scholarly journals ANALISIS HUBUNGAN PRODUKSI PADI DAN INDIKATOR ENSO DI KABUPATEN TABANAN DENGAN PENDEKATAN COPULA

2016 ◽  
Vol 5 (4) ◽  
pp. 164
Author(s):  
LUH GEDE UDAYANI ◽  
I WAYAN SUMARJAYA ◽  
MADE SUSILAWATI
Keyword(s):  
Joint Distribution ◽  
Southern Oscillation ◽  
Pearson Correlation ◽  
Archimedean Copula ◽  
Model Structure ◽  
Wide Range ◽  
Frank Copula ◽  
Probability And Statistics ◽  
Dependency Model ◽  
Dependence Relationship

Dependence relationship between two or more variables is an issue that is often studied in the science of probability and statistics. Pearson correlation is often the easiest option to measure dependencies between variables. It is well known, that Pearson correlation assumes that the variable under study must be normally distributed. However, in reality this is not the case; for example, data in fields such as climatology and meteorology, insurance, and financial. Copula is a tool that can be used to model the joint distribution because it does not require the assumption of normality of the data so that it is resilient against a wide range of data. In this study, we discussed the application of copula in modeling the structure of dependencies between two variables: the production of rice and El-Nino Southern Oscillation (ENSO) indicator per period in Tabanan Regency. The best dependency model structure is given by the Frank copula of the Archimedean copula family with estimation parameter,  ? = 2,817 and the loglikelihood value of 3,47.

CORRELATION BETWEEN RAINFALL PATTERN AND OIL PALM PERFORMANCE IN SUMATRA AND BORNEO ISLAND DURING EL NIÑO 2015

2018 ◽  
Vol 24 (2) ◽  
pp. 87-96
Author(s):  
Iput Pradiko ◽  
Eko Novandy Ginting ◽  
Nuzul Hijri Darlan ◽  
Winarna Winarna ◽  
Hasril Hasan Siregar
Keyword(s):  
Oil Palm ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Pearson Correlation ◽  
Rainfall Data ◽  
Rainfall Pattern ◽  
Dry Spell ◽  
Male Flowers ◽  
Central South

El Niño 2015 is one of the strongest El Niño. Drought stress due to El Niño could affect oil palm performances. This study was conducted to determine rainfall pattern and oil palm performance in Sumatra and Borneo Island during El Niño 2015. Data employed in this study is monthly rainfall data, Southern Oscillation Index (SOI) January-December 2015, andoil palm performances. Pearson correlation between SOI and rainfall data was used to analyze rainfall pattern, while oil palm performances were observed based on morphological conditions. Result shows that southern part of Sumatra and mostly part of Borneo suffer from more dry spell, dry month, and water deficit such as 37-133 days, 3-5 months, and 349-524 mm respectively. Analysis of rainfall pattern shows that Jambi, South Sumatra, Lampung, Central, South, and East Borneo are significantly (r ≥ +0,60) affected by El Niño 2015. Oil palms in southern part of Sumatra and mostly part of Borneo are suffer from drought stressmarked by the emergence of more than two spear fronds, appearing of many male flowers, malformations on bunches, fronds tend to hanging down, and lower fronds tend to dry.

Surface bypass as a means of protecting downstream-migrating fish: lack of standardised evaluation criteria complicates evaluation of efficacy

2018 ◽  
Vol 69 (12) ◽  
pp. 1882 ◽  
Author(s):  
Elena-Maria Klopries ◽  
Zhiqun Daniel Deng ◽  
Theresa U. Lachmann ◽  
Holger Schüttrumpf ◽  
Bradly A. Trumbo
Keyword(s):  
Performance Studies ◽  
Pearson Correlation ◽  
Evaluation Criteria ◽  
Fish Passage ◽  
Performance Criteria ◽  
Design Criteria ◽  
Good Surface ◽  
Wide Range ◽  
Student’S T ◽  
Meta Analyses

