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The UK Critical Minerals Strategy (BEIS, 2022) includes a commitment to “begin a nationalscale assessment of the critical minerals within the UK. By March 2023, we will collate geoscientific data and identify target areas of potential”. This report provides that national-scale assessment of the geological potential for critical raw materials in the UK. It represents the published output of a study, jointly funded by the British Geological Survey and the Department for Business and Trade, which reviewed available geoscientific data in order to identify areas of potential geological prospectivity for critical raw materials in the UK. Critical raw materials (CRMs) are those mineral commodities that are both economically important and at risk of supply disruption. The commodities addressed in this report are those identified as critical to the UK by the Critical Minerals Intelligence Centre (CMIC) (Lusty et al., 2021). These CRMs are currently obtained from mining across the world, but at the time of writing none are produced in the UK, although tungsten has been mined in recent years. Some CRMs such as lithium, tin and graphite are typically the primary products of mines, whereas others are produced as co- or by-products of major commodities such as gold, copper or zinc. Current understanding of the UK’s mineral resource endowment rests largely on evidence from historic mining and exploration, together with targeted academic research. The UK has an extensive history of mining that dates to prehistoric times. Gold, barite, fluorite, gypsum, potash and polyhalite are among the commodities that are currently mined, and exploration for many raw materials is occurring across the whole of the UK. The work presented in this report follows a methodology known as a mineral systems approach, which relies on the concept that all mineral deposits of a certain type were formed by a combination of particular geological processes (McCuaig et al., 2010). The processes that must operat

This report gives an assessment of the strengths and weaknesses of current approaches to managing the supply of critical raw materials (CRMs). It builds upon an initial phase of work, published in the Overview of activities and policy report. This reviewed current global activities, research and policy leading to the identification of the key issues related to CRM resource management and the sustainability of supply. This review provided the basis for the formulation of a series of recommendation in this study.

© 2019, The Author(s). The chaotic distribution and dispersal of phosphorus (P) used in food systems (defined here as disorderly disruptions to the P cycle) is harming our environment beyond acceptable limits. An analysis of P stores and flows across Europe in 2005 showed that high fertiliser P inputs relative to productive outputs was driving low system P efficiency (38 % overall). Regional P imbalance (P surplus) and system P losses were highly correlated to total system P inputs and animal densities, causing unnecessary P accumulation in soils and rivers. Reducing regional P surpluses to zero increased system P efficiency (+ 16 %) and decreased total P losses by 35 %, but required a reduction in system P inputs of ca. 40 %, largely as fertiliser. We discuss transdisciplinary and transformative solutions that tackle the P chaos by collective stakeholder actions across the entire food value chain. Lowering system P demand and better regional governance of P resources appear necessary for more efficient and sustainable food systems.

© 2019, The Author(s). The chaotic distribution and dispersal of phosphorus (P) used in food systems (defined here as disorderly disruptions to the P cycle) is harming our environment beyond acceptable limits. An analysis of P stores and flows across Europe in 2005 showed that high fertiliser P inputs relative to productive outputs was driving low system P efficiency (38 % overall). Regional P imbalance (P surplus) and system P losses were highly correlated to total system P inputs and animal densities, causing unnecessary P accumulation in soils and rivers. Reducing regional P surpluses to zero increased system P efficiency (+ 16 %) and decreased total P losses by 35 %, but required a reduction in system P inputs of ca. 40 %, largely as fertiliser. We discuss transdisciplinary and transformative solutions that tackle the P chaos by collective stakeholder actions across the entire food value chain. Lowering system P demand and better regional governance of P resources appear necessary for more efficient and sustainable food systems.

