Using greater Christchurch as a case study, this research seeks to understand the key drivers of residential choice of families with children who live in recently developed, low-density greenfield subdivisions. In particular, the research examines the role that transport-related implications play in families’ choice of residence and location. It also explores the lived experience of the quotidian travel of these households, and the intrinsic value of their time in the car. While the research is situated in one particular location, it is designed to gain an understanding of urban processes and residents’ experiences of these as applicable to broader settings. Concerns about the pernicious environmental, fiscal, and wellbeing effects of sprawling urban form have been growing over the past few decades, inciting many cities including Christchurch to start shifting planning policies to try and achieve greater intensification and a denser development pattern. The 2010/2011 Christchurch earthquake sequence and its destruction of thousands of homes however created huge pressure for housing development, the bulk of which is now occurring on greenfield sites on the peripheries of Christchurch City and its neighbouring towns. Drawing on the insights provided by a wide body of both qualitative and quantitative literature on residential choice, transport and urban form, and mobilities literature as a basis, this research is interested in the attraction of these growing neighbourhoods to families, and puts the focus firmly on the attitudes, values, motivations, decisions, and lived experience of those who live in the growing suburbs of Christchurch.
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.
As a global phenomenon, many cities are undergoing urban renewal to accommodate rapid growth in urban population. However, urban renewal can struggle to balance social, economic, and environmental outcomes, whereby economic outcomes are often primarily considered by developers. This has important implications for urban forests, which have previously been shown to be negatively affected by development activities. Urban forests serve the purpose of providing ecosystem services and thus are beneficial to human wellbeing. Better understanding the effect of urban renewal on city trees may help improve urban forest outcomes via effective management and policy strategies, thereby maximising ecosystem service provision and human wellbeing. Though the relationship between certain aspects of development and urban forests has received consideration in previous literature, little research has focused on how the complete property redevelopment cycle affects urban forest dynamics over time. This research provides an opportunity to gain a comprehensive understanding of the effect of residential property redevelopment on urban forest dynamics, at a range of spatial scales, in Christchurch, New Zealand following a series of major earthquakes which occurred in 2010 – 2011. One consequence of the earthquakes is the redevelopment of thousands of properties over a relatively short time-frame. The research quantifies changes in canopy cover city-wide, as well as, tree removal, retention, and planting on individual residential properties. Moreover, the research identifies the underlying reasons for these dynamics, by exploring the roles of socio-economic and demographic factors, the spatial relationships between trees and other infrastructure, and finally, the attitudes of residential property owners. To quantify the effect of property redevelopment on canopy cover change in Christchurch, this research delineated tree canopy cover city-wide in 2011 and again in 2015. An object-based image analysis (OBIA) technique was applied to aerial imagery and LiDAR data acquired at both time steps, in order to estimate city-wide canopy cover for 2011 and 2015. Changes in tree canopy cover between 2011 and 2015 were then spatially quantified. Tree canopy cover change was also calculated for all meshblocks (a relatively fine-scale geographic boundary) in Christchurch. The results show a relatively small magnitude of tree canopy cover loss, city-wide, from 10.8% to 10.3% between 2011 and 2015, but a statistically significant change in mean tree canopy cover across all the meshblocks. Tree canopy cover losses were more likely to occur in meshblocks containing properties that underwent a complete redevelopment cycle, but the loss was insensitive to the density of redevelopment within meshblocks. To explore property-scale individual tree dynamics, a mixed-methods approach was used, combining questionnaire data and remote sensing analysis. A mail-based questionnaire was delivered to residential properties to collect resident and household data; 450 residential properties (321 redeveloped, 129 non- redeveloped) returned valid questionnaires and were identified as analysis subjects. Subsequently, 2,422 tree removals and 4,544 tree retentions were identified within the 450 properties; this was done by manually delineating individual tree crowns, based on aerial imagery and LiDAR data, and visually comparing the presence or absence of these trees between 2011 and 2015. The tree removal rate on redeveloped properties (44.0%) was over three times greater than on non-redeveloped properties (13.5%) and the average canopy cover loss on redeveloped properties (52.2%) was significantly greater than on non-redeveloped properties (18.8%). A classification tree (CT) analysis was used to model individual tree dynamics (i.e. tree removal, tree retention) and candidate explanatory variables (i.e. resident and household, economic, land cover, and spatial variables). The results indicate that the model including land cover, spatial, and economic variables had the best predicting ability for individual tree dynamics (accuracy = 73.4%). Relatively small trees were more likely to be removed, while trees with large crowns were more likely to be retained. Trees were most likely to be removed from redeveloped properties with capital values lower than NZ$1,060,000 if they were within 1.4 m of the boundary of a redeveloped building. Conversely, trees were most likely to be retained if they were on a property that was not redeveloped. The analysis suggested that the resident and household factors included as potential explanatory variables did not influence tree removal or retention. To conduct a further exploration of the relationship between resident attitudes and actions towards trees on redeveloped versus non-redeveloped properties, this research also asked the landowners from the 450 properties that returned mail questionnaires to indicate their attitudes towards tree