scholarly journals Prediction of Potential Fishing Zones for Skipjack Tuna During the Northwest Monsoon Using Remotely Sensed Satellite Data

2017 ◽  
Vol 22 (2) ◽  
pp. 59-66
Author(s):  
Mukti Zainuddin ◽  
Safruddin Safruddin ◽  
Muhammad Banda Selamat ◽  
Aisjah Farhum ◽  
Sarip Hidayat
Keyword(s):  
Chlorophyll A ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Skipjack Tuna ◽  
Catch Per Unit Effort ◽  
Catch Data ◽  
Mean Sea Surface ◽  
Fishery Data ◽  
And Migration ◽  
The Relationship

One of economically important fish in the Bay of Bone is Skipjack tuna which their distribution and migration are influenced by surrounding environment.  This study aims to investigate the relationship between skipjack tuna and their environments, and to predict potential fishing zones (PFZs) for the fish in the Bone Bay-Flores Sea using satellite-based oceanography and catch data. Generalized additive models (GAMs) were used to assess the relationship. A generalized linear model(GLM) constructed from GAMs was used for prediction. Monthly mean sea surface temperature (SST) and chlorophyll-a during the northwest monsoon (December-January) together with catch data were used for the year 2012-2013. We used the GAMs to assess the effect of the environment variables on skipjack tuna CPUE (catch per unit effort). The best GLM was selected to predict skipjack tuna abundance.  Results indicated that the highest CPUEs (fish/trip) occurred in areas where SST and chlorophyll-a ranged from 29.5°-31.5°C and 0.15 - 0.25 mg m-3, respectively. The PFZs for skipjack were closely related to the spatial distribution of the optimum oceanographic conditions and these mainly developed in three locations, northern area of Bone Bay in December, in the middle area of the bay (4°-5.5°S and 120.5°-121.5°E) during January and moved to the Flores Sea in February. The movement of skipjack concentration was consistent with the fishery data.  This suggests that the dynamics of the optimum oceanographic signatures provided a good indicator for predicting feeding grounds as hotspot areas for skipjack tuna in Bone Bay-Flores Sea during northwest monsoon. Keywords:  skipjack tuna, potential fishing zones, satellite based-oceanographic data, Northwest monsoon

scholarly journals THE IMPACT OF OCEANOGRAPHIC PARAMETERS CHANGES ON THE DISTRIBUTION AND ABUNDANCE OF SKIPJACK TUNA Katsuwonus pelamis IN MAKASSAR STRAIT

2019 ◽  
Vol 11 (1) ◽  
pp. 171-180 ◽  
Author(s):  
Zabhika Dinda Istnaeni ◽  
Mukti Zainuddin
Keyword(s):  
Generalized Additive Models ◽  
Secondary Data ◽  
Additive Models ◽  
Primary Data ◽  
Survey Method ◽  
Skipjack Tuna ◽  
Catch Per Unit Effort ◽  
Chl A ◽  
Level 3 ◽  
The Impact

This study aimed to identify the changes of oceanographic parameters and to analyze the effects of the parameter changes on the distribution and abundance of skipjack tuna captured by purse seine fishing gear operated in Coastal Waters of Makassar Strait. This study collected fishing and field oceanographic data from May to October 2017. A survey method was used to obtain primary data (skipjack catch per unit effort/CPUE) and secondary data including sea surface temperature (SST) and Chl-a level 3 with a monthly temporal and spatial resolution of 4 km from 2007-2017, interview, and study literature. The data were processed by using SeaDAS and ArcGIS software packages and were analyzed by anomalies, standard deviation, and Generalized Additive Models (GAMs) analyses. The results showed there were anomalies for both SST and Chl-a near study area reflecting the significant changes in the oceanographic conditions. The changes for both SST and Chl-a were 1.5ºC and -0.97 mg.m-3 respectively. This study suggests that the Chl-a parameter has more significant effects on skipjack tuna distribution and CPUE than SST. Understanding of the areas of the oceanographic changes strongly supports the available habitat for the fishing operation and conservation

Oceanographic Conditions on Small Pelagic Fishery in the Gulf of Bone Waters

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Safruddin Safruddin ◽  
Rachmat Hidayat ◽  
Mukti Zainuddin
Keyword(s):  
Chlorophyll A ◽  
Generalized Additive Models ◽  
Pelagic Fish ◽  
Additive Models ◽  
Fish Distribution ◽  
Fishing Ground ◽  
Small Pelagic Fish ◽  
The Relationship ◽  
Pelagic Fishery ◽  
Oceanographic Conditions

