Understanding wood formation - ScienceDirect

Dendrochronologia 20/1-2 (2002) 37±51 ã Urban & Fischer Verlag http://www.urbanfischer.de/journals/dendro

Understanding wood formation: gains to commercial forestry through treering research Geoffrey M. Downes1, Rupert Wimmer2 and Robert Evans3 1

CSIRO Forestry and Forest Products, Hobart, Tasmania, Australia University of Agricultural Sciences, Vienna, Austria 3 CSIRO Forestry and Forest Products, Clayton, Victoria, Australia 2

Summary Tree-ring research, in its varied manifestations, has made many contributions to our understanding of how trees grow and respond to a changing world. Environmental factors can vary from periodic and/or predictable changes in temperature, precipitation and anthropogenic stress factors, to occasional `one-off' events like fire, landslides or storms. The robustness of trees to change is indicated by their longevity. A major advantage of this longevity is that the pattern of response to change is recorded in their wood structure. The variation in wood properties over time is a net result of a complex web of interactions. This pattern of variation is a function of genotype x environment interactions on the whole tree as they impact on the factors controlling cambial growth. A combination of recent advances in measurement technology, cambial development and process modeling offers strong possibilities for making major advances in the understanding of wood formation. This understanding is important to both dendrochronology/dendroecology and commercial forestry. This paper examines some of the recent advances in technology and describes how they have been used to bridge the gap between these two disciplines, addressing areas of interest to both. Changes to the way research is being funded means that greater attention must be paid to the benefits obtained from it. To ensure that research opportunities are captured, there is a need to strengthen links between traditional tree-ring research and research in commercial forestry. Tree-ring research has a major contribution to make to both areas. Understanding the physiology of wood formation will lead to an improvement in the efficiency of our timber production industries and to a better interpretation of the tree-ring record. Keywords: Wood formation, wood properties, SilviScan, dendrometers, cambium, tree rings, process modelling, stem growth

Address for correspondence: Geoffrey M. Downes CSIRO Forestry and Forest Products, GPO Box 252-12, Hobart, Tasmania, 7001, Australia

1125-7865/02/20/1-2-37 $ 15.00/0

38 G. M. Downes et al.

Introduction Historically dendrochronology has been focused on non-commercial situations, aiding studies of climate change, population history and ecology among others. Those working in more commercial areas of forestry have tended to ignore or be unaware of the large body of information pertaining to wood formation within the dendrochronology literature. Two key figures dominate this contribution. Fritts (1976) presents a landmark contribution to the body of knowledge that is still unique in the insights it provides to the dynamics of tree growth. Similarly, the work of F. H. Schweingruber (Schweingruber 1987) has made a major contribution in the understanding of how factors such as site and environment are sources of variation in wood properties. Over the past two decades we have seen activities in these fields increasing. This trend is likely to continue with increasing pressure to improve the economics and sustainability of wood production. The following text will endeavour to present and describe several key, emerging technologies that offer considerable potential in furthering the work of Fritts, Schweingruber and others, to more fully understand the process of wood formation. It will attempt to demonstrate how these technologies are being used to clarify relationships between growth rate and wood property variation. These studies can, in turn, provide input into improved methods of modeling tree growth that will benefit both commercial forestry and dendrochronology. Over recent decades cambial physiology has been a field of study for relatively few researchers. This is strange as the economy of almost every nation on earth is impacted by its ability to produce timber. This paper is not an attempt to provide an overview of cambial research; this has been done ably by others (Savidge 1996). Rather it is an attempt to describe a sequence of research that the authors have followed over recent years, building on conceptual foundations laid by earlier researchers, and utilizing recent technological advances to provide a basis for relating temporal changes in site and climate to spatial changes recorded in wood structure. It is by no means a completed study. But it does provide a

Dendrochronologia 20/1-2 (2002)

bridge between two largely unconnected fields of endeavour: commercial forestry and dendrochronology. This is done in the belief that a large body of untapped information and understanding is available to commercial forestry within the dendrochronology literature and research community. Combining expertise will allow rapid advances in basic understanding with the benefit of improving the ability to predict wood properties and their variation, which is of importance to industry, as well as for a better interpretation of tree-ring series.

