Social connection and practice-dependence: some recent developments in the global justice literature

This review essay discusses two recent attempts to reform the framework in which issues of international and global justice are discussed: Iris Marion Young’s ‘social connection’ model and the practice-dependent approach, here exemplified by Ayelet Banai, Miriam Ronzoni and Christian Schemmel’s edited collection. I argue that while Young’s model may fit some issues of international or global justice, it misconceives the problems that many of them pose. Indeed, its difficulties point precisely in the direction of practice dependence as it is presented by Banai et al. I go on to discuss what seem to be the strengths of that method, and particularly Banai et al.’s defence of it against the common claim that it is biased towards the status quo. I also discuss Andrea Sangiovanni and Kate MacDonald’s contributions to the collection.

Functional identity and diversity of animals predict ecosystem functioning better than species-based indices

Drastic biodiversity declines have raised concerns about the deterioration of ecosystem functions and have motivated much recent research on the relationship between species diversity and ecosystem functioning. A functional trait framework has been proposed to improve the mechanistic understanding of this relationship, but this has rarely been tested for organisms other than plants. We analysed eight datasets, including five animal groups, to examine how well a trait-based approach, compared with a more traditional taxonomic approach, predicts seven ecosystem functions below- and above-ground. Trait-based indices consistently provided greater explanatory power than species richness or abundance. The frequency distributions of single or multiple traits in the community were the best predictors of ecosystem functioning. This implies that the ecosystem functions we investigated were underpinned by the combination of trait identities (i.e. single-trait indices) and trait complementarity (i.e. multi-trait indices) in the communities. Our study provides new insights into the general mechanisms that link biodiversity to ecosystem functioning in natural animal communities and suggests that the observed responses were due to the identity and dominance patterns of the trait composition rather than the number or abundance of species per se.

A fast radiative transfer model for the assimilation of water vapor radiances from the Kalpana very high resolution radiometer

A fast radiative transfer model (RTM) to compute emitted infrared radiances for a very high resolution radiometer (VHRR), onboard the operational Indian geostationary satellite Kalpana has been developed and verified. This work is a step towards the assimilation of Kalpana water vapor (WV) radiances into numerical weather prediction models. The fast RTM uses a regression‐based approach to parameterize channel‐specific convolved level to space transmittances. A comparison between the fast RTM and the line‐by‐line RTM demonstrated that the fast RTM can simulate line‐by‐line radiances for the Kalpana WV channel to an accuracy better than the instrument noise, while offering more rapid radiance calculations. A comparison of clear sky radiances of the Kalpana WV channel with the ECMWF model first guess radiances is also presented, aiming to demonstrate the fast RTM performance with the real observations. In order to assimilate the radiances from Kalpana, a simple scheme for bias correction has been suggested.

A new set of orthogonal patterns in weather and climate: Optimally interpolated patterns.

A new spectral-based approach is presented to find orthogonal patterns from gridded weather/climate data. The method is based on optimizing the interpolation error variance. The optimally interpolated patterns (OIP) are then given by the eigenvectors of the interpolation error covariance matrix, obtained using the cross-spectral matrix. The formulation of the approach is presented, and the application to low-dimension stochastic toy models and to various reanalyses datasets is performed. In particular, it is found that the lowest-frequency patterns correspond to largest eigenvalues, that is, variances, of the interpolation error matrix. The approach has been applied to the Northern Hemispheric (NH) and tropical sea level pressure (SLP) and to the Indian Ocean sea surface temperature (SST). Two main OIP patterns are found for the NH SLP representing respectively the North Atlantic Oscillation and the North Pacific pattern. The leading tropical SLP OIP represents the Southern Oscillation. For the Indian Ocean SST, the leading OIP pattern shows a tripole-like structure having one sign over the eastern and north- and southwestern parts and an opposite sign in the remaining parts of the basin. The pattern is also found to have a high lagged correlation with the Niño-3 index with 6-months lag.

