An overview of closed capture-recapture models

This article reviews various models for both discrete-time and continuous-time closed capture-recapture experiments. The traditional discrete-time models assume that the samples are independent. Dependence may be caused by local dependence (list dependence) within each animal or by heterogeneity among animals. Three different approaches that can incorporate dependence into models are reviewed, i.e., ecological models, log-linear models, and the sample-coverage approach. The statistical tools involved in population size estimation in these three approaches cover a wide range of methodologies. There has been relatively little published research for the continuous-time counterparts. The counting process approach, which is the framework for most existing estimation procedures for continuous-time models, is reviewed. The connection of continuous-time models to recurrent event analysis in the context of failure time inferences is discussed. The applications of capture-recapture models to other disciplines are briefly presented. Remarks about the limitations of the models are made and some future research directions are also suggested.     

Metals and acidification: An overview

Both upland soils and lake sediments appear to retain atmospherically deposited trace metals (e.g. Pb) even under acid conditions. The abundant, local, mineralogically derived metals (e.g. Al and Mn) are exported from upland soils under acidic conditions, but are usually retained by lake sediments. Acidification, however, reduces the extent of retention in lake sediments and soils, potentially inducing elevated metal levels in lake water. Only under conditions of extreme acidification and with the more mobile metals do lakes become net exporters of metals. Surface depletion of metals in sediment cores may not be the result of recent acidification.     

An overview: Impact of environmental regulations

An overview of environmental concerns shows the grave consequences of overregulation and the current adversary postures of industry and government. Political action is often taken on the basis of preliminary research findings that have been extrapolated beyond scientific prudence. Ecological processes are so complex and man's impact so pervasive that actions based upon political expediency can often do more harm than good. The overview will include examples relating to energy, pollution, chemicals, and the impact on engineers and scientists.     

An overview: recycling nutrients from crop residues for space applications

Without some form of regenerative life support system, long duration space habitation or travel will be limited severely by the prohibitive costs of resupplying air, water, and food from Earth. Components under consideration for inclusion in a regenerative life support system are based on either physicochemical or biological processes. Physicochemical systems would use filtration and elemental phase changes to convert waste materials into usable products, while biological systems would use higher plants and bioreactors to supply crew needs. Neither a purely biological nor strictly a physicochemical approach can supply all crew needs, thus, the best each approach can offer will be combined into a hybrid regenerative life support system. Researchers at Kennedy Space Center (KSC) Advanced Life Support Breadboard Project have taken the lead on bioregenerative aspects of space life support. The major focus has been on utilization of higher plants for production of food, oxygen, and clean water. However, a key to any regenerative life support system is recycling and recovery of resources (wastes). In keeping with the emphasis at KSC on bioregenerative systems and with the focus on plants, this paper focuses on research with biologically-based options for resource recovery from inedible crop residues.     

Statistical models for exposure-biomarker relationships with measurement error and censoring

Measurements of biomarkers have been used, in conjunction with those of external exposure, to provide information about the rates of human uptake, bioactivation, and detoxification of chemicals. Direct knowledge of these processes is valuable because it can reduce reliance on animal models for making extrapolations about disease risks in humans. In practice, however, valid and precise quantification of exposure—biomarker relationships has been hampered by a number of problems. These include errors in the measurement of true mean exposure and true mean biomarker levels, nonlinear exposure—biomarker relationships, background biomarker levels in unexposed individuals, and response levels that fall below analytic limits of detection. In this article we develop nonlinear mixed models and corresponding likelihood expressions that can address these concerns, and we describe maximum likelihood estimation techniques that permit valid statistical inferences to be made using standard software. The models and methods are applied to both experimental and simulated exposure—biomarker data to illustrate their utility and limitations.     

Adaptive spatio-temporal models for satellite ecological data

This article develops models for environmental data recorded by meteorological satellites. In general, such data are continuously available for suitable space and time units and are intrinsically nonstationary. Space-time auto-regression (STAR) is a class of models that can be used in monitoring and forecasting, but it must be adapted to nonstationary processes. A set of adaptive recursive estimators is then proposed to estimate STAR parameters that change both over space and time. An extensive application to the normalized difference vegetation index (NDVI), for a region of sub-Saharan Africa, illustrates and checks the approach.     

Closed mark-recapture models to estimate species richness: An example using data on epigeal spiders

Species richness is a fundamental ecological property. The problem of estimating the number of species is quite similar to that of estimating the population size of a single species. Some authors of mark-recapture statistics have proposed using some of these methods to estimate species richness. This necessitates understanding how the recording probabilities of individuals differ from those of species. In particular, the species of a species pool are likely to exhibit a wide range of recording probabilities. Depending on sampling conditions, temporal or spatial variation in species detection probability may also occur, making model M _th estimators particularly useful. Empirical detection probabilities and estimates of species numbers using three coverage, one point, and two jackknife estimators are presented for series of spatial and temporal trapping occasions of epigeal spiders.     