Technological advances help improve the knowledge base Rapidly advancing technologies offer many options to help improve our understanding of wood formation. Of central importance to commercial forestry is the ability to measure physical and chemical wood properties at high radial resolution. The SilviScan technology (Evans et al. 1995, 1996) is a move in this direction.

SilviScanTM X-ray densitometry has been a part of tree-ring research for several decades (e. g. Lenz et al. 1976, Schweingruber et al. 1978, 1993). The ability to obtain wood density information with high spatial resolution provides valuable insights into tree responses to environmental signals (Wimmer, Grabner 2000). SilviScanTM (SS) expands this potential by providing additional information on cell dimensions (radial and tangential diameter). These allow the environmental signals evident in density to be resolved into cell size or wall thickness changes (Downes et al. 1994). Further development has added x-ray diffraction methods to allow the measurement of microfibril angle (MFA) (Evans 1999), longitudinal stiffness (Modulus of Elasticity), cellulose crystallinity and crystallite width. The relatively low cost of these analyses makes it possible to analyse large numbers of samples rapidly. Figure 1 illustrates the nature of this information. The relationship between

Understanding wood formation: gains to commercial forestry through tree-ring research 39

Figure 1. The correspondence between variation in density (thin line), radial cell diameter (dashed line) and microfibril angle (thick line) within annual rings is evident within this Larch sample. The resolution of the MFA data is 200 microns compared to the 50 microns of the density data.

density and MFA in a fast-grown European larch tree (Figure 1) shows that MFA increases across the earlywood and drops into the latewood, while density is running the opposite course. SilviScan has been designed for speed of analysis in order to provide a system capable of measuring thousands of samples per year. This has resulted in some compromise with spatial resolution. Unlike the high-resolution density profiles available from optical densitometry of x-ray radiographs, SS uses direct densitometry. The need to combine this with automated image analysis has resulted in a system where density information is obtained from a 50 lm beam traveling perpendicular to the radial longitudinal surface. Image analysis provides information on ray and growth ring angle to allow the sample to be rotated, such that the beam travels parallel to growth rings maximizing the resolution of latewood density. However small deviations in the ring boundary across the sample width often result in the latewood

density being slightly under-estimated (Evans et al. 1996). This resolution can make it difficult to resolve growth rings from slow growing trees, which are often less than 0.25 mm apart (Figure 2). Similarly the system has been designed to utilize increment cores greater than 10 mm (preferably 12 mm) in diameter. Typical studies in dendrochronology utilize cores with 5 mm diameter. Depending on the quality small diameter cores can be used with SS but require careful preparation.

WoodtraxTM Increasingly technology is being made available to efficiently obtain chemical information from treerings. The Swedish developed ``Woodtraxº combines radiographic recording with an x-ray fluorescent spectrometer for elemental analysis. The instrument operates with a Cu (also Cr or Mo) diffraction x-ray tube as source and uses a flatbeam collimator



Figure 2. Samples where rings exhibit a large amount of curvature across the tangential width can be difficult to resolve using SilviScan.

and slit system for confinement of the beam (Lindeberg 2001, Bergsten et al. 2001). The slit system is 25 lm wide and 22 mm long and up to 20 increment cores with a maximum length of 200 mm can be processed in a batch. It is possible to generate trace element profiles (for elements with an atomic number ranging from ca. 19 and upward) on increment cores, non-destructively and at high spatial resolution. A second x-ray detector records the wood density, which allows direct comparisons between tree-ring density structure and trace elements. Applications such as the investigation of temporal changes in toxic heavy metals, nutrient status of trees or im-


pact of human activities can be addressed, but require a sound understanding of wood anatomical, chemical and ecological factors (Cutter, Guyette 1993).

