Sperm competition and the level of polyandry in a bushcricket with large nuptial gifts

Variation in paternity due to sperm competition or post-copulatory female choice has a major influence on animal mating system evolution and on the levels of genetic variability in natural populations. However, there are relatively few studies comparing the outcome of sperm-competition experiments in the laboratory with natural variation in polyandry among families from the field. In the bushcricket Ephippiger ephippiger, females mate multiply, and the males provide them with a large, nutritious, and probably expensive, donation at mating. We examined paternity in a series of laboratory matings, where females mated with two males, and amongst a series of families collected from a natural population. In the laboratory, paternity was highly bimodally distributed: 24% of families had offspring fathered by the first male to mate, 68% by the second male (in only 8% was paternity shared). In the field, paternity was more mixed: only 27% of families had a single father, 14% had more than two fathers, whilst 59% had two fathers. While unsuccessful matings may contribute to the highly biased paternity in the laboratory, they cannot fully explain the high incidence of complete P2 families. Nonrandom sperm utilisation is therefore likely. Greater sperm mixing in the field probably results from females mating with more males, but the distribution of paternity also reflects an active process of nonrandom sperm utilisation. Confidence of paternity due to last male advantage may be relatively high in this species, and therefore may have facilitated the evolution of the large spermatophore in E. ephippiger.Communicated by D. Gwynne     

Global-scale vs. regional-scale scenario assumptions: implications for estimating future water withdrawals in the Elbe River basin

In this paper, we explore how scenarios of future water withdrawals in a river basin are influenced by scale-dependent quantifications of the driving forces for two global-scale storylines. Either global-scale information or region-specific information is used to do the quantifications. In addition, we analyze the impact of including or not some restricted regional-scale information in the employed water use model. To develop scenarios of water withdrawals in the German part of the Elbe River basin, we applied the modules for domestic, thermoelectric power and manufacturing water use of the global water model WaterGAP, using scale-dependent driving forces scenarios and other scale-dependent model input. In the global-scale quantitative interpretations of the storylines of the IPCC SRES scenarios A1 and B2, all major driving forces of water withdrawals in the basin—population, thermoelectric power production and industrial gross domestic product—show vigorous increases between 2000 and 2025, while from the regional perspective, smaller increases but mostly decreases appear to be plausible. These discrepancies are partly due to the fact that for the global-scale interpretations only the historic developments until 1990 were taken into account, and not until 2000 as in the regional case. The resulting scenarios of sectoral water withdrawals in 2025 differ strongly between the two scale-dependent interpretations of the storylines, with the global one leading to much higher absolute water withdrawals and much lower withdrawal decreases between 2000 and 2025. Therefore, for regional assessments of water withdrawals, we recommend to embed the scenario analysis in global-scale storylines by performing regional-scale quantifications of the global qualitative driving forces scenarios, based on a limited amount of region-specific information.     

Estimating receptor sensitivity to spatial proximity of emissions sources

Spatial proximity of emissions sources to receptors may affect sensitivity to potential adverse human health effects. This research investigates whether receptor sensitivity to the location of emission sources can be utilized efficiently to minimize health risk in selecting sites for industrial enterprises, thermal electric stations, etc. A sensitivity function that is independent of the location of pre-existing emission sources is derived and applied to Minsk, Belarus. The function estimates exposures based on weather and climatic conditions as well as the distribution of population density at a given locality. Arraying prospective sites based on their sensitivity function magnitude provides a technique for minimizing health risk based on receptor sensitivity to the spatial proximity of atmospheric emissions sources.     

Geographic variability of Escherichia coli ribotypes from animals in Idaho and Georgia

Several genotypic methods have been developed for determining the host origin of fecal bacteria in contaminated waters. Some of these methods rely on a host origin database to identify environmental isolates. It is not well understood to what degree these host origin isolates are geographically variable (i.e., cosmopolitan or endemic). This is important because a geographically limited host origin database may or may not be universally applicable. The objective of our study was to use one genotypic method, ribotyping, to determine the geographic variability of the fecal bacterium, Escherichia coli, from one location in Idaho and three locations in Georgia for cattle (Bos taurus), horse (Equus caballus), swine (Sus scrofa), and chicken (Gallus gallus domesticus). A total of 568 fecal E. coli isolates from Kimberly, ID (125 isolates), Athens, GA (210 isolates), Brunswick, GA (102 isolates), and Tifton, GA (131 isolates), yielded 213 ribotypes. The percentage of ribotype sharing within an animal species increased with decreased distance between geographic locations for cattle and horses, but not for swine and chicken. When the E. coli ribotypes among the four host species were compared at one location, the percent of unshared ribotypes was 86, 89, 81, and 79% for Kimberly, Athens, Brunswick, and Tifton, respectively. These data suggest that there is good ribotype separation among host animal species at each location. The ability to match environmental isolates to a host origin database may depend on a large number of environmental and host origin isolates that ideally are not geographically separated.     

Alles Schadstoff, alles Umwelt?

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