The use of Arabidopsis thaliana populations to understand the genetic basis for natural variation has been highlighted in recent years. The role of adaptation in natural variation remains of key interest. Here, natural variation in growth rate, flowering time and seed production were examined in local populations of A. thaliana from the Edinburgh area using a common garden approach. Growth rate and seed production were found to be highly genetically determined and sometimes correlated, and some genotypes were found to perform consistently better as winter annuals and others as summer annuals, suggesting that adaptation to different seasons might maintain natural variation locally. In order to dissect the environmental factors that could affect growth, these genotypes were also grown under controlled conditions. Photoperiod and temperature were identified as two of the seasonal variables to which different genotypes may be adapted. The relationship between growth rate and competition was also examined. In general, competition exaggerated the differences in performance between genotypes, although the identity of neighbours was observed to have an effect on both growth rate and fitness of A. thaliana in competition. To understand the genetic basis of growth rate variation, the genetic relationships between local populations was examined. Local accessions were usually found to be more closely related to each other than to world-wide accessions, suggesting that their variation did not reflect recent immigration. To examine the genetic architecture of growth rate variation, hybrids between local genotypes with different growth rates were used in QTL analysis. Four chromosomal regions were detected; these regions represent potential growth-rate associated QTL.

Masters of Science / In 1976 Rozeff and Kinney found that seasonality exists in the monthly rates of return on the New York Stock Exchange with peak periods in January. By making use of this information and the fact that the rates of return lag real activity by one month, Chang en Pinegar (1986) indicated that rates of return unidirectionally predict future growth rates in industrial production for large companies. They also found that the seasonal growth rates in industrial production partially reflect the January seasonals in the rates of return for small companies. This is inconsistent with the efficient market hypothesis. Altough numerous studies in South Africa have been conducted on the efficiency of the Johannesburg Stock Exchange, no one has departed from the viewpoint of seasonality. The aim of this study is to investigate the efficiency of the Johannesburg stock Exchange with respect to seasonality in industrial production. It will be shown that there is no relationship between rates of return and real activity in the majority of sectors. The clothing sector is inefficient in the sense that real activity unidirectionally predicts rates of return three months in advance. At a six months lag period there are strong relationships, in both ways, between rates of return and real activity for this sector, that also implies inefficiency. Lastly it will be indicated that the November peaks on the Johannesburg stock Exchange do not coincide with the January peaks found overseas and that they do not lag real activity by one month. In the international research the attention was mainly focussed on the size of companies and stock price sensitivity to changes in industrial production while in this paper it focusses on different sectors.