Nature has endowed New Zealand with unique geologic, climatic, and biotic conditions. Her volcanic cones and majestic Southern Alps and her verdant plains and rolling hills provide a landscape as rugged and beautiful as will be found anywhere. Her indigenous fauna and flora are often quite different from that of the rest of the world and consequently have been of widespread interest to biologists everywhere. Her geologic youth and structure and her island climate, in combination with the biological resources, have made a land which is ecologically on edge. These natural endowments along with the manner in which she has utilized her land, have given New Zealand some of the most spectacular and rapid erosion to be found.
It is quite evident that geologic and climatic conditions combine to give unusually high rates of natural erosion. Present topographic features indicate the past occurrence of large-scale flooding as well. Prior to the arrival of the Maori, it is very likely that most of the land mass of New Zealand below present bush lines was covered with indigenous bush or forest. Forest fires of a catastrophic nature undoubtedly occurred as a result of lightning, and volcanic eruptions. The exposed soils left by these catastrophes contributed to natural deterioration. While vast areas of forest cover were destroyed, they probably were healed by nature with forest or with grass or herbaceous cover. Further, it is probable that large areas in the mountains were, as they are now, subject to landslides and slipping due to earthquakes and excessive local rainfall. Again, the healing process was probably rapid in most of such exposed areas.
Artificial Neural Networks (ANN) as a tool offers opportunities for modeling the inherent complexity and uncertainty associated with socio-environmental systems. This study draws on New Zealand ski
fields (multiple locations) as socio- environmental systems while considering their perceived resilience to low
probability but potential high consequences catastrophic natural events (specifically earthquakes). We gathered
data at several ski fields using a mixed methodology including: geomorphic assessment, qualitative interviews,
and an adaptation of Ozesmi and Ozesmi’s (2003) multi-step fuzzy cognitive mapping (FCM) approach. The data
gathered from FCM are qualitatively condensed, and aggregated to three different participant social groups. The
social groups include ski fields users, ski industry workers, and ski field managers. Both quantitative and
qualitative indices are used to analyze social cognitive maps to identify critical nodes for ANN simulations. The
simulations experiment with auto-associative neural networks for developing adaptive preparation, response and
recovery strategies. Moreover, simulations attempt to identify key priorities for preparation, response, and
recovery for improving resilience to earthquakes in these complex and dynamic environments. The novel mixed
methodology is presented as a means of linking physical and social sciences in high complexity, high uncertainty
socio-environmental systems. Simulation results indicate that participants perceived that increases in Social
Preparation Action, Social Preparation Resources, Social Response Action and Social Response Resources have
a positive benefit in improving the resilience to earthquakes of ski fields’ stakeholders.
One of the great challenges facing human systems today is how to prepare for, manage, and adapt successfully to the profound and rapid changes wreaked by disasters. Wellington, New Zealand, is a capital city at significant risk of devastating earthquake and tsunami, potentially requiring mass evacuations with little or short notice. Subsequent hardship and suffering due to widespread property damage and infrastructure failure could cause large areas of the Wellington Region to become uninhabitable for weeks to months. Previous research has shown that positive health and well-being are associated with disaster-resilient outcomes. Preventing adverse outcomes before disaster strikes, through developing strengths-based skill sets in health-protective attitudes and behaviours, is increasingly advocated in disaster research, practise, and management. This study hypothesised that well-being constructs involving an affective heuristic play vital roles in pathways to resilience as proximal determinants of health-protective behaviours. Specifically, this study examined the importance of health-related quality of life and subjective well-being in motivating evacuation preparedness, measured in a community sample (n=695) drawn from the general adult population of Wellington’s isolated eastern suburbs. Using a quantitative epidemiological approach, the study measured the prevalence of key quality of life indicators (physical and mental health, emotional well-being or “Sense of Coherence”, spiritual well-being, social well-being, and life satisfaction) using validated psychometric scales; analysed the strengths of association between these indicators and the level of evacuation preparedness at categorical and continuous levels of measurement; and tested the predictive power of the model to explain the variance in evacuation preparedness activity. This is the first study known to examine multi-dimensional positive health and global well-being as resilient processes for engaging in evacuation preparedness behaviour. A cross-sectional study design and quantitative survey were used to collect self-report data on the study variables; a postal questionnaire was fielded between November 2008 and March 2009 to a sampling frame developed through