This study assessed sediment contamination by heavy metals and pesticide active ingredients linked to chemical inputs used in agricultural activities in the lower Ouémé. Pesticide residues from the organochl...This study assessed sediment contamination by heavy metals and pesticide active ingredients linked to chemical inputs used in agricultural activities in the lower Ouémé. Pesticide residues from the organochlorine, pyrethroid and organophosphorus families were investigated by gas chromatography, and heavy metals (Cd, Pb, As, Ni, Zn, Fe, Mg, Cr and Hg) by atomic absorption spectrophotometry. The metallic pollution indices, the contamination factor (CF) and the ecological risk index were calculated. The results revealed 8 active ingredients in the rainy season and 9 in the dry season. Glyphosate was the active ingredient with the highest concentration at all stations, 9.65 ± 0.84 mg/kg recorded in the dry season at the Aguigadji station. All glyphosate values were above the EQS. DDT, Atrazine and Endosulfan also showed high concentrations in the dry and rainy seasons. Emamectin, Abamectin and Lambda Cyhalothrin also showed high concentrations in the dry season at Aguigadji, Ahlan and Sele. Only glyphosate was recorded at the control station (Toho), but in very low concentrations. Lead showed the highest concentrations at all the stations, 265.96 ± 21.02 mg/Kg in the rainy season and 255.38 ± 79.09 mg/Kg in the dry season, all detected at the Aguigadji station and above the EQS. Zn, Ni, Fe, Cu and Cr were all representative in both the dry and rainy seasons at the contaminated stations. Manganese showed high concentrations in the rainy season. Pb showed very high contamination (FC ≥ 6) at the Aguigadji and Ahlan stations and significant contamination (3 ≤ FC 6) at the Sele station in both the rainy and dry seasons. Ni, Hg and Cd, showed either moderate or significant contamination at the contaminated stations. The risk values showed a considerable ecological Ri (190 ≤ Ri < 380) in the rainy season and a moderate ecological Ri (95 ≤ Ri < 190) in the dry season at these contaminated stations.展开更多
Albacore tuna(Thunnus alalunga)is one of the target species of tuna longline fishing,and waters near the Cook Islands are a vital albacore tuna fishing ground.Marine environmental data are usually presented with diffe...Albacore tuna(Thunnus alalunga)is one of the target species of tuna longline fishing,and waters near the Cook Islands are a vital albacore tuna fishing ground.Marine environmental data are usually presented with different spatial resolutions,which leads to different results in tuna fishery prediction.Study on the impact of different spatial resolutions on the prediction accuracy of albacore tuna fishery to select the best spatial resolution can contribute to better management of albacore tuna resources.The nominal catch per unit effort(CPUE)of albacore tuna is calculated according to vessel monitor system(VMS)data collected from Chinese distantwater fishery enterprises from January 1,2017 to May 31,2021.A total of 26 spatiotemporal and environmental factors,including temperature,salinity,dissolved oxygen of 0–300 m water layer,chlorophyll-a concentration in the sea surface,sea surface height,month,longitude,and latitude,were selected as variables.The temporal resolution of the variables was daily and the spatial resolutions were set to be 0.5°×0.5°,1°×1°,2°×2°,and 5°×5°.The relationship between the nominal CPUE and each individual factor was analyzed to remove the factors irrelavant to the nominal CPUE,together with a multicollinearity diagnosis on the factors to remove factors highly related to the other factors within the four spatial resolutions.The relationship models between CPUE and spatiotemporal and environmental factors by four spatial resolutions were established based on the long short-term memory(LSTM)neural network model.The mean absolute error(MAE)and root mean square error(RMSE)were used to analyze the fitness and accuracy of the models,and to determine the effects of different spatial resolutions on the prediction accuracy of the albacore tuna fishing ground.The results show the resolution of 1°×1°can lead to the best prediction accuracy,with the MAE and RMSE being 0.0268 and 0.0452 respectively,followed by 0.5°×0.5°,2°×2°and 5°×5°with declining prediction accuracy.The results suggested that 1)albacore tuna fishing ground can be predicted by LSTM;2)the VMS records the data in detail and can be used scientifically to calculate the CPUE;3)correlation analysis,and multicollinearity diagnosis are necessary to improve the prediction accuracy of the model;4)the spatial resolution should be 1°×1°in the forecast of albacore tuna fishing ground in waters near the Cook Islands.展开更多
