A refined sampling strategy for intra-tooth stable isotope analysis of mammalian enamel

Serial sampling and stable isotope analysis performed along the growth axis of vertebrate tooth enamel records differences attributed to seasonal variation in diet, climate or animal movement. Because several months are required to obtain mature enamel in large mammals, modifications in the isotopic composition of environmental parameters are not instantaneously recorded, and stable isotope analysis of tooth enamel returns a time-averaged signal attenuated in its amplitude relative to the input signal. For convenience, stable isotope profiles are usually determined on the side of the tooth where enamel is thickest. Here we investigate the possibility of improving the time resolution by targeting the side of the tooth where enamel is thinnest. Observation of developing third molars (M3) in sheep shows that the tooth growth rate is not constant but decreases exponentially, while the angle between the first layer of enamel deposited and the enamel–dentine junction increases as a tooth approaches its maximal length. We also noted differences in thickness and geometry of enamel growth between the mesial side (i.e., the side facing the M2) and the buccal side (i.e., the side facing the cheek) of the M3. Carbon and oxygen isotope variations were measured along the M3 teeth from eight sheep raised under controlled conditions. Intra-tooth variability was systematically larger along the mesial side and the difference in amplitude between the two sides was proportional to the time of exposure to the input signal. Although attenuated, the mesial side records variations in the environmental signal more faithfully than the buccal side. This approach can be adapted to other mammals whose teeth show lateral variation in enamel thickness and could potentially be used as an internal check for diagenesis.

Sampling uncertainty properties of cloud fraction estimates from random transect observations

[1] Cloud cover is conventionally estimated from satellite images as the observed fraction of cloudy pixels. Active instruments such as radar and Lidar observe in narrow transects that sample only a small percentage of the area over which the cloud fraction is estimated. As a consequence, the fraction estimate has an associated sampling uncertainty, which usually remains unspecified. This paper extends a Bayesian method of cloud fraction estimation, which also provides an analytical estimate of the sampling error. This method is applied to test the sensitivity of this error to sampling characteristics, such as the number of observed transects and the variability of the underlying cloud field. The dependence of the uncertainty on these characteristics is investigated using synthetic data simulated to have properties closely resembling observations of the spaceborne Lidar NASA-LITE mission. Results suggest that the variance of the cloud fraction is greatest for medium cloud cover and least when conditions are mostly cloudy or clear. However, there is a bias in the estimation, which is greatest around 25% and 75% cloud cover. The sampling uncertainty is also affected by the mean lengths of clouds and of clear intervals; shorter lengths decrease uncertainty, primarily because there are more cloud observations in a transect of a given length. Uncertainty also falls with increasing number of transects. Therefore a sampling strategy aimed at minimizing the uncertainty in transect derived cloud fraction will have to take into account both the cloud and clear sky length distributions as well as the cloud fraction of the observed field. These conclusions have implications for the design of future satellite missions. This paper describes the first integrated methodology for the analytical assessment of sampling uncertainty in cloud fraction observations from forthcoming spaceborne radar and Lidar missions such as NASA's Calipso and CloudSat.

Investigating the impact of defects on key stakeholders in the UK new housing sector

The UK house building sector is facing dual pressures to expand supply, along with delivering against tougher Building Regulations’ requirements, predominantly in the areas of sustainability. A review of current literature has highlighted that the pressures the UK house building industry is currently under may be having a negative impact on build quality, causing an increase in defects. A review and synthesis of the current defect literature with respect to new-build housing and the wider construction sector has found that the prevailing emphasis is limited to the classification, causes, pathology and statistical analysis of defects. There is thus a need to better understand the overall impact of individual defects on key stakeholders within the new-build housing defect detection and remediation process. As part of ongoing research to develop and verify a defect impact assessment rating system, this paper seeks to contribute to our understanding of the impact of individual defects from a key stakeholder perspective by undertaking the literature review and synthesis phase. The literature review identifies the three distinct, but interrelated, dominant impact factors: cost, disruption, and health and safety. By pulling the strands of defect literature together the theoretical lens and key stakeholder sampling strategy is formed as the basis for the subsequent impact weighting development phase.

