Exceptionally Long Distance Transport of Volcanic Ash: Implications for Stratigraphy, Hazards and the Sourcing of Distal Tephra Deposits

Cryptotephras (tephra not visible to the naked eye) form the foundation of the tephrostratigraphic frameworks used in Europe to date and correlate widely distributed geologic, paleoenvironmental and archaeological records. Pyne-O'Donnell et al. (2012) established the potential for developing a similar crypto-tephrostratigraphy across eastern North America by identifying multiple tephra, including the White River Ash (east; WRAe), St. Helens We and East Lake, in a peat core located in Newfoundland. Following on from this work, several ongoing projects have examined additional peat cores from Michigan, New York State, Maine, Nova Scotia and Newfoundland to build a tephrostratigraphic framework for this region. Using the precedent set by recent research by Jensen et al.(in press) that correlated the Alaskan WRAe to the European cryptotephra AD860B, unknown tephras identified in this work were not necessarily assumed to be from "expected" source areas (e.g. the Cascades). Here we present several examples of the preservation of tephra layers with an intercontinental distribution (i.e. WRAe and Ksudach 1), from relatively small magnitude events (i.e. St. Helens layer T, Mono Crater), and the first example of a Mexican ash in the NE (Volcan Ceboruco, Jala pumice). There are several implications of the identification of these units. These far-travelled ashes: (1) highlight the need to consider "ultra" distal source volcanoes for unknown cryptotephra deposits,. (2) present an opportunity for physical volcanologists to examine why some eruptions have an exceptional distribution of ash that is not necessarily controlled by the magnitude of the event. (3) complicate the idea of using tephrostratigraphic frameworks to understand the frequency of eruptions towards aiding hazard planning and prediction (e.g. Swindles et al., 2011). (4) show that there is a real potential to link tropical and mid to high-latitude paleoenvironmental records. Jensen et al. (in press) Transatlantic correlation of the Alaskan White River Ash. Geology. Pyne-O'Donnell et al. (2012). High-precision ultra-distal Holocene tephrochronology in North America. Quaternary Science Reviews, 52, 6-11. Swindles et al. (2011). A 7000 yr perspective on volcanic ash clouds affecting northern Europe. Geology, 39, 887-890.

Land use history of Village Bay, Hirta, St Kilda World Heritage Site:A palynological investigation of plaggen soils

This paper presents findings based on a palynological investigation of artificially accreting (plaggen) soils from the settlement of Village Bay, Hirta, in the St Kilda archipelago, which was perhaps the most distant and inhospitable outpost of sustained human habitation in the British Isles. The soils were developed principally through the addition of turf ash and seabird waste, although some ash may have been derived from upland peats. It is assumed that the woodland pollen signal (much lower in the soils than in an upland peat site nearby) represents off-island sources. Corylus avellana-type pollen (frequent in upland sites), along with Potentilla-type, may provide markers in the Village Bay profiles for the addition of ashed hillside turf, and possibly peat, to the plaggen soils. Cereal-type pollen is well represented through the profiles and is often strongly associated with the record for Chrysanthemum segetum (corn marigold), a frequent indicator of arable land. The Brassicaceae signal may partly reflect the cultivation of cabbages; Chelidonium majus (greater celandine) may have been grown for medicinal use. Soil mixing has rendered radiocarbon dating meaningless at this site, but the establishment of a change in cultivation regime before AD 1830 may have been identified from the patterns of pollen concentration and preservation in the profiles. © 2008 Elsevier B.V. All rights reserved.

The long-term fate of permafrost peatlands under rapid climate warming

Permafrost peatlands contain globally important amounts of soil organic carbon, owing to cold conditions which suppress anaerobic decomposition. However, climate warming and permafrost thaw threaten the stability of this carbon store. The ultimate fate of permafrost peatlands and their carbon stores is unclear because of complex feedbacks between peat accumulation, hydrology and vegetation. Field monitoring campaigns only span the last few decades and therefore provide an incomplete picture of permafrost peatland response to recent rapid warming. Here we use a high-resolution palaeoecological approach to understand the longer-term response of peatlands in contrasting states of permafrost degradation to recent rapid warming. At all sites we identify a drying trend until the late-twentieth century; however, two sites subsequently experienced a rapid shift to wetter conditions as permafrost thawed in response to climatic warming, culminating in collapse of the peat domes. Commonalities between study sites lead us to propose a five-phase model for permafrost peatland response to climatic warming. This model suggests a shared ecohydrological trajectory towards a common end point: inundated Arctic fen. Although carbon accumulation is rapid in such sites, saturated soil conditions are likely to cause elevated methane emissions that have implications for climate-feedback mechanisms.

A mid to late Holocene cryptotephra framework from eastern North America

Holocene cryptotephras of Alaskan and Pacific Northwestern origin have recently been detected ca. 7000 km away on the east coast of North America. This study extends the emerging North American tephrochronological framework by geochemically characterising seventeen cryptotephra layers from four newly explored peatlands. All detected tephras were deposited during the late Holocene, with no horizons present in the peat between ca. 3000–5000 years ago. The prevalence of the Alaskan White River Ash eastern lobe (AD 847 ± 1) is confirmed across the eastern seaboard from Newfoundland to Maine and a regional depositional pattern from Mount St Helens Set W (AD 1479–1482) is presented. The first occurrences of four additional cryptotephras in eastern North America are described, three of which may originate from source regions in Mexico, Kamchatka (Russia) and Hokkaido (Japan). The possibility of such tephras reaching eastern North America presents the opportunity to link palaeo-archives from the tropics and eastern Asia with those from the western Atlantic seaboard, aiding inter-regional comparisons of proxy-climatic records.

Catchment and in-stream influences on metal concentration and ochre deposit density in upland streams, Northern Ireland

Metal concentrations from stream waters in two geological blocks in Northern Ireland were compared to determine the contributions of catchment characteristics and in-stream conditions. One block is composed of metamorphosed schist and unconsolidated glacial drift with peat or peaty podzol (mainly humic) soils, while the other block consists of tertiary basalt with brown earth and gley soils. Water samples were collected from 52 stream sites and analysed for Fe, Mn and Al as well as a range of other chemical determinands known to affect metal solubility. Densities of metal-rich ochre deposit were determined for stream bed stone samples. Higher conductivities and concentrations of bicarbonate, alkalinity, Ca and Mg occurred on basalt than on schist. Despite higher Fe and Mn oxide concentrations in basalt-derived non-humic soils, stream water concentrations were much lower and ochre deposit densities only one third of those on schist overlain by humic soils. Neither rock nor soil type predicted Al concentrations, but pH and dissolved oxygen did. Peat-generated acidity and the limited acid neutralising capacity of base-poor metamorphosed schist have resulted in elevated concentrations of metals and ochre deposit in surface waters.

Compositional data-driven alternatives to single geochemical component maps

Conventional practice in Regional Geochemistry includes as a final step of any geochemical campaign the generation of a series of maps, to show the spatial distribution of each of the components considered. Such maps, though necessary, do not comply with the compositional, relative nature of the data, which unfortunately make any conclusion based on them sensitive
to spurious correlation problems. This is one of the reasons why these maps are never interpreted isolated. This contribution aims at gathering a series of statistical methods to produce individual maps of multiplicative combinations of components (logcontrasts), much in the flavor of equilibrium constants, which are designed on purpose to capture certain aspects of the data.
We distinguish between supervised and unsupervised methods, where the first require an external, non-compositional variable (besides the compositional geochemical information) available in an analogous training set. This external variable can be a quantity (soil density, collocated magnetics, collocated ratio of Th/U spectral gamma counts, proportion of clay particle fraction, etc) or a category (rock type, land use type, etc). In the supervised methods, a regression-like model between the external variable and the geochemical composition is derived in the training set, and then this model is mapped on the whole region. This case is illustrated with the Tellus dataset, covering Northern Ireland at a density of 1 soil sample per 2 square km, where we map the presence of blanket peat and the underlying geology. The unsupervised methods considered include principal components and principal balances
(Pawlowsky-Glahn et al., CoDaWork2013), i.e. logcontrasts of the data that are devised to capture very large variability or else be quasi-constant. Using the Tellus dataset again, it is found that geological features are highlighted by the quasi-constant ratios Hf/Nb and their ratio against SiO2; Rb/K2O and Zr/Na2O and the balance between these two groups of two variables; the balance of Al2O3 and TiO2 vs. MgO; or the balance of Cr, Ni and Co vs. V and Fe2O3. The largest variability appears to be related to the presence/absence of peat.