Surface bypasses are downstream migration structures that can help reduce hydropower-induced damage to migrating fish. However, no comprehensive design concept that facilitates good surface bypass performance for a wide range of sites and species is available. This is why fish-passage efficiencies at recently built bypass structures vary widely between 0% and up to 97%. We reviewed 50 surface bypass performance studies and existing guidelines for salmonids, eels and potamodromous species to identify crucial design criteria for surface bypasses employed in North America, Europe and Australia. Two-tailed Pearson correlation of bypass efficiency and bypass design criteria shows that bypass entrance area (r=0.3300, P=0.0036) and proportion of inflow to the bypass (r=0.3741, P=0.0032) are the most influential parameters on bypass efficiency. However, other parameters such as guiding structures (P=0.2181, ordinary Student’s t-test) and trash-rack spacing (r=–0.1483, P=0.3951, Spearman correlation), although not statistically significant, have been shown to have an effect on efficiency in some studies. The use of different performance criteria and efficiency definitions for bypass evaluation hampers direct comparison of studies and, therefore, deduction of design criteria. To enable meta-analyses and improve bypass design considerations, we suggest a list of standardised performance parameters for bypasses that should be considered in future bypass-performance studies.

scholarly journals Use of Global Reanalysis Data in the Study of the Aridity Index in the Magdalena-Cauca Macro-Basin, Colombia

10.29007/92l9 ◽  
2018 ◽  
Author(s):  
Carolina Vega-Viviescas ◽  
David A. Zamora ◽  
Erasmo A. Rodríguez
Keyword(s):  
Southern Oscillation ◽  
Pearson Correlation ◽  
Regional Scale ◽  
Correlation Coefficients ◽  
Aridity Index ◽  
Remote Sensing Data ◽  
Reanalysis Data ◽  
In Situ Data ◽  
Global Reanalysis

The Magdalena-Cauca macro-basin (MCMB) in Colombia, by its tropical location, annually experiences the effects of movement of the Intertropical Convergence Zone, and it is highly affected by interannual macro-climatic phenomena, such as El Niño– Southern Oscillation (ENSO). With the aim of increasing the use of global reanalysis and remote sensing data for supporting water management decisions at the watershed scale and within the framework of the eartH2Observe research project, the aridity index (AI) was calculated with three different data sources. Precipitation products and AI results were compared with their corresponding in-situ national official data. The comparison shows high correlations between the AI derived from observed data and AI obtained from the reanalysis, with Pearson correlation coefficients above 0.8 for two of the products investigated. This shows the importance of using global reanalysis data in water availability studies on a regional scale for the MCMB and the potential of this information in others macrobasins in Colombia including the Orinoquia and Amazon regions, where in-situ data is scarce.

scholarly journals Ubiquity of human-induced changes in climate variability

2021 ◽  
Vol 12 (4) ◽  
pp. 1393-1411
Author(s):  
Keith B. Rodgers ◽  
Sun-Seon Lee ◽  
Nan Rosenbloom ◽  
Axel Timmermann ◽  
Gokhan Danabasoglu ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Climate Adaptation ◽  
Southern Oscillation ◽  
System Modeling ◽  
Greenhouse Warming ◽  
Earth System ◽  
Wide Range ◽  
State Changes ◽  
Mean State

Abstract. While climate change mitigation targets necessarily concern maximum mean state changes, understanding impacts and developing adaptation strategies will be largely contingent on how climate variability responds to increasing anthropogenic perturbations. Thus far Earth system modeling efforts have primarily focused on projected mean state changes and the sensitivity of specific modes of climate variability, such as the El Niño–Southern Oscillation. However, our knowledge of forced changes in the overall spectrum of climate variability and higher-order statistics is relatively limited. Here we present a new 100-member large ensemble of climate change projections conducted with the Community Earth System Model version 2 over 1850–2100 to examine the sensitivity of internal climate fluctuations to greenhouse warming. Our unprecedented simulations reveal that changes in variability, considered broadly in terms of probability distribution, amplitude, frequency, phasing, and patterns, are ubiquitous and span a wide range of physical and ecosystem variables across many spatial and temporal scales. Greenhouse warming in the model alters variance spectra of Earth system variables that are characterized by non-Gaussian probability distributions, such as rainfall, primary production, or fire occurrence. Our modeling results have important implications for climate adaptation efforts, resource management, seasonal predictions, and assessing potential stressors for terrestrial and marine ecosystems.

scholarly journals Chironomidae (Order: Diptera) diversity in relation to water quality of highland rivers at Cameron Highlands, Malaysia

2021 ◽  
Vol 42 (3(SI)) ◽  
pp. 824-831
Author(s):  
A.K. Ahmad ◽  
◽  
A. Hafizah ◽  
S.O. Sharifah Aisyah ◽  
◽  
...  
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Pearson Correlation ◽  
Diversity Indices ◽  
Class I ◽  
Small Rivers ◽  
Tropical Region ◽  
Wide Range ◽  
Cameron Highlands

