The role of forest productivity in defining the sustainability of plantation forests in New Zealand

Forest Ecology and Management 122 (1999) 125±137

The role of forest productivity in de®ning the sustainability of plantation forests in New Zealand B. Richardson*, M.F. Skinner, G. West New Zealand Forest Research Institute Ltd, Private Bag 3020, Rotorua, New Zealand

Abstract New Zealand has signed an international agreement that commits it to report on progress towards sustainable forest management as measured by indicators grouped within seven criteria. This paper evaluates the role of forest productivity in de®ning the sustainability of plantation forests in New Zealand. A key factor dictating the extent of the plantation forest industry in New Zealand is pro®tability. Therefore, forest productivity is an important criterion of sustainability because of its important relationship with economics and pro®tability. Another important issue is whether plantations could be grown for an inde®nite number of rotations without adversely affecting the site's capacity for biomass production. Where management practices lead to reductions in productivity, some form of amelioration is required and, as long as this is economically viable the practice is still sustainable. Forest productivity is not a good indicator of soil quality because of the confounding effects of plantation management. While improved modeling techniques may help to overcome this problem, measurement of soil- or tree-based indicators may provide a more sensitive measurement of soil quality. For a given soil type, if the effect of management practices on the soil indicator and the effect of the soil indicator on forest productivity were known, then an assessment could be made of the impact of various management practices on productivity (or other sustainability criteria). This would allow the establishment of management guidelines, constraints, and ameliorative requirements necessary to maintain or enhance soil quality. # 1999 Elsevier Science B.V. All rights reserved. Keywords: Montreal process; Forest productivity; Soil quality; Pinus radiata; New Zealand

1. Introduction The New Zealand forestry sector is committed to practising sustainable forest management, and the Resource Management Act (RMA) (1991) ensures that forest management practices do not degrade on or off-site environmental values. At an international level, there have been a number of agreements relating to the sustainable management of forests, driven by

the prospect of certi®cation of products that are derived from `sustainably managed' forests (Raison and Khanna, 1995). In February 1995, New Zealand became a signatory to the `Santiago Declaration'. This agreement endorsed the `Montreal Process' (Anon, 1995) (a working group representing 10 countries), and commits New Zealand to report on progress towards sustainable forest management as measured by indicators grouped within seven criteria listed below:

*Corresponding author. Tel.: +64-7-347-5899; fax: +64-7-3479380; e-mail: [email protected]

1. Conservation of biological diversity (diversity of ecosystems, between species, and genetic diversity within species).

0378-1127/99/$ ± see front matter # 1999 Elsevier Science B.V. All rights reserved. PII: S 0 3 7 8 - 1 1 2 7 ( 9 9 ) 0 0 0 3 7 - 7

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2. Maintenance of productive capacity of forest ecosystems. 3. Maintenance of forest ecosystem health and vitality. 4. Conservation and maintenance of soil and water resources. 5. Maintenance of forest contribution to global carbon cycles. 6. Maintenance and enhancement of long-term multiple socio-economic benefits to meet the needs of societies. 7. Legal, institutional, and economic framework for forest conservation and sustainable management.

 evaluate the concept of sustainability in relation to plantation forests;  discuss the functional relationship between productivity and site quality, in the context of maintaining the productivity of New Zealand's plantation forests; and  evaluate the utility of productivity measurements within the Montreal Process Criteria and Indicators framework;

