The uncertainty of valuation

Valuation is often said to be “an art not a science” but this relates to the techniques employed to calculate value not to the underlying concept itself. Valuation is the process of estimating price in the market place. Yet, such an estimation will be affected by uncertainties. Uncertainty in the comparable information available; uncertainty in the current and future market conditions and uncertainty in the specific inputs for the subject property. These input uncertainties will translate into an uncertainty with the output figure, the valuation. The degree of the uncertainties will vary according to the level of market activity; the more active a market, the more credence will be given to the input information. In the UK at the moment the Royal Institution of Chartered Surveyors (RICS) is considering ways in which the uncertainty of the output figure, the valuation, can be conveyed to the use of the valuation, but as yet no definitive view has been taken apart from a single Guidance Note (GN5, RICS 2003) stressing the importance of recognising uncertainty in valuation but not proffering any particular solution. One of the major problems is that Valuation models (in the UK) are based upon comparable information and rely upon single inputs. They are not probability based, yet uncertainty is probability driven. In this paper, we discuss the issues underlying uncertainty in valuations and suggest a probability-based model (using Crystal Ball) to address the shortcomings of the current model.

Modelling phosphorus dynamics in multi-branch river systems: A study of the Black River, Lake Simcoe, Ontario, Canada

High rates of nutrient loading from agricultural and urban development have resulted in surface water eutrophication and groundwater contamination in regions of Ontario. In Lake Simcoe (Ontario, Canada), anthropogenic nutrient contributions have contributed to increased algal growth, low hypolimnetic oxygen concentrations, and impaired fish reproduction. An ambitious programme has been initiated to reduce phosphorus loads to the lake, aiming to achieve at least a 40% reduction in phosphorus loads by 2045. Achievement of this target necessitates effective remediation strategies, which will rely upon an improved understanding of controls on nutrient export from tributaries of Lake Simcoe as well as improved understanding of the importance of phosphorus cycling within the lake. In this paper, we describe a new model structure for the integrated dynamic and process-based model INCA-P, which allows fully-distributed applications, suited to branched river networks. We demonstrate application of this model to the Black River, a tributary of Lake Simcoe, and use INCA-P to simulate the fluxes of P entering the lake system, apportion phosphorus among different sources in the catchment, and explore future scenarios of land-use change and nutrient management to identify high priority sites for implementation of watershed best management practises.

The uncertainty of valuation

Valuation is often said to be “an art not a science” but this relates to the techniques employed to calculate value not to the underlying concept itself. Valuation is the process of estimating price in the market place. Yet, such an estimation will be affected by uncertainties. Uncertainty in the comparable information available; uncertainty in the current and future market conditions and uncertainty in the specific inputs for the subject property. These input uncertainties will translate into an uncertainty with the output figure, the valuation. The degree of the uncertainties will vary according to the level of market activity; the more active a market, the more credence will be given to the input information. In the UK at the moment the Royal Institution of Chartered Surveyors (RICS) is considering ways in which the uncertainty of the output figure, the valuation, can be conveyed to the use of the valuation, but as yet no definitive view has been taken. One of the major problems is that Valuation models (in the UK) are based upon comparable information and rely upon single inputs. They are not probability based, yet uncertainty is probability driven. In this paper, we discuss the issues underlying uncertainty in valuations and suggest a probability-based model (using Crystal Ball) to address the shortcomings of the current model.

Hydrochemical processes in lowland rivers: insights from in situ, high-resolution monitoring

This paper introduces new insights into the hydrochemical functioning of lowland river systems using field-based spectrophotometric and electrode technologies. The streamwater concentrations of nitrogen species and phosphorus fractions were measured at hourly intervals on a continuous basis at two contrasting sites on tributaries of the River Thames – one draining a rural catchment, the River Enborne, and one draining a more urban system, The Cut. The measurements complement those from an existing network of multi-parameter water quality sondes maintained across the Thames catchment and weekly monitoring based on grab samples. The results of the sub-daily monitoring show that streamwater phosphorus concentrations display highly complex dynamics under storm conditions dependent on the antecedent catchment wetness, and that diurnal phosphorus and nitrogen cycles occur under low flow conditions. The diurnal patterns highlight the dominance of sewage inputs in controlling the streamwater phosphorus and nitrogen concentrations at low flows, even at a distance of 7 km from the nearest sewage treatment works in the rural River Enborne. The time of sample collection is important when judging water quality against ecological thresholds or standards. An exhaustion of the supply of phosphorus from diffuse and multiple septic tank sources during storm events was evident and load estimation was not improved by sub-daily monitoring beyond that achieved by daily sampling because of the eventual reduction in the phosphorus mass entering the stream during events. The results highlight the utility of sub-daily water quality measurements and the discussion considers the practicalities and challenges of in situ, sub-daily monitoring.

