A fuzzy logic model with genetic algorithm for analyzing fish stock-recruitment relationships

2000 ◽  
Vol 57 (9) ◽  
pp. 1878-1887 ◽  
Author(s):  
D G Chen ◽  
N B Hargreaves ◽  
D M Ware ◽  
Y Liu
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Logic Model ◽  
Sea Surface ◽  
Oncorhynchus Gorbuscha ◽  
Fish Stock ◽  
Fuzzy Logic Model ◽  
Stock Recruitment

A new fuzzy logic model with a genetic algorithm is developed that overcomes some of the inherent uncertainties in the fish stock-recruitment process. This model is applied to stock-recruitment relationships for the Southeast Alaska pink salmon (Oncorhynchus gorbuscha) and the West Coast Vancouver Island Pacific herring (Clupea pallasi) stocks. In both examples, the annual mean sea surface temperature is used as an environmental intervention in the model. The fuzzy logic model provides the functional relationship between the number of fish spawners and the sea surface temperature that is used to reconstruct the historical fish recruitment time series and also to predict the number of fish that will recruit in the future. Globally optimized genetic learning algorithms are used to find the optimal values of the parameters for the fuzzy logic model. The results from this fuzzy logic model are compared with results from both a traditional Ricker stock-recruitment model and a recent artificial neural network model. These comparisons demonstrate the superior capability of the fuzzy logic model for addressing problems of uncertainty and vagueness in both the data and the stock-recruitment relationship. The fuzzy logic model approach is recommended as a useful addition to the analytical tools currently available for fish stock assessment and management.

scholarly journals Assessing causal links in fish stock–recruitment relationships

2017 ◽  
Vol 75 (3) ◽  
pp. 903-911 ◽  
Author(s):  
Maud Pierre ◽  
Tristan Rouyer ◽  
Sylvain Bonhommeau ◽  
J M Fromentin
Keyword(s):  
Time Series ◽  
Dynamical Systems ◽  
Surface Temperature ◽  
Sea Surface ◽  
Fish Stock ◽  
Stochastic Forcing ◽  
Forecasting Methods ◽  
Stock Biomass ◽  
Spawning Stock ◽  
Stock Recruitment

Abstract Understanding whether recruitment fluctuations in fish stock arise from stochastic forcing (e.g. environmental variations) rather than deterministic forces (e.g. intrinsic dynamics) is a long standing question with important applied consequences for fisheries ecology. In particular, the relationship between recruitment, spawning stock biomass and environmental factors is still poorly understood, even though this aspect is crucial for fisheries management. Fisheries data are often short, but arise from complex dynamical systems with a high degree of stochastic forcing, which are difficult to capture through classic modelling approaches. In the present study, recent statistical approaches based on the approximation of the attractors of dynamical systems are applied on a large dataset of time series to assess (i) the directionality of potential causal relationships between recruitment and spawning stock biomass and potential influence of sea-surface temperature on recruitment and (ii) their performance to forecast recruitment. Our study shows that (i) whereas spawning stock biomass and sea surface temperature influence the recruitment to a lesser extent, recruitment causes also parental stock size and (ii) that non-linear forecasting methods performed well for the short-term predictions of recruitment time series. Our results underline that the complex and stochastic nature of the processes characterizing recruitment are unlikely to be captured by classical stock–recruitment relationships, but that non-linear forecasting methods provide interesting perspectives in that respect.

A semiparametric model to examine stock–recruitment relationships incorporating environmental data

2001 ◽  
Vol 58 (6) ◽  
pp. 1178-1186 ◽  
Author(s):  
D G Chen ◽  
J R Irvine
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Semiparametric Model ◽  
Clupea Harengus ◽  
Environmental Data ◽  
Sea Surface ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Ricker Model ◽  
Stock Recruitment

A novel semiparametric model that can incorporate environmental and fishery data is developed to analyze stock–recruitment relationships. Unlike traditional stock–recruitment models that assume a log-linear relationship between recruitment and environmental and fishery variables, the new model uses a nonparametric smoothing algorithm, which helps quantify the underlying empirical relationships and enables more accurate parameter estimates. Bootstrap resampling is used to evaluate uncertainties in the model parameters. Distribution plots can be produced for stock–recruitment productivity and capacity parameters. This approach is applied to southeast Alaska pink salmon (Oncorhynchus gorbuscha) with sea surface temperature as the environmental variable and West Coast Vancouver Island herring (Clupea harengus) with sea surface temperature and hake biomass as two environmental variables. Results from diagnostic tests indicate that our model performed better than the traditional Ricker model and a Ricker model that was extended to include environmental effects.