A number of indicators were identi®ed for each of these criteria. Indicators are measures of an aspect of a criterion, namely ``quantitative or qualitative variables which when observed periodically demonstrate trends'' (Anon, 1995). Taken together, these criteria and indicators implicitly provide a de®nition of sustainable forest management that acknowledges the importance and interdependence of many related factors. Montreal Process indicators are required to assess sustainability at a national scale. However, at the forest management unit (coupe or compartment) level not all soil will be treated sustainably, for example on ¯at country in Kaingaroa forest, 7% of the plantation area is occupied by skid sites and trails from logging operations (Murphy, 1983). Although early results suggest these areas can sometimes be rehabilitated (Hall, 1995), the cost-bene®t of rehabilitation practices varies greatly according to site factors. It is, therefore, desirable to minimise the area of land treated in a non-sustainable manner. The speci®c criteria used for assessing sustainability may vary between land units, such as native forest vs. plantation forest, that is to say not all Criteria will have equal importance. With the relatively long rotation ages in forestry, consideration must also be given to the time scale, namely the point in time when indicators are measured. Normal ecosystem processes are likely to result in considerable ¯uctuations in certain indicators as a forest progresses from the seedling stage to mature trees prior to harvest (Cole and Van Miegroet, 1989; Skinner, 1978). The purpose of this paper is to evaluate whether forest productivity is a useful measure or indicator of sustainability criteria. Speci®c objectives are to:

Many countries have signed various international agreements, e.g. Montreal and Helsinki Processes (Anon, 1995; Helsinki Process, 1994; FAO, 1997) which de®ne criteria for sustainable forest management and indicators for assessing sustainability. At this political level, there is little disagreement in respect of the de®nition of the elements contributing to sustainability. However, it is clear that not all forests can be judged by the same standard because different forests serve different functions. New Zealand's plantation forests, consisting predominantly of radiata pine (Pinus radiata D. Don), are managed with the objective of maximising ®nancial returns (as opposed to yield), whereas the indigenous forests are generally managed for conservation, to maintain the indigenous biodiversity, for recreation, and other non-timber values. This has been explicitly acknowledged in New Zealand following the NZ Forest Accord 1991, an agreement between conservation groups and all major plantation growers and users to (NZFOA, 1997):

2. Applicability of the criteria to plantations

 define areas unsuitable for plantation forestry;  acknowledge the existing natural forest should be maintained;  recognise commercial plantation forestry as essential;  ensure any use of wood from indigenous forest is on a sustainable, value-added basis; and  ensure new plantation forests will not disturb areas of natural indigenous vegetation. While this agreement does not focus on sustainable management, it clearly recognises the commercial focus of plantation forests. Without pro®tability there would be few, if any, forest plantations in New

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Zealand regardless of other issues relating to sustainability (e.g. biodiversity, carbon cycles, etc). With unfavourable economics, commercial plantation forestry would only survive if tax payers were prepared to pay subsidies, possibly on the basis that plantation forestry has inherent value to the community other than the production of wood or ®bre. This would be unlikely on a large scale given the prevailing freemarket philosophy. Thus, an economic indicator relating to pro®tability is clearly the critical determinant for plantation forests in New Zealand, and forest productivity is obviously an important component of pro®tability. While economics are a dominant factor in determining the area of New Zealand land in plantation forests, other aspects of sustainability cannot be ignored. One key sustainability issue with respect to P. radiata forestry (or with any other intensively managed crop species), is whether it could be grown for an inde®nite number of rotations without adversely affecting the site's capacity for net primary production (Criterion 2). There should be no irreversible detrimental effects to the soil, and the land should be maintained in a state whereby it remains in a suitable condition for alternative land uses by future generations (Criteria 4 and 6). Similarly, forest operations should not decrease water or air quality. Current legislation (e.g. the Resource Management Act (RMA), 1991) and industry standards (e.g. Codes of Practice) place constraints on management practices. While plantation forests may well provide a positive contribution to other Montreal Process Criteria to be reported on at a national level (e.g. biodiversity), it is questionable whether plantations should be managed to meet de®ned targets relating to these objectives. The requirement for sustainability does not mean that plantation management practices that have a negative impact on aspects of sustainability are no longer options. However, if such practices are used, provision must be made for ameliorating their impacts, for instance amelioration of skid trails by cultivation and fertiliser application. In an economic context, this requires a pro®table ®nancial return from wood production which is balanced against inputs necessary to maintain economic yields and to protect site quality and environmental standards. If the costs of maintaining site quality and environmental protection are projected to continually increase in relation to

