Electrical charging of ash in Icelandic volcanic plumes

The existence of volcanic lightning and alteration of the atmospheric potential gradient in the vicinity of near-vent volcanic plumes provides strong evidence for the charging of volcanic ash. More subtle electrical effects are also visible in balloon soundings of distal volcanic plumes. Near the vent, some proposed charging mechanisms are fractoemission, triboelectrification, and the so-called "dirty thunderstorm" mechanism, which is where ash and convective clouds interact electrically to enhance charging. Distant from the vent, a self-charging mechanism, probably triboelectrification, has been suggested to explain the sustained low levels of charge observed on a distal plume. Recent research by Houghton et al. (2013) linked the self-charging of volcanic ash to the properties of the particle size distribution, observing that a highly polydisperse ash distribution would charge more effectively than a monodisperse one. Natural radioactivity in some volcanic ash could also contribute to self-charging of volcanic plumes. Here we present laboratory measurements of particle size distributions, triboelectrification and radioactivity in ash samples from the Gr\'{i}msv\"{o}tn and Eyjafjallaj\"{o}kull volcanic eruptions in 2011 and 2010 respectively, and discuss the implications of our findings.Comment: XV Conference on Atmospheric Electricity, 15-20 June 2014, Norman, Oklahoma, US

Are osseous artefacts a window to perishable material culture? Implications of an unusually complex bone tool from the Late Pleistocene of East Timor

We report the discovery of an unusually complex and regionally unique bone artefact in a Late Pleistocene archaeological assemblage (c. 35 ka [thousands of years ago]) from the site of Matja Kuru 2 on the island of Timor, in Wallacea. The artefact is interpreted as the broken butt of a formerly hafted projectile point, and it preserves evidence of a complex hafting mechanism including insertion into a shaped or split shaft, a complex pattern of binding including lateral stabilization of the cordage within a bilateral series of notches, and the application of mastic at several stages in the hafting process. The artefact provides the earliest direct evidence for the use of this combination of hafting technologies in the wider region of Southeast Asia, Wallacea, Melanesia and Australasia, and is morphologically unparallelled in deposits of any age. By contrast, it bears a close morphological resemblance to certain bone artefacts from the Middle Stone Age of Africa and South Asia. Examination of ethnographic projectile technology from the region of Melanesia and Australasia shows that all of the technological elements observed in the Matja Kuru 2 artefact were in use historically in the region, including the unusual feature of bilateral notching to stabilize a hafted point. This artefact challenges the notion that complex bone-working and hafting technologies were a relatively late innovation in this part of the world. Moreover, its regional uniqueness encourages us to abandon the perception of bone artefacts as a discrete class of material culture, and to adopt a new interpretative framework in which they are treated as manifestations of a more general class of artefacts that more typically were produced on perishable raw materials including wood

Aspirated capacitor measurements of air conductivity and ion mobility spectra

Measurements of ions in atmospheric air are used to investigate atmospheric electricity and particulate pollution. Commonly studied ion parameters are (1) air conductivity, related to the total ion number concentration, and (2) the ion mobility spectrum, which varies with atmospheric composition. The physical principles of air ion instrumentation are long-established. A recent development is the computerised aspirated capacitor, which measures ions from (a) the current of charged particles at a sensing electrode, and (b) the rate of charge exchange with an electrode at a known initial potential, relaxing to a lower potential. As the voltage decays, only ions of higher and higher mobility are collected by the central electrode and contribute to the further decay of the voltage. This enables extension of the classical theory to calculate ion mobility spectra by inverting voltage decay time series. In indoor air, ion mobility spectra determined from both the novel voltage decay inversion, and an established voltage switching technique, were compared and shown to be of similar shape. Air conductivities calculated by integration were: 5.3 +- 2.5 fS/m and 2.7 +- 1.1 fS/m respectively, with conductivity determined to be 3 fS/m by direct measurement at a constant voltage. Applications of the new Relaxation Potential Inversion Method (RPIM) include air ion mobility spectrum retrieval from historical data, and computation of ion mobility spectra in planetary atmospheres.Comment: To be published in Review of Scientific Instrument

Field methods for rodent studies in Asia and the Indo-Pacific

Farm Management,

Toxic ferns of Western Australia

Botanical descriptions and notes on the distribution of six species of ferns are given. These plants contain the enzyme thiaminase, which may induce thiamin deficiency, or other constituents toxic to animals. The clinical signs of both thiamin deficiency and fern toxicity in affected livestock are described

Tropical Peatland Vegetation Structure and Biomass: Optimal Exploitation of Airborne Laser Scanning

Accurate estimation of above ground biomass (AGB) is required to better understand the variability and dynamics of tropical peat swamp forest (PSF) ecosystem function and resilience to disturbance events. The objective of this work is to examine the relationship between tropical PSF AGB and small-footprint airborne Light Detection and Ranging (LiDAR) discrete return (DR) and full waveform (FW) derived metrics, with a view to establishing the optimal use of this technology in this environment. The study was undertaken in North Selangor peat swamp forest (NSPSF) reserve, Peninsular Malaysia. Plot-based multiple regression analysis was performed to established the strongest predictive models of PSF AGB using DR metrics (only), FW metrics (only), and a combination of DR and FW metrics. Overall, the results demonstrate that a Combination-model, coupling the benefits derived from both DR and FW metrics, had the best performance in modelling AGB for tropical PSF (R2 = 0.77, RMSE = 36.4, rRMSE = 10.8%); however, no statistical difference was found between the rRMSE of this model and the best models using only DR and FW metrics. We conclude that the optimal approach to using airborne LiDAR for the estimation of PSF AGB is to use LiDAR metrics that relate to the description of the mid-canopy. This should inform the use of remote sensing in this ecosystem and how innovation in LiDAR-based technology could be usefully deployed

