Morphological and morphometrical analysis of Heterodera spp. populations in Jordan

Phenotypic diversity of five Jordanian populations of cyst nematodes, Heterodera spp. collected from five regions from Jordan (Ar-Ramtha, Madaba, Dana, Al-Karak, and Jerash) was investigated. Soil samples were collected from one representative field in each region. Morphological and morphometrical characteristics revealed that Heterodera latipons is dominated in cereal fields at Ar-Ramtha, Madaba, Dana and Al-Karak regions and Heterodera schachtii in Jerash. Cysts populations from all cereal fields had bifenestrate vulval cone and a strong underbridge. Wherever, cysts of the cabbage population had ambifenestrate vulval cone with long vulval slit. The bullae were absent in Ar-Ramtha, Madaba and Dana populations, but present in Al-Karak and Jerash. Based on 12 morphometrical characters, the first three functions in canonical discriminant analysis accounted 99.3% of the total variation. Distance from dorsal gland duct opening to stylet base, underbridge length, a = L/W (body length/midbody width) and length of hyaline tail tip had strong and significant contributions in the first function. While the second function was strongly influenced by length of hyaline tail, fenestral length, fenestral width and tail length. However, the third canonical discriminate function was found to be influenced by stylet length, fenestral length, a = L/W (body length/midbody width) and underbridge width. The graphical representation of the distribution of the samples showed that the first canonical discriminant function clearly separated H. schachtii from Jerash from other populations. Whereas, H. latipons collected from Madaba and Dana were clearly separated in the second function. The results indicated that differences at morphological and morphometrical levels revealed diverse populations of Heterodera spp. in Jordan.     

Identification of a 13-kDa protein associated with the polyhydroxyalkanoic acid granules from Acinetobacter spp.

Abstract Transferrin-binding proteins from Neisseria meningitidis vary among different isolates. We have identified and studied a hypervariable region adjacent to the carboxyl-end of the transferrin-binding domain of the Tbp2 molecule. The tbp2 genes from six strains of N. meningitidis were cloned and sequenced in this particular region. Sequence analysis of these regions along with five other sequences available from pathogenic Neisseria showed a common organisation of seven highly variable nucleotide stretches interspersed with six conserved nucleotide stretches. The variable regions correlated with the location of immunoreactive epitopes in polyclonal antisera raised to transferrin-binding proteins identified by peptide pin technology. Sequence analysis suggested a mosaic-like organisation of the tbp2 genes. Taken together, these data suggest that the antigenic variation in this part of the protein may result from a strong host immune pressure.     

Assessing population genetic structure and variability with RAPD data: Application to Vaccinium macrocarpon (American Cranberry)

A method for estimating and comparing population genetic variation using random amplified polymorphic DNA (RAPD) profiling is presented. An analysis of molecular variance (AMOVA) is extended to accomodate phenotypic molecular data in diploid populations in Hardy-Weinberg equilibrium or with an assumed degree of selfing. We present a two step strategy: 1) Estimate RAPD site frequencies without preliminary assumptions on the unknown population structure, then perform significance testing for population substructuring. 2) If population structure is evident from the first step, use this data to calculate better estimates for RAPD site frequencies and sub-population variance components. A nonparametric test for the homogeneity of molecular variance (HOMOVA) is also presented. This test was designed to statistically test for differences in intrapopulational molecular variances (heteroscedasticity among populations). These theoretical developments are applied to a RAPD data set in Vaccinium macrocarpon (American cranberry) using small sample sizes, where a gradient of molecular diversity is found between central and marginal populations. The AMOVA and HOMOVA methods provide flexible population analysis tools when using data from RAPD or other DNA methods that provide many polymorphic markers with or without direct allelic data.     