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®nancial returns from timber or ®bre, it is likely that plantation forestry may not be sustainable. In other words, one measure of sustainability is related to the management intensity (or cost) necessary to sustain a pro®table level of production (Ford, 1983). This essentially economic de®nition of sustainability demands an understanding of the off-site impacts, the biology of the system and consideration of the time scale over which assessments are to be made. Biology is important because the impacts of forest operations on a site, and resulting effects on productivity, must be known so that appropriate ameliorative treatments can be de®ned and accounted for in the economic analysis. With the large time scale in forestry, it is also important that practices that damage a site in ways that are not easily reversible are identi®ed and prevented, because, by the time these effects become apparent in terms of yield reductions or decreased pro®tability, it may be too late. Another advantage of including costs for management inputs and amelioration is that it inherently accounts for the proposition that high inputs of fertiliser and pesticides are not sustainable, in the long term, due to increasing scarcity of resources required for their manufacture. 2.1. Relationship of productivity to criteria and indicators of sustainability Forest productivity has been identi®ed as a criterion of sustainability. In its own right, it is useful as a measure of timber production that can be offset against harvesting rates, i.e. the system is sustainable as long as production rates equal or exceed harvesting rates (Criterion 2). However, it also has probable links to, and is therefore a potential indicator for, other criteria. The relationship between productivity and pro®tability has already been mentioned. The productive capacity of a healthy ecosystem is maintained through the activities of soil organisms that contribute to the development of soil structure, decomposition of organic matter, and nutrient mineralisation and transformation (Shaw et al., 1991). A minimum level of soil microbial diversity is required to maintain nutrient turnover dynamics, for example nitrogen and carbon mineralisation (Alexander, 1976). Therefore, it seems probable that a healthy functioning ecosystem is also productive and that links should be observed between productivity and ecosystem health, biodiversity, and

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soil characteristics. The important issue of the relationship of site quality, the inherent capacity of the site to produce biomass as determined by soil and climate (Dyck and Skinner, 1990), to productivity is directly addressed by Criterion 4. There is also a direct relationship between production and the contribution of plantations to carbon cycles (Criterion 5) and to socioeconomic bene®ts (Criterion 6). 3. Is productivity a useful indicator of soil sustainability? Forest productivity can be de®ned as the rate at which trees are growing on a site. It is appealing to use measures of productivity as an indicator of sustainability because productivity is relatively easily measured and estimates of national productivity are already collated by the New Zealand Forest Owners Association and the Ministry of Forestry (NZFOA, 1997). Productivity is most directly linked with Montreal Process Criteria 2 and 4, but also has relevance to other Criteria because of its important relationships with biodiversity, ecosystem health, soil properties, carbon budgets, and socio-economic bene®ts. 3.1. Productivity and site quality The relatively simple concept of monitoring productivity changes over time or successive rotations

to indicate sustainability of the soil resource depends on a predictable relationship between a measure of soil sustainability (e.g. site quality or soil fertility) and productivity. Any site has an inherent capacity to support forest growth that is set by abiotic factors such as soil fertility and climate and this de®nes site quality (Dyck and Skinner, 1990). However, the realised forest productivity from a site is also affected by other factors (e.g. wild®re, disease) and especially by management practices (e.g. stocking, fertiliser, weed control, establishment techniques, silvicultural management, species genotype) (Fig. 1). Management cannot affect the prevailing climatic conditions but can signi®cantly alter the microclimate around individual trees (Menzies and Chavasse, 1982). Site quality can also be affected by management practices that have a lasting effect on soil properties, as for instance P application, soil compaction, and drainage. Poor quality sites can have high productivity with appropriate management inputs, even though inherent productivity is low. Good site quality leads to high productivity with low management inputs. Management strategies, and choice of crop species and genotype are usually in¯uenced or constrained by soil type, and climatic factors but decisions are ultimately dependent on cost-bene®t analyses. The dependence of forest productivity on management practices and genotype as well as site quality means that productivity can be sustained or enhanced

Fig. 1. The relationship between crop productivity, site quality, and management practices (after Dyck and Cole (1990)).

