A non-negative matrix factorization based clustering to identify potential tuna fishing zones

<span lang="EN-US">Many nonnegative matrix factorization based clusterings are employed in discovering pattern and knowledge. Considering the sparseness nature of our data set about the daily tuna fishing data, we attempted to utilize a clustering approach, which is based on non-negative matrix factorization. Adding sparseness constraint and assigning good initial value in the modified NMF method, a proposed algorithm Direct-NMFSC yielded better result cluster compared to other methods which are also utilizing sparse constraint to their approaches, SNMF and NMFSC. The result of this study shows that Direct-NMFSC has 5.376 times of iteration number less than NMFSC in average with 531.97 as the CH index result. The determination of potential fishing zones is one of the essential efforts in the potential fishing zone mapping system for tuna fishing. By means of this novel data-driven study to construct the information and to identify the potential tuna fishing zones is done. We also showed that utilizing the Direct-NMFSC can spot and identify the potential tuna fishing zones presented in red cluster that covers both the spatial and temporal information.</span>

Mapping of fishing area (Euthynnus affinis) GIS based in Bone’s Bay Waters

The purpose of this study was to identify the relationship between oceanographic factors and the catch of tuna (Euthynnus affinis) and to determine the potential fishing zone (ZPPI) in the waters of the Gulf of Bone. The data collection method is carried out by literature study and field observation study by taking coordinate points and measuring oceanographic parameters. The types of data collected were temperature, salinity, currents, and tuna catches. Data were analyzed using GIS software with the Kolmogorov-Smirnov normality test and ANOVA test. This research was conducted in Bone Bay Waters in October-November 2018. The results showed that the highest catch based on sea surface temperature was in the range of 32°C with a total yield of 1207.5 kg, the highest net based on salinity was in the field of 34‰, namely as much as 836.5 kg, and the highest catch is based on a current speed of 0.04 m/sec, which is as much as 334.5 kg. Based on the ANOVA table, the significance value of the effect of temperature (X1), salinity (X2), and current (X3) simultaneously on the tuna catch (Y) is 0.0425<0.05 and the Fcrit>Ftabel (5.960>4,75) which means that there is a significant effect of oceanographic parameters on the tuna catch. Overlay analysis of oceanographic parameters shows potential areas for Euthynnus affinis is located most of the waters of Sinjai to the south of the Sembilan Island to the outside of Bone Bay.

Mapping potential fishing zones for skipjack tuna in the southern Makassar Strait, Indonesia, using Pelagic Habitat Index (PHI)

Putri ARS, Zainuddin M, Musbir, Mustapha MA, Hidayat R. 2021. Mapping potential fishing zones for skipjack tuna in the southern Makassar Strait, Indonesia, using Pelagic Habitat Index (PHI). Biodiversitas 22: 3037-3045. Southern Makassar Strait is one of the potential fishing grounds for skipjack tuna in the Indonesian waters. Oceanographic factors become the primary factors that limit the distribution and abundance of fish. The study aimed to identify the relationship between fish distribution with sea surface temperature (SST) and primary productivity (PP) and map out the potential fishing grounds of skipjack tuna in the southern Makassar Strait. It used pelagic habitat index (PHI) analysis, which is strengthened by the results of correlation analysis in the form of generalized additive models (GAM) and Empirical cumulative distribution function (ECDF) analysis. The results showed that the distribution of skipjack tuna was significantly associated with the preferred range of SST 29-30.5°C and PP 350-400 mg C/m2/day. The potential fishing zone is well established near the coast to offshore of Barru and Polman waters (3°-6°S and 117°-119°E), with the peak season in May and October. The spatial pattern of potential fishing grounds for skipjack fishing is associated with hotspots (oceanographic preference), leading to increased feeding opportunities. This study suggests that the spatial pattern of high potential fishing zones could improve fishing, management, and conservation strategies along the southern Makassar Strait.