© 2019, The Author(s). The chaotic distribution and dispersal of phosphorus (P) used in food systems (defined here as disorderly disruptions to the P cycle) is harming our environment beyond acceptable limits. An analysis of P stores and flows across Europe in 2005 showed that high fertiliser P inputs relative to productive outputs was driving low system P efficiency (38 % overall). Regional P imbalance (P surplus) and system P losses were highly correlated to total system P inputs and animal densities, causing unnecessary P accumulation in soils and rivers. Reducing regional P surpluses to zero increased system P efficiency (+ 16 %) and decreased total P losses by 35 %, but required a reduction in system P inputs of ca. 40 %, largely as fertiliser. We discuss transdisciplinary and transformative solutions that tackle the P chaos by collective stakeholder actions across the entire food value chain. Lowering system P demand and better regional governance of P resources appear necessary for more efficient and sustainable food systems.

A geochemical anomaly is a concentration of an element or other constituent in a medium (soil, sediment or surface water) which is unusual in its local setting. Geochemical anomalies may be interesting as indicators of processes such as point contamination or mineralizations. They may therefore be practically useful, indicating sources of pollution or mineral deposits which may be of economic value. As defined, a geochemical anomaly is not merely a large (or small) concentration of a constituent as compared to the marginal distribution. To detect anomalies we must therefore do more than simply map the spatial distribution of the constituent. One proposed approach makes use of a singularity index based on fractal representation of spatial variation. The singularity index can be computed from local concentration measures in nested windows. In this paper we propose an approach to compute threshold values for the index to identify enrichment and depletion anomalies, separate from background information. The approach is based on a mixture model for the singularity index, and it can be supported by computing a distribution for background values of the index by parametric bootstrapping from a robustly-estimated variogram model for the target constituent. This approach is illustrated here using data on elements in the soil in four settings in Great Britain and Ireland.

A geochemical anomaly is a concentration of an element or other constituent in a medium (soil, sediment or surface water) which is unusual in its local setting. Geochemical anomalies may be interesting as indicators of processes such as point contamination or mineralizations. They may therefore be practically useful, indicating sources of pollution or mineral deposits which may be of economic value. As defined, a geochemical anomaly is not merely a large (or small) concentration of a constituent as compared to the marginal distribution. To detect anomalies we must therefore do more than simply map the spatial distribution of the constituent. One proposed approach makes use of a singularity index based on fractal representation of spatial variation. The singularity index can be computed from local concentration measures in nested windows. In this paper we propose an approach to compute threshold values for the index to identify enrichment and depletion anomalies, separate from background information. The approach is based on a mixture model for the singularity index, and it can be supported by computing a distribution for background values of the index by parametric bootstrapping from a robustly-estimated variogram model for the target constituent. This approach is illustrated here using data on elements in the soil in four settings in Great Britain and Ireland.

Item does not contain fulltext, New human mutations are thought to originate in germ cells, thus making a recurrence of the same mutation in a sibling exceedingly rare. However, increasing sensitivity of genomic technologies has anecdotally revealed mosaicism for mutations in somatic tissues of apparently healthy parents. Such somatically mosaic parents might also have germline mosaicism that can potentially cause unexpected intergenerational recurrences. Here, we show that somatic mosaicism for transmitted mutations among parents of children with simplex genetic disease is more common than currently appreciated. Using the sensitivity of individual-specific breakpoint PCR, we prospectively screened 100 families with children affected by genomic disorders due to rare deletion copy-number variants (CNVs) determined to be de novo by clinical analysis of parental DNA. Surprisingly, we identified four cases of low-level somatic mosaicism for the transmitted CNV in DNA isolated from parental blood. Integrated probabilistic modeling of gametogenesis developed in response to our observations predicts that mutations in parental blood increase recurrence risk substantially more than parental mutations confined to the germline. Moreover, despite the fact that maternally transmitted mutations are the minority of alleles, our model suggests that sexual dimorphisms in gametogenesis result in a greater proportion of somatically mosaic transmitting mothers who are thus at increased risk of recurrence. Therefore, somatic mosaicism together with sexual differences in gametogenesis might explain a considerable fraction of unexpected recurrences of X-linked recessive disease. Overall, our results underscore an important role for somatic mosaicism and mitotic replicative mutational mechanisms in transmission genetics.

