THE TWO-WAVELENGTH METHOD OF MICROSPECTROPHOTOMETRY : IV. A New Solution

In connection with the potential development of automatic two-wavelength microspectrophotometry, a new version of the two-wavelength method has been formulated. Unlike its predecessors, the Ornstein and Patau versions, the new method varies the area of the photometric field seeking to maximize a relationship between distributional errors at the two wavelengths. Stating this distributional error relationship in conventional photometric terms, the conditions at the maximum are defined by taking the first derivative with respect to field size and setting it equal to zero. This operation supplies two equations; one relates the transmittances at the two wavelengths, and a second states the relative amount of chromophore in the field in terms of transmittance at one wavelength. With the first equation to drive a servomechanism which sets the appropriate field size, the desired answer can then be obtained directly and continuously from the second equation. The result is identical in theory with those of the earlier methods, but the technique is more suitable for electronic computing.     

Evaluation of algorithms for ratio imaging in fluorescence microscopy

Ratio imaging in fluorescence microscopy is used in measuring parameters such as pH, pCa, cytoplasmic porosity, and the relative concentration of fluorescent analogs within single cells. The fastest method for ratio imaging is to use lookup tables on special-purpose image processors. Since lookup tables store integers in integer addresses, using a lookup table will generate rounding errors. The magnitude of the error will depend on the transformation performed and on the number of levels used in the lookup table. We examined ratio imaging by lookup table and computed the errors generated by both inversion and log subtraction methods. Both uniformly fluorescing fields and fluorescing cell images were employed to provide data for use in confirming our calculations and illustrating both the magnitude and spatial incidence of errors. It is shown that, through proper design of lookup tables, a significant reduction can be made in the errors generated in comparison with common methods available in most image processors.     

ESTIMATING SPECIATION AND EXTINCTION RATES FROM DIVERSITY DATA AND THE FOSSIL RECORD

Understanding the processes that underlie biodiversity requires insight into the evolutionary history of the taxa involved. Accurate estimation of speciation, extinction, and diversification rates is a prerequisite for gaining this insight. Here, we develop a stochastic birth–death model of speciation and extinction that predicts the probability distribution of both extinct and extant numbers of species in a clade. We present two estimation methods based on this model given data on the number of extinct species (from the fossil record) and extant species (from diversity assessments): a multivariate method of moments approach and a maximum-likelihood approach. We show that, except for some special cases, the two estimation methods produce very similar estimates. This is convenient, because the usually preferred maximum-likelihood approach is much more computationally demanding, so the method of moments can serve as a proxy. Furthermore, we introduce a correction for possible bias that can arise by the mere fact that we will normally only consider extant clades. We find that in some cases the bias correction affects the estimates profoundly. Finally, we show how our model can be extended to incorporate incomplete preservation. Preservation rates can, however, not be reliably estimated on the basis of numbers of extant and extinct species alone.     

Methods of automatic nucleotide-sequence analysis. Multicomponent spectrophotometric analysis of mixtures of nucleic acid components by a least-squares procedure

1. A theoretical analysis of the errors in multicomponent spectrophotometric analysis of nucleoside mixtures, by a least-squares procedure, has been made to obtain an expression for the error coefficient, relating the error in calculated concentration to the error in extinction measurements. 2. The error coefficients, which depend only on the `library' of spectra used to fit the experimental curves, have been computed for a number of `libraries' containing the following nucleosides found in s-RNA: adenosine, guanosine, cytidine, uridine, 5-ribosyluracil, 7-methylguanosine, 6-dimethylaminopurine riboside, 6-methylaminopurine riboside and thymine riboside. 3. The error coefficients have been used to determine the best conditions for maximum accuracy in the determination of the compositions of nucleoside mixtures. 4. Experimental determinations of the compositions of nucleoside mixtures have been made and the errors found to be consistent with those predicted by the theoretical analysis. 5. It has been demonstrated that, with certain precautions, the multicomponent spectrophotometric method described is suitable as a basis for automatic nucleotide-composition analysis of oligonucleotides containing nine nucleotides. Used in conjunction with continuous chromatography and flow chemical techniques, this method can be applied to the study of the sequence of s-RNA.     