With the popularization of vessel satellite AIS(automatic identification system)equipment and the continuous improve-ment of the AIS data’s coverage,continuity and effectiveness,AIS has become an important data sourc...With the popularization of vessel satellite AIS(automatic identification system)equipment and the continuous improve-ment of the AIS data’s coverage,continuity and effectiveness,AIS has become an important data source to study the navigation char-acteristics of vessel groups.This study established an identification model to extract the fishing state and intensity information of fishing vessels,based on the AIS data of purse seine fishing vessels,combined with the variables of vessel position,speed and course.Expert experience,spatial statistics and data mining analysis methods were applied to establish the model,and the Western and Cen-tral Pacific Ocean areas were studied.The results showed that the overall accuracy of identification of the fishing state using Support Vector Machine method is higher,and the method has a good modeling effect.The spatial distribution characteristics of the vessels’fishing intensity based on AIS data showed a significant cluster distribution pattern.The obtained high-intensity fishing area can be used as a prediction of purse seine fishing grounds in the Western and Central Pacific areas.Through the processing and research of AIS data,this study provided important scientific support for the identification of fishing state of purse seine fishing vessels.The spatial fishing intensity of fishing vessels based on AIS data can also be used for the analysis of fishery resources and fishing grounds,and further serve the sustainable development of marine fisheries.展开更多
Maritime safety equipment allows to prevent and minimize the risks inherent to navigation at sea. However, in the artisanal maritime fishery in Gabon, fishermen are confronted with the major difficulty of the inaccess...Maritime safety equipment allows to prevent and minimize the risks inherent to navigation at sea. However, in the artisanal maritime fishery in Gabon, fishermen are confronted with the major difficulty of the inaccessibility of protective tools to carry out fishing trips in all peace of mind. The absence of equipment to help maritime navigation poses the problem of insecurity in which the various artisanal fishermen work, often victims of numerous accidents at sea. This article aims at highlighting the difficulties of accessibility, by the fishermen, of all the conventional protection tools recommended by the administrations. In fact, the methodology used is based on the consultation of official reports and publications on the subject, field observations and semi-structured interviews with 110 actors. The results obtained reveal, on the one hand, a plethora of conventional protective equipment required of fishing vessels. On the other hand, they reveal the high cost of safety equipment which creates, among the professionals concerned, a reluctance to acquire all of the said tools and forces the interested parties to associate them very often with the traditional procedures for rescue at sea.展开更多
文摘This study assessed sediment contamination by heavy metals and pesticide active ingredients linked to chemical inputs used in agricultural activities in the lower Ouémé. Pesticide residues from the organochlorine, pyrethroid and organophosphorus families were investigated by gas chromatography, and heavy metals (Cd, Pb, As, Ni, Zn, Fe, Mg, Cr and Hg) by atomic absorption spectrophotometry. The metallic pollution indices, the contamination factor (CF) and the ecological risk index were calculated. The results revealed 8 active ingredients in the rainy season and 9 in the dry season. Glyphosate was the active ingredient with the highest concentration at all stations, 9.65 ± 0.84 mg/kg recorded in the dry season at the Aguigadji station. All glyphosate values were above the EQS. DDT, Atrazine and Endosulfan also showed high concentrations in the dry and rainy seasons. Emamectin, Abamectin and Lambda Cyhalothrin also showed high concentrations in the dry season at Aguigadji, Ahlan and Sele. Only glyphosate was recorded at the control station (Toho), but in very low concentrations. Lead showed the highest concentrations at all the stations, 265.96 ± 21.02 mg/Kg in the rainy season and 255.38 ± 79.09 mg/Kg in the dry season, all detected at the Aguigadji station and above the EQS. Zn, Ni, Fe, Cu and Cr were all representative in both the dry and rainy seasons at the contaminated stations. Manganese showed high concentrations in the rainy season. Pb showed very high contamination (FC ≥ 6) at the Aguigadji and Ahlan stations and significant contamination (3 ≤ FC 6) at the Sele station in both the rainy and dry seasons. Ni, Hg and Cd, showed either moderate or significant contamination at the contaminated stations. The risk values showed a considerable ecological Ri (190 ≤ Ri < 380) in the rainy season and a moderate ecological Ri (95 ≤ Ri < 190) in the dry season at these contaminated stations.