A three-dimensional magnetometer for motion sensing of a balloon-carried atmospheric measurement package

An instrument is described which carries three orthogonal geomagnetic field sensors on a standard meteorological balloon package, to sense rapid motion and position changes during ascent through the atmosphere. Because of the finite data bandwidth available over the UHF radio link, a burst sampling strategy is adopted. Bursts of 9s of measurements at 3.6Hz are interleaved with periods of slow data telemetry lasting 25s. Calculation of the variability in each channel is used to determine position changes, a method robust to periods of poor radio signals. During three balloon ascents, variability was found repeatedly at similar altitudes, simultaneously in each of three orthogonal sensors carried. This variability is attributed to atmospheric motions. It is found that the vertical sensor is least prone to stray motions, and that the use of two horizontal sensors provides no additional information over a single horizontal sensor

The accuracy of digital elevation models derived from digitised contour data

Although accuracy of digital elevation models (DEMs) can be quantified and measured in different ways, each is influenced by three main factors: terrain character, sampling strategy and interpolation method. These parameters, and their interaction, are discussed. The generation of DEMs from digitised contours is emphasised because this is the major source of DEMs, particularly within member countries of OEEPE. Such DEMs often exhibit unwelcome artifacts, depending on the interpolation method employed. The origin and magnitude of these effects and how they can be reduced to improve the accuracy of the DEMs are also discussed.

A case study of sample design for longitudinal research: young lives

This paper presents a case study to illustrate the range of decisions involved in designing a sampling strategy for a complex, longitudinal research study. It is based on experience from the Young Lives project and identifies the approaches used to sample children for longitudinal follow-up in four less developed countries (LDCs). The rationale for decisions made and the resulting benefits, and limitations, of the approaches adopted are discussed. Of particular importance is the choice of sampling approach to yield useful analysis; specific examples are presented of how this informed the design of the Young Lives sampling strategy.

Boundary layer dynamics over London, UK, as observed using Doppler lidar during REPARTEE-II

Urban boundary layers (UBLs) can be highly complex due to the heterogeneous roughness and heating of the surface, particularly at night. Due to a general lack of observations, it is not clear whether canonical models of boundary layer mixing are appropriate in modelling air quality in urban areas. This paper reports Doppler lidar observations of turbulence profiles in the centre of London, UK, as part of the second REPARTEE campaign in autumn 2007. Lidar-measured standard deviation of vertical velocity averaged over 30 min intervals generally compared well with in situ sonic anemometer measurements at 190 m on the BT telecommunications Tower. During calm, nocturnal periods, the lidar underestimated turbulent mixing due mainly to limited sampling rate. Mixing height derived from the turbulence, and aerosol layer height from the backscatter profiles, showed similar diurnal cycles ranging from c. 300 to 800 m, increasing to c. 200 to 850 m under clear skies. The aerosol layer height was sometimes significantly different to the mixing height, particularly at night under clear skies. For convective and neutral cases, the scaled turbulence profiles resembled canonical results; this was less clear for the stable case. Lidar observations clearly showed enhanced mixing beneath stratocumulus clouds reaching down on occasion to approximately half daytime boundary layer depth. On one occasion the nocturnal turbulent structure was consistent with a nocturnal jet, suggesting a stable layer. Given the general agreement between observations and canonical turbulence profiles, mixing timescales were calculated for passive scalars released at street level to reach the BT Tower using existing models of turbulent mixing. It was estimated to take c. 10 min to diffuse up to 190 m, rising to between 20 and 50 min at night, depending on stability. Determination of mixing timescales is important when comparing to physico-chemical processes acting on pollutant species measured simultaneously at both the ground and at the BT Tower during the campaign. From the 3 week autumnal data-set there is evidence for occasional stable layers in central London, effectively decoupling surface emissions from air aloft.