Demographic stochasticity, allee effects, and extinction: the influence of mating system and sex ratio

Demographic stochasticity has a substantial influence on the growth of small populations and consequently on their extinction risk. Mating system is one of several population characteristics that may affect this. We use a stochastic pair-formation model to investigate the combined effects of mating system, sex ratio, and population size on demographic stochasticity and thus on extinction risk. Our model is designed to accommodate a continuous range of mating systems and sex ratios as well as several levels of stochasticity. We show that it is not mating system alone but combinations of mating system and sex ratio that are important in shaping the stochastic dynamics of populations. Specifically, polygyny has the potential to give a high demographic variance and to lower the stochastic population growth rate substantially, thus also shortening the time to extinction, but the outcome is highly dependent on the sex ratio. In addition, population size is shown to be important. We find a stochastic Allee effect that is amplified by polygyny. Our results demonstrate that both mating system and sex ratio must be considered in conservation planning and that appreciating the role of stochasticity is key to understanding their effects.     

Correcting errors in shotgun sequences

Sequencing errors in combination with repeated regions cause major problems in shotgun sequencing, mainly due to the failure of assembly programs to distinguish single base differences between repeat copies from erroneous base calls. In this paper, a new strategy designed to correct errors in shotgun sequence data using defined nucleotide positions, DNPs, is presented. The method distinguishes single base differences from sequencing errors by analyzing multiple alignments consisting of a read and all its overlaps with other reads. The construction of multiple alignments is performed using a novel pattern matching algorithm, which takes advantage of the symmetry between indices that can be computed for similar words of the same length. This allows for rapid construction of multiple alignments, with no previous pair-wise matching of sequence reads required. Results from a C++ implementation of this method show that up to 99% of sequencing errors can be corrected, while up to 87% of the single base differences remain and up to 80% of the corrected reads contain at most one error. The results also show that the method outperforms the error correction method used in the EULER assembler. The prototype software, MisEd, is freely available from the authors for academic use.     

Managed relocation as an adaptation strategy for mitigating climate change threats to the persistence of an endangered lizard

The distributional ranges of many species are contracting with habitat conversion and climate change. For vertebrates, informed strategies for translocations are an essential option for decisions about their conservation management. The pygmy bluetongue lizard, Tiliqua adelaidensis, is an endangered reptile with a highly restricted distribution, known from only a small number of natural grassland fragments in South Australia. Land‐use changes over the last century have converted perennial native grasslands into croplands, pastures and urban areas, causing substantial contraction of the species' range due to loss of essential habitat. Indeed, the species was thought to be extinct until its rediscovery in 1992. We develop coupled‐models that link habitat suitability with stochastic demographic processes to estimate extinction risk and to explore the efficacy of potential climate adaptation options. These coupled‐models offer improvements over simple bioclimatic envelope models for estimating the impacts of climate change on persistence probability. Applying this coupled‐model approach to T. adelaidensis, we show that: (i) climate‐driven changes will adversely impact the expected minimum abundance of populations and could cause extinction without management intervention, (ii) adding artificial burrows might enhance local population density, however, without targeted translocations this measure has a limited effect on extinction risk, (iii) managed relocations are critical for safeguarding lizard population persistence, as a sole or joint action and (iv) where to source and where to relocate animals in a program of translocations depends on the velocity, extent and nonlinearities in rates of climate‐induced habitat change. These results underscore the need to consider managed relocations as part of any multifaceted plan to compensate the effects of habitat loss or shifting environmental conditions on species with low dispersal capacity. More broadly, we provide the first step towards a more comprehensive framework for integrating extinction risk, managed relocations and climate change information into range‐wide conservation management.     

