Nitrogen fertilization increases diversity and productivity of prairie communities used for bioenergy

Using prairie biomass as a renewable source of energy may constitute an important opportunity to improve the environmental sustainability of managed land. To date, assessments of the feasibility of using prairies for bioenergy production have focused on marginal areas with low yield potential. Growing prairies on more fertile soil or with moderate levels of fertilization may be an effective means of increasing yields, but increased fertility often reduces plant community diversity. At a fertile site in central Iowa with high production potential, we tested the hypothesis that nitrogen fertilization would increase aboveground biomass production but would decrease diversity of prairies sown and managed for bioenergy production. Over a 3 year period (years 2–4 after seeding), we measured aboveground biomass after plant senescence and species and functional‐group diversity in June and August for multispecies mixtures of prairie plants that received no fertilizer or 84 kg N ha^?1 year^?1. We found that nitrogen fertilization increased aboveground biomass production, but with or without fertilization, the prairies produced a substantial amount of biomass: averaging (±SE) 12.2 ± 1.3 and 9.1 ± 1.0 Mg ha^?1 in fertilized and unfertilized prairies, respectively. Unfertilized prairies had higher species diversity in June, whereas fertilized prairies had higher species diversity in August at the end of the study period. Functional‐group diversity was almost always higher in fertilized prairies. Composition of unfertilized prairies was characterized by native C₄ grasses and legumes, whereas fertilized prairies were characterized by native C₃ grasses and forbs. Although most research has found that nitrogen fertilization reduces prairie diversity, our results indicate that early‐spring nitrogen fertilization, when used with a postsenescence annual harvest, may increase prairie diversity. Managing prairies for bioenergy production, including the judicious use of fertilization, may be an effective means of increasing the amount of saleable products from managed lands while potentially increasing plant diversity.     

The genetics of complex diseases

Genetic factors influence virtually every human disorder, determining disease susceptibility or resistance and interactions with environmental factors. Our recent successes in the genetic mapping and identification of the molecular basis of mendelian traits have been remarkable. Now, attention is rapidly shifting to more-complex, and more-prevalent, genetic disorders and traits that involve multiple genes and environmental effects, such as cardiovascular disease, diabetes, rheumatoid arthritis and schizophrenia. Rather than being due to specific and relatively rare mutations, complex diseases and traits result principally from genetic variation that is relatively common in the general population. Unfortunately, despite extensive efforts by many groups, only a few genetic regions and genes involved in complex diseases have been identified. Completion of the human genome sequence will be a seminal accomplishment, but it will not provide an immediate solution to the genetics of complex traits.     

参数序列比对算法研究

序列比对是生物信息学中的一项重要任务,通过序列比对可以发现生物序列中的功能、结构和进化的信息。序列比对结果的生物学意义与所选择的匹配、不匹配、插入和删除以及空隙的罚分函数密切相关。现介绍一种参数序列比对方法,该方法把最佳比对作为权值和罚分的函数,可以系统地得到参数的选择对最佳比对结果的影响。然后将其应用于RNA序列比对,分析不同的参数选择对序列比对结果的影响。最后指出参数序列比对算法的应用以及未来的发展方向。     

Structural analysis based on state-space modeling.

A new method has been developed to compute the probability that each amino acid in a protein sequence is in a particular secondary structural element. Each of these probabilities is computed using the entire sequence and a set of predefined structural class models. This set of structural classes is patterned after Jane Richardson''s taxonomy for the domains of globular proteins. For each structural class considered, a mathematical model is constructed to represent constraints on the pattern of secondary structural elements characteristic of that class. These are stochastic models having discrete state spaces (referred to as hidden Markov models by researchers in signal processing and automatic speech recognition). Each model is a mathematical generator of amino acid sequences; the sequence under consideration is modeled as having been generated by one model in the set of candidates. The probability that each model generated the given sequence is computed using a filtering algorithm. The protein is then classified as belonging to the structural class having the most probable model. The secondary structure of the sequence is then analyzed using a "smoothing" algorithm that is optimal for that structural class model. For each residue position in the sequence, the smoother computes the probability that the residue is contained within each of the defined secondary structural elements of the model. This method has two important advantages: (1) the probability of each residue being in each of the modeled secondary structural elements is computed using the totality of the amino acid sequence, and (2) these probabilities are consistent with prior knowledge of realizable domain folds as encoded in each model. As an example of the method''s utility, we present its application to flavodoxin, a prototypical alpha/beta protein having a central beta-sheet, and to thioredoxin, which belongs to a similar structural class but shares no significant sequence similarity.     