Steady state and dynamic modelling of nitrogen in the River Kennet: impacts of land use change since the 1930s

Steady state and dynamic models have been developed and applied to the River Kennet system. Annual nitrogen exports from the land surface to the river have been estimated based on land use from the 1930s and the 1990s. Long term modelled trends indicate that there has been a large increase in nitrogen transport into the river system driven by increased fertiliser application associated with increased cereal production, increased population and increased livestock levels. The dynamic model INCA Integrated Nitrogen in Catchments. has been applied to simulate the day-to-day transport of N from the terrestrial ecosystem to the riverine environment. This process-based model generates spatial and temporal data and reproduces the observed instream concentrations. Applying the model to current land use and 1930s land use indicates that there has been a major shift in the short term dynamics since the 1930s, with increased river and groundwater concentrations caused by both non-point source pollution from agriculture and point source discharges. �

Online bayesian inference in some time-frequency representations of non-stationary processes

The use of Bayesian inference in the inference of time-frequency representations has, thus far, been limited to offline analysis of signals, using a smoothing spline based model of the time-frequency plane. In this paper we introduce a new framework that allows the routine use of Bayesian inference for online estimation of the time-varying spectral density of a locally stationary Gaussian process. The core of our approach is the use of a likelihood inspired by a local Whittle approximation. This choice, along with the use of a recursive algorithm for non-parametric estimation of the local spectral density, permits the use of a particle filter for estimating the time-varying spectral density online. We provide demonstrations of the algorithm through tracking chirps and the analysis of musical data.

Forecasting with vector autoregressive models of data vintages: US output growth and inflation

Vintage-based vector autoregressive models of a single macroeconomic variable are shown to be a useful vehicle for obtaining forecasts of different maturities of future and past observations, including estimates of post-revision values. The forecasting performance of models which include information on annual revisions is superior to that of models which only include the first two data releases. However, the empirical results indicate that a model which reflects the seasonal nature of data releases more closely does not offer much improvement over an unrestricted vintage-based model which includes three rounds of annual revisions.

Adapting wheat in Europe for climate change

Increasing cereal yield is needed to meet the projected increased demand for world food supply of about 70% by 2050. Sirius, a process-based model for wheat, was used to estimate yield potential for wheat ideotypes optimized for future climatic projections (HadCM3 global climate model) for ten wheat growing areas of Europe. It was predicted that the detrimental effect of drought stress on yield would be decreased due to enhanced tailoring of phenology to future weather patterns, and due to genetic improvements in the response of photosynthesis and green leaf duration to water shortage. Yield advances could be made through extending maturation and thereby improve resource capture and partitioning. However the model predicted an increase in frequency of heat stress at meiosis and anthesis. Controlled environment experiments quantify the effects of heat and drought at booting and flowering on grain numbers and potential grain size. A current adaptation of wheat to areas of Europe with hotter and drier summers is a quicker maturation which helps to escape from excessive stress, but results in lower yields. To increase yield potential and to respond to climate change, increased tolerance to heat and drought stress should remain priorities for the genetic improvement of wheat.

Enhanced Australian carbon sink despite increased wildfire during the 21st century

Climate projections show Australia becoming significantly warmer during the 21st century, and precipitation decreasing over much of the continent. Such changes are conventionally considered to increase wildfire risk. Nevertheless, we show that burnt area increases in southern Australia, but decreases in northern Australia. Overall the projected increase in fire is small (0.72–1.31% of land area, depending on the climate scenario used), and does not cause a decrease in carbon storage. In fact, carbon storage increases by 3.7–5.6 Pg C (depending on the climate scenario used). Using a process-based model of vegetation dynamics, vegetation–fire interactions and carbon cycling, we show increased fire promotes a shift to more fire-adapted trees in wooded areas and their encroachment into grasslands, with an overall increase in forested area of 3.9–11.9%. Both changes increase carbon uptake and storage. The increase in woody vegetation increases the amount of coarse litter, which decays more slowly than fine litter hence leading to a relative reduction in overall heterotrophic respiration, further reducing carbon losses. Direct CO2 effects increase woody cover, water-use efficiency and productivity, such that carbon storage is increased by 8.5–14.8 Pg C compared to simulations in which CO2 is held constant at modern values. CO2 effects tend to increase burnt area, fire fluxes and therefore carbon losses in arid areas, but increase vegetation density and reduce burnt area in wooded areas.