The Two-Wavelength Method of Microspectrophotometry : III. An Extension Based on Photographic Color Transparencies

The two-wavelength method of microspectrophotometry corrects for distributional error and measures the amount of absorbing material by taking advantage of certain spectral characteristics of the specimen. Under certain circumstances, such as the absorption of nucleic acids in the ultraviolet and of black or multiple stains in the visible, the spectral characteristics are not suitable for the application of the method. To circumvent this, a photomicrograph of the object is taken with monochromatic light of a suitable wavelength. A second plate is exposed as a contact print of the photomicrograph and is developed in the presence of a coupling agent. After bleaching and fixation, the positive appears as a monochromatic color transparency. Two-wavelength analysis of such a transparency can be made in terms of the new color. The measurements will be free of distributional error and can be equated to the original object. The necessary formulae are derived, and a method which has proven suitable for color development is given. The photographic and the direct two-wavelength method were found to give equivalent results when both were used on the same series of liver nuclei. The application of the photographic method to ultraviolet absorption has been demonstrated. The new method is potentially applicable to other types of photographic densitometry involving heterogeneous images.     

The use of Markovian metapopulation models: a comparison of three methods reducing the dimensionality of transition matrices

The use of Markovian models is an established way for deriving the complete distribution of the size of a population and the probability of extinction. However, computationally impractical transition matrices frequently result if this mathematical approach is applied to natural populations. Binning, or aggregating population sizes, has been used to permit a reduction in the dimensionality of matrices. Here, we present three deterministic binning methods and study the errors due to binning for a metapopulation model. Our results indicate that estimation errors of the investigated methods are not consistent and one cannot make generalizations about the quality of a method. For some compared output variables of populations studied, binning methods that caused a strong reduction in dimensionality of matrices resulted in better estimations than methods that produced a weaker reduction. The main problem with deterministic binning methods is that they do not properly take into account the stochastic population process itself. Straightforward usage of binning methods may lead to substantial errors in population-dynamical predictions.     

The two-wavelength method of microspectrophotometry. III. An extension based on photographic color transparencies

The two-wavelength method of microspectrophotometry corrects for distributional error and measures the amount of absorbing material by taking advantage of certain spectral characteristics of the specimen. Under certain circumstances, such as the absorption of nucleic acids in the ultraviolet and of black or multiple stains in the visible, the spectral characteristics are not suitable for the application of the method. To circumvent this, a photomicrograph of the object is taken with monochromatic light of a suitable wavelength. A second plate is exposed as a contact print of the photomicrograph and is developed in the presence of a coupling agent. After bleaching and fixation, the positive appears as a monochromatic color transparency. Two-wavelength analysis of such a transparency can be made in terms of the new color. The measurements will be free of distributional error and can be equated to the original object. The necessary formulae are derived, and a method which has proven suitable for color development is given. The photographic and the direct two-wavelength method were found to give equivalent results when both were used on the same series of liver nuclei. The application of the photographic method to ultraviolet absorption has been demonstrated. The new method is potentially applicable to other types of photographic densitometry involving heterogeneous images.     

Correction Approaches for Doubly Labeled Water in Situations of Changing Background Water Abundance

Doubly labeled water (DLW) is an accurate, portable method for measuring free-living energy expenditure. However, under certain conditions shifts in baseline abundance of deuterium and oxygen-18 tracers used in the method may produce errors in derivation of both turnover (k) rates and calculated energy expenditure. Present objectives were to examine during what experimental situations baseline errors arise and to address means of correcting for such baseline shifts so that consequent errors in energy expenditure calculations are minimized. Under conditions where shifts in baseline abundance for deuterium and oxygen-18 parallel abundances corresponding to the natural meteoric water ratio, self-compensating changes in k values for both deuterium and oxygen will result in minimal error to the DLW energy expenditure calculations, provided that the dose ratio of isotopes also mimics the meteoric water line. However, in situations where relative shifts in abundance of each isotope across the measurement period are not in parallel relative to the natural meteoric water line, then the potential for larger DLW errors exists. Optimally, subjects should equilibrate with the new water source. Failing this, correction for shifting baseline can be accomplished by measuring isotopic abundance changes in a control group of subjects not given the DLW dose, but performing similar tasks and consuming the same diet as the group given DLW. Alternatively, theoretically based correction values can be calculated given knowledge of the abundances of the final drinking water and the interval time that subjects consumed the new fluid.     