基金the National Natural Science Foundation of China(No.32273185)the National Key R&D Program of China(No.2020YFD0901205)the Marine Fishery Resources Investigation and Exploration Program of the Ministry of Agriculture and Rural Affairs of China in 2021(No.D-8006-21-0215)。
文摘Albacore tuna(Thunnus alalunga)is one of the target species of tuna longline fishing,and waters near the Cook Islands are a vital albacore tuna fishing ground.Marine environmental data are usually presented with different spatial resolutions,which leads to different results in tuna fishery prediction.Study on the impact of different spatial resolutions on the prediction accuracy of albacore tuna fishery to select the best spatial resolution can contribute to better management of albacore tuna resources.The nominal catch per unit effort(CPUE)of albacore tuna is calculated according to vessel monitor system(VMS)data collected from Chinese distantwater fishery enterprises from January 1,2017 to May 31,2021.A total of 26 spatiotemporal and environmental factors,including temperature,salinity,dissolved oxygen of 0–300 m water layer,chlorophyll-a concentration in the sea surface,sea surface height,month,longitude,and latitude,were selected as variables.The temporal resolution of the variables was daily and the spatial resolutions were set to be 0.5°×0.5°,1°×1°,2°×2°,and 5°×5°.The relationship between the nominal CPUE and each individual factor was analyzed to remove the factors irrelavant to the nominal CPUE,together with a multicollinearity diagnosis on the factors to remove factors highly related to the other factors within the four spatial resolutions.The relationship models between CPUE and spatiotemporal and environmental factors by four spatial resolutions were established based on the long short-term memory(LSTM)neural network model.The mean absolute error(MAE)and root mean square error(RMSE)were used to analyze the fitness and accuracy of the models,and to determine the effects of different spatial resolutions on the prediction accuracy of the albacore tuna fishing ground.The results show the resolution of 1°×1°can lead to the best prediction accuracy,with the MAE and RMSE being 0.0268 and 0.0452 respectively,followed by 0.5°×0.5°,2°×2°and 5°×5°with declining prediction accuracy.The results suggested that 1)albacore tuna fishing ground can be predicted by LSTM;2)the VMS records the data in detail and can be used scientifically to calculate the CPUE;3)correlation analysis,and multicollinearity diagnosis are necessary to improve the prediction accuracy of the model;4)the spatial resolution should be 1°×1°in the forecast of albacore tuna fishing ground in waters near the Cook Islands.
基金supported by the Project of Developing of Tuna Fishing Grounds Forecasting(No.ZD 202101-06).
文摘With the popularization of vessel satellite AIS(automatic identification system)equipment and the continuous improve-ment of the AIS data’s coverage,continuity and effectiveness,AIS has become an important data source to study the navigation char-acteristics of vessel groups.This study established an identification model to extract the fishing state and intensity information of fishing vessels,based on the AIS data of purse seine fishing vessels,combined with the variables of vessel position,speed and course.Expert experience,spatial statistics and data mining analysis methods were applied to establish the model,and the Western and Cen-tral Pacific Ocean areas were studied.The results showed that the overall accuracy of identification of the fishing state using Support Vector Machine method is higher,and the method has a good modeling effect.The spatial distribution characteristics of the vessels’fishing intensity based on AIS data showed a significant cluster distribution pattern.The obtained high-intensity fishing area can be used as a prediction of purse seine fishing grounds in the Western and Central Pacific areas.Through the processing and research of AIS data,this study provided important scientific support for the identification of fishing state of purse seine fishing vessels.The spatial fishing intensity of fishing vessels based on AIS data can also be used for the analysis of fishery resources and fishing grounds,and further serve the sustainable development of marine fisheries.
文摘Maritime safety equipment allows to prevent and minimize the risks inherent to navigation at sea. However, in the artisanal maritime fishery in Gabon, fishermen are confronted with the major difficulty of the inaccessibility of protective tools to carry out fishing trips in all peace of mind. The absence of equipment to help maritime navigation poses the problem of insecurity in which the various artisanal fishermen work, often victims of numerous accidents at sea. This article aims at highlighting the difficulties of accessibility, by the fishermen, of all the conventional protection tools recommended by the administrations. In fact, the methodology used is based on the consultation of official reports and publications on the subject, field observations and semi-structured interviews with 110 actors. The results obtained reveal, on the one hand, a plethora of conventional protective equipment required of fishing vessels. On the other hand, they reveal the high cost of safety equipment which creates, among the professionals concerned, a reluctance to acquire all of the said tools and forces the interested parties to associate them very often with the traditional procedures for rescue at sea.
