利用试差法确定林业抽样调查中的样本容量

本文针对正态总体的情形,讨论了如何利用试差法确定样本容量,即利用 n=1+s~2/(Δ (?)~2)·t~2_(n-1)(a) 式反复迭代,直到求出的n值差异很小为止,这时的n值即为所求的样本容量。文中并给出了试差法在林业中的应用实例。     

室内空气中甲醛采样检测研究

以江苏省南京市某办公室为研究对象,研究了采样环境温湿度、采样点位和采样时间对室内甲醛浓度检测结果的影响。研究结果表明,环境温湿度对室内甲醛含量有明显影响;室内甲醛浓度存在不均匀性,污染源周围的甲醛浓度最高;无太阳直射情况下,采样点宜选择门口位置,有太阳直射情况下,采样点宜选择污染源附近。     

云杉树叶象幼虫空间分布型及其抽样技术研究

为调查云杉树叶象幼虫在云杉S2-2、S2-3、S2-4苗龄型苗木上空间分布型及开展抽样技术调查研究,在云杉苗木中共设置了30块样地对该幼虫进行了调查。通过应用数理统计方法分析后得出:该幼虫有虫株率分布在云杉S2-2苗龄型苗木上呈对数函数分布趋势;在云杉S2-3、S2-4苗龄型苗木上呈指数函数分布趋势。应用聚集指标法分析得出:该幼虫空间分布型属聚集分布,并通过Iwao回归分析法和Toylor幂法则分析得出,云杉S2-2、S2-3苗龄型苗木上的幼虫个体间相互排斥;云杉S2-4苗龄型苗木上的幼虫个体间相互吸引。同时,应用Iwao的m*-m关系和序贯抽样方法,确定出了该幼虫的理论抽样数及抽样上限值和下限值。     

兼顾面积属性与不确定性信息的样本点权重调整方法

样本点权重调整是遥感分类精度评价中样本点空间分配的关键环节。以北京市顺义区精度评价样本点为例,提出了一种兼顾面积属性与不确定性信息的样本点权重调整方法——模糊调整权重法,用于布设精度评价样本点。首先,构建用于表达不确定性信息的模糊中和指数及其权重,融合模糊中和指数权重和面积权重构建模糊调整权重,并计算各个分层的模糊调整权重结果,完成样本点特征空间分配;其次,设置不同梯度样本点集,结合平均最短距离最小化准则和空间模拟退火算法实现样本点地理空间优化布设;最后,构建权重调整效果评价指标,进行模糊调整权重效果评价,并与其他权重调整方法和未进行权重调整的布点方法进行对比分析。结果表明：顺义区不确定性大、中、小的层模糊调整权重分别为0.45、0.37、0.18,与面积权重相比,不确定性大的层权重显著增加、中层权重稍微增加、小层权重明显降低;5个不同数据集样本点权重调整的精度评价总体精度、相对精度、均方根误差和标准偏差结果分别为69.90%～73.48%、96.28%～99.82%、0.01和0.01;模糊调整权重布点方法评价效果优于面积权重、模糊中和指数权重、不确定性空间分层权重布点方法,以及空间...     

N tracing models with a Monte Carlo optimization procedure provide new insights on gross N transformations in soils

¹⁵N tracing studies in combination with analyses via process-based models are the current “state-of-the-art” technique to quantify gross nitrogen (N) transformation rates in soils. A crucial component of this technique is the optimization algorithm which primarily decides how many model parameters can simultaneously be estimated. Recently, we published a Markov chain Monte Carlo (MCMC) method which has the potential to simultaneously estimate large number of parameters in ¹⁵N tracing models [Müller et al., 2007. Estimation of parameters in complex ¹⁵N tracing models by Monte Carlo sampling. Soil Biology & Biochemistry 39, 715-726].Here, we present the results of a reanalysis of datasets by Kirkham and Bartholomew [1954. Equations for following nutrient transformations in soil, utilizing tracer data. Soil Science Society of America Proceedings 18, 33-34], Myrold and Tiedje [1986. Simultaneous estimation of several nitrogen cycle rates using ¹⁵N: theory and application. Soil Biology & Biochemistry 18, 559-568] and Watson et al. [2000. Overestimation of gross N transformation rates in grassland soils due to non-uniform exploitation of applied and native pools. Soil Biology & Biochemistry 32, 2019-2030] using the MCMC technique. Analytical solutions such as the ones derived by Kirkham and Bartholomew [1954. Equations for following nutrient transformations in soil, utilizing tracer data. Soil Science Society of America Proceedings 18, 33-34] result in gross rates without uncertainties. We show that the analysis of the same data sets with the MCMC method provides standard deviations for gross N transformations. The standard deviations are further reduced if realistic data uncertainties are considered. Reanalyzing data by Myrold and Tiedje [1986. Simultaneous estimation of several nitrogen cycle rates using ¹⁵N: theory and application. Soil Biology & Biochemistry 18, 559-568] (Capac soil) resulted in a model fit similar to the one of the original analysis but with more precise estimates of gross N transformations. In addition, our analysis showed that small N transformations such as heterotrophic nitrification, which was neglected in the original analysis, could be quantified for this soil. Watson et al. [2000. Overestimation of gross N transformation rates in grassland soils due to non-uniform exploitation of applied and native pools. Soil Biology & Biochemistry 32, 2019-2030] provided evidence of a non-uniform exploitation of applied and native N that led to an overestimation of gross N transformations. Reanalyzing the data (CENIT soil, low N application) with the Müller et al. [2007. Estimation of parameters in complex ¹⁵N tracing models by Monte Carlo sampling. Soil Biology & Biochemistry 39, 715-726] model where oxidation was set to Michaelis-Menten kinetics resulted in a satisfactory fit between modeled and observed data, indicating that the observed artifact by Watson et al. [2000. Overestimation of gross N transformation rates in grassland soils due to non-uniform exploitation of applied and native pools. Soil Biology & Biochemistry 32, 2019-2030] was mainly due to inappropriate kinetic settings. Our study shows that the combination of a MCMC method with ¹⁵N tracing models is able to consider more complex and possibly more realistic models and kinetic settings to estimate gross N transformation rates and thus overcomes restriction of previous ¹⁵N tracing techniques.     