multi-stage cluster randomisation. The survey response rate was 28.5%, yielding a margin of error of +/- 3.8% with 95% confidence and 80% statistical power to detect a true correlation coefficient of 0.11 or greater. In addition to the primary study variables, data were collected on demographic and ancillary variables relating to contextual factors in the physical environment (risk perception of physical and personal vulnerability to disaster) and the social environment (through the construct of self-determination), and other measures of disaster preparedness. These data are reserved for future analyses. Results of correlational and regression analyses for the primary study variables show that Wellingtonians are highly individualistic in how their well-being influences their preparedness, and a majority are taking inadequate action to build their resilience to future disaster from earthquake- or tsunami-triggered evacuation. At a population level, the conceptual multi-dimensional model of health-related quality of life and global well-being tested in this study shows a positive association with evacuation preparedness at statistically significant levels. However, it must be emphasised that the strength of this relationship is weak, accounting for only 5-7% of the variability in evacuation preparedness. No single dimension of health-related quality of life or well-being stands out as a strong predictor of preparedness. The strongest associations for preparedness are in a positive direction for spiritual well-being, emotional well-being, and life satisfaction; all involve a sense of existential meaningfulness. Spiritual well-being is the only quality of life variable making a statistically significant unique contribution to explaining the variance observed in the regression models. Physical health status is weakly associated with preparedness in a negative direction at a continuous level of measurement. No association was found at statistically significant levels for mental health status and social well-being. These findings indicate that engaging in evacuation preparedness is a very complex, holistic, yet individualised decision-making process, and likely involves highly subjective considerations for what is personally relevant. Gender is not a factor. Those 18-24 years of age are least likely to prepare and evacuation preparedness increases with age. Multidimensional health and global well-being are important constructs to consider in disaster resilience for both pre-event and post-event timeframes. This work indicates a need for promoting self-management of risk and building resilience by incorporating a sense of personal meaning and importance into preparedness actions, and for future research into further understanding preparedness motivations.
The purpose of this paper is to empirically investigate the effects of a major disaster on the management of human resources in the construction sector. It sets out to identify the construction skills challenges and the factors that affected skills availability following the 2010/2011 earthquakes in Christchurch. It is hoped that this study will provide insights for on-going reconstruction and future disaster response with respect to the problem of skills shortages. Design/methodology/approach A triangulation method was adopted. The quantitative method, namely, a questionnaire survey, was employed to provide a baseline description. Field observations and interviews were used as a follow-up to ascertain issues and potential shortages over time. Three focus groups in the form of research workshops were convened to gain further insight into the feedback and to investigate the validity and applicability of the research findings. Findings The earthquakes in Christchurch had compounded the pre-existing skills shortages in the country due to heightened demand from reconstruction. Skills shortages primarily existed in seismic assessment and design for land and structures, certain trades, project management and site supervision. The limited technical capability available nationally, shortage of temporary accommodation to house additional workers, time needed for trainees to become skilled workers, lack of information about reconstruction workloads and lack of operational capacity within construction organisations, were critical constraints to the resourcing of disaster recovery projects. Research limitations/implications The research findings contribute to the debate on skills issues in construction. The study provides evidence that contributes to an improved understanding of the industry’s skills vulnerability and emerging issues that would likely exist after a major disaster in a resource-limited country such as New Zealand. Practical implications From this research, decision makers and construction organisations can gain a clear direction for improving the construction capacity and capability for on-going reconstruction. Factors that affected the post-earthquake skills availability can be considered by decision makers and construction organisations in their workforce planning for future disaster events. The recommendations will assist them in addressing skills shortages for on-going reconstruction. Originality/value Although the study is country-specific, the findings show the nature and scale of skills challenges the construction industry is likely to face following a major disaster, and the potential issues that may compound skills shortages. It provides lessons for other disaster-prone countries where the resource pool is small and a large number of additional workers are needed to undertake reconstruction.
