河滨湿地不同植物群落根系分布特征与土壤理化性状的关系——以黄河中游荥阳段为例

在黄河中游郑州荥阳段,选择了5种河滨湿地植物群落进行根系和土壤性状特征研究,以期阐明不同植物群落的根系分布规律与土壤性状的关系,为河滨湿地植物群落组成以及土壤质量恢复提供科学参考。结果表明(1)在0—40 cm土层,根生物量密度与根长密度的平均值均表现为：芦苇群落(Phragmites australis)和芦苇-狗牙根(Cynodon dactylon)群落均大于芦苇-拂子茅(Calamagrostis epigeios)-狗牙根群落、拂子茅-狗牙根群落、拂子茅-狗牙根-水莎草(Juncellus serotinus)群落。拂子茅-狗牙根、芦苇-拂子茅-狗牙根、拂子茅-水莎草-狗牙根三种植物群落类型下根生物量密度、根长密度在0—20 cm表层土壤较大,芦苇群落和芦苇-狗牙根群落的根生物量密度、根长密度在10—40 cm的土层较大。(2)黄河河滨湿地芦苇群落、芦苇-狗牙根群落的土壤以粉粒为主,拂子茅-狗牙根群落、芦苇-拂子茅-狗牙根群落、拂子茅-狗牙根-水莎草群落的土壤主要以砂粒为主。在0—40 cm土层,芦苇群落、芦苇-狗牙根群落的土壤含水率、土壤有机质、有效氮和有效磷含量均显著高于...     

荒漠植物不同功能群性状特征及其与土壤环境的关系

研究不同功能群植物性状差异及其与土壤环境关系对于充分掌握植物的环境适应策略至关重要。以艾比湖流域为研究区,利用荒漠植物的植物高度、叶片碳、氮、磷、硫、钾、钙、钠、镁含量等9个性状,将高、低土壤水盐环境下的植物划分为5个功能群,分析不同功能群的植物组成、性状差异及其与土壤环境的关系。结果表明：(1)不同土壤水盐环境下,其植物功能群组成不同;其中白刺、胡杨和罗布麻在两个土壤水盐环境下的功能群中均存在。(2)植物的功能性状在不同土壤水盐环境下也发生了适应性的变化。高土壤水盐环境下3个功能群的植物高度、叶片碳、氮、磷和钙含量显著高于低土壤水盐环境功能群(P<0.05);低土壤水盐环境下2个功能群的植物叶片硫、钠和镁含量高于高土壤水盐环境功能群。(3)土壤含水量(SVWC)、电导率(EC)、pH以及土壤磷含量对荒漠植物功能性状影响较大。在高土壤水盐环境下,EC、pH与植物高度,叶片钾、钙含量正相关,与叶片硫含量负相关;在低土壤水盐环境下,SVWC、EC与植物高度呈显著正相关(P<0.05)。研究有助于理解荒漠植物对极端环境的适应对策,为保护荒漠地区生物多样性提供理论依据。     

金沙江下游典型库区消落带植被恢复模式

消落带植被分布、生活型、多样性的调查研究显著促进了消落带植被恢复技术的进步,然而相邻两梯级库区消落带植被分布的差异以及植被群落特征的年际变化并不明确。此外,金沙江下游部分区域表现出一定的干热特征,其影响下的消落带植被群落特征有待深入了解。基于2019年和2021年向家坝和溪洛渡库区消落带植被调查结果,分析表明：(1)金沙江下游消落带按照下垫面特性主要分为硬岩型、软岩型、松软堆积型3种类型,坡度平缓的松软堆积型消落带是植被恢复的主要类型;(2)整体上,消落带优势植被类型是一年生和多年生草本,单优势种、少优势种群落较为普遍,两个库区消落带优势种重要值差异显著,植被生活型较少;(3)向家坝、溪洛渡库区消落带在分别经历6次和8次周期性水淹后,消落带植被分布与群落物种多样性特征变化不显著,表明消落带植被群落结构相对稳定。综上说明向家坝、溪洛渡两个相邻的梯级库区消落带植被恢复需要以灌草为主,且具有不同的潜在恢复模式,因此需要对应采取不同的恢复策略。研究对于科学指导金沙江下游梯级水电站库区消落带植被恢复具有重要意义。     

黄土高原草地植物多样性与群落稳定性的关系及其驱动因素

植物多样性对维持生态功能的稳定发挥具有重要作用。以黄土高原不同植被带草地为研究对象,基于野外调查和实验分析,探究黄土高原不同植被带草地植物多样性与群落稳定性特征和二者之间的关系以及影响因素。结果表明：黄土高原草地群落结构特征(地上生物量、地下生物量)与植物多样性具有明显的纬度分布格局,草地植物多样性和生物量均表现出自东南向西北沿森林草原带—森林带—草原带—草原荒漠带逐渐递减趋势。森林草原带草地植物多样性和群落稳定性显著高于森林带、草原带和草原荒漠带;植物多样性与群落稳定性之间存在显著正相关关系,可以作为衡量群落稳定性的指标,其稳定性大小表现为森林草原带>森林带>草原带>草原荒漠带。降雨量是影响植物多样性和群落稳定性的主要因素,并通过改变土壤含水量影响群落稳定性。研究结果揭示了草地植物多样性与群落稳定性之间的关系及驱动机制,为维持黄土高原草地生态系统的群落稳定性提供了科学依据。     

