Biomass estimation of Artemia at Lake Grassmere, Marlborough, New Zealand

1985 ◽  
Vol 36 (4) ◽  
pp. 537 ◽  
Author(s):  
SJ Haslett ◽  
RG Wear
Keyword(s):  
New Zealand ◽  
Bootstrap Method ◽  
Estimation Procedure ◽  
Dry Weight ◽  
Biomass Estimation ◽  
Total Biomass ◽  
Solar Salt ◽  
Log Normal ◽  
Confidence Interval Estimates ◽  
The Bootstrap Method

During 1980-1982, a sampling program to estimate Artemia biomass was carried out over an annual cycle in the solar salt ponds of Lake Grassmere, Marlborough, New Zealand. Density of Artemia was highest over 238.5 ha of the 1782 ha in 13 ponds, averaging 0.55 m deep, which form the final stages in salt concentration. Artemia and hydrological samples were taken twice a month on 23 occasions from April 1981 to April 1982 inclusive, and on each occasion, 86 sample stations over four ponds were sampled in triplicate. An unbiased estimate of biomass using the arithmetic mean was developed, together with confidence interval estimates based on the bootstrap method giving 95% confidence bound estimates within 25% of the estimated total Artemia biomass in each sampled pond. Artemia biomass concentrations within 50 m of the pond edges were, on average, 2.5 times those at the pond centre, and the biomass estimation procedure was thus accordingly stratified. Generally, Artemia were contagiously distributed with the edge stratum biomass having a log-normal distribution at each sampling time. Biomass was highest during late spring and summer, and lowest in late autumn through winter. Maximum estimated total biomass over 238.5 ha was 12 000 kg dry weight during January 1982.

ERRORS ASSOCIATED WITH HERBAGE DISSECTION ANALYSES 2. Problems of species identification

1976 ◽  
pp. 213-225
Author(s):  
I.M. Ritchie ◽  
C.C. Boswell ◽  
A.M. Badland
Keyword(s):  
New Zealand ◽  
Dry Weight ◽  
Analytical Tool ◽  
Species Level ◽  
Weight Basis ◽  
Plant Identification ◽  
Leaf Fragment ◽  
Research Division ◽  
Or Groups ◽  
Botanical Analysis

HERBACE DISSECTION is the process in which samples of herbage cut from trials are separated by hand into component species. Heavy reliance is placed on herbage dissection as an analytical tool ,in New Zealand, and in the four botanical analysis laboratories in the Research Division of the Ministry of Agriculture and Fisheries about 20 000 samples are analysed each year. In the laboratory a representative subsample is taken by a rigorous quartering procedure until approximately 400 pieces of herbage remain. Each leaf fragment is then identified to species level or groups of these as appropriate. The fractions are then dried and the composition calculated on a percentage dry weight basis. The accuracy of the analyses of these laboratories has been monitored by a system of interchanging herbage dissection samples between them. From this, the need to separate subsampling errors from problems of plant identification was, appreciated and some of this work is described here.

scholarly journals Statistical Estimates of the Pulsar Glitch Activity

Universe ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 8
Author(s):  
Alessandro Montoli ◽  
Marco Antonelli ◽  
Brynmor Haskell ◽  
Pierre Pizzochero
Keyword(s):  
Linear Regression ◽  
Upper Bound ◽  
Bootstrap Method ◽  
Waiting Times ◽  
Statistical Estimates ◽  
Equal Variance ◽  
Linear Fit ◽  
The Moment ◽  
The Bootstrap Method

A common way to calculate the glitch activity of a pulsar is an ordinary linear regression of the observed cumulative glitch history. This method however is likely to underestimate the errors on the activity, as it implicitly assumes a (long-term) linear dependence between glitch sizes and waiting times, as well as equal variance, i.e., homoscedasticity, in the fit residuals, both assumptions that are not well justified from pulsar data. In this paper, we review the extrapolation of the glitch activity parameter and explore two alternatives: the relaxation of the homoscedasticity hypothesis in the linear fit and the use of the bootstrap technique. We find a larger uncertainty in the activity with respect to that obtained by ordinary linear regression, especially for those objects in which it can be significantly affected by a single glitch. We discuss how this affects the theoretical upper bound on the moment of inertia associated with the region of a neutron star containing the superfluid reservoir of angular momentum released in a stationary sequence of glitches. We find that this upper bound is less tight if one considers the uncertainty on the activity estimated with the bootstrap method and allows for models in which the superfluid reservoir is entirely in the crust.

