Snow products for assimilation and verification

Snow is an important component of the land surface, and the choice of products for assimilation or verification can have a large impact on the surface analysis. This paper introduces the many sources of snow data that are currently available, both in situ and from remote sensing from space, along with some recent developments. Snow extent products are derived from the biggest range of sensors and are the most widely used, while information on snow mass from space is still too error-prone to be used successfully in assimilation schemes.

The binding site distance test score: a robust method for the assessment of predicted protein binding sites

We propose a novel method for scoring the accuracy of protein binding site predictions – the Binding-site Distance Test (BDT) score. Recently, the Matthews Correlation Coefficient (MCC) has been used to evaluate binding site predictions, both by developers of new methods and by the assessors for the community wide prediction experiment – CASP8. Whilst being a rigorous scoring method, the MCC does not take into account the actual 3D location of the predicted residues from the observed binding site. Thus, an incorrectly predicted site that is nevertheless close to the observed binding site will obtain an identical score to the same number of nonbinding residues predicted at random. The MCC is somewhat affected by the subjectivity of determining observed binding residues and the ambiguity of choosing distance cutoffs. By contrast the BDT method produces continuous scores ranging between 0 and 1, relating to the distance between the predicted and observed residues. Residues predicted close to the binding site will score higher than those more distant, providing a better reflection of the true accuracy of predictions. The CASP8 function predictions were evaluated using both the MCC and BDT methods and the scores were compared. The BDT was found to strongly correlate with the MCC scores whilst also being less susceptible to the subjectivity of defining binding residues. We therefore suggest that this new simple score is a potentially more robust method for future evaluations of protein-ligand binding site predictions.

Experimental verification of suction sampler capture efficiency in grasslands of differing vegetation height and structure

1. Suction sampling is a popular method for the collection of quantitative data on grassland invertebrate populations, although there have been no detailed studies into the effectiveness of the method. 2. We investigate the effect of effort (duration and number of suction samples) and sward height on the efficiency of suction sampling of grassland beetle, true bug, planthopper and spider Populations. We also compare Suction sampling with an absolute sampling method based on the destructive removal of turfs. 3. Sampling for durations of 16 seconds was sufficient to collect 90% of all individuals and species of grassland beetles, with less time required for the true bugs, spiders and planthoppers. The number of samples required to collect 90% of the species was more variable, although in general 55 sub-samples was sufficient for all groups, except the true bugs. Increasing sward height had a negative effect on the capture efficiency of suction sampling. 4. The assemblage structure of beetles, planthoppers and spiders was independent of the sampling method (suction or absolute) used. 5. Synthesis and applications. In contrast to other sampling methods used in grassland habitats (e.g. sweep netting or pitfall trapping), suction sampling is an effective quantitative tool for the measurement of invertebrate diversity and assemblage structure providing sward height is included as a covariate. The effective sampling of beetles, true bugs, planthoppers and spiders altogether requires a minimum sampling effort of 110 sub-samples of duration of 16 seconds. Such sampling intensities can be adjusted depending on the taxa sampled, and we provide information to minimize sampling problems associated with this versatile technique. Suction sampling should remain an important component in the toolbox of experimental techniques used during both experimental and management sampling regimes within agroecosystems, grasslands or other low-lying vegetation types.

Extending Zelterman’s approach for robust estimation of population size to zero-truncated clustered data

Estimation of population size with missing zero-class is an important problem that is encountered in epidemiological assessment studies. Fitting a Poisson model to the observed data by the method of maximum likelihood and estimation of the population size based on this fit is an approach that has been widely used for this purpose. In practice, however, the Poisson assumption is seldom satisfied. Zelterman (1988) has proposed a robust estimator for unclustered data that works well in a wide class of distributions applicable for count data. In the work presented here, we extend this estimator to clustered data. The estimator requires fitting a zero-truncated homogeneous Poisson model by maximum likelihood and thereby using a Horvitz-Thompson estimator of population size. This was found to work well, when the data follow the hypothesized homogeneous Poisson model. However, when the true distribution deviates from the hypothesized model, the population size was found to be underestimated. In the search of a more robust estimator, we focused on three models that use all clusters with exactly one case, those clusters with exactly two cases and those with exactly three cases to estimate the probability of the zero-class and thereby use data collected on all the clusters in the Horvitz-Thompson estimator of population size. Loss in efficiency associated with gain in robustness was examined based on a simulation study. As a trade-off between gain in robustness and loss in efficiency, the model that uses data collected on clusters with at most three cases to estimate the probability of the zero-class was found to be preferred in general. In applications, we recommend obtaining estimates from all three models and making a choice considering the estimates from the three models, robustness and the loss in efficiency. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

Some new three-level orthogonal main effects plans robust to model uncertainty

In this paper, we list some new orthogonal main effects plans for three-level designs for 4, 5 and 6 factors in IS runs and compare them with designs obtained from the existing L-18 orthogonal array. We show that these new designs have better projection properties and can provide better parameter estimates for a range of possible models. Additionally, we study designs in other smaller run-sizes when there are insufficient resources to perform an 18-run experiment. Plans for three-level designs for 4, 5 and 6 factors in 13 to 17 runs axe given. We show that the best designs here are efficient and deserve strong consideration in many practical situations.