论Paracarinachitids

研究证明Paracarinachitids的外骨骼都不是由8个骨板组成,骨片具有清楚的微层构造,表明它们是由叠覆的生长层组成,每个生长节上有一个小刺,在顶端下侧面前端都有肾形缺凹。同一标本上存在顶端部的融合和远顶端部的分节彼此递交的现象表明这种表象上的差异是后期次生磷灰石包裹或腐蚀的结果;其下侧缘融合和下侧面无缝隙的现象说明将Paracarinachites spinus的骨片分成头板、中间板和尾板是没有根据的。骨片表面存在的针状体是成岩作用的产物,它是粘土矿物和磷酸盐针状结晶体而不是多板纲的骨针。凡此强有力地说明Yangtzechiton是Paracarinachites的晚出同义名。根据形态功能、组织结构,特别是叠覆状排列的骨片和孤立的生长节等特征,paracarinachitids 可能与zhijinitids有密切关系,但两者是否同源尚缺少进一步的证据、据此,笔者认为将paracarinachitids 暂置于分类位置未定的具骨片后生动物较妥。     

流式细胞术的发展及在植物研究中的应用

流式细胞术是通过对液流中各种荧光标记的颗粒进行多参数快速高效的定性或定量测定的方法,在科学研究的多个领域发挥重要作用。然而,由于植物组织及细胞壁和次生代谢产物等细胞的特殊成分和结构,限制了其在植物研究领域的应用。本文在介绍流式细胞仪发展和组成分类的基础上,着重讨论了流式细胞术在植物领域的应用、研究进展及应用限制,进而展望该研究领域的发展趋势,为拓宽植物流式细胞术的潜在应用范围提供新的思考方向。     

Al-(L-丙氨酸)胰岛素晶体学研究

应用微量过饱和静置法在含柠檬酸钠和氯化钠的晶体生长体系中得到适合Ｘ射线衍射分析用的Ａｌ－（Ｌ－丙氯酸）胰岛素单晶体。晶体属于三方晶系,空间群为Ｒ３晶体衍射分辨率可达１．８Ａ以上。晶胞参数：ａＨ＝８０．８９Ａ,ｂＨ＝８０．８９Ａ,ｃＨ＝３７＼６４Ａ,α＝β＝９０°,γ＝１２０°。每个结晶学不对称单位含有两个Ａｌ－（Ｌ－丙氨酸）胰岛素分子。     

Fertile plant regeneration from protoplasts of meadow fescue (Festuca pratensis Huds.)

Suspension cultures from mature embryo-derived compact callus were initiated in seven meadow fescue (Festuca pratensis Huds.) cultivars. Four to six months after initiation, embryogenic suspension cultures with a moderate growth rate were established from three of them (cvs. Barmondo, Belimo and Leopard). These suspension cultures showed the capacity, maintained over six months, to regenerate green plants which could be grown to maturity under greenhouse conditions.Morphogenic suspension cultures from single genotypes of three F. pratensis cultivars (cvs. Barmondo, Belimo and Leopard) yielded large numbers of protoplasts, which upon culture in agarose beads using nurse cells formed microcalli with an overall plating efficiency in the range of 10^-3 to 10^-4. Mature plants were reproducibly regenerated and established in soil, from such protoplasts during a period of six months. The regeneration of fertile plants from protoplasts derived from suspension cultures of meadow fescue and its implications on gene transfer technology for this species are discussed.Abbreviations 2,4-D 2,4-dichlorophenoxy-acetic acid.     

Marginal proportional hazards models for clustered interval-censored data with time-dependent covariates

The Botswana Combination Prevention Project was a cluster-randomized HIV prevention trial whose follow-up period coincided with Botswana's national adoption of a universal test and treat strategy for HIV management. Of interest is whether, and to what extent, this change in policy modified the preventative effects of the study intervention. To address such questions, we adopt a stratified proportional hazards model for clustered interval-censored data with time-dependent covariates and develop a composite expectation maximization algorithm that facilitates estimation of model parameters without placing parametric assumptions on either the baseline hazard functions or the within-cluster dependence structure. We show that the resulting estimators for the regression parameters are consistent and asymptotically normal. We also propose and provide theoretical justification for the use of the profile composite likelihood function to construct a robust sandwich estimator for the variance. We characterize the finite-sample performance and robustness of these estimators through extensive simulation studies. Finally, we conclude by applying this stratified proportional hazards model to a re-analysis of the Botswana Combination Prevention Project, with the national adoption of a universal test and treat strategy now modeled as a time-dependent covariate.     

Integrating sample similarities into latent class analysis: a tree-structured shrinkage approach

This paper is concerned with using multivariate binary observations to estimate the probabilities of unobserved classes with scientific meanings. We focus on the setting where additional information about sample similarities is available and represented by a rooted weighted tree. Every leaf in the given tree contains multiple samples. Shorter distances over the tree between the leaves indicate a priori higher similarity in class probability vectors. We propose a novel data integrative extension to classical latent class models with tree-structured shrinkage. The proposed approach enables (1) borrowing of information across leaves, (2) estimating data-driven leaf groups with distinct vectors of class probabilities, and (3) individual-level probabilistic class assignment given the observed multivariate binary measurements. We derive and implement a scalable posterior inference algorithm in a variational Bayes framework. Extensive simulations show more accurate estimation of class probabilities than alternatives that suboptimally use the additional sample similarity information. A zoonotic infectious disease application is used to illustrate the proposed approach. The paper concludes by a brief discussion on model limitations and extensions.