National Academies Press: OpenBook

Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies (1986)

Chapter: 19. Optimizing Timber Yields in New Brunswick Forests

« Previous: 18. Restoring Derelict Lands in Great Britain
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 275
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 276
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 277
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 278
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 279
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 280
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 281
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 282
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 283
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 284
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 285
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 286
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 287
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 288
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 289
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 290
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 291
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 292
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 293
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 294
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 295
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 296
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 297
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 298
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 299
Suggested Citation:"19. Optimizing Timber Yields in New Brunswick Forests." National Research Council. 1986. Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies. Washington, DC: The National Academies Press. doi: 10.17226/645.
×
Page 300

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

19 Optimizing Timber Yields in New Brunswick Forests Management of commercially important species to increase yields is usually a local matter, independent of conditions and management actions undertaken elsewhere. That is especially true in forestry, in which indi- vidual trees are stationary, long-lived, and easily countable. Nevertheless, plot-by-plot management can create long-term supply problems on a larger scale. These larger-scale effects are the most important ones that influence the vitality of economic activity based on exploitation of the resource. This case study illustrates an attempt to link local decisions with regional ones where the valued ecosystem component (wood) is readily identified and the processes producing wood are well known. The major uncertainties are associated with changes in scale, and they require a balancing of scientific and social issues. 275

Case Study THOM A. ERDLE, Forest Management Branch, New Brunswick Department of Natural Resources, Fredericton, Canada GORDON L. BASKERVILLE, Faculty of Forestry, University of New Brunswick, Fredericton, Canada INTRODUCTION Silviculture and wood technology are highly developed, and the factors that influence wood production rates are well known, despite the very long cycle of the crop. Like many other areas, New Brunswick depends heavily on industrial forestry. However, the forest base probably cannot continue indefinitely to supply the quantity and quality of wood required by industry without a large and expensive effort to develop the forest resources. Recognition of this need by government and industry forestry decision-makers has resulted in a strong commitment to carry out the necessary development, which entails legislative changes in forest ad- ministration, changes in the allocation of raw material to industrial wood consumers, and intensified action aimed at making the forest biologically more productive (Bird, 19801. Increasing the productivity of the forest requires special consideration, because it includes direct intervention in the development of a natural system. Tools for direct biological intervention in forest development include harvesting, protection, and silviculture; and the use of those tools requires explicit decisions on how much, where, and when to implement them. Their implementation initiates a biological response that alters forest development and production of wood, and the response must be forecast to permit the design of useful intervention strategies. This is all made difficult by disparities of scale, in both time and space, between the stand level at which the actions are taken and the forest level at which the response must be assessed. Stands, considered here as small homogeneous communities of trees (10-50 hectares), collectively constitute a forest. A forest can be enor- mously complex, encompassing many thousands of stands and many hundreds of thousands of hectares. Forest management attempts to deal with complexity of this scale by orchestrating the implementation of har- vesting, silviculture, and protection at the stand level. The direct results of local interventions are immediate and visible, as stands are harvested, established, and protected. But the interventions 276

OPTIMIZING TIMBER YIELDS IN NEW BRUNSWICK FORESTS 277 alter local dynamics that govern the development of stands and that con- tribute to the unfolding of forest dynamics. Because of the complexity of the forest and the long periods associated with stand growth, forest-level responses triggered by local interventions are not readily apparent and can accumulate into unforeseen, undesirable, and essentially unalterable pro- portions. How can the time and scale differences between the stand level at which actions are taken and the forest level at which management is planned and evaluated be bridged to permit the formulation of local intervention tactics that address the forest management problem in the most appropriate, biologically realistic manner? The case described here, involving a 300,000- ha forest management license in New Brunswick, is an attempt to construct a part of that local-global bridge. The results of similar analyses have led to management decisions that affect a large fraction of the forests of New Brunswick. THE ENVIRONMENTAL PROBLEMS The issue in this case is impact assessment, i.e., designing local inter- ventions that change the development of a biological system and fore- casting the nature and extent of the change (impact) to permit evaluation of the desirability of proposed interventions. Three entities must be considered with respect to wood supply: the quantity of wood, the quality of available wood, and the timing of avail- ability. Analyses have revealed that development of New Brunswick's forest under management restricted solely to harvesting and protection, as has been the practice, yields wood whose volume is insufficient to meet industrial demand, whose quality is below minimal standards, and whose availability is discontinuous and erratic (Baskerville, 1982~. Studies have shown that incorporation of silviculture, particularly tree planting and tending in the present case, can mitigate these supply problems (Basker- ville, 19831. This case study addresses the specific questions: What are the probable forest-level responses to an array of local, stand-level de- cisions regarding the amount of planting and density at which plantations are established, and what are the immediate and long-term impacts of the decisions on wood supply? The restriction of the present analysis to planting is solely for illustrative purposes. Stand spacing, thinning, and fertilization are other powerful silvicultural tools. The procedure described here could well be extended to those other tactics. In planting, two major points are at issue. First, at what rate (hectares per year) should plantations be established? Tree planting, an expensive

