基于区域剖分算法的土壤碳通量空间采样策略

由于土壤碳通量在空间分布上具有很强的异质性,传统的采样方法难以对区域土壤碳通量进行精确估算,因此确定适当的采样策略对区域土壤碳通量的估算具有重要意义.本文提出一种逐点递增式采样的区域剖分部署策略(RDPG):设定初始采样点,使用改进的凸包插值算法构造Delaunay三角网,根据邻近已知采样点插值计算三角形各边垂直平分线的交点的离散度,选择离散度最大的点作为新增采样点.采用该方法对变异系数为0.42～0.59的仿真试验区域进行多次试验,结果表明:在相同试验条件下,RDPG布局策略能够获得比随机采样和均匀采样策略更高的区域土壤碳通量估算准确度.RDPG方法考虑了区域土壤碳通量的空间异质性,提高了区域土壤碳通量拟合精度.     

An under-appreciated difficulty: sampling of plant populations for analysis using molecular markers

Results of studies using molecular markers for determining demographic and genetical population parameters especially in plants or sessile animals under field conditions are strongly dependent on the sampling strategy adopted. There are two critical decisions to make when determining this strategy: (i) what is the unit to be sampled?, (ii) how should units to be sampled in the field be selected? For the first decision, there are two conceptually different approaches: sampling ramets of clonal plants as units (to get information about within-genet parameters, such as genet sizes or numbers) and sampling genets of clonal or non-clonal plants as units (to get information of the genetic structure of the population). For the second decision, it is critically important to make the goal of the study explicit. We argue that in this case fully random sampling is needed only when an estimate of the true value of the population parameter is needed; if a comparison between populations is the goal, however, other sampling schemes may be adopted. The efficiency of different types of sampling strategies to recover relative values in a spatially extended population is studied by means of a spatially explicit simulation model. The results show that a regular pattern of sampling is best for obtaining information on genet sizes or inbreeding coefficients; in contrast, random or hierarchical sampling strategies are better for obtaining information on parameters that are based on comparison of pairs of individuals, such as distribution of genet sizes or autocorrelation in genetic structure. A set of recommendations is provided for designing a good sampling strategy.     

非损伤性取样研究进展

非损伤性取样即在不捕获、触及,甚至是未亲眼见到动物的情况下,收集不同形式的样品获取样品中的DNA。通过介绍各种类型非损伤性取样的研究进展,就该取样存在的问题及现有解决方法进行讨论,并在此基础上对非损伤性取样的研究和应用前景进行了分析,以期对进一步研究提供有价值的参考。     

基于湿度分布特征的小尺度土壤碳通量空间采样策略

由于土壤碳通量的空间异质性很强,传统的随机抽样方法无法对区域土壤碳通量进行准确估算,而多点采样需耗费大量的人力及设备成本,因此确定适当的采样点数量及分布策略对于区域土壤碳通量的测算非常重要。提出一种基于湿度空间分布特征的小尺度土壤碳通量空间采样策略:首先利用无线传感网密集测量区域的土壤湿度,根据湿度数据的空间分布特征划分监测区域,通过Hammond Mc Cullagh方程计算各子区域内的最优采样点数量,最终确定整个监测区域的空间采样点部署策略。提出的方法考虑了各子区域间土壤碳通量空间分布的差异,使得采样点的部署位置与土壤碳通量的分布具有较好的相关性。研究结果证明:土壤碳通量部署策略能够获得比均匀部署策略、随机部署策略更高的区域土壤碳通量估算准确度。     

On the Use of Jack‐Knife Techniques in Systematic Sampling

We have proposed two general classes of ratio and product type estimators to estimate an unknown population parameter of a response variable y under systematic sampling strategy. Jack‐Knife technique is employed to make the classes almost/exactly unbiased and sampling variance of the proposed estimators are derived to the first order of approximation. The merits of the proposed estimators over other estimators are discussed in this paper.     