Holocene sea surface temperature variations recorded in corals from Kikai Island, Japan

2017 ◽  
Vol 51 (4) ◽  
pp. e9-e14 ◽  
Author(s):  
Hiroto Kajita ◽  
Atsuko Yamazaki ◽  
Takaaki Watanabe ◽  
Chung-Che Wu ◽  
Chuan-Chou Shen ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Temperature Variations

PENENTUAN DAERAH POTENSIAL BUDIDAYA RUMPUT LAUT KAPPAPHYCUS ALVAREZII DI PROVINSI NUSA TENGGARA TIMUR

2019 ◽  
Vol 3 ◽  
pp. 929
Author(s):  
Marianus Filipe Logo ◽  
N M. R. R. Cahya Perbani ◽  
Bayu Priyono
Keyword(s):  
Dissolved Oxygen ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Kappaphycus Alvarezii ◽  
Sea Surface

Provinsi Nusa Tenggara Timur (NTT) merupakan penghasil rumput laut kappaphycus alvarezii kedua terbesar di Indonesia berdasarkan data Badan Pusat Statistik (2016). Oleh karena itu diperlukan zonasi daerah potensial budidaya rumput laut kappaphycus alvarezii untuk pengembangan lebih lanjut. Penelitian ini bertujuan untuk menentukan daerah yang potensial untuk budidaya rumput laut kappaphycus alvarezii di Provinsi NTT berdasarkan parameter sea surface temperature (SST), salinitas, kedalaman, arus, dissolved oxygen (DO), nitrat, fosfat, klorofil-a, dan muara sungai. Penentuan kesesuaian lokasi budidaya dilakukan dengan memberikan bobot dan skor bagi setiap parameter untuk budidaya rumput laut kappaphycus alvarezii menggunakan sistem informasi geografis melalui overlay peta tematik setiap parameter. Dari penelitian ini diperoleh bahwa kadar nitrat, arus, kedalaman, dan lokasi muara sungai menjadi parameter penentu utama. Jarak maksimum dari bibir pantai adalah sekitar 10 km. Potensial budidaya rumput laut kappaphycus alvarezii ditemukan di Pulau Flores bagian barat, kepulauan di Kabupaten Flores Timur dan Alor, selatan Pulau Sumba, Pulau Rote, dan Teluk Kupang.

EXTREME VALUES OF SEA SURFACE TEMPERATURE ASSOCIATED WITH LONG-PERIOD PHENOMENA OCCURRED DURING 1960-2015 IN THE COLOMBIAN PACIFIC OCEAN

2017 ◽  
Author(s):  
Diaz Juan Navia ◽  
Diaz Juan Navia ◽  
Bolaños Nancy Villegas ◽  
Bolaños Nancy Villegas ◽  
Igor Malikov ◽  
...  
Keyword(s):  
Time Series ◽  
Pacific Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Extreme Values ◽  
Sea Surface ◽  
Absolute Maximum ◽  
Data Set ◽  
Arctic Oscillation Index ◽  
Colombian Pacific

Sea Surface Temperature Anomalies (SSTA), in four coastal hydrographic stations of Colombian Pacific Ocean, were analyzed. The selected hydrographic stations were: Tumaco (1°48'N-78°45'W), Gorgona island (2°58'N-78°11'W), Solano Bay (6°13'N-77°24'W) and Malpelo island (4°0'N-81°36'W). SSTA time series for 1960-2015 were calculated from monthly Sea Surface Temperature obtained from International Comprehensive Ocean Atmosphere Data Set (ICOADS). SSTA time series, Oceanic Nino Index (ONI), Pacific Decadal Oscillation index (PDO), Arctic Oscillation index (AO) and sunspots number (associated to solar activity), were compared. It was found that the SSTA absolute minimum has occurred in Tumaco (-3.93°C) in March 2009, in Gorgona (-3.71°C) in October 2007, in Solano Bay (-4.23°C) in April 2014 and Malpelo (-4.21°C) in December 2005. The SSTA absolute maximum was observed in Tumaco (3.45°C) in January 2002, in Gorgona (5.01°C) in July 1978, in Solano Bay (5.27°C) in March 1998 and Malpelo (3.64°C) in July 2015. A high correlation between SST and ONI in large part of study period, followed by a good correlation with PDO, was identified. The AO and SSTA have showed an inverse relationship in some periods. Solar Cycle has showed to be a modulator of behavior of SSTA in the selected stations. It was determined that extreme values of SST are related to the analyzed large scale oscillations.

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