Dairy wintering systems in southern New Zealand : quantification and modelling of nutrient transfers and losses from contrasting wintering systems : a thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Soil Science at Massey University, Palmerston North, New Zealand

Traditional dairy wintering practice in the lower South Island of New Zealand has been to graze brassica crops in situ. This practice has been under increasing scrutiny from local Regional Councils due to the relatively high nitrogen (N) leaching losses from this component of the whole farm system. Alternative wintering options to reduce N leaching losses that are currently available to farmers (such as barns and permanent wintering pads) are high cost and involve a large capital investment. In this work a new wintering system (termed a ‘portable pad’) was developed for use on support blocks (which can be located many kilometres from the milking platform) as an interim measure for reducing N leaching losses that is low cost and low input. This system is designed as a mitigation strategy that is available for use immediately while research investigates more permanent solutions. This system is a hybrid of the traditional crop grazing system and an off-paddock system, where effluent is captured. It makes use of the advantages of each of the original systems utilising the low cost feed source of the brassica crops, grazed in situ, while also utilising the benefits of duration controlled grazing with its associated effluent capture and irrigation at low rates. The aim of the research was to generate whole system N leaching loss values for each of the three farm systems investigated (crop wintering, deep-litter wintering barn, and portable pad). Field and laboratory research was conducted to fill identified knowledge gaps such that system N loss values could be estimated. OVERSEER Nutrient Budget software tool was used in conjunction with measured and modelled (APSIM) data to simulate whole farm N leaching loss values for the three farm systems investigated. Nitrogen leaching losses from the portable pad and barn systems were between 5 and 26 % and between 13 and 26 % lower, respectively, than the crop wintering system

Community Surveillance of Omicron in Ontario: Wastewater-based Epidemiology Comes of Age

Wastewater-based surveillance of SARS-CoV-2 RNA has been implemented at building, neighbourhood, and city levels throughout the world. Implementation strategies and analysis methods differ, but they all aim to provide rapid and reliable information about community COVID-19 health states. A viable and sustainable SARS-CoV-2 surveillance network must not only provide reliable and timely information about COVID-19 trends, but also provide for scalability as well as accurate detection of known or unknown emerging variants. Emergence of the SARS-CoV-2 variant of concern Omicron in late Fall 2021 presented an excellent opportunity to benchmark individual and aggregated data outputs of the Ontario Wastewater Surveillance Initiative in Canada; this public health-integrated surveillance network monitors wastewaters from over 10 million people across major population centres of the province. We demonstrate that this coordinated approach provides excellent situational awareness, comparing favourably with traditional clinical surveillance measures. Thus, aggregated datasets compiled from multiple wastewater-based surveillance nodes can provide sufficient sensitivity (i.e., early indication of increasing and decreasing incidence of SARS-CoV-2) and specificity (i.e., allele frequency estimation of emerging variants) with which to make informed public health decisions at regional- and state-levels.Ontario Ministry of the Environment, Conservation and Parks|| Genome Canada and Ontario Genomics (OGI-209)||NSERC (ALLRP 555041-20 to C.O.)||Ontario Clean Water Agenc

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

The Effect of ACTN3 Gene Doping on Skeletal Muscle Performance

Loss of expression of ACTN3, due to homozygosity of the common null polymorphism (p.Arg577X), is underrepresented in elite sprint/power athletes and has been associated with reduced muscle mass and strength in humans and mice. To investigate ACTN3 gene dosage in performance and whether expression could enhance muscle force, we performed meta-analysis and expression studies. Our general meta-analysis using a Bayesian random effects model in elite sprint/power athlete cohorts demonstrated a consistent homozygous-group effect across studies (per allele OR = 1.4, 95% CI 1.3–1.6) but substantial heterogeneity in heterozygotes. In mouse muscle, rAAV-mediated gene transfer overexpressed and rescued α-actinin-3 expression. Contrary to expectation, in vivo “doping” of ACTN3 at low to moderate doses demonstrated an absence of any change in function. At high doses, ACTN3 is toxic and detrimental to force generation, to demonstrate gene doping with supposedly performance-enhancing isoforms of sarcomeric proteins can be detrimental for muscle function. Restoration of α-actinin-3 did not enhance muscle mass but highlighted the primary role of α-actinin-3 in modulating muscle metabolism with altered fatiguability. This is the first study to express a Z-disk protein in healthy skeletal muscle and measure the in vivo effect. The sensitive balance of the sarcomeric proteins and muscle function has relevant implications in areas of gene doping in performance and therapy for neuromuscular disease

Predicting species distributions for conservation decisions

Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of translators' between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes