Data mining approach identifies research priorities and data requirements for resolving the red algal tree of life

Background. The assembly of the tree of life has seen significant progress in recent years but algae and protists have been largely overlooked in this effort. Many groups of algae and protists have ancient roots and it is unclear how much data will be required to resolve their phylogenetic relationships for incorporation in the tree of life. The red algae, a group of primary photosynthetic eukaryotes of more than a billion years old, provide the earliest fossil evidence for eukaryotic multicellularity and sexual reproduction. Despite this evolutionary significance, their phylogenetic relationships are understudied. This study aims to infer a comprehensive red algal tree of life at the family level from a supermatrix containing data mined from GenBank. We aim to locate remaining regions of low support in the topology, evaluate their causes and estimate the amount of data required to resolve them. Results. Phylogenetic analysis of a supermatrix of 14 loci and 98 red algal families yielded the most complete red algal tree of life to date. Visualization of statistical support showed the presence of five poorly supported regions. Causes for low support were identified with statistics about the age of the region, data availability and node density, showing that poor support has different origins in different parts of the tree. Parametric simulation experiments yielded optimistic estimates of how much data will be needed to resolve the poorly supported regions (ca. 103 to ca. 104 nucleotides for the different regions). Nonparametric simulations gave a markedly more pessimistic image, some regions requiring more than 2.8 105 nucleotides or not achieving the desired level of support at all. The discrepancies between parametric and nonparametric simulations are discussed in light of our dataset and known attributes of both approaches. Conclusions. Our study takes the red algae one step closer to meaningful inclusion in the tree of life. In addition to the recovery of stable relationships, the recognition of five regions in need of further study is a significant outcome of this work. Based on our analyses of current availability and future requirements of data, we make clear recommendations for forthcoming research.

Ligand arsenic complexation and immunoperoxidase detection of metallothionein in the earthworm Lumbricus rubellus inhabiting arsenic-rich soil

Although earthworms have been found to inhabit arsenic-rich soils in the U.K., the mode of arsenic detoxification is currently unknown. Biochemical analyses and subcellular localization studies have indicated that As3+-thiol complexes may be involved; however, it is not known whether arsenic is capable of inducing the expression of metallothionein (MT) in earthworms. The specific aims of this paper were (a) to detect and gain an atomic characterization of ligand complexing by X-ray absorption spectrometry (XAS), and (b) to employ a polyclonal antibody raised against an earthworm MT isoform (w-MT2) to detect and localize the metalloprotein by immunoperoxidase histochemistry in the tissues of earthworms sampled from arsenic-rich soil. Data suggested that the proportion of arsenate to sulfur-bound species varies within specific earthworm tissues. Although some arsenic appeared to be in the form of arsenobetaine, the arsenic within the chlorogogenous tissue was predominantly coordinated with S in the form of -SH groups. This suggests the presence of an As::MT complex. Indeed, MT was detectable with a distinctly localized tissue and cellular distribution. While MT was not detectable in the surface epithelium or in the body wall musculature, immunoperoxidase histochemistry identified the presence of MT in chloragocytes around blood vessels, within the typhlosolar fold, and in the peri-intestinal region. Focal immunostaining was also detectable in a cohort of cells in the intestinal wall. The results of this study support the hypothesis that arsenic induces MT expression and is sequestered by the metalloprotein in certain target cells and tissues.

Using geostatistical Bayesian Updating to integrate airborne radiometrics and soil geochemistry to improve mapping for mineral exploration

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 economic minerals exploration. The fact that airborne geophysical and traditional soil-sampling data are generated at different spatial resolutions means that 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. With increasing numbers of variables the inference of the cross-covariance 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 maximise information generated from the soil survey, to enable more accurate geological interpretation for the exploration and development of natural resources. The Bayesian updating technique decomposes the collocated estimate into a production of 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 where the history of mineral prospecting for precious and base metals dates from the 18th century. Vein-hosted, strata-bound and volcanogenic occurrences of mineralisation are found. The geostatistical technique was used to improve the resolution of soil geochemistry, collected 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 in the Bayesian approach and the airborne radiometric data were used as secondary data. The approach produced more detailed updated maps and in particular maximized information on mapped estimates of zinc, copper and lead. Greater delineation of an elongated northwest/southeast trending zone in the updated maps strengthened the potential to investigate stratabound base metal deposits.

