Patterns of nucleotide substitution in angiosperm cpDNA trnL (UAA)-trnF (GAA) regions

Patterns of substitution in chloroplast encoded trnL_F regions were compared between species of Actaea (Ranunculales), Digitalis (Scrophulariales), Drosera (Caryophyllales), Panicoideae (Poales), the small chromosome species clade of Pelargonium (Geraniales), each representing a different order of flowering plants, and Huperzia (Lycopodiales). In total, the study included 265 taxa, each with > 900-bp sequences, totaling 0.24 Mb. Both pairwise and phylogeny-based comparisons were used to assess nucleotide substitution patterns. In all six groups, we found that transition/transversion ratios, as estimated by maximum likelihood on most-parsimonious trees, ranged between 0.8 and 1.0 for ingroups. These values occurred both at low sequence divergences, where substitutional saturation, i.e., multiple substitutions having occurred at the same (homologous) nucleotide position, was not expected, and at higher levels of divergence. This suggests that the angiosperm trnL-F regions evolve in a pattern different from that generally observed for nuclear and animal mtDNA (transitional/transversion ratio > or = 2). Transition/transversion ratios in the intron and the spacer region differed in all alignments compared, yet base compositions between the regions were highly similar in all six groups. A>-C transversions were significantly less frequent than the other four substitution types. This correlates with results from studies on fidelity mechanisms in DNA replication that predict A<->T and G<->C transversions to be least likely to occur. It therefore strengthens confidence in the link between mutation bias at the polymerase level and the actual fixation of substitutions as recorded on evolutionary trees, and concomitantly, in the neutrality of nucleotide substitutions as phylogenetic markers.

Uncertainty and feasibility studies: an Italian case study

Uncertainty affects all aspects of the property market but one area where the impact of uncertainty is particularly significant is within feasibility analyses. Any development is impacted by differences between market conditions at the conception of the project and the market realities at the time of completion. The feasibility study needs to address the possible outcomes based on an understanding of the current market. This requires the appraiser to forecast the most likely outcome relating to the sale price of the completed development, the construction costs and the timing of both. It also requires the appraiser to understand the impact of finance on the project. All these issues are time sensitive and analysis needs to be undertaken to show the impact of time to the viability of the project. The future is uncertain and a full feasibility analysis should be able to model the upside and downside risk pertaining to a range of possible outcomes. Feasibility studies are extensively used in Italy to determine land value but they tend to be single point analysis based upon a single set of “likely” inputs. In this paper we look at the practical impact of uncertainty in variables using a simulation model (Crystal Ball ©) with an actual case study of an urban redevelopment plan for an Italian Municipality. This allows the appraiser to address the issues of uncertainty involved and thus provide the decision maker with a better understanding of the risk of development. This technique is then refined using a “two-dimensional technique” to distinguish between “uncertainty” and “variability” and thus create a more robust model.

The relative importance sector and regional factors in Italy

The benefits of sector and regional diversification have been well documented in the literature but have not previously been investigated in Italy. In addition, previous studies have used geographically defined regions, rather than economically functional areas, when performing the analysis even though most would argue that it is the economic structure of the area that will lead to differences in demand and hence property performance. This study therefore uses economically defined regions of Italy to test the relative benefits of regional diversification versus sector diversification within the Italian real estate portfolio. To examine this issue we use constrained cross-section regressions the on the sector and regional affiliation of 14 cities in Italy to extract the “pure” return effects of the different factors using annual data over the period 1989 to 2003. In contrast, to previous studies we find that regional factors effects in Italy have a much greater influence on property returns than sector-specific effects, which is probably a direct result of using the extremely diverse economic regions of Italy rather than arbitrary geographically locations. Be that as it may, the results strongly suggest that that diversification across the regions of Italy used here is likely to offer larger risk reduction benefits than a sector diversification strategy within a region. In other words, fund managers in Italy must monitor the regional composition of their portfolios more closely than its sector allocation. Additionally, the results supports that contemporary position that ‘regional areas’ based on economic function, provide greater diversification benefits rather than areas defined by geographical location.

Another look at the relative importance of sectors and regions in determining property returns

This paper re-examines the relative importance of sector and regional effects in determining property returns. Using the largest property database currently available in the world, we decompose the returns on individual properties into a national effect, common to all properties, and a number of sector and regional factors. However, unlike previous studies, we categorise the individual property data into an ever-increasing number of property-types and regions, from a simple 3-by-3 classification, up to a 10 by 63 sector/region classification. In this way we can test the impact that a finer classification has on the sector and regional effects. We confirm the earlier findings of previous studies that sector-specific effects have a greater influence on property returns than regional effects. We also find that the impact of the sector effect is robust across different classifications of sectors and regions. Nonetheless, the more refined sector and regional partitions uncover some interesting sector and regional differences, which were obscured in previous studies. All of which has important implications for property portfolio construction and analysis.