Long term individual load forecast under different electrical vehicles uptake scenarios

More and more households are purchasing electric vehicles (EVs), and this will continue as we move towards a low carbon future. There are various projections as to the rate of EV uptake, but all predict an increase over the next ten years. Charging these EVs will produce one of the biggest loads on the low voltage network. To manage the network, we must not only take into account the number of EVs taken up, but where on the network they are charging, and at what time. To simulate the impact on the network from high, medium and low EV uptake (as outlined by the UK government), we present an agent-based model. We initialise the model to assign an EV to a household based on either random distribution or social influences - that is, a neighbour of an EV owner is more likely to also purchase an EV. Additionally, we examine the effect of peak behaviour on the network when charging is at day-time, night-time, or a mix of both. The model is implemented on a neighbourhood in south-east England using smart meter data (half hourly electricity readings) and real life charging patterns from an EV trial. Our results indicate that social influence can increase the peak demand on a local level (street or feeder), meaning that medium EV uptake can create higher peak demand than currently expected.

The response of northern hemisphere extratropical climate and vegetation to orbitally-induced changes in insolation during the last interglaciation

The last interglaciation (substage 5e) provides an opportunity to examine the effects of extreme orbital changes on regional climates. We have made two atmospheric general circulation model experiments: P+T+ approximated the northern hemisphere seasonality maximum near the beginning of 5e; P-T- approximated the minimum near the end of 5e. Simulated regional climate changes have been translated into biome changes using a physiologically based model of global vegetation types. Major climatic and vegetational changes were simulated for the northern hemisphere extratropics, due to radiational effects that were both amplified and modified by atmospheric circulation changes and sea-ice feedback. P+T+ showed mid-continental summers up to 8°C warmer than present. Mid-latitude winters were 2-4°C cooler than present but in the Arctic, summer warmth reduced sea-ice extent and thickness, producing winters 2-8°C warmer than present. The tundra and taiga biomes were displaced poleward, while warm-summer steppes expanded in the mid latitudes due to drought. P-T- showed summers up to 5°C cooler than present, especially in mid latitudes. Sea ice and snowpack were thicker and lasted longer; polar desert, tundra, and taiga biomes were displaced equatorward, while cool-summer steppes and semideserts expanded due to the cooling. A slight winter warming in mid latitudes, however, caused warm-temperate evergreen forests and scrub to expand poleward. Such qualitative contrasts in the direction of climate and vegetation change during 5e should be identifiable in the paleorecord

Engineering a plant community to deliver multiple ecosystem services

The sustainable delivery of multiple ecosystem services requires the management of functionally diverse biological communities. In an agricultural context, an emphasis on food production has often led to a loss of biodiversity to the detriment of other ecosystem services such as the maintenance of soil health and pest regulation. In scenarios where multiple species can be grown together, it may be possible to better balance environmental and agronomic services through the targeted selection of companion species. We used the case study of legume-based cover crops to engineer a plant community that delivered the optimal balance of six ecosystem services: early productivity, regrowth following mowing, weed suppression, support of invertebrates, soil fertility building (measured as yield of following crop), and conservation of nutrients in the soil. An experimental species pool of 12 cultivated legume species was screened for a range of functional traits and ecosystem services at five sites across a geographical gradient in the United Kingdom. All possible species combinations were then analyzed, using a process-based model of plant competition, to identify the community that delivered the best balance of services at each site. In our system, low to intermediate levels of species richness (one to four species) that exploited functional contrasts in growth habit and phenology were identified as being optimal. The optimal solution was determined largely by the number of species and functional diversity represented by the starting species pool, emphasizing the importance of the initial selection of species for the screening experiments. The approach of using relationships between functional traits and ecosystem services to design multifunctional biological communities has the potential to inform the design of agricultural systems that better balance agronomic and environmental services and meet the current objective of European agricultural policy to maintain viable food production in the context of the sustainable management of natural resources.