Biochemical aspects of nitrogen use efficiency: An overview

Crop productivity relies heavily on nitrogen (N) fertilization. N is an essential macronutrient limiting the growth and development of plants in agriculture. Both organic and inorganic forms of N are metabolized in plants; nitrate and ammonia are common forms of inorganic N that can be metabolized in all plants. In the last 40 years the amount of synthetic N applied to crops has risen dramatically, resulting in significant increases in yield but with considerable impacts on the environment. Production and application of N fertilizers consume huge amounts of energy, and excess is detrimental to the environment. A requirement for crops that require decreased N fertilizer levels has been recognized in the call for a ‘Second Green Revolution’ and research in the field of nitrogen-use efficiency (NUE) has continued to grow. Nitrogen-use efficiency is inherently a complex trait, as each step-including N uptake, translocation, assimilation, and remobilization-is governed by multiple interacting genetic and environmental factors. The limiting factors in plant metabolism for maximizing NUE are different at high and low N supplies, indicating great potential for improving the NUE of present cultivars. Decreasing environmental losses and increasing the productivity of crop-acquired N requires the coordination of carbohydrate and N metabolism to give high yields. This has prompted a search to identify genes that improve the NUE of crop plants, with candidate NUE genes existing in pathways relating to N uptake, assimilation, amino acid biosynthesis, carbon (C)/N storage and metabolism, signaling and regulation of N metabolism and translocation, remobilization and senescence. In this review, we present the over view of N metabolism, relation of C/N metabolism and future prospects of improving NUE in crops using various complementary approaches.     

Choosing models for soil chronofunctions and fitting them to data

The effectiveness and utility of soil chronofunctions is examined in the light of existing pedogenic theory. Statistical treatments applied in chronofunction research are reviewed, including linear transformations of raw data, which may improve the utility of the chronofunction. We advocate using a particular statistical model only if it can be justified based on our current understanding of the functioning of the pedologic system. We emphasize the potential difficulties of using linear chronofunction methods; simple linear and logarithmic functions are not always the best option for chronofunctions. Hyperbolic, polynomial or nonlinear functions might improve not only the fit of the chronofunction but also advance our understanding of the pedologic system. When the chronofunction explaining the most variance is not best suited to a process-based understanding of pedogenic theory, other functions with slightly smaller r² values that have been judged suitable by a priori reasoning or theory might better reflect the functioning of the pedologic system. We justify limited extrapolation of some chronofunctions to time zero and discuss how this can be useful in the identification of pedogenic thresholds and ‘step functions’. Interpretation of the Y-intercept of chronofunctions can, at times, aid our understanding of the soil system near time zero and be useful in the identification of the existence and timing of thresholds.     

Response of zooplankton,benthos, and fish to acidification: An overview

This paper presents an overview of the response to acidification of aquatic fauna with special emphasis on Zooplankton, benthos, and fishes. Changes in behavior, body chemistry, reproduction, and species diversity are presented based on laboratory experiments and field studies in both Europe and North America. Differences in species sensitivity are discussed as they relate, not only to acidification but also to low calcium concentrations in the water, elevated aluminum concentrations, and presence of naturally occurring organic acids. The mechanisms—behavioral, physiological and ecological—enabling aquatic fauna to survive in acidified waters are discussed.     

Empirical Bayes analysis of variance component models for microarray data

A gene-by-gene mixed model analysis is a useful statistical method for assessing significance for microarray gene differential expression. While a large amount of data on thousands of genes are collected in a microarray experiment, the sample size for each gene is usually small, which could limit the statistical power of this analysis. In this report, we introduce an empirical Bayes (EB) approach for general variance component models applied to microarray data. Within a linear mixed model framework, the restricted maximum likelihood (REML) estimates of variance components of each gene are adjusted by integrating information on variance components estimated from all genes. The approach starts with a series of single-gene analyses. The estimated variance components from each gene are transformed to the “ANOVA components”. This transformation makes it possible to independently estimate the marginal distribution of each “ANOVA component.” The modes of the posterior distributions are estimated and inversely transformed to compute the posterior estimates of the variance components. The EB statistic is constructed by replacing the REML variance estimates with the EB variance estimates in the usual t statistic. The EB approach is illustrated with a real data example which compares the effects of five different genotypes of male flies on post-mating gene expression in female flies. In a simulation study, the ROC curves are applied to compare the EB statistic and two other statistics. The EB statistic was found to be the most powerful of the three. Though the null distribution of the EB statistic is unknown, a t distribution may be used to provide conservative control of the false positive rate.     

