scholarly journals Detection of pelagic habitats and abundance of skipjack tuna in relation to the environment in the Indian Ocean around Sri Lanka

2019 ◽  
Author(s):  
Thushani Suleka Madhubha Elepathage ◽  
Danling Tang
Keyword(s):  
Monsoon Season ◽  
Remote Sensing Data ◽  
Cumulative Distribution ◽  
Optimum Level ◽  
Skipjack Tuna ◽  
Chl A ◽  
Catch Data ◽  
South West Monsoon ◽  
Pelagic Habitat ◽  
Fish Catch

Using remote sensing data of sea surface temperature (SST), chlorophyll-a (Chl-a) together with catch data, the pelagic hotspots of Skipjack tuna (SKPJ) were identified. MODIS/Aqua satellite data and the fish catch data were obtained during 2002-2016 period. Empirical cumulative distribution frequency (ECDF) model of satellite-based oceanographic data in relation to skipjack fishing was used for the initial statistical analysis and the results showed that key pelagic habitat corresponded mainly with the 0.4 – 0.7 mg m-3 Chl-a concentration. Chl-a represents the phytoplankton that attracts the food items of SKPJ like zooplankton and nekton The favorable SST range for SKPJ is 26 - 27 0C which provides suitable thermocline and an optimum level of upwelling to circulate nutrients needed for the primary production. The high total catches and CPUEs were found within the months of September to December and the optimum levels of Chl-a, SST also were observed in similar months. Hence, the South-West monsoon season was identified as the best and peak season of SKPJ fisheries. SST and Chl-a are important indicators to detect the habitats of SKPJ and the maps prepared can be used in the future to cost-effectively and efficiently identify and demarcate the biological conservation regions or fisheries zones of SKPJ. According to GAM the 0.3 - 0.6 mg m-3 Chl-a, 28 - 28.5 0C SST in Western and 0.25 - 0.3 mg m-3 Chl-a and 28.5 - 28.80C SST in Eastern were found as highly correlated predictor variables value ranges with SKPJ abundance. The deviances explained in above areas in GAM were 90.8% and 61.4% respectively. The GAM was considered as a robustly dealing method with nonlinear relationships and it can be used to model the fish catch abundance with influencing variables significantly since it could predict the CPUE values greater than 90% similarly to nominal CPUEs in both subregions of the study area.

scholarly journals Detection of pelagic habitats and abundance of skipjack tuna in relation to the environment in the Indian Ocean around Sri Lanka

2019 ◽  
Author(s):  
Thushani Suleka Madhubha Elepathage ◽  
Danling Tang
Keyword(s):  
Monsoon Season ◽  
Remote Sensing Data ◽  
Cumulative Distribution ◽  
Optimum Level ◽  
Skipjack Tuna ◽  
Chl A ◽  
Catch Data ◽  
South West Monsoon ◽  
Pelagic Habitat ◽  
Fish Catch

Using remote sensing data of sea surface temperature (SST), chlorophyll-a (Chl-a) together with catch data, the pelagic hotspots of Skipjack tuna (SKPJ) were identified. MODIS/Aqua satellite data and the fish catch data were obtained during 2002-2016 period. Empirical cumulative distribution frequency (ECDF) model of satellite-based oceanographic data in relation to skipjack fishing was used for the initial statistical analysis and the results showed that key pelagic habitat corresponded mainly with the 0.4 – 0.7 mg m-3 Chl-a concentration. Chl-a represents the phytoplankton that attracts the food items of SKPJ like zooplankton and nekton The favorable SST range for SKPJ is 26 - 27 0C which provides suitable thermocline and an optimum level of upwelling to circulate nutrients needed for the primary production. The high total catches and CPUEs were found within the months of September to December and the optimum levels of Chl-a, SST also were observed in similar months. Hence, the South-West monsoon season was identified as the best and peak season of SKPJ fisheries. SST and Chl-a are important indicators to detect the habitats of SKPJ and the maps prepared can be used in the future to cost-effectively and efficiently identify and demarcate the biological conservation regions or fisheries zones of SKPJ. According to GAM the 0.3 - 0.6 mg m-3 Chl-a, 28 - 28.5 0C SST in Western and 0.25 - 0.3 mg m-3 Chl-a and 28.5 - 28.80C SST in Eastern were found as highly correlated predictor variables value ranges with SKPJ abundance. The deviances explained in above areas in GAM were 90.8% and 61.4% respectively. The GAM was considered as a robustly dealing method with nonlinear relationships and it can be used to model the fish catch abundance with influencing variables significantly since it could predict the CPUE values greater than 90% similarly to nominal CPUEs in both subregions of the study area.

scholarly journals Detection of pelagic habitats and abundance of skipjack tuna in relation to the environment in the Indian Ocean around Sri Lanka