Near Infra Red analysis Another technology being developed at CSIRO's, as well as other laboratories, is the adaptation of vibrational spectroscopic measurements absorbing in the near infrared (NIR) to the analysis of increment cores. The NIR region, which covers the range between 780±2500 nm, contains absorption


bands corresponding to overtones and combinations of fundamental C±H, O±H and N±H vibrations. With proper calibrations NIR has the capability to estimate a variety of wood chemical and physico-mechanical properties (Furumoto et al. 1999, Schimleck et al. 1998, 2000, 2001, Gierlinger et al. 2002).

Geographic Information Systems GIS systems are increasingly being utilized by commercial forest growers to map the various site characteristics across their resource. Forest enterprises are becoming interested in resource evaluation that includes information on tree growth rates and wood properties. These data will be linked to GIS systems allowing a better management of wood flows with tree logs better targeted for optimal utilization. For example forest growers in Australia, New Zealand, USA and Canada are utilizing extensive wood property analyses to characterize the timber resources they manage across multiple sites, species, genotypes and age classes. High-resolution profiles of wood property variation from pith to bark, and from base to apex, are being obtained to better understand how wood properties vary as a function of site and forest history. The information gained from these studies has significant potential to improve the understanding of wood formation. Sites range from foothills to sub-alpine regions, many of which regenerated following fire. The pioneering research of F. H. Schweingruber and co-workers has resulted in databases of wood density time-series covering wide areas in North America, most of Europe and transects across the Eurasian Northern boreal zone (Schweingruber 1988, Schweingruber et al. 1993, Schweingruber, Briffa 1996, Briffa et al. 1998). Likewise, an International Databank has been serving as a permanent repository for tree-ring data developed and contributed by scientists from around the world (Grissino-Meyer, Fritts 1997). While these data resources are mainly utilized for dendroclimatic purposes, they would also be of considerable value in wood quality assessment studies of forest resources. The ongoing development and utilization of GIS with tree-ring research will ultimately allow an

expanding information database to capture local work on tree-rings that could integrate into a more complete and global picture. Opportunities to link these kinds of studies will allow greater application and better use of research findings to improve timber production, reducing pressure on forests with high heritage value. A major need in the interpretation of these data is a more complete understanding of how climate, site and genotype interact in the formation of wood, in order to explain the variability recorded in the treering series and the pith-to-bark profiles of wood properties currently being produced.

The importance of understanding the physiology when looking at wood A better understanding of the physiology of wood formation has important ramifications for dendrochronology as well as commercial forestry. Innovative dendrochronological techniques have been heavily used in many studies to date historical events and sites, and provide information regarding global climate change (e. g. Cook et al. 1991, D'Arrigo et al. 1992, Ettl, Peterson 1995, Briffa et al. 1998, Eronen et al.1999, Briffa 2000). The result has been the development of an extensive network of chronologies extending back thousands of years (e. g. Zetterberg et al. 1996). Most of their benefit has been derived from the pattern of ring width variation and the inferences that can be made regarding the various climate patterns that can be related to them. By better understanding what drives the dynamics of cell production and development, and how this impacts on annual ring structure, it should be possible to gain much greater insight into past climates at a sub-annual resolution. One of the more intriguing questions that are commonly asked of dendrochronologists is the issue of growth rings versus annual rings. It is common for these two expressions to be equated. However, in reality the latter is best defined as a subset of the former. An annual ring is a growth ring, but a growth ring is not necessarily an annual ring. While this is true for many species from the tropical region (Worbes 1995) it is also evident in many of the currently existing Pinus radiata plantations. Annual rings can be difficult to define



Figure 3. Drought index, density and radial cell diameter for the period August 1986 to August 1988 at (a) breast height and (b) 15 metres. The peaks in the density and radial diameter traces can be attributed to the increase in drought index as shown by the dashed line. Drought index is provided at a daily time increments. Wood property data is shown at 50 lm radial increments.

when `false' rings are common. This typically occurs on sites subject to periodic, seasonal water deficits. Figure 3 shows the effect of a single rainfall event on wood density and cell diameter as a function of a major change in drought index. The release of the tree from a severely stressed condition by a 70 mm rainfall event in January 1987, resulted in a growth release and a latewood false ring. The same false ring is evident in wood sampled 15 m above the ground and is more resolved than at breast height. These features can be used as time markers to indicate the cambial position within years. Not infrequently false-ring formation can make annual ring definition difficult (see Figure 6). The major difficulty in interpreting these data is that of relating


temporal changes in climate and growth to spatial changes in sub-annual ring structure. An example of this is the confusion that exists over the relationship between growth rate and wood density.