Reforesting degraded agricultural landscapes with Eucalypts: effects on carbon storage and soil fertility after 26years

In the Western Australian wheatbelt, the restoration of native eucalypt forests for managing degraded agricultural landscapes is a critical part of managing dryland salinity and rebuilding biodiversity. Such reforestation will also sequester carbon. Whereas most investigative emphasis has been on carbon stored in biomass, the effects of reforestation on soil organic carbon (SOC) stores and fertility are not known. Two 26 year old reforestation experiments with four Eucalyptus species (E. cladocalyx var nana, E. occidentalis, E. sargentii and E. wandoo) were compared with agricultural sites (Field). SOC stores (to 0.3 m depth) ranged between 33 and 55 Mg ha−1, with no statistically significant differences between tree species and adjacent farmland. Farming comprised crop and pasture rotations. In contrast, the reforested plots contained additional carbon in the tree biomass (23–60 Mg ha−1) and litter (19–34 Mg ha−1), with the greatest litter accumulation associated with E. sargentii. Litter represented between 29 and 56% of the biomass carbon and the protection or utilization of this litter in fire-prone, semi-arid farmland will be an important component of carbon management. Exch-Na and Exch-Mg accumulated under E. sargentii and E. occidentalis at one site. The results raise questions about the conclusions of SOC sequestration studies following reforestation based on limited sampling and reiterate the importance of considering litter in reforestation carbon accounts.

Resolving the unresolved tribe: a molecular phylogenetic framework for the Merremieae (Convolvulaceae)

Tribe Merremieae, as currently circumscribed, comprise c. 120 species classified in seven genera, the largest of which (Merremia) is morphologically heterogeneous. Previous studies, with limited sampling, have suggested that neither Merremieae nor Merremia are monophyletic. In the present study, the monophyly of Merremia and its allied genera was re-assessed, sampling 57 species of Merremieae for the plastid matK, trnL–trnF and rps16 regions and the nuclear internal transcribed spacer (ITS) region. All genera of Merremieae and all major morphotypes in Merremia were represented. Phylogenetic analyses resolve Merremieae in a clade with Ipomoeae, Convolvuleae and Daustinia montana. Merremia is confirmed as polyphyletic and a number of well-supported and morphologically distinct clades in Merremieae are recognized which accommodate most of the species in the tribe. These provide a framework for a generic revision of the assemblage.

Layer-by-layer electrostatic entrapment of protein molecules on superparamagnetic nanoparticle: new strategy to enhance adsorption capacity and maintain biological activity

There is a recent interest to use inorganic-based magnetic nanoparticles as a vehicle to carry biomolecules for various biophysical applications, but direct attachment of the molecules is known to alter their conformation leading to attenuation in activity. In addition, surface immobilization has been limited to monolayer coverage. It is shown that alternate depositions of negatively charged protein molecules, typically bovine serum albumin (BSA) with a positively charged aminocarbohydrate template such as glycol chitosan (GC) on magnetic iron oxide nanoparticle surface as a colloid, are carried out under pH 7.4. Circular dichroism (CD) clearly reveals that the secondary structure of the entrapped BSA sequential depositions in this manner remains totally unaltered which is in sharp contrast to previous attempts. Probing the binding properties of the entrapped BSA using small molecules (Site I and Site II drug compounds) confirms for the first time the full retention of its biological activity as compared with native BSA, which also implies the ready accessibility of the entrapped protein molecules through the porous overlayers. This work clearly suggests a new method to immobilize and store protein molecules beyond monolayer adsorption on a magnetic nanoparticle surface without much structural alteration. This may find applications in magnetic recoverable enzymes or protein delivery.

