太白山栎属树种气孔特征沿海拔梯度的变化规律

气孔是植物与外界环境进行水分和气体交换的主要通道,调节植物碳同化和水分散失的平衡关系,在一定程度上反映植物对外界环境变化的适应。沿太白山北坡1100—2300 m海拔,测定4种栎属树种的气孔性状,分析气孔性状沿海拔的变化规律和其对环境因子的响应。结果表明:(1)气孔密度与气孔长度间的负相关在4个树种间均显著存在(P0.05);除栓皮栎(Quercus variabilis)外,气孔密度与潜在气孔导度指数的正相关关系均达显著水平;而气孔宽度与气孔长度之间只在栓皮栎和锐齿栎(Q. aliena var. acuteserrata)达到显著水平。(2)栓皮栎和槲栎(Q. aliena)的气孔长度和宽度随海拔升高而下降,气孔密度、潜在气孔导度指数增加,辽东栎(Q. wutaishansea)变化形式则相反;锐齿栎气孔宽度减小,其余性状沿海拔呈单峰变化,在约1600 m处气孔长度达到最小值,气孔密度和潜在气孔导度指数达到最大值。(3)与土壤因子相比,气孔性状主要受气候因素的影响。潜在气孔导度指数与大气温度、空气湿度成极显著正相关(P0.01),与降水量显著负相关(P0.05)。其中,空气相对湿度是影响潜在气孔导度指数的主要因素,能够解释气孔变异的22.9%。本研究结果对于深入认识秦岭太白山地区栎属树种对环境变化的响应和适应提供理论证据。     

中国栎属(壳斗科)基于叶表皮及叶结构特征的分支分析

以三棱栎为外类群,基于叶表皮及叶结构特征对中国栎属进行初步的分支分析,结果显示了栎属内稳定的“支”结构及其种间关系。栎亚属可划分为5个组,分别为巴东栎组,高山栎组,Jiang子栎组,麻栎组和槲栎组,Jiang子栎组是栎亚属常绿栎类与落叶栎类之间的过渡类群;高山栎组应为栎亚属常绿栎类中的特化类群,而非最原始类群,5个组中,仅巴东栎组不是单系类群,而是一个多系类群,青冈亚属较栎亚属早分支,可划分为3大类;无毛类,简单被毛类和复杂被毛类;无毛类最原始,复杂被毛类与栎亚属关系最近,因此,叶表皮及叶结构特征对解决栎亚属组间亲缘关系有重要的分类学意义。     

伏牛山栎类群落多样性研究

本文研究了暖温带、北亚热带过渡地区５个分布最广泛的杆类群落的结构、生活型、区系组成、物种多样性、均匀度和种间相遇机率。结果表明：群落外貌整齐,各层优势种显著;生活型以小高位芽植物、地面芽植物为主;群落属温带性质,含有一定的热带成分。Ｓｈａｎｎｏｎ指数和Ｓｉｍｐｓｏｎ指数测定均表明：灌木层多样性指数最高,草本植物次之,乔木层最低;各群落间多样性指数高低的排列顺序是：锐齿栎群落、短柄群落、槲栎群落、麻栎群落、栓皮栎群落．     

