Towards identifying pathogenic determinants of the chickpea pathogen <Emphasis Type="Italic">Ascochyta rabiei</Emphasis>

Ascochyta blight is a serious disease of cool-season grain legumes (chickpea, faba bean, lentil and pea) caused by fungal species of the anamorphic genus Ascochyta and related genera. Despite extensive studies on the biology, ecology, epidemiology and management of the disease, little is known about the pathogenic determinants of these pathogens. This research aims at using Ascochyta rabiei as a model for the genus in investigating genetic factors of pathogenicity, with the ultimate goal of elucidating pathogenic mechanisms. Three advances were made: (1) insertional mutants with altered pathogenicity were identified through in vivo screening, and genomic regions adjacent to the insertion sites in selected mutants were determined; (2) a phage library of A. rabiei genomic DNA was constructed, and the library was estimated to provide complete coverage of the A. rabiei genome. This library was used successfully to recover clones with DNA adjacent to insertional mutation sites and to isolate specific genes; (3) DNA probes specific for an acyl-CoA ligase (cps1) and a polyketide synthase gene (pks1) were developed and library clones containing the corresponding genomic regions were identified from the phage library. These advances provide the foundation and necessary tools for experimentation of ectopic complementation assays and targeted mutagenesis to elucidate the genetic mechanisms of pathogenicity of A. rabiei.     

表证动物模型研究概况

中兽医对表证动物模型的研究相对起步较晚，自1992年沈映君等为研究解表方药报道建立“类表寒证”、“类表热证”动物模型以来，风寒表证、风热表证、卫气（阳）虚证等相关动物模型的研究陆续见诸报道。笔者将近10余年来表证动物模型的研究概况综述如下。     

公鸡和母鸡氮代谢及氮维持需要量的比较研究

试验采用氮平衡试验研究产蛋高峰期罗曼公、母鸡的氮维持需要量(Nm),并分析公、母鸡氮代谢的变化规律。试验选取27周龄健康的公、母鸡各30只,分别分为5个处理,每处理6个重复,每个重复1只试鸡,对公、母鸡分别饲喂5个不同粗蛋白质水平的试验日粮。结果表明:相同蛋白水平处理组的公鸡氮食入量和氮沉积率均高于母鸡的结果。母鸡和公鸡的氮食入量(NI)与氮沉积量(NB)间的回归方程分别为NB=0.3743NI-0.1589(R2=0.79)和NB=0.6228NI-0.3151(R2=0.85)。母鸡和公鸡的氮维持需要量分别为每天0.4245g和0.5059g;每千克体重0.2364g和0.2754g;每千克代谢体重0.2739g和0.3208g。     

牛瑟氏泰勒虫P33表面蛋白基因的克隆与序列分析

为分析吉林省流行的牛瑟氏泰勒虫基因序列，根据GenBank上发表的牛瑟氏泰勒虫P33表面蛋白基因序列设计合成一对引物，用PCR方法扩增出牛瑟氏泰勒虫的基因片段，并成功地将该基因纯化后克隆到pGEM-TEasy载体上，将经EcoRⅠ酶切鉴定和PCR鉴定为阳性的重组质粒进行测序。结果表明克隆的基因片段长度为868bp，编码283个氨基酸，有2个潜在的糖基化位点。核苷酸同源性分析表明，该基因片段与韩国株（AF521557）、日本株（AB016280）、俄罗斯株（AB016279）的核苷酸序列同源性分别为99．4％、88.0％、88．1％。     

Simulating the cumulative effects of multiple forest management strategies on landscape measures of forest sustainability

While the cumulative effects of the actions of multiple owners have long been recognized as critically relevant to efforts to maintain sustainable forests at the landscape scale, few studies have addressed these effects. We used the HARVEST timber harvest simulator to predict the cumulative effects of four owner groups (two paper companies, a state forest and non-industrial private owners) with different management objectives on landscape pattern in an upper Michigan landscape managed primarily for timber production. We quantified trends in landscape pattern metrics that were linked to Montreal Process indicators of forest sustainability, and used a simple wildlife habitat model to project habitat trends. Our results showed that most trends were considered favorable for forest sustainability, but that some were not. The proportion of all age classes and some forest types moved closer to presettlement conditions. The trend for the size of uneven-aged patches was essentially flat while the average size of patches of the oldest and youngest age classes increased and the size of patches of the remaining age classes decreased. Forest fragmentation generally declined, but edge density of age classes increased. Late seral forest habitat increased while early successional habitat declined. The owners use different management systems that cumulatively produce a diversity of habitats. Our approach provides a tool to evaluate such cumulative effects on other landscapes owned by multiple owners. The approach holds promise for helping landowner groups develop and evaluate cooperative strategies to improve landscape patterns for forest sustainability.     

