Modeling of inorganic contaminant transport in dense bentonite

To assess the safety of the waste disposal site, a knowledge of the molecular diffusion coefficient through the bentonite‐clay barrier is required. The methods commonly used to determine molecular diffusion coefficient in clay are very time consuming. Because of the large number of species involved in the radioactive waste disposal site, a model that allows diffusion coefficient to be predicted for use is desirable. Models based on free water have been proposed but are found to be inadequate for compacted bentonitic clays. A model that incorporates clay‐species‐water interaction is presented for dense bentonite. The modeling results show that the diffusion coefficient depends on the charge nature and size of the diffusing species, water chemistry, temperature, and soil structure. The predicted diffusion coefficients for some species are shown to be in excellent agreement with those measured in dense bentonite.     

利用分布有/无数据预测物种空间分布的研究方法综述

详细的物种地理分布信息是生态学研究和制定保护策略的基础。相比较于直接估测种群数量,获取物种分布的有/无数据更为实用。因此,利用分布有/无数据并结合环境变量建立模型预测物种空间分布的方法在近年来得到了长足发展,并被广泛应用。利用分布有/无数据预测物种分布,关键的步骤包括：1)构建总体概念模型,2)收集物种分布有/无数据,并准备环境变量图层;3)选择合适的统计模型和算法,以及4)对模型进行评估。概念模型提出研究假设,并确定数据收集及模型方法。收集物种分布数据有系统调查及非系统调查方法。筛选并准备与物种分布相关的环境变量,利用GIS工具处理,使之成为符合模型条件的具有合适的空间尺度的数字化图层。利用环境变量和物种分布有/无的数据,选择合适的方法及软件建立模型,并对模型进行检验和评估。我们总结了用于构建物种分布模型的不同算法和软件。本文将针对以上各个环节,阐述利用物种分布有/无数据进行研究所需要的技术细节,以期望为读者提供借鉴。     

How valuable are model organisms for transposable element studies?

Model organisms have proved to be highly informative for many types of genetic studies involving ‘conventional’ genes. The results have often been successfully generalized to other closely related organisms and also, perhaps surprisingly frequently, to more distantly related organisms. Because of the wealth of previous knowledge and their availability and convenience, model organisms were often the species of choice for many of the earlier studies of transposable elements. The question arises whether the results of genetic studies of transposable elements in model organisms can be extrapolated in the same ways as those of conventional genes? A number of observations suggest that special care needs to be taken in generalizing the results from model organisms to other species. A hallmark of many transposable elements is their ability to amplify rapidly in species genomes. Rapid spread of a newly invaded element throughout a species range has also been demonstrated. The types and genomic copy numbers of transposable elements have been shown to differ greatly between some closely related species. Horizontal transfer of transposable elements appears to be more frequent than for nonmobile genes. Furthermore, the population structure of some model organisms has been subject to drastic recent changes that may have some bearing on their transposable element genomic complements. In order to initiate discussion of this question, several case studies of transposable elements in well-studied Drosophila species are presented.     

Modeling species distributions by breaking the assumption of self-similarity

Species distributions are commonly measured as the number of sites, or geographic grid cells occupied. These data may then be used to model species distributions and to examine patterns in both intraspecific and interspecific distributions. Harte et al. (1999) used a model based on a bisection rule and assuming self-similarity in species distributions to do so. However, this approach has also been criticized for several reasons. Here we show that the self-similarity in species distributions breaks down according to a power relationship with spatial scales, and we therefore adopt a power-scaling assumption for modeling species occupancy distributions. The outcomes of models based on these two assumptions (self-similar and power-scaling) have not previously been compared. Based on Harte's bisection method and an occupancy probability transition model under these two assumptions (self-similar and power-scaling), we compared the scaling pattern of occupancy (also known as the area-of-occupancy) and the spatial distribution of species. The two assumptions of species distribution lead to a relatively similar interspecific occupancy frequency distribution pattern, although the spatial distribution of individual species and the scaling pattern of occupancy differ significantly. The bimodality in occupancy frequency distributions that is common in species communities, is confirmed to a result for certain mathematical and statistical properties of the probability distribution of occupancy. The results thus demonstrate that the use of the bisection method in combination with a power-scaling assumption is more appropriate for modeling species distributions than the use of a self-similarity assumption, particularly at fine scales.     

