油松毛虫(Dendrolimus labulaeformis)幼虫抽样技术的研究

本文在测定油松毛虫幼虫静态格局和动态格局的条件下,全面而系统地进行了株抽样、轮抽样和“枝”抽样的研究。根据幼虫在各轮垂直分布的特征和喜食二年生针叶的特性,建立回归模型,从轮抽样发展到“枝”抽样,通过检验,预报精度在91—98％之间。轮抽样比株抽样平均提高效率6倍,“枝”抽样比轮抽样又平均提高1.5倍。如费用以每株0.20元计,轮抽样比株抽样每株平均减少0.16元,“枝”抽样每株又减少0.032元。     

Ranked Set Sub Sampling the Non Response Strata for Estimating the Difference of Means

The existence of missing observations when the difference of means is estimated determines the need of sub sampling among the non respondents. Ranked set sampling is used for sub sampling. The information provided on one of the variables by the non respondents at the first attempt permits to rank them. The behavior of a ranked set sampling model with respect to other alternattives is studied in this paper. An unbiased estimator is derived and its expected variance is obtained. The proposed model is compared with the use of simple random sampling and Two‐phase sampling for stratification.     

Evaluating noninvasive genetic sampling techniques to estimate large carnivore abundance

Monitoring large carnivores is difficult because of intrinsically low densities and can be dangerous if physical capture is required. Noninvasive genetic sampling (NGS) is a safe and cost‐effective alternative to physical capture. We evaluated the utility of two NGS methods (scat detection dogs and hair sampling) to obtain genetic samples for abundance estimation of coyotes, black bears and Canada lynx in three areas of Newfoundland, Canada. We calculated abundance estimates using program capwire , compared sampling costs, and the cost/sample for each method relative to species and study site, and performed simulations to determine the sampling intensity necessary to achieve abundance estimates with coefficients of variation (CV) of <10%. Scat sampling was effective for both coyotes and bears and hair snags effectively sampled bears in two of three study sites. Rub pads were ineffective in sampling coyotes and lynx. The precision of abundance estimates was dependent upon the number of captures/individual. Our simulations suggested that ~3.4 captures/individual will result in a < 10% CV for abundance estimates when populations are small (23–39), but fewer captures/individual may be sufficient for larger populations. We found scat sampling was more cost‐effective for sampling multiple species, but suggest that hair sampling may be less expensive at study sites with limited road access for bears. Given the dependence of sampling scheme on species and study site, the optimal sampling scheme is likely to be study‐specific warranting pilot studies in most circumstances.     

A photographic method and a ranking procedure for estimating numbers of the rose aphid,Macrosiphum rosae (L.), on rose buds

Two sampling methods for aphids are described. The first is a photographic method that allows sampling with replacement for use in field experiments and in which a linear regression technique is used to estimate the errors of sampling. The second method is a ranking procedure for sampling natural populations in which regressions of aphid numbers on ‘colony length’ are used to minimize bias.     

Sparse sampling of water density fluctuations near liquid-vapor coexistence

Abstract

The free energetics of water density fluctuations in bulk water, at interfaces, and in hydrophobic confinement inform the hydration of hydrophobic solutes as well as their interactions and assembly. The characterisation of such free energetics is typically performed using enhanced sampling techniques such as umbrella sampling. In umbrella sampling, order parameter distributions obtained from adjacent biased simulations must overlap in order to estimate free energy differences between biased ensembles. Many biased simulations are typically required to ensure such overlap, which exacts a steep computational cost. We recently introduced a sparse sampling method, which circumvents the overlap requirement by using thermodynamic integration to estimate free energy differences between biased ensembles. Here we build upon and generalise sparse sampling for characterising the free energetics of water density fluctuations in systems near liquid-vapor coexistence. We also introduce sensible heuristics for choosing the biasing potential parameters and strategies for adaptively refining them, which facilitate the estimation of such free energetics accurately and efficiently. We illustrate the method by characterising the free energetics of cavitation in a large volume in bulk water. We also use sparse sampling to characterise the free energetics of capillary evaporation for water confined between two hydrophobic plates. In both cases, sparse sampling is nearly two orders of magnitude faster than umbrella sampling. Given its efficiency, the sparse sampling method is particularly well suited for characterising free energy landscapes for systems wherein umbrella sampling is prohibitively expensive.     

