CPUE in the southern part of Lake Malawi after the subsequent closure of the fishery within 1992/1993. In Lake Nasser, Egypt, the time series of size and CPUE also showed a negative trend indicating the high exploitation rate of the most important commercial fish species in the lake by the fishing gears [32]. A similar situation is reported in Lake Chilwa, Lake Malawi, and other inland lakes [35][36][37].…”

Section: Discussionsupporting

confidence: 62%

“…According to Weyl et al [31], CPUE variation is strongly linked to the difference in the number of fishers, man-hours, and the categories of fishing gears. Low CPUE indicates a relatively low abundance of fish which results in prolonged man-hours and an increase in the number of fishers and low catches [32,33]. Alexander et al [34] had similar observations and reported a strong relationship between whole lake CPUE to relative fish biomass and abundance.…”

Section: Discussionmentioning

confidence: 88%

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

et al. 2021

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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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Section: Discussionsupporting

confidence: 62%

Section: Discussionmentioning

confidence: 88%

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

et al. 2021

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“…Nevertheless, the main number of commercial species were from the khors of Lake Nasser, where most of the fishing activities take place in the area from 5.4 to 7.9 km of the shoreline, depending on the lake water [70,71]. Nowadays, the lake fisheries and the ecosystem have undergone negative changes, and biodiversity has declined, obscuring its potential for sustainable development [70,72].…”

Section: Discussionmentioning

confidence: 99%

Comprehensive Insight into Lake Nasser Environment: Water Quality and Biotic Communities—A Case Study before Operating the Renaissance Dam

Goher

Napiórkowska‐Krzebietke

Aly

et al. 2021

Water

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This study focused on the monitoring and assessment of aquatic ecosystem functioning based on the abiotic and biotic features of Lake Nasser in the post-flood and pre-flood periods as the last ones before water storing behind the Grand Ethiopian Renaissance Dam. The physicochemical parameters, distribution and structure of biotic communities, including bacteria, phytoplankton, zooplankton, macrophytes, epiphytes and fish were analyzed at 15 sites. The values of most parameters (primarily temperature, total suspended solids, pH, orthophosphates, carbonates, sulphates and some cations) were higher in the pre-flood period, whereas higher values of conductivity, total dissolved solids, total solids, nitrites, nitrates, chemical oxygen demand, bicarbonates and chlorophyll a were recorded in the post-flood period. Cyanobacteria-dominated phytoplankton and total coliform bacteria were more abundant in the pre-flood period, and especially at sites 10–15, whereas higher abundances of zooplankton were recorded in the post-flood period. All these changes in parameters were significantly differentiated, and only the concentrations of dissolved oxygen, biochemical oxygen demand, ammonium and silicates were at similar level in both periods. The study also indicated that environmental factors had affected the macrophyte distribution and the adaptation of the invasive species Myriophyllum spicatum to thrive under different environmental factors in the lake. Besides, macrophytes provided the habitat to other aquatic organisms, especially epiphytes, and also helped maintaining the good water quality, nutrient cycling and stabilizing rivers’ and lakes’ banks. Generally, these conditions were rather favorable for biological processes and fish production.

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“…b C represents the daily average catch of one boat, s B is the number of active fishing boats in area and s D is the number of active fishing days [24].…”

Section: Data Collectionmentioning

confidence: 99%

Ichthyofaunic Inventory and Fish Landings of Lom Pangar Hydropower Dam Reservoir in the Eastern Region of Cameroon

Pandong¹,

Thierry²,

Mbangue³

et al. 2020

OJMS

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The Lom Pangar hydroelectric dam project located in the eastern region of Cameroon was implemented by Electricity Development Corporation (EDC). The impoundment of the Lom Pangar dam created a large reservoir with an area ~590 km 2 and a useful storage capacity ~6 billion m 3 . Thereby, this impoundment has created favourable conditions for the proliferation of fishery resources. However, a fisheries assessment study based on fishing activities is essential to attain reliable information for implementing a management plan to achieve rational and sustainable exploitation. This study was carried out on the ichtyofaunic inventory and the assessment of fish landings in Lom Pangar hydroelectric dam reservoir from April 2016 to September 30, 2016. Three main groups of fishing gear have been identified, among which gillnets, traps and longlines occupy major fishing activities. Indeed, the spatial and landing sites surveies were conducted on species composition, size composition, and quantities of fish landed during the study period. Moreover, 37 species of fish divided into 16 families were found in seven different selected fish landing sites. Carp (Cyprinus carpio) was the major fish species abundantly caught by these fishing gears which accounted for 81.60% of the total catch, and the least species was sardine (Sardinella aurita). A total of 623,229 Kg of fish were landed which were dominated by those of the Wami landing site with 480,773 Kg representing 76.96% of the total landed catches. The smallest species caught was the white carp (7 cm) while the longest one was the catfish (71 cm). In addition, the species of fish in the breeding season are carp, catfish,

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Fisheries management based on gear selectivity of a tropical reservoir, Lake Nasser, Egypt

Cited by 14 publications

References 8 publications

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

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

Comprehensive Insight into Lake Nasser Environment: Water Quality and Biotic Communities—A Case Study before Operating the Renaissance Dam

Ichthyofaunic Inventory and Fish Landings of Lom Pangar Hydropower Dam Reservoir in the Eastern Region of Cameroon

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