Identification of functional corridors with movement characteristics of brown bears on the Kenai Peninsula,Alaska

We identified primary habitat and functional corridors across a landscape using Global Positioning System (GPS) collar locations of brown bears (Ursus arctos). After deriving density, speed, and angular deviation of movement, we classified landscape function for a group of animals with a cluster analysis. We described areas with high amounts of sinuous movement as primary habitat patches and areas with high amounts of very directional, fast movement as highly functional bear corridors. The time between bear locations and scale of analysis influenced the number and size of corridors identified. Bear locations should be collected at intervals ≤6 h to correctly identify travel corridors. Our corridor identification technique will help managers move beyond the theoretical discussion of corridors and linkage zones to active management of landscape features that will preserve connectivity.     

Prediction of multinomial probability of land use change using a bisection decomposition and logistic regression

Land use change is an important research area in landscape ecology and urban development. Prediction of land use change (urban development) provides critical information for making the right policies and management plans in order to maintain and improve ecosystem and city functions. Logistic regression is a widely used method to predict binomial probabilities of land use change when just two responses (change and no-change) are considered. However, in practice, more than two types of change are encountered and multinomial probabilities are therefore needed. The existing methods for predicting multinomial probabilities have limits in building multinomial probability models and are often based on improper assumptions. This is due to the lack of proper methodology and inadequate software. In this study, a procedure has been developed for building models to predict the multinomial probabilities of land use change and urban development. The foundation of this procedure consists of a special bisection decomposition system for the decomposition of multiple-class systems to bi-class systems, conditional probability inference, and logistic regression for binomial probability models. A case study of urban development has been conducted to evaluate this procedure. The evaluation results demonstrated that different samples and bisection decomposition systems led to very similar quality and performance in the developed multinomial probability models, which indicates the high stability of the proposed procedure for this case study.     

Neutral models for testing landscape hypotheses

Neutral landscape models were originally developed to test the hypothesis that human-induced fragmentation produces patterns distinctly different from those associated with random processes. Other uses for neutral models have become apparent, including the development and testing of landscape metrics to characterize landscape pattern. Although metric development proved to be significant, the focus on metrics obscured the need for iterative hypothesis testing fundamental to the advancement of the discipline. We present here an example of an alternative neutral model and hypothesis designed to relate the process of landscape change to observed landscape patterns. The methods and program, QRULE, are described and options for statistical testing outlined. The results show that human fragmentation of landscapes results in a non-random association of land-cover types that can be describe by simple statistical methods. Options for additional landscape studies are discussed and access to QRULE described in the hope that these methods will be employed to advance our understanding of the processes that affect the structure and function in human dominated landscapes.     

Agent-based land-use models: a review of applications

Agent-based modelling is an approach that has been receiving attention by the land use modelling community in recent years, mainly because it offers a way of incorporating the influence of human decision-making on land use in a mechanistic, formal, and spatially explicit way, taking into account social interaction, adaptation, and decision-making at different levels. Specific advantages of agent-based models include their ability to model individual decision-making entities and their interactions, to incorporate social processes and non-monetary influences on decision-making, and to dynamically link social and environmental processes. A number of such models are now beginning to appear—it is timely, therefore, to review the uses to which agent-based land use models have been put so far, and to discuss some of the relevant lessons learnt, also drawing on those from other areas of simulation modelling, in relation to future applications. In this paper, we review applications of agent-based land use models under the headings of (a) policy analysis and planning, (b) participatory modelling, (c) explaining spatial patterns of land use or settlement, (d) testing social science concepts and (e) explaining land use functions. The greatest use of such models so far has been by the research community as tools for organising knowledge from empirical studies, and for exploring theoretical aspects of particular systems. However, there is a need to demonstrate that such models are able to solve problems in the real world better than traditional modelling approaches. It is concluded that in terms of decision support, agent-based land-use models are probably more useful as research tools to develop an underlying knowledge base which can then be developed together with end-users into simple rules-of-thumb, rather than as operational decision support tools. This paper arises from research conducted as part of the UK Research Councils’ RELU Programme (award number RES-224-25-0102). RELU is funded jointly by the Economic and Social Research Council, the Biotechnology and Biological Sciences Research Council and the Natural Environment Research Council, with additional funding from the Department for Environment, Food and Rural Affairs and the Scottish Executive Environment and Rural Affairs Department.