Systematics of Pseudorchis albida s.l. (Orchidaceae) in Europe and North America

In Scandinavia Pseudorchis albida (Orchidaceae)usually divided into the lowland and subalpine P. albida s.s. and the more or less alpine P. straminea. There have been some uncertainties and conflicting views concerning die taxonomic treatment of diese taxa. To address this issue, herbarium specimens of P. albida s.l. were studied for variation in morphological characters. A small-scale population study approach was used, as herbarium sheets with two or three plants were used as population samples. Canonical Variates Analysis (CVA) indicated a distinction between taxa in population means, corresponding to P. albida s.s. and P. straminea , respectively. Principal Components Analysis (PCA), however, revealed an overlap between individuals of the two taxa. The PGA analysis, furthermore, revealed that the overlap was considerably larger in material from Central Europe man in material from Fennoscandia. Student t -tests on separate characters confirmed the picture, wim more characters significantly different in Fennoscandian than in Central European material. Furthermore, a Tukey-Kramer test revealed that there were small differences between regional populations of P. albida s.s. , while there were several significant differences in single characters between the Norm American regional population of P. straminea , as compared with the Central European and Fennoscandian regional populations. In Central Europe there is no clear separation between taxa, while in Fennoscandia the taxa are more clearly separated. This probably means that there is a difference in the time of establishment in the different regions. The author suggests a distinction of taxa at the subspecies level, and argues that the clear distinction seen in Fennoscandian material is due to separate immigration histories for die two subspecies into Fennoscandia after the last period of glaciation.     

Spatial metrics for detecting ecosystem degradation in the ridge-slough patterned landscape

Indicators of landscape condition should be selected based on their sensitivity to environmental changes and their capacity to provide early warning detection of those changes. We assessed the performance of a suite of spatial-pattern metrics selected to quantify the condition of the ridge-slough landscape in the Everglades (South Florida, USA). Spatial pattern metrics (n = 14) that describe landscape composition, geometry and hydrologic connectivity were enumerated from vegetation maps of twenty-five 2 × 2 km primary sampling units (PSUs) that span a gradient of hydrologic and ecological condition across the greater Everglades ecosystem. Metrics were assessed in comparison with field measurements from each PSU of landscape condition obtained from regional surveys of soil elevation, which have previously been shown to capture dramatic differences between conserved and degraded locations. Elevation-based measures of landscape condition included soil elevation bi-modality (BI_SE), a binary measure of landscape condition, and also the standard deviation of soil elevation (SD_SE), a continuous measure of condition. Metric performance was assessed based on the strength (sensitivity) and shape (leading vs. lagging) of the relationship between spatial pattern metrics and these elevation-based measures. We observed significant logistic regression slopes with BI_SE for only 4 metrics (slough width, ridge density, directional connectivity index – DCI, and least flow cost – LFC). More significant relationships (n = 8 metrics) were observed with SD_SE, with the strongest associations for slough density, mean ridge width, and the average length of straight flow, as well as for a suite of hydrologic connectivity metrics (DCI, LFC and landscape discharge competence – LDC). Leading vs. lagging performance, inferred from the curvature of the association obtained from the exponent of fitted power functions, suggest that only DCI was a leading metric of the loss of soil elevation variation; most metrics were indeterminate, though some were clearly lagging. Our findings support the contention that soil elevation changes from altered peat accretion dynamics precede changes in landscape pattern, and offer insights that will enable efficient monitoring of the ridge-slough landscape as part of the ongoing Everglades restoration effort.     

Geographic Information System (GIS) modeling approach to determine the fastest delivery routes

This study involves the adoption of the Geographic Information System (GIS) modeling approach to determine the quickest routes for fresh vegetable delivery. During transport, fresh vegetables mainly deteriorate on account of temperature and delivery time. Nonetheless, little attention has been directed to transportation issues in most areas within Kuala Lumpur. In addition, perishable food normally has a short shelf life, thus timely delivery significantly affects delivery costs. Therefore, selecting efficient routes would consequently reduce the total transportation costs. The regression model is applied in this study to determine the parameters that affect route selection with respect to the fastest delivery of fresh vegetables. For the purpose of this research, ArcGIS software with network analyst extension is adopted to solve the problem of complex networks. The final output of this research is a map of quickest routes with the best delivery times based on all variables. The variables tested from regression analysis are the most effective parameters to make the flow of road networks slower. The objective is to improve the delivery services by achieving the least drive time. The main findings of this research are that Land use such as residential area and population as variables are the effective parameters on drive time.