黄耆属裂萼亚属6种植物叶表皮微形态特征研究

为了明确黄耆属裂萼亚属内部类群的关系,该研究采用光学显微镜和扫描电镜,观察了黄耆属裂萼亚属6个组6种植物的叶表皮特征。结果表明:(1)在光学显微镜下,裂萼亚属6种植物的表皮毛密度、长度、臂长比以及气孔频率都存在较大差异:除莲山黄耆和地八角上表皮无毛外,其他种上下表皮都有毛分布并且下表皮毛密度较大;表皮毛臂长比在1.22~2.15之间;表皮毛的长度为104.7~902.0μm,同一个种的同一叶片上表皮毛长度差异在200~400μm之间,但上下表皮毛长度没有明显差别,其中短序组地八角的表皮毛长度最短(195.5μm),剑叶组鸡峰山黄耆的表皮毛长度最长(781.6μm)。(2)在光学显微镜下,裂萼亚属6种植物的表皮细胞形状和垂周壁式样也各不相同,其中灰叶黄耆和地八角垂周壁平直,莲山黄耆和鸡峰山黄耆为明显的波状,而斜茎黄耆和糙叶黄耆的垂周壁介于两者之间,相对应的表皮细胞形状分别为:多边形、不规则形和近多边形,这些特征可以作为物种鉴别的依据。(3)扫描电镜下,裂萼亚属6种植物的微形态特征基本一致,表皮毛均呈圆柱状,表面具有棱状条纹或乳头状突起,其中地八角的棱状条纹最为明显,其他各种之间的毛表面特征差异不明显;表皮细胞的蜡质层纹饰均为薄片状,气孔器外拱盖边缘平滑或微波状,其中地八角的气孔器周围角质层有明显的"T"型加厚。(4)比较不同环境下6种植物的气孔频率和密度发现,采自水边的地八角气孔频率最大,且上下表皮气孔频率一致,而采自黄土高原干旱地区鸡峰山黄耆的气孔频率却最小,与前人研究结果不一致。     

落羽杉属(杉科)叶表皮结构及气孔参数

落羽杉属Taxodium Rich.现生3种植物——落羽杉T. distichum (L.) Rich.、池杉T. ascendens Brongn.和墨西哥落羽杉T. mucronatum Tenore.的条形叶为双面气孔型或单面气孔型。叶片远轴面气孔分布于中脉两侧,每侧各有4-8列气孔。叶片中部气孔数量稳定,顶部和基部气孔数量比中部略少。近轴面气孔在中脉两侧各有1-4行,有时仅少数几个气孔或没有气孔分布。非气孔分布区内,表皮细胞长方形,细胞壁直或稍微呈波状,细胞长轴与叶片长轴一致。气孔分布区内的表皮细胞有时为多边形。气孔器椭圆形,长轴与叶片长轴垂直或成一定的角度。保卫细胞壁加厚明显,极端联合形成极层结构。落羽杉属3种现生植物的气孔密度和气孔指数差异显著,不同采集地的落羽杉气孔密度和气孔指数差异不显著。这3种植物的气孔指数的变异系数均小于气孔密度的变异系数,用气孔指数指示大气CO2浓度比用气孔密度可靠。     

木兰科16种含笑属植物的花粉形态

该研究对含笑属5组16种植物(其中:峨眉含笑、多脉含笑、蔼和含笑、毛果含笑、南亚含笑、展毛含笑、阔瓣含笑和壮丽含笑等8种为首次报道)的花粉样品进行了扫描电子显微镜观测,并对其花粉粒形态及大小性状进行统计分析,以揭示木兰科含笑属植物的花粉形态特征,探讨其系统分类学意义。结果显示:含笑属植物的花粉粒形态均为两侧对称,异极,具1远极单沟萌发孔,沟长几乎达两端,极面观为椭圆状,赤道面观为舟状,表面无脊或具脊;含笑属花粉粒表面小穿孔的密度为0.002 5~1.500 0个/μm~2,最长轴长为30.69~58.02μm、变异系数为2.85%~8.20%,最短赤道轴长为15.29~31.29μm、变异系数为4.29%~15.53%,轴比值为1.43~2.69、变异系数为2.53%~13.00%。经组间、种间和种内比较,含笑属植物的花粉粒仅在小穿孔密度和3个大小性状上存在一定的种间分类学价值。     

