187 research outputs found

    Surface erosion assessment using 137 Cs: examples from New Zealand

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    The 137Cs technique has provided the first quantitative, medium-term data on rates of soil redistribution by surface erosion on both cropland and rangeland in New Zealand. Use of the technique has demonstrated: high rates of soil redistribution by water erosion at two cropland sites under intensive vegetable production; a slow rate of net loss of soil by wind erosion associated with arable farming; a strong association between vegetation depletion and wind erosion on grazed rangeland. Research has also provided data on natural short-range variability of 137Cs in uneroded soils, and a technique for independently estimating 137Cs reference values from rainfall. The greatest research need remains the development of robust, accurate calibration procedures for conve rting 137Cs measurements to rates of erosion

    Error in total ozone measurements arising from aerosol attenuation

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    A generalized least squares method for deducing both total ozone and aerosol extinction spectrum parameters from Dobson spectrophotometer measurements was developed. An error analysis applied to this system indicates that there is little advantage to additional measurements once a sufficient number of line pairs have been employed to solve for the selected detail in the attenuation model. It is shown that when there is a predominance of small particles (less than about 0.35 microns in diameter) the total ozone from the standard AD system is too high by about one percent. When larger particles are present the derived total ozone may be an overestimate or an underestimate but serious errors occur only for narrow polydispersions

    Late Holocene landscape change history related to the Alpine Fault determined from drowned forests in Lake Poerua, Westland, New Zealand

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    Abstract. Lake Poerua is a small, shallow lake that abuts the scarp of the Alpine Fault on the West Coast of New Zealand's South Island. Radiocarbon dates from drowned podocarp trees on the lake floor, a sediment core from a rangefront alluvial fan, and living tree ring ages have been used to deduce the late Holocene history of the lake. Remnant drowned stumps of kahikatea (Dacrycarpus dacrydioides) at 1.7–1.9 m water depth yield a preferred time-of-death age at 1766–1807 AD, while a dryland podocarp and kahikatea stumps at 2.4–2.6 m yield preferred time-of-death ages of ca. 1459–1626 AD. These age ranges are matched to, but offset from, the timings of Alpine Fault rupture events at ca. 1717 AD, and either ca. 1615 or 1430 AD. Alluvial fan detritus dated from a core into the toe of a rangefront alluvial fan, at an equivalent depth to the maximum depth of the modern lake (6.7 m), yields a calibrated age of AD 1223–1413. This age is similar to the timing of an earlier Alpine Fault rupture event at ca. 1230 AD ± 50 yr. Kahikatea trees growing on rangefront fans give ages of up to 270 yr, which is consistent with alluvial fan aggradation following the 1717 AD earthquake. The elevation levels of the lake and fan imply a causal and chronological link between lake-level rise and Alpine Fault rupture. The results of this study suggest that the growth of large, coalescing alluvial fans (Dry and Evans Creek fans) originating from landslides within the rangefront of the Alpine Fault and the rise in the level of Lake Poerua may occur within a decade or so of large Alpine Fault earthquakes that rupture adjacent to this area. These rises have in turn drowned lowland forests that fringed the lake. Radiocarbon chronologies built using OxCal show that a series of massive landscape changes beginning with fault rupture, followed by landsliding, fan sedimentation and lake expansion. However, drowned Kahikatea trees may be poor candidates for intimately dating these events, as they may be able to tolerate water for several decades after metre-scale lake level rises have occurred

    Late Holocene landscape change history related to the Alpine Fault determined from drowned forests in Lake Poerua, Westland, New Zealand

    Get PDF
    Lake Poerua is a small, shallow lake that abuts the scarp of the Alpine Fault on the West Coast of New Zealand’s South Island. Radiocarbon dates from drowned podocarp trees on the lake floor, a sediment core from a rangefront alluvial fan, and living tree ring ages have been used to deduce the late Holocene history of the lake. Remnant drowned stumps of kahikatea (Dacrycarpus dacrydioides) at 1.7–1.9m water depth yield a preferred time-ofdeath age at 1766–1807 AD, while a dryland podocarp and kahikatea stumps at 2.4–2.6m yield preferred time-of-death ages of ca. 1459–1626 AD. These age ranges are matched to, but offset from, the timings of Alpine Fault rupture events at ca. 1717 AD, and either ca. 1615 or 1430 AD. Alluvial fan detritus dated from a core into the toe of a rangefront alluvial fan, at an equivalent depth to the maximum depth of the modern lake (6.7 m), yields a calibrated age of AD 1223–1413. This age is similar to the timing of an earlier Alpine Fault rupture event at ca. 1230AD±50 yr. Kahikatea trees growing on rangefront fans give ages of up to 270 yr, which is consistent with alluvial fan aggradation following the 1717AD earthquake. The elevation levels of the lake and fan imply a causal and chronological link between lake-level rise and Alpine Fault rupture. The results of this study suggest that the growth of large, coalescing alluvial fans (Dry and Evans Creek fans) originating from landslides within the rangefront of the Alpine Fault and the rise in the level of Lake Poerua may occur within a decade or so of large Alpine Fault earthquakes that rupture adjacent to this area. These rises have in turn drowned lowland forests that fringed the lake. Radiocarbon chronologies built using OxCal show that a series of massive landscape changes beginning with fault rupture, followed by landsliding, fan sedimentation and lake expansion. However, drowned Kahikatea trees may be poor candidates for intimately dating these events, as they may be able to tolerate water for several decades after metre-scale lake level rises have occurred