Aim: This study aims to determine Chironomidae diversity and distribution in three small rivers at Cameron Highlands in relation to their response to water quality conditions. Methodology: Fifteen sites from three rivers (Palas River, Pauh River and Bertam River) were chosen for water quality measurements and Chironomidae sampling. Water quality was analysed following APHA standard methods and chironomid was identified to genus level. The rivers were classified based on Malaysian’s Water Quality Index (WQI) and macroinvertebrates diversity and distribution was analysed using diversity indices. Comparison between sites and river was undertaken using one-way ANOVA and chironomid appearance in relation to water quality was evaluated using Pearson correlation test. Results: Chironomidae (Order: Diptera) distribution at high altitude rivers in Malaysia is not well documented although this group of insect has a wide range of distribution in tropical region. Based on Malaysian water quality index (WQI), result shows all rivers were in Class I. Although still in Class I, Bertam River has slight lower water quality due to higher ammoniacal nitrogen and total suspended solids. The diversity indices also demonstrate that Bertam Rivers was in stress conditions, and other two were in moderate conditions. Three subfamilies (Chironominae, Orthocladiinae and Tanypodinae) were recorded, which comprises of 1963 individuals. Tvetenia (Subfamily: Orthocladiinae) was the most dominant but only dominated Palas River and Pauh River. Another genus from Orthocladiinae (Crocotopus and Rheocrocotopus) also recorded dominant only in Palas River and Pauh River, but lesser in Bertam River. Only Polypedilum (Subfamily: Chironominae) which was second highest recorded, dominated in all rivers, even highest in Bertam River. Amongst dominant genus, only Polypedilum was found dominant in all rivers, others were only dominating Palas River and Pauh River only. Interpretation: This findings exhibit wide range of adaptations and potential use of Polypedilum as biological indicator. Due to availability of incomplete keys, identification to species level cannot be undertaken. However, this study reveals thirteen different sub-group of Polypedilum based mouthpart organs, which represent different species for tropical ecosystems.

scholarly journals Droplet-based microfluidics platform for antifungal analysis against filamentous fungi

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sehrish Iftikhar ◽  
Aurélie Vigne ◽  
Julia Elisa Sepulveda-Diaz
Keyword(s):  
Fungal Pathogens ◽  
Antimicrobial Agents ◽  
Pearson Correlation ◽  
Hyphal Growth ◽  
Bulk Analysis ◽  
Single Spore ◽  
Microfluidic Platform ◽  
Viability Assay ◽  
Wide Range ◽  
Potential Applications

AbstractFungicides are extensively used in agriculture to control fungal pathogens which are responsible for significant economic impact on plant yield and quality. The conventional antifungal screening techniques, such as water agar and 96-well plates, are based on laborious protocols and bulk analysis, restricting the analysis at the single spore level and are time consuming. In this study, we present a droplet-based microfluidic platform that enables antifungal analysis of single spores of filamentous fungus Alternaria alternata. A droplet-based viability assay was developed, allowing the germination and hyphal growth of single A. alternata spores within droplets. The viability was demonstrated over a period of 24 h and the antifungal screening was achieved using Kunshi/Tezuma as antifungal agent. The efficacy results of the droplet-based antifungal analysis were compared and validated with the results obtained from conventional protocols. The percentage inhibitions assessed by the droplet-based platform were equivalent with those obtained by the other two methods, and the Pearson correlation analysis showed high correlation between the three assays. Taken together, this droplet-based microfluidic platform provides a wide range of potential applications for the analysis of fungicide resistance development as well as combinatorial screening of other antimicrobial agents and even antagonistic fungi.

scholarly journals Detection of Mesoscale Seasonal and Interannual Variation in the Vegetation of the Amazon Basin

2005 ◽  
Vol 9 (25) ◽  
pp. 1-16
Author(s):  
Miles G. Logsdon ◽  
Robin Weeks ◽  
Milton Smith ◽  
Jeffery E. Richey ◽  
Victoria Ballester ◽  
...  
Keyword(s):  
Time Series ◽  
El Niño ◽  
Amazon Basin ◽  
El Nino ◽  
Southern Oscillation ◽  
Mathematical Framework ◽  
Spectral Change ◽  
Range Analysis ◽  
Local Variance ◽  
Wide Range

