Wetland ecosystem comparison using a suite of plant assessment measures

In light of extensive human impact on wetlands it is necessary that we develop an effective way to monitor the effects of impact in order to prevent further destruction. One method is plant community assessment, specifically Floristic Quality Assessment (FQA), which is common, but can be subjective. In this case study, we implement FQA, as well as specific morphological and chemical assessment measures over a two-year period in order to compare two wetlands in the Lake George watershed in the Adirondack mountains and their response to human impact. While the wetlands studied demonstrated very different water chemistry profiles makeups, FQA did not reveal substantial differences between plant communities. However, more specific analyses of plant morphology and tissue chemistry did reveal significant differences that reflected the level of impact at these two sites. Namely, the simple plant Lemna minor had consistently shorter roots and Nuphar lutea contained higher amounts of nitrogen in above ground tissues when growing in an anthropogenically impacted wetland. We suggest that FQA and specific plant morphology and tissue chemistry measurements be performed concurrently to provide indication of both long- and short-term effects of human impact in wetland ecosystems.     

Machine learning approaches in MALDI-MSI: clinical applications

Introduction: Despite the unquestionable advantages of Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging in visualizing the spatial distribution and the relative abundance of biomolecules directly on-tissue, the yielded data is complex and high dimensional. Therefore, analysis and interpretation of this huge amount of information is mathematically, statistically and computationally challenging.

Areas covered: This article reviews some of the challenges in data elaboration with particular emphasis on machine learning techniques employed in clinical applications, and can be useful in general as an entry point for those who want to study the computational aspects. Several characteristics of data processing are described, enlightening advantages and disadvantages. Different approaches for data elaboration focused on clinical applications are also provided. Practical tutorial based upon Orange Canvas and Weka software is included, helping familiarization with the data processing.

Expert commentary: Recently, MALDI-MSI has gained considerable attention and has been employed for research and diagnostic purposes, with successful results. Data dimensionality constitutes an important issue and statistical methods for information-preserving data reduction represent one of the most challenging aspects. The most common data reduction methods are characterized by collecting independent observations into a single table. However, the incorporation of relational information can improve the discriminatory capability of the data.     

注册分类改革视角下药品数据保护制度效应分析

在国际趋势的压力下,兼受跨太平洋伙伴关系协定（TPP）影响,我国实施药品数据保护制度已成大势所趋。鉴于药品数据保护与药品注册审批体系紧密相关,我国化学药注册分类改革后,药品数据保护对医药产业发展必然会带来不同影响。结合我国分类注册改革新标准,在理论上对数据保护制度实施效果进行研究,进而探讨新注册分类下数据保护的实施对1至4类药品及医药产业的影响。     

The Urfold: Structural similarity just above the superfold level?

We suspect that there is a level of granularity of protein structure intermediate between the classical levels of “architecture” and “topology,” as reflected in such phenomena as extensive three‐dimensional structural similarity above the level of (super)folds. Here, we examine this notion of architectural identity despite topological variability, starting with a concept that we call the “Urfold.” We believe that this model could offer a new conceptual approach for protein structural analysis and classification: indeed, the Urfold concept may help reconcile various phenomena that have been frequently recognized or debated for years, such as the precise meaning of “significant” structural overlap and the degree of continuity of fold space. More broadly, the role of structural similarity in sequence?structure?function evolution has been studied via many models over the years; by addressing a conceptual gap that we believe exists between the architecture and topology levels of structural classification schemes, the Urfold eventually may help synthesize these models into a generalized, consistent framework. Here, we begin by qualitatively introducing the concept.     

Distributional dynamics of a specialized subterranean community oppose the classical understanding of the preferred subterranean habitats

Troglobionts are organisms that are specialized for living in a subterranean environment. These organisms reside prevalently in the deepest zones of caves and in shallow subterranean habitats, and complete their entire life cycles therein. Because troglobionts in most caves depend on organic matter resources from the surface, we hypothesized that they would also select the sections of caves nearest the surface, as long as environmental conditions were favorable. Over 1 year, we analyzed, in monthly intervals, the annual distributional dynamics of a subterranean community consisting of 17 troglobiont species, in relation to multiple environmental factors. Cumulative standardized annual species richness and diversity clearly indicated the existence of two ecotones within the cave: between soil and shallow subterranean habitats, inhabited by soil and shallow troglobionts; and between the transition and inner cave zones, where the spatial niches of shallow and deep troglobionts overlap. The mean standardized annual species richness and diversity showed inverse relationships, but both contributed to a better insight into the dynamics of subterranean fauna. Regression analyses revealed that temperatures in the range 7–10°C, high moisture content of substrate, large cross section of the cave, and high pH of substrate were the most important ecological drivers governing the spatiotemporal dynamics of troglobionts. Overall, this study shows general trends in the annual distributional dynamics of troglobionts in shallow caves and reveals that the distribution patterns of troglobionts within subterranean habitats may be more complex than commonly assumed.     

