Evaluation of discrete host–parasitoid models for diamondback moth and Diadegma semiclausum field time population density series

The performance of discrete mathematical models to describe the population dynamics of diamondback moth (DBM) (Plutella xylostella L.) and its parasitoid Diadegma semiclausum was investigated. The parameter values for several well-known models (Nicholson–Bailey, Hassell and Varley, Beddington, Free and Lawton, May, Holling type 2, 3 and Getz and Mills functional responses) were estimated. The models were tested on 20 consecutive sets of time series data collected at 14 days interval for pest and parasitoid populations obtained from a highland cabbage growing area in eastern Kenya. Model parameters were estimated from minimized squared difference between the numerical solution of the model equations and the empirical data using Powell's method. Maximum calculated DBM growth rates varied between 0.02 and 0.07. The carrying capacity determined at 16.5 DBM/plant by the Beddington et al. model was within the range of field data. However, all the estimated parameter values relating to the parasitoid, including the instantaneous searching rate (0.07–0.28), per capita searching efficiency (0.20–0.27), search time (5.20–5.33), handling time (0.77–0.90), and parasitism aggregation index (0.33), were well outside the range encountered empirically. All models evaluated for DBM under Durbin–Watson criteria, except the May model, were not autocorrelated with respect to residuals. In contrast, the criteria applied to the parasitoid residuals showed strong autocorrelations. Thus, these models failed to estimate parasitoid dynamics. We conclude that the interactions of the DBM with its parasitoid cannot be explained by any of the models tested. Two factors may be associated with this failure. First, the parasitoid in this integrated biological control system may not be playing a major role in regulating DBM population. Second, and perhaps more likely, poor correlations reflect gross inadequacies in the theoretical assumptions that underlie the existing models.     

Soil amendments and cultivar selection can improve rice yield in salt-influenced (tsunami-affected) paddy fields in Sri Lanka

The tsunami disaster in the Indian Ocean in December 2004 caused devastation of agricultural soils by salt water over wide areas. Many rice fields located close to the coast were affected by the flood of seawater. Electric conductivity (EC) of soils in tsunami-affected rice fields was found to be higher compared to unaffected fields 2 years after the tsunami. Four soil amendments (gypsum, dolomite, cinnamon ash and rice-husk-charcoal) were tested for their influence on improving the yield parameters of rice grown in a tsunami-affected and a non-affected area. Yield parameters were compared with an untreated control of the same cultivar (AT362) and with a salt resistant rice variety (AT354). The salt resistant variety had the highest grain yield. The two amendments gypsum and rice-husk-charcoal led to an increase in grain yield compared to the untreated control, whereas dolomite and cinnamon ash had no significant effect on grain yield.     

On the use of manned hydrogen-gas ballooning in boundary layer studies

Measurements of nitrogen dioxide, ozone and, for the first time, on-line, nonmethane hydrocarbons with a quasicontinuous gaschromatographic/flame ionization technique were performed on a manned hydrogen-gas balloon platform. A cycle time of 10 min allowed the determination of nonmethane hydrocarbons in the carbon number range of C₄-C₁₀ with a detection limit of 10 pptv. In addition, meteorological parameters (atmospheric pressure, temperature, humidity) along with GPS-data (global positioning system) was accomplished during the balloon flights. Balloon measurements of trace compounds provide valuable information about photochemical processes in the boundary layer since gas ballooning offers the only technique that stays in the same air parcel along Langrangian trajectories. In addition, gas ballooning represents a unique tool to elucidate micrometeorological observations such as atmospheric stability oscillations and local wind fields.     

城市有机垃圾蚯蚓堆肥处理的实验研究

采用蚯蚓堆肥处理4种不同有机废物,通过分析样品的温度、有机分含量、pH值以及实验前后样品的质量等参数的变化,比较蚯蚓堆肥处理不同有机垃圾的效果。实验结果表明:1.在合理条件下,蚯蚓堆肥可以直接处理生活有机垃圾和污泥(包括其堆肥后产物);2.在同样的实验条件下,蚯蚓堆肥处理生活有机垃圾和污泥及其堆肥后产物过程中,其处理城市生活有机垃圾的效果最好,减量化和物降解率分别为69.8%和75%。     

Comparative genomics: methods and applications

Interpreting the functional content of a given genomic sequence is one of the central challenges of biology today. Perhaps the most promising approach to this problem is based on the comparative method of classic biology in the modern guise of sequence comparison. For instance, protein-coding regions tend to be conserved between species. Hence, a simple method for distinguishing a functional exon from the chance absence of stop codons is to investigate its homologue from closely related species. Predicting regulatory elements is even more difficult than exon prediction, but again, comparisons pinpointing conserved sequence motifs upstream of translation start sites are helping to unravel gene regulatory networks. In addition to interspecific studies, intraspecific sequence comparison yields insights into the evolutionary forces that have acted on a species in the past. Of particular interest here is the identification of selection events such as selective sweeps. Both intra- and interspecific sequence comparisons are based on a variety of computational methods, including alignment, phylogenetic reconstruction, and coalescent theory. This article surveys the biology and the central computational ideas applied in recent comparative genomics projects. We argue that the most fruitful method of understanding the functional content of genomes is to study them in the context of related genomic sequences. In particular, such a study may reveal selection, a fundamental pointer to biological relevance.     

An object-oriented software for fate and exposure assessments

The model system CemoS¹ (Chemical Exposure Model System) was developed for the exposure prediction of hazardous chemicals released to the environment. Eight different models were implemented involving chemicals fate simulation in air, water, soil and plants after continuous or single emissions from point and diffuse sources. Scenario studies are supported by a substance and an environmental data base. All input data are checked on their plausibility. Substance and environmental process estimation functions facilitate generic model calculations. CemoS is implemented in a modular structure using object-oriented programming. e-mail: cemos@aphrodite.mathematik.uni-osnabrueck.de