The Eastern Humps and Leader faults, situated in the Mount Stewart Range in North Canterbury, are two of the ≥17 faults which ruptured during the 2016 MW7.8 Kaikōura Earthquake. The earthquake produced complex, intersecting ground ruptures of these faults and the co-seismic uplift of the Mount Stewart Range. This thesis aims to determine how these two faults accommodated deformation during the 2016 earthquake and how they interact with each other and with pre-existing geological structures. In addition, it aims to establish the most likely subsurface geometry of the fault complex across the Mount Stewart Range, and to investigate the paleoseismic history of the Leader Fault. The Eastern Humps Fault strikes ~240° and dips 80° to 60° to the northwest and accommodated right- lateral – reverse-slip, with up to 4 m horizontal and 2 m vertical displacement in the 2016 earthquake. The strike of the Leader Fault varies from ~155 to ~300°, and dips ~30 to ~80° to the west/northwest, and mainly accommodated left-lateral – reverse-slip of up to 3.5 m horizontal and 3.5 m vertical slip in the 2016 earthquake. On both the Eastern Humps and Leader faults the slip is variable along strike, with areas of low total displacement and areas where horizontal and vertical displacement are negatively correlated. Fault traces with low total displacement reflect the presence of off-fault (distributed) displacement which is not being captured with field measurements. The negative correlation of horizontal and vertical displacement likely indicates a degree of slip partitioning during the 2016 earthquake on both the Eastern Humps and Leader faults. The Eastern Humps and Leader faults have a complex, interdependent relationship with the local bedrock geology. The Humps Fault appears to be a primary driver of ongoing folding and deformation of the local Mendip Syncline and folding of the Mount Stewart Range, which probably began prior to, or synchronous with, initial rupture of The Humps Fault. The Leader Fault appears to use existing lithological weaknesses in the Cretaceous-Cenozoic bedrock stratigraphy to rupture to the surface. This largely accounts for the strong variability on the strike and dip of the Leader Fault, as the geometry of the surface ruptures tend to reflect the strike and dip of the geological strata which it is rupturing through. The Leader Fault may also accommodate some degree of flexural slip in the Cenozoic cover sequence of the Mendip Syncline, contributing to the ongoing growth of the fold. The similarity between topography and uplift profiles from the 2016 earthquake suggest that growth of the Mount Stewart Range has been primarily driven by multiple (>500) discrete earthquakes that rupture The Humps and Leader faults. The spatial distribution of surface displacements across the Mount Stewart Range is more symmetrical than would be expected if uplift is driven primarily by The Humps and Leader faults alone. Elastic dislocation forward models were used to model potential sub-surface geometries and the resulting patterns of deformation compared to photogrammetry-derived surface displacements. Results show a slight preference for models with a steeply southeast-dipping blind fault, coincident with a zone of seismicity at depth, as a ‘backthrust’ to The Humps and Leader faults. This inferred Mount Stewart Fault accommodated contractional strain during the 2016 earthquake and contributes to the ongoing uplift of the Mount Stewart Range with a component of folding. Right-lateral and reverse shear stress change on the Hope Fault was also modelled using Coulomb 3.3 software to examine whether slip on The Humps and Leader faults could transfer enough stress onto the Hope Fault to trigger through-going rupture. Results indicate that during the 2016 earthquake right-lateral shear and reverse stress only increased on the Hope Fault in small areas to the west of the Leader Fault, and similar ruptures would be unlikely to trigger eastward propagating rupture unless the Hope Fault was close to failure prior to the earthquake. Paleoseismic trenches were excavated on the Leader Fault at four locations from 2018 to 2020, revealing near surface (< 4m depth) contractional deformation of Holocene stratigraphy. Three of the trench locations uncovered clear evidence for rupture of the Leader Fault prior to 2016, with fault displacement of near surface stratigraphy being greater than displacement recorded during the 2016 earthquake. Radiocarbon dating of in-situ organic material from two trenches indicate a date of the penultimate earthquake on the Leader Fault within the past 1000 years. This date is consistent with The Humps and Leader faults having ruptured simultaneously in the past, and with multi-fault ruptures involving The Humps, Leader, Hundalee and Stone Jug faults having occurred prior to the 2016 Kaikōura earthquake. Overall, the results contribute to an improved understanding of the Kaikōura earthquake and highlight the importance of detailed structural and paleoseismic investigations in determining controls on earthquake ‘complexity’.