Mineral exploration programmes around the world use data from remote sensing, geophysics, and direct sampling. On a regional scale, the combination of airborne geophysics and ground-based geochemical sampling can aid geological mapping and mineral exploration. Since airborne geophysical and traditional soil-sampling data are generated at different spatial resolutions, they are not immediately comparable due to their different sampling density. Several geostatistical techniques, including indicator cokriging and collocated cokriging, can be used to integrate different types of data into a geostatistical model. However, with increasing numbers of variables the inference of the crosscovariance model required for cokriging can be demanding in terms of effort and computational time. In this paper a Gaussian-based Bayesian updating approach is applied to integrate airborne radiometric data and ground-sampled geochemical soil data to maximize information generated from the soil survey, enabling more accurate geological interpretation for the exploration and development of natural resources. The Bayesian updating technique decomposes the collocated estimate into two models: prior and likelihood models. The prior model is built from primary information and the likelihood model is built from secondary information. The prior model is then updated with the likelihood model to build the final model. The approach allows multiple secondary variables to be simultaneously integrated into the mapping of the primary variable. The Bayesian updating approach is demonstrated using a case study from Northern Ireland. The geostatistical technique was used to improve the resolution of soil geochemistry, at a density of one sample per 2 km2, by integrating more closely measured airborne geophysical data from the GSNI Tellus Survey, measured over a footprint of 65 x 200 m. The directly measured geochemistry data were considered as primary data and the airborne radiometric data were used as se

Item does not contain fulltext, New human mutations are thought to originate in germ cells, thus making a recurrence of the same mutation in a sibling exceedingly rare. However, increasing sensitivity of genomic technologies has anecdotally revealed mosaicism for mutations in somatic tissues of apparently healthy parents. Such somatically mosaic parents might also have germline mosaicism that can potentially cause unexpected intergenerational recurrences. Here, we show that somatic mosaicism for transmitted mutations among parents of children with simplex genetic disease is more common than currently appreciated. Using the sensitivity of individual-specific breakpoint PCR, we prospectively screened 100 families with children affected by genomic disorders due to rare deletion copy-number variants (CNVs) determined to be de novo by clinical analysis of parental DNA. Surprisingly, we identified four cases of low-level somatic mosaicism for the transmitted CNV in DNA isolated from parental blood. Integrated probabilistic modeling of gametogenesis developed in response to our observations predicts that mutations in parental blood increase recurrence risk substantially more than parental mutations confined to the germline. Moreover, despite the fact that maternally transmitted mutations are the minority of alleles, our model suggests that sexual dimorphisms in gametogenesis result in a greater proportion of somatically mosaic transmitting mothers who are thus at increased risk of recurrence. Therefore, somatic mosaicism together with sexual differences in gametogenesis might explain a considerable fraction of unexpected recurrences of X-linked recessive disease. Overall, our results underscore an important role for somatic mosaicism and mitotic replicative mutational mechanisms in transmission genetics.

Mineral exploration programmes around the world use data from remote sensing, geophysics, and direct sampling. On a regional scale, the combination of airborne geophysics and ground-based geochemical sampling can aid geological mapping and mineral exploration. Since airborne geophysical and traditional soil-sampling data are generated at different spatial resolutions, they are not immediately comparable due to their different sampling density. Several geostatistical techniques, including indicator cokriging and collocated cokriging, can be used to integrate different types of data into a geostatistical model. However, with increasing numbers of variables the inference of the crosscovariance model required for cokriging can be demanding in terms of effort and computational time. In this paper a Gaussian-based Bayesian updating approach is applied to integrate airborne radiometric data and ground-sampled geochemical soil data to maximize information generated from the soil survey, enabling more accurate geological interpretation for the exploration and development of natural resources. The Bayesian updating technique decomposes the collocated estimate into two models: prior and likelihood models. The prior model is built from primary information and the likelihood model is built from secondary information. The prior model is then updated with the likelihood model to build the final model. The approach allows multiple secondary variables to be simultaneously integrated into the mapping of the primary variable. The Bayesian updating approach is demonstrated using a case study from Northern Ireland. The geostatistical technique was used to improve the resolution of soil geochemistry, at a density of one sample per 2 km2, by integrating more closely measured airborne geophysical data from the GSNI Tellus Survey, measured over a footprint of 65 x 200 m. The directly measured geochemistry data were considered as primary data and the airborne radiometric data were used as se