Assessment of Polycyclic Aromatic Hydrocarbons in an Urban Soil Dataset

We compare a suite of Polycyclic Aromatic Hydrocarbons (Parent PAHs) in soils and air across an urban area (Belfast UK). Isomeric PAH ratios suggest that soil PAHs are mainly from a combustion source. Fugacity modelling across a range of soil temperatures predicts that four ring and larger PAHs from pyrene to indeno[1,2,3–cd]pyrene all partition strongly (>98%) to the soil compartment. This modelling also implies that these PAHs do not experience losses through partitioning to other phases (air, water) due to soil temperature effects. Such modelling may help in understanding the overall contaminantdistribution in soils. The air and soil data together with modelling suggests that care must be taken when considering isomeric ratios of compounds with mass lighter than 178 (i.e. phenanthrene and anthracene) in the soil phase. Comparison of duplicate and replicate samples suggest that field sampling of duplicates dominates uncertainty and validated methodologies for selection of field duplicates and lab splitting are required. As the urban soil four ring PAHs are at equilibrium in the soil phase, and have characteristic ratios that are dominated by a combustion source that is a single controlling factor over spatial distribution, methods that calculate background concentrations can be compared.

A roadmap for marine spatial planning: A critical examination of the European Commission's guiding principles based on their application in the Clyde MSP Pilot Project

The European Commission has developed a set of common principles for marine spatial planning in the European Union. A critical examination of these principles in practice is undertaken through an evaluation of the Clyde Marine Spatial Planning Pilot Project. The principles are found to be lacking in specificity and somewhat inconsistent with the ecosystem based approach, which they advocate. Lessons for new marine spatial planning initiatives, relating particularly to stakeholder participation, governance, data requirements, objective setting, and skills and knowledge needs, are derived from the Clyde Pilot. © 2011.

Spatial and Temporal Changes in Soil Organic Carbon Assessment using an Integrated Geostatistical and Compositional Data Analysis Approach

The Irish and UK governments, along with other countries, have made a commitment to limit the concentrations of greenhouse gases in the atmosphere by reducing emissions from the burning of fossil fuels. This can be achieved (in part) through increasing the sequestration of CO2 from the atmosphere including monitoring the amount stored in vegetation and soils. A large proportion of soil carbon is held within peat due to the relatively high carbon density of peat and organic-rich soils. This is particularly important for a country such as Ireland, where some 16% of the land surface is covered by peat. For Northern Ireland, it has been estimated that the total amount of carbon stored in vegetation is 4.4Mt compared to 386Mt stored within peat and soils. As a result it has become increasingly important to measure and monitor changes in stores of carbon in soils. The conservation and restoration of peat covered areas, although ongoing for many years, has become increasingly important. This is summed up in current EU policy outlined by the European Commission (2012) which seeks to assess the relative contributions of the different inputs and outputs of organic carbon and organic matter to and from soil. Results are presented from the EU-funded Tellus Border Soil Carbon Project (2011 to 2013) which aimed to improve current estimates of carbon in soil and peat across Northern Ireland and the bordering counties of the Republic of Ireland.
Historical reports and previous surveys provide baseline data. To monitor change in peat depth and soil organic carbon, these historical data are integrated with more recently acquired airborne geophysical (radiometric) data and ground-based geochemical data generated by two surveys, the Tellus Project (2004-2007: covering Northern Ireland) and the EU-funded Tellus Border project (2011-2013) covering the six bordering counties of the Republic of Ireland, Donegal, Sligo, Leitrim, Cavan, Monaghan and Louth. The concept being applied is that saturated organic-rich soil and peat attenuate gamma-radiation from underlying soils and rocks. This research uses the degree of spatial correlation (coregionalization) between peat depth, soil organic carbon (SOC) and the attenuation of the radiometric signal to update a limited sampling regime of ground-based measurements with remotely acquired data. To comply with the compositional nature of the SOC data (perturbations of loss on ignition [LOI] data), a compositional data analysis approach is investigated. Contemporaneous ground-based measurements allow corroboration for the updated mapped outputs. This provides a methodology that can be used to improve estimates of soil carbon with minimal impact to sensitive habitats (like peat bogs), but with maximum output of data and knowledge.