From 2010, Canterbury, a province of Aotearoa New Zealand, experienced three major disaster events. This study considers the socio-ecological impacts on cross-sectoral suicide prevention agencies and their service users of the 2010 – 2016 Canterbury earthquake sequence, the 2019 Christchurch mosque attacks and the COVID-19 pandemic in Canterbury. This study found the prolonged stress caused by these events contributed to a rise in suicide risk factors including anxiety, fear, trauma, distress, alcohol misuse, relationship breakdown, childhood adversity, economic loss and deprivation. The prolonged negative comment by the media on wellbeing in Canterbury was also unhelpful and affected morale. The legacy of these impacts was a rise in referrals to mental health services that has not diminished. This adversity in the socio-ecological system also produced post-traumatic growth, allowing Cantabrians to acquire resilience and help-seeking abilities to support them psychologically through the COVID-19 pandemic. Supporting parental and teacher responses, intergenerational support and targeted public health campaigns, as well as Māori family-centred programmes, strengthened wellbeing. The rise in suicide risk led to the question of what services were required and being delivered in Canterbury and how to enable effective cross-sectoral suicide prevention in Canterbury, deemed essential in all international and national suicide prevention strategies. Components from both the World Health Organisation Suicide Prevention Framework (WHO, 2012; WHO 2021) and the Collective Impact model (Hanleybrown et al., 2012) were considered by participants. The effectiveness of dynamic leadership and the essential conditions of resourcing a supporting agency were found as were the importance of processes that supported equity, lived experience and the partnership of Māori and non-Māori stakeholders. Cross-sectoral suicide prevention was found to enhance the wellbeing of participants, hastening learning, supporting innovation and raising awareness across sectors which might lower stigma. Effective communication was essential in all areas of cross-sectoral suicide prevention and clear action plans enabled measurement of progress. Identified components were combined to create a Collective Impact Suicide Prevention framework that strengthens suicide prevention implementation and can be applied at a local, regional and national level. This study contributes to cross-sectoral suicide prevention planning by considering the socio- ecological, policy and practice mitigations required to lower suicide risk and to increase wellbeing and post-traumatic growth, post-disaster. This study also adds to the growing awareness of the contribution that social work can provide to suicide prevention and conceptualises an alternative governance framework and practice and policy suggestions to support effective cross-sectoral suicide prevention.
INTRODUCTION: Connections between environmental factors and mental health issues have been postulated in many different countries around the world. Previously undertaken research has shown many possible connections between these fields, especially in relation to air quality and extreme weather events. However, research on this subject is lacking in New Zealand, which is difficult to analyse as an overall nation due to its many micro-climates and regional differences.OBJECTIVES: The aim of this study and subsequent analysis is to explore the associations between environmental factors and poor mental health outcomes in New Zealand by region and predict the number of people with mental health-related illnesses corresponding to the environmental influence.METHODS: Data are collected from various public-available sources, e.g., Stats NZ and Coronial services of New Zealand, which comprised four environmental factors of our interest and two mental health indicators data ranging from 2016 up until 2020. The four environmental factors are air pollution, earthquakes, rainfall and temperature. Two mental health indicators include the number of people seen by District Health Boards (DHBs) for mental health reasons and the statistics on suicide deaths. The initial analysis is carried out on which regions were most affected by the chosen environmental factors. Further analysis using Auto-Regressive Integrated Moving Average(ARIMA) creates a model based on time series of environmental data to generate estimation for the next two years and mental health projected from the ridge regression.RESULTS: In our initial analysis, the environmental data was graphed along with mental health outcomes in regional charts to identify possible associations. Different regions of New Zealand demonstrate quite different relationships between the environmental data and mental health outcomes. The result of later analysis predicts that the suicide rate and DHB mental health visits may increase in Wellington, drop-in Hawke's Bay and slightly increase in Canterbury for the year 2021 and 2022 with different environmental factors considered.CONCLUSION: It is evident that the relationship between environmental and mental health factors is regional and not national due to the many micro-climates that exist around the nation. However, it was observed that not all factors displayed a good relationship between the regions. We conclude that our hypotheses were partially correct, in that increased air pollution was found to correlate to increased mental health-related DHB visits. Rainfall was also highly correlated to some mental health outcomes. Higher levels of rainfall reduced DHB visits and suicide rates in some areas of the country.