Preparation of consistent soil data sets for modelling purposes: Secondary SOTER data for four case study areas

The common GIS-based approach to regional analyses of soil organic carbon (SOC) stocks and changes is to define geographic layers for which unique sets of driving variables are derived, which include land use, climate, and soils. These GIS layers, with their associated attribute data, can then be fed into a range of empirical and dynamic models. Common methodologies for collating and formatting regional data sets on land use, climate, and soils were adopted for the project Assessment of Soil Organic Carbon Stocks and Changes at National Scale (GEFSOC). This permitted the development of a uniform protocol for handling the various input for the dynamic GEFSOC Modelling System. Consistent soil data sets for Amazon-Brazil, the Indo-Gangetic Plains (IGP) of India, Jordan and Kenya, the case study areas considered in the GEFSOC project, were prepared using methodologies developed for the World Soils and Terrain Database (SOTER). The approach involved three main stages: (1) compiling new soil geographic and attribute data in SOTER format; (2) using expert estimates and common sense to fill selected gaps in the measured or primary data; (3) using a scheme of taxonomy-based pedotransfer rules and expert-rules to derive soil parameter estimates for similar soil units with missing soil analytical data. The most appropriate approach varied from country to country, depending largely on the overall accessibility and quality of the primary soil data available in the case study areas. The secondary SOTER data sets discussed here are appropriate for a wide range of environmental applications at national scale. These include agro-ecological zoning, land evaluation, modelling of soil C stocks and changes, and studies of soil vulnerability to pollution. Estimates of national-scale stocks of SOC, calculated using SOTER methods, are presented as a first example of database application. Independent estimates of SOC stocks are needed to evaluate the outcome of the GEFSOC Modelling System for current conditions of land use and climate. (C) 2007 Elsevier B.V. All rights reserved.

Predicted soil organic carbon stocks and changes in Kenya between 1990 and 2030

Under the United Nations Framework Convention on Climate Change (UNFCCC), Non-Annex 1 countries such as Kenya are obliged to report green house gas (GHG) emissions from all sources where possible, including those from soils as a result of changes in land use or land management. At present, the convention encourages countries to estimate emissions using the most advanced methods possible, given the country circumstances and resources. Estimates of soil organic carbon (SOC) stocks and changes were made for Kenya using the Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System. The tool conducts analysis using three methods: (1) the Century general ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The required datasets included: land use history, monthly mean precipitation, monthly mean minimum and maximum temperatures for all the agro-climatic zones of Kenya and historical vegetation cover. Soil C stocks of 1.4-2.0 Pg (0-20 cm), compared well with a Soil and Terrain (SOTER) based approach that estimated similar to .8-2.0 Pg (0-30 cm). In 1990 48% of the country had SOC stocks of < 18 t C ha(-1) and 20% of the country had SOC stocks of 18-30 t C ha(-1), whereas in 2000 56% of the country had SOC stocks of < 18 t C ha(-1) and 31% of the country had SOC stocks of 18-30 t C ha(-1). Conversion of natural vegetation to annual crops led to the greatest soil C losses. Simulations suggest that soil C losses remain substantial throughout the modelling period of 1990-2030. All three methods involved in the GEFSOC System estimated that there would be a net loss of soil C between 2000 and 2030 in Kenya. The decline was more marked with RothC than with Century or the IPCC method. In non-hydric soils the SOC change rates were more pronounced in high sandy soils compared to high clay soils in most land use systems. (C) 2007 Elsevier B.V. All rights reserved.