Clarifying the relationship between growth rate and density One of the issues that has generated major confusion in the commercial forestry literature is the relationship between growth rate and density. There is a general belief that faster growth results in lower density and consequently faster grown trees will result in less dense timber of poorer quality. Genetic studies have consistently pointed to a negative genetic corre-


lation between growth rate (stem diameter) and wood density (Zobel and Jett 1995). Similarly many recent studies have associated numerous quantitative trait loci for various wood properties. The strength of these associations can vary between sites, indicating the need to understand the physiological link between genes and their expression in terms of wood variability. The literature has shown that the phenotypic relationships are tenuous at best and variable or absent at worst (Zobel, van Buijtenen 1989, Downes et al. 1997, Nyakuengama et al. 2002a, b). The confusion appears to have arisen from a poor understanding of the relationship between growth rate and wood density; specifically a variable definition of growth rate. Genetic correlations are the result of differences in physiological expression and ultimately need to be understood at this level. In general, rotations have become shorter as increases in growth rates have produced merchantable log classes in less time. The harvested logs contain higher proportions of lower-density juvenile wood, with its characteristic lower density and higher microfibril angle (Wang, Chiu 1988, Nyakuengama et al. 2002b). This has given rise to the strong perception in the forest products industry that faster growth, however it is achieved, is synonymous with poorer wood quality. Thus saw-millers have a preference for slower-grown older stands. In general this concern is valid. The natural pattern of variation of wood properties in the tree makes the wood produced in the lower regions of the stem, toward the end of the rotation the most valuable. Thus shortening rotation times will have a negative impact on the recovery of higher strength timber. However, it is not only the growth rate that has resulted in a drop in wood quality but also the shorter rotation that the faster growth allowed. Recently Wimmer, Downes (2002) endeavoured to clarify the relationship between growth rate and density utilizing spruce trees grown in Germany. In this study the changing strength of the correlation between ring width and density was investigated across the radius. Age effects were controlled by restricting the correlation to rings formed in the same year. Thus, as one moves from pith to bark the pattern of the changing relationship between ring width and

density is revealed. It was shown that the relationship changed over time and certain climatic patterns as well as forest operations may play a prominent role. A common mistake in comparing ring width ± density relationships is to average across the radius. Larson (1969) pointed out the role of the tree crown in wood formation: the development and structure of the tree crown is related with an inherent increase in latewood proportion. With age and stand closure, crowns of trees gradually recede upwards, resulting in tree-rings with a higher proportion of latewood (Zobel, Sprague 1998). In Wimmer, Downes (2002) the variable nature of this relationship became evident. In general there was a weak negative correlation with wider rings having lower density. However, not infrequently density was found to increase with ring width, and this was largely driven by increases in rainfall, typically late-summer rainfall. This relationship was also found in plantation grown Pinus radiata (Nyakuengama et al. 2002b). This raises the issue of annual growth pattern and its effect on the relationship. Downes et al. (2000) argued that growth pattern and not rate of growth was the main driver of variability in wood properties. This position was argued on the basis of dendrometer data, which provided an indicator of growth pattern over a year. Such dendrometers provide a useful template for relating temporal variation in growth to spatial change in wood properties. There is an increasing application of dendrometers to understanding the dynamics of stem growth.

Dendrometers and growth patterns The contribution of Fritts (1976) to the understanding of the physiology of wood formation cannot be over-stated. That this has not received more attention in commercial forestry is probably testimony to the degree to which the commercial study of wood formation lags behind that in dendrochronology. Fritts (1976) pioneered the application of high-resolution measurements of stem growth and their interpretation in terms of climate/environmental signals and its mediation in response to whole-tree physiological processes. These insights have provided valuable interpretative power to the various relationships


44 G. M. Downes et al. between growth and wood properties. The efforts of Fritts, Shashkin (1995) to then summarise decades of research into a mathematical processed-based computer model is invaluable (Fritts et al. 1999) and will provide an important foundation for the development of predictive models for commercial use into the future. These contributions will be discussed later. Automated dendrometer systems are becoming more common (Herzog et al. 1995, Downes et al. 1999a, b, Wimmer et al. 2002), and their value to commercial forestry better recognized (McLaughlin and Downing 1995). Improved methods for processing the dendrometer signal promise greater insights into the response of the cambial region to external and internal stimuli. Knowing the pattern of growth

over the year allows the effect of growth rate versus growth pattern to be explored. As indicated above, it is commonly understood that faster growth will result in low-density wood. This is true within limits. But to understand this fully we need to be careful in our definition of growth rate. Growth rate can, and has, been defined in terms of radial increment per day, week, month, year or years. However, these are very different measures of time, both qualitatively and quantitatively. Time units such as day and year embody within them complete cycles: diurnal and annual. The diurnal cycle of stem shrinkage and expansion has been well documented (Impens, Schalck 1965, Zweifel, Haesler 2000) and indicates a markedly changing suite of conditions that impact on cambial growth. Similarly annual cycles contain

Figure 4. Growth and wood property variation across a single annual ring of a droughted (a, c) and an irrigated (b, d) radiata pine. The density data (thick line) is expressed as a percentage of ring width (lower x-axis). The dendrometer data (thin line) is expressed on the upper x-axis on a time scale. In (c) and (d) the dendrometer data has been rotated 90° to illustrate the correspondence between slower growth and false ring formation.



markedly changing patterns of climate that also impact the overall physiology of the tree and the cambium in particular. On a daily basis the amount of growth produced (cells.day±1 or lm.day±1) varies in both rate and duration over the year (Downes et al. 1999a, b), regulated by hormonal flows. Recent work by Sundberg et al. (2000) indicates that auxin concentration decreases non-linearly from the cambial dividing zone across the enlarging zone into the wall-thickening zone. This concentration gradient would vary both daily and seasonally affecting the activity within each zone. It is highly probable that the rate of cell production also varies over a day, with some indication that growth and wood properties are more related to night-time conditions (Downes et al. 1999b; Richardson 1964). Similarly the increment put on over a year is not constant over time. In general the greatest proportion of the annual ring is formed during spring when water is less limiting and temperatures are moderate.

Summer and autumn growth are often affected by water deficits. In softwoods the switch from earlywood to latewood production is probably controlled by hormonal changes associated with the cessation of needle elongation (Richardson 1964, Larson 1969). This is probably closely related to the cessation of vertical shoot growth and winter bud formation. The average properties of the annual ring are thus more related to the relative proportions contributed by earlywood and latewood, rather than a direct rate of growth expressed as cells per day. Figure 4 illustrates this scenario using dendrometer data from an irrigated and droughted radiata pine study (Benson unpublished). Two differing scenarios are illustrated. In Figure 4(a) the majority of the annual ring is produced in spring, typical of the site which experiences summer drought. There is some resurgence of growth in autumn. This growth pattern shows the fastest rate of growth during spring. The pattern recorded in Fig-

Figure 5. A schematic representation of the factors driving increases in ring width and the expected effects on average ring density.