Biosensor-based diagnostics of contaminated groundwater: assessment and remediation strategy

Shallow groundwater beneath a former airfield site in southern England has been heavily contaminated with a wide range of chlorinated solvents. The feasibility of using bacterial biosensors to complement chemical analysis and enable cost-effective, and focussed sampling has been assessed as part of a site evaluation programme. Five different biosensors, three metabolic (Vibrio fischeri, Pseudomonas fluorescens 10568 and Escherichia coli HB101) and two catabolic (Pseudomonas putida TVA8 and E. coli DH5alpha), were employed to identify areas where the availability and toxicity of pollutants is of most immediate environmental concern. The biosensors used showed different sensitivities to each other and to the groundwater samples tested. There was generally a good agreement with chemical analyses. The potential efficacy of remediation strategies was explored by coupling sample manipulation to biosensor tests. Manipulation involved sparging and charcoal treatment procedures to simulate remediative engineering solutions. Sparging was sufficient at most locations. (C) 2004 Elsevier Ltd. All rights reserved.

The importance of precision in sampling sludges, biowastes and treated soils in a regulatory framework

As part of the European Commission (EC)'s revision of the Sewage Sludge Directive and the development of a Biowaste Directive, there was recognition of the difficulty of comparing data from Member States (MSs) because of differences in sampling and analytical procedures. The 'HORIZONTAL' initiative, funded by the EC and MSs, seeks to address these differences in approach and to produce standardised procedures in the form of CEN standards. This article is a preliminary investigation into aspects of the sampling of biosolids, composts and soils to which there is a history of biosolid application. The article provides information on the measurement uncertainty associated with sampling from heaps, large bags and pipes and soils in the landscape under a limited set of conditions, using sampling approaches in space and time and sample numbers based on procedures widely used in the relevant industries and when sampling similar materials. These preliminary results suggest that considerably more information is required before the appropriate sample design, optimum number of samples, number of samples comprising a composite, and temporal and spatial frequency of sampling might be recommended to achieve consistent results of a high level of precision and confidence. (C) 2004 Elsevier Ltd. All rights reserved.

Sensitivity analysis of a catchment-scale nitrogen model

There are now considerable expectations that semi-distributed models are useful tools for supporting catchment water quality management. However, insufficient attention has been given to evaluating the uncertainties inherent to this type of model, especially those associated with the spatial disaggregation of the catchment. The Integrated Nitrogen in Catchments model (INCA) is subjected to an extensive regionalised sensitivity analysis in application to the River Kennet, part of the groundwater-dominated upper Thames catchment, UK The main results are: (1) model output was generally insensitive to land-phase parameters, very sensitive to groundwater parameters, including initial conditions, and significantly sensitive to in-river parameters; (2) INCA was able to produce good fits simultaneously to the available flow, nitrate and ammonium in-river data sets; (3) representing parameters as heterogeneous over the catchment (206 calibrated parameters) rather than homogeneous (24 calibrated parameters) produced a significant improvement in fit to nitrate but no significant improvement to flow and caused a deterioration in ammonium performance; (4) the analysis indicated that calibrating the flow-related parameters first, then calibrating the remaining parameters (as opposed to calibrating all parameters together) was not a sensible strategy in this case; (5) even the parameters to which the model output was most sensitive suffered from high uncertainty due to spatial inconsistencies in the estimated optimum values, parameter equifinality and the sampling error associated with the calibration method; (6) soil and groundwater nutrient and flow data are needed to reduce. uncertainty in initial conditions, residence times and nitrogen transformation parameters, and long-term historic data are needed so that key responses to changes in land-use management can be assimilated. The results indicate the general, difficulty of reconciling the questions which catchment nutrient models are expected to answer with typically limited data sets and limited knowledge about suitable model structures. The results demonstrate the importance of analysing semi-distributed model uncertainties prior to model application, and illustrate the value and limitations of using Monte Carlo-based methods for doing so. (c) 2005 Elsevier B.V. All rights reserved.

A jackknife variance estimator for unequal probability sampling

The jackknife method is often used for variance estimation in sample surveys but has only been developed for a limited class of sampling designs.We propose a jackknife variance estimator which is defined for any without-replacement unequal probability sampling design. We demonstrate design consistency of this estimator for a broad class of point estimators. A Monte Carlo study shows how the proposed estimator may improve on existing estimators.