A Multiplexed Assay for Exon Recognition Reveals that an Unappreciated Fraction of Rare Genetic Variants Cause Large-Effect Splicing Disruptions

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Composition and ecological drivers of the kwongan scrub and woodlands in the northern Swan Coastal Plain,Western Australia

The nature of community patterns and environmental drivers in kwongan mediterranean‐type shrubland on nutrient‐poor soils occurring in Western Australia remain poorly examined. We aimed to determine whether (i) classification of the kwongan vegetation of the northern Swan Coastal Plain would be ecologically informative and (ii) which environmental drivers underpin the plant community patterns. The study area was positioned on the northern Swan Coastal Plain, locality of Cooljarloo (30°39′ S, 115°22′ E), situated 170 km north of Perth, Western Australia. Compositional (518 species × 337 relevés) and environmental data set (29 variables × 87 relevés) describing time since last fire, soil chemical and physical properties, and terrain characteristics were analysed using classification and ordination techniques. OptimClass assisted in the selection of a robust data transformation, resemblance function and clustering algorithm to identify the vegetation patterns. Major ecological drivers of the vegetation patterns were detected using distance‐based redundancy analysis (db‐RDA). Classification revealed major groupings of Wet Heath and Banksia Woodland distinguishable by the high prevalence of myrtyoid and proteoid taxa, respectively. On floristic‐sociological grounds, we recognised four Wet Heath and two Banksia Woodland communities. The Wet Heath was constrained to areas of higher litter depth (db‐RDA axis 1: 9%). Soil chemical and physical properties explained the highest proportion (17%) of the compositional variance, while the terrain‐ and fire‐related variables explained 2% and <0.001%, respectively. While fire explained little compositional variance overall, a separate db‐RDA analysis found that it may play an important pattern‐structuring role within Banksia Woodlands. Fine‐scale compositional patterns correspond only to a small extent to environmental data; the substantial unexplained variance may be due to slow‐acting neutral and stochastic processes.     

基于多源遥感数据的植物物种分类与识别: 研究进展与展望

物种分类与识别是生物多样性监测的基础, 明确物种的类别及其分布是解决几乎所有生态学问题的前提。为深入了解基于多源遥感数据的植物物种分类与识别相关研究的发展现状和存在的问题, 本文对2000年以来该领域的研究进行了总结分析, 发现: 当前大多数研究集中在欧洲和北美地区的温带或北方森林以及南非的热带稀树草原; 使用最多的遥感数据是机载高光谱数据, 而激光雷达作为补充数据, 通过单木分割及提供单木的三维垂直结构信息, 显著提高了分类精度; 支持向量机和随机森林作为应用最广的非参数分类算法, 平均分类精度达80%; 随着计算机技术及机器学习领域的不断成熟, 人工神经网络在物种识别领域得以迅速发展。基于此, 本文对目前基于遥感数据的植物物种分类与识别中在分类对象复杂性、多源遥感数据整合、植物物候与纹理特征整合和分类算法技术等方面面临的挑战进行了总结, 并建议通过整合多时相监测数据、高光谱和激光雷达数据、短波红外等特定波谱信息、采用深度学习等方法来提高分类精度。     

东北地区草本植物1个新记录科和3个新记录属

东北地区位于我国东北部,共有维管束植物164科928属3 103种。根据野外调查结果及相关资料,报道了东北地区草本植物1个新记录科—粟米草科(Molluginaceae)和3个新记录属—粟米草属(Mollugo L.)、牛膝属(Achyranthes L.)和秃疮花属(Dicranostigma Hook. f. et Thoms.),以及对应的3个新纪录种—粟米草(Mollugo stricta L.)、牛膝(Achyranthes bidentata Blume)和秃疮花[Dicranostigma leptopodum(Maxim.) Fedde]。新记录种凭证标本保存于大连自然博物馆植物标本室。这些新记录草本植物的发现,对东北地区生物多样性的研究具有重要意义,为其在我国的地理分布研究提供了新资料。