Focusing modelling on the tracheid development period – An alternative method for treatment of xylogenesis intra-annual data

Intra-annual repeated micro-sampling of the developing tree ring is getting more and more applied in xylogenesis studies. Variability in growth magnitude, notably due to different sampling positions on the stem, encouraged application of standardization and modelling techniques. Among these, methods using Gompertz equation had become widely spread, but tests made with black spruce revealed a frequent occurrence of crossovers between the cumulative number of cells in enlargement and the cumulative number of cells in wall thickening. This was due to a localized problem in the fitting for values close to the asymptote and was a major problem for estimating the timing of each individual cell development phases, which is an interesting application of these data. In this paper, a new method, based on a different approach, has been developed in order to avoid that problem and applied to intra-annual growth curves from four sites in Quebec (Canada). Since tracheid development analysis allows discriminating between active and inactive period of a phase, modelling can be restricted on the active period alone. The new method did not cause crossovers between the fitted curves. Therefore, it has been considered appropriate for estimating the timing for each individual cell in the whole range of data. Since resulting functions are polynomials from degree 1 to 3, possible studies concerning general tendency should be easy to lead. Also, the method has been tested with different sampling frequencies. To do this, number of observations from weekly samplings has been halved to simulate a semi-monthly sampling frequency and a comparison of the results from the new method applied on each version of the datasets has been tested. Generally, the simulated semi-monthly sampled dataset did not give significantly different results from the original weekly sampled dataset, in terms of general tendency and predicted intercept time in the extremities of the data range. This is very encouraging for situations when only semi-monthly sampling is available.     

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.     

Automatic containment sampling of recombinant escherichia coli fermentations

A containment sampling system for shake flasks and fermentors has been developed from a blood collection system used in hospitals. The core of the system is a collection vial with a vacuum inside. When a needle connected to the fermentation fluid penetrates a rubber seal on the vial, a sample is withdrawn. The system has been developed in two versions, a manual method for shake flasks, and an automated version for fermentors including cool storage of samples. The sampling system offers the same safety for fermentation containment as the original system offers safety for patients and hospital staff. (c) 1992 John Wiley & Sons, Inc.     

Methods of neuston sampling for the quantitative characteristic of microbial communities of Lake Baikal

The efficiency of neuston sampling from freshwater Lake Baikal with Garrett’s metal screen and polycarbonate membrane filters has been estimated. It is revealed that both sampling methods demonstrate similar results. Method selection is determined by climatic and hydrological factors. The results of the present work demonstrate that sampling using a metal screen can be recommended for the complex characterization of neuston biofilm and estimation not only microbiological, but also molecular and chemical parameters, because it allows collecting the water volume required for all analyses.     

Multi-variate models are essential for understanding vertebrate diversification in deep time

Statistical models are helping palaeontologists to elucidate the history of biodiversity. Sampling standardization has been extensively applied to remedy the effects of uneven sampling in large datasets of fossil invertebrates. However, many vertebrate datasets are smaller, and the issue of uneven sampling has commonly been ignored, or approached using pairwise comparisons with a numerical proxy for sampling effort. Although most authors find a strong correlation between palaeodiversity and sampling proxies, weak correlation is recorded in some datasets. This has led several authors to conclude that uneven sampling does not influence our view of vertebrate macroevolution. We demonstrate that multi-variate regression models incorporating a model of underlying biological diversification, as well as a sampling proxy, fit observed sauropodomorph dinosaur palaeodiversity best. This bivariate model is a better fit than separate univariate models, and illustrates that observed palaeodiversity is a composite pattern, representing a biological signal overprinted by variation in sampling effort. Multi-variate models and other approaches that consider sampling as an essential component of palaeodiversity are central to gaining a more complete understanding of deep time vertebrate diversification.     

Minimal sampling requirements for a precise assessment of soft-bottom macrobenthic communities, using AMBI

Since AMBI was published originally in 2000, it has been used in an increasing number of investigations with monitoring purposes, or to analyse impacts on soft-bottom macrobenthic communities. Some guidelines for its correct use were published in 2005; however, a main issue remained without an answer — which are the minimal area and number of replicates necessary, to obtain a precise estimate for AMBI? In this study, new methodologies such as bootstrap techniques have been applied to this particular problem.Data were obtained from sampling carried out in 1995, within the framework of the Littoral Water Quality Monitoring and Control Network of the Basque Country (northern Spain). The sampling strategy consisted of 11 intertidal estuarine sampling stations (0.25m², sampled for each of six replicates) and 17 subtidal estuarine and coastal sampling stations (0.125m², sampled for each of six replicates).Two replicates have been established as being sufficient, both for intertidal and subtidal sampling stations, to classify 80% of the pseudosamples into the same disturbance level, in terms of AMBI, for 64% of the stations.For the minimal area, it has been determined also (for both intertidal and subtidal sampling stations) that 0.25m² is sufficient to classify 80% of the iterations into the same disturbance level, for 64% of the stations.     