Stocking effectiveness of hatchery-released kuruma prawns estimated by two-stage sampling of commercial catch in Ariake Sound, Japan

ABSTRACT:    To evaluate the stocking effectiveness of the kuruma prawn Penaeus japonicus , a two-stage sampling survey of Gensiki bottom-drift-netters was carried out in Ariake Sound, Saga Prefecture, Japan. A total of 471 000 hatchery-produced juveniles, marked by cutting off the right uropods, was released. Thirty-three fishing days were randomly drawn from four boats, which were selected from the 80 boats operating in the fishery. All prawns caught on the selected days were examined, and the hatchery-produced individuals were identified by their regenerated uropods. A telephone survey of all boats was also conducted, to determine the number of fishing days. A total of 286 marked prawns were caught on the survey days for the Saga area in Ariake Sound, from the last half of July to the first half of September 2002. The recapture rate and standard error were estimated at 0.76 ± 0.52%. Economic efficiency was estimated at 0.28 ± 0.02. Strategies for sampling schemes and stock recovery are also discussed.     

Investigating the Link between Particulate Exposure and Airway Inflammation in the Horse

Inhalant exposure to airborne irritants commonly encountered in horse stables is implicated in the pathogenesis of inflammatory airway disease (IAD) and recurrent airway obstruction (RAO), non‐infectious, inflammatory pulmonary disorders that impact the health and performance of horses across all equine disciplines. IAD and RAO have overlapping clinical, cytological, and functional manifestations of the pulmonary response to organic dust and noxious gases encountered in the barn environment. Study of these diseases has provided important but incomplete understanding of the effect of air quality upon the respiratory health of horses. In this review, the principles of particulate exposure assessment, including health‐related aerosol size fractions and size‐selective sampling, the factors influencing air quality in equine environments, and the effect of air quality on the equine respiratory tract are discussed. The objective of this review is to provide the reader with a summary of the most common chronic inflammatory airway diseases in the horse and the principles of air sampling that are essential to the planning, interpretation, and assessment of equine respiratory health‐related exposure studies.     

Efficiency of presence-absence sampling used to estimate the mean abundance of fish eggs

ABSTRACT:   Statistical properties of estimators relating to the mean abundance of fish eggs were investigated using the data from the presence-absence sampling (PAS) and counting sampling (CS). PAS, which focuses on the presence-absence of eggs in a sample, is more cost-effective yet is unlikely to give more precise estimates than CS, which counts the number of eggs. But when limitations are given on the sampling cost and number of sampling stations, PAS may have advantages. This study shows that the mean square error (MSE) of the maximum likelihood estimator (MLE) based on PAS may become smaller than the MSE of the MLE based on counting data when the number of observations for PAS becomes larger. The observation number for PAS is determined, which minimizes the MSE of a combined estimator from the two MLE under a restriction of the total cost of observation. A dual problem is also solved. It is shown that MSE of the MLE in PAS is a monotone increasing function of the oversight probability. PAS becomes more informative as the distribution of the number of eggs is more aggregated.     

Sampling error resulting from depth-dependent plankton distributions and current differentials in a two-layered system

We evaluate a source of error observed in standard ichthyoplankton bongo tows in which volumes of water filtered did not result in increased catches of red-fish. Our analyses demonstrate that, under conditions where redfish larvae are distributed in surface waters in a two-layered system, current differentials between surface and subsurface layers resulted in biased, standardized estimates of larval abundances as a result of filtering varying amounts of subsurface waters. Analysis of standard survey results on Flemish Cap demonstrated that this source of bias was limited to the May-June period, after waters became stratified and before redfish passed from the larvae to pelagic juvenile stage. Correcting for this source of sampling bias wIII result in more accurate absolute estimates of ichthyoplankton abundance, and we estimate that variation (CV) for replicate samples may be reduced by 10%.     

Remedies for pseudoreplication

Pseudoreplication is the failure of a statistical analysis to properly incorporate the true structure of randomness present in the data. It has been well documented and studied in the ecological literature but has received little attention in the fisheries literature. Avoiding pseudoreplication in analyses of fisheries data can be difficult due to the complexity of the statistical procedures required. However, recent developments in statistical methodology are decreasing the extent to which pseudoreplication has to be tolerated. Seven examples are given here, beginning with simple design-based remedies and progressing to more challenging examples including the model-based remedies of mixed-effects modelling, generalized linear mixed models, state-space models, and geostatistics.