Host-related antennal variation in the polyphagous egg parasite Telenomus alsophilae (Hymenoptera: Scelionidae)

Abstract. The solitary egg parasite Telenomus alsophilae was reared from the eggs of six lepidopteran hosts of two families. One-way analyses of variance showed statistically significant differences among host classes for means of (a) lengths and widths of all female antennomeres; and (b) in twelve of twenty-three means of log-transformed ratios constructed from pairs of antennomere dimensions. Principal component analyses of dispersion matrices of both untransformed and log-transformed antennomere dimensions were conducted to examine patterns of variation among variables. In both analyses PCI was a general component and interpreted as a measure of overall size. One-way analyses of variance of projection scores of OTUs on each of the first five principal components showed significant differences among host classes for means of scores on (a) PCI (both analyses) and (b) PC4 for untransformed data and PC3 for log-transformed data. Differences among hosts classes for scores on the latter two components are interpreted to indicate that antennal variation results from factors in addition to simple size differences among host eggs and the allometric growth of body parts of parasites reared from them.     

Russian genofond. Genogeography of surnames

Surnames are traditionally used in population genetics as "quasi-genetic" markers (i.e., analogs of genes) when studying the structure of the gene pool and the factors of its microevolution. In this study, spatial variation of Russian surnames was analyzed with the use of computer-based gene geography. Gene geography of surnames was demonstrated to be promising for population studies on the total Russian gene pool. Frequencies of surnames were studied in 64 sel'sovets (rural communities; a total of 33 thousand persons) of 52 raions (districts) of 22 oblasts (regions) of the European part of Russia. For each of 75 widespread surnames, an electronic map of its frequency was constructed. Summary maps of principal components were drawn based on all maps of individual surnames. The first 5 of 75 principal components accounted for half of the total variance, which indicates high resolving power of surnames. The map of the first principal component exhibits a trend directed from the northwestern to the eastern regions of the area studied. The trend of the second component was directed from the southwestern to the northern regions of the area studied, i.e., it was close to latitudinal. This trend almost coincided with the latitudinal trend of principal components for three sets of data (genetic, anthropological, and dermatoglyphical). Therefore, the latitudinal trend may be considered the main direction of variation of the Russian gene pool. The similarity between the main scenarios for the genetic and quasi-genetic markers demonstrates the effectiveness of the use of surnames for analysis of the Russian gene pool. In view of the dispute between R. Sokal and L.L. Cavalli-Sforza about the effects of false correlations, the maps of principal components of Russian surnames were constructed by two methods: through analysis of maps and through direct analysis of original data on the frequencies of surnames. An almost complete coincidence of these maps (correlation coefficient rho = 0.96) indicates that, taking into account the reliability of the data, the resultant maps of principal components have no errors of false correlations.     

广西平果县喀斯特山地蚬木生存群落物种多样性与环境的关系

基于野外调查和室内实验数据,采取主成分分析和典型相关分析相结合的方法,分析了广西平果县喀斯特山地蚬木(Excentrodendron hsienmu)生存群落物种多样性与土壤养分和地形因子间的关系。结果表明:群落各层的物种数、Shannon-Wiener指数和Pielou均匀度指数表现为乔木层灌木层草本层。主成分分析的前3个主成分解释了总变异的78.8%,第一主成分的特征值为5.29,方差贡献率为44.0%,主要反映了土壤养分的综合信息。典型相关分析显示乔木层多样性能敏感指示土壤养分变化,与土壤全磷间呈负相关、与全氮间呈正相关;灌木层物种多样性对地形变化更为敏感,与坡位和海拔间均表现为正相关关系;土壤与地形因子间存在较为密切的耦合关系,土壤全磷与坡位间呈正相关、土壤pH与岩石裸露率间呈负相关。     