Soil phosphorus dynamics and phytoavailability from sewage sludge at different stages in a treatment stream

The effect of different stages of sewage sludge treatment on phosphorus (P) dynamics in amended soils was determined using samples of undigested liquid (UL), anaerobically digested liquid (AD) and dewatered anaerobically digested (DC) sludge. Sludges were taken from three points in the same treatment stream and applied to a sandy loam soil in field-based mesocosms at 4, 8 and 16t ha−1 dry solids. Mesocosms were sown with perennial ryegrass (Lolium perenne cv. Melle), and the sward was harvested after 35 and 70 days to determine yield and foliar P concentration. Soils were also sampled during this period to measure P transformations and the activities of acid phosphomonoesterase and phosphodiesterase. Data show that the AD amended soils had the greatest plant-available and foliar P content up to the second harvest, but the UL amended soils had the greatest enzyme activity. Characterisation of control and 16t ha−1 soils and sludge using solution 31P nuclear magnetic resonance (NMR) spectroscopy after NaOH–EDTA extraction revealed that P was predominantly in the inorganic pool in all three sludge samples, with the highest proportion (of the total extracted P) as inorganic P in the anaerobically digested liquid sludge. After sludge incorporation, P was immobilised to organic species. The majority of organic P was in monoester-P forms, while the remainder of organic P (diester P and phosphonate P) was more susceptible to transformations through time and showed variation with sludge type. These results show that application of sewage sludge at rates as low as 4t ha−1 can have a significant nutritional benefit to ryegrass over an initial 35-day growth and subsequent 35-day re-growth periods. Differences in P transformation, and hence nutritional benefit, between sludge types were evident throughout the experiment. Thus, differences in sludge treatment process alter the edaphic mineralisation characteristics of biosolids derived from the same source material.

Nitrogen dynamics under Lolium perenne after a single application of different sewage sludge types from the same treatment stream

Three sludge types from the same treatment stream (undigested liquid, anaerobically digested liquid and dewatered, anaerobically digested cake) were used in a field based tub study. Amendments (4, 8, and 16 Mg dry solid (ds)ha(-1)) were incorporated into the upper 15 cm of a sandy loam soil prior to sowing with rye-grass (Lolium perenne L.). Nitrogen transformations in the soil were determined for the 80 d period following incorporation. Nitrogen uptake and crop yield were measured in the cut sward 35 and 70 d after sowing. The study showed that application of sewage sludge at rates as low as 4 Mgha(-1) can have a nutritional benefit to rye-grass over the two harvests. Differences in N transformation, and hence crop nutritional benefit, between sludge types were evident throughout the experiment. In particular, the dewatering process changed the mineral N characteristics of the anaerobically digested sludge, which, when not dewatered, outperformed the other sludges in terms of yield and mineralisation rate at both harvests. The dewatered sludge produced the lowest yield of rye-grass. The undigested liquid sludge had the lowest foliar N and soil NO(3)-N concentrations, possibly immobilised as the large oxidisable C component of this sludge was metabolised by the microbial biomass. Correlation data support the concept of preferential uptake of NH(4)-N over NO(3)-N in Lolium perenne. Results are discussed in the context of managing sludge type and application for a plant nutrient source and NO(3)-N release.

In the mood: the dynamics of collective sentiments on Twitter

We study the relationship between the sentiment levels of Twitter users and the evolving network structure that the users created by @-mentioning each other. We use a large dataset of tweets to which we apply three sentiment scoring algorithms, including the open source SentiStrength program. Specifically we make three contributions. Firstly we find that people who have potentially the largest communication reach (according to a dynamic centrality measure) use sentiment differently than the average user: for example they use positive sentiment more often and negative sentiment less often. Secondly we find that when we follow structurally stable Twitter communities over a period of months, their sentiment levels are also stable, and sudden changes in community sentiment from one day to the next can in most cases be traced to external events affecting the community. Thirdly, based on our findings, we create and calibrate a simple agent-based model that is capable of reproducing measures of emotive response comparable to those obtained from our empirical dataset.