Can You Judge a Disease Host by the Company It Keeps? Predicting Disease Hosts and Their Relative Importance: A Case Study for Leishmaniasis

Zoonoses are an important class of infectious diseases. An important element determining the impact of a zoonosis on domestic animal and human health is host range. Although for particular zoonoses some host species have been identified, until recently there have been no methods to predict those species most likely to be hosts or their relative importance. Complex inference networks infer potential biotic interactions between species using their degree of geographic co-occurrence, and have been posited as a potential tool for predicting disease hosts. Here we present the results of an interdisciplinary, empirical study to validate a model based on such networks for predicting hosts of Leishmania (L.) mexicana in Mexico. Using systematic sampling to validate the model predictions we identified 22 new species of host (34% of all species collected) with the probability to be a host strongly dependent on the probability of co-occurrence of vector and host. The results confirm that Leishmania (L.) mexicana is a generalist parasite but with a much wider host range than was previously thought. These results substantially change the geographic risk profile for Leishmaniasis and provide insights for the design of more efficient surveillance measures and a better understanding of potential dispersal scenarios.     

Testing the success of palaeontological methods in the delimitation of clam shrimp (Crustacea,Branchiopoda) on extant species

Fossil spinicaudatan taxonomy heavily relies on carapace features (size, shape, ornamentation) and palaeontologists have greatly refined methods to study and describe carapace variability. Whether carapace features alone are sufficient for distinguishing between species of a single genus has remained untested. In our study, we tested common palaeontological methods on 481 individuals of the extant Australian genus Ozestheria that have been previously assigned to ten species based on genetic analysis. All species are morphologically distinct based on geometric morphometrics (p ≤ 0.001), but they occupy overlapping regions in Ozestheria morphospace. Linear discriminant analysis of Fourier shape coefficients reaches a mean model performance of 93.8% correctly classified individuals over all possible 45 pairwise species comparisons. This can be further increased by combining the size and shape datasets. Nine of the ten examined species are clearly sexually dimorphic but male and female morphologies strongly overlap within species with little influence on model performance. Ornamentation is commonly species-diagnostic; seven ornamentation types are distinguished of which six are species-specific while one is shared by four species. A transformation of main ornamental features (e.g. from punctate to smooth) can occur among closely related species suggesting short evolutionary timescales. Our overall results support the taxonomic value of carapace features, which should also receive greater attention in the taxonomy of extant species. The extensive variation in carapace shape and ornamentation is noteworthy and several species would probably have been assigned to different genera or families if these had been fossils, bearing implications for the systematics of fossil Spinicaudata.     

A study of prey-predator relations for mammals

In this paper, we present a prey-predator nonlinear model for mammals, consisting of large- and small-size prey species with group defence, in a partially protected habitat. If the prey size is small, then it is more prone to the predator at higher densities. Conversely, large prey size at higher densities tend to develop group defence. Therefore, the predator will be attracted towards that area where prey are less in number. A new physical constant has been introduced into the radiation-type condition on that part of the boundary where interaction between prey and predator takes place. This constant allows us to efficiently model group defence capabilities of the herds and its numerical values have to be determined for different pairs of prey-predator species from field observations. A way of measuring the constants involved in the model is suggested. Numerical results are provided and thoroughly discussed for a habitat of circular shape. The obtained results show that in the region away from the protected area, the density of large-size prey species is higher than that of small-size prey species, a fact that is in accordance with observations.     

Simplification of Stochastic Chemical Reaction Models with Fast and Slow Dynamics

Biological systems often involve chemical reactions occurring in low-molecule-number regimes, where fluctuations are not negligible and thus stochastic models are required to capture the system behaviour. The resulting models are generally quite large and complex, involving many reactions and species. For clarity and computational tractability, it is important to be able to simplify these systems to equivalent ones involving fewer elements. While many model simplification approaches have been developed for deterministic systems, there has been limited work on applying these approaches to stochastic modelling. Here, we describe a method that reduces the complexity of stochastic biochemical network models, and apply this method to the reduction of a mammalian signalling cascade and a detailed model of the process of bacterial gene expression. Our results indicate that the simplified model gives an accurate representation for not only the average numbers of all species, but also for the associated fluctuations and statistical parameters.     

