Knowledge of past climate variability is essential for understanding present and future climate trends. This study used Halocarpus biformis (pink pine) ring-width chronologies to investigate palaeotemperature history in Westland, New Zealand. The ensuing reconstruction is among the longest palaeoseries produced for New Zealand to date. It is in good agreement with other tree-ring-based records, and with instrumental (both local and hemispheric) data.
Thirteen pink pine chronologies were developed. Ring-width measurements were detrended using the Regional Curve Standardisation method to retain as much low-frequency variance as possible. Crossdating revealed the existence of a strong common signal among trees. Inter-site comparison indicated that a common control mechanism affected tree growth not only within sites, but also across sites.
To determine whether climate was the main factor that controlled the growth of pink pine in Westland, correlation and response function analyses were employed. Temperature, precipitation and the Southern Oscillation Index were tested for their relationship with tree growth. Mean monthly temperature was identified as the primary growth-limiting factor. Chronologies were positively correlated with temperature over an extended period (5-17 months), and climate response modelling showed that temperature explained 11-60% variance in the tree-ring data. The highest and most stable correlations occurred between tree growth and summer (January-March) temperatures.
Tree-ring data from the six sites that contained the strongest temperature signal were combined, and the Westland Regional Chronology (WRC) was developed. The WRC was then used to reconstruct January-March temperatures back to A.D. 1480. The calibration model explained 43% of the variance in temperature, and all calibration and verification tests were passed at high levels of significance. The reconstruction showed that temperatures in Westland have been following a positive trend over the last 520 years. The coolest 25-year period was 1542-1566, while temperatures reached their maximum in 1966-1990. Spectral analysis of the Westland palaeotemperature record revealed cycles at periods of about 3, 5-6, 11, 14, 22, 45 and 125 years.
This study also confirmed that climate response is species-dependent. A separate exercise, which compared two species from the same site, demonstrated that while pink pine's growth was mainly influenced by summer temperatures, Libocedrus bidwillii was affected by conditions at the beginning of the growing season. However, the temperature signal in Westland's Libocedrus bidwillii was insufficient to produce a reliable reconstruction. It might be because the climate signal in this species was obscured by disturbances, as was shown in the final section of this project. Frequent growth releases and suppressions implied that Libocedrus bidwillii integrated both major (Alpine Fault earthquakes) and minor (windthrow) disturbances in its ring widths. Pink pine, on the other hand, was not sensitive to disturbance, and was therefore a better indicator of palaeotemperatures in Westland.
This research has strengthened the New Zealand network of chronology sites, and confirmed that pink pine has great dendroclimatic value. The last 520 years of temperature fluctuations were reconstructed with a high degree of fidelity - the model developed in this thesis is currently the most accurate estimate of a temperature-growth relationship in the country.
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.
