Using soil survey data for series-level environmental phosphorus risk assessment

2014 ◽  
Vol 72 (7) ◽  
pp. 2345-2356 ◽  
Author(s):  
Bharpoor S. Sekhon ◽  
Devinder K. Bhumbla ◽  
John Sencindiver ◽  
Louis M. McDonald
1985 ◽  
Vol 49 (5) ◽  
pp. 1238-1244 ◽  
Author(s):  
J. H. M. Wösten ◽  
J. Bouma ◽  
G. H. Stoffelsen

2002 ◽  
Vol 11 (4) ◽  
pp. 381-390
Author(s):  
A. TALKKARI ◽  
L. JAUHIAINEN ◽  
M. YLI-HALLA

In precision farming fields may be divided into management zones according to the spatial variation in soil properties. Clay content is an important soil characteristic, because it is associated with other soil properties that are important in management. Soil survey data from 150 sampling sites taken from an area of 218 ha were used to predict the spatial variation of clay percentage geostatistically in an agricultural soil in Jokioinen, Finland. The exponential and spherical models with a nugget component were fitted to the experimental variogram. This indicated that the medium-range pattern could be modelled, but the short-range variation could not, due to sparsity of sample points at short distances. The effect of sampling density on the kriging error was evaluated using the random simulation method. Kriging with a spherical model produced a map with smooth variation in clay percentage. The standard error of kriging estimates decreased only slightly when the density of samples was increased. The predictions were divided into three classes based on the clay percentage. Areas with clay content below 30%, between 30% and 60% and over 60% belong to non-clay, clay and heavy clay zones, respectively. With additional information from the soil samples on the contents of nutrients and organic matter these areas can serve as agricultural management zones.;


PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249937
Author(s):  
Danielle M. McLaughlin ◽  
Jack Mewhirter ◽  
Rebecca Sanders

We use survey data collected from 12,037 US respondents to examine the extent to which the American public believes that political motives drive the manner in which scientific research is conducted and assess the impact that such beliefs have on COVID-19 risk assessments. We find that this is a commonly held belief and that it is negatively associated with risk assessments. Public distrust in scientists could complicate efforts to combat COVID-19, given that risk assessments are strongly associated with one’s propensity to adopt preventative health measures.


2011 ◽  
Vol 50 (No. 8) ◽  
pp. 352-357 ◽  
Author(s):  
V. Penížek ◽  
L. Borůvka

The aim of this study is to find a suitable treatment of conventional soil survey data for geostatistical exploitation. Different aims and methods of a conventional soil survey and the geostatistics can cause some problems. The spatial variability of clay content and pH for an area of 543 km<sup>2</sup> was described by variograms. First the original untreated data were used. Then the original data were treated to overcome the problems that arise from different aims of conventional soil survey and geostatistical approaches. Variograms calculated from the original data, both for clay content and pH, showed a big portion of nugget variability caused by a few extreme values. Simple exclusion of data representing some specific soil units (local extremes, non-zonal soils) did not bring almost any improvement. Exclusion of outlying values from the first three lag classes that were the most influenced due to a relatively big portion of these extreme values provided much better results. The nugget decreased from pure nugget to 50% of the sill variability for clay content and from 81 to 23% for pH.


2020 ◽  
Vol 8 (1) ◽  
pp. e001569
Author(s):  
Yanyun Li ◽  
Huiru Jiang ◽  
Minna Cheng ◽  
Weiyuan Yao ◽  
Hua Zhang ◽  
...  

IntroductionTo compare the performance and the costs of various assumed screening strategies for type 2 diabetes mellitus (T2DM) among Chinese adults, and identify an optimal one for the population.Research design and methodsTwo multistage-sampling surveys were conducted in Shanghai, China, in 2009 and 2017. All participants were interviewed, had anthropometry, measured fasting plasma glucose (FPG), hemoglobin A1c (A1c) and/or postprandial glucose. The 1999 WHO diagnostic criteria was used to identify undiagnosed T2DM. A previously developed Chinese risk assessment system and a specific risk assessment system developed in this study were applied to calculate diabetes risk score (DRS) 1 and 2. Optimal screening strategies were selected based on the sensitivity, Youden index and the costs using the 2009 survey data as the training set and the 2017 survey data as the validation set. A twofold cross-validation was also performed.ResultsOf numerous assumed strategies, FPG ≥5.6 mmol/L alone performed well (Youden index of 71.8%) and cost least (US$18.4 for each case detected), followed by the strategy of DRS2 ≥8 combining with FPG ≥5.6 mmol/L (Youden index of 71.7% and US$20.2 per case detected) and the strategy of DRS1 ≥17 combining with FPG ≥5.6 mmol/L (Youden index of 72.0% and US$21.6 per case detected). However, FPG alone resulted in more subjects requiring oral glucose tolerance test (OGTT) than did combining with DRS. The strategy of FPG ≥5.6 mmol/L combining with A1c ≥4.7% achieved a Youden index of 72.1%, but had a cost as high as US$48.8 for each case identified. Twofold cross-validation also supported the use of FPG alone, but with an optimal cut-off of 6.1 mmol/L.ConclusionsOur results support the use of FPG alone in T2DM screening in Chinese adults. DRS may be used combining with FPG in populations with available electronic health records to reduce the number of OGTT and save costs of screening.


1973 ◽  
Vol 53 (4) ◽  
pp. 435-443
Author(s):  
B. KLOOSTERMAN ◽  
L. M. LAVKULICH

The British Columbia Soil Survey Data File was used to numerically classify soils of the Lower Fraser Valley of British Columbia. The data employed in the numerical-classification procedure were routine soil survey data and this classification was compared with the Canadian Soil Classification System. Three types of soil-profile data sets were used: average surface slice, selected average profile, and average profile. Methods of statistical analysis were cluster analysis and hierarchial grouping analysis. No marked differences in grouping resulted by the two methods of analyses. The average profile method seemed to give better correspondence with the Canadian System of Soil Classification. Consideration of surface layers alone did not correspond with the Canadian Soil Classification. The hierarchical grouping scheme resulted in better defined groups than the cluster analysis approach.


1978 ◽  
Vol 14 (1) ◽  
pp. 41-43
Author(s):  
P. J. Cole ◽  
K. A. Watson
Keyword(s):  

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