STORM: a general model to determine the number and adaptive changes of epithelial stem cells in teleost, murine and human intestinal tracts

Intestinal stem cells play a pivotal role in the epithelial tissue renewal, homeostasis and cancer development. The lack of a general marker for intestinal stem cells across species has hampered analysis of stem cell number in different species and their adaptive changes upon intestinal lesions or during development of cancer. Here a two-dimensional model, named STORM, has been developed to address this issue. By optimizing epithelium renewal dynamics, the model examines the epithelial stem cell number by taking experimental input information regarding epithelium proliferation and differentiation. As the results suggest, there are 2.0-4.1 epithelial stem cells on each pocket section of zebrafish intestine, 2.0-4.1 stem cells on each crypt section of murine small intestine and 1.8-3.5 stem cells on each crypt section of human duodenum. The model is able to provide quick results for stem cell number and its adaptive changes, which is not easy to measure through experiments. Its general applicability to different species makes it a valuable tool for analysis of intestinal stem cells under various pathological conditions.     

A General and Dynamic Species Abundance Model, Embracing the Lognormal and the Gamma Models

One aspect of community ecology that has been given particular attention is the pattern of species abundances in a community. The species may have a wide range of abundances; some are very common and others rare. When species abundance models are fitted to observations, the lognormal model and one of the gamma models (e.g., the log-series model) are usually applied. The model that gives the best fit according to some goodness-of-fit test is then chosen. By applying a diffusion approximation for each species' dynamics with density regulation of the straight theta-logistic type, we here present a general species abundance model that embraces the two most widely applied species abundance models, the lognormal and the gamma. Our general model will, therefore, provide a better fit than the two special cases, except when it corresponds to one of them. In contrast to the classical models, ours is also dynamic, making it possible to evaluate the fluctuations in species abundance over time through both biotic and abiotic factors. The model is fitted to several species abundance data sets and our results compared to previous attempts to fit a model, usually either the lognormal or the log-series.     

Interspecific pregnancy: barriers and prospects

Investigations on the mechanisms that allow survival of the fetal allograft have been extended by pregnancies in which the fetus and pregnant female are from different species. Such interspecific pregnancies are useful models for the study of maternal/fetal interactions and also may assist in the preservation of endangered species. Results of experiments with three different interspecific model systems are discussed: a murine model using Mus musculus and M. caroli; an equine model involving primarily the domestic horse and donkey, but including several wild Equidae; and a bovid model that crosses genera--pregnancy between the domestic sheep and goat. Species differences are reflected in results of experiments involving the various models. An immunological barrier appears to restrict interspecific pregnancy, but how the barrier is manifested appears to differ with species. Evidence for inappropriate interaction between trophoblast and endometrium is also presented. Results of experiments aimed at overcoming barriers to interspecific reproduction are discussed.     

基于三个分子标记的粉毛蚜亚科DNA条形码

【目的】粉毛蚜亚科昆虫是重要的林业害虫,但是由于蚜虫体型较小,形态特征趋于简化,可用于物种鉴定的有效特征非常有限,因此一般基于外部形态特征难以对蚜虫物种实现快速准确的鉴定。本研究获取该亚科2属10种的DNA条形码标准序列,解决部分物种的分类问题,同时比较了3种标记对粉毛蚜亚科（Pterocommatinae）物种快速鉴定的效率。【方法】基于蚜虫的线粒体细胞色素氧化酶C亚基I（cytochrome oxidase subunit I, COI）基因、细胞色素b（cytochrome b, Cytb）基因和蚜虫初级内共生菌Buchnera 6-磷酸葡萄糖酸脱氢酶（gluconate-6-phosphate dehydrogenase, gnd）基因,对2属10种共197号样品进行NJ分析、遗传距离的计算以及基于相似性的物种鉴定分析。【结果】与K-2P模型相比,基于p-distance模型计算得到的遗传距离更小,序列差异频次图上种内距离与种间距离的重叠区域也小于前者;COI序列的物种鉴定成功率最高。获取了粉毛蚜亚科近200条DNA条形码标准序列,并建立了基于3个标记的该亚科物种DNA条形码序列库。【结论】在粉毛蚜亚科DNA条形码研究中,p-distance模型要优于K-2P模型;COI序列具有最高的条形码分析效率;增毛卷粉毛蚜Plocamaphis assetacea可能为蜡卷粉毛蚜Plocamaphis flocculosa的同物异名。     