遗传多样性的取样策略

合理取样是生物多样性有效保护、利用和研究所面临的最基本问题 ,它在很大程度上受到植物自身的生物学特性、环境条件和取样目的的影响。遗传多样性的取样策略是指对一定地理分布范围内的生物个体取样时 ,使样本具有代表性和包含尽可能多的遗传变异的最佳取样方法 ,包括了取样数目 (一个给定区域的居群数和一个居群的个体数 )以及取样方式。包括“哈迪 温伯格平衡 (Hardy WeinbergEquilibrium)”定律在内的居群遗传学基本原理是研究取样策略的理论基础 ,在此基础上可以对居群内的取样个体数及应获取的居群数进行理论计算 ,同时还可以根据物种居群的遗传结构特点和环境条件的异质性来决定取样的方式。因此 ,应该依据研究对象本身的特点和取样的目的来确定某一特定区域的居群取样数 ,以及某一居群内的样本数及取样方式。     

中华通草蛉卵、幼虫和成虫在麦田分布型的研究

研究了中华通草蛉卵、幼虫和成虫在麦田的分布型,均属聚集分布,分析提出适宜的取样调查方法,即双对象线或棋盘式10点,每点调查1m^2麦株。     

Should we use proportional sampling for species–area studies?

Aim In this paper we aim to show that proportional sampling can detect species–area relationships (SARs) more effectively than uniform sampling. We tested the contribution of alpha and beta diversity in ant communities as explanations for the SAR. Location Tropical forest remnants in Viçosa, Minas Gerais, Brazil (20 °45′ S, 42 °50′ W). Methods We sampled 17 forest remnants with proportional sampling. To disentangle sampling effects from other mechanisms, species richness was fitted in a model with remnant size, number of samples (sampling effects) and an interaction term. Results A SAR was observed independent of the number of samples, discarding sampling effects. Alpha diversity was not influenced by remnant size, and beta diversity increased with remnant size; evidence to the fact that habitat diversity within remnants could be the dominant cause of the SAR. Such a relationship between beta diversity and remnant area may have also arisen due to the combined effects of territoriality and aggregation of ant species. Main conclusions The proposed model, together with proportional sampling, allowed the distinction between sampling effects and other mechanisms.     

Optimal sampling and estimation strategies under the linear model

In some cases model-based and model-assisted inferences canlead to very different estimators. These two paradigms are notso different if we search for an optimal strategy rather thanjust an optimal estimator, a strategy being a pair composedof a sampling design and an estimator. We show that, under alinear model, the optimal model-assisted strategy consists ofa balanced sampling design with inclusion probabilities thatare proportional to the standard deviations of the errors ofthe model and the Horvitz–Thompson estimator. If the heteroscedasticityof the model is 'fully explainable’ by the auxiliary variables,then this strategy is also optimal in a model-based sense. Moreover,under balanced sampling and with inclusion probabilities thatare proportional to the standard deviation of the model, thebest linear unbiased estimator and the Horvitz–Thompsonestimator are equal. Finally, it is possible to construct asingle estimator for both the design and model variance. Theinference can thus be valid under the sampling design and underthe model.     

利用ISSR分子标记构建濒危植物水青树核心种质

基于全国26个居群的174份水青树Tetracentron sinense种质,利用14条ISSR引物,采用UPGMA聚类法进行多次逐步聚类,利用三种取样策略(随机取样策略、位点优先取样策略和偏离度取样策略)构建初始核心种质,并将各遗传多样性指标进行比较分析,从而确定构建水青树核心种质的最佳方法。利用14条ISSR引物扩增出180个条带,其观测等位基因数(Na)、有效等位基因数(Ne)、Nei’s基因多样性指数(H)与Shannon信息指数(I)分别为1.6944、1.3912、0.2321和0.3509,说明水青树具有较低的遗传多样性。采用位点优先取样策略构建的核心种质各遗传多样性指数均大于随机取样策略和偏离度取样策略。利用位点优先取样策略构建了78 份核心种质资源,保留了44.83%原种质样品,遗传多样性指数Na、Ne、H和I的保留率分别为98.69%、100.01%、99.27%和98.67%,比较完好地保留了原种质的遗传多样性和遗传变异。因此,位点优先取样策略是构建水青树核心种质的最佳取样策略。     

