Lignin signatures show the effects of changes in heather and bracken cover on the composition of organic matter in a moorland soil profile

Bracken (Pteridium aquilinum) is aggressively displacing heather (Calluna vulgaris) on many moorlands in Britain. We investigated the use of lignin derivatives to identify the distribution of soil organic matter (SOM) derived from bracken in moorland soil profiles formed under heather. Phenylpropanoids extracted from recently senesced litters, roots and SOM, using alkaline CuO oxidation, showed distinct signatures for bracken and heather, with vanillyl moieties dominating bracken litter extracts and vanillyl and syringyl dominating heather litter extracts. Ratios of vanillyl and syringyl concentrations characterised the SOM derived from heather and bracken better than the concentrations of the individual moieties. The analysis showed up to a depth of 5 cm under pure bracken cover, and at the interface between heather and bracken, the SOM was largely derived from bracken litter but below that depth SOM was apparently derived from heather. The use of these methods to identify the plant origin of SOM not only enables understanding the effects of changing vegetation cover on organic matter dynamics in moorland soils but could also facilitate management techniques in moorland/heathland restoration which involve the removal of comparatively nutrient-rich SOM derived from bracken. Received: 30 November 1997 / Accepted: 11 April 1998     

Competition between heather and grasses on Scottish moorlands: Interacting effects of nutrient enrichment and grazing regime

Abstract. Considerable losses and degradation of heathlands (in moorlands and lowlands) have been reported across Europe, with Calluna vulgaris (heather) being replaced by other species, often grasses. Increasing atmospheric nitrogen deposition and overgrazing have been suggested as the driving factors behind this change. This possibility was investigated in a study of the interacting effects of nutrient inputs and grazing on heather and three grass species (Nardus stricta, Deschampsia cespitosa and D. flexuosa) in the field, on a moorland in northeastern Scotland. In addition, the interacting effects of increasing nutrients and Calluna canopy height on N. stricta and D. cespitosa were studied using turves in an outdoor experimental area. In the field, fencing had a larger effect than fertilizer on the growth of all species, except for N. stricta, the species most unpalatable to herbivores. Fencing led to an increase in the height of the Calluna canopy, which may reduce light availability for the grasses. In the turf experiment, the height of the Calluna canopy affected the diameter of the grass tussocks and percentage of green matter (i.e. live leaf material), with plants under the more closed Calluna canopies being smaller. This study suggests that the slow‐growing, evergreen Calluna is a more effective competitor than the faster growing grasses when it has a tall, intact canopy, even at increased levels of nutrient supply. However, overgrazing promotes gap formation in the Calluna canopy, providing an opportunity for grasses to take advantage of increased nutrients. Thus the conservation of heather moorlands requires an understanding of the grazing level which allows Calluna to maintain sufficient canopy structure to outcompete grasses for light.     

On the need for a control line in selection experiments: A likelihood analysis

The question of whether selection experiments ought to include a control line, as opposed to investing all facilities in a single selected line, is addressed using a likelihood perspective. The consequences of using a control line are evaluated under two scenarios. In the first one, environmental trend is modeled and inferred from the data. In this case, a control line is shown to be highly beneficial in terms of the efficiency of inferences about eheritability and response to selection. In the second scenario, environmental trend is not modeled. One can imagine that a previous analysis of the experimental data had lent support to this decision. It is shown that in this situation where a control line may seem superfluous, inclusion of a control line can result in minor gains in efficiency if a high selection intensity is practiced in the selected line. Further, if there is a loss, it is moderately small. The results are verified to hold under more complicated data structures via Monte Carlo simulation. For completeness, divergent selection designs are also reviewed, and inferences based on a conditional and full likelihood approach are contrasted.     

Isolation and characterization of microsatellite loci from Lochmaea suturalis, the heather beetle (Coleoptera: Chrysomelidae), a pest in Europe and a biocontrol agent in New Zealand

The heather beetle Lochmaea suturalis which is native to northwest Europe has been released as a biocontrol agent for heather in New Zealand. We have isolated and optimized eight microsatellite loci from New Zealand beetles. These loci provide markers with high polymorphism ranging from four to 20 alleles per locus. Observed heterozygosity averaged 0.631 per locus. These results suggest the markers are useful for population studies that will contribute to assessment of L. suturalis as a biocontrol agent.     

基于结构方程模型分析荒漠啮齿动物优势种对不同放牧干扰的响应

放牧被认为是草地生态系统的主要干扰之一。许多研究表明,放牧影响了啮齿动物的个体条件、繁殖、种群动态、群落组成及群落多样性等多个方面。由于受传统统计学方法的限制,这些研究只是单独的对放牧作用进行假设检验,而没有将多个假设放在同一个框架内进行验证。2006—2011年,采用标志重捕法对内蒙古阿拉善荒漠区不同放牧生境中啮齿动物优势种的数量进行研究并使用结构方程建模的方法将可能影响荒漠啮齿动物优势种的环境因子(气候条件、土壤硬度、植物隐蔽、植物生物量等19个指标)与啮齿动物优势种种群动态结合后进行多假设检验,旨在找出不同放牧干扰下制约优势啮齿动物环境因子的发生途径。结果表明:气候条件对五趾跳鼠和三趾跳鼠有直接不利影响,隐蔽对于两足活动的五趾跳鼠有负效应,而对四足活动的子午沙鼠有正效应。植物生物量对五趾跳鼠有正效应,但对子午沙鼠有负效应。土壤硬度的增加间接的有利于五趾跳鼠,对子午沙鼠有直接的正效应。因此荒漠啮齿动物优势种种群动态是多个过程共同作用的结果,气候条件是驱动啮齿动物种群动态的根本原因,而放牧会因为改变植物隐蔽而影响啮齿动物在群落中的组成。     