Geostatistical Fisher discriminant analysis

A geostatistical version of the classical Fisher rule (linear discriminant analysis) is presented.This method is applicable when a large dataset of multivariate observations is available within a domain split in several known subdomains, and it assumes that the variograms (or covariance functions) are comparable between subdomains, which only differ in the mean values of the available variables. The method consists on finding the eigen-decomposition of the matrix W-1B, where W is the matrix of sills of all direct- and cross-variograms, and B is the covariance matrix of the vectors of weighted means within each subdomain, obtained by generalized least squares. The method is used to map peat blanket occurrence in Northern Ireland, with data from the Tellus
survey, which requires a minimal change to the general recipe: to use compositionally-compliant variogram tools and models, and work with log-ratio transformed data.

Volumetric Carbon Content Calculations: A Geostatistical and Compositional Approach

This study applies spatial statistical techniques including cokriging to integrate airborne geophysical (radiometric) data with ground-based measurements of peat depth and soil organic carbon (SOC) to monitor change in peat cover for carbon stock calculations. The research is part of the EU funded Tellus Border project and is supported by the INTERREG IVA development programme of the European Regional Development Fund, which is managed by the Special EU Programmes Body (SEUPB). The premise is that saturated peat attenuates the radiometric signal from underlying soils and rocks. Contemporaneous ground-based measurements were collected to corroborate mapped estimates and develop a statistical model for volumetric carbon content (VCC) to 0.5 metres. Field measurements included ground penetrating radar, gamma ray spectrometry and a soil sampling methodology which measured bulk density and soil moisture to determine VCC. One aim of the study was to explore whether airborne radiometric survey data can be used to establish VCC across a region. To account for the footprint of airborne radiometric data, five cores were obtained at each soil sampling location: one at the centre of the ground radiometric equivalent sample location and one at each of the four corners 20 metres apart. This soil sampling strategy replicated the methodology deployed for the Tellus Border geochemistry survey. Two key issues will be discussed from this work. The first addresses the integration of different sampling supports for airborne and ground measured data and the second discusses the compositional nature of the VOC data.

A 250-year periodicity in Southern Hemisphere westerly winds over the last 2600 years

Southern Hemisphere westerly airflow has a significant influence on the ocean–atmosphere system of the mid- to high latitudes with potentially global climate implications. Unfortunately, historic observations only extend back to the late 19th century, limiting our understanding of multi-decadal to centennial change. Here we present a highly resolved (30-year) record of past westerly wind strength from a Falkland Islands peat sequence spanning the last 2600 years. Situated within the core latitude of Southern Hemisphere westerly airflow (the so-called furious fifties), we identify highly variable changes in exotic pollen and charcoal derived from South America which can be used to inform on past westerly air strength. We find a period of high charcoal content between 2000 and 1000 cal. years BP, associated with increased burning in Patagonia, most probably as a result of higher temperatures and stronger westerly airflow. Spectral analysis of the charcoal record identifies a pervasive ca. 250-year periodicity that is coherent with radiocarbon production rates, suggesting that solar variability has a modulating influence on Southern Hemisphere westerly airflow. Our results have important implications for understanding global climate change through the late Holocene.

Exploring the joint compositional variability of major components and trace elements in the Tellus soil geochemistry survey (Northern Ireland)

The complexity of modern geochemical data sets is increasing in several aspects (number of available samples, number of elements measured, number of matrices analysed, geological-environmental variability covered, etc), hence it is becoming increasingly necessary to apply statistical methods to elucidate their structure. This paper presents an exploratory analysis of one such complex data set, the Tellus geochemical soil survey of Northern Ireland (NI). This exploratory analysis is based on one of the most fundamental exploratory tools, principal component analysis (PCA) and its graphical representation as a biplot, albeit in several variations: the set of elements included (only major oxides vs. all observed elements), the prior transformation applied to the data (none, a standardization or a logratio transformation) and the way the covariance matrix between components is estimated (classical estimation vs. robust estimation). Results show that a log-ratio PCA (robust or classical) of all available elements is the most powerful exploratory setting, providing the following insights: the first two processes controlling the whole geochemical variation in NI soils are peat coverage and a contrast between “mafic” and “felsic” background lithologies; peat covered areas are detected as outliers by a robust analysis, and can be then filtered out if required for further modelling; and peat coverage intensity can be quantified with the %Br in the subcomposition (Br, Rb, Ni).

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.