Plant extinction risk under climate change: are forecast range shifts alone a good indicator of species vulnerability to global warming?

Models that couple habitat suitability with demographic processes offer a potentially improved approach for estimating spatial distributional shifts and extinction risk under climate change. Applying such an approach to five species of Australian plants with contrasting demographic traits, we show that: (i) predicted climate‐driven changes in range area are sensitive to the underlying habitat model, regardless of whether demographic traits and their interaction with habitat patch configuration are modeled explicitly; and (ii) caution should be exercised when using predicted changes in total habitat suitability or geographic extent to infer extinction risk, because the relationship between these metrics is often weak. Measures of extinction risk, which quantify threats to population persistence, are particularly sensitive to life‐history traits, such as recruitment response to fire, which explained approximately 60% of the deviance in expected minimum abundance. Dispersal dynamics and habitat patch structure have the strongest influence on the amount of movement of the trailing and leading edge of the range margin, explaining roughly 40% of modeled structural deviance. These results underscore the need to consider direct measures of extinction risk (population declines and other measures of stochastic viability), as well as measures of change in habitat area, when assessing climate change impacts on biodiversity. Furthermore, direct estimation of extinction risk incorporates important demographic and ecosystem processes, which potentially influence species’ vulnerability to extinction due to climate change.     

种群生存力分析研究进展和趋势

种群生存力分析（PVA）是正在迅速发展的新方法,已成为保护生物学研究的热点。它主要研究随机干扰对小种群绝灭的影响,其目的是制定最小可存活种群（MVP）,把绝灭减少到可接受的水平。随机干扰可分四类;统计随机性,环境随机性,自然灾害和遗传随机性。确定MVP的方法有三种：理论模型,模拟模型,模拟模型和岛屿生物地理学方法。理论模型主要研究理想或特定条件下随机因素对种群的影响;模拟模型是利用计算机模拟种群绝灭过程;岛屿生物地理学方法主要分析岛屿物种的分布和存活,证实分析模型和模拟模型。已有大量的文献研究统计随机性,环境随机性和自然灾害的行为特征,但遗传因素与种群生存力之间的关系还不清楚。建立包括四种随机性的综合性模型,广泛地检验PVA模型,系统地研制目标种的遗传和生态特性以及MVP的实际应用是PVA的发展趋势。     

Semiparametric maximum likelihood for measurement error model regression

This paper presents an EM algorithm for semiparametric likelihood analysis of linear, generalized linear, and nonlinear regression models with measurement errors in explanatory variables. A structural model is used in which probability distributions are specified for (a) the response and (b) the measurement error. A distribution is also assumed for the true explanatory variable but is left unspecified and is estimated by nonparametric maximum likelihood. For various types of extra information about the measurement error distribution, the proposed algorithm makes use of available routines that would be appropriate for likelihood analysis of (a) and (b) if the true x were available. Simulations suggest that the semiparametric maximum likelihood estimator retains a high degree of efficiency relative to the structural maximum likelihood estimator based on correct distributional assumptions and can outperform maximum likelihood based on an incorrect distributional assumption. The approach is illustrated on three examples with a variety of structures and types of extra information about the measurement error distribution.     

Measurement error and estimates of population extinction risk

It is common to estimate the extinction probability for a vulnerable population using methods that are based on the mean and variance of the long‐term population growth rate. The numerical values of these two parameters are estimated from time series of population censuses. However, the proportion of a population that is registered at each census is typically not constant but will vary among years because of stochastic factors such as weather conditions at the time of sampling. Here, we analyse how such sampling errors influence estimates of extinction risk and find sampling errors to produce two opposite effects. Measurement errors lead to an exaggerated overall variance, but also introduce negative autocorrelations in the time series (which means that estimates of annual growth rates tend to alternate in size). If time series data are treated properly these two effects exactly counter balance. We advocate routinely incorporating a measure of among year correlations in estimating population extinction risk.     