2019 ◽  
Author(s):  
Thushani Suleka Madhubha Elepathage ◽  
Danling Tang
Keyword(s):  
Monsoon Season ◽  
Remote Sensing Data ◽  
Cumulative Distribution ◽  
Optimum Level ◽  
Skipjack Tuna ◽  
Chl A ◽  
Catch Data ◽  
South West Monsoon ◽  
Pelagic Habitat ◽  
Fish Catch

Using remote sensing data of sea surface temperature (SST), chlorophyll-a (Chl-a) together with catch data, the pelagic hotspots of Skipjack tuna (SKPJ) were identified. MODIS/Aqua satellite data and the fish catch data were obtained during 2002-2016 period. Empirical cumulative distribution frequency (ECDF) model of satellite-based oceanographic data in relation to skipjack fishing was used for the initial statistical analysis and the results showed that key pelagic habitat corresponded mainly with the 0.4 – 0.7 mg m-3 Chl-a concentration. Chl-a represents the phytoplankton that attracts the food items of SKPJ like zooplankton and nekton The favorable SST range for SKPJ is 26 - 27 0C which provides suitable thermocline and an optimum level of upwelling to circulate nutrients needed for the primary production. The high total catches and CPUEs were found within the months of September to December and the optimum levels of Chl-a, SST also were observed in similar months. Hence, the South-West monsoon season was identified as the best and peak season of SKPJ fisheries. SST and Chl-a are important indicators to detect the habitats of SKPJ and the maps prepared can be used in the future to cost-effectively and efficiently identify and demarcate the biological conservation regions or fisheries zones of SKPJ. According to GAM the 0.3 - 0.6 mg m-3 Chl-a, 28 - 28.5 0C SST in Western and 0.25 - 0.3 mg m-3 Chl-a and 28.5 - 28.80C SST in Eastern were found as highly correlated predictor variables value ranges with SKPJ abundance. The deviances explained in above areas in GAM were 90.8% and 61.4% respectively. The GAM was considered as a robustly dealing method with nonlinear relationships and it can be used to model the fish catch abundance with influencing variables significantly since it could predict the CPUE values greater than 90% similarly to nominal CPUEs in both subregions of the study area.

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

2021 ◽  
Vol 22 (7) ◽  
Author(s):  
ANDI RANI SAHNI PUTRI ◽  
Mukti Zainuddin ◽  
MUSBIR MUSBIR ◽  
RACHMAT HIDAYAT ◽  
MUZZNEENA AHMAD MUSTAPHA
Keyword(s):  
Spatial Pattern ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Fish Distribution ◽  
Cumulative Distribution ◽  
Conservation Strategies ◽  
Skipjack Tuna ◽  
Empirical Cumulative Distribution Function ◽  
Pelagic Habitat ◽  
Potential Fishing Zone

Abstract. 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.

scholarly journals Mapping spatial-temporal skipjack tuna habitat as a reference for Fish Aggregating Devices (FADs) settings in Makassar Strait, Indonesia

2021 ◽  
Vol 22 (9) ◽  
Author(s):  
RACHMAT HIDAYAT ◽  
MUKTI ZAINUDDIN ◽  
ACHMAR MALLAWA ◽  
MUZZNEENA AHMAD MUSTAPHA ◽  
A. RANI SAHNI PUTRI
Keyword(s):  
Economic Value ◽  
Additive Model ◽  
Sea Surface ◽  
Habitat Characteristics ◽  
Cumulative Distribution ◽  
Skipjack Tuna ◽  
Empirical Cumulative Distribution Function ◽  
Pelagic Habitat ◽  
High Consistency ◽  
Fish Aggregating Devices

Abstract. Hidayat R, Zainuddin M, Mallawa A, Mustapha MA, Putri ARS. 2021. Mapping spatial-temporal skipjack tuna habitat as a reference for Fish Aggregating Devices (FADs) settings in Makassar Strait, Indonesia. Biodiversitas 22: 3637-3647. Skipjack tuna (Katsuwonus pelamis) has a high economic value in the international market. Catching skipjack tuna using fish aggregating devices (FADs) without knowing its habitat characteristics can damage the ecosystem. This study aimed to determine suitable fishing areas for setting skipjack’s FADs. The data used included that on catch, sea surface temperature (SST), and sea surface chlorophyll-a (SSC) in the Makassar Strait obtained for 2017-2019. The generalized additive model (GAM) and empirical cumulative distribution function (ECDF) analyses were used to investigate the skipjack’s tuna habitat. A pelagic habitat index (PHI), with PHI > 75%, was applied to determine suitable FAD positions. The gravity center of the skipjack tuna habitat for ten months (January-October 2020) was calculated to validate the model’s results. The results showed that the optimum SST range was from 28.78°C to 31.25°C, while the SSC from 0.18 to 0.28 mg m-3. The best skipjack habitats in the southern Makassar Strait are criterion 4 (PHI > 90%) and criterion 3 (PHI = 85-90%), having a relatively high consistency of the average PHI values. These results can help determine the optimal positions for setting FADs to benefit the global management and sustainable development of skipjack tuna fisheries.

