Calcrete profile development in quaternary alluvial sequences, southeast Spain: Implications for using calcretes as a basis for landform chronologies

A detailed study of the morphology and micro-morphology of Quaternary alluvial calcrete profiles from the Sorbas Basin shows that calcretes may be morphologically simple or complex. The 'simple' profiles reflect pedogenesis occurring after alluvial terrace formation and consist of a single pedogenic horizon near the land surface. The 'complex' profiles reflect the occurrence of multiple calcrete events during terrace sediment aggradation and further periods of pedogenesis after terrace formation. These 'complex' calcrete profiles are consequently described as composite profiles. The exact morphology of the composite profiles depends upon: (1) the number of calcrete-forming events occurring during terrace sediment aggradation; (2) the amount of sediment accretion that occurs between each period of calcrete formation; and (3) the degree of pedogenesis after terrace formation. Simple calcrete profiles are most useful in establishing landform chronologies because they represent a single phase of pedogenesis after terrace formation. Composite profiles are more problematic. Pedogenic calcretes that form within them may inherit carbonate from calcrete horizons occurring lower down in the terrace sediments. In addition erosion may lead to the exhumation of older calcretes within the terrace sediment. Calcrete 'inheritance' may make pedogenic horizons appear more mature than they actually are and produce horizons containing carbonate embracing a range of ages. Calcrete exhumation exposes calcrete horizons whose morphology and radiometric ages are wholly unrelated to terrace surface age. Composite profiles are, therefore, only suitable for chronological studies if the pedogenic horizon capping the terrace sequence can be clearly distinguished from earlier calcrete-forming events. Thus, a detailed morphological/micro-morphological study is required before any chronological study is undertaken. This is the only way to establish whether particular calcrete profiles are suitable for dating purposes. Copyright (C) 2003 John Wiley Sons, Ltd.

Mineral and geochemical characterization of a leptic aluandic soil and a thapto aluandic-ferralsol developed on trachytes in Mount Bambouto (Cameroon volcanic line)

Mineral and geochemical investigations were carried out on soil samples and fresh rock (trachytes) from two selected soil profiles (TM profile on leptic aluandic soils and TL profile on thapto aluandic-ferralsols) from Mount Bambouto to better understand geochemical processes and mineral paragenesis involved in the development of soils in this environment. In TM profile, the hydrated halloysites and goethite occur in the weathered saprolite boulders of BC horizon while dehydrated halloysite, gibbsite and goethite dominate the soils matrices of BC and A horizons. In TL profile, the dehydrated halloysites and goethite are the most abundant secondary minerals in the weathered saprolites of C and BC horizons while gibbsite, hematite and kaolinite occur in the soil matrices of BC, B and A horizons. The highest gibbsite content is in the platy nodules of B horizon. In both soil profiles, organo-metal complexes (most likely of AI and Fe) are present in the surface A horizon. Geochemically, between the fresh rock and the weathered saprolites in both soils, SiO2, K2O, CaO, Na2O and MgO contents decrease strongly while Fe2O3 and Al2O3 tend to accumulate. The molar ratio of SiO2/Al2O3 (Ki) and the sum of Ca, Mg, K and Na ions (TRB) also decreases abruptly between fresh rocks and the weathered saprolites, but increases significantly at the soil surface. The TM profile shows intense Al enrichment whereas the TL profile highlights enrichment in both AI and Fe as the weathering progresses upwards. Both soil profiles are enriched in Ni, Cu, Ba and Co and depleted in U, Th, Ta, Hf, Y, Sr, Pb, Zr and Zn relative to fresh rock. They also show a relatively low fractionation of the rare earth elements (REE: La, Nd, Sm, Eu, Tb, Yb and Lu), except for Ce which tends to be enriched in soils compared to CI chondrite. All these results give evidence of intense hydrolysis at soil deep in Mount Bambouto resulting in the formation of halloysite which progressively transforms into gibbsite and/or dehydrated halloysite. At the soil surface, the prominent pedogenetic process refers to andosolization with formation of organo-metal complexes. In TL profile, the presence of kaolinite in soil matrices BC and B horizons is consistent with ferralitization at soil deep. In conclusion, soil forming processes in Mount Bambouto are strongly influenced by local climate: (i) in the upper mountain (>2000 m), the fresh, misty and humid climate favors andosolization; whereas (ii) in the middle lands (1700-2000 m) with a relatively dry climate, both andosolization at the soil surface and ferralitization at soil deep act together. (C) 2009 Elsevier B.V. All rights reserved.