A Web-GIS and Mobile-Based Application for a Safe Ocean for Fishers

One of the societal outcomes envisaged for the United Nations Decade of Ocean Science for Sustainable Development (2021‐2030) is a safe ocean where the safety of operations at sea and the coast are ensured. The Indian coast is prone to tropical cyclones, and the recent Ockhi, Gaja, Nilam, and Nivar cyclones devastated coastal Tamil Nadu in southern India, particularly the fishing community. This brought into focus the need to develop tools for the safety of fishermen at sea. A user-friendly application was developed named “Thoondil” (meaning fishing rod in the local language) by the National Centre for Coastal Research and made operational by the Department of Fisheries, Government of Tamil Nadu. It comprises a web-GIS-based dashboard for the state administrators and an android application for the fishermen. The salient features of the mobile application include the compass, weather, rescue plan, offline maps that provide the route to the nearest ports, incidence reporting, weather details, and potential fishing zone. The Thoondil dashboard provides information about the users and travel details, and helps to get information about the fishermen at sea at any point of time. A two-way communication between the administrators and the fishing community is enabled. The system is available in vernacular language with more than 15,000 downloads in a couple of months. Based on user interactions, it has evolved as a pan-India application and currently replicated in Kozhikode, Kerala. The use of the app has reduced risk to the fishing community, especially during hazards and has also contributed to the resilience of the coastal fishing communities.

POTENTIAL FISHING ZONES ESTIMATION BASED ON APPROACH OF AREA MATCHING BETWEEN THERMAL FRONT AND MESOTROPHIC AREA

Research in Potential Fishing Zone (PFZ) has undergone many developments, including parameter suitability selection. The thermal front has become the primary parameter input of ZPPI (LAPAN's PFZ). The accuracy of the thermal front parameter to predict PFZ cannot be known with certainty because of the radius between ZPPI with fishing areas, so it is necessary to develop parameters to support the thermal front. The thermal front described the meeting area of two water masses with different temperature characteristics associated with high nutrients (chlorophyll-a) and indicate an upwelling's appearance. This study aims to determine ZPPI by approaching the thermal front and mesotrophic area's matching area (chlorophyll-a concentration 0.2-0.5 mg/m3). Chlorophyll-a and sea surface temperature data for thermal fronts detection are derived from Aqua MODIS satellite on Google Earth Engine (GEE). The matching area's approach between the thermal front and mesotrophic area is used in the analysis of ZPPI. The results show thermal front and mesotrophic area on WPPNRI 715 have a variation seasonally where December appears like the peak event. The two parameters are distributed evenly from coastal areas to high seas. This method generates thermal fronts that have more than 60.3% matching with the mesotrophic area where the amount is acceptable due to has more than 50% amount of moderate ZPPI. The accuracy improvement in ZPPI both on the coast and open sea can be determined through this approach.

ROLLING MOSAIC METHOD TO SUPPORT THE DEVELOPMENT OF POTENTIAL FISHING ZONE FORECASTING FOR COASTAL AREAS

The production of the Indonesian Institute for Marine Research and Observation’s mapping of forecast fishing areas (peta prakiraan daerah penangkapan ikan or PPDPI) based on passive satellite imagery is often constrained by high-cloud-cover issues, which lead to sub-optimal results. This study examines the use of the rolling mosaic method for providing geophysical variables, in particular, seasurface temperature (STT) together with minimum cloud cover, to enable clearer identification of oceanographic conditions. The analysis was carried out in contrasting seasons: dry season in July 2018 and rainy season in December 2018. In general, the rolling mosaic method is able to reduce cloud cover for sea-surface temperature (SST) data. A longer time range will increase the coverage percentage (CP) of SST data. In July, the CP of SST data increased significantly, from 15.3 % to 30.29% for the reference 1D mosaic and up to 84.19 % to 89.07% for the 14D mosaic. In contrast, the CP of SST data in December tended to be lower, from 4.93 % to 13.03% in the 1D mosaic to 41.48 % to 51.60% in the14D mosaic. However, the longer time range decreases the relationship between the reference SST data and rolling mosaic method data. A strong relationship lies between the 1D mosaic and 3D mosaics, with correlation coefficients of 0.984 for July and 0.945 for December. Furthermore, a longer time range will decrease root mean square error (RMSE) values. In July, RMSE decreased from 0.288°C (3D mosaic) to 0.471°C (14D mosaic). The RMSE value in December decreased from 0.387°C (3D mosaic) to 0.477°C (14D mosaic). Based on scoring analysis of CP, correlation coefficient and RMSE value, results indicate that the 7D mosaic method is useful for providing low-cloud-coverage SST data for PPDPI production in the dry season, while the 14D mosaic method is suitable for the rainy season.