scholarly journals Earth observation for monitoring and mapping of cyanobacteria blooms. Case studies on five Italian lakes

2016 ◽  
Vol 76 (s1) ◽  
Author(s):  
Mariano Bresciani ◽  
Claudia Giardino ◽  
Rosaria Lauceri ◽  
Erica Matta ◽  
Ilaria Cazzaniga ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Algal Blooms ◽  
Remote Sensing Data ◽  
Late Summer ◽  
Eutrophic Lake ◽  
Cyanobacterial Blooms ◽  
Landsat 8 ◽  
Negative Effects ◽  
Eutrophic Lakes ◽  
Chl A

Cyanobacterial blooms occur in many parts of the world as a result of entirely natural causes or human activity. Due to their negative effects on water resources, efforts are made to monitor cyanobacteria dynamics. This study discusses the contribution of remote sensing methods for mapping cyanobacterial blooms in lakes in northern Italy. Semi-empirical approaches were used to flag scum and cyanobacteria and spectral inversion of bio-optical models was adopted to retrieve chlorophyll-a (Chl-a) concentrations. Landsat-8 OLI data provided us both the spatial distribution of Chl-a concentrations in a small eutrophic lake and the patchy distribution of scum in Lake Como. ENVISAT MERIS time series collected from 2003 to 2011 enabled the identification of dates when cyanobacterial blooms affected water quality in three small meso-eutrophic lakes in the same region. On average, algal blooms occurred in the three lakes for about 5 days a year, typically in late summer and early autumn. A suite of hyperspectral sensors on air- and space-borne platforms was used to map Chl-a concentrations in the productive waters of the Mantua lakes, finding values in the range of 20 to 100 mgm-3. The present findings were obtained by applying state of the art of methods applied to remote sensing data. Further research will focus on improving the accuracy of cyanobacteria mapping and adapting the algorithms to the new-generation of satellite sensors.

scholarly journals Studies on fish diversity concerning Hydro-ecology of Kangsabasti river in Purulia district, West Bengal, India

2020 ◽  
Vol 26 (2) ◽  
Author(s):  
Manab Kumar Saha
Keyword(s):  
Fish Species ◽  
Physicochemical Parameters ◽  
West Bengal ◽  
Monsoon Season ◽  
Fish Diversity ◽  
Riverine Ecosystem ◽  
Post Monsoon ◽  
Fish Catch ◽  
Purulia District

Fish diversity depends both on various physicochemical parameters and the biological components of the riverine ecosystem. During the study period from January 2017 to December 2019 the highest fish diversity and density were observed in post-monsoon and lowest in pre-monsoon season in the Kangsabati River, Purulia District of West Bengal. Twenty five fish species, associated with 19 genera, 10 families and 5 orders have been identified. It was recorded that the Cyprinidae was the predominant family, which represented 56% of the entire fish catch.

scholarly journals Optimization of Rain Gauge Networks for Arid Regions Based on Remote Sensing Data

2021 ◽  
Vol 13 (21) ◽  
pp. 4243
Author(s):  
Mona Morsy ◽  
Ruhollah Taghizadeh-Mehrjardi ◽  
Silas Michaelides ◽  
Thomas Scholten ◽  
Peter Dietrich ◽  
...  
Keyword(s):  
Arid Regions ◽  
Flash Flood ◽  
Primary Source ◽  
Remote Sensing Data ◽  
Test Site ◽  
Rain Gauge ◽  
Cumulative Distribution ◽  
Climatic Data ◽  
Empirical Cumulative Distribution Function ◽  
Rain Gauges

Water depletion is a growing problem in the world’s arid and semi-arid areas, where groundwater is the primary source of fresh water. Accurate climatic data must be obtained to protect municipal water budgets. Unfortunately, the majority of these arid regions have a sparsely distributed number of rain gauges, which reduces the reliability of the spatio-temporal fields generated. The current research proposes a series of measures to address the problem of data scarcity, in particular regarding in-situ measurements of precipitation. Once the issue of improving the network of ground precipitation measurements is settled, this may pave the way for much-needed hydrological research on topics such as the spatiotemporal distribution of precipitation, flash flood prevention, and soil erosion reduction. In this study, a k-means cluster analysis is used to determine new locations for the rain gauge network at the Eastern side of the Gulf of Suez in Sinai. The clustering procedure adopted is based on integrating a digital elevation model obtained from The Shuttle Radar Topography Mission (SRTM 90 × 90 m) and Integrated Multi-Satellite Retrievals for GPM (IMERG) for four rainy events. This procedure enabled the determination of the potential centroids for three different cluster sizes (3, 6, and 9). Subsequently, each number was tested using the Empirical Cumulative Distribution Function (ECDF) in an effort to determine the optimal one. However, all the tested centroids exhibited gaps in covering the whole range of elevations and precipitation of the test site. The nine centroids with the five existing rain gauges were used as a basis to calculate the error kriging. This procedure enabled decreasing the error by increasing the number of the proposed gauges. The resulting points were tested again by ECDF and this confirmed the optimum of thirty-one suggested additional gauges in covering the whole range of elevations and precipitation records at the study site.