木焦油污染土壤中微生物特性的空间变异性研究

运用地统计学方法研究了木焦油污染土壤中微生物量、微生物群落结构、微生物活性等的空间变异特征.分别采用26种主要磷脂类脂肪酸(PLFA)的总含量(totPLFA)、PLFA的第一主成分和第二主成分(PLFA PC1和PC2)以及土壤培养过程中CO₂-C的累积释放量(Cre)来表征土壤中的微生物量、微生物群落结构以及微生物活性.结果表明,多数微生物特性指标均存在不同程度的空间自相关性,其半变异函数曲线可用带块金效应的球状模型进行拟合.变量的空间相关距离在2.50～16.60 m之间.PLFA PC1、totPLFA和Cre均具有较强的空间依赖性,其相对结构变差（由结构性因素引起的空间变异）分别为82.3%、79.6%和64.7%,而PLFA PC2 不存在明显的空间依赖性.克立格空间插值图表明,样地中存在几处微生物相对密集分布且代谢活性较高的区域,其中优势微生物菌群是由PLFAs 16:1ω7t,cy17:0,18:1ω7 和cy19:0所表征的革兰氏阴性细菌.土壤中主要污染物多环芳烃含量和空间分布是影响微生物特性空间分布格局的重要因素之一.     

"Synthetic" maps of the Mari gene pool (from immunobiochemical polymorphism data)]

Models of geographic distribution of 33 alleles of 10 loci (AB0, TF, GC, PI, HP, AHS, F13B, ACP1, PGM1, GLO1) in the indigenous population of five raions (districts) of Marii El Republic were analyzed by cartographic statistical methods. Based on 33 maps for individual alleles, synthetic maps were constructed; they reflected the general characteristics of the spatial variability of the Mari gene pool. A map of reliability of the synthetic maps was also obtained. This study was the first to use estimates of the reliability of the gene-geographic prognosis for constructing and interpreting the maps of principal components. Synthetic maps of principal components reveal the geography of the main factors that determine the genetic diversity of the Maris. In the map of the first principal component (accounting for 25.5% of the total variation of the Mari gene pool), isolines clearly ran in the latitudinal direction; i.e., the variability exhibited a north-south gradient. The direction of changes reflects the characteristic features of the microevolution of the Mari gene pool, because it differs from the direction of the principal components of in the total Ural gene pool. The second principal component (24.3% of variation) also exhibited a latitudinal gradient in the western part of Marii El. In the eastern part of the republic, isolines drastically change their direction and display a marked west-east gradient. This longitudinal orientation of principal components is characteristic of the Maris in the synthetic maps of the Ural region. Contributions of individual genes in the variation of principal components were analyzed. In proceeding from the geographic space to the space of principal components, it was found that Highland Maris are separated from Meadow Maris not only geographically, but also genetically.     

The Russian Gene Pool: Gene Geography of Surnames

Surnames are traditionally used in population genetics as quasi-genetic markers (i.e., analogs of genes) when studying the structure of the gene pool and the factors of its microevolution. In this study, spatial variation of Russian surnames was analyzed with the use of computer-based gene geography. Gene geography of surnames was demonstrated to be promising for population studies on the total Russian gene pool. Frequencies of surnames were studied in 64 sel'sovets (rural communities; a total of 33 thousand persons) of 52 raions (districts) of 22 oblasts (regions) of the European part of Russia. For each of 75 widespread surnames, an electronic map of its frequency was constructed. Summary maps of principal components were drawn based on all maps of individual surnames. The first 5 of 75 principal components accounted for half of the total variance, which indicates high resolving power of surnames. The map of the first principal component exhibits a trend directed from the northwestern to the eastern regions of the area studied. The trend of the second component was directed from the southwestern to the northern regions of the area studied, i.e., it was close to latitudinal. This trend almost coincided with the latitudinal trend of principal components for three sets of data (genetic, anthropological, and dermatoglyphical). Therefore, the latitudinal trend may be considered the main direction of variation of the Russian gene pool. The similarity between the main scenarios for the genetic and quasi-genetic markers demonstrates the effectiveness of the use of surnames for analysis of the Russian gene pool. In view of the dispute between R. Sokal and L.L. Cavalli-Sforza about the effects of false correlations, the maps of principal components of Russian surnames were constructed by two methods: through analysis of maps and through direct analysis of original data on the frequencies of surnames. An almost complete coincidence of these maps (correlation coefficient = 0.96) indicates that, taking into account the reliability of the data, the resultant maps of principal components have no errors of false correlations.     

Gene geography of South America: testing models of population displacement based on archeological evidence.