Inexpensive Device for the Aerobic and Anaerobic Sampling of Microorganisms in Lake and Shallow Ocean Waters

An inexpensive device suitable for sampling microorganisms in water and easily constructed from readily available laboratory equipment is described. The need to transfer subsamples to culturing flasks after collection is eliminated by partly filling the sampling vessels with growth medium prior to sampling. The device is readily adapted for sampling different volumes, is simple and quick to operate, and is suitable for use with prereduced media. Contamination from layers other than that being sampled is insignificant.     

Sequential sampling protocols for Spodoptera frugiperda (Lepidoptera: Noctuidae), on Zea mays fields: influence of sampling unit size

Spodoptera frugiperda (J.E. Smith) is a major pest in maize fields in Argentina. However, a sampling method that accounts for spatial pattern and allows reliable pest density estimations is still lacking. This paper addresses the issue of how sampling unit size can influence the characterization of S. frugiperda spatial pattern and the performance of sampling plans. An intensive sampling programme for S. frugiperda larvae was carried out in maize fields from October until March in four growing seasons. On each sampling date, 12 to 20 sampling units were taken at random. Each unit consisted of 1, 2, 4, 6, 8, 10 or 12 consecutive plants along a row. The linearized version of the Taylor's power law (TPL) was fitted to mean and variance estimated for each sampling date and data set through least squares regression. In general, b values from TPL were significantly >1 (P<0.05), indicating an aggregated sampling distribution. Regression slopes (b) ranged from 1.28 to 1.48 in small larvae and from 1.06 to 1.24 in large larvae, indicating stronger clumping in the former. TPL parameters were used to develop constant precision sampling plans. The efficiency of these plans in terms of expected total cost (searching and handling sampling units) was very sensitive to the size of the sampling units with small larvae but not with large larvae. The influence of sampling unit size and spatial pattern on TPL parameters and sampling costs is discussed.     

Modification and Application of a Leaf Blower-vac for Field Sampling of Arthropods

Rice fields host a large diversity of arthropods, but investigating their population dynamics and interactions is challenging. Here we describe the modification and application of a leaf blower-vac for suction sampling of arthropod populations in rice. When used in combination with an enclosure, application of this sampling device provides absolute estimates of the populations of arthropods as numbers per standardized sampling area. The sampling efficiency depends critically on the sampling duration. In a mature rice crop, a two-minute sampling in an enclosure of 0.13 m² yields more than 90% of the arthropod population. The device also allows sampling of arthropods dwelling on the water surface or the soil in rice paddies, but it is not suitable for sampling fast flying insects, such as predatory Odonata or larger hymenopterous parasitoids. The modified blower-vac is simple to construct, and cheaper and easier to handle than traditional suction sampling devices, such as D-vac. The low cost makes the modified blower-vac also accessible to researchers in developing countries.     

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。     

Could ecologists be more random? Straightforward alternatives to haphazard spatial sampling

When conducting field studies, it is common for ecologists to choose the locations of sampling units arbitrarily at the time sampling occurs, rather than using a properly randomised sampling design. Unfortunately, this ‘haphazard’ sampling approach cannot provide formal statistical inference from the sample to the population without making untestable assumptions. Here, we argue that two recent technological developments remove the need for haphazard sampling in many situations. A general approach to simple randomised sampling designs is outlined, and some examples demonstrate that even complicated designs can be implemented easily using software that is widely used among ecologists. We consider that more rigorous, randomised sampling designs would strengthen the validity of the conclusions drawn from ecological studies, to the benefit of the discipline as a whole.     

Quantitative study on exact reconstruction sampling condition by verifying solution uniqueness in limited-view CT

In limited-view computed tomography reconstruction, iterative image reconstruction with sparsity-exploiting methods, such as total variation (TV) minimization, inspired by compressive sensing, potentially claims large reductions in sampling requirements. However, a quantitative notion of this claim is non-trivial because of the ill-defined reduction in sampling achieved by the sparsity-exploiting method. In this paper, exact reconstruction sampling condition for limited-view problem is studied by verifying the uniqueness of solution in TV minimization model. Uniqueness is tested by solving a convex optimization problem derived from the sufficient and necessary condition of solution uniqueness. Through this method, the sufficient sampling number of exact reconstruction is quantified for any fixed phantom and settled geometrical parameter in the limited-view problem. This paper provides a reference to quantify the sampling condition. Three phantoms are tested to study the sampling condition of limited view exact reconstruction in this paper. The experiment results show the quantified sampling number and indicate that an object would be accurately reconstructed as the scanning range becomes narrower by increasing sampling number. The increased samplings compensate for the deficiency of the projection angle. However, the lower bound of the scanning range corresponding to three different phantoms are presented, in which an exact reconstruction cannot be obtained once the projection angular is narrowed to this extent no matter how to increase sampling.     