    Analysis of structural transformations during the synthesis of a MoVTeNb mixed oxide calalyst

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    This work presents a detailed investigation of the preparation routine for the multi-metal oxide Mo1V0.30Te0.23Nb0.125Ox used as catalyst for the selective oxidation of propane to acrylic acid. In situ Raman spectroscopy on the initial aqueous polyoxometalate solution prepared from ammonium heptamolybdate, ammonium metavanadate and hexaoxotelluric acid reveals the coexistence of Anderson-type anions [TeM6O24]n−, M = Mo, V; n ≥ 6 and protonated decavanadate species [HxV10O28](6−x)−. Raman analysis showed that the monomeric motif of the Anderson-type tellurate is preserved after addition of the Nb precursor and the subsequent spray-drying process. Calcination of the X-ray amorphous spray-dried material in air at 548 K seems to be the essential step, leading to a re-arrangement of the tellurate building blocks, generating nanocrystalline precursors of the phases finally established during treatment in helium at 873 K

    Methods for the Study of Marine Biodiversity

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    Recognition of the threats to biodiversity and its importance to society has led to calls for globally coordinated sampling of trends in marine ecosystems. As a step to defining such efforts, we review current methods of collecting and managing marine biodiversity data. A fundamental component of marine biodiversity is knowing what, where, and when species are present. However, monitoring methods are invariably biased in what taxa, ecological guilds, and body sizes they collect. In addition, the data need to be placed, and/or mapped, into an environmental context. Thus a suite of methods will be needed to encompass representative components of biodiversity in an ecosystem. Some sampling methods can damage habitat and kill species, including unnecessary bycatch. Less destructive alternatives are preferable, especially in conservation areas, such as photography, hydrophones, tagging, acoustics, artificial substrata, light-traps, hook and line, and live-traps. Here we highlight examples of operational international sampling programmes and data management infrastructures, notably the Continuous Plankton Recorder, Reef Life Survey, and detection of Harmful Algal Blooms and MarineGEO. Data management infrastructures include the World Register of Marine Species for species nomenclature and attributes, the Ocean Biogeographic Information System for distribution data, Marine Regions for maps, and Global Marine Environmental Datasets for global environmental data. Existing national sampling programmes, such as fishery trawl surveys and intertidal surveys, may provide a global perspective if their data can be integrated to provide useful information. Less utilised and emerging sampling methods, such as artificial substrata, light-traps, microfossils and eDNA also hold promise for sampling the less studied components of biodiversity. All of these initiatives need to develop international standards and protocols, and long-term plans for their governance and support.published_or_final_versio

    Models for short term malaria prediction in Sri Lanka

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    <p>Abstract</p> <p>Background</p> <p>Malaria in Sri Lanka is unstable and fluctuates in intensity both spatially and temporally. Although the case counts are dwindling at present, given the past history of resurgence of outbreaks despite effective control measures, the control programmes have to stay prepared. The availability of long time series of monitored/diagnosed malaria cases allows for the study of forecasting models, with an aim to developing a forecasting system which could assist in the efficient allocation of resources for malaria control.</p> <p>Methods</p> <p>Exponentially weighted moving average models, autoregressive integrated moving average (ARIMA) models with seasonal components, and seasonal multiplicative autoregressive integrated moving average (SARIMA) models were compared on monthly time series of district malaria cases for their ability to predict the number of malaria cases one to four months ahead. The addition of covariates such as the number of malaria cases in neighbouring districts or rainfall were assessed for their ability to improve prediction of selected (seasonal) ARIMA models.</p> <p>Results</p> <p>The best model for forecasting and the forecasting error varied strongly among the districts. The addition of rainfall as a covariate improved prediction of selected (seasonal) ARIMA models modestly in some districts but worsened prediction in other districts. Improvement by adding rainfall was more frequent at larger forecasting horizons.</p> <p>Conclusion</p> <p>Heterogeneity of patterns of malaria in Sri Lanka requires regionally specific prediction models. Prediction error was large at a minimum of 22% (for one of the districts) for one month ahead predictions. The modest improvement made in short term prediction by adding rainfall as a covariate to these prediction models may not be sufficient to merit investing in a forecasting system for which rainfall data are routinely processed.</p
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