Gene frequencies for 13 marker systems are used to construct synthetic gene frequency maps of South America. The surfaces generated using the first three principal components exhibit clines which validate models of population displacement based on archeological data and a previous analysis of craniometrical variation.     

Leaf architecture of the genus Didymaea Hook. f. (Rubiaceae)

We examined 532 specimens representing eight species of Didymaea (Rubiaceae) to describe their leaf architecture. Characters observed in the herbarium specimens and cleared leaves were leaf base, apex, and margin; trichome type and distribution; vein orders from primary to higher order veins, veinlets, and ultimate marginal vein. Six morphometric variables were analyzed using variance and principal component analysis to identify which characters are useful to distinguish species. Most of the species present brochidodromous venation pattern, except D. hispidula, which has eucamptodromous venation pattern; Didymaea floribunda is unique in having cylindrical and bicellular trichomes. Principal component analysis revealed that 78% of the total variation is mainly related to leaf maximum width. Variance analysis showed significant differences between D. microflosculosa and the other species. Architectural features were useful for differentiating all the species, and an identification key for the species of Didymaea based only on leaf characters is presented.     

Use of direct gradient analysis to study the climate-vegetation relationships in Galicia,Spain

This paper reports a bioclimatic analysis of plant species in Galicia, NW Spain. A set of floristic data obtained from 150 plots located at euclimatopes (sites with monitored climate) was analysed using direct gradient analysis and clustering with respect to the 8 climatic variables thought to play a major role in regulating the distribution of the species considered in the study area. Principal component analysis (PCA) and hierarchical clustering were based on a matrix of species by climatic variables. Indicator taxa for the variables were identified on the basis of their Indicator values (Brisse & Grandjouan 1978) and grouped by cluster analysis. The groups produced were compatible with the results of principal component analysis and the frequential analysis of the species, which identified their phytoclimatic nature. The groups were then characterized by determining their climatic positions and indicator values with respect to the chief climatic variables. The first three PCA axes, which were associated with Oceanity, Mean minimum temperatures and the temperature range in the coldest month, together accounted for 97.2% of the variance of the data.     

Determinant variables of Iberian Peninsula Aphodiinae diversity (Coleoptera, Scarabaeoidea, Aphodiidae)

Aim The aims of this paper are to examine diversity–variability patterns for species of Aphodiinae (Coleoptera, Scarabaeoidea, Aphodiidae) on the Iberian Peninsula, and to determine the factors that influence their geographic distribution. Location Iberian Peninsula (Spain and Portugal). Methods Data from 30 studies and their bibliographies on species of Iberian Peninsula Aphodiinae were compiled. The reliability of the inventories was evaluated using parametric species richness estimators. In addition, a further 11 variables related to rarity, geographic distribution, or phylogenetic diversity were considered. Diversity variables were analysed using principal components analysis to reduce the number of dependent variables. Subsequently, the effect of differences in locality size among the 30 studies was eliminated by calculating and retaining the residuals of the curvilinear relationship of each diversity variable with the area. Generalized linear models were used to examine the relationships between diversity and 17 environmental variables. The diversity variables and their residuals were also subject to trend surface analysis in order to identify the relevance of spatially structured variables that had not been considered. The contribution of explanatory variables was determined through hierarchical variance analysis. Results Principal components analysis of biodiversity variables revealed that most of the variability could be explained using three biodiversity indexes: BI1, correlated positively with species richness, widely distributed species, frequent species, abundant species, species occurring in North Africa, Europe and the Iberian Peninsula, and phylogenetic diversity; BI2, correlated positively with numbers of infrequent and African–Iberian species; and, BI3, correlated positively with numbers of endemic, non‐abundant, European, and Iberian‐restricted species. A latitudinal disjunction emerged in BI1, with maximum scores at the north‐western and southern corners, while maximum BI2 scores were found throughout the south, and maximum BI3 scores in the north‐west. For BI1, it was climate that had the greatest influence, followed by lithology, and livestock presence. Geographic variables were the most significant for BI2, followed by climate and livestock presence. Finally, for BI3, climate variables were the most important, while geography, lithology and livestock presence had some relevance. Main conclusions The relevance of geographic variables indicates that other unaccounted‐for factors that are spatially structured could possibly explain additional variation in Aphodiinae diversity. These factors may be historic in nature, relating to the species groups, namely the Ibero‐European and the Mediterranean or Afro‐Iberian. The northern pattern could reflect the fact that the Iberian Peninsula acted as a colonization route and as a refuge during the glacial/interglacial cycles, while the southern pattern could be a consequence of the connection between the Iberian Peninsula and North Africa during the Messinian crisis, and/or a historic relationship in common, related to human activity.     