Integrating methods for developing sustainability indicators that can facilitate learning and action

Bossel's (2001) systems-based approach for deriving comprehensive indicator sets provides one of the most holistic frameworks for developing sustainability indicators. It ensures that indicators cover all important aspects of system viability, performance, and sustainability, and recognizes that a system cannot be assessed in isolation from the systems upon which it depends and which in turn depend upon it. In this reply, we show how Bossel's approach is part of a wider convergence toward integrating participatory and reductionist approaches to measure progress toward sustainable development. However, we also show that further integration of these approaches may be able to improve the accuracy and reliability of indicators to better stimulate community learning and action. Only through active community involvement can indicators facilitate progress toward sustainable development goals. To engage communities effectively in the application of indicators, these communities must be actively involved in developing, and even in proposing, indicators. The accuracy, reliability, and sensitivity of the indicators derived from local communities can be ensured through an iterative process of empirical and community evaluation. Communities are unlikely to invest in measuring sustainability indicators unless monitoring provides immediate and clear benefits. However, in the context of goals, targets, and/or baselines, sustainability indicators can more effectively contribute to a process of development that matches local priorities and engages the interests of local people.

Individual differences in the effects of perceived controllability on pain perception: critical role of the prefrontal cortex

The degree to which perceived controllability alters the way a stressor is experienced varies greatly among individuals. We used functional magnetic resonance imaging to examine the neural activation associated with individual differences in the impact of perceived controllability on self-reported pain perception. Subjects with greater activation in response to uncontrollable (UC) rather than controllable (C) pain in the pregenual anterior cingulate cortex (pACC), periaqueductal gray (PAG), and posterior insula/SII reported higher levels of pain during the UC versus C conditions. Conversely, subjects with greater activation in the ventral lateral prefrontal cortex (VLPFC) in anticipation of pain in the UC versus C conditions reported less pain in response to UC versus C pain. Activation in the VLPFC was significantly correlated with the acceptance and denial subscales of the COPE inventory [Carver, C. S., Scheier, M. F., & Weintraub, J. K. Assessing coping strategies: A theoretically based approach. Journal of Personality and Social Psychology, 56, 267–283, 1989], supporting the interpretation that this anticipatory activation was associated with an attempt to cope with the emotional impact of uncontrollable pain. A regression model containing the two prefrontal clusters (VLPFC and pACC) predicted 64% of the variance in pain rating difference, with activation in the two additional regions (PAG and insula/SII) predicting almost no additional variance. In addition to supporting the conclusion that the impact of perceived controllability on pain perception varies highly between individuals, these findings suggest that these effects are primarily top-down, driven by processes in regions of the prefrontal cortex previously associated with cognitive modulation of pain and emotion regulation.

Extraction of tidal channel networks from aerial photographs alone and combined with laser altimetry

Tidal channel networks play an important role in the intertidal zone, exerting substantial control over the hydrodynamics and sediment transport of the region and hence over the evolution of the salt marshes and tidal flats. The study of the morphodynamics of tidal channels is currently an active area of research, and a number of theories have been proposed which require for their validation measurement of channels over extensive areas. Remotely sensed data provide a suitable means for such channel mapping. The paper describes a technique that may be adapted to extract tidal channels from either aerial photographs or LiDAR data separately, or from both types of data used together in a fusion approach. Application of the technique to channel extraction from LiDAR data has been described previously. However, aerial photographs of intertidal zones are much more commonly available than LiDAR data, and most LiDAR flights now involve acquisition of multispectral images to complement the LiDAR data. In view of this, the paper investigates the use of multispectral data for semiautomatic identification of tidal channels, firstly from only aerial photographs or linescanner data, and secondly from fused linescanner and LiDAR data sets. A multi-level, knowledge-based approach is employed. The algorithm based on aerial photography can achieve a useful channel extraction, though may fail to detect some of the smaller channels, partly because the spectral response of parts of the non-channel areas may be similar to that of the channels. The algorithm for channel extraction from fused LiDAR and spectral data gives an increased accuracy, though only slightly higher than that obtained using LiDAR data alone. The results illustrate the difficulty of developing a fully automated method, and justify the semi-automatic approach adopted.