Multivariate analysis of regional-scale geochemical data for environmental monitoring

A compositional multivariate approach is used to analyse regional scale soil geochemical data obtained as part of the Tellus Project generated by the Geological Survey Northern Ireland (GSNI). The multi-element total concentration data presented comprise XRF analyses of 6862 rural soil samples collected at 20cm depths on a non-aligned grid at one site per 2 km2. Censored data were imputed using published detection limits. Using these imputed values for 46 elements (including LOI), each soil sample site was assigned to the regional geology map provided by GSNI initially using the dominant lithology for the map polygon. Northern Ireland includes a diversity of geology representing a stratigraphic record from the Mesoproterozoic, up to and including the Palaeogene. However, the advance of ice sheets and their meltwaters over the last 100,000 years has left at least 80% of the bedrock covered by superficial deposits, including glacial till and post-glacial alluvium and peat. The question is to what extent the soil geochemistry reflects the underlying geology or superficial deposits. To address this, the geochemical data were transformed using centered log ratios (clr) to observe the requirements of compositional data analysis and avoid closure issues. Following this, compositional multivariate techniques including compositional Principal Component Analysis (PCA) and minimum/maximum autocorrelation factor (MAF) analysis method were used to determine the influence of underlying geology on the soil geochemistry signature. PCA showed that 72% of the variation was determined by the first four principal components (PC’s) implying “significant” structure in the data. Analysis of variance showed that only 10 PC’s were necessary to classify the soil geochemical data. To consider an improvement over PCA that uses the spatial relationships of the data, a classification based on MAF analysis was undertaken using the first 6 dominant factors. Understanding the relationship between soil geochemistry and superficial deposits is important for environmental monitoring of fragile ecosystems such as peat. To explore whether peat cover could be predicted from the classification, the lithology designation was adapted to include the presence of peat, based on GSNI superficial deposit polygons and linear discriminant analysis (LDA) undertaken. Prediction accuracy for LDA classification improved from 60.98% based on PCA using 10 principal components to 64.73% using MAF based on the 6 most dominant factors. The misclassification of peat may reflect degradation of peat covered areas since the creation of superficial deposit classification. Further work will examine the influence of underlying lithologies on elemental concentrations in peat composition and the effect of this in classification analysis.

Soil Carbon stocks and schanges in the Republic of Ireland

The soil carbon (C) stock of the Republic of Ireland is estimated to have been 2048 Mt in 1990 and 2021 Mt in 2000. Peat holds around 53% of the soil C stock, but on 17% of the land area. The C density of soils (t C ha-1) is mapped at 2 km*2 km resolution. The greatest soil C densities occur where deep raised bogs are the dominant soil; in these grid squares C density can reach 3000 t C ha-1. Most of the loss of soil C between 1990 and 2000-up to 23 Mt C (1% of 1990 soil C stock)-was through industrial peat extraction. The average annual change in soil C stocks from 1990 to 2000 due to land use change was estimated at around 0.02% of the 1990 stock. Considering uncertainties in the data used to calculate soil C stocks and changes, the small average annual 'loss' could be regarded as 'no change'.

Retrospective assessment of dryland soil stability in relation to grazing and climate change

Accelerated soil erosion is an aspect of dryland degradation that is affected by repeated intense drought events and land management activities such as commercial livestock grazing. A soil stability index (SSI) that detects the erosion status and susceptibility of a landscape at the pixel level, i.e., stable, erosional, or depositional pixels, was derived from the spectral properties of an archived time series (from 1972 to 1997) of Landsat satellite data of a commercial ranch in northeastern Utah. The SSI was retrospectively validated with contemporary field measures of soil organic matter and erosion status that was surveyed by US federal land management agencies. Catastrophe theory provided the conceptual framework for retrospective assessment of the impact of commercial grazing and soil water availability on the SSI. The overall SSI trend was from an eroding landscape in the early drier 1970s towards stable conditions in the wetter mid-1980s and late 1990s. The landscape catastrophically shifted towards an extreme eroding state that was coincident with the “The Great North American Drought of 1988”. Periods of landscape stability and trajectories toward stability were coincident with extremely wet El Niño events. Commercial grazing had less correlation with soil stability than drought conditions. However, the landscape became more susceptible to erosion events under multiple droughts and grazing. Land managers now have nearly a year warning of El Niño and La Niña events and can adjust their management decisions according to predicted landscape erosion conditions.