Analysis of landings of Indian mackerel during the period 2014 to 2018 at Junglighat fish landing centre, South Andaman, India

Junglighat fishing harbour is a very large and dynamic fish landing Centre (FLC) in Andaman & Nicobar Islands where the maximum fishing gears operations occur. A study has been done to find out the status of Indian Mackerel catches by ring net at Junglighat FLC. Monthwise periodic visits have been done at this FLC for 5 (five) consecutive years from 2014 to 2018. 1322 operation of ring net were noted during the period (2014-18) and 1594 tons of fishes were captured i.e. ring net contributed 40.1 % of the catch amongst the other gears. There were indications that a single/similar stock of fish was being attracted to PFZ in comparison to Non –PFZ. This has been observed in the catches of Rastrelliger kanagurta caught (300 to 5270 kg) which was exceptionally higher at Potential Zones. The same was indicated during the experiments in two or three hauls. The fishes captured from the PFZ and Non PFZ were 56850 kg with an average of 1672.1±209.37 kg and 14700 kg with an average of 432.4±46.88 kg respectively. The Length-weight measurements of the fishes caught from both the zones have been done. Altogether 9 Class Intervals with respect to length were observed from the catch of R. kanagurta i.e. 141-160 mm, 161-180 mm ........301-320 mm. In the Class Intervals of 261-280 altogether199 specimens have been observed contributing 30.9% in the PFZ and the Class Intervals of 201-220, 144 specimens were observed contributing to 23% of the catch from the Non-PFZ. The length weight relationship (LWR) were illustrated for this species, the R2 value of R. Kanagurta corresponded to the PFZ and Non-PFZ were 0.926 and 0.893 respectively. The R2 value of the species at PFZ was higher which could be attributed to higher abundance food from the Potential Fishing Zone. The water samples were collected from various sites of PFZ and Non-PFZ during the study period and analysed. The average visibility at PFZ and Non-PFZ were 15.49±0.28 m and 16.74 ± 0.25 during respectively. The average dissolved oxygen (DO) at PFZ and Non-PFZ were 6.30±0.05 mg/lit respectively. Due to density of phytoplankton and Eddies the dissolved oxygen increased at PFZ than Non-PFZ. Alkalinity was at PFZ 111.16±1.09 ml/lit and Non PFZ 113.68 ± 1.28 ml/lit respectively.

Role of Remote Sensing in Potential Fishing Zone Forecast

Forecasting of Potential Fishing Zone (PFZ) is considered as economically and environmentally significant towards ensuring profitable base of economy and planning for sustenance of existing fishing pool. Changes in environmental conditions affect the distribution, abundance and availability of fish. The traditional sampling approaches for PFZ identification using boats and vessels are not only costly and time consuming but practically absurd considering the vastness of seas and oceans. In this chapter importance of alternative but effective methods of airborne and satellite remote sensing has been given. The chapter elucidates the factors for PFZ identification like thermal condition in sea controlling its thermal circulation, chlorophyll-a concentration estimated from ocean color dynamics, etc. Tools/system to prepare PFZ advisories and also the platforms for dissemination of the same, have been illustrated based on Indian scenario.