Statistical analysis of amounts and ratios in pheromone composition: a mixed model approach

Analysis of variation in pheromone amounts and ratios between individuals is usually performed separately for amounts and ratios of the different components. Non-parametric tests are regularly applied. This way of analysis is statistically correct, yet, limited for several reasons. The use of a parametric linear mixed model approach to analyze both amounts and ratios of different components at the same time is proposed. This method appears to be very flexible and may facilitate the analysis of pheromone data.     

ml‐relate: a computer program for maximum likelihood estimation of relatedness and relationship

Genetic data are useful for estimating the genealogical relationship or relatedness between individuals of unknown ancestry. We present a computer program, ml ‐relate that calculates maximum likelihood estimates of relatedness and relationship. ml ‐relate is designed for microsatellite data and can accommodate null alleles. It uses simulation to determine which relationships are consistent with genotype data and to compare putative relationships with alternatives. ml ‐relate runs on the Microsoft Windows operating system and is available from http://www.montana.edu/kalinowski .     

COANCESTRY: a program for simulating, estimating and analysing relatedness and inbreeding coefficients

The software package COANCESTRY implements seven relatedness estimators and three inbreeding estimators to estimate relatedness and inbreeding coefficients from multilocus genotype data. Two likelihood estimators that allow for inbred individuals and account for genotyping errors are for the first time included in this user-friendly program for PCs running Windows operating system. A simulation module is built in the program to simulate multilocus genotype data of individuals with a predefined relationship, and to compare the estimators and the simulated relatedness values to facilitate the selection of the best estimator in a particular situation. Bootstrapping and permutations are used to obtain the 95% confidence intervals of each relatedness or inbreeding estimate, and to test the difference in averages between groups.     

Mixture model for inferring susceptibility to mastitis in dairy cattle: a procedure for likelihood-based inference

A Gaussian mixture model with a finite number of components and correlated random effects is described. The ultimate objective is to model somatic cell count information in dairy cattle and to develop criteria for genetic selection against mastitis, an important udder disease. Parameter estimation is by maximum likelihood or by an extension of restricted maximum likelihood. A Monte Carlo expectation-maximization algorithm is used for this purpose. The expectation step is carried out using Gibbs sampling, whereas the maximization step is deterministic. Ranking rules based on the conditional probability of membership in a putative group of uninfected animals, given the somatic cell information, are discussed. Several extensions of the model are suggested.     

Comparative methods for the analysis of gene-expression evolution: an example using yeast functional genomic data

Understanding the evolution of gene function is a primary challenge of modern evolutionary biology. Despite an expanding database from genomic and developmental studies, we are lacking quantitative methods for analyzing the evolution of some important measures of gene function, such as gene-expression patterns. Here, we introduce phylogenetic comparative methods to compare different models of gene-expression evolution in a maximum-likelihood framework. We find that expression of duplicated genes has evolved according to a nonphylogenetic model, where closely related genes are no more likely than more distantly related genes to share common expression patterns. These results are consistent with previous studies that found rapid evolution of gene expression during the history of yeast. The comparative methods presented here are general enough to test a wide range of evolutionary hypotheses using genomic-scale data from any organism.     

A bayesian framework for parentage analysis: the value of genetic and other biological data

We develop fractional allocation models and confidence statistics for parentage analysis in mating systems. The models can be used, for example, to estimate the paternities of candidate males when the genetic mother is known or to calculate the parentage of candidate parent pairs when neither is known. The models do not require two implicit assumptions made by previous models, assumptions that are potentially erroneous. First, we provide formulas to calculate the expected parentage, as opposed to using a maximum likelihood algorithm to calculate the most likely parentage. The expected parentage is superior as it does not assume a symmetrical probability distribution of parentage and therefore, unlike the most likely parentage, will be unbiased. Second, we provide a mathematical framework for incorporating additional biological data to estimate the prior probability distribution of parentage. This additional biological data might include behavioral observations during mating or morphological measurements known to correlate with parentage. The value of multiple sources of information is increased accuracy of the estimates. We show that when the prior probability of parentage is known, and the expected parentage is calculated, fractional allocation provides unbiased estimates of the variance in reproductive success, thereby correcting a problem that has previously plagued parentage analyses. We also develop formulas to calculate the confidence interval in the parentage estimates, thus enabling the assessment of precision. These confidence statistics have not previously been available for fractional models. We demonstrate our models with several biological examples based on data from two fish species that we study, coho salmon (Oncorhychus kisutch) and bluegill sunfish (Lepomis macrochirus). In coho, multiple males compete to fertilize a single female's eggs. We show how behavioral observations taken during spawning can be combined with genetic data to provide an accurate calculation of each male's paternity. In bluegill, multiple males and multiple females may mate in a single nest. For a nest, we calculate the fertilization success and the 95% confidence interval of each candidate parent pair.     

The frequency of ion-pair substructures in proteins is quantitatively related to electrostatic potential: a statistical model for nonbonded interactions

A statistical analysis of ion pairs in protein crystal structures shows that their abundance with respect to uncharged controls is accurately predicted by a Boltzmann-like function of electrostatic potential. It appears that the mechanisms of protein folding and/or evolution combine to produce a "thermal" distribution of local nonbonded interactions, as has been suggested by statistical-mechanical theories. Using this relationship, we develop a maximum likelihood methodology for estimation of apparent energetic parameters from the data base of known structures, and we derive electrostatic potential functions that lead to optimal agreement of observed and predicted ion-pair frequencies. These are similar to potentials of mean force derived from electrostatic theory, but departure from Coulombic behavior is less than has been suggested.