基于几何形态分析的栎属白栎组叶片形态特征

以壳斗科栎属白栎组的5个种作为研究对象进行叶片几何形态学分析(GMMs)。选取了20个天然种群,共采集182个个体,887张叶片,对每张叶片采用几何形态学的标点法,数字化叶形态特征,使5个种的叶形态差异可视化。结果表明: 广义普氏分析可以有效地排除叶片位置和大小对叶片形状的影响。基于个体水平的主成分分析表明,槲树分别与槲栎和枹栎2个种的叶片形态差异明显,基于个体水平的典型变量分析表明,叶片的对称组分可以将槲栎与其他4个种准确区分。叶片非对称组分的多变量分析表明,5个种彼此间区别不明显。基于叶片水平的分析表明: 区分度较高的两组是槲栎vs.槲树(99.5% vs. 100%)和槲树vs.枹栎(99.0% vs. 100%),可以通过叶形准确区分;区分度略低的两组是白栎vs.枹栎(90.5% vs. 86.8%)和槲树vs.蒙古栎(85.1% vs. 82.9%)。本研究为存在频繁杂交渐渗的物种间叶型鉴定提供了新思路。     

15种铁角蕨科植物叶表皮形态特征的研究

利用光学显微镜对铁角蕨科15种植物的叶表皮形态特征进行观察。研究结果表明：（1）15种铁角蕨科植物的叶上、下表皮细胞形状为不规则型,垂周壁为深波状、波状或浅波状;上表皮细胞长宽比1.3~2.6,下表皮细胞长宽比1.3~4.1;（2）在15种铁角蕨科植物中共观察到7种气孔器类型,分别为腋下细胞型、不等细胞型、无规则四细胞型、无规则型、极细胞型、聚合极细胞型和聚腋下细胞型,每种植物具有2~5种气孔器类型,气孔均为下生型,多为椭圆形;气孔的长宽比1.12~2.81,气孔密度16.4~105.1个·mm^-2,气孔指数为5.7%~21.1%;（3）铁角蕨科植物叶表皮形态特征中的上表皮细胞形状、垂周壁形状、上表皮细胞长宽比、主要气孔器类型及衍生类型等具有一定的属内稳定性,可作为铁角蕨科属间分类的依据之一;（4）该研究在一定程度上支持秦仁昌和吴兆洪对铁角蕨科的划分以及铁角蕨属内分组和组内分系,并为铁角蕨科植物的分类鉴定及系统演化研究提供基础资料。     

叉蕨科30种植物叶表皮形态特征研究

利用光镜对叉蕨科7属30种植物叶表皮形态特征进行详细观察研究。结果显示：（1）叉蕨科30种植物的叶上表皮和下表皮细胞形状均为不规则型,垂周壁式样为深波状或浅波状,具单晶或针晶;上表皮细胞的长宽比为1.62~4.0,下表皮细胞的长宽比为1.63~3.06。（2）在30种植物中共观察到7种气孔器类型,分别为：极细胞型、腋下细胞型、聚合极细胞型、聚腋下细胞型、不等细胞型、无规则四细胞型和不规则型,每种植物分别具有4~7种气孔器类型,均为下生型气孔;气孔长宽比为1.22~1.91,气孔密度为8~76个/mm²,气孔指数为3.9%~25.7%。（3）基于气孔器类型组成进行聚类分析,可将30种植物分成3个类群。（4）对叶表皮形态特征分析认为,轴脉蕨属应介于叉蕨属和肋毛蕨属之间,且与叉蕨属关系更近;叉蕨属的范畴还有待进一步研究;支持将肋毛蕨属从叉蕨科中分离出来置于鳞毛蕨科,但不支持黄腺羽蕨属归入鳞毛蕨科。     

浙东南杨梅叶片气孔观察与相似性研究

对浙江省东南部台州、温州、宁波及绍兴4个地区25份杨梅地方品种材料叶片的气孔特性进行研究,测定了气孔密度、气孔面积、气孔长、短轴和气孔器长、短轴。结果表明:所有材料气孔均属于平行型;气孔密度在500～1200个/mm2之间,主栽品种东魁、荸荠和丁岙梅气孔密度偏小;气孔面积从40～80μm2不等,以50μm2较为集中;气孔器长、短轴以变异1号最大,温州土梅最小;气孔长、短轴的变化规律为长轴>短轴。利用重心距离法对气孔密度、气孔面积、气孔大小和气孔器大小进行聚类分析,从距离0.5处进行分类,可分为5类。聚类分析表明:气孔的相似度在某种程度上可以作为区别品种的依据,但要精确地研究它们之间的遗传关系,还需与分子生物学、形态学等综合手段相结合予以鉴定。     