management (i.e. tree removal, tree retention, and tree planting) on their properties. The results show that residents from redeveloped properties were more likely to remove and/or plant trees, while residents from non- redeveloped properties were more likely to retain existing trees. A principal component analysis (PCA) was used to explore resident attitudes towards tree management. The results of the PCA show that residents identified ecosystem disservices (e.g. leaf litter, root damage to infrastructure) as common reasons for tree removal; however, they also noted ecosystem services as important reasons for both tree planting and tree retention on their properties. Moreover, the reasons for tree removal and tree planting varied based on whether residents’ property had been redeveloped. Most tree removal occurred on redeveloped properties because trees were in conflict with redevelopment, but occurred on non- redeveloped properties because of perceived poor tree health. Residents from redeveloped properties were more likely to plant trees due to being aesthetically pleasing or to replace trees removed during redevelopment. Overall, this research adds to, and complements, the existing literature on the effects of residential property redevelopment on urban forest dynamics. The findings of this research provide empirical support for developing specific legislation or policies about urban forest management during residential property redevelopment. The results also imply that urban foresters should enhance public education on the ecosystem services provided by urban forests and thus minimise the potential for tree removal when undertaking property redevelopment.
When disasters and crises, both man-made and natural, occur, resilient higher education institutions adapt in order to continue teaching and research. This may necessitate the closure of the whole institution, a building and/or other essential infrastructure. In disasters of large scale the impact can be felt for many years. There is an increasing recognition of the need for disaster planning to restructure educational institutions so that they become more resilient to challenges including natural disasters (Seville, Hawker, & Lyttle, 2012).The University of Canterbury (UC) was affected by seismic events that resulted in the closure of the University in September 2010 for 10 days and two weeks at the start of the 2011 academic year This case study research describes ways in which e-learning was deployed and developed by the University to continue and even to improve learning and teaching in the aftermath of a series of earthquakes in 2010 and 2011. A qualitative intrinsic embedded/nested single case study design was chosen for the study. The population was the management, support staff and educators at the University of Canterbury. Participants were recruited with purposive sampling using a snowball strategy where the early key participants were encouraged to recommend further participants. Four sources of data were identified: (1) documents such as policy, reports and guidelines; (2) emails from leaders of the colleges and academics; (3) communications from senior management team posted on the university website during and after the seismic activity of 2010 and 2011; and (4) semi-structured interviews of academics, support staff and members of senior management team. A series of inductive descriptive content analyses identified a number of themes in the data. The Technology Acceptance Model 2 (Venkatesh & Davis, 2000) and the Indicator of Resilience Model (Resilient Organisations, 2012) were used for additional analyses of each of the three cases. Within the University case, the cases of two contrasting Colleges were embedded to produce a total of three case studies describing e-learning from 2000 - 2014. One contrast was the extent of e-learning deployment at the colleges: The College of Education was a leader in the field, while the College of Business and Law had relatively little e-learning at the time of the first earthquake in September 2010. The following six themes emerged from the analyses: Communication about crises, IT infrastructure, Availability of e-learning technologies, Support in the use of e-learning technologies, Timing of crises in academic year and Strategic planning for e-learning. One of the findings confirmed earlier research that communication to members of an organisation and the general public about crises and the recovery from crises is important. The use of communication channels, which students were familiar with and already using, aided the dissemination of the information that UC would be using e-learning as one of the options to complete the academic year. It was also found that e-learning tools were invaluable during the crises and facilitated teaching and learning whilst freeing limited campus space for essential activities and that IT infrastructure was essential to e-learning. The range of e-learning tools and their deployment evolved over the years influenced by repeated crises and facilitated by the availability of centrally located support from the e-Learning support team for a limited set of tools, as well as more localised support and collaboration with colleagues. Furthermore, the reasons and/or rate of e-learning adoption in an educational institution during crises varied with the time of the academic year and the needs of the institution at the time. The duration of the crises also affected the adoption of e-learning. Finally, UC’s lack of an explicit e-learning strategy influenced the two colleges to develop college-specific e-learning plans and those College plans complemented the incorporation of e-learning for the first time in the University’s teaching and learning strategy in 2013. Twelve out of the 13 indicators of the Indicators of Resilience Model were found in the data collected for the study and could be explained using the model; it revealed that UC has become more resilient with e-learning in the aftermath of the seismic activities in 2010 and 2011. The interpretation of the results using TAM2 demonstrated that the adoption of technologies during crises aided in overcoming barriers to learning at the time of the crisis. The recommendations from this study are that in times of crises, educational institutions take advantage of Cloud computing to communicate with members of the institution and stakeholders. Also, that the architecture of a university’s IT infrastructure be made more resilient by increasing redundancy, backup and security, centralisation and Cloud computing. In addition, when under stress it is recommended that new tools are only introduced when they are essential.