The use of principal component analysis for the modelling of high performance liquid chromatography

Principal component analysis (PCA) was used to analyse the behaviour of a chromatographic separation as its scale increased. Three 4.6 mm diameter columns identical in every respect except for column length (25, 15 and 5 cm), were used to generate the data from a test system based on the reversed-phase HPLC separation of crude erythromycin on a polystyrene matrix (PLRP 1000) having a particle diameter of 8 mu;m and a pore diameter of 100 nm. The species were separated with an isocratic solvent composed of 45/55 acetonitrile/water at about pH 7. An experimental design technique was used to investigate the effects of four process variables (load volume, load concentration, temperature and pH of buffer) on the chromatogram shapes. Following appropriate pre-processing of the chromatographic data, subsets of critical chromatograms were selected which sufficiently characterised the entire data set. From this subset, the corresponding runs were performed on the different sized columns and principal component models were generated for each. At 5 and 15 cm a single principal component was sufficient to characterise all the variance in the chromatograms which the range of process variables introduced, but at 25 cm two principal components were required, particularly to characterise the chromatograms with small loads. Excellent correlations were observed between the first principal components at the three scales. The possibility of predicting the separations on the 25 cm column from an analysis of the separations observed at 5 cm was investigated. The study revealed that good predictions could be made at high loads (>92%) , but the model was not effective at low loads because of the need to incorporate a second principal component which was not defined by the range of variables applied to the 5 cm column.     

Morphometric differentiation of Pseudocalanus minutus populations in the Barents Sea

Dvoretsky VG. and Dvoretsky AG. 2011. Morphometric differentiation of Pseudocalanus minutus populations in the Barents Sea. —Acta Zoologica (Stockholm) 00 : 1–12. We investigated spatial variations in the morphometric characteristics (total length of body, lengths of cephalothorax, abdomen and antennules, and their relative proportions) of Pseudocalanus minutus, an abundant copepod species across the Barents Sea in August–September 2007. Females were found to have higher values for the measured parameters than males. The average absolute morphometric characters of both sexes increased from the south to the north. In most cases, parameters were similar in the southern, central, and eastern regions delineated by cluster analyses of oceanographic variables. The morphometric characteristics were strongly correlated with environmental variables in both males and females. Multiple regression analysis showed that temperature together with salinity explained 72–85% (in females) and 38–91% (in males) of the total variations in the log₁₀‐transformed morphometric parameters. According to principal component analysis and discriminant function analysis, two distinct groups could be separated in the Barents Sea. The first group included the copepods from the northern region; the other included populations from the southern, central, and eastern regions. The observed morphological variation can be interpreted as geographical variation connected with hydrological variability.     

Quantitative analysis of correlations among flower traits in Gerbera hybrida, Compositae. III. Genetic variability and structure of principal component traits

 A sample of 36 flower traits consisting of six morphological categories in the Davis population of gerbera was restructured into phenotypic and genetic principal component traits. The first 5 phenotypic principal component traits accounted for 62% of the total phenotypic variance of the 36 traits and have moderate to high heritablities. The first 5 genetic principal component traits account for 97% of total genetic variance and all have high heritability. Morphological structure of these component traits suggest an underlying process identified by the first genetic principal component involving largely trans and disk floret traits. The results of this study indicate that the quantitative genetic structure of the gerbera flower is controlled by a few independent components and that principal component analysis is a useful tool to reveal variation in this structure. These composite traits are heritable and are expected to respond to selection. Received: 20 September 1997 / Accepted: 19 January 1998     

Intraspecific Functional Trait Variation in a Tree Species (Lithocarpus dealbatus) along Latitude

