Browsing by Author "Wilson T"

Now showing 1 - 4 of 4
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    Comparing the Carbon Storage Potential of Naturally Regenerated Tea Trees with Default New Zealand Carbon Look-Up Tables: A Case Study
    (MDPI, 12/04/2023) Wilson T; Grafton M; Irwin M; Hatano, R
    The New Zealand Emissions Trading Scheme allows landowners to be remunerated for the carbon sequestration capabilities of eligible forests established post 1990. For afforested areas of 100 hectares or fewer, carbon sequestration is estimated with the use of default carbon look-up tables administered by the Ministry for Primary Industries. However, a disparity exists between exotic pines (Pinus radiata), where carbon sequestration predictions are regionally differentiated, and native species, where carbon sequestration estimations are neither distinguished by species or locality. This paper aims to highlight this inequality by comparing the calculated carbon storage of endemic tree species with the ‘Indigenous Forest’ category in the carbon look-up tables. The carbon storage of 12-year-old naturally regenerated tea trees (Leptospermum scoparium and Kunzea ericoides) was calculated using allometric measurements and compared to the look-up tables. The results suggest that carbon look-up tables underestimate the carbon sequestration of native tea trees by 81.8%. A bimodal data distribution suggests that carbon sequestration is heavily dependent on light interception levels. It is recommended that carbon sequestration data for specific native species in different environments are collected and integrated into such tables.
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    DEMONSTRATING THE COMPATIBILITY OF A NEW SPREADMARK TEST WITH THE CURRENT METHOD
    (12/04/2019) Wilson T; Grafton M; Currie, L; Christensen, C
    The New Zealand Spreadmark test which although proven to accurately measure the Coefficient of Variation (CV) of spreading equipment, entails a laborious procedure which is expensive to implement. This study aims to validate the accuracy of a newly developed test method based on the current one that hastens the process, making it increasingly cost effective. The proposed solution reduces the amount of trays used to collect and measure the fertiliser spread pattern. The proposed method reduces the number of trays by half, placing them one meter apart compared to the current industry standard of half a meter. An electronic tray weighing system developed by EuroAgri streamlines the process. This allows the scales to be, zeroed, after each pass by removing the need to empty trays. Collated data of previous Spreadmark tests sourced from certified Spreadmark testers. This had the support of the Fertiliser Quality Council that manages the scheme used in the study. Tray weights of each successive 0.5 and 1.0 metres were, averaged to imitate tray spaces of 1.0 metre. The 1.0 metre tray spacing showed a strong correlation to the 0.5 meter spaces, maintaining the normal distribution pattern of the spread fertilizer albeit in a slightly lower definition. Coupled with the electronic scales that reduces human error, this forms an accurate and efficient method of undertaking testing. This new system could have marked effects upon the future of spreader testing in New Zealand, including higher proportions of conforming spreaders (due to increased time and cost effectiveness) leading to lower field coefficient of variation (CV). As a result, fertiliser efficacy would increase, as would financial returns.
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    Development of a Bayesian event tree for short-term eruption onset forecasting at Taupō volcano
    (Elsevier BV, 2022-12) Scott E; Bebbington M; Wilson T; Kennedy B; Leonard G
    Taupō volcano, located within the Taupō Volcanic Zone (TVZ) in the central North Island of Aotearoa-New Zealand, is one of the world's most active silicic caldera systems. Silicic calderas such as Taupō are capable of a broad and complex range of volcanological activity, ranging from minor unrest episodes to large destructive supereruptions. A critical tool for volcanic risk management is eruption forecasting. The Bayesian Event Tree for Eruption Forecasting (BET_EF) is one probabilistic eruption forecasting tool that can be used to produce short-term eruption forecasts for any volcano worldwide. A BET_EF model is developed for Taupō volcano, informed by geologic and historic data. Monitoring parameters for the model were obtained through a structured expert elicitation workshop with 30 of Aotearoa-New Zealand's volcanologists and volcano monitoring scientists. The eruption probabilities output by the BET_EF model for Taupō volcano's 17 recorded unrest episodes (between 1877 and 2019) were examined. We found time-inhomogeneity in the probabilities stemming from both the changes over time in the monitoring network around Taupō volcano and increasing level of past data (number of non-eruptive unrest episodes). We examine the former issue through the lens of the latest episodes, and the latter by re-running the episodes assuming knowledge of all 16 other episodes (calibration to 2021 data). The time variable monitoring network around Taupō volcano and parameter weights had a substantial impact on the estimated probabilities of magmatic unrest and eruption. We also note the need for improved monitoring and data processing at Taupō volcano, the existence of which would prompt updates and therefore refinements in the BET_EF model.
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    Mapping immunogenic epitopes of an adhesin-like protein from Methanobrevibacter ruminantium M1 and comparison of empirical data with in silico prediction methods.
    (Springer Nature Limited, 2022-06-21) Khanum S; Carbone V; Gupta SK; Yeung J; Shu D; Wilson T; Parlane NA; Altermann E; Estein SM; Janssen PH; Wedlock DN; Heiser A
    In silico prediction of epitopes is a potentially time-saving alternative to experimental epitope identification but is often subject to misidentification of epitopes and may not be useful for proteins from archaeal microorganisms. In this study, we mapped B- and T-cell epitopes of a model antigen from the methanogen Methanobrevibacter ruminantium M1, the Big_1 domain (AdLP-D1, amino acids 19-198) of an adhesin-like protein. A series of 17 overlapping 20-mer peptides was selected to cover the Big_1 domain. Peptide-specific antibodies were produced in mice and measured by ELISA, while an in vitro splenocyte re-stimulation assay determined specific T-cell responses. Overall, five peptides of the 17 peptides were shown to be major immunogenic epitopes of AdLP-D1. These immunogenic regions were examined for their localization in a homology-based model of AdLP-D1. Validated epitopes were found in the outside region of the protein, with loop like secondary structures reflecting their flexibility. The empirical data were compared with epitope predictions made by programmes based on a range of algorithms. In general, the epitopes identified by in silico predictions were not comparable to those determined empirically.