The research is funded by Callaghan Innovation (grant number MAIN1901/PROP-69059-FELLOW-MAIN) and the Ministry of Transport New Zealand in partnership with Mainfreight Limited. Need – The freight industry is facing challenges related to climate change, including natural hazards and carbon emissions. These challenges impact the efficiency of freight networks, increase costs, and negatively affect delivery times. To address these challenges, freight logistics modelling should consider multiple variables, such as natural hazards, sustainability, and emission reduction strategies. Freight operations are complex, involving various factors that contribute to randomness, such as the volume of freight being transported, the location of customers, and truck routes. Conventional methods have limitations in simulating a large number of variables. Hence, there is a need to develop a method that can incorporate multiple variables and support freight sustainable development. Method - A minimal viable model (MVM) method was proposed to elicit tacit information from industrial clients for building a minimally sufficient simulation model at the early modelling stages. The discrete-event simulation (DES) method was applied using Arena® software to create simulation models for the Auckland and Christchurch corridor, including regional pick-up and delivery (PUD) models, Christchurch city delivery models, and linehaul models. Stochastic variables in freight operations such as consignment attributes, customer locations, and truck routes were incorporated in the simulation. The geographic information system (GIS) software ArcGIS Pro® was used to identify and analyse industrial data. The results obtained from the GIS software were applied to create DES models. Life cycle assessment (LCA) models were developed for both diesel and battery electric (BE) trucks to compare their life cycle greenhouse gas (GHG) emissions and total cost of ownership (TCO) and support GHG emissions reduction. The line-haul model also included natural hazards in several scenarios, and the simulation was used to forecast the stock level of Auckland and Christchurch depots in response to each corresponding scenario. Results – DES is a powerful technique that can be employed to simulate and evaluate freight operations that exhibit high levels of variability, such as regional pickup and delivery (PUD) and linehaul. Through DES, it becomes possible to analyse multiple factors within freight operations, including transportation modes, routes, scheduling, and processing times, thereby offering valuable insights into the performance, efficiency, and reliability of the system. In addition, GIS is a useful tool for analysing and visualizing spatial data in freight operations. This is exemplified by their ability to simulate the travelling salesman problem (TSP) and conduct cluster analysis. Consequently, the integration of GIS into DES modelling is essential for improving the accuracy and reliability of freight operations analysis. The outcomes of the simulation were utilised to evaluate the ecological impact of freight transport by performing emission calculations and generating low-carbon scenarios to identify approaches for reducing the carbon footprint. LCA models were developed based on simulation results. Results showed that battery-electric trucks (BE) produced more greenhouse gas (GHG) emissions in the cradle phase due to battery manufacturing but substantially less GHG emissions in the use phase because of New Zealand's mostly renewable energy sources. While the transition to BE could significantly reduce emissions, the financial aspect is not compelling, as the total cost of ownership (TCO) for the BE truck was about the same for ten years, despite a higher capital investment for the BE. Moreover, external incentives are necessary to justify a shift to BE trucks. By using simulation methods, the effectiveness of response plans for natural hazards can be evaluated, and the system's vulnerabilities can be identified and mitigated to minimize the risk of disruption. Simulation models can also be utilized to simulate adaptation plans to enhance the system's resilience to natural disasters. Novel contributions – The study employed a combination of DES and GIS methods to incorporate a large number of stochastic variables and driver’s decisions into freight logistics modelling. Various realistic operational scenarios were simulated, including customer clustering and PUD truck allocation. This showed that complex pickup and delivery routes with high daily variability can be represented using a model of roads and intersections. Geographic regions of high customer density, along with high daily variability could be represented by a two-tier architecture. The method could also identify delivery runs for a whole city, which has potential usefulness in market expansion to new territories. In addition, a model was developed to address carbon emissions and total cost of ownership of battery electric trucks. This showed that the transition was not straightforward because the economics were not compelling, and that policy interventions – a variety were suggested - could be necessary to encourage the transition to decarbonised freight transport. A model was developed to represent the effect of natural disasters – such as earthquake and climate change – on road travel and detour times in the line haul freight context for New Zealand. From this it was possible to predict the effects on stock levels for a variety of disruption scenarios (ferry interruption, road detours). Results indicated that some centres rather than others may face higher pressure and longer-term disturbance after the disaster subsided. Remedies including coastal shipping were modelled and shown to have the potential to limit the adverse effects. A philosophical contribution was the development of a methodology to adapt the agile method into the modelling process. This has the potential to improve the clarification of client objectives and the validity of the resulting model.
