Quantitative expression and examination of possible differences in dynamics hrrowth patterns between plants of different ontogenetic state as suggested previously by Borchert ( 1 976), Borchert and Tomlinson ( 1 984) and others (Tomlinson, 1 978; Atkinson, 1 992; Kelly, 1 994; Day and Gould, 1 997; McGowran, 1 998) has been the main goal of this chapter. In addition, response to temperature allowed a preliminary estimate to be made of a temperature optimal for hastening the progress of phase change.
Other plant growth studies rarely examined the modelled growth in such detail as that used in this study. This was due to a number of differences in modelling approach, including the omission of growth phenology, the method used for
measuring tree growth, or due to long-term growth examinations where phenological information would compromise the feasibility of modelling. Commonly,
experimental growth data in most studies concentrated on re-construction of plant growth by fitting growth function in order to calculate relative growth rates (Richards, 1 959; Causton, 1 99 1 ; 1 994; Magnussen, 1 995) . This enabled these authors to examine growth against a common relative time, as opposed to real time sequences that were used in this study.
Alternatively, analyses of growth dynamics were carried out by other authors under arbitrarily set conditions that also enabled the examination of growth functions under common relative time. For example, although Baltunis and Greenwood ( 1 999) conducted statistical analyses similar to those in this study, they used arbitrarily defined points of growth evaluation, such as growth initiation set to the point of 20 mm of shoot length. Consequently, this obscured the real time sequences of shoot growth. Moreover, growth data were often fitted from an arbitrarily defined time zero (Baltunis and Greenwood, 1 999), or using rel ative time (Karlsson and Heins,
1 994), instead of capturing real time sequences and, thus, shoot phenology. In this respect, direct comparison of the current study with other growth modelling studies is
difficult. This is in addition to the use of two-dimensional parameters for whole crowns of shoots in comparison to reports of single shoot growth (e.g. Karlsson and Heins, 1 994; B altunis and Greenwood, 1 999). Moreover, in these studies growth was not examined in relation to phase change. Although developmental processes such as flowering (Karlsson and Heins, 1 994) have been studied by growth analysis, reports of growth analysis with respect to phase change have not appeared in the l iterature. Borchert ( 1 976) and Pearson et al. ( 1 994) noted this inadequacy and a poor
understanding of phase change itself as result.
Examining the growth of the plants in the three developmental states with respect to the position of point of inflection, i.e. point of highest relative growth rate, the growth model for plantlets was approaching almost exact symmetry. The growth of j uvenile plants approached the point of inflection earlier than did plantiets, but stil l relatively c lose to the middle point of growth. O n the other hand, adult plants reached maximal growth rate significantly earlier than both j uvenile plants and plantlets (Table 4. 1 ; Table 4. 1 1 ). This was likely to be due to a high degree of shoot growth synchronisation. This conclusion was also be supported by the initial Growth Lag Period analyses (Chapter 3, Table 3 .4), showing high synchronisation between adult tree repl ications. High synchronisation of shoots growth was correlated previously with the adult state by Borchert and Tomlinson ( 1 984) and Borchert ( 1 972, 1 973, 1 975, 1 983), while j uveniles showed asynchronous shoot growth initiation (Borchert and Tomlinson, 1 984). However, the similarities in growth rates for topological size between plants in the juvenile and adult states were somewhat surprising. This is in view of a general acceptance that slower growth rates (reduced vigour) are associated with the adult state (Corderso et al., 1 985; Hackett, 1 985; Westwood, 1 987; Greenwood, 1 995), rather than associated with physiological ageing or changes in growth phenology.
A number of explanations for these results can be considered. For example, growth rate evaluation from one growth period may not necessarily be indicative of seasonal or long-term growth rate. However, if additional growth information is considered, such as the short GLP for rej uvenated plantlets (Chapter 3 , Table 3 .4) and the tendency for multiple growth flushes as observed in the 24/26 and 32/24°C
temperature regimes, then a seasonally-adjusted growth rate for plantlets would be 1 63
even higher. Moreover, Causton ( 1 99 1 ; 1 994) examined a number of studies of relative growth rates, and reported that the effect of experimental factors on relative growth rate was generally not statistically significant. The highly statistically significant differences detected for relative growth rates, particularly for topological size between plants of different state were remarkable. Snowball ( 1 989) and
Snowball et a1. ( 1 994a,b) who investigated phase change in relation to plant size (i.e. height) noted that hypotheses that assumed a slower growth rate in the adult phase were often established intuitively. In this respect, even in forestry, where tree size and growth modelling can be considered to be well established, Madgwick ( 1 994) disputed the merits of tree size biometrics in many, if not most, studies. Considering this, and the results of the current study, it is suggested that a loss of 'vigour' defined as plant maximum relative growth rate (Magnussen, 1 995) in the adult state
(Borchert, 1 976; Hackett, 1 985) is not correlated with phase change. Rather, the decline in relative growth rate in adult plants is a result of the overall long-tenn decline in the number of flushes or the length of each growth period. Borchert and Tomlinson ( 1 984) have made a similar suggestion. Consequently, in the long-term examination of growth carried out by other authors, it is not possible to distinguish between the effects of physiological ageing and of maturation on plant growth rate.
Such uncertainty about the effect on plant growth associated with either with maturation and/or physiological ageing stil l exists ( Peer and Greenwood, 200 1 ). It is suggested that the use of the intrinsic growth rate coefficient in ontogenetic studies may be more appropriate than the use of relative growth rate. This is due to the fact that in growth studies the mathematically time dependent relative growth rates are commonly analysed in a manner that effectivel y eliminates real time sequences (Richards, 1 959; M. Kimberley, pers. comm.). This factor could lead to the situation in which relative growth rates do not show statistically significant effects of experimental factors (Causton, 1 99 1 ; 1 994). This may be because relative growth rates from different growth stages are compared or calculated from long-tenn growth data that combine growth periods with non-growth periods. Therefore, reported lower relative growth rates associated with maturation in long-tenn studies, such as that of Menzies and Klomp ( 1 988), should be considered as seasonal growth increment rather than growth rate, because it combines information from a number of f,lJ·owth flushes (M. Kimberley pers. comm.).
With respect to plant complexity, the growth modelling results indicated that topological parameters contain information about tree structure, and thus should be able to distinguish quantitatively between developmental states or their strategies for building crown complexity. Of particular importance was the result that the
underlying growth function for the complexity parameter in the j uvenile plants was different from that for the p lantlets and adult plants, which fol lowed a general sigmoid shape. In addition, there were differences between plantlets and adult plants in growth rates for topological size and complexity. These results suggest that the three topological parameters indeed accommodated different architectural
information that may have the ability to distinguish between the juvenile state, plantlets and adult state. Consequently, detailed analyses of tree architecture using the Metrosideros Model were warranted. These are described later (Chapter 5 ). By focusing on modular growth expression (Room et al., 1 994), such as meristem pool size and its complexity, rather than on measuring growth in metric units, a new concept of correlation between plant size-complexity and ontogenetic process was presented. Based on these results and literature reports ( Snowball, 1 994b;
Greenwood, 1 995; Sachs, 1 999), it would appear that it is not only the distance (topological or metric) from the root system examined by Snowball ( 1 989) that is instrumental in the attainment of phase ehange. Importantly, a particular balance of meristem distribution (eomplexity) and their distance (size) from the root of the plant may be the determining factors of phase change.
Moreover, it is hypothesised that the spatial dynamics of growth in crown meristems may be instrumental in both the determination of phase change, and the l ater
determination of particular meristems to reproductive growth in the adult plant. Such a hypo'thesis bridges the gap between the two otherwise separate developmental events of phase change and the reproductive determination of the apical meristem. This approach is similar to a hypothesis proposed recently by Sachs ( 1 999) that also takes into account the distance of meristems from the root (equivalent to centrifugal topological distance) and the cumulative memory of the number of nodes produced by the apex. Despite the similarities between these hypotheses, Sachs ( 1 999) considered architectural complexity only indirectly. As pointed out earlier, plant complexity was disregarded in the literature owing to the non-existence of suitable
biometric methods (Pearcy and Vallanderes, 2000). In this respect, the successfully tested Metrosideros Model and its parameters in growth analysis, as described in this chapter, presents a new and useful experimental tool.