Weaver syndrome, first described in 1974, is characterized by tall stature, a typical facial appearance, and variable intellectual disability. In 2011, mutations in the histone methyltransferase, EZH2, were shown to cause Weaver syndrome. To date, we have identified 48 individuals with EZH2 mutations. The mutations were primarily missense mutations occurring throughout the gene, with some clustering in the SET domain (12/48). Truncating mutations were uncommon (4/48) and only identified in the final exon, after the SET domain. Through analyses of clinical data and facial photographs of EZH2 mutation-positive individuals, we have shown that the facial features can be subtle and the clinical diagnosis of Weaver syndrome is thus challenging, especially in older individuals. However, tall stature is very common, reported in >90% of affected individuals. Intellectual disability is also common, present in ~80%, but is highly variable and frequently mild. Additional clinical features which may help in stratifying individuals to EZH2 mutation testing include camptodactyly, soft, doughy skin, umbilical hernia, and a low, hoarse cry. Considerable phenotypic overlap between Sotos and Weaver syndromes is also evident. The identification of an EZH2 mutation can therefore provide an objective means of confirming a subtle presentation of Weaver syndrome and/or distinguishing Weaver and Sotos syndromes. As mutation testing becomes increasingly accessible and larger numbers of EZH2 mutation-positive individuals are identified, knowledge of the clinical spectrum and prognostic implications of EZH2 mutations should improve.

Weaver syndrome, first described in 1974, is characterized by tall stature, a typical facial appearance, and variable intellectual disability. In 2011, mutations in the histone methyltransferase, EZH2, were shown to cause Weaver syndrome. To date, we have identified 48 individuals with EZH2 mutations. The mutations were primarily missense mutations occurring throughout the gene, with some clustering in the SET domain (12/48). Truncating mutations were uncommon (4/48) and only identified in the final exon, after the SET domain. Through analyses of clinical data and facial photographs of EZH2 mutation-positive individuals, we have shown that the facial features can be subtle and the clinical diagnosis of Weaver syndrome is thus challenging, especially in older individuals. However, tall stature is very common, reported in >90% of affected individuals. Intellectual disability is also common, present in ~80%, but is highly variable and frequently mild. Additional clinical features which may help in stratifying individuals to EZH2 mutation testing include camptodactyly, soft, doughy skin, umbilical hernia, and a low, hoarse cry. Considerable phenotypic overlap between Sotos and Weaver syndromes is also evident. The identification of an EZH2 mutation can therefore provide an objective means of confirming a subtle presentation of Weaver syndrome and/or distinguishing Weaver and Sotos syndromes. As mutation testing becomes increasingly accessible and larger numbers of EZH2 mutation-positive individuals are identified, knowledge of the clinical spectrum and prognostic implications of EZH2 mutations should improve.

Weaver syndrome, first described in 1974, is characterized by tall stature, a typical facial appearance, and variable intellectual disability. In 2011, mutations in the histone methyltransferase, EZH2, were shown to cause Weaver syndrome. To date, we have identified 48 individuals with EZH2 mutations. The mutations were primarily missense mutations occurring throughout the gene, with some clustering in the SET domain (12/48). Truncating mutations were uncommon (4/48) and only identified in the final exon, after the SET domain. Through analyses of clinical data and facial photographs of EZH2 mutation-positive individuals, we have shown that the facial features can be subtle and the clinical diagnosis of Weaver syndrome is thus challenging, especially in older individuals. However, tall stature is very common, reported in >90% of affected individuals. Intellectual disability is also common, present in ~80%, but is highly variable and frequently mild. Additional clinical features which may help in stratifying individuals to EZH2 mutation testing include camptodactyly, soft, doughy skin, umbilical hernia, and a low, hoarse cry. Considerable phenotypic overlap between Sotos and Weaver syndromes is also evident. The identification of an EZH2 mutation can therefore provide an objective means of confirming a subtle presentation of Weaver syndrome and/or distinguishing Weaver and Sotos syndromes. As mutation testing becomes increasingly accessible and larger numbers of EZH2 mutation-positive individuals are identified, knowledge of the clinical spectrum and prognostic implications of EZH2 mutations should improve.