46 G. M. Downes et al. ure 4(b) is from an irrigated tree and exhibits a uniform growth rate over 10 months of the year. The rate of growth during spring is equal to, or slightly less than, that of the droughted tree. In Figures 4(c) and (d) the growth pattern recorded by the dendrometers has been expressed as a percentage of ring width and rotated 90 degrees. Thus the periods of slow growth are indicated by a more vertical slope and correspond closely with increases in density. In this context slower growth does equate to marked increases in density as cell division slows and cells spend less time enlarging and more time producing secondary walls (Horacek et al. 1999). It is this relationship that results in growth ring formation, both false and annual. It is evident that the relationship between annual growth rate and density will depend largely on the relative size of the increments produced at different times of the year. For example a site, which experiences a spring drought but has good growth over summer and autumn might be expected to yield a positive relationship between ring width and density. However it is more probable that most of the growth increment will be produced in spring (earlywood), thus resulting in a negative relationship between density and growth rate (ring width). Figure 5 endeavours to conceptualise the relationship. In hardwoods the situation is complicated by the effect of water stress/availability on vessel size and frequency, but in general we have shown in eucalypts that wood properties such as density and pulp yield are more related to the pattern of growth over the year than the actual size of the annual increment (Downes unpublished, Schimleck et al. 2000).

to the pith, the ring structure is regular and annual. Then an erratic pattern of growth emerges where it is impossible to distinguish annual from sub-annual rings. The portion from 85 to 125 mm from the pith contains rapid and marked changes in wood properties, and in the resultant ring structure annual versus false growth rings cannot be distinguished. It is only our additional knowledge of when the trees were planted that tells us the ring structure cannot be annual. These same features are evident in hardwoods such as eucalypts. Eucalyptus globulus and E. nitens both tend to grow when the conditions are right. Being evergreen, they are less influenced by loss of foliage over winter and the resultant bud burst in spring. Downes et al. (2000) and Wimmer et al. (2002) showed the relationship between daily growth rate and annual ring structure as measured by SilviScan 2. Increasing soil water deficit resulted in a slowing down of cambial growth and a consequent increase in density. This increase was explained by a reduction in vessel size and an increase in fibre wall thickness. An irrigated tree growing less than 100 meters away exhibited none of this variation in wood properties. Understanding the growth pattern allows us to date particular features within the annual ring and relate changes in wood properties to changes in the environment (Wimmer et al. 2002). The true test of our understanding lies in the ability to predict changes in ring structure as a function of climate and site, and then test these predictions against reality. Advances in both empirical and process-based modeling over recent years indicate this ability is not far away.

Climate effects on wood lead to deconvolving climate from wood records

Observations, statistics and processmodelling

Improving our understanding of these relationships will allow us to make better management decisions in commercial forests and increase the interpretative power from a tree-ring series in dendrochronology applications. A typical example of this is evident in Pinus radiata. Figure 6 shows a radial profile of density and radial cell diameter from an 18-year old P. radiata grown in eastern Victoria, Australia. Close

Many historians like to look at human history in categories. In classifying the past they talk about the agrarian age, the industrial age and now the information age. Many are predicting major changes in the near future as a result of the effects of technological advances. In many ways we can also classify the history of biology into ages. Biology is in essence the net effect of a complicated interaction of physics,



Figure 6. One of many 18 year old radiata pines on a site sensitive to changes in soil water, which led to the formation of multiple false rings per year, making the distinction of annual rings difficult. The lower 3 graphs are an expansion of a portion of the radius in the upper graph.

chemistry and information theory (genetic code). The complexity of living systems has made the classical reductionist approach to science difficult. Often, perhaps usually, all variables cannot be directly controlled simultaneously to allow the effect of changing a single variable to be determined by sim-

ple observation. Early biologists focused heavily on simple observation, for example the revolutionary work of Louis Pasteur and Francesco Redi to establish the law of biogenesis. Over the 1900's the rapid increase in statistical theory has brought about a statistical age where the effects of multiple variables