Markov Systematic Sampling

In this paper, a new systematic sampling scheme with Markovian behaviour which yields positive first order inclusion probabilities for all units and positive second order inclusion probabilities for all pairs of units is introduced. The suggested method has been compared with sample random sampling, stratified random sampling, linear systematic sampling and systematic sampling with two random starts for the populations exhibiting exponential trend, autocorrelatedness and randomness. Throughout the discussion, the sample size is assumed to be even and the population size is a multiple of the sample size. The suggested method works well for estimating a finite population total for the population exhibiting exponential trend.     

Knowledge-based nonuniform sampling in multidimensional NMR

The full resolution afforded by high-field magnets is rarely realized in the indirect dimensions of multidimensional NMR experiments because of the time cost of uniformly sampling to long evolution times. Emerging methods utilizing nonuniform sampling (NUS) enable high resolution along indirect dimensions by sampling long evolution times without sampling at every multiple of the Nyquist sampling interval. While the earliest NUS approaches matched the decay of sampling density to the decay of the signal envelope, recent approaches based on coupled evolution times attempt to optimize sampling by choosing projection angles that increase the likelihood of resolving closely-spaced resonances. These approaches employ knowledge about chemical shifts to predict optimal projection angles, whereas prior applications of tailored sampling employed only knowledge of the decay rate. In this work we adapt the matched filter approach as a general strategy for knowledge-based nonuniform sampling that can exploit prior knowledge about chemical shifts and is not restricted to sampling projections. Based on several measures of performance, we find that exponentially weighted random sampling (envelope matched sampling) performs better than shift-based sampling (beat matched sampling). While shift-based sampling can yield small advantages in sensitivity, the gains are generally outweighed by diminished robustness. Our observation that more robust sampling schemes are only slightly less sensitive than schemes highly optimized using prior knowledge about chemical shifts has broad implications for any multidimensional NMR study employing NUS. The results derived from simulated data are demonstrated with a sample application to PfPMT, the phosphoethanolamine methyltransferase of the human malaria parasite Plasmodium falciparum.     

Spatial and temporal distribution of Anopheles gambiae s.l. (Diptera: Culicidae) in two Tanzanian villages: implication for designing mosquito sampling routines

This paper describes the spatial and temporal distribution of Anopheles gambiae s.l. Giles in two Tanzanian villages based on data collected from a five-month intensive mosquito sampling programme and analysed using Taylor's power law. The degree of spatial aggregation of female A. gambiae in each village was similar to its corresponding temporal aggregation, indicating that in designing sampling routines for estimating the abundance of mosquitoes, sampling effort should be allocated equally to houses (spatial) and nights (temporal). The analysis also showed that for a given amount of sampling effort, estimates of village-level mosquito abundance are more precise when sampling is carried out in randomly selected houses, than when the same houses are used on each sampling occasion. Also, the precision of estimating parous rates does not depend on whether mosquito sampling is carried out in the same or a random selection of houses. The implications of these findings for designing sampling routines for entomological evaluation of vector control trials are discussed.     

Median Ranked Set Sampling with Size Biased Probability of Selection

Median ranked set sampling may be combined with size biased probability of selection. A two-phase sample is assumed. In the first phase, units are selected with probability proportional to their size. In the second phase, units are selected using median ranked set sampling to increase the efficiency of the estimators relative to simple random sampling. There is also an increase in the efficiency relative to ranked set sampling (for some probability distribution functions). There will be a loss in efficiency depending on the amount of errors in ranking the units, the median ranked set sampling can be used to reduce the errors in ranking the units selected from the population. Estimators of the population mean and the population size are considered. The median ranked set sampling with probability proportion to size and with errors in ranking is considered and compared with ranked set sampling with errors in ranking. Computer simulation results for some probability distributions are also given.     

How to evaluate and reduce sampling effort for ants

Representative sampling of ant communities is time-consuming and laborious. Due to their manifold habitat requirements and sociobiological attributes, a suite of sampling methods is necessary to detect nearly all ant species in a given habitat. We analysed how well different combinations and intensities of sampling methods are suited to assess ant species richness and community patterns. Sampling occurred at 24 sites in mountain and floodplain habitats in Austria using pitfall traps, Winkler litter extraction, hand sampling of foragers, and colony sampling. Of these, pitfall traps delivered the largest species numbers. We drew 19 subsets of sampling approaches and compared these to the complete data. Many subsets that allowed for substantial reduction of work effort nonetheless reflected well the beta diversity patterns of the whole dataset. In contrast, alpha diversity assessment was more sensitive to reduced sampling effort. Pitfall traps turned out to be indispensable to collect ant species for biodiversity studies, but the optimal combination of sampling methods varied between habitat types. In rugged montane habitats pitfalls should be complemented at least by colony sampling. In floodplain forests the number of pitfall trap replicates can be reduced, but inclusion of Winkler samples is advisable.     

