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Hadia OM Khair Ibrahim A Adam Shakir B Bushara Kamal H Eltom Nasreen O Musa Imadeldin E Aradaib 《Irish veterinary journal》2014,67(1):4
Background
Bluetongue virus (BTV) is an insect-transmitted virus, which causes bluetongue disease (BT) in sheep and a fatal hemorrhagic infection in North American white-tailed deer. However, in cattle the disease is typically asymptomatic and no overt clinical signs of disease appear to be associated with BTV infection. Serological evidence and isolation of different BTV serotypes have been reported in Sudan, however, no information is currently available in regard to previous exposure of Sudanese livestock to BTV infection in East Darfur State, Sudan.Aims
To determine the prevalence of BTV antibodies and to identify the potential risk factors associated with BTV infection among cattle in East Darfur State, Sudan.Methods
A total of 224 blood samples were collected randomly from five localities in East Darfur State, Sudan. The serum samples were screened for detection of BTV-specific immunoglobulin G (IgG) antibodies using a competitive enzyme-linked immunosorbent assay (c-ELISA).Results
Serological evidence of BTV infection was observed in 150 out of 224 animals accounting for a 67% prevalence rate among cattle in East Darfur State. Older cattle (>2 years of age) were six times more likely to be infected with BTV (OR = 6.62, CI = 2.87-15.26, p-value = 0.01). Regarding animal source (contact with other herds) as a risk factor, it was shown that cattle purchased from market or introduced from other herds were 3 times at higher risk of being infected with BTV (OR = 3.87, CI = 1.07-13.87, p value = 0.03). Exposure of cattle to the insect vector increased the risk of contracting BTV infection by six times compared to non-exposed cattle (OR = 6.44, CI = 1.53-27.08, p value = 0.01).Conclusion
The present study indicated that age, animal source and the intensity of the insect vector are influential risk factors for BTV infection in cattle in the Darfur region. Surveillance for BTV infection should be extended to include other susceptible ruminants and to study the distribution of the insect vectors to better predict and respond to a possible BTV outbreak in the State of East Darfur, Sudan. 相似文献3.
Steen Magnussen Michael Köhl Konstantin Olschofsky 《European Journal of Forest Research》2014,133(6):1137-1155
According to the United Nations International Panel on Climate Change good practice guidance, an annual forest biomass carbon balance (AFCB) can be estimated by either the stock-difference (SD) or the gain–loss (GL) method. An AFCB should be accompanied by an analysis and estimation of uncertainty (EU). EUs are to be practicable and supported by sound statistical methods. Sampling and model errors both contribute to an EU. As sample size increases, the sampling error decreases but not the error due to errors in model parameters. Uncertainty in GL AFCB estimates is dominated by model-parameter errors. This study details the delta technique for obtaining an EU with the SD and the GL method applicable to the carbon in aboveground forest biomass. We employ a Brownian bridge process to annualize the uncertainty in SD AFCBs. A blend of actual and simulated data from three successive inventories are used to demonstrate the application of the delta technique to SD- and GL-derived AFCBs during the years covered by the three inventories (SD) and rescaled national wood volume harvest statistics (GL). Examples are limited to carbon in live trees with a stem diameter of 7 cm or greater. We confirm that a large contribution to the uncertainty in an AFCB comes from models used to estimate biomass. Application of the delta technique to summary statistics can significantly underestimate uncertainty as some sources of uncertainty cannot be quantified from the available information. We discuss limitations and problems with the Monte Carlo technique for quantifying uncertainty in an AFCB. 相似文献
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A new composite k-tree estimator of stem density 总被引：1，自引：1，他引：0
Steen Magnussen 《European Journal of Forest Research》2012,131(5):1513-1527
This study presents a generally applicable and robust k-tree composite estimator of density. We propose to estimate stem density by a weighted average $ \left( {\hat{\lambda }_{\text{aic}} } \right) $ of 16 individual density estimators. The weights given to individual estimators are inversely proportional to the relative fit (Akaike’s corrected information criterion) of each estimator to the assumed distribution of observed k-tree distances. The performance of the proposed estimator is evaluated in simulated simple random sampling with k?=?3 and 6 in 58 forest stands (54 actual and 4 simulated) and 600 replications. Sample sizes were 15 and 30 locations per stand. Eleven estimators were novel, including three designed for regular spatial patterns. Absolute stand-level bias with k?=?6 varied from 0.1 to 8.1% (mean 1.8%), and a bias larger than 6% was limited to 3 stands with either pronounced density gradients or a strong clustering of stem locations. Root mean squared errors were approximately 16% (k?=?6 and n?=?15) versus 12% for sampling with comparable fixed-area plots. Coverage of computed 95% confidence intervals ranged from 0.72 to 0.99 (median?=?0.98 with n?=?15 and 0.95 with n?=?30), with 98% of all intervals achieving a coverage of 0.85 or better. In seven stands used in an assessment of a novel spatial point pattern reconstruction k-tree density estimator (RDE) by Nothdurft et al. (Can J For Res 40:953–967, 2010), the average absolute bias of $ \hat{\lambda }_{\text{aic}} $ with k?=?6 was 1.5 versus 0.7% for $ \hat{\lambda }_{\text{RDE}} $ . 相似文献