scholarly journals Environmental Influence on the Spatiotemporal Variability of Fishing Grounds in the Beibu Gulf, South China Sea

2020 ◽  
Vol 8 (12) ◽  
pp. 957
Author(s):  
Yanfeng Wang ◽  
Lijun Yao ◽  
Pimao Chen ◽  
Jing Yu ◽  
Qia’er Wu
Keyword(s):  
Environmental Influence ◽  
Net Primary Production ◽  
Influencing Factor ◽  
Additive Model ◽  
Remote Sensing Data ◽  
Spatiotemporal Variability ◽  
Beibu Gulf ◽  
Northeast Monsoon ◽  
Catch Per Unit Effort ◽  
Chl A

The spatiotemporal distribution of fishing grounds in the Beibu Gulf and its relationship with marine environment were analyzed using the survey data of light falling-net vessels and satellite remote sensing data including sea surface temperature (SST), chlorophyll a concentration (Chl a) and net primary production (NPP), based on the generalized additive model (GAM) and the center of gravity (COG) of fishing grounds. The results showed that the total deviance explained by GAM for the catch per unit effort (CPUE) in the Beibu Gulf was 42.9%, in which SST was the most important influencing factor on CPUE, with a relative contribution of 40%; followed by latitude, Chl a, month and NPP, with relative contributions of 25.2%, 19%, 10.4% and 5.4%, respectively. Fishing grounds in the Beibu Gulf were mainly distributed in waters with SST of 27–29 °C, Chl a of 0.5–1.5 mg m−3 and NPP of 500–700 mg m−2 d−1. Light falling-net fishing grounds were concentrated in waters with latitude of 18.5° N and 20–20.25° N. There was a significant correlation between the mean latitude of optimum NPP and the latitudinal COG of CPUE, with the R2 being 0.91. These were connected with environmental factors such as the northeast monsoon that began in autumn and winter, warm pools near 19° N and local upwelling in the Beibu Gulf.

Automated Multi-Sensor Near-Real Time Flood Monitoring in the Lower Mekong

2020 ◽  
Author(s):  
Amanda Markert ◽  
Kel Markert ◽  
Timothy Mayer ◽  
Farrukh Chisthie ◽  
Biplov Bhandari Bhandari ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Southeast Asia ◽  
Real Time ◽  
Disaster Response ◽  
Monsoon Season ◽  
Remote Sensing Data ◽  
Microwave Remote Sensing ◽  
Cost Effective ◽  
Google Earth ◽  
Flood Maps

<p>Floods and water-related disasters impact local populations across many regions in Southeast Asia during the annual monsoon season.  Satellite remote sensing serves as a critical resource for generating flood maps used in disaster efforts to evaluate flood extent and monitor recovery in remote and isolated regions where information is limited.  However, these data are retrieved by multiple sensors, have varying latencies, spatial, temporal, and radiometric resolutions, are distributed in different formats, and require different processing methods making it difficult for end-users to use the data.  SERVIR-Mekong has developed a near real-time flood service, HYDRAFloods, in partnership with Myanmar’s Department of Disaster Management that leverages Google Earth Engine and cloud computing to generate automated multi-sensor flood maps using the most recent imagery available of affected areas. The HYDRAFloods application increases the spatiotemporal monitoring of hydrologic events across large areas by leveraging optical, SAR, and microwave remote sensing data to generate flood water extent maps.  Beta testing of HYDRFloods conducted during the 2019 Southeast Asia monsoon season emphasized the importance of multi-sensor observations as frequent cloud cover limited useable imagery for flood event monitoring. Given HYDRAFloods’ multi-sensor approach, cloud-based resources offer a means to consolidate and streamline the process of accessing, processing, and visualizing flood maps in a more cost effective and computationally efficient way. The HYDRAFlood’s cloud-based approach enables a consistent, automated methodology for generating flood extent maps that are made available through a single, tailored, mapviewer that has been customized based on end-user feedback, allowing users to switch their focus to using data for disaster response.</p>

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