48 G. M. Downes et al. can be examined by determining the variance explained in the dependent variable by variance in independent variables simultaneously. These approaches can often be considered reductionist in as much as they endeavour to explain changes in one variable whilst keeping others constant. The various fields of dendrochronology have made significant contributions to this area in the development of methods for time-series analysis (Cook, Kairiukstis 1990). Recent advances in computing power, as well as the increasing power of statistical comparisons, allows the development of process-based predictive and simulation models. Typically what is decribed as a process model in reality utilizes many empirical relationships and is not purely process-based. Greater computing power allows us to express the conceptual understanding we have about a system in a mathematical form. Generally these models will have complex relationships embedded in them that are not testable using a pure statistical approach. Process-modelling has the advantage of allowing us to make testable predictions, and determining the extent to which our understanding is accurate. We can then use these models as decision-making tools to help us identify areas where knowledge or understanding is lacking. Similarly the ability to predict even a nominal proportion of the variance in a system may have considerable economic value. This does not negate the need for either simple observation or statistical approaches. Process-modelling just adds more opportunities to further the research by helping to identify areas where knowledge is inadequate. In forestry systems, most process-based modeling approaches are directed at predicting increases in stem growth only (Battaglia, Sands 1997, Dixon et al. 1978, Running, Coughlan 1988). These are commonly driven by photosynthetic sub-models, which provide the substance for stem growth. Increasing interest is turning now to predicting not only the volume of wood produced, but also its quality (e. g. KellomaÈki et al. 1999). TREERING represents the most sophisticated attempt to do this (Fritts et al. 1999). By combining TREERING with SilviScan we have a means of combining prediction with evaluation, as


SilviScan measures what TREERING predicts. However, considerably more work is needed to take this beginning and turn it into a useful commercial tool.

Conclusions: bringing together tree-ring research and commercial forestry Recent advances in technology offer great opportunities to understand the relationships between climate change and wood formation and variability. Technologies such as SilviScan, Woodtrax, NIR analysis and automated dendrometers, combined with process-modelling and GIS approaches, and understood within the context of hormonal and developmental studies of cambial regulation will need to be the focus of future research. It is in this integration of research activity that future advances will be made and applied for both commercial and environmental gain. The large amounts of information existing within the various tree-ring series can then be fully used to make many contributions to help commercial forestry understand the sources of variation within their forests. The increasing pressure on global forests, and the continuing trend towards developing sustainability in forest industries will require increases in conversion efficiency and productivity. This will need to be achieved by continuing the trend to maximize volume production, but utilizing better breeding silvicultural and harvesting practices to minimize degradation in wood quality and better match wood quality to product. Advances in computer processing power and the development of sophisticated statistical and process-based models will allow more information to be gained from existing data sets. The integration of results from specific sites into wider ranging GIS systems will provide greater opportunities for interpolating tree growth and wood formation responses spatially. However, global trends indicate an increasing pressure on the availability of government funds for basic research, and research funding in the future will increasingly become dependent on an ability to show an economic gain. It is funding pressures that offer the single largest threat to further advances.


Funding research in the future

References

In predicting the future it is common to look back over the past and then extrapolate forward into the future. This is analogous to driving on the freeway by looking in the rearview mirror. It works fine until you come to a bend in the road. Many economic and social commentators are predicting a `bend in the road', which will not be accommodated by predictions from past decades. The current pressures to do `more with less' will continue. However, the changing balance in many western countries will result in less government money being available for research funding. In highly-welfare dependent societies like Australia, Canada and increasingly the USA, Davidson and Rees-Moggs (1997) predict dramatic changes over the next 25 years, many of which are already occurring. Increases in welfare dependency owing to aging populations increase tax burdens that drive wealthy investors off-shore. This reduces job availability, further increasing the demands on government welfare, and causes major changes in the availability of government funds. Davidson and Rees-Moggs (1999) predict government taxation revenues to fall by 50±70 % by 2010±2015. While all future predictions are fraught with danger, the trends are already in place. This will result in a need for research to be increasingly commercially driven. Long-term fundamental research will become increasingly rare. However, there are some very real opportunities for tree-ring research in this. By establishing greater communication and data exchange across the global research community, the bringing together of complimentary data sets to develop more complete and detailed understanding has considerable potential.

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Acknowledgements Thanks to Laurie Schimleck and Carolyn Raymond, together with another reviewer for the many beneficial comments they made on the structure and content of the manuscript. Rupert Wimmer was supported through the APART program of the Austrian Academy of Science.


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