Spatial Uncertainty and Ecological Models

Applied ecological models that are used to understand and manage natural systems often rely on spatial data as input. Spatial uncertainty in these data can propagate into model predictions. Uncertainty analysis, sensitivity analysis, error analysis, error budget analysis, spatial decision analysis, and hypothesis testing using neutral models are all techniques designed to explore the relationship between variation in model inputs and variation in model predictions. Although similar methods can be used to answer them, these approaches address different questions. These approaches differ in (a) whether the focus is forward or backward (forward to evaluate the magnitude of variation in model predictions propagated or backward to rank input parameters by their influence); (b) whether the question involves model robustness to large variations in spatial pattern or to small deviations from a reference map; and (c) whether processes that generate input uncertainty (for example, cartographic error) are of interest. In this commentary, we propose a taxonomy of approaches, all of which clarify the relationship between spatial uncertainty and the predictions of ecological models. We describe existing techniques and indicate a few areas where research is needed.     

影响水稻光合日变化的酶和相关因素的分析

水稻叶片的最大光合速率出现在上午１０：００时,Ｒｕｂｉｓｃｏ初始活力也在此时达到最大,然后逐渐降低,下午１４：００时略上升后又下降．Ｒｕｂｉｓｃｏ初始活力与光合速率之间极显著相关,相关系数为 ０．９４７４．运用相关性分析、回归分析、通径分析,对晴（有时有云）天气水稻叶片的光合速度、光合关键酶及有关因素的日变化进行综合评估,结果发现中午光合下降主要来自气孔限制,同时Ｒｕｂｉｓｃｏ活性也下降;Ｒｕｂｉｓｃｏ活性是影响光合日变化的又一重要生化因子．体内Ｒｕｂｉｓｃｏ活性受Ｒｕｂｉｓｃｏ活化酶的调节．     

Pluralism and diversity: trends in the use and application of ordination methods 1990‐2007

Question: What are the trends and patterns in the application of ordination techniques in vegetation science since 1990? Location: Worldwide literature analysis. Methods: Evaluation of five major journals of vegetation science; search of all ISI‐listed ecological journals. Data were analysed with ANCOVAs, Spearman rank correlations, GLMs, biodiversity indices and simple graphs. Results: The ISI search retrieved fewer papers that used ordinations than the manual evaluation of five selected journals. Both retrieval methods revealed a clear trend in increasing frequency of ordination applications from 1990 to the present. Canonical Correspondence Analysis was far more frequently detected by the ISI search than any other method. Applications such as Correspondence Analysis/Reciprocal Averaging and Detrended Correspondence Analysis have increasingly been used in studies published in “applied” journals, while Canonical Correspondence Analysis, Redundancy Analysis and Non‐Metric Multidimensional Scaling were more frequently used in journals focusing on more “basic” research. Overall, Detrended Correspondence Analysis was the most commonly applied method within the five major journals, although the number of publications slightly decreased over time. Use of Non‐Metric Multidimensional Scaling has increased over the last 10 years. Conclusion: The availability of suitable software packages has facilitated the application of certain techniques such as Non‐Metric Multidimensional Scaling. However, choices of ordination techniques are currently less driven by the constraints imposed by the software; there is also limited evidence that the choice of methods follows social considerations such as the need to use fashionable methods. Methodological diversity has been maintained or has even increased over time and reflects the researcher's need for diverse analytical tools suitable to address a wide range of questions.     