Estimation of Prevalence and Relative Risk in Repetitive Surveys

The Theory of double sampling as proposed by Neyman (1938) and subsequently used for successive sampling by Jesson (1942), Yates (1960), Patterson (1950), Eckler (1955), Kuldroff (1963) and Tikkiwal (1960, 1967) has been explored to develop a general estimator which can be used for estimation of parameters such as mean, ratio or double ratio. A simple case of sampling on two occasions has only been considered but the logic can easily be extended for more than two occasions. The results show that the generalised estimator will be very useful for the applied statisticians.     

Assessment of the efficiency of a hand-held suction device for sampling spiders: improved density estimation or oversampling?

In the study a comparison is made between the results of two sampling procedures, both based on the application of the same hand-held suction apparatus. Sampling was aimed at spiders, and was carried out on two alfalfa fields. In the first method suction sampling was applied to an enclosure of 0.48 m². The enclosed area was sampled intensively, which was facilitated by the removal of the vegetation. The second method was a transect sampling procedure during which the suction apparatus with a 0.01 m² nozzle was applied to single unenclosed sampling points 1 m apart. A linear series of 48 such subsamples comprised a transect, thus the total area covered in a transect equalled the area of the enclosure. In the transect samples three times more spiders were caught than in the enclosures. This result was consistent on different occasions and at both fields. This basic trend was found in all spider families that were present in significant numbers in the samples. Species composition in the samples collected by the two methods was similar, and species abundance ranks were highly correlated across dates. We propose that an “edge effect” can explain higher catches in transect samples. This edge effect is caused by lateral suction at the edges, which inflated the number of animals caught in the transect application.     

Hidden population size estimation and diagnostics using two respondent-driven samples with applications in Armenia

Estimating the size of hidden populations is essential to understand the magnitude of social and healthcare needs, risk behaviors, and disease burden. However, due to the hidden nature of these populations, they are difficult to survey, and there are no gold standard size estimation methods. Many different methods and variations exist, and diagnostic tools are needed to help researchers assess method-specific assumptions as well as compare between methods. Further, because many necessary mathematical assumptions are unrealistic for real survey implementation, assessment of how robust methods are to deviations from the stated assumptions is essential. We describe diagnostics and assess the performance of a new population size estimation method, capture–recapture with successive sampling population size estimation (CR-SS-PSE), which we apply to data from 3 years of studies from three cities and three hidden populations in Armenia. CR-SS-PSE relies on data from two sequential respondent-driven sampling surveys and extends the successive sampling population size estimation (SS-PSE) framework by using the number of individuals in the overlap between the two surveys and a model for the successive sampling process to estimate population size. We demonstrate that CR-SS-PSE is more robust to violations of successive sampling assumptions than SS-PSE. Further, we compare the CR-SS-PSE estimates to population size estimations using other common methods, including unique object and service multipliers, wisdom of the crowd, and two-source capture–recapture to illustrate volatility across estimation methods.     

Modelling disease spread through random and regular contacts in clustered populations

An epidemic spreading through a network of regular, repeated, contacts behaves differently from one that is spread by random interactions: regular contacts serve to reduce the speed and eventual size of an epidemic. This paper uses a mathematical model to explore the difference between regular and random contacts, considering particularly the effect of clustering within the contact network. In a clustered population random contacts have a much greater impact, allowing infection to reach parts of the network that would otherwise be inaccessible. When all contacts are regular, clustering greatly reduces the spread of infection; this effect is negated by a small number of random contacts.     

