executed the experiments. Tanya Verma, Purbasha Dasgupta and Bodhisatta Nandy analysed and interpreted the results.

No abstract

Notwithstanding recent evidences, paternal environment is thought to be a potential but unlikely source of fitness variation that can affect trait evolution. Here we studied intergenerational effects of males’ exposure to varying adult density in Drosophila melanogasterlaboratory populations. We held sires at normal (N), medium (M) and high (H) adult densities for 2 days before allowing them to mate with virgin females. This treatment did not introduce selection through differential mortality. Further, we randomly paired males and females and allowed a single round of mating between the sires and the dams. We then collected eggs from the dams and measured the egg size. Finally, we investigated the effect of the paternal treatment on juvenile and adult (male) fitness components. We found a significant treatment effect on juvenile competitive ability where the progeny sired by the H‐males had higher competitive ability. Since we did not find the treatment to affect egg size, this effect is unlikely to be mediated through variation in female provisioning. Male fitness components were also found to have a significant treatment effect: M‐sons had lower dry weight at eclosion, higher mating latency, and lower competitive mating success. While being the first study to show both adaptive and non‐adaptive effect of the paternal density in Drosophila, our results highlight the importance of considering paternal environment as important source of fitness variation.

No abstract

Individual inequality is growing in America today and the subject is of great interest. But spatial inequality —“how and why spatial context contributes to inequality” (Labao et. al. 2007:3) -has just begun to be studied. If certain geographical areas are inherently richer due to accessibility, population size, or soils, for example, how much individual equality can a society hope to achieve? Furthermore, inequality due to spatial differences seems to endure over time (Labao and Hooks 2007:48; Peters 2012) and may be quite difficult to alter. This paper describes spatial inequality in wealth at the county level in the middle of the nineteenth century in the Northeastern US at a time when the US economy was growing rapidly and individual inequality was increasing. It applies Bayesian hierarchical spatial modeling in an attempt to understand the underlying causes of the differences in wealth between counties. The underlying spatial structure of inequality was rather different at this time: indeed, the urban agglomerations and industrial economy we know today were just coming into being. A unique feature of our work is the inclusion of a measure of soil quality that has not been used so far in either historical or contemporary investigations.