Discrimination of higher plant calluses based on embryogenic capacity and taxonomic classification by pyrolysis mass spectrometry

Pyrolysis mass spectrometry (PyMS) is a rapid, simple, high-resolution analytical method based on thermal degradation of complex material in a vacuum, and has been widely applied to the discrimination of closely related microbial strains. Minimally prepared samples of embryogenic and non-embryogenic calluses derived from various higher plants (sweet potato, morning glory, Korean ginseng, Siberian ginseng, and balloon flower) were subjected to PyMS for spectral fingerprinting. A dendrogram based on the unweighted pair group method, with arithmetic mean of pyrolysis mass spectra, divided the calluses into Siberian ginseng embryogenic callus and the others, which were subsequently divided into embryogenic and non-embryogenic callus groups, regardless of plant species from which the calluses were derived. In the non-embryogenic callus group, the dendrogram was in agreement with the known taxonomy of the plants. These results indicate that PyMS analysis could be applied for discriminating plant calluses based on embryogenic capacity and taxonomic classification.     

Reconstructing paleoecology and paleoenvironmental variables using factor analysis and regression: some limitations

We test the success of Principal Components, Factor and Regression Analysis at recovering environmental signals using numerical experiments in which we control species environmental responses, the environmental conditions and the sampling scheme used for calibration. We use two general conditions, one in which sampling of a continental margin for benthic foraminiferal assemblages is done in a standard grid and the driving environmental variables are correlated to one another, and the other where sampling is done so that the environmental variables are uncorrelated. The first condition mimics many studies in the literature. We find that where the controlling environmental variables are correlated, Principal Components/Factor Analysis yield factors that reflect the common variance (correlation) of those variables. Since this common variance is largely a product of the sampling scheme, the factors extracted do not reliably present true species ecologic behavior. This behavior cannot be accurately diagnosed and faulty interpretations may lead to substantial error when using factor coefficients to reconstruct conditions in the past. When the sampling scheme is constructed so that the controlling environmental variables for the calibration data set are uncorrelated the factor patterns will reflect these variables more accurately. Species responses can be more successfully interpreted from the Principal Components/Factor Analysis structure matrices. Additionally, regression analysis can successfully extract the independent environmental signals from the biotic data set. However, matrix closure is a confounding effect in all our numerical results as it distorts species' abundances and spatial distribution in the calibration data set. Our results show clearly that a knowledge of the controlling environmental variables, and the correlations among these variables over a study area, is essential for the successful application of multivariate techniques for paleoenvironmental reconstruction.     

Fish ecoregions of Kansas: stream fish assemblage patterns and associated environmental correlates

Synopsis Principal components analysis was performed on fish presence/absence data for 39 common fish species from 410 stream sites in Kansas. The analysis confirmed ten ecologically meaningful fish assemblages, based on species associations. Factor scores based on these assemblages were then clustered into six geographic areas or fish ecoregions. Canonical discriminant analysis identified environmental variables that distinguished the derived fish ecoregions. Mean annual runoff, mean annual growing season, and discharge appear most important. Mean width, mean depth, chloride concentration, water temperature, substrate type, gradient, and percent of pool habitat were less important. Correspondence exists between these fish ecoregions and the patterns of physiographic regions, river basins, geology, soil, and potential natural vegetation in Kansas. The multivariate statistical approach used to classify fish ecoregions should have considerable potential value for fish assessment and management purposes in areas other than the state of Kansas.     

Chemometric evaluation of the anti-cancer pro-drug podophyllotoxin and potential therapeutic analogues in Juniperus and Podophyllum species