Estimating Propensity Scores and Causal Survival Functions Using Prevalent Survival Data

Summary This article develops semiparametric approaches for estimation of propensity scores and causal survival functions from prevalent survival data. The analytical problem arises when the prevalent sampling is adopted for collecting failure times and, as a result, the covariates are incompletely observed due to their association with failure time. The proposed procedure for estimating propensity scores shares interesting features similar to the likelihood formulation in case‐control study, but in our case it requires additional consideration in the intercept term. The result shows that the corrected propensity scores in logistic regression setting can be obtained through standard estimation procedure with specific adjustments on the intercept term. For causal estimation, two different types of missing sources are encountered in our model: one can be explained by potential outcome framework; the other is caused by the prevalent sampling scheme. Statistical analysis without adjusting bias from both sources of missingness will lead to biased results in causal inference. The proposed methods were partly motivated by and applied to the Surveillance, Epidemiology, and End Results (SEER)‐Medicare linked data for women diagnosed with breast cancer.     

Evaluation of different observational sampling regimes for use in zoological parks

Observational sampling methods provide clearly-defined guidelines for collection and analysis of behavioral data. In some situations, use of formal sampling regimes may be impractical or impossible. A case in point is data collection conducted by animal care staff at zoological parks and aquaria. Often, time is sufficiently limited that data collection is perceived as a task that cannot be accomplished given the normal constraints of the day. Here, we explore the efficacy and validity of using more variable and abridged sampling regimes in an effort to identify the appropriateness of such observation schemes for systematic monitoring of behavior. We describe the results of studies on three species (two polar bears, an Atlantic bottlenose dolphin calf, and two brown bears), conducted over a period of several years at the Brookfield Zoo, Brookfield, Illinois, USA. Data collection schemes varied both within and across groups in order to provide a basis of comparison. In all cases, there were significant differences based on sampling regime for rare behaviors (those that individually comprised <15% of the activity budget), but not for common behaviors. Subsampling from larger data sets indicated that data reliability increases with increasing observation number. We discuss the strengths and weaknesses of such sporadic sampling methods, and suggest that, in many instances such limited data collection may yet yield an accurate picture of animal activity and should not be overlooked as a viable management tool.     

Locating hybrid individuals in the red wolf (Canis rufus) experimental population area using a spatially targeted sampling strategy and faecal DNA genotyping

Hybridization with coyotes (Canis latrans) continues to threaten the recovery of endangered red wolves (Canis rufus) in North Carolina and requires the development of new strategies to detect and remove coyotes and hybrids. Here, we combine a spatially targeted faecal collection strategy with a previously published reference genotype data filtering method and a genetic test for coyote ancestry to screen portions of the red wolf experimental population area for the presence of nonred wolf canids. We also test the accuracy of our maximum-likelihood assignment test for identifying hybrid individuals using eight microsatellite loci instead of the original 18 loci and compare its performance to the Bayesian approach implemented in newhybrids. We obtained faecal DNA genotypes for 89 samples, 73 of which were matched to 23 known individuals. The performance of two sampling strategies - comprehensive sweep and opportunistic spot-check was evaluated. The opportunistic spot-check sampling strategy required less effort than the comprehensive sweep sampling strategy but identified fewer individuals. Six hybrids or coyotes were detected and five of these individuals were subsequently captured and removed from the population. The accuracy and power of the genetic test for coyote ancestry is decreased when using eight loci; however, nonred wolf canids are identified with high frequency. This combination of molecular and traditional field-based approaches has great potential for addressing the challenge of hybridization in other species and ecosystems.     