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even if soil quality declines (Burger, 1994). Therefore, forest productivity is not a good indicator of soil sustainability unless the contribution of management to productivity can be accounted for (Morris and Miller, 1994). There is a large database (over 10 000 plots dating back to the 1950s) of P. radiata productivity measurements taken from permanent sample plot(s) (PSPs) located throughout the 1.5million-hectare plantation forest estate in New Zealand. A signi®cant proportion of the forests are moving into second or third rotations, so an attempt should be made to assess productivity trends over time and to account for variable management practices, climatic and genetic factors using appropriate modelling techniques. With problems in using productivity as an indicator of soil sustainability, as discussed above, there is also a need to ®nd alternatives, such as direct (e.g. physical and chemical soil properties) or indirect measures (e.g. tree foliar nutrients) of soil attributes or processes. Productive forests are supported by ecosystems with the following characteristics:  good water-holding capacity;  adequate fertility;  good aeration and drainage to permit root proliferation and, consequently, plant uptake of water and nutrients;  organic matter and soil organisms necessary for decomposition; and  maintenance of structure and symbioses (Carmen, 1975; Powers, 1989; Shaw et al., 1991). It follows that any management practice producing a deterioration in physical, chemical or biological properties will reduce soil sustainability. However, the significance of change in these indicators for a particular ecosystem cannot be easily interpreted unless their relationship is known to important ecosystem processes (Smith and Raison, 1995), and ultimately productivity. Understanding these relationships would enable predictions to be made on the effect of management practices on long-term productivity (Fig. 2). It must be emphasised that all soil properties are interactive with each other and with vegetation (Bormann and Likens, 1979) and that indicators of soil sustainability will, therefore, have to be considered in relation to the soil as a physical, chemical and biological (macro- and micro-) medium.

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Fig. 2. Appropriate soil-based indicators must be defined that are sensitive to management practices and that can be related to productivity.

4. Use of existing productivity data Assessing growth trends over time could enable a test of the hypothesis that productivity over successive rotations has declined. This in itself does not directly allow conclusions about sustainability, unless the factors causing changes in productivity are identi®ed and, if appropriate, the costs of amelioration or alternative practices are incorporated into the evaluation. For example, previously noted occurrences of secondrotation decline in P. radiata productivity (Stone and Will, 1965; Keeves, 1966) have led to modi®ed management practices that have actually resulted in increased productivity (e.g. see Will, 1984; Boardman, 1988; Squire et al., 1991). On a world-wide scale, there has been no evidence of serious long-term productivity problems in plantation forests (e.g. see Evans, 1984a; Dyck and Cole, 1990; Evans, 1990; Long, 1997; Morris and Miller, 1994; Evans, 1996), but Evans (1990) cautions that existing data provide little basis for con®dent statement as to sustainability of plantation forests. This suggests the need for (i) developing better methods or models to account for variable management practices or climatic conditions, and (ii) determining the relationship between productivity and key soil indicators that relate to processes controlling productivity. These indicators may have to fall below a threshold before productivity is impacted (Knight and Will, 1970; Will and Knight, 1968). It has been stated that a decline in forest productivity over successive rotations would not necessarily mean that plantation forestry is non-sustainable, it