Recommendations for sampling littoral diatoms in lakes for ecological status assessments

This review summarises the existing literature and outlines the theoretical basis for using standard methods for sampling diatoms from rivers to sample littoral diatoms and other phytobenthos from standing waters. The European Union's Water Framework Directive has created a statutory obligation for EU Member States to monitor macrophytes and phytobenthos in lakes. Although there has been a considerable amount of work using phytobenthos (especially diatoms) to monitor river water quality in Europe, there are fewer studies on the use of phytobenthos for monitoring in lakes. European standard methods for sampling diatoms from rivers should be suitable, with only minor modifications, for sampling littoral diatoms from lakes and other standing water bodies. These recommendations should be applicable to all temperate regions.     

A scaling approach to spatial variability in early diagenetic processes

The traditional approach to understanding early diagenetic processes in sediments has generally been to analyze pore water and solid phases from a single core on depth scales of centimeters. The resulting data is then modeled using the approximations of lateral homogeneity and steady-state conditions. However, the continuing advancement of the field of benthic biogeochemistry and development of new microelectrode analytic techniques are clearly demonstrating that in many sedimentary environments a more sophisticated approach to measure the spatial and temporal variability is necessary. Although no one approach is appropriate for all situations, a scaling method is presented, with examples, in this study for determining appropriate sampling intervals in time and space that has considerable utility for investigating early changes in sediment geochemistry in complex natural systems. This approach is derived from scaling techniques that have been developed by physical oceanographers for the study of processes in the water column where many analogous sampling problems are encountered.     

Two-phase species–time relationships in North American land birds

The species–time relationship (STR) is a macroecological pattern describing the increase in the observed species richness with the length of time censused. Understanding STRs is important for understanding the ecological processes underlying temporal turnover and species richness. However, accurate characterization of the STR has been hampered by the influence of sampling. I analysed STRs for 521 breeding bird survey communities. I used a model of sampling effects to demonstrate that the increase in richness was not due exclusively to sampling. I estimated the time scale at which ecological processes became dominant over sampling effects using a two‐phase model combining a sampling phase and either a power function or logarithmic ecological phase. These two‐phase models performed significantly better than sampling alone and better than simple power and logarithmic functions. Most community dynamics were dominated by ecological processes over scales <5 years. This technique provides an example of a rigorous, quantitative approach to separating sampling from ecological processes.     

Geographical sampling bias and its implications for conservation priorities in Africa

Aim To design and apply statistical tests for measuring sampling bias in the raw data used to the determine priority areas for conservation, and to discuss their impact on conservation analyses for the region. Location Sub‐Saharan Africa. Methods An extensive data set comprising 78,083 vouchered locality records for 1068 passerine birds in sub‐Saharan Africa has been assembled. Using geographical information systems, we designed and applied two tests to determine if sampling of these taxa was biased. First, we detected possible biases because of accessibility by measuring the proximity of each record to cities, rivers and roads. Second, we quantified the intensity of sampling of each species inside and surrounding proposed conservation priority areas and compared it with sampling intensity in non‐priority areas. We applied statistical tests to determine if the distribution of these sampling records deviated significantly from random distributions. Results The analyses show that the location and intensity of collecting have historically been heavily influenced by accessibility. Sampling localities show dense, significant aggregation around city limits, and along rivers and roads. When examining the collecting sites of each individual species, the pattern of sampling has been significantly concentrated within and immediately surrounding areas now designated as conservation priorities. Main conclusions Assessment of patterns of species richness and endemicity at the scale useful for establishing conservation priorities, below the continental level, undoubtedly reflects biases in taxonomic sampling. This is especially problematic for priorities established using the criterion of complementarity because the estimated spatial costs of this approach are highly sensitive to sampling artefacts. Hence such conservation priorities should be interpreted with caution proportional to the bias found. We argue that conservation priority setting analyses require (1) statistical tests to detect these biases, and (2) data treatment to reflect species distribution rather than patterns of collecting effort.     