UK commercial property lease structures: Landlord and tenant mismatch

UK commercial property lease structures have come under considerable scrutiny during the past decade since the property crash of the early 1990s. In particular, tenants complained that the system was unfair and that it has blocked business change. Government is committed, through its 2001 election manifesto, to promote flexibility and choice in the commercial property lettings market and a new voluntary Commercial Leases Code of Practice was launched in April 2002. This paper investigates whether occupiers are being offered the leases they require or whether there is a mismatch between occupier requirements and actual leases in the market. It draws together the substantial data now available on the actual terms of leases in the UK and surveys of corporate occupiers' attitude to their occupation requirements. Although the data indicated that UK leases have become shorter and more diverse since 1990, this is still not sufficient to meet the current requirements of many corporate occupiers. It is clear that the inability to manage entry and exit strategies is a major concern to occupiers. Lease length is the primary concern of tenants and a number of respondents comment on the mismatch between lease length in the UK and business planning horizons. The right to break and other problems with alienation clauses also pose serious difficulties for occupiers, thus reinforcing the mismatch. Other issues include repairing and insuring clauses and the type of review clause. There are differences in opinion between types of occupier. In particular, international corporate occupiers are significantly more concerned about the length of lease and the incidence of break clauses than national occupiers and private-sector tenants are significantly more concerned about leasing in general than public-sector occupiers. Proposed solutions by tenants are predictable and include shorter leases, more frequent breaks and relaxation of restrictions concerning alienation and other clauses. A significant number specify that they would pay more for shorter leases and other improved terms. Short leases would make many of the other terms more acceptable and this is why they are the main concern of corporate occupiers. Overall, the evidence suggests that there continues to be a gap between occupiers' lease requirements and those currently offered by the market. There are underlying structural factors that act as an inertial force on landlords and inhibit the changes which occupiers appear to want. Nevertheless, the findings raise future research questions concerning whether UK lease structures are a constraining factor on UK competitiveness.

Vertical distribution, size and composition of the weed seedbank under various tillage and herbicide treatments in a sequence of industrial crops

Investigations were conducted during the 2003, 2004 and 2005 growing seasons in northern Greece to evaluate effects of tillage regime (mouldboard plough, chisel plough and rotary tiller), cropping sequence (continuous cotton, cotton-sugar beet rotation and continuous tobacco) and herbicide treatment on weed seedbank dynamics. Amaranthus spp. and Portulaca oleracea were the most abundant species, ranging from 76% to 89% of total weed seeds found in 0-15 and 15-30 cm soil depths during the 3 years. With the mouldboard plough, 48% and 52% of the weed seedbank was found in the 0-15 and 15-30 cm soil horizons, while approximately 60% was concentrated in the upper 15 cm soil horizon for chisel plough and rotary tillage. Mouldboard ploughing significantly buried more Echinochloa crus-galli seeds in the 15-30 cm soil horizon compared with the other tillage regimes. Total seedbank (0-30 cm) of P. oleracea was significantly reduced in cotton-sugar beet rotation compared with cotton and tobacco monocultures, while the opposite occurred for E. crus-galli. Total seed densities of most annual broad-leaved weed species (Amaranthus spp., P. oleracea, Solanum nigrum) and E. crus-galli were lower in herbicide treated than in untreated plots. The results suggest that in light textured soils, conventional tillage with herbicide use gradually reduces seed density of small seeded weed species in the top 15 cm over several years. In contrast, crop rotation with the early established sugar beet favours spring-germinating grass weed species, but also prevents establishment of summer-germinating weed species by the early developing crop canopy.

A fuzzy multi-criteria decision approach for enhanced auto-tracking of seismic events

The main activity carried out by the geophysicist when interpreting seismic data, in terms of both importance and time spent is tracking (or picking) seismic events. in practice, this activity turns out to be rather challenging, particularly when the targeted event is interrupted by discontinuities such as geological faults or exhibits lateral changes in seismic character. In recent years, several automated schemes, known as auto-trackers, have been developed to assist the interpreter in this tedious and time-consuming task. The automatic tracking tool available in modem interpretation software packages often employs artificial neural networks (ANN's) to identify seismic picks belonging to target events through a pattern recognition process. The ability of ANNs to track horizons across discontinuities largely depends on how reliably data patterns characterise these horizons. While seismic attributes are commonly used to characterise amplitude peaks forming a seismic horizon, some researchers in the field claim that inherent seismic information is lost in the attribute extraction process and advocate instead the use of raw data (amplitude samples). This paper investigates the performance of ANNs using either characterisation methods, and demonstrates how the complementarity of both seismic attributes and raw data can be exploited in conjunction with other geological information in a fuzzy inference system (FIS) to achieve an enhanced auto-tracking performance.

The indirect global warming potential and global temperature change potential due to methane oxidation

Methane is the second most important anthropogenic greenhouse gas in the atmosphere next to carbon dioxide. Its global warming potential (GWP) for a time horizon of 100 years is 25, which makes it an attractive target for climate mitigation policies. Although the methane GWP traditionally includes the methane indirect effects on the concentrations of ozone and stratospheric water vapour, it does not take into account the production of carbon dioxide from methane oxidation. We argue here that this CO2-induced effect should be included for fossil sources of methane, which results in slightly larger GWP values for all time horizons. If the global temperature change potential is used as an alternative climate metric, then the impact of the CO2-induced effect is proportionally much larger. We also discuss what the correction term should be for methane from anthropogenic biogenic sources.