Temperature response of ex-situ greenhouse gas emissions from tropical peatlands: Interactions between forest type and peat moisture conditions

Climate warming is likely to increase carbon dioxide (CO2) and methane (CH4) emissions from tropical wetlands by stimulating microbial activity, but the magnitude of temperature response of these CO2 and CH4 emissions, as well as variation in temperature response among forest types, is poorly understood. This limits the accuracy of predictions of future ecosystem feedbacks on the climate system, which is a serious knowledge gap as these tropical wetland ecosystems represent a very large source of greenhouse gas emissions (e.g. two-thirds of CH4 emissions from natural wetlands are estimated to be from tropical systems). In this study, we experimentally manipulated temperatures and moisture conditions in peat collected from different forest types in lowland neotropical peatlands in Panama and measured how this impacted ex-situ CO2 and CH4 emissions. The greatest temperature response was found for anaerobic CH4 production (Q10 = 6.8), and CH4 consumption (mesic conditions, Q10 = 2.7), while CO2 production showed a weaker temperature response (Q10 2 production was found under flooded oxic conditions. Net emissions of CO2 and CH4 were greatest from palm forest under all moisture treatments. Furthermore, the temperature response of CH4 emissions differed among dominant vegetation types with the strongest response at palm forest sites where fluxes increased from 42 ± 25 to 2166 ± 842 ng CH4 g−1 h−1 as temperatures were raised from 20 to 35 °C. We conclude that CH4 fluxes are likely to be more strongly impacted by higher temperatures than CO2 fluxes but that responses may differ substantially among forest types. Such differences in temperature response among forest types (e.g. palm vs evergreen broad leaved forest types) need to be considered when predicting ecosystem greenhouse gas responses under future climate change scenarios

Probabilistic Mapping and Spatial Pattern Analysis of Grazing Lawns in Southern African Savannahs Using WorldView-3 Imagery and Machine Learning Techniques

Savannah grazing lawns are a key food resource for large herbivores such as blue wildebeest (Connochaetes taurinus), hippopotamus (Hippopotamus amphibius) and white rhino (Ceratotherium simum), and impact herbivore densities, movement and recruitment rates. They also exert a strong influence on fire behaviour including frequency, intensity and spread. Thus, variation in grazing lawn cover can have a profound impact on broader savannah ecosystem dynamics. However, knowledge of their present cover and distribution is limited. Importantly, we lack a robust, broad-scale approach for detecting and monitoring grazing lawns, which is critical to enhancing understanding of the ecology of these vital grassland systems. We selected two sites in the Lower Sabie and Satara regions of Kruger National Park, South Africa with mesic and semiarid conditions, respectively. Using spectral and texture features derived from WorldView-3 imagery, we (i) parameterised and assessed the quality of Random Forest (RF), Support Vector Machines (SVM), Classification and Regression Trees (CART) and Multilayer Perceptron (MLP) models for general discrimination of plant functional types (PFTs) within a sub-area of the Lower Sabie landscape, and (ii) compared model performance for probabilistic mapping of grazing lawns in the broader Lower Sabie and Satara landscapes. Further, we used spatial metrics to analyse spatial patterns in grazing lawn distribution in both landscapes along a gradient of distance from waterbodies. All machine learning models achieved high F-scores (F1) and overall accuracy (OA) scores in general savannah PFTs classification, with RF (F1 = 95.73±0.004%, OA = 94.16±0.004%), SVM (F1 = 95.64±0.002%, OA = 94.02±0.002%) and MLP (F1 = 95.71±0.003%, OA = 94.27±0.003%) forming a cluster of the better performing models and marginally outperforming CART (F1 = 92.74±0.006%, OA = 90.93±0.003%). Grazing lawn detection accuracy followed a similar trend within the Lower Sabie landscape, with RF, SVM, MLP and CART achieving F-scores of 0.89, 0.93, 0.94 and 0.81, respectively. Transferring models to the Satara landscape however resulted in relatively lower but high grazing lawn detection accuracies across models (RF = 0.87, SVM = 0.88, MLP = 0.85 and CART = 0.75). Results from spatial pattern analysis revealed a relatively higher proportion of grazing lawn cover under semiarid savannah conditions (Satara) compared to the mesic savannah landscape (Lower Sabie). Additionally, the results show strong negative correlation between grazing lawn spatial structure (fractional cover, patch size and connectivity) and distance from waterbodies, with larger and contiguous grazing lawn patches occurring in close proximity to waterbodies in both landscapes. The proposed machine learning approach provides a novel and robust workflow for accurate and consistent landscape-scale monitoring of grazing lawns, while our findings and research outputs provide timely information critical for understanding habitat heterogeneity in southern African savannah