基于混沌理论的蛋白质序列特性的研究

蛋白质序列特性的研究对于蛋白质的结构及功能具有重要意义。该文为了研究蛋白质序列是否具有混沌行为,先将蛋白质序列通过氨基酸电子离子相互作用势(electron interaction potential,EIIP)转化为时间序列,再根据混沌理论对其进行相空间重构,利用去偏自相关系数,经典G-P算法确定系统的时间延迟t和嵌入维数m,系统的最大Lyapunov指数则用改进的最大Lyapunov指数计算方法计算,其结果绝大多数为正,从而确认了蛋白质时间序列的混沌行为,并对特例进行了说明。     

藜麦及其资源开发利用

藜麦Chenopodium quinoa Willd.英文名:quinoa,原产于南美洲安第斯山区,是印加土著居民的主要传统食物,至今已有5 000~7 000多年的利用和种植历史。古代印加人将它称之为"粮食之母"。藜麦在20世纪80年代,被美国宇航局用于宇航员的太空食品。联合国粮农组织认为藜麦是唯一的单一植物即可满足人体基本营养需求的食物,正式推荐藜麦为最适宜人类的完美的全营养食品。本文对藜麦的植物形态、生态特性、营养价值以及在我国种植展望作了综合报道。     

Assisted colonization as a climate change adaptation tool

Assisted colonization is a form of conservation translocation which introduces species at risk from extinction to new habitats, beyond their current range, in anticipation of more suitable conditions. Identifying which species, communities and ecosystems may benefit most from assisted colonization in coming decades is a key goal for conservation. Climate change is expected to lead to the loss or movement of suitable habitat for a range of species and anticipating which can be effectively conserved through assisted colonization is critical. Here, we identify a series of scenarios that may predispose terrestrial species to the need for assisted colonization in order to reduce extinction risk resulting from anthropogenic climate change and assemble a list of traits commonly associated with at‐risk species. These traits may help to provide broad‐scale guidance on how to select species to target for assisted colonization as a conservation management response to climate change. We also identify six key themes associated with successful conservation translocations including recipient site selection and preparation, a clear understanding of species biology and ecology, and taking lessons from invasive species research.     

Relationship between functional diversity and productivity in meadow and marsh plant communities

功能多样性-生产力关系研究结果支持质量比假说和多样性假说, 但对于这两种假说的适用条件尚有争议。通过对吉林省西部草甸和沼泽植物群落的地上生物量、2个物种多样性指标(物种丰富度和Shannon-Weaver指数)、7种植物性状的两类功能多样性指标(群落权重均值和Rao二次熵), 以及土壤环境因子进行调查测量, 研究了群落功能多样性与生产力的关系。结果表明: 1)功能多样性与生产力的关系比物种多样性与生产力的关系更为密切; 2)功能群落权重均值解释生产力变异的能力好于Rao二次熵, 即优势物种对群落生产力的影响作用更大; 3)水淹条件影响着功能多样性与生产力的关系, 以群落权重均值为基础的质量比假说适于解释草甸群落功能多样性与生产力的关系, 而以Rao二次熵为基础的多样性假说适于解释有强烈环境筛(水淹)的沼泽群落功能多样性与生产力的关系。     

Key characteristics for facilitating Leucaena leucocephala to successfully invade pioneer communities of tropical rain forests

Aims Due to fast-growing and high drought stress tolerance, Leucaena leucocephala has been widely used for afforestation in degraded tropical forests worldwide, but it is also a global invasive exotic species. Studies have shown that fast-growing can help L. leucocephala successfully invade subtropical forests. In this study, we aimed to investigate whether fast-growing and high drought stress tolerance can help L. leucocephala invade tropical rain forests.Methods The pioneer community of tropical rain forest which had been invaded by L. leucocephala in the Baopoling Mountain, Sanya, China was the research object. Through the t-test, we compared the differences in key functional traits that were related to growth rate (photosynthesis rate, stomatal conductance and transpiration rate) and drought stress tolerance (leaf turgor loss point) in both wet and dry seasons between L. leucocephala and eight dominant native species of pioneer community of tropical rain forest. And the principal component analysis (PCA) was used to investigate whether these functional traits can best discriminate between Leucaena leucocephala and the eight dominant native species.Important findings Leucaena leucocephala could be invariably growing fast (photosynthesis rate, stomatal conductance and transpiration rate much higher than native species) from wet to dry seasons and had higher drought stress tolerance (leaf turgor loss point much lower than native species) in the dry season. The results of PCA showed that these functional traits could significantly discriminate between L. leucocephala and the eight dominant native species. Therefore, invariable fast-growing from wet to dry season and high drought stress tolerance in the dry season make L. leucocephala successfully invade pioneer communities of tropical rain forests. In the future, these functional traits can be used to select many native species to perform biological control of L. leucocephala in other tropical forests.