The biological processes controlling human growth are diverse, complex and poorly understood. Genetic factors are important and human height has been shown to be a highly polygenic trait to which common and rare genetic variation contributes. Weaver syndrome is a human overgrowth condition characterised by tall stature, dysmorphic facial features, learning disability and variable additional features. We performed exome sequencing in four individuals with Weaver syndrome, identifying a mutation in the histone methyltransferase, EZH2, in each case. Sequencing of EZH2 in additional individuals with overgrowth identified a further 15 mutations. The EZH2 mutation spectrum in Weaver syndrome shows considerable overlap with the inactivating somatic EZH2 mutations recently reported in myeloid malignancies. Our data establish EZH2 mutations as the cause of Weaver syndrome and provide further links between histone modifications and regulation of human growth.

Airborne electromagnetic (EM) results have been applied to estimating depth-to-bedrock and to mapping shallow aggregate resources in selected areas of Northern Ireland. A detailed low-level airborne survey of Northern Ireland was flown in 2005-6 (the Tellus Project) in which magnetic, gamma-radiation and EM data were acquired. Data were acquired with a range of frequencies and inverted into apparent resistivity. Electrical resistivity of rocks is a function mainly of porosity, pore-water salinity, saturation and clay content. ‘Apparent’ resistivity as measured remotely is a complex function of these variables, of the geometry of the measuring system, and of local geology; the thickness and resistivity of the superficial layer are prominent factors. Depth-to-bedrock may only be determined uniquely where other parameters are consistent, where some local borehole control exists and where there is a contrast in apparent resistivity between bedrock and cover.

We present measurements of the dissipation and frequency shift in gold nanomechanical resonators at temperatures down to 10 mK. The resonators were fabricated as doubly clamped beams above a GaAs substrate and actuated magnetomotively. Measurements on beams with frequencies 7.95 and 3.87 MHz revealed that from 30 to 500 mK the dissipation increases with temperature as T 0.5 , with saturation occurring at higher temperatures. The relative frequency shift of the resonators increases logarithmically with temperature up to at least 400 mK. Similarities with the behavior of bulk amorphous solids suggest that the dissipation in our resonators is dominated by two-level systems.

We present measurements of the dissipation and frequency shift in gold nanomechanical resonators at temperatures down to 10 mK. The resonators were fabricated as doubly clamped beams above a GaAs substrate and actuated magnetomotively. Measurements on beams with frequencies 7.95 and 3.87 MHz revealed that from 30 to 500 mK the dissipation increases with temperature as T 0.5 , with saturation occurring at higher temperatures. The relative frequency shift of the resonators increases logarithmically with temperature up to at least 400 mK. Similarities with the behavior of bulk amorphous solids suggest that the dissipation in our resonators is dominated by two-level systems.

Airborne electromagnetic (EM) results have been applied to estimating depth-to-bedrock and to mapping shallow aggregate resources in selected areas of Northern Ireland. A detailed low-level airborne survey of Northern Ireland was flown in 2005-6 (the Tellus Project) in which magnetic, gamma-radiation and EM data were acquired. Data were acquired with a range of frequencies and inverted into apparent resistivity. Electrical resistivity of rocks is a function mainly of porosity, pore-water salinity, saturation and clay content. ‘Apparent’ resistivity as measured remotely is a complex function of these variables, of the geometry of the measuring system, and of local geology; the thickness and resistivity of the superficial layer are prominent factors. Depth-to-bedrock may only be determined uniquely where other parameters are consistent, where some local borehole control exists and where there is a contrast in apparent resistivity between bedrock and cover.