This study aimed to investigate the relationship between the dinamic oceanographic condition and fluctuation in the catch of small pelagic fish. Study on the dinamic oceanographic conditions were focused on the sea surface temperature (SST), chlorophyll-a concentration (SSC) and water depth. The study took place in the area of Gulf of Bone located, data collection was started from April to September 2017. The data were collected using experimental fishing metode (large liftnet) and applications of remote sensing in satellite oceanography, which then analysed using Geographic Information System (GIS) dan Generalized Additive Models (GAMs). The result showed that the distribution of small pelagic fish tends to be within the area of temperature ranging from 29.5 to 30.0oC, the chlorophyll-a from 0.7 to 0.9 mg.m-3 and concentrated within the coastal area with in waters depth maximum of 100 m.Keywords: Oceanography, small pelagic fish, distribution, fishing ground, Gulf of Bone

The Relationship between Mobility and COVID-19 in Germany: Modeling Case Occurrence using Apple's Mobility Trends Data

2021 ◽  
Author(s):  
Mark David Walker ◽  
Mihály Sulyok
Keyword(s):  
Generalized Additive Models ◽  
Information Criterion ◽  
Additive Models ◽  
Online Data ◽  
German Government ◽  
Explanatory Variables ◽  
Mobility Data ◽  
Community Mobility ◽  
The Relationship ◽  
Potential Use

Abstract Background Restrictions on social interaction and movement were implemented by the German government in March 2020 to reduce the transmission of coronavirus disease 2019 (COVID-19). Apple's “Mobility Trends” (AMT) data details levels of community mobility; it is a novel resource of potential use to epidemiologists. Objective The aim of the study is to use AMT data to examine the relationship between mobility and COVID-19 case occurrence for Germany. Is a change in mobility apparent following COVID-19 and the implementation of social restrictions? Is there a relationship between mobility and COVID-19 occurrence in Germany? Methods AMT data illustrates mobility levels throughout the epidemic, allowing the relationship between mobility and disease to be examined. Generalized additive models (GAMs) were established for Germany, with mobility categories, and date, as explanatory variables, and case numbers as response. Results Clear reductions in mobility occurred following the implementation of movement restrictions. There was a negative correlation between mobility and confirmed case numbers. GAM using all three categories of mobility data accounted for case occurrence as well and was favorable (AIC or Akaike Information Criterion: 2504) to models using categories separately (AIC with “driving,” 2511. “transit,” 2513. “walking,” 2508). Conclusion These results suggest an association between mobility and case occurrence. Further examination of the relationship between movement restrictions and COVID-19 transmission may be pertinent. The study shows how new sources of online data can be used to investigate problems in epidemiology.

ENVIRONMENTAL DISASTERS IN NORTHEAST BRAZIL: HYDROMETEOROLOGICAL, SOCIAL AND SANITARY FACTORS

2021 ◽  
Author(s):  
Marcos Samuel Matias Ribeiro ◽  
Lara de Melo Barbosa Andrade ◽  
Maria Helena Constantino Spyrides ◽  
Kellen Carla Lima ◽  
Pollyane Evangelista da Silva ◽  
...  
Keyword(s):  
Generalized Additive Models ◽  
Flash Floods ◽  
Additive Models ◽  
Northeast Brazil ◽  
Waste Collection ◽  
Climate Conditions ◽  
Environmental Disasters ◽  
Basic Services ◽  
The Relationship ◽  
Drought Occurrence

AbstractThe occurrence of environmental disasters affects different social segments, impacting health, education, housing, economy and the provision of basic services. Thus, the objective of this study was to estimate the relationship between the occurrence of disasters and extreme climate, sociosanitary and demographic conditions in the Northeast region of Brazil during the period from 1993 to 2013. Initially, we analyzed the spatial pattern of the incidence of events and, subsequently, generalized additive models for location, scale and shape were used in order to identify and estimate the magnitude of associations between factors. Results showed that droughts are the predominant disasters in the NEB representing 81.1% of the cases, followed by events triggered by excessive rainfall such as flash floods (11.1%) and floods (7.8%). Climate conditions presented statistically significant associations with the analyzed disasters, in which indicators of excess rainfall positively contributed to the occurrence of flash floods and floods, but negatively contributed to the occurrence of drought. Sociosanitary factors, such as percentage of households with inadequate sewage, waste collection and water supply, were also positively associated with the model’s estimations, i.e., contributing to an increase in the occurrence of events, with the exception of floods, which were not significantly influenced by sociosanitary parameters. A decrease of 19% in the risk of drought occurrence was estimated, on average. On the other hand, events caused by excessive rainfall increased by 40% and 57%, in the cases of flash floods and floods, respectively.