Random median sampling to enhance the precision of population estimates

We describe the characteristics of a sampling procedure called random median sampling that was proposed to enhance the precision of population estimates. In performing random median sampling, we first select a sampling item at random from the sampling area. We roughly compare the abundance of individuals in the selected item with that of the adjacent two items in order to identify the item that has median abundance, i.e., the item that has the second largest abundance among the three items. We count the number of individuals of the item having the median abundance. This procedure is repeated n times in the sampling area (i = 1, 2, ..., n). Let m _i be the ith median abundance. The estimates of the mean abundance per sampling item and the variance of estimates are given by Σm _i /n and Σ(m _i –Σm _i /n)²/n(n – 1), respectively. This method is a local application of the median ranked set sampling that was proposed by Muttlak (J Appl Stat Sci 6:245–255, 1997). Random median sampling is effective when the correlation coefficient between adjacent items is small. If the correlation coefficient is close to zero, random median sampling reduces the variance of estimates to 45 or 32% of that in simple random sampling when the distribution follows a normal distribution or a Laplace distribution, respectively. The sample size required to achieve a given precision of estimate decreases accordingly. The effectiveness of random median sampling, however, is small if the correlation coefficient is large. The condition in which random median sampling is superior to simple random sampling is also discussed.     

Transmission of Multidrug-Resistant and Drug-Susceptible Tuberculosis within Households: A Prospective Cohort Study

Background

The “fitness” of an infectious pathogen is defined as the ability of the pathogen to survive, reproduce, be transmitted, and cause disease. The fitness of multidrug-resistant tuberculosis (MDRTB) relative to drug-susceptible tuberculosis is cited as one of the most important determinants of MDRTB spread and epidemic size. To estimate the relative fitness of drug-resistant tuberculosis cases, we compared the incidence of tuberculosis disease among the household contacts of MDRTB index patients to that among the contacts of drug-susceptible index patients.

Methods and Findings

This 3-y (2010–2013) prospective cohort household follow-up study in South Lima and Callao, Peru, measured the incidence of tuberculosis disease among 1,055 household contacts of 213 MDRTB index cases and 2,362 household contacts of 487 drug-susceptible index cases.A total of 35/1,055 (3.3%) household contacts of 213 MDRTB index cases developed tuberculosis disease, while 114/2,362 (4.8%) household contacts of 487 drug-susceptible index patients developed tuberculosis disease. The total follow-up time for drug-susceptible tuberculosis contacts was 2,620 person-years, while the total follow-up time for MDRTB contacts was 1,425 person-years. Using multivariate Cox regression to adjust for confounding variables including contact HIV status, contact age, socio-economic status, and index case sputum smear grade, the hazard ratio for tuberculosis disease among MDRTB household contacts was found to be half that for drug-susceptible contacts (hazard ratio 0.56, 95% CI 0.34–0.90, p = 0.017). The inference of transmission in this study was limited by the lack of genotyping data for household contacts. Capturing incident disease only among household contacts may also limit the extrapolation of these findings to the community setting.

Conclusions

The low relative fitness of MDRTB estimated by this study improves the chances of controlling drug-resistant tuberculosis. However, fitter multidrug-resistant strains that emerge over time may make this increasingly difficult.     

刺槐叶瘿蚊越冬幼虫空间格局及抽样调查技术

本文采用聚集指标法分析了刺槐叶瘿蚊Obolodiplosis robiniae(Haldemann)越冬幼虫的空间分布格局,结果表明:刺槐叶瘿蚊越冬幼虫在林间呈聚集分布;其聚集的原因与刺槐叶瘿蚊自身的行为习性有关或由刺槐叶瘿蚊本身与环境的异质性共同作用所造成。采用"z"字型、平行线、棋盘式、大五点、对角线5种抽样方法估计林间刺槐叶瘿蚊越冬幼虫虫口密度,确定对角线法调查15样方为最佳抽样方法。对土壤不同深度土层中越冬幼虫数量调查,明确最适取样深度为3cm。同时利用Iwao回归建立了理论抽样数量模型:n=t2/D2(1.1957/x珋+0.8905)。利用过筛手检和过筛水漂2种方法检数土中幼虫,对检出刺槐叶瘿蚊越冬幼虫虫量及检虫时间进行了对比分析,结果表明过筛水漂法检虫较为可取。