A review of climate risk information for adaptation and development planning

Although the use of climate scenarios for impact assessment has grown steadily since the 1990s, uptake of such information for adaptation is lagging by nearly a decade in terms of scientific output. Nonetheless, integration of climate risk information in development planning is now a priority for donor agencies because of the need to prepare for climate change impacts across different sectors and countries. This urgency stems from concerns that progress made against Millennium Development Goals (MDGs) could be threatened by anthropogenic climate change beyond 2015. Up to this time the human signal, though detectable and growing, will be a relatively small component of climate variability and change. This implies the need for a twin-track approach: on the one hand, vulnerability assessments of social and economic strategies for coping with present climate extremes and variability, and, on the other hand, development of climate forecast tools and scenarios to evaluate sector-specific, incremental changes in risk over the next few decades. This review starts by describing the climate outlook for the next couple of decades and the implications for adaptation assessments. We then review ways in which climate risk information is already being used in adaptation assessments and evaluate the strengths and weaknesses of three groups of techniques. Next we identify knowledge gaps and opportunities for improving the production and uptake of climate risk information for the 2020s. We assert that climate change scenarios can meet some, but not all, of the needs of adaptation planning. Even then, the choice of scenario technique must be matched to the intended application, taking into account local constraints of time, resources, human capacity and supporting infrastructure. We also show that much greater attention should be given to improving and critiquing models used for climate impact assessment, as standard practice. Finally, we highlight the over-arching need for the scientific community to provide more information and guidance on adapting to the risks of climate variability and change over nearer time horizons (i.e. the 2020s). Although the focus of the review is on information provision and uptake in developing regions, it is clear that many developed countries are facing the same challenges. Copyright © 2009 Royal Meteorological Society

Storm surge frequency reduction in Venice under climate change

Increased tidal levels and storm surges related to climate change are projected to result in extremely adverse effects on coastal regions. Predictions of such extreme and small-scale events, however, are exceedingly challenging, even for relatively short time horizons. Here we use data from observations, ERA-40 reanalysis, climate scenario simulations, and a simple feature model to find that the frequency of extreme storm surge events affecting Venice is projected to decrease by about 30% by the end of the twenty-first century. In addition, through a trend assessment based on tidal observations we found a reduction in extreme tidal levels. Extrapolating the current +17 cm/century sea level trend, our results suggest that the frequency of extreme tides in Venice might largely remain unaltered under the projected twenty-first century climate simulations.

The consistency of private and public real estate within mixed-asset portfolios

This study considers the consistency of the role of both the private and public real estate markets within a mixed-asset context. While a vast literature has developed that has examined the potential role of both the private and public real estate markets, most studies have largely relied on both single time horizons and single sample periods. This paper builds upon the analysis of Lee and Stevenson (2005) who examined the consistency of REITs in a US capital market portfolio. The current paper extends that by also analyzing the role of the private market. To address the question, the allocation of both the private and traded markets is evaluated over different holding periods varying from 5- to 20-years. In general the results show that optimum mixed-asset portfolios already containing private real estate have little place for public real estate securities, especially in low risk portfolios and for longer investment horizons. Additionally, mixed-asset portfolios with public real estate either see the allocations to REITs diminished or eliminated if private real estate is also considered. The results demonstrate that there is a still a strong case for private real estate in the mixed-asset portfolio on the basis of an increase in risk-adjusted performance, even if the investor is already holding REITs, but that the reverse is not always the case.

International evidence on the predictability of returns to securitized real estate assets: econometric models versus neural networks

The performance of various statistical models and commonly used financial indicators for forecasting securitised real estate returns are examined for five European countries: the UK, Belgium, the Netherlands, France and Italy. Within a VAR framework, it is demonstrated that the gilt-equity yield ratio is in most cases a better predictor of securitized returns than the term structure or the dividend yield. In particular, investors should consider in their real estate return models the predictability of the gilt-equity yield ratio in Belgium, the Netherlands and France, and the term structure of interest rates in France. Predictions obtained from the VAR and univariate time-series models are compared with the predictions of an artificial neural network model. It is found that, whilst no single model is universally superior across all series, accuracy measures and horizons considered, the neural network model is generally able to offer the most accurate predictions for 1-month horizons. For quarterly and half-yearly forecasts, the random walk with a drift is the most successful for the UK, Belgian and Dutch returns and the neural network for French and Italian returns. Although this study underscores market context and forecast horizon as parameters relevant to the choice of the forecast model, it strongly indicates that analysts should exploit the potential of neural networks and assess more fully their forecast performance against more traditional models.