Sampling in ecology and evolution – bridging the gap between theory and practice

Sampling is a key issue for answering most ecological and evolutionary questions. The importance of developing a rigorous sampling design tailored to specific questions has already been discussed in the ecological and sampling literature and has provided useful tools and recommendations to sample and analyse ecological data. However, sampling issues are often difficult to overcome in ecological studies due to apparent inconsistencies between theory and practice, often leading to the implementation of simplified sampling designs that suffer from unknown biases. Moreover, we believe that classical sampling principles which are based on estimation of means and variances are insufficient to fully address many ecological questions that rely on estimating relationships between a response and a set of predictor variables over time and space. Our objective is thus to highlight the importance of selecting an appropriate sampling space and an appropriate sampling design. We also emphasize the importance of using prior knowledge of the study system to estimate models or complex parameters and thus better understand ecological patterns and processes generating these patterns. Using a semi‐virtual simulation study as an illustration we reveal how the selection of the space (e.g. geographic, climatic), in which the sampling is designed, influences the patterns that can be ultimately detected. We also demonstrate the inefficiency of common sampling designs to reveal response curves between ecological variables and climatic gradients. Further, we show that response‐surface methodology, which has rarely been used in ecology, is much more efficient than more traditional methods. Finally, we discuss the use of prior knowledge, simulation studies and model‐based designs in defining appropriate sampling designs. We conclude by a call for development of methods to unbiasedly estimate nonlinear ecologically relevant parameters, in order to make inferences while fulfilling requirements of both sampling theory and field work logistics.     

Performance tradeoffs in target‐group bias correction for species distribution models

Species distribution models (SDMs) are often calibrated using presence‐only datasets plagued with environmental sampling bias, which leads to a decrease of model accuracy. In order to compensate for this bias, it has been suggested that background data (or pseudoabsences) should represent the area that has been sampled. However, spatially‐explicit knowledge of sampling effort is rarely available. In multi‐species studies, sampling effort has been inferred following the target‐group (TG) approach, where aggregated occurrence of TG species informs the selection of background data. However, little is known about the species‐ specific response to this type of bias correction. The present study aims at evaluating the impacts of sampling bias and bias correction on SDM performance. To this end, we designed a realistic system of sampling bias and virtual species based on 92 terrestrial mammal species occurring in the Mediterranean basin. We manipulated presence and background data selection to calibrate four SDM types. Unbiased (unbiased presence data) and biased (biased presence data) SDMs were calibrated using randomly distributed background data. We used real and TG‐estimated sampling efforts in background selection to correct for sampling bias in presence data. Overall, environmental sampling bias had a deleterious effect on SDM performance. In addition, bias correction improved model accuracy, and especially when based on spatially‐explicit knowledge of sampling effort. However, our results highlight important species‐specific variations in susceptibility to sampling bias, which were largely explained by range size: widely‐distributed species were most vulnerable to sampling bias and bias correction was even detrimental for narrow‐ranging species. Furthermore, spatial discrepancies in SDM predictions suggest that bias correction effectively replaces an underestimation bias with an overestimation bias, particularly in areas of low sampling intensity. Thus, our results call for a better estimation of sampling effort in multispecies system, and cautions the uninformed and automatic application of TG bias correction.     

Fish species richness evaluation in Mexican coastal lagoons: a case study in the Gulf of Mexico

We analyze the origin of knowledge about fish species richness in the Tuxpan-Tampamachoco estuarine system, in Veracuz, México. A complete inventory of the fish species known to date for this system (N = 179) was elaborated from published lists and from sampling seagrass meadows of Tampamachoco Lagoon, which yielded 14 previously unknown species. When compared, the different lists showed a low similarity that may reflect differences in sampling methods and collecting strategies. Current data suggest that fish species richness in Mexican coastal lagoons (Gulf of Mexico) is not related with lagoon surface area, as has been suggested, but with the number of inventories available for each lagoon, being these a reflection of the sampling effort. A sampling design for the assessment of fish species richness in estuarine systems should consider: a) using the highest possible variety of sampling fishing gears, b) collecting in all microhabitat types and c) the preference of bimonthly or quarterly samplings for two or more years over monthly samplings in a single year.     

Large-scale heterogeneity of the fossil record: implications for Phanerozoic biodiversity studies

Patterns of origination, extinction and standing diversity through time have been inferred from tallies of taxa preserved in the fossil record. This approach assumes that sampling of the fossil record is effectively uniform over time. Although recent evidence suggests that our sampling of the available rock record has indeed been very thorough and effective, there is also overwhelming evidence that the rock record available for sampling is itself distorted by major systematic biases. Data on rock outcrop area compiled for post-Palaeozoic sediments from Western Europe at stage level are presented. These show a strongly cyclical pattern corresponding to first- and second-order sequence stratigraphical depositional cycles. Standing diversity increases over time and, at the coarsest scale, is decoupled from surface outcrop area. This increasing trend can therefore be considered a real pattern. Changes in standing diversity and origination rates over time-scales measured in tens of millions of years, however, are strongly correlated with surface outcrop area. Extinction peaks conform to a random-walk model, but larger peaks occur at just two positions with respect to second-order stratigraphical sequences, towards the culmination of stacked transgressive system tracts and close to system bases, precisely the positions where taxonomic last occurrences are predicted to cluster under a random distribution model. Many of the taxonomic patterns that have been described from the fossil record conform to a species-area effect. Whether this arises primarily from sampling bias, or from changing surface area of marine shelf seas through time and its effect on biodiversity, remains problematic.     