The Bootstrap-Method: Discussion and Proposal for Improvement / Das bootstrap-Verfahren: Diskussion und Verbesserungsvorschlag

1998 ◽  
Vol 217 (1) ◽  
Author(s):  
Hans Schneeberger
Keyword(s):  
Bootstrap Method ◽  
Law School ◽  
Mean Deviation ◽  
Alternative Method ◽  
Doubling Method ◽  
The Mean ◽  
The Bootstrap Method

SummaryWith Efron’s law-school example the bootstrap method is compared with an alternative method, called doubling. It is shown, that the mean deviation of the estimator is always smaller for the doubling method.

scholarly journals Sulfur application alleviates chromium stress in maize and wheat

2020 ◽  
Vol 18 (1) ◽  
pp. 1093-1104
Author(s):  
Grzegorz Kulczycki ◽  
Elżbieta Sacała
Keyword(s):  
Adverse Effects ◽  
Mineral Nutrition ◽  
Elemental Sulfur ◽  
Marked Decrease ◽  
Total Yield ◽  
Growth Yield ◽  
Dry Weight ◽  
Total Biomass ◽  
Cr Content ◽  
Chromium Stress

AbstractThis study aimed to examine the influence of increasing doses of chromium (Cr) (26, 39, and 52 mg kg−1 soil) and elemental sulfur (S) (60 mg kg−1 soil) on growth, yield, and mineral nutrition in wheat and maize. Macro- and micronutrients and Cr concentrations were determined in the aboveground parts of plants. All examined doses of Cr caused a marked decrease in the fresh and dry weight of maize. Wheat was more tolerant than maize, and lower Cr doses caused a small but statistically significant increase in the total yield. Wheat accumulated more than twofold Cr than maize, and the concentrations increased with higher Cr concentrations in the soil. The application of S significantly improved the total biomass production and lowered the Cr content in both plants. Cr changed the mineral nutrition in both cereals, but the pattern of changes observed was not the same. Applying S alleviated some adverse effects caused by the Cr. Hence, it is concluded that the application of elemental S may be an effective strategy to reduce adverse effects in plants grown on soil contaminated by heavy metals, especially Cr.

Application of the bootstrap method to quantify uncertainty in seismic hazard estimates

1992 ◽  
Vol 82 (1) ◽  
pp. 104-119
Author(s):  
Michéle Lamarre ◽  
Brent Townshend ◽  
Haresh C. Shah
Keyword(s):  
Confidence Interval ◽  
Seismic Hazard ◽  
Statistical Method ◽  
Bootstrap Method ◽  
Earthquake Magnitude ◽  
Earthquake Catalog ◽  
Uncertainty Measure ◽  
Attenuation Models ◽  
The Bootstrap Method

Abstract This paper describes a methodology to assess the uncertainty in seismic hazard estimates at particular sites. A variant of the bootstrap statistical method is used to combine the uncertainty due to earthquake catalog incompleteness, earthquake magnitude, and recurrence and attenuation models used. The uncertainty measure is provided in the form of a confidence interval. Comparisons of this method applied to various sites in California with previous studies are used to confirm the validity of the method.

Diet of European freshwater pearl mussels Margaritifera margaritifera (Mollusca: Bivalvia: Unionoida) in small river (Republic of Karelia, Russia)

2021 ◽  
Vol 325 (4) ◽  
pp. 502-515
Author(s):  
S.F. Komulaynen
Keyword(s):  
Algal Species ◽  
Dry Weight ◽  
Lake Ladoga ◽  
Total Biomass ◽  
Margaritifera Margaritifera ◽  
Pearl Mussel ◽  
Organic Detritus ◽  
Unicellular Algae ◽  
Wide Range ◽  
Intestinal Contents

The freshwater pearl mussel Margaritifera margaritifera (Linnaeus,1758) is endangered in Europe and is now listed in the Red Data Book of many countries and regions. The diet of the species in the Syskyänjoki River (a tributary of Lake Ladoga) has been studied. The contents of the intestine generally correspond to the composition of seston, and include organic detritus, filamentous and unicellular algae, fragments of invertebrates and macrophyte tissues mixed with silt and sand. The total biomass of the intestinal contents of varied from 0.8 to 30.6 mg per organism (absolutely dry weight). Margaritifera margaritifera consumes a wide range of particles, from 0.5 μm3 (bacteria and unicellular algae) to 200 000 μm3 (fragments of invertebrates and macrophyte tissues). About 90–95% (by volume) of the intestinal contents was consisted by fine organic detritus. The food composition did not differ significantly for mollusks of different sexes and size. In the intestinal contents, 63 taxa of algae were identified. The number of algal species in the content of one intestine varied from 3 to 17, with their abundance from 250 to 9560 cells per organism. The most abundant and constant in the contents of the intestines are unicellular algae. Diatoms are the most diverse, they make up 50.8% of the total number of species.

Standard Error Estimation of 3PL IRT True Score Equating With an MCMC Method

2008 ◽  
Vol 33 (3) ◽  
pp. 257-278 ◽  
Author(s):  
Yuming Liu ◽  
E. Matthew Schulz ◽  
Lei Yu
Keyword(s):  
Bootstrap Method ◽  
Standard Errors ◽  
True Score ◽  
Mcmc Method ◽  
Test Form ◽  
True Score Equating ◽  
Standard Error Estimation ◽  
Equivalent Test ◽  
Mean Square Errors ◽  
The Bootstrap Method

A Markov chain Monte Carlo (MCMC) method and a bootstrap method were compared in the estimation of standard errors of item response theory (IRT) true score equating. Three test form relationships were examined: parallel, tau-equivalent, and congeneric. Data were simulated based on Reading Comprehension and Vocabulary tests of the Iowa Tests of Basic Skills®. For parallel and congeneric test forms within valid IRT true score ranges, the pattern and magnitude of standard errors of IRT true score equating estimated by the MCMC method were very close to those estimated by the bootstrap method. For tau-equivalent test forms, the pattern of standard errors estimated by the two methods was also similar. Bias and mean square errors of equating produced by the MCMC method were smaller than those produced by the bootstrap method; however, standard errors were larger. In educational testing, the MCMC method may be used as an additional or alternative procedure to the bootstrap method when evaluating the precision of equating results.

Forest Biomass Estimation Based on Forest Inventory Data in Middle and Last Scales

2011 ◽  
Vol 183-185 ◽  
pp. 220-224
Author(s):  
Ming Ze Li ◽  
Wen Yi Fan ◽  
Ying Yu
Keyword(s):  
Tree Species ◽  
Forest Inventory ◽  
Forest Biomass ◽  
Biomass Estimation ◽  
Total Biomass ◽  
Inventory Data ◽  
Biomass Equation ◽  
Tree Species Composition ◽  
Forest Inventory Data ◽  
Ecosystem Carbon

The forest biomass (which is referred to the arbor aboveground biomass in this research) is one of the most primary factors to determine the forest ecosystem carbon storages. There are many kinds of estimating methods adapted to various scales. It is a suitable method to estimate forest biomass of the farm or the forestry bureau in middle and last scales. First each subcompartment forest biomass should be estimated, and then the farm or the forestry bureau forest biomass was estimated. In this research, based on maoershan farm region, first the single tree biomass equation of main tree species was established or collected. The biomass of each specie was calculated according to the materials of tally, such as height, diameter and so on in the forest inventory data. Secondly, each specie’s biomass and total biomass in subcompartment were calculated according to the tree species composition in forest management investigation data. Thus the forest biomass spatial distribution was obtained by taking subcompartment as a unit. And last the forest total biomass was estimated.

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