We quantied intraspecic variation and covariation of leaf mass per area (LMA), leaf dry matter concentration (LD), leaf frost sensitivity (LFS) and Fv/Fm of leaves of 8 Lithocarpus dealbatus populations across the geographical distribution from north to south to determine the magnitude and whether it is related to environmental conditions, latitude and mean annual temperature. The results showed that the total variation (coefcient of variation) of LMA, LD, LFS and Fv/Fm were 160%, 177%, 211% and 401% respectively. The total intraspecic variation was contributed by the difference among populations, individuals and leaves. The difference among populations accounted for the largest total variation in LMA, LD and Fv/Fm, whereas the difference among leaves accounted for the largest total variation in LFS. On population level, LMA was significantly positive related to the latitude and Fv/Fm was significantly negative, but LD and LFS were not related to the latitude. LMA decreased while Fv/Fm increased significantly with the increase of mean annual temperature. LD was a downward quadratic variation, and LFS was upward with the increase of mean annual temperature. The principal component analysis of four functional traits showed that no population was located nearer to the origin of the first and second principal component, and populations at the edge of distribution area located at both sides of the first principal component axis. The results suggested that the environmental variation in the distribution could cause intraspecic variation of functional traits. There is no population could represent a species in functional traits. When an average trait value for species is considered and trait comparisons are done among species, intraspecific variation of traits could not be ignored.     

Morphological variability of potato cyst nematodes (Globodera spp.) in the Canary Islands

Thirty populations of potato cyst nematode (Globodera spp.) from the Island of Tenerife and two populations from the UK were assessed for several morphometric and non-morphometric characters thought to discriminate between the species G. rostochiensis and G. pallida. Also 200 cysts from each population were analysed by isoelectric focusing of soluble proteins. Correlation analysis, analysis of variance and principal component analysis were used to investigate relationships between the morphometric characters, how the relationships varied between species and between populations, and which characters were most useful for discriminating between species. The two species differed significantly for each of the four morphometric characters: stylet length, fenestra length, anus-fenestra distance and the number of ridges. The stylet length and fenestra length also showed differences between populations of G. rostochiensis while stylet length and number of ridges showed differences between populations of C. pallida. In general, populations of G. pallida showed greater variation than populations of C. rostochiensis. Principal component analysis of the population means indicated that over 73% of the variation in the characters could be explained by the contrast of stylet and fenestra lengths against the anus-fenestra distance and number of ridges. A plot of the first two principal components separated the two species. Stepwise discriminant analysis provided a linear combination of these four variables which discriminated between the species. Stylet length was found to be the most useful characteristic for distinguishing the species whilst anus-fenestra distance was the least useful.     

Placental polar lipid composition is associated with placental gene expression and neonatal body composition

The polar-lipid composition of the placenta reflects its cellular heterogeneity and metabolism. This study explored relationships between placental polar-lipid composition, gene expression and neonatal body composition.Placental tissue and maternal and offspring data were collected in the Southampton Women's Survey. Lipid and RNA were extracted from placental tissue and polar lipids measured by mass spectrometry, while gene expression was assessed using the nCounter analysis platform. Principal component analysis was used to identify patterns within placental lipid composition and these were correlated with neonatal body composition and placental gene expression.In the analysis of placental lipids, the first three principal components explained 19.1%, 12.7% and 8.0% of variation in placental lipid composition, respectively. Principal component 2 was characterised by high principal component scores for acyl-alkyl-glycerophosphatidylcholines and lipid species containing DHA. Principal component 2 was associated with placental weight and neonatal lean mass; this component was associated with gene expression of APOE, PLIN2, FATP2, FABP4, LEP, G0S2, PNPLA2 and SRB1. Principal components 1 and 3 were not related to birth outcomes but they were associated with the gene expression of lipid related genes. Principal component 1 was associated with expression of LEP, APOE, FATP2 and ACAT2. Principal component 3 was associated with expression of PLIN2, PLIN3 and PNPLA2.This study demonstrates that placentas of different sizes have specific differences in polar-lipid composition and related gene expression. These differences in lipid composition were associated with birth weight and neonatal lean mass, suggesting that placental lipid composition may influence prenatal lean mass accretion.     