scholarly journals A Longitudinal Analysis of the Impact of Distance Driven on the Probability of Car Accidents

Risks ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 91
Author(s):  
Jean-Philippe Boucher ◽  
Roxane Turcotte
Keyword(s):  
Poisson Distribution ◽  
Fixed Effects ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Panel Count Data ◽  
Insurance Company ◽  
Smooth Functions ◽  
Claim Frequency ◽  
The Impact ◽  
The Relationship

Using telematics data, we study the relationship between claim frequency and distance driven through different models by observing smooth functions. We used Generalized Additive Models (GAM) for a Poisson distribution, and Generalized Additive Models for Location, Scale, and Shape (GAMLSS) that we generalize for panel count data. To correctly observe the relationship between distance driven and claim frequency, we show that a Poisson distribution with fixed effects should be used because it removes residual heterogeneity that was incorrectly captured by previous models based on GAM and GAMLSS theory. We show that an approximately linear relationship between distance driven and claim frequency can be derived. We argue that this approach can be used to compute the premium surcharge for additional kilometers the insured wants to drive, or as the basis to construct Pay-as-you-drive (PAYD) insurance for self-service vehicles. All models are illustrated using data from a major Canadian insurance company.

Application of generalized additive models to examine ontogenetic and seasonal distributions of spiny dogfish (Squalus acanthias) in the Northeast (US) shelf large marine ecosystem

2014 ◽  
Vol 71 (6) ◽  
pp. 847-877 ◽  
Author(s):  
Skyler R. Sagarese ◽  
Michael G. Frisk ◽  
Robert M. Cerrato ◽  
Kathy A. Sosebee ◽  
John A. Musick ◽  
...  
Keyword(s):  
Generalized Additive Models ◽  
Marine Ecosystem ◽  
Additive Models ◽  
Squalus Acanthias ◽  
Seasonal Occurrence ◽  
Spiny Dogfish ◽  
Science Center ◽  
Large Marine Ecosystem ◽  
Northeast Us ◽  
The Relationship

Increased commercial importance of spiny dogfish (Squalus acanthias) combined with an often debated, and controversial, ecological impact has warranted an investigation of the relationship among distribution, environment, and prey to better understand the species ecology and inform management. To elucidate mechanisms behind distributional changes, we modeled seasonal occurrence and abundance of neonate, immature, and mature spiny dogfish as functions of abiotic and biotic factors using generalized additive models and Northeast Fisheries Science Center bottom trawl survey data. Significant nonlinear relationships were widespread throughout dogfish stages and seasons. Seasonal occurrence was tightly linked to depth and bottom temperature, with year and Julian day influential for some stages. While these factors also influenced abundance, ecological factors (e.g., squid abundances) significantly contributed to trends for many stages. Potential impacts of climate change were evaluated by forecasting distributions under different temperature scenarios, which revealed higher regional probabilities of occurrence for most stages during a warmer than average year. Our results can be used to better understand the relationship between sampling periods and movement drivers to survey catchability of the population in the Northeast (US) shelf large marine ecosystem.

scholarly journals A Decision Support Model for the Necessity of Cardio-Angiography, A Result of Generalized Additive and logistic Regression Model

2021 ◽  
Author(s):  
Fatemeh Rezaeisharif ◽  
Azadeh Saki ◽  
Ali Taghipour ◽  
Mohammad Tajfard
Keyword(s):  
Coronary Artery ◽  
Blood Sugar ◽  
Logistic Regression Model ◽  
Generalized Additive Models ◽  
Coronary Artery Occlusion ◽  
Artery Occlusion ◽  
Additive Models ◽  
Evidence Based ◽  
Hs Crp ◽  
The Relationship