Uses of airborne scanning laser altimetry for river flood modelling and coastal geomorphology

Two ongoing projects at ESSC that involve the development of new techniques for extracting information from airborne LiDAR data and combining this information with environmental models will be discussed. The first project in conjunction with Bristol University is aiming to improve 2-D river flood flow models by using remote sensing to provide distributed data for model calibration and validation. Airborne LiDAR can provide such models with a dense and accurate floodplain topography together with vegetation heights for parameterisation of model friction. The vegetation height data can be used to specify a friction factor at each node of a model’s finite element mesh. A LiDAR range image segmenter has been developed which converts a LiDAR image into separate raster maps of surface topography and vegetation height for use in the model. Satellite and airborne SAR data have been used to measure flood extent remotely in order to validate the modelled flood extent. Methods have also been developed for improving the models by decomposing the model’s finite element mesh to reflect floodplain features such as hedges and trees having different frictional properties to their surroundings. Originally developed for rural floodplains, the segmenter is currently being extended to provide DEMs and friction parameter maps for urban floods, by fusing the LiDAR data with digital map data. The second project is concerned with the extraction of tidal channel networks from LiDAR. These networks are important features of the inter-tidal zone, and play a key role in tidal propagation and in the evolution of salt-marshes and tidal flats. The study of their morphology is currently an active area of research, and a number of theories related to networks have been developed which require validation using dense and extensive observations of network forms and cross-sections. The conventional method of measuring networks is cumbersome and subjective, involving manual digitisation of aerial photographs in conjunction with field measurement of channel depths and widths for selected parts of the network. A semi-automatic technique has been developed to extract networks from LiDAR data of the inter-tidal zone. A multi-level knowledge-based approach has been implemented, whereby low level algorithms first extract channel fragments based mainly on image properties then a high level processing stage improves the network using domain knowledge. The approach adopted at low level uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels. The higher level processing includes a channel repair mechanism.

A cross-taxonomic index for quantifying the health of farmland biodiversity

P>1. The development of sustainable, multi-functional agricultural systems involves reconciling the needs of agricultural production with the objectives for environmental protection, including biodiversity conservation. However, the definition of sustainability remains ambiguous and it has proven difficult to identify suitable indicators for monitoring progress towards, and the successful achievement of, sustainability. 2. In this study, we show that a trait-based approach can be used to assess the detrimental impacts of agricultural change to a broad range of taxonomic groupings and derive a standardised index of farmland biodiversity health, built around an objective of achieving stable or increasing populations in all species associated with agricultural landscapes. 3. To demonstrate its application, we assess the health of UK farmland biodiversity relative to this goal. Our results suggest that the populations of two-thirds of 333 plant and animal species assessed are unsustainable under current UK agricultural practices. 4. We then explore the potential benefits of an agri-environment scheme, Entry Level Stewardship (ELS), to farmland biodiversity in the UK under differing levels of risk mitigation delivery. We show that ELS has the potential to make a significant contribution to progress towards sustainability targets but that this potential is severely restricted by current patterns of scheme deployment. 5.Synthesis and applications: We have developed a cross-taxonomic sustainability index which can be used to assess both the current health of farmland biodiversity and the impacts of future agricultural changes relative to quantitative biodiversity targets. Although biodiversity conservation is just one of a number of factors that must be considered when defining sustainability, we believe our cross-taxonomic index has the potential to be a valuable tool for guiding the development of sustainable agricultural systems.

Novel high-resolution characterization of ancient DNA reveals C > U-type base modification events as the sole cause of post mortem miscoding lesions

Ancient DNA (aDNA) research has long depended on the power of PCR to amplify trace amounts of surviving genetic material from preserved specimens. While PCR permits specific loci to be targeted and amplified, in many ways it can be intrinsically unsuited to damaged and degraded aDNA templates. PCR amplification of aDNA can produce highly-skewed distributions with significant contributions from miscoding lesion damage and non-authentic sequence artefacts. As traditional PCR-based approaches have been unable to fully resolve the molecular nature of aDNA damage over many years, we have developed a novel single primer extension (SPEX)-based approach to generate more accurate sequence information. SPEX targets selected template strands at defined loci and can generate a quantifiable redundancy of coverage; providing new insights into the molecular nature of aDNA damage and fragmentation. SPEX sequence data reveals inherent limitations in both traditional and metagenomic PCR-based approaches to aDNA, which can make current damage analyses and correct genotyping of ancient specimens problematic. In contrast to previous aDNA studies, SPEX provides strong quantitative evidence that C U-type base modifications are the sole cause of authentic endogenous damage-derived miscoding lesions. This new approach could allow ancient specimens to be genotyped with unprecedented accuracy.

Agonist-dependent internalization of D2 receptors: imaging quantification by confocal microscopy

In positron emission tomography and single photon emission computed tomography studies using D2 dopamine (DA) receptor radiotracers, a decrease in radiotracer binding potential (BP) is usually interpreted in terms of increased competition with synaptic DA. However, some data suggest that this signal may also reflect agonist (DA)-induced increases in D2 receptor (D2R) internalization, a process which would presumably also decrease the population of receptors available for binding to hydrophilic radioligands. To advance interpretation of alterations in D2 radiotracer BP, direct methods of assessment of D2R internalization are required. Here, we describe a confocal microscopy-based approach for the quantification of agonist-dependent receptor internalization. The method relies upon double-labeling of the receptors with antibodies directed against intracellular as well as extracellular epitopes. Following agonist stimulation, DA D2R internalization was quantified by differentiating, in optical cell sections, the signal due to the staining of the extracellular from intracellular epitopes of D2Rs. Receptor internalization was increased in the presence of the D2 agonists DA and bromocriptine, but not the D1 agonist SKF38393. Pretreatment with either the D2 antagonist sulpiride, or inhibitors of internalization (phenylarsine oxide and high molarity sucrose), blocked D2-agonist induced receptor internalization, thus validating this method in vitro. This approach therefore provides a direct and streamlined methodology for investigating the pharmacological and mechanistic aspects of D2R internalization, and should inform the interpretation of results from in vivo receptor imaging studies.

Analysing the ability to retain sidechain hydrogen-bonds in mutant proteins

Motivation: Hydrogen bonds are one of the most important inter-atomic interactions in biology. Previous experimental, theoretical and bioinformatics analyses have shown that the hydrogen bonding potential of amino acids is generally satisfied and that buried unsatisfied hydrogen-bond-capable residues are destabilizing. When studying mutant proteins, or introducing mutations to residues involved in hydrogen bonding, one needs to know whether a hydrogen bond can be maintained. Our aim, therefore, was to develop a rapid method to evaluate whether a sidechain can form a hydrogen-bond. Results: A novel knowledge-based approach was developed in which the conformations accessible to the residues involved are taken into account. Residues involved in hydrogen bonds in a set of high resolution crystal structures were analyzed and this analysis is then applied to a given protein. The program was applied to assess mutations in the tumour-suppressor protein, p53. This raised the number of distinct mutations identified as disrupting sidechain-sidechain hydrogen bonding from 181 in our previous analysis to 202 in this analysis.

Evolution of micromorphological and chemical characters in the lichen-forming fungal family Pertusariaceae

Micromorphological characters of the fruiting bodies, such as ascus-type and hymenial amyloidity, and secondary chemistry have been widely employed as key characters in Ascomycota classification. However, the evolution of these characters has yet not been studied using molecular phylogenies. We have used a combined Bayesian and maximum likelihood based approach to trace character evolution on a tree inferred from a combined analysis of nuclear and mitochondrial ribosomal DNA sequences. The maximum likelihood aspect overcomes simplifications inherent in maximum parsimony methods, whereas the Markov chain Monte Carlo aspect renders results independent of any particular phylogenetic tree. The results indicate that the evolution of the two chemical characters is quite different, being stable once developed for the medullary lecanoric acid, whereas the cortical chlorinated xanthones appear to have been lost several times. The current ascus-types and the amyloidity of the hymenial gel in Pertusariaceae appear to have been developed within the family. The basal ascus-type of pertusarialean fungi remains unknown. (c) 2006 The Linnean Society of London, Biological Journal of the Linnean Society, 2006, 89, 615-626.