Intercluster correlations for binomial data: An application to Seed Testing

Certification of crop seeds from a seed lot requires determination of the seed germination rate through tests governed by the International Seed Testing Association (ISTA) and the Association of Official Seed Analysts (AOSA). The results from four tests of 100 seeds each are compared with published tolerances to determine whether seed lots concur with a labeled germination rate. Examination of results from numerous corn and soybean seed lots sent to more than 30 member laboratories of the AOSA and the Society of Commercial Seed Technologists (SCST) suggested that, in aggregate, counts reported by the laboratories frequently show less sample variability than expected under independentbinomial sampling due to positive correlation among the individual test results. Whereas much of the recent literature on correlated binomial data is concerned with efficient methods for estimating the binomial success probabilities, comparatively little attention is paid to the problem of diagnosing whether correlations exist and are significant. Considering the replicate tests as clusters, we propose an estimator for the intercluster (interreplicate count) correlation coefficient and examine its statistical properties. Results from applying the estimator in unblinded and blinded seed tests are presented. The results are revealing; the estimates tend to be larger and significant in the unblinded seed tests.     

Soil colour: its measurement and its designation in models of uniform colour space

The principles of colour perception are outlined and applied to the problems of soil colour measurement using ‘Munsell Soil Color Charts’. As care is needed in using these charts to make an accurate assessment of soil colour, recommendations for the correct methods for soil colour measurement are outlined. The three soil colour characteristics of Munsell Hue, Value and Chroma are commonly used in multivariate analyses as orthogonal, equi-dimensional, linear variables that describe perceived colour space. Such an approach may be inappropriate because the angular separation of Hue and an approximately 2.5:1 scaling relationship between Value and Chroma should be accounted for in any model of perceived colour space. An appropriate and simple polar transformation of Munsell colour data is compared with some other coordinate systems for representing colour space, including the CIELAB system. This polar transformation is recommended for processing colour data in multivariate analyses.     

种子引发对小麦抗盐及抗旱特性影响综述

小麦是我国北方重要粮食作物,在农业生产中经常受到干旱和盐分胁迫影响,造成减产。种子引发是在种子萌发前用天然或人工合成试剂对种子进行处理,从而提高植物抗逆性的一种简单而有效的方法。在干旱或高盐条件下,利用引发剂对小麦种子引发后,种子萌发提前,幼苗生长发育代谢增强,抗逆境相关生理指标提升,作物抗旱耐盐能力增强,最终产量及质量得到提高。本文阐述了水、有机物、植物激素、生物活性物质、生物、氧化物、无机信号物质等不同种类引发剂对小麦种子引发的作用机理和效果。并总结了种子引发的主要作用机制,如:减少植株对Na~+的吸收,增加对K~+、Ca~(2+)的吸收,减少盐分对生长造成的阻碍;促进可溶性蛋白和可溶性糖等渗透调节物质的合成和积累,细胞内维持高渗透压,有利于根系吸水;诱使胁迫条件下细胞内超氧化物歧化酶、过氧化物酶、过氧化氢酶、抗坏血酸过氧化物酶等抗氧化酶的合成增多、活性增强,有效清除活性氧,维持细胞内氧平衡;调节植物内源激素合成与运输从而使激素水平处于更加适应胁迫条件的平衡状态等。并讨论了引发剂与植物逆境生理研究之间相互补充、相互促进的关系,展望了种子引发在农业方面的发展及应用前景。     

An improved method for combining map data

Abstract. A system is described using data processed to combine maps from different sources in order to meet specific needs. The system, known as the KALEIDOS-INRA system, has many advantages over traditional map making and provides the user with better information. Its value is illustrated by a map showing the risk of drought to crops growing in central France.     

基于气温估算参考作物蒸散量方法的对比与改进

为提高基于气温数据估算参考作物蒸散量(ET0)模型的精度,该研究对比分析了基于温度数据估算ET0的Penman-Monteith(PMT)模型、Hargreaves-Samani(HS)模型和改进HS模型,并运用基于气温数据估算实际水汽压和太阳辐射的最新进展改进PMT模型.结果表明:改进HS模型较传统HS模型提高了半干...     

Acid precipitation and its influence upon aquatic ecosystems — An overview

The impact of acid precipitation reflects a usually deleterious balance between good and bad effects which may lead to serious and sometimes extreme degradation of aquatic as well as terrestrial ecosystems, particularly around metal smelters. Addition of H ions as H₂SO₄, HNO₃, and HCl can alter and impoverish the species composition of biotic communities, and lead to severe leaching of beneficial metal cations such as Ca from ecosystems. Heavy metals and other trace elements which accompany acid precipitation may reach toxic levels, particularly where acid fallout leaches additional amounts from the soil into streams and lakes. Complex and often toxic hydrocarbons also comprise a little known organic component of acid precipitation. Alternatively, acid precipitation usually is enriched in plant nutrients such as nitrate- and ammonia-nitrogen, K, Ca, and S; and at certain concentrations some of the associated trace elements may also be beneficial. Moreover the initial effect of soil leaching by acid fallout may be to enrich aquatic ecosystems in metal cations such as Ca. Basic materials in air pollution, biogenic NH₃ from the soil, dust fall from arid regions, and soils rich in adsorbed metal cations or in carbonates may neutralize some of the harmful effects of acid precipitation upon ecosystems. However, associated heavy metals, other trace elements, and toxic hydrocarbons may still constitute serious problems in many environments.