Microdialysis sampling of cytokines

Microdialysis sampling is a well-known method for collection of low molecular weight hydrophilic analytes. Due to the success of this sampling technique for these analytes, many researchers have wanted to extend the use of this method to a wider range of analytes-particularly proteins and peptides. These analytes pose unique challenges during microdialysis sampling. The primary challenges are the reduced recovery across the dialysis semi-permeable membrane and the volume limitations/requirements for the typical immunoassay methods used for detection of proteins. This review covers the practical and theoretical aspects needed for in vivo microdialysis sampling of cytokines, which are a vitally important class of signaling proteins. In addition to the basics of the microdialysis method for sampling cytokines, the use of the microdialysis device as a localized cytokine delivery method is also described. Since relative recovery of cytokines is often low during microdialysis sampling, methods to improve the membrane recovery are discussed for in vitro and in vivo applications.     

Sequential sampling: a novel method in farm animal welfare assessment

Lameness in dairy cows is an important welfare issue. As part of a welfare assessment, herd level lameness prevalence can be estimated from scoring a sample of animals, where higher levels of accuracy are associated with larger sample sizes. As the financial cost is related to the number of cows sampled, smaller samples are preferred. Sequential sampling schemes have been used for informing decision making in clinical trials. Sequential sampling involves taking samples in stages, where sampling can stop early depending on the estimated lameness prevalence. When welfare assessment is used for a pass/fail decision, a similar approach could be applied to reduce the overall sample size. The sampling schemes proposed here apply the principles of sequential sampling within a diagnostic testing framework. This study develops three sequential sampling schemes of increasing complexity to classify 80 fully assessed UK dairy farms, each with known lameness prevalence. Using the Welfare Quality herd-size-based sampling scheme, the first ‘basic’ scheme involves two sampling events. At the first sampling event half the Welfare Quality sample size is drawn, and then depending on the outcome, sampling either stops or is continued and the same number of animals is sampled again. In the second ‘cautious’ scheme, an adaptation is made to ensure that correctly classifying a farm as ‘bad’ is done with greater certainty. The third scheme is the only scheme to go beyond lameness as a binary measure and investigates the potential for increasing accuracy by incorporating the number of severely lame cows into the decision. The three schemes are evaluated with respect to accuracy and average sample size by running 100 000 simulations for each scheme, and a comparison is made with the fixed size Welfare Quality herd-size-based sampling scheme. All three schemes performed almost as well as the fixed size scheme but with much smaller average sample sizes. For the third scheme, an overall association between lameness prevalence and the proportion of lame cows that were severely lame on a farm was found. However, as this association was found to not be consistent across all farms, the sampling scheme did not prove to be as useful as expected. The preferred scheme was therefore the ‘cautious’ scheme for which a sampling protocol has also been developed.     

HMM sampling and applications to gene finding and alternative splicing

The standard method of applying hidden Markov models to biological problems is to find a Viterbi (maximal weight) path through the HMM graph. The Viterbi algorithm reduces the problem of finding the most likely hidden state sequence that explains given observations, to a dynamic programming problem for corresponding directed acyclic graphs. For example, in the gene finding application, the HMM is used to find the most likely underlying gene structure given a DNA sequence. In this note we discuss the applications of sampling methods for HMMs. The standard sampling algorithm for HMMs is a variant of the common forward-backward and backtrack algorithms, and has already been applied in the context of Gibbs sampling methods. Nevetheless, the practice of sampling state paths from HMMs does not seem to have been widely adopted, and important applications have been overlooked. We show how sampling can be used for finding alternative splicings for genes, including alternative splicings that are conserved between genes from related organisms. We also show how sampling from the posterior distribution is a natural way to compute probabilities for predicted exons and gene structures being correct under the assumed model. Finally, we describe a new memory efficient sampling algorithm for certain classes of HMMs which provides a practical sampling alternative to the Hirschberg algorithm for optimal alignment. The ideas presented have applications not only to gene finding and HMMs but more generally to stochastic context free grammars and RNA structure prediction.     

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.