种群生存力分析:准确性和保护应用

目前已提出了五类估计濒危物种绝灭风险的种群生存力分析模型 ,即 :分析模型、单种群确定性模型、单种群随机模型、异质种群模型和显空间模型。模型的选择取决于物种的生活史特征和可用的数据。与用于保护实践的其他方法相比 ,种群生存力分析 (PVA)是相对准确的量化工具。然而 ,一些濒危物种种群统计学数据质量差和种群动态的有关假说模糊不清可能影响到模型预测的准确性 ,因此 ,要谨慎地使用PVA。在西方国家 ,PVA在濒危物种保护计划和管理中应用越来越广泛。它主要用于 :( 1)预测濒危物种未来的种群大小 ;( 2 )估计一定时间内物种的绝灭风险 ;( 3 )评估一套保护措施 ,确定哪个能使种群的存活时间最长 ;( 4)探索不同假说对小种群动态的影响 ;( 5 )指导濒危动物野外数据的搜集工作。我国的濒危物种很多 ,然而开展PVA研究的濒危物种却很少。应大力发展适合于模拟我国特有濒危物种及其保护问题的PVA模型     

东北4种林木干基腐朽病原真菌潜在分布范围预测及其生态位分析

东北地区木生真菌物种资源丰富, 包括了数十种林木干基腐朽病原真菌。过去对该类真菌曾进行多次调查, 获取了大量物种分布数据, 但对于非重点调查区域是否存在某种真菌物种却不明确。本文选取东北地区具有代表性的4种林木干基腐朽病原真菌, 即红缘拟层孔菌(Fomitopsis pinicola)、落叶松锈迷孔菌(Porodaedalea laricis)、桦剥管孔菌(Piptoporus betulinus)和香栓孔菌(Trametes suaveolens), 根据其地理分布数据和分布地的环境因子数据, 以最大熵模型(MaxEnt)对这些种类在东北地区可能的分布范围进行了模拟预测, 以曲线下面积(area under the receiver operating characteristic curve, AUC)对模型有效性进行评价, 并对各物种的生态位进行了分析。结果显示, 以MaxEnt方法获得的各物种预测模型均获得了较高的AUC值, 分别为0.990, 0.990, 0.989和0.967, 表明4种林木干基腐朽病原真菌预测模型的有效性较高。物种分布模型涉及的环境变量对模型的贡献率显示, 最暖季降水量(Bio18)、温度的年较差(Bio7)、最干季均温(Bio9)等变量对各物种模型贡献率较高。该研究结果为预测4种病原真菌在东北地区的分布范围和科学防治该类病原真菌提供了依据。     

栖息地毁坏与动物物种灭绝关系的模拟研究

利用多个物种共存模式模拟了不同情况下的不同动物种群演化的动力学特性,研究结果表明：（1）由于栖息地的毁坏所导致的动手的种灭绝是依赖于对物种死亡率和有关平衡态的假设的,不同的假设下,既使栖息地的破坏率相同,灭绝的物种可能是竞争能力最强的若干物种,也可能是竞争能力相对较弱的若干物种,既不象传统的物种进化理论所认为的必是弱的物种先灭绝,也不象Tilman等人所认为的一定是最强的若干物种先灭绝;（2）如果弱的物种具有较高的平均死亡率,则当栖息地受到一定的毁坏时,将有较多强的物种灭绝,而且物种灭绝时间将大大缩短;（3）在物种死亡率不变的情形下,物种在未受毁坏栖息地上的平衡态和大占有率pl^0,将有利于物种的生存。     