An outbreak of oseltamivir-resistant influenza A (H1N1) occurred in a long-term care facility. Eight (47%) of 17 and 1 (6%) of 16 residents in 2 wards had oseltamivir-resistant influenza A virus (H1N1) infections. Initial outbreak response included treatment and prophylaxis with oseltamivir. The outbreak abated, likely because of infection control measures.

Economic theory suggests that coupled and decoupled direct payments have different impacts on agricultural rental values because of the different production responses associated with these payments. This study investigates the impact of both coupled and decoupled EU CAP direct payments on rental values in Northern Ireland, using panel data taken from the farm business survey for the period from 1994 to 2002. Theoretically, agricultural land rents are a function of expected market returns and expected associated direct payments. The unobservable nature of expected returns means that actual market returns must be used as a proxy for the former in the empirical specification. As a consequence, the problem of bias due to expectation error arises. Using a GMM technique to take account of this problem, the results of this study show that the impact of CAP direct payments on rental values depends on the type of payment and on the nature of the production characteristics of the associated agricultural commodity.

Economic theory suggests that coupled and decoupled direct payments have different impacts on agricultural rental values because of the different production responses associated with these payments. This study investigates the impact of both coupled and decoupled EU CAP direct payments on rental values in Northern Ireland, using panel data taken from the farm business survey for the period from 1994 to 2002. Theoretically, agricultural land rents are a function of expected market returns and expected associated direct payments. The unobservable nature of expected returns means that actual market returns must be used as a proxy for the former in the empirical specification. As a consequence, the problem of bias due to expectation error arises. Using a GMM technique to take account of this problem, the results of this study show that the impact of CAP direct payments on rental values depends on the type of payment and on the nature of the production characteristics of the associated agricultural commodity.

Economic theory suggests that coupled and decoupled direct payments have different impacts on agricultural rental values because of the different production responses associated with these payments. This study investigates the impact of both coupled and decoupled EU CAP direct payments on rental values in Northern Ireland, using panel data taken from the farm business survey for the period from 1994 to 2002. Theoretically, agricultural land rents are a function of expected market returns and expected associated direct payments. The unobservable nature of expected returns means that actual market returns must be used as a proxy for the former in the empirical specification. As a consequence, the problem of bias due to expectation error arises. Using a GMM technique to take account of this problem, the results of this study show that the impact of CAP direct payments on rental values depends on the type of payment and on the nature of the production characteristics of the associated agricultural commodity.

Economic theory suggests that coupled and decoupled direct payments have different impacts on agricultural rental values because of the different production responses associated with these payments. This study investigates the impact of both coupled and decoupled EU CAP direct payments on rental values in Northern Ireland, using panel data taken from the farm business survey for the period from 1994 to 2002. Theoretically, agricultural land rents are a function of expected market returns and expected associated direct payments. The unobservable nature of expected returns means that actual market returns must be used as a proxy for the former in the empirical specification. As a consequence, the problem of bias due to expectation error arises. Using a GMM technique to take account of this problem, the results of this study show that the impact of CAP direct payments on rental values depends on the type of payment and on the nature of the production characteristics of the associated agricultural commodity.

A geochemical anomaly is a concentration of an element or other constituent in a medium (soil, sediment or surface water) which is unusual in its local setting. Geochemical anomalies may be interesting as indicators of processes such as point contamination or mineralizations. They may therefore be practically useful, indicating sources of pollution or mineral deposits which may be of economic value. As defined, a geochemical anomaly is not merely a large (or small) concentration of a constituent as compared to the marginal distribution. To detect anomalies we must therefore do more than simply map the spatial distribution of the constituent. One proposed approach makes use of a singularity index based on fractal representation of spatial variation. The singularity index can be computed from local concentration measures in nested windows. In this paper we propose an approach to compute threshold values for the index to identify enrichment and depletion anomalies, separate from background information. The approach is based on a mixture model for the singularity index, and it can be supported by computing a distribution for background values of the index by parametric bootstrapping from a robustly-estimated variogram model for the target constituent. This approach is illustrated here using data on elements in the soil in four settings in Great Britain and Ireland.

