scholarly journals The Analysis of Phytoplankton Abundance Using Weibull Distribution (A Case Study in the Coastal Area of East Yapen in the Regency of Yapen Islands, Papua)

2018 ◽  
Vol 7 (3) ◽  
pp. 251
Author(s):  
Ervina Indrayani ◽  
Lisiard Dimara ◽  
Kalvin Paiki ◽  
Felix Reba
Keyword(s):  
Coastal Waters ◽  
Likelihood Estimation ◽  
Cumulative Probability ◽  
Marine Biota ◽  
Phytoplankton Abundance ◽  
Chi Square ◽  
Phytoplankton Distribution ◽  
Distribution Parameters ◽  
Primary Producer ◽  
Special Studies

The coastal waters of East Yapen is one of the spawning sites and areas of care for marine biota in Papua. Because of its very open location, it is widely used by human activities such as fishing, residential, industrial and cruise lines. This indirectly affects the balance of coastal waters condition of East Yapen that impact on the existence of marine biota, especially phytoplankton. Phytoplanktons have a very important role because phytoplankton is the primary producer in the food chain as a link to higher tropical levels. Therefore, special studies are needed such as looking at the distribution of phytoplankton abundance at each site. The data analysis uses the American Public Health Association (APHA), Geo-statistical data, and Chi Square. Then, the distribution parameters are estimated using the Maximum Likelihood Estimation (MLE) method.The obtained parameters are used to describe the cumulative probability and survival of phytoplankton distribution. Samples are taken from fifteen sampling points. The form parameter of the phytoplankton abundance data is 3.9844 and the scale parameter is 79.929. So phytoplankton is the most widely spread in the 15th location, followed by the 6th location. While phytoplankton is at least in the 8th location.The results showthat the highest phytoplankton abundance composition is Bacillariophyceae (50%) and the lowest is Phyrrophyceae (9%) and Cyanophceae. The research is expected to provide an overview of the fertility rate of East Yapen Coastal Waters in particular and Yapen Islands regency in general.

Utilizarea teoriei valorilor extreme în climatologie

2019 ◽  
Author(s):  
Valentin Raileanu ◽  
Keyword(s):  
Maximum Likelihood ◽  
Extreme Values ◽  
Probability Distributions ◽  
Simulated Data ◽  
Likelihood Estimation ◽  
R Software ◽  
Data Set ◽  
Data Format ◽  
Generalized Pareto ◽  
Distribution Parameters

The article briefly describes the history and fields of application of the theory of extreme values, including climatology. The data format, the Generalized Extreme Value (GEV) probability distributions with Bock Maxima, the Generalized Pareto (GP) distributions with Point of Threshold (POT) and the analysis methods are presented. Estimating the distribution parameters is done using the Maximum Likelihood Estimation (MLE) method. Free R software installation, the minimum set of required commands and the GUI in2extRemes graphical package are described. As an example, the results of the GEV analysis of a simulated data set in in2extRemes are presented.

scholarly journals Phytoplankton community of a polymictic reservoir, La Plata River basin, Uruguay

1999 ◽  
Vol 59 (4) ◽  
pp. 535-541 ◽  
Author(s):  
M. C. PÉREZ ◽  
S. BONILLA ◽  
G. MARTÍNEZ
Keyword(s):  
Spatial Heterogeneity ◽  
River Basin ◽  
Phytoplankton Community ◽  
Water Reservoir ◽  
Phytoplankton Composition ◽  
Phytoplankton Abundance ◽  
La Plata ◽  
Phytoplankton Distribution ◽  
Aulacoseira Granulata

This paper deals with the analysis of phytoplankton composition and abundance from four sampling stations at the polymictic system, Rincón del Bonete water reservoir in Uruguay. Sampling data were obtained in 4 seasonal periods between February and November 1993. A hundred and twenty-four taxa were identified, where Aulacoseira granulata (Ehrenb.) Simon., A. granulata var. angustissima (Muller) Simon., A. granulata var. angustissima f. spiralis, (Muller) Simon., A. cf. ambigua, (Grun.) Simon., A. cf.. distans (Ehrenb.) Simon., Cryptomonas spp. and Synedra ulna (Nitzsch) Ehrenberg, were always present. Phytoplankton abundance fluctuated between 29 (autumn) and 2129 (summer) ind/ml. The general dominance of Aulacoseira spp. could be related to the polymictic condition of the system. In cold months phytoplankton distribution was homogeneous among sampling stations, while in warm months, spatial heterogeneity was detected, suggesting that sampling stations can behave as independent compartments.

scholarly journals The Relationship Between Water Quality and Phytoplankton Abundance at The Eastern Part of Segara Anakan Cilacap, Central Java