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Seven variance estimators to be used under systematic sampling are evaluated in a simulation study with 270 artificial spatial populations with different levels and structure of autocorrelation. In settings without an auxiliary variable a proposed new spatial resampling estimator RHO is recommended. In setting with an auxiliary variable, an estimator based on post-stratification (PST), and one with a correction for spatial autocorrelation (DOR), generated estimates with less bias than the SRS estimator in the majority of studied settings. Only in populations with either a near zero autocorrelation at the interval of sampling, or a very strong correlation between the target and the auxiliary variable did the otherwise conservative SRS estimator perform as well as the alternatives. 相似文献
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Survey of Victorian small ruminant herds for mycoplasmas associated with contagious agalactia and molecular characterisation of Mycoplasma mycoides subspecies capri isolates from one herd 
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下载免费PDF全文 OM Olaogun A Kanci SR Barber KA Tivendale PF Markham MS Marenda GF Browning 《Australian veterinary journal》2017,95(10):392-400
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Steen Magnussen Lutz Fehrman William J. Platt 《European Journal of Forest Research》2012,131(2):307-320
Density estimators for k-tree distance sampling are sensitive to the amount of extra Poisson variance in distances to the kth tree. To lessen this sensitivity, we propose an adaptive composite estimator (COM). In simulated sampling from 16 test
populations, a three-component composite density estimator (COM)–with weights determined by a multinomial logistic function
of four readily available ancillary variables–was identified as superior in terms of average relative absolute bias. Results
from a different set of nine validation populations–with widely different stem densities and spatial patterns of tree locations—confirmed
that relative root mean squared errors (RRMSE) of COM were, on average, considerably lower than those obtained with the three-component
k-tree density estimators. The RRMSE performance of COM improved with increasing values of k. With k = 6 and sample sizes of 10, 20, and 30, the average relative bias of COM was between −5 and 5% in seven validation populations
but in an open low-density savanna-like population bias reached −12% (1979 data) and 7% (1996 data). For k = 6 and n = 10, the RRMSE of COM was, in six of the nine validation populations, within 3.3 percentage points of the RRMSE for sampling
with fixed-area plots. Jackknife estimates of the precision of COM estimates of density were negatively biased, leading to
under-coverage (7%) of computed 95% confidence intervals. 相似文献
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Anders B. Magnussen Albert K. Imsland Atle Foss 《Journal of the World Aquaculture Society》2008,39(6):804-811
The aim of this study was to investigate the effects of different salinities and temperatures and their possible interactive effect on growth performance, feeding parameters, and blood physiology in juvenile spotted wolffish, Anarhichas minor, reared at different temperature (7 and 10 C) and salinity (15, 25, and 34‰) combinations. There was a significant interactive effect between temperature and salinity on growth, as a growth‐enhancing effect was seen at intermediate and full salinities at higher temperature, whereas the reciprocal trend was seen at lower temperature. Mean total feed consumption, daily feeding rate, and feed conversion efficiency were all highest at the intermediate salinity at 10 C, whereas at 7 C, the feeding parameters were highest at low and intermediate salinities. Blood plasma sodium content was lowest at 15‰, whereas the opposite trend was seen in partial pressure of CO2 and bicarbonate in blood where the highest concentrations were seen at 15‰. This study demonstrates that spotted wolffish has a high osmoregulatory and acclimatory capacity. In an aquaculture context, growth of juvenile spotted wolffish can be improved by rearing the species at high temperature and intermediate salinity combinations at least in a limited period of the juvenile phase. 相似文献