Isotopic composition of tropospheric and soil N2O from successive depths of agricultural plots with contrasting crops and nitrogen amendments

Agricultural soils are the dominant contributor to increases in atmospheric nitrous oxide (N2O). Few studies have investigated the natural N and O isotopic composition of soil N2O. We collected soil gas samples using horizontal sampling tubes installed at successive depths under five contrasting agricultural crops (e.g., unamended alfalfa, fertilized cereal), and tropospheric air samples. Mean d 15N and d 18O values of soil N2O ranged from -28.0 to +8.9‰, and from +29.0 to +53.6‰. The mean d 15N and d 18O values of tropospheric N2O were +4.6 ± 0.7‰ and +48.3 ± 0.2‰, respectively. In general, d values were lowest at depth, they were negatively correlated to soil [N2O], and d 15N was positively correlated to d 18O for every treatment on all sampling dates. N2O from the different agricultural treatments had distinct d 15N and d 18O values that varied among sampling dates. Fertilized treatments had soil N2O with low d values, but the unamended alfalfa yielded N2O with the lowest d values. Diffusion was not the predominant process controlling N2O concentration profiles. Based on isotopic and concentration data, it appears that soil N2O was consumed, as it moved from deeper to shallower soil layers. To better assess the main process(es) controlling N2O within a soil profile, we propose a conceptual model that integrates data on net N2O production or consumption and isotopic data. The direct local impact of agricultural N2O on the isotopic composition of tropospheric N2O was recorded by a shift toward lower d values of locally measured tropospheric N2O on a day with very high soil N2O emissions.

Nitrogen-15 and Oxygen-18 Natural Abundance of Potassium Chloride Extractable Soil Nitrate Using the Denitrifier Method

In agroecosystems, most isotopic investigations of NO3- involve the use of tracers that are artificially enriched in 15N. Although the dual isotope composition of NO3-— d15N and d18O is especially beneficial for understanding the origin and fate of NO3-, its use for KCl-extractable soil NO3- has been hampered by the lack of a suitable analytical technique. Our objective was to test whether the denitrifier method, whereby NO3- is reduced to N2O before mass spectrometric analysis, can be used to determine the N and O isotopic composition of NO3- from 2 M KCl soil extracts. Several internationally accepted NO3- standards were dissolved in 2 M KCl, the conventional extractant for soil inorganic N, and inoculated with the bacterial strain Pseudomonas aureofaciens (ATCC no. 13985). The standard deviation of the NO3- standards analyzed did not exceed 0.2‰ for d15N and 0.3‰ for d18O values. After appropriate corrections, differences between our measured and consensus d15N and d18O values of standard NO3- generally were within the standard deviations given for the consensus values. Both d15N and d18O values were reproducible among separate analytical runs. The method was also tested on genuine 2 M KCl extracts from unfertilized and fertilized soils. Depending on N fertilization, the soils had distinct d15N and d18O values, which were attributed to amendment with NH4NO3 fertilizer. Hence, our data indicate that the denitrifier method provides a fast, reliable, precise, and accurate way of simultaneously analyzing the natural abundances of 15N and 18O in KCl-extractable soil NO3-.

Deep weathering of calcareous sedimentary rock and the redistribution of iron and manganese in soil and saprolite

Iron and Mn redistribute in soil and saprolite during weathering. The geological weathering fronts ofcalcareous sedimentary rock were investigated by examining the bulk density, porosity, and distribution ofCa, Fe, and Mn. Core samples were taken ofsoil, saprolite, and bedrock material from both summit (HHMS-4B) and sideslope (HHMS-5A) positions on an interbedded Nolichucky shale and Maryville limestone landform in Solid Waste Storage Area 6 (SWSA-6). This is a low-level radioactive solids waste disposal site on the Dept. ofEnergy (DOE) Oak Ridge Reservation in Roane County Tennessee. This work was initiated because data about the properties of highly weathered sedimentary rock on this site were limited. The core samples were analyzed for pH, calcium carbonate equivalence (CCE), hydroxylamine-extractable (HA) Mn, and dithionite-citrate (CBD)-extractable Fe and Mn. Low pH values occurred from the soil surface down to the depth of the oxidized and leached saprolite in both cores. The CCE and HA-extractable Mn results were also influenced by the weathering that has occurred in these zones. Extractable Mn oxide was higher at a lower depth in the oxidized and leached saprolite compared with the Fe oxide, which was higher in the overlying soil solum. Amounts of Mn oxides were higher in the sideslope core (HHMS-5A) than in the summit core (HHMS-4B). Iron was more abundant in the deeper weathered summit core, but the highest value, 39.4 g kg-1, was found at 1.8 to 2.4 m in the sideslope core. The zone encompassing the oxidized and partially leached saprolite down to the unoxidized and unleached bedrock had higher densities and larger quantities of CaCO3 than the soil solum and oxidized and leached saprolite. The overlying soil and oxidized and leached saprolite had lower pH and CCE values and were higher in Fe and Mn oxides than the oxidized and unleached saprolite. The distribution of Fe and Mn is important when evaluating soil and saprolite for hazardous waste disposal site assessment.