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could simply re¯ect fewer management inputs. However, if a decline were to be demonstrated in New Zealand it would be cause for concern, given the expectation of both improved management practices and tree genetics over the past 20 years or more. Indeed, if forest productivity has not improved over previous rotations there may be cause to suggest that improvements in tree genetics and management practices are merely offsetting declining site productivity, as was argued by Burger (1994) in relation to American agriculture. 4.1. Indirect measures of productivity While actual productivity (biomass) is the ultimate indicator of a tree's response to the environment in which it is growing, productivity varies with management practices. For this reason, there have been attempts to classify sites according to their quality, a measure that is to a certain degree independent of management. Various systems of quality, yield class, or site index provide measures of productivity that are accurate enough for management but are a crude index for comparing growth between rotations (Evans, 1984a). Site index (height of dominant trees at a speci®c age (20 years in New Zealand) is the most commonly accepted index of site quality and potential productivity in New Zealand and elsewhere (Tesch, 1981; Hunter and Gibson, 1984; Eyles, 1986). One advantage of site index is that height growth is not as sensitive as diameter growth to many management treatments (e.g. weed control or fertiliser application) (West et al., 1982; Hunter et al., 1985; Richardson et al., 1993), at least when measured over the ®rst 5±10 years after planting. Despite its widespread use, there are a number of drawbacks with site index (J. Grace, personal communication): 1. at very low stockings, height growth of the largest trees per ha is not independent of stocking; 2. for a given site index, the basal area growth varies around the country and on farm sites; 3. site index will change with improved radiata pine breeds and possibly with changes in CO2 and temperature (climate change); 4. site index is not a predictive measure in itself, i.e. it cannot be used to predict whether management practices will impact productivity in the near- or long-term; and

5. there is no quantitative link between site index and sustainability. For these reasons, site index is clearly not an ideal indicator of sustainable production capacity. Its relative insensitivity to management practices compared with basal area or volume explains its widespread use as a measure of site quality. However, even if an indirect measure of productivity was used, ultimately it would have to be related to and validated against an actual direct measure of wood production such as basal area or volume. Measures of height have been shown to be much less sensitive than direct measures of productivity in comparisons between first- and second-rotation stands of P. radiata in New South Wales. 4.2. Direct measures of productivity The most common direct measures of productivity used by foresters and researchers are: basal area, volume, and biomass (Evans, 1984a). In terms of sustainable production capacity, biomass and volume are of most interest but are also the most dif®cult to measure. Basal area is most easily measured and is highly correlated with yield. There are two aspects to measurements of productivity. The yield or rate of growth up to a point in time (e.g. mean annual increment, MAI) or various asymptotes of performance (e.g. site basal area potential) (Fight et al., 1995). These measures relate to the carrying capacity of the site and the rate at which this asymptote is reached (the biotic potential as de®ned by Burger, 1994). While the use of direct measures of productivity as indicators of sustainability is appealing, they suffer from many of the same problems as indirect measures and from the dependence of productivity on both, site quality and management practices. Four possible factors which could lead to a change in productivity between rotations are: 1. 2. 3. 4.

climate changes; genetic differences; site changes due to growing plantations; and biological and silvicultural differences (e.g. fertiliser application, weed control, stocking level, pruning/thinning regimes) (Evans, 1984b).

Modelling approaches have been suggested that might help to account for these sources of variation.

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Snowdon (personal communication) has proposed a technique for using stand growth as an indicator of sustainability of site resources. This is based on the hypothesis that stands respond to silvicultural treatments in two ways (Snowdon and Waring, 1984). A Type-1 response results from treatments that have little or no permanent effect on site resources or soil characteristics and leads to parallel growth trends between treated and untreated stands, that is to say the rate of stand development is altered, but not the carrying capacity; Type-2 responses are characterised by changes in site resources (or site quality) and a divergence of growth curves of treated and untreated stands. In this latter situation, both the rate of growth and the biomass carrying capacity of the site are changed. If tree growth is used as an indicator of site productivity or an index of sustainability of site resources, Type-1 responses must be eliminated. State-space models (Garcia, 1994) offer one possible means for achieving this. These models are based on a set of stochastic differential equations for the statevariables top height, basal area, and stems per hectare. Future state values are a function of the `state-space' characterised at the beginning point in time. Therefore, if assessed at the same growth stage (e.g. similar volume or basal area), stand growth from successive rotations would be similar if site conditions had not changed. However, for this approach to be successful, `all' state variables must be included in the analysis; otherwise variance associated with these variables will be allocated to `error'. If the error is large, it will probably mask any small productivity trends between rotations. Inclusion of environmental variables into growth models may also help to minimise the error term. A number of other modelling approaches are possible. For example, a state-space model could be ®tted to carefully selected (to minimise management variation) datasets for each rotation and coef®cients compared. Alternatively, an approach similar to the incorporation of a genetic gain growth-rate multiplier could be investigated. In this approach, the base model's coef®cients are not re-estimated. Instead, a `growth-rate multiplier' term is introduced into the base model, isolated, then solved for and quanti®ed using a dataset of particular interest (e.g. different rotation datasets). The value of the multiplier relative to that obtained from the base model (assumed to be