Abstract In the Amazon basin, seasonal and interannual spectral changes measured by satellites result from anthropogenic disturbance and from the interaction between climate variation and the surface cover. Measurements of spectral change, and the characterization of that change, provide information concerning the physical processes evident at this mesoscale. A 17-yr sequence of daily Advanced Very High Resolution Radiometer (AVHRR) global area coverage (GAC) images were analyzed to produce a monthly record of surface spectral change encompassing El Niño–Southern Oscillation (ENSO) cycles. Monthly cloud-free composite images from daily AVHRR data were produced by linear filters that minimized the finescale spatial variance and allowed for a wide range analysis within a consistent mathematical framework. Here the use of a minimized local variance (MLV) filter that produced spatially smooth images in which major land-cover boundaries and spatial gradients are clearly represented is discussed. Changes in the configuration of these boundaries and the composition of the landscape elements they defined are described in terms of quantitative changes in landscape pattern. The time series produced with the MLV filter revealed a marked seasonal difference in the pattern of the landscape and structural differences over the length of the time series. Strikingly, the response of the region to drier El Niño years appears to be delayed in the MLV series, the maximum response being in the year following El Niño with little or no change seen during El Niño.

Male Weight Trainers’ Body Dissatisfaction and Exercise Dependence: Mediating Role of Muscularity Drive

2018 ◽  
Vol 122 (6) ◽  
pp. 2137-2154
Author(s):  
Hong-Yu Liu ◽  
Chiu-Chen Chang ◽  
Diane L. Gill ◽  
Shu-Ching Wu ◽  
Frank J. H. Lu
Keyword(s):  
Body Image ◽  
Body Dissatisfaction ◽  
Pearson Correlation ◽  
The Body ◽  
Exercise Dependence ◽  
Drive For Muscularity ◽  
Mediating Role ◽  
Weight Trainers ◽  
Dependence Relationship ◽  
Southern City

In considering that body image-related perceptions may be associated with weight trainers’ exercise dependence, the purpose of this study was to examine the (a) relationship between body dissatisfaction and drive for muscularity and (b) drive for muscularity as a mediator of the body dissatisfaction–exercise dependence relationship. In sum, 278 male weight trainers ( Mage =29.03 years, SD = 7.83) residing in a southern city of Taiwan completed scales of body dissatisfaction, drive for muscularity, and exercise dependence. Pearson correlation analysis found that body dissatisfaction, drive for muscularity, and exercise dependence were all correlated. Further, the indirect mediation model with bootstrapping found that drive for muscularity partially mediated the body dissatisfaction–exercise dependence relationship (c path: β = .51, SE = 0.07, p=.001: c′ path: β = .13, SE = 0.80, p = .03). We concluded that male weight trainers’ body image-related perceptions influence exercise behavior and suggested that body image-related perceptions might be considered in studying exercise dependence.

scholarly journals Tuning the Bivariate Meta-Gaussian Distribution Conditionally in Quantifying Precipitation Prediction Uncertainty

Forecasting ◽  
2020 ◽  
Vol 2 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Limin Wu
Keyword(s):  
Gaussian Distribution ◽  
Conditional Distribution ◽  
Joint Distribution ◽  
Goodness Of Fit ◽  
Pearson Correlation ◽  
Parameter Tuning ◽  
Bivariate Distribution ◽  
Distribution Model ◽  
Standard Normal ◽  
Forecast Variable

One of the ways to quantify uncertainty of deterministic forecasts is to construct a joint distribution between the forecast variable and the observed variable; then, the uncertainty of the forecast can be represented by the conditional distribution of the observed given the forecast. The joint distribution of two continuous hydrometeorological variables can often be modeled by the bivariate meta-Gaussian distribution (BMGD). The BMGD can be obtained by transforming each of the two variables to a standard normal variable and the dependence between the transformed variables is provided by the Pearson correlation coefficient of these two variables. The BMGD modeling is exact provided that the transformed joint distribution is standard normal. In real-world applications, however, this normality assumption is hardly fulfilled. This is often the case for the modeling problem we consider in this paper: establish the joint distribution of a forecast variable and its corresponding observed variable for precipitation amounts accumulated over a duration of 24 h. In this case, the BMGD can only serve as an approximate model and the dependence parameter can be estimated in a variety of ways. In this paper, the effect of tuning this parameter is studied. Numerical simulations conducted suggest that, while the parameter tuning results in limited improvements in goodness-of-fit (GOF) for the BMGD as a bivariate distribution model, better results may be achieved by tuning the parameter for the one-dimensional conditional distribution of the observed given the forecast greater than a certain large value.

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