Introduction: Angiography is used as the gold standard for diagnosis of coronary artery disease (CAD). It is an invasive procedure and has several complications. Also, some patients refuse angiograms for reasons such as fear, high cost, and loss of trust in physician diagnosis. The negative results of this test is more than a third. Therefore, having a statistical predictive model for estimating the risk of CAD, as an evidence-based support system, can help the physician and patient decide on the necessity of angiography. Aims: In this study we aimed to find an evidence-based supportive model for decision making on the necessity of angiography in people who were candidates for angiography by the physician after initial tests. Methods: In this study, 1187 patients who had been referred to Ghaem Hospital of Mashhad University of Medical Sciences and diagnosed with physicians after initial tests were enrolled. Demographic data, lipid and blood sugar levels, and the history of underlying disorders were variables that were studied in the statistical model fitting. Initially, generalized additive models were used singularly for quantitative predictors, then by applying right transformations on the predictor variables we entered them simultaneously in logistic and count regression models. These two models were fitted to the data using R software and then compared in terms of predictive accuracy. Findings: Generalized additive models showed that the relationship between CAD with the hs-CRP level was not monotone. Exploratory analyzes showed that 62% of people with hs-CRP level <3 and 50% of people with hs-CRP levels between 3 and 6 were suffered from the CAD. The highest rate of CAD was seen in the range of 6-8 (93%) but with increasing the hs-CRP level to above 8 it decreased to 70%. The relationship between age and the risk of CAD was S-shaped. Risk of CAD in diabetic subjects with normal FBS was equal to that of nondiabetic subjects with normal fasting blood sugar. The age, gender, diabetes, FBS, and hs-CRP were significant in both models (p <0.05). The area under the ROC curve was upgraded to 81 for the logistic model. Conclusion: The most important finding of this exploratory study was that out of 232 patients with hs-CRP level between 6 to 8, 217 (93%) had coronary artery occlusion, for these subjects the probability of occluding a coronary artery was 0.93. The present study also showed that if the blood sugar is controlled in patients with diabetes, then this disease will not be a risk factor for patients with coronary artery occlusion. The logistic regression model presented in this study is recommended as the final model to support decision-making about the necessity of angiography.

scholarly journals Distributional Regression Techniques in Socioeconomic Research on the Inequality of Health with an Application on the Relationship between Mental Health and Income

2019 ◽  
Vol 16 (20) ◽  
pp. 4009 ◽  
Author(s):  
Alexander Silbersdorff ◽  
Kai Sebastian Schneider
Keyword(s):  
Mental Health ◽  
Health Inequalities ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Mental Health Score ◽  
Cross Sectional ◽  
Regression Techniques ◽  
German Socioeconomic Panel ◽  
The Relationship ◽  
Distributional Regression

This study addresses the much-discussed issue of the relationship between health and income. In particular, it focuses on the relation between mental health and household income by using generalized additive models of location, scale and shape and thus employing a distributional perspective. Furthermore, this study aims to give guidelines to applied researchers interested in taking a distributional perspective on health inequalities. In our analysis we use cross-sectional data of the German socioeconomic Panel (SOEP). We find that when not only looking at the expected mental health score of an individual but also at other distributional aspects, like the risk of moderate and severe mental illness, that the relationship between income and mental health is much more pronounced. We thus show that taking a distributional perspective, can add to and indeed enrich the mostly mean-based assessment of existent health inequalities.

scholarly journals Sardine potential habitat and environmental forcing off western Portugal

2010 ◽  
Vol 67 (8) ◽  
pp. 1553-1564 ◽  
Author(s):  
Juan P. Zwolinski ◽  
Paulo B. Oliveira ◽  
Victor Quintino ◽  
Yorgos Stratoudakis
Keyword(s):  
Chlorophyll A ◽  
Seasonal Pattern ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Seasonal Effect ◽  
Oceanic Circulation ◽  
Environmental Forcing ◽  
Potential Habitat ◽  
The North ◽  
Spatio Temporal

Abstract Zwolinski, J. P., Oliveira, P. B., Quintino, V., and Stratoudakis, Y. 2010. Sardine potential habitat and environmental forcing off western Portugal. – ICES Journal of Marine Science, 67: 1553–1564. Relationships between sardine (Sardina pilchardus) distribution and the environment off western Portugal were explored using data from seven acoustic surveys (spring and autumn of 2000, 2001, 2005, and spring 2006). Four environmental variables (salinity, temperature, chlorophyll a, and acoustic epipelagic backscatter other than fish) were related to the acoustic presence and density of sardine. Univariate quotient analysis revealed sardine preferences for waters with high chlorophyll a content, low temperature and salinity, and low acoustic epipelagic backscatter. Generalized additive models depicted significant relationships between the environment and sardine presence but not with sardine density. Maps of sardine potential habitat (SPH) built upon the presence/absence models revealed a clear seasonal effect in the across-bathymetry and alongshelf extension of SPH off western Portugal. During autumn, SPH covered a large part of the northern Portuguese continental shelf but was almost absent from the southern region, whereas in spring SPH extended farther south but was reduced to a narrow band of shallow coastal waters in the north. This seasonal pattern agrees with the spatio-temporal variation of primary production and oceanic circulation described for the western Iberian shelf.

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