131

unity, or 1) re¯ects the change in time-scale required to achieve similar shifts in state-space commensurate with the base model. A ®nal method is to determine the relationship between environmental variables and growth by plotting the residuals (errors) from ®tting a growth model against environmental variables. For any of these approaches to be useful, the variation in productivity due to changes in climate or management practices over successive rotations must be less than the change in productivity due to altered site quality. It has already been mentioned that productivity measurements on P. radiata have been used as an indicator of declining site quality (Stone and Will, 1965; Keeves, 1966). If the errors associated with these measurements could be reduced, forest productivity would clearly be a more sensitive indicator of sustainable practices. However, measures of productivity may only identify changes in site quality after a threshold value is exceeded impacted (Knight and Will, 1970; Will and Knight, 1968) which reemphasises the importance of understanding the relationship between productivity and key soil indicators. 5. Soil- and tree-based indicators of soil sustainability 5.1. Identification of indicators 5.1.1. Multiple regression A number of researchers have used multiple regression analysis to relate soil and climatic variables (indicators) to some measure of forest productivity, commonly site index. While useful empirical models can be derived in this manner, the relationships should also be explainable in biological terms, if they are to have practical value. The success of these approaches, in terms of accounting for variation in productivity between sites, has been mixed. Gale et al. (1991) identi®ed the following three problems with this method: 1. multicollinearity between soil variables; 2. failure to incorporate soil-property interactions and small sampling range for soil variables; and 3. problems relating to sampling area. The in¯uence of environmental variables on P. radiata growth has been reviewed previously

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a useful function in that they help to explain variation in data that might otherwise mask effects on sustainability. Growth also varies with soil variables that can be in¯uenced by management (Table 1).

(Raupach, 1967; Lavery, 1986; Grey, 1989). A wide range of variables have been identi®ed as in¯uencing P. radiata (Table 1) and other species (e.g. see Allison et al., 1994; Lortz et al., 1994). The inclusion of climatic and some site variables (e.g. soil depth, soil group) in various types of growth models is useful for accounting for site differences (including climate change), especially in environments where growth is primarily limited by a single environmental factor (McLeod and Running, 1988; Wang et al., 1991). While these variables have marginal relevance to sustainability, as they cannot be realistically managed, they serve

5.2. Consideration of soil processes Raison and Khanna (1995) listed the following processes that can contribute to losses in soil fertility:  nutrient loss due to biomass harvesting, burning, soil erosion, leaching and gaseous losses;

Table 1 Summary of fourteen Pinus radiata soil site studies, showing variables used in growth prediction equations (after Wells, unpublished data) Source Study scale Dependent variable: Site index Volume Basal area Independent variable: Rainfall Altitude Soil Soil phosphorus Soil nitrogen Soil cations Soil calcium Soil water Effective soil depth Soil texture Soil organic matter Soil group Temperature Model R2 a