A multipoint method for detecting genotyping errors and mutations in sibling-pair linkage data

The identification of genes contributing to complex diseases and quantitative traits requires genetic data of high fidelity, because undetected errors and mutations can profoundly affect linkage information. The recent emphasis on the use of the sibling-pair design eliminates or decreases the likelihood of detection of genotyping errors and marker mutations through apparent Mendelian incompatibilities or close double recombinants. In this article, we describe a hidden Markov method for detecting genotyping errors and mutations in multilocus linkage data. Specifically, we calculate the posterior probability of genotyping error or mutation for each sibling-pair-marker combination, conditional on all marker data and an assumed genotype-error rate. The method is designed for use with sibling-pair data when parental genotypes are unavailable. Through Monte Carlo simulation, we explore the effects of map density, marker-allele frequencies, marker position, and genotype-error rate on the accuracy of our error-detection method. In addition, we examine the impact of genotyping errors and error detection and correction on multipoint linkage information. We illustrate that even moderate error rates can result in substantial loss of linkage information, given efforts to fine-map a putative disease locus. Although simulations suggest that our method detects 相似文献   

Modelling the responses of Andean and Amazonian plant species to climate change: the effects of georeferencing errors and the importance of data filtering

Aim Species distribution models are a potentially powerful tool for predicting the effects of global change on species distributions and the resulting extinction risks. Distribution models rely on relationships between species occurrences and climate and may thus be highly sensitive to georeferencing errors in collection records. Most errors will not be caught using standard data filters. Here we assess the impacts of georeferencing errors and the importance of improved data filtering for estimates of the elevational distributions, habitat areas and predicted relative extinction risks due to climate change of nearly 1000 Neotropical plant species. Location The Amazon basin and tropical Andes, South America. Methods We model the elevational distributions, or ‘envelopes’, of 932 Amazonian and Andean plant species from 35 families after performing standard data filtering, and again using only data that have passed through an additional layer of data filtering. We test for agreement in the elevations recorded with the collection and the elevation inferred from a digital elevation model (DEM) at the collection coordinates. From each dataset we estimate species range areas and extinction risks due to the changes in habitat area caused by a 4.5 °C increase in temperature. Results Amazonian and Andean plant species have a median elevational range of 717 m. Using only standard data filters inflates range limits by a median of 433 m (55%). This is equivalent to overestimating the temperature tolerances of species by over 3 °C – only slightly less than the entire regional temperature change predicted over the next 50–100 years. Georeferencing errors tend to cause overestimates in the amount of climatically suitable habitat available to species and underestimates in species extinction risks due to global warming. Georeferencing error artefacts are sometimes so great that accurately predicting whether species habitat areas will decrease or increase under global warming is impossible. The drawback of additional data filtering is large decreases in the number of species modelled, with Andean species being disproportionately eliminated. Main conclusions Even with rigorous data filters, distribution models will mischaracterize the climatic conditions under which species occur due to errors in the collection data. These errors affect predictions of the effects of climate change on species ranges and biodiversity, and are particularly problematic in mountainous areas. Additional data filtering reduces georeferencing errors but eliminates many species due to a lack of sufficient ‘clean’ data, thereby limiting our ability to predict the effects of climate change in many ecologically important and sensitive regions such as the Andes Biodiversity Hotspot.     

Kinetic microphotometric activity determination in enzyme containing gels and model studies with tissue sections

Summary The dependence of microphotometrically recorded reaction rate on local enzyme concentration was studied as a basic prerequisite of comparative microphotometric enzyme activity determinations at initial rate conditions in tissue sections. Polyacrylamide gels containing defined concentrations of glucose-6-phosphate dehydrogenase served as a model. Optimal conditions of preparing enzyme containing gels are reported. Measurements in which either thickness of gel sections or enzyme concentration was varied proved the linear relationship between local enzyme concentration and microphotometrically recorded reaction rate. Sections of enzyme containing gels as well as cross-sections of rat muscles were used as models for studying possible influences of heterogeneous chromophore distribution (distributional error). No such influences could be detected during the initial phase of the staining reaction which suggests that distributional error is of no significance for kinetic microphotometric enzyme activity determination at initial rate conditions.