Models of Quantitative Variation of Flux in Metabolic Pathways

As a model of variation in a quantitative character, enzyme activity variation segregating in a population is assumed to affect the flux in simple metabolic pathways. The genetic variation of flux is partitioned into additive and nonadditive components. An interaction component of flux variance is present because the effect of an allelic substitution is modified by other substitutions which change the concentrations of shared metabolites. In a haploid population, the the proportion of interaction variance is a function of the gene frequencies at the loci contributing to the flux variation, enzyme activities of mutant and wild type at variable loci and activities at nonvariable loci. The proportion of interaction variance is inversely related to the ratio of mutant to wild-type activities at the loci controlling the enzyme activities. The interaction component as a function of gene frequencies is at a maximum with high mutant allele frequencies. In contrast, the dominance component which would apply to a diploid population is maximal as a proportion of the total when mutant alleles are at low frequencies. Unless there are many loci with large differences in activity between the alleles, the interaction component is a small proportion of the total variance. Data on enzyme activity variation from natural and artificial populations suggest that such variation generates little nonadditive variance despite the highly interactive nature of the underlying biochemical system.     

Stock structure analysis of Labeo rohita (Hamilton, 1822) across the Ganga basin (India) using a truss network system

In this study the intraspecific variation of wild Labeo rohita was investigated on the basis of morphometric characters using the truss network system constructed from the fish body. Altogether 435 fish samples were collected from six drainages of the Ganga basin in India. Data were subjected to principal component analysis, discriminant function analysis and univariate analysis of variance. The first principal component (PC1) explained 47.88% of the total variation, while PC2 and PC3 explained 17.22 and 8.33%, respectively. The step‐wise discriminant function analysis retained three variables that significantly discriminated the populations. Using these variables, 62.3% of the original groups were classified into their correct samples and 53.1% of the cross‐validated groups omitting one procedure were classified into their correct samples. Misclassification was higher for samples from the River Gomti (28.6%). Of the total of 31 transformed truss measurements, 30 exhibited significant differences among populations. These findings indicate the presence of six different stocks of L. rohita in the Ganga basin.     

Past,current, and future trends of red spiny lobster based on PCA with MaxEnt model in Galapagos Islands,Ecuador

In order to enhance in terms of accuracy and predict the modeling of the potential distribution of species, the integration of using principal components of environmental variables as input of maximum entropy (MaxEnt) has been proposed in this study. Principal components selected previously from the principal component analysis results performed in ArcGIS in the environmental variables was used as an input data of MaxEnt instead of raw data to model the potential distribution of red spiny lobster from the year 1997 to 2015 and for three different future scenarios 2020, 2050, and 2070. One set of six original environmental variables pertaining to the years 1997–2015 and one set of four variables for future scenarios were transformed independently into a single multiband raster in ArcGIS in order to select the variables whose eigenvalues explains more than 5% of the total variance with the purpose to use in the modeling prediction in MaxEnt. The years 1997 and 1998 were chosen to compare the accuracy of the model, showing better results using principal components instead of raw data in terms of area under the curve and partial receiver operating characteristic as well as better predictions of suitable areas. Using principal components as input of MaxEnt enhances the prediction of good habitat suitability for red spiny lobster; however, future scenarios suggest an adequate management by researches to elaborate appropriate guidelines for the conservation of the habitat for this valuable specie with face to the climate change.     

Biometric analysis of the mandibles of Papio anubis and Cercopithecus aethiops

Six biometric measurements were recorded from dry mandibles of 53 Papio anubis and 84 Cercopithecus aethiops: intercondylar width, intercoronoid width, intermolar width (IMW), mesiodistal width of the condyles, height of the occlusal table and anteroposterior length of the chewing surface from P4 to M3 (CL). The mean values and correlation matrices of these variables show that, despite the difference in size, the overall shape of the mandible in male and female is similar within species. The principal component analysis shows that in P. anubis the six variables contribute almost equally to the first component (75% of total variance), suggesting that the large mandible may be force related because of the greater mechanical forces required for chewing certain foods. In C. aethiops, the contribution of IMW and CL is less in the first component (52.7% of total variance), suggesting that the biochemical forces of mastication are more complex to adapt the mandible to a shorter muzzle and a particular diet.