A geochemical anomaly is a concentration of an element or other constituent in a medium (soil, sediment or surface water) which is unusual in its local setting. Geochemical anomalies may be interesting as indicators of processes such as point contamination or mineralizations. They may therefore be practically useful, indicating sources of pollution or mineral deposits which may be of economic value. As defined, a geochemical anomaly is not merely a large (or small) concentration of a constituent as compared to the marginal distribution. To detect anomalies we must therefore do more than simply map the spatial distribution of the constituent. One proposed approach makes use of a singularity index based on fractal representation of spatial variation. The singularity index can be computed from local concentration measures in nested windows. In this paper we propose an approach to compute threshold values for the index to identify enrichment and depletion anomalies, separate from background information. The approach is based on a mixture model for the singularity index, and it can be supported by computing a distribution for background values of the index by parametric bootstrapping from a robustly-estimated variogram model for the target constituent. This approach is illustrated here using data on elements in the soil in four settings in Great Britain and Ireland.

A geochemical anomaly is a concentration of an element or other constituent in a medium (soil, sediment or surface water) which is unusual in its local setting. Geochemical anomalies may be interesting as indicators of processes such as point contamination or mineralizations. They may therefore be practically useful, indicating sources of pollution or mineral deposits which may be of economic value. As defined, a geochemical anomaly is not merely a large (or small) concentration of a constituent as compared to the marginal distribution. To detect anomalies we must therefore do more than simply map the spatial distribution of the constituent. One proposed approach makes use of a singularity index based on fractal representation of spatial variation. The singularity index can be computed from local concentration measures in nested windows. In this paper we propose an approach to compute threshold values for the index to identify enrichment and depletion anomalies, separate from background information. The approach is based on a mixture model for the singularity index, and it can be supported by computing a distribution for background values of the index by parametric bootstrapping from a robustly-estimated variogram model for the target constituent. This approach is illustrated here using data on elements in the soil in four settings in Great Britain and Ireland.

A geochemical anomaly is a concentration of an element or other constituent in a medium (soil, sediment or surface water) which is unusual in its local setting. Geochemical anomalies may be interesting as indicators of processes such as point contamination or mineralizations. They may therefore be practically useful, indicating sources of pollution or mineral deposits which may be of economic value. As defined, a geochemical anomaly is not merely a large (or small) concentration of a constituent as compared to the marginal distribution. To detect anomalies we must therefore do more than simply map the spatial distribution of the constituent. One proposed approach makes use of a singularity index based on fractal representation of spatial variation. The singularity index can be computed from local concentration measures in nested windows. In this paper we propose an approach to compute threshold values for the index to identify enrichment and depletion anomalies, separate from background information. The approach is based on a mixture model for the singularity index, and it can be supported by computing a distribution for background values of the index by parametric bootstrapping from a robustly-estimated variogram model for the target constituent. This approach is illustrated here using data on elements in the soil in four settings in Great Britain and Ireland.

A geochemical anomaly is a concentration of an element or other constituent in a medium (soil, sediment or surface water) which is unusual in its local setting. Geochemical anomalies may be interesting as indicators of processes such as point contamination or mineralizations. They may therefore be practically useful, indicating sources of pollution or mineral deposits which may be of economic value. As defined, a geochemical anomaly is not merely a large (or small) concentration of a constituent as compared to the marginal distribution. To detect anomalies we must therefore do more than simply map the spatial distribution of the constituent. One proposed approach makes use of a singularity index based on fractal representation of spatial variation. The singularity index can be computed from local concentration measures in nested windows. In this paper we propose an approach to compute threshold values for the index to identify enrichment and depletion anomalies, separate from background information. The approach is based on a mixture model for the singularity index, and it can be supported by computing a distribution for background values of the index by parametric bootstrapping from a robustly-estimated variogram model for the target constituent. This approach is illustrated here using data on elements in the soil in four settings in Great Britain and Ireland.