2019 ◽  
Vol 1 (2) ◽  
pp. 1
Author(s):  
Hasby Ghoni Asiddiqi ◽  
Agatha Sih Piranti ◽  
Erwin Ardli Riyanto
Keyword(s):  
Water Quality ◽  
Negative Correlation ◽  
Physical Factor ◽  
Phytoplankton Abundance ◽  
Chemical Factor ◽  
Strong Negative Correlation ◽  
Positive Correlation ◽  
Central Java ◽  
Primary Producer ◽  
The Relationship

Phytoplankton is the primary producer whose existence depends not only on the nutrient. The eastern part of Segara Anakan waters experienced changes where the decline in quality which received input from organic and inorganic wastes and residential, industrial and factory wastes of Holcim and Pertamina factories. The purpose of this research is to study the water quality and to study the relationship between water quality and abundance of phytoplankton at the eastern part of Segara Anakan. The result showed that Water quality in Segara Anakan waters in the eastern part of Cilacap consists of several parameters that beyond the quality standards according to the Keputusan Menteri Lingkungan Hidup No. 51 of 2004 such as pH, Nitrate, Ammonia, Phosphate, and TSS. Water temperature is a physical factor which has a strong negative correlation with the abundance of phytoplankton, followed by TSS as a physical factor which has a positive correlation. The chemical factor which has a positive correlation with abundance are TDS, Nitrite and pH, followed by Phosphate, Salinity, Ammonia, and Nitrate which has a negative correlation with the abundance of phytoplankton. Key Words: Environmental factor, phytoplankton, Segara Anakan, Spatial variation, temporal variation.

scholarly journals Modelling the number of olive groves in Spanish municipalities

2016 ◽  
Vol 14 (1) ◽  
pp. e0201
Author(s):  
Maria-Dolores Huete ◽  
Juan A. Marmolejo
Keyword(s):  
Goodness Of Fit ◽  
Likelihood Estimation ◽  
External Factors ◽  
Discrete Distributions ◽  
Future Research ◽  
Total Output ◽  
Goodness Of Fit Test ◽  
Chi Square ◽  
Total Variability ◽  
Olive Groves

<p>The univariate generalized Waring distribution (UGWD) is presented as a new model to describe the goodness of fit, applicable in the context of agriculture. In this paper, it was used to model the number of olive groves recorded in Spain in the 8,091 municipalities recorded in the 2009 Agricultural Census, according to which the production of oil olives accounted for 94% of total output, while that of table olives represented 6% (with an average of 44.84 and 4.06 holdings per Spanish municipality, respectively). UGWD is suitable for fitting this type of discrete data, with strong left-sided asymmetry. This novel use of UGWD can provide the foundation for future research in agriculture, with the advantage over other discrete distributions that enables the analyst to split the variance. After defining the distribution, we analysed various methods for fitting the parameters associated with it, namely estimation by maximum likelihood, estimation by the method of moments and a variant of the latter, estimation by the method of frequencies and moments. For oil olives, the chi-square goodness of fit test gives <em>p</em>-values of 0.9992, 0.9967 and 0.9977, respectively. However, a poor fit was obtained for the table olive distribution. Finally, the variance was split, following Irwin, into three components related to random factors, external factors and internal differences. For the distribution of the number of olive grove holdings, this splitting showed that random and external factors only account about 0.22% and 0.05%. Therefore, internal differences within municipalities play an important role in determining total variability.</p>

Enhancement of tritium concentrations on uptake by marine biota: experience from UK coastal waters

2010 ◽  
Vol 30 (1) ◽  
pp. 73-83 ◽  
Author(s):  
G J Hunt ◽  
T A Bailey ◽  
S B Jenkinson ◽  
K S Leonard
Keyword(s):  
Coastal Waters ◽  
Marine Biota

Reliability Analysis for Masked Data under Type-II Generalized Progressively Hybrid Censored Scheme

2014 ◽  
Vol 687-691 ◽  
pp. 1198-1201
Author(s):  
Bin Liu ◽  
Yi Min Shi ◽  
Jing Cai ◽  
Mo Chen
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Expectation Maximization ◽  
Expectation Maximization Algorithm ◽  
Likelihood Estimation ◽  
Lifetime Data ◽  
Type Ii ◽  
Distribution Parameters ◽  
System Lifetime Data ◽  
Quasi Newton

The Type-II generalized progressively hybrid censored scheme with masked data is presented. Based on masked system lifetime data, using the expectation maximization algorithm and the Quasi-Newton method, we obtain the Maximum Likelihood Estimation (MLE) of the components distribution parameters in the Weibull case. Finally, Monte Carlo simulation is presented to illustrate the effect.

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