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.     

Review of capture-recapture methods applicable to noninvasive genetic sampling

The use of noninvasive genetic sampling to identify individual animals for capture-recapture studies has become widespread in the past decade. Strong emphasis has been placed on the field protocols and genetic analyses with fruitful results. Little attention has been paid to the capture-recapture application for this specific type of data beyond stating the effects of assumption violations. Here, we review the broad class of capture-recapture methods that are available for use with DNA-based capture-recapture data, noting the array of biologically interesting parameters such as survival, emigration rates, state transition rates and the finite rate of population change that can be estimated from such data. We highlight recent developments in capture-recapture theory specifically designed for noninvasive genetic sampling data.     

The partial stream sampling assumption in intestinal perfusion studies

During the past several years, the technique ofin vivo intestinal perfusion with partial stream sampling has been increasingly widely used to gather information on intestinal absorptive processes in man. The basic technique involves infusion of test solution through a proximal opening; and aspiration of samples through one or more distal openings a fixed distance apart. Samples are analyzed for test solute concentrations; from such sample data, conclusions are drawn concerning alterations in stream concentrations between the sampling sites. An underlying assumption for the validity of such a method is: that sample concentrations are the same as average stream concentrations. This assumption has not previously been precisely stated. A precise statement of it is given here, together with an analytic proof of conditions necessary and sufficient for its validity. A brief verbal comment is included to clarify the practical meaning of the analytic statement.     

Comparability of macroinvertebrate biomonitoring indices of river health derived from semi-quantitative and quantitative methodologies

Aquatic macroinvertebrates have been the basis for one of the primary indicators and a cornerstone of lotic biomonitoring for over 40 years. Despite the widespread use of lotic invertebrates in statutory biomonitoring networks, scientific research and citizen science projects, the sampling methodologies employed frequently vary between studies. Routine statutory biomonitoring has historically relied on semi-quantitative sampling methods (timed kick sampling), while much academic research has favoured fully quantitative methods (e.g. Surber sampling). There is an untested assumption that data derived using quantitative and semi-quantitative samples are not comparable for biomonitoring purposes. As a result, data derived from the same site, but using different sampling techniques, have typically not been analysed together or directly compared. Here, we test this assumption by comparing a range of biomonitoring metrics derived from data collected using timed semi-quantitative kick samples and quantitative Surber samples from the same sites simultaneously. In total, 39 pairs of samples from 7 rivers in the UK were compared for two seasons (spring and autumn). We found a strong positive correlation (r_s = +0.84) between estimates of taxa richness based on ten Surber sub-samples and a single kick sample. The majority of biomonitoring metrics were comparable between techniques, although only fully quantitative sampling allows the density of the community (individual m⁻²) to be determined. However, this advantage needs to be balanced alongside the greater total sampling time and effort associated with the fully quantitative methodology used here. Kick samples did not provide a good estimate of relative abundance of a number of species/taxa and, therefore, the quantitative method has the potential to provide important additional information which may support the interpretation of the biological metrics.     

Finding the needle in the haystack: towards solving the protein-folding problem computationally

Prediction of protein tertiary structures from amino acid sequence and understanding the mechanisms of how proteins fold, collectively known as “the protein folding problem,” has been a grand challenge in molecular biology for over half a century. Theories have been developed that provide us with an unprecedented understanding of protein folding mechanisms. However, computational simulation of protein folding is still difficult, and prediction of protein tertiary structure from amino acid sequence is an unsolved problem. Progress toward a satisfying solution has been slow due to challenges in sampling the vast conformational space and deriving sufficiently accurate energy functions. Nevertheless, several techniques and algorithms have been adopted to overcome these challenges, and the last two decades have seen exciting advances in enhanced sampling algorithms, computational power and tertiary structure prediction methodologies. This review aims at summarizing these computational techniques, specifically conformational sampling algorithms and energy approximations that have been frequently used to study protein-folding mechanisms or to de novo predict protein tertiary structures. We hope that this review can serve as an overview on how the protein-folding problem can be studied computationally and, in cases where experimental approaches are prohibitive, help the researcher choose the most relevant computational approach for the problem at hand. We conclude with a summary of current challenges faced and an outlook on potential future directions.     

On a Simple Procedure of Inclusion Probability Proportional to Sizes (IPPS) Sampling

A simple method of inclusion probability proportional to sizes is proposed for samples of size three units. It is shown that the variance of the HORVITZ -THOMPSON estimator based on the proposed sampling scheme is uniformly smaller than that of the customary estimator used in the probability proportional to sizes with replacement sampling. Further, its performance over RAO -HARTLEY -COCHRAN and SAMPFORD sampling schemes has been studied empirically for some of the natural populations.