1a 2b regional

3c

4d

*

*

*

*

*

*

*

*

*

*

*

* *

*

*

* 0.66

*

*

*

* * *

7g

8h

9i

*

*

10 j

*

11 k

*

12 l

13 m

14 n

*

*

*

* * * * *

*

* *

*

* *

*

*

* * *

*

*

*

* 0.67

Czarnowski et al., 1971 Jackson and Gifford, 1974 c Hunter and Gibson, 1984 d Schlatter and Gerding, 1984 e Grey, 1989 f Ballard, 1971 g Truman et al., 1983 h Turvey et al., 1986 i Turner and Holmes, 1985 j Ryan, 1986 k Smethurst and Nambiar, 1990 l Louw, 1991 m Benson et al., 1992 n Wells, unpublished data o Model R2 was 0.77 on pumice sites and 0.65 on loam sites. b

6f local

*

*

*

0.58

5e

0.7

0.88

0.65

0.5

0.33

0.77

0.91

* * * * 0.77 o

B. Richardson et al. / Forest Ecology and Management 122 (1999) 125±137

 organic matter loss ± due to physical displacement (windrowing, raking), fire or accelerated soil respiration;  surface soil loss due to erosion or windrowing;  soil disturbance profile mixing, compaction and puddling;  lowered rates of N-fixation by leguminous understorey plants, caused by altered species composition or abundance following disturbance; and  change in hydrology and levels of the water table. Not all of these variables will be important on all sites, with some sites having great sensitivity to some factors but not others (Table 1). It is unlikely that a small number of generic indicators could be applied over the national estate, which is a major weakness of regression or other modelling approaches in the absence of some form of site strati®cation. 5.2.1. Tree-based indicators Tree-based indicators may overcome some of the problems associated with de®ning key soil indicators. Tree foliar nutrients are sometimes related to the `availability' of soil nutrients, in which case the tree becomes the `bio-assay' of the prevailing soil conditions (Smith et al., 1997). To be effective, the forest manager needs to have a sampling strategy and a set of nutrient criteria in place against which to make judgements on tree performance over time (i.e. the entire rotation) to determine if preventative ameliorative action is required. In other words a detailed picture of the ongoing nutrient health of the crop is needed against which to make decisions on management options. Given the complexity of soil interactions that may be dictating a particular foliar nutrient scenario, the use of the crop as a `bio-assay' must be approached with some caution. For example, low nutrient concentrations may result from conditions of waterlogging; ameliorative action by applying fertiliser nutrients would have to be in conjunction with improved drainage. Rotation-end measurements (last year before harvest) assessing de®ned soil- and tree-based indicators may offer a method for assessing the status of soils and crops from rotation to rotation, that is long-term detection of soil changes in relation to crop attributes.

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6. Benchmarks and a monitoring framework Forest productivity is easily measured and is potentially both, an important criterion and an indicator of sustainability. However, unless growth modelling techniques can be improved to account for variable management practices, the large amounts of productivity data already in databases are of questionable value in relation to determining sustainability. An improved system of growth monitoring may provide a framework for monitoring sustainability in the future. An important element of any new productivity monitoring plots would be to control management and plant factors so that measurements of tree height, stand volume or stand basal area will provide a reliable index of site productivity and change. Morris and Miller (1994) identi®ed three conditions that must be met to provide acceptable evidence of long-term changes in productivity: 1. Differences in tree growth must be attributable to differences in soil conditions rather than differences in management practices, genetics or climate. 2. Growth results must be available for a sufficient duration of time so that the influence of ephemeral differences in initial site conditions has diminished and the capacity of the site to support tree growth is stressed. 3. There must be adequate experimental control. Adlard et al. (1984) noted that normally measured stand variables may indicate that there is a decline (or increase) in productivity over successive rotations, but not the reasons causing it. They described a strategy for developing four levels of `productivity sample plots', with different types of variables being measured at the various levels. The four levels of plot intensity were de®ned as: 1. Conventional continuous forest inventory (PSPs); re-establish plots at same locations after harvest. 2. Soil and plant monitoring on a sub-sample of PSPs; re-establish plots after harvest. 3. Biomass sampling on a small number of destructive sample plots. 4. Ecosystem analysis on small catchment areas on key sites.