Globally, the maximum elevations at which treelines are observed to occur coincide with a 6.4 °C soil isotherm. However, when observed at finer scales, treelines display a considerable degree of spatial complexity in their patterns across the landscape and are often found occurring at lower elevations than expected relative to the global-scale pattern. There is still a
lack of understanding of how the abiotic environment imposes constraints on treeline patterns, the scales at which different effects are acting, and how these effects vary over large spatial extents. In this thesis, I examined abrupt Nothofagus treelines across seven degrees of
latitude in New Zealand in order to investigate two broad questions: (1) What is the nature and extent of spatial variability in Nothofagus treelines across the country? (2) How is this variation associated with abiotic variation at different spatial scales? A range of GIS, statistical, and atmospheric modelling methods were applied to address these two questions.
First, I characterised Nothofagus treeline patterns at a 15x15km scale across New Zealand using a set of seven, GIS-derived, quantitative metrics that describe different aspects of treeline position, shape, spatial configuration, and relationships with adjacent vegetation.
Multivariate clustering of these metrics revealed distinct treeline types that showed strong spatial aggregation across the country. This suggests a strong spatial structuring of the abiotic environment which, in turn, drives treeline patterns. About half of the multivariate treeline
metric variation was explained by patterns of climate, substrate, topographic and disturbance variability; on the whole, climatic and disturbance factors were most influential.
Second, I developed a conceptual model that describes how treeline elevation may
vary at different scales according to three categories of effects: thermal modifying effects, physiological stressors, and disturbance effects. I tested the relevance of this model for Nothofagus treelines by investigating treeline elevation variation at five nested scales (regional to local) using a hierarchical design based on nested river catchments. Hierarchical linear modelling revealed that the majority of the variation in treeline elevation resided at the broadest, regional scale, which was best explained by the thermal modifying effects of solar radiation, mountain mass, and differences in the potential for cold air ponding. Nonetheless, at finer scales, physiological and disturbance effects were important and acted to modify the regional trend at these scales. These results suggest that variation in abrupt treeline elevations
are due to both broad-scale temperature-based growth limitation processes and finer-scale stress- and disturbance-related effects on seedling establishment.
Third, I explored the applicability of a meso-scale atmospheric model, The Air
Pollution Model (TAPM), for generating 200 m resolution, hourly topoclimatic data for
temperature, incoming and outgoing radiation, relative humidity, and wind speeds. Initial assessments of TAPM outputs against data from two climate station locations over seven years showed that the model could generate predictions with a consistent level of accuracy for both sites, and which agreed with other evaluations in the literature. TAPM was then used to generate data at 28, 7x7 km Nothofagus treeline zones across New Zealand for January
(summer) and July (winter) 2002. Using mixed-effects linear models, I determined that both
site-level factors (mean growing season temperature, mountain mass, precipitation,
earthquake intensity) and local-level landform (slope and convexity) and topoclimatic factors (solar radiation, photoinhibition index, frost index, desiccation index) were influential in
explaining variation in treeline elevation within and among these sites. Treelines were
generally closer to their site-level maxima in regions with higher mean growing season
temperatures, larger mountains, and lower levels of precipitation. Within sites, higher
treelines were associated with higher solar radiation, and lower photoinhibition and
desiccation index values, in January, and lower desiccation index values in July. Higher treelines were also significantly associated with steeper, more convex landforms.
Overall, this thesis shows that investigating treelines across extensive areas at multiple study scales enables the development of a more comprehensive understanding of treeline variability and underlying environmental constraints. These results can be used to formulate new hypotheses regarding the mechanisms driving treeline formation and to guide the optimal choice of field sites at which to test these hypotheses.