Species richness correlates of raw and standardized co‐occurrence metrics

Measuring β‐diversity and changes in species composition across multiple sites and environments is a major research focus in macroecology, and a variety of metrics have been proposed to quantify species co‐occurrence patterns in a species × site occurrence matrix. However, indices of β‐diversity and species co‐occurrence are often statistically dependent on the number of species in an assemblage. We compared the results of several common co‐occurrence metrics with patterns generated by a spatially explicit neutral model simulation. We found that all measures of co‐occurrence and β‐diversity, whether raw, rescaled or standardized by a null model expectation, were highly correlated with the total species richness of the landscape. The one important exception were the effect sizes of the fixed–fixed null model algorithm, which preserves row and column sums of the original matrix during matrix randomization. Our results call for a careful interpretation of meta‐analyses of assemblages that differ widely in species richness. At a minimum, observed species richness should be used as a statistical covariate in regression analyses, and results of the fixed–fixed algorithm should be compared carefully with the results of other randomization tests.     

An evaluation of a GARP model as an approach to predicting the spatial distribution of non-vagile invertebrate species

One of the primary goals of any systematic, taxonomic or biodiversity study is the characterization of species distributions. While museum collection data are important for ascertaining distributional ranges, they are often biased or incomplete. The Genetic Algorithm for Rule-set Prediction (GARP) is an ecological niche modelling method based on a genetic algorithm that has been argued to provide an accurate assessment of the spatial distribution of organisms that have dispersal capabilities. The primary objective of this study is to evaluate the accuracy of a GARP model to predict the spatial distribution of a non-invasive, non-vagile invertebrate whose full distributional range was unknown. A GARP predictive model based on seven environmental parameters and 42 locations known from historical museum records for species of the trapdoor spider genus Promyrmekiaphila was produced and subsequently used as a guide for ground truthing the model. The GARP model was neither a significant nor an accurate predictor of spider localities and was outperformed by more simplistic BIOCLIM and GLM models. The isolated nature of Promyrmekiaphila populations mandates that environmental layers and their respective resolutions are carefully chosen for model production. Our results strongly indicate that, for modelling the spatial distribution of low vagility organisms, one should employ a modelling method whose results are more conducive to interpretation than models produced by a 'black box' algorithm such as GARP.     

Predicting the species composition of Nardus stricta communities by logistic regression modelling

Question: Predictive models in plant ecology usually deal with single species or community types. Little effort has so far been made to predict the species composition of a community explicitly. The modelling approach presented here provides a conceptual framework on how to achieve this by combining habitat models for a large number of species to an additive community model. Our approach is exemplified by Nardus stricta communities (acidophilous, low‐productive grassland). Location: Large areas of Germany, 0–2040 m a.s.l. Methods: Logistic regression is applied for individual species models which are subsequently combined for an explicit prediction of species composition. Several parameters reflecting soil, management and climatic conditions serve as predictor variables. For validation, bootstrap and jackknife resampling procedures are used as well as ordination techniques (DCA, CCA). Results: We calculated significant models for 138 individual species. The predictions of species composition and species richness yield good agreements with the observed data. DCA and CCA results show that the community model preserves the main patterns in floristic space. Conclusions: Our approach of predicting species composition is an effective tool that can be applied in nature conservation, e.g. to assess the effects of different site conditions and alternative management scenarios on species composition and richness.     

Coexistence, saturation and invasion resistance in simulated plant assemblages

A popular hypothesis is that species-rich systems are less susceptible to invasion. This hypothesis is based on the idea that species richness correlates with community saturation so that establishment by a new species is more difficult in saturated communities. Little attention has been focussed on how changing assumptions about the processes regulating species richness will alter community properties such as invasion resistance. Here, we simulate plant community assembly using four models that have different underlying coexistence mechanisms (and so differ in the amount of available niche space) and subject them to invasion. We created species richness gradients by comparing between models or by considering the output of a single model with different parameter values. We found that the relation between species richness and invasion resistance depends critically on the model considered and the cause of the species richness gradient. Overall, our results suggest that species richness does not necessarily correlate with saturation and is likely to be a poor predictor of invasion resistance. These results provide a possible explanation for the variety of outcomes reported in recent experimental and observational studies that examine the relationship between species richness and invasion resistance. We conclude that consideration of the processes regulating species richness is crucial for a successful understanding of invasion resistance along species richness gradients.