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To a certain degree, most of the elements of the strategy outlined by Adlard et al. (1984) are already present in New Zealand. There is a comprehensive network of PSPs, although these are not necessarily always re-established at the same location in successive rotations as recommended by Adlard et al. Similarly, existing PSPs do not have a standard design (stocking, genotype, and management practices) so it is not easy to make comparisons in the presence of these potentially confounding factors. There has been a signi®cant amount of biomass sampling on a wide range of experiments (Madgwick, 1994) and there are already a number of major studies on at the catchment level (e.g. Beets and Brownlie, 1987). The major de®ciency is at Level 2, site productivity monitoring. While there has been intensive measurement of site variables for speci®c studies, there is no current programme that routinely monitors site variables as well as productivity throughout the forest estate. Sampling at this level is essential to provide a database for testing hypotheses regarding factors in¯uencing soil processes or attributes, and their relationship to productivity. However, at present there is still uncertainty as to which variables should be monitored on different site types, and when and how frequently they should be measured. Experiments focusing on de®ning key soil variables and their relationship to productivity should be a priority in association with any new sustainability monitoring network. While soil or tree-based indicators and their relationship to productivity, or other aspects of sustainability, could be determined, dif®culties arise in de®ning benchmarks against which these indicators should be assessed. Furthermore, it is clearly not practical to advocate that detailed measurements should be taken on each management unit given that some potential indicators of sustainability are dif®cult to obtain and that different indicators are likely to be important in different areas. A more logical approach is to develop general relationships between management practices, soil- or tree-based indicators, and productivity (or other attributes of interest) at casestudy sites (Fig. 2). This information could be used to de®ne management guidelines, constraints, and ameliorative requirements necessary to maintain productivity and could form the basis of a Code of Practice. The adoption and adherence to the Code could form the basis for reporting at a national level.

7. Conclusions  Forest productivity is a critical Criterion of sustainability for New Zealand's plantation forests because of its important relationship with economics and profitability.  Management can override site quality effects. Low quality sites can be highly productive with inputs such as mechanical site preparation, fertiliser application, and the adoption of faster growing genotypes. Therefore, productivity is not a good indicator of sustainability unless the effects of these and other management practices are included in the analysis.  Modelling techniques are suggested that may help to account for effects of management practices on productivity. If this could be achieved, productivity could be related to changes in soil quality.  Measurement of soil- or tree-based indicators of soil quality may provide a more sensitive measurement of sustainability. For a given soil type, if the effect of management on the soil indicator, and the effect of the soil indicator on forest productivity were known, then an assessment of the impact of various management practices on productivity (or other sustainability Criteria) could be made. This would allow the establishment of management guidelines, constraints, and ameliorative requirements necessary to maintain productivity. References Adlard, P.G., Johnson, J.A., Evans, J., 1984. A strategy for detecting productivity change in tropical plantations. In: Grey, D.C., Schonau, A.P.G., Schutz, C.J. (Eds.), Proceedings, IUFRO Symposium On Site and Productivity of Fast Growing Plantations. Pretoria and Pietermaritzburg, South Africa, 30 April±11 May, 1984. ISBN 0 621 08513 8. pp. 857±869. Alexander, M., 1976. Introduction to Soil Microbiology, second edn., John Wiley & Sons, New York. Allison, S.M., Proe, M.F., Matthews, K.B., 1994. The prediction and distribution of general yield classes of Sitka spruce in Scotland by empirical analysis of site factors using a geographical information system. Can. J. For. Res. 24, 2166± 2171. Anon, 1995. Criteria and Indicators for the Conservation and Sustainable Management of Temperate and Boreal Forests ± The Montreal Process. Canadian Forest Service, Natural Resources Canada, Hull, Quebec, Canada K1A 1G5. pp. 27.

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