Introduction – Podophyllotoxin, deoxypodophyllotoxin, demethylpodophyllotoxin and podophyllotoxone are four therapeutically potent secondary metabolites. There is a dearth of information on the holistic analysis of their distribution pattern in both phylogenetic and ecological contexts. Objectives – To analyse the continuum of the above metabolites in Juniperus and Podophyllum species collected from natural populations in Himalayan environments and the botanical gardens of Rombergpark and Haltern (Germany) using multi‐component LC‐ESI‐MS/MS, coupled with statistically relevant chemometric assessment. Methodology – We evaluated the individual and holistic metabolite profiles and chemometrically correlated the phytochemical loads between various species (infraspecific), organic and aqueous extracts, and populations of the same species from different locations, different species from same location, different species from different locations and infrageneric populations from same and different locations. Results – Multivariate analysis revealed Juniperus x‐media Pfitzeriana as a suitable alternative to Podophyllum hexandrum for commercial exploitation. A significant positive correlation of podophyllotoxone with both podophyllotoxin and demethylpodophyllotoxin, and a negative correlation of podophyllotoxin with both deoxypodophyllotoxin and demethylpodophyllotoxin (infraspecific among Podophyllum), were observed by Kruskal's multidimensional scaling and corroborated by principal component analysis, indicating probable similarity and/or difference between the biosynthetic pathways, and synergistic and/or antagonistic principles, respectively. Finally, linear discriminant analysis and hierarchical agglomerative cluster analysis revealed considerable infrageneric and infraspecific variability in secondary compound spectra and load of the different populations under study. Conclusion – Such holistic studies of plants and their therapeutic metabolites ought to assist in selecting plants, geographical areas and environmental conditions for bioprospecting and global‐scale phytochemical and phylogenetic diversity studies in the future. Copyright © 2010 John Wiley & Sons, Ltd.     

凡纳滨对虾各月龄性状的主成分与判别分析

为了研究凡纳滨对虾各性状增长规律和判定最佳生长季节凡纳滨对虾的体格与月龄的关系,选择1～6月龄凡纳滨对虾各1000只,选择全长、体长、第一腹节背高、第三腹节背高、第一腹节背宽、头胸甲长和体重共7个性状,进行主成分与判别分析.结果表明:各月龄凡纳滨对虾性状之间均呈现显著的正相关(P<0.01), 其中以全长与体长的相关性最为明显,1月龄凡纳滨对虾体重与形态性状的相关系数较小.各月龄凡纳滨对虾的主成分有所不同,1～2月龄凡纳滨对虾的第一主成分为长度因子,第二主成分为宽度因子,第三主成分为高度因子;3月龄凡纳滨对虾的第一主成分与1～2月龄凡纳滨对虾一致,但第二主成分为高度因子,第三主成分为体重因子;4～6月龄凡纳滨对虾的第一主成分为体重因子,第二主成分为高度因子,第三主成分为宽度因子.1～3月龄凡纳滨对虾形态性状的增长优先于体重, 4～6月龄凡纳滨对虾体重优先于形态性状的增长.错过最佳生长季节的凡纳滨对虾的与体格大小相符的月龄可通过建立的判别式来判断,总的判别准确率为98.98%,其中2～4月龄凡纳滨对虾的判别准确率为100%.     

Population structure,morphological and genetic diversity within and among melon (Cucumis melo L.) landraces in Iran

ISSR markers were applied to evaluate the genetic diversity and differentiation of 270 individuals of 27 Iranian C. melo landraces of various varietal groups include vars. inodorous, cantalupensis, reticulatus, ameri, dudaim. Genetic diversity among the studied genotypes obtained by GeneAlex analysis (H?=?0.08, I?=?0.12, Na?=?0.77, PPL?=?22.6%). Cluster analysis divided Iranian melon landraces into two main cluster. Non-sweet genotype (dudaim group) was well separated from sweet genotypes (inodorous, ameri, reticulatus, cantalupensis). The most similar genotypes were BANI and TONI (0.95) and the most dissimilar ones were GER and TS (0.58). AMOVA result showed that the percentage of genetic variation among and within Iranian melon is 69% and 31%, respectively. All landraces evaluated based on 10 morphological traits which revealed the diversity of melon varietal groups. Bayesian analysis assigned ten landraces to Pop 1, eight landraces to Pop 2 and nine melon landraces to Pop 3. Bayesian and UPGMA cluster analyses demonstrated the almost related results. Our results indicated that ISSR markers technique alongside polyacrylamide gel analysis could be helpful to discriminate varieties of melon.