278 SELECTED CASE STUDIES undertaking initially, forces a continuing commitment to tend planted stands as they develop. Second, at what tree density (trees per hectare) should plantations be established? High volume per unit area and large trees are both desirable in a stand. However, the density dependence of individual tree growth in a stand is such that volume per stand and volume per tree cannot be maximized simultaneously. The former tends to be directly related to stand density, the latter inversely related to it. Thus, any chosen planting density represents a trade-off between volume per unit area and volume per tree, and the impact of this trade-off must be forecast for the proposed strategy and expressed in a form suitable for review by a decision-maker. Sophisticated routines have been developed that help to optimize stand performance (Brodie and Kao, 1979; Hann et al., 19831. But they con- centrate on stand-level responses and ignore the interplay of stand dy- namics, governed by the interactions among trees in a stand, and forest dynamics, governed by the collective development of stands in the forest. Failure to place stand development in the context of forest development has separated the elegant silvicultural solutions from the forest manage- ment problem and has impeded evaluation and selection of efficient means to address overall wood-supply concerns. THE APPROACH The approach presented here is an analytical framework that presents probable outcomes of a wide array of decisions and yet retains the linkages between trees, stands, and the forest. The framework is built around six steps, as follows: Step 1. Select a specific forest holding and determine the future wood supply and the precise nature of the biological limitations on wood supply produced by restricting management actions to harvesting and protection. This is the biological definition of the economic problem of wood supply. Step 2. Identify an array of remedial measures that can be applied to the strategic problem of wood supply. These are tactical approaches and, in this case study, are limited to the rate and density at which plantations are established. Step 3. Forecast the stand-level outcomes of each alternative in Step 2. Step 4. Link the stand-level responses into the forest mosaic and forecast the new forest dynamics that would result from implementing each of the planting interventions of Step 2. Step 5. Translate forest-level outcomes into performance indicators rel- evant to the wood-supply problem (identified in Step 11.

OPTIMIZING TIMBER YIELDS IN NEW BRUNSWICK FORESTS 279 Step 6. Assemble the performance indicators of all the alternatives in Step 2 to create a response surface (impact statement) that displays re- lationships between stand-level decision variables and forest-level per- formance indicators. USES OF KNOWLEDGE AND UNDERSTANDING Valued Ecosystem Component Within the six-step framework described above, the valued ecosystem component is the wood supply, as described by the performance indicators at the stand and forest levels. These indicators can be divided into two sets. The first set, at the forest level, includes short-term indicators of maximal sustainable harvest and associated unit cost and long-term in- dicators of potential harvest expansion and associated unit cost. These are the most important measures, because they are related directly to the wood supply. The second set, at the stand level, includes accumulated salable volume and average tree size at any point in the life of the stand. Although these are not the direct basis of decision-mal~ing, they collectively con- tribute to the forest-level indicators. Significance of Impacts The significance attached to changes in forest-level indicators brought about by the exercising of a set of stand-level control options is largely a function of the goals of the decision-making agency. Interpretations of significance can vary considerably between and within public and private agencies. Therefore, interpretations of significance are deliberately omit- ted here; "significance" has meaning peculiar to each agency, given its current perspective on the problem. The magnitude of reforestation effects on wood supply must be shown in a form that enables decision-makers to impose their own values and to draw their own conclusions regarding the significance of the impacts of a wide variety of strategies. Bounding the Problem The scale differences between forest-management control of stands and silvicultural control of trees necessitate different spatial bounding. At the forest level, spatial bounds can be logically established around the wood- supply base for a mill or group of mills controlled by one management agency. In this case, that supply base comprises 300,00(J ha in north- western New Brunswick. At the stand level, the spatial bounds must be

280 SELECTED CASE STUDIES expressed with a resolution consistent with silvicultural intervention (plan- tations), usually about 20 ha. The density dependence of tree growth operates at a very local level, so there is little interaction among non- neighbors. For a given stand structure, this leads to a perfectly linear relationship between stand production and size of stand (or group of stands of a given size). Two considerations were involved in imposing temporal bounds at the stand and forest management levels. Because of the long period required for stand development and the societal importance of the forest as a long- term renewable resource, the appropriate period for examining wood flow is necessarily long. Furthermore, the forest age structure has a biological memory: effects of disturbances, such as harvesting and planting, will surface and persist as the forest develops. A time horizon of 80 years was therefore deemed appropriate. In wood-supply problems, it is not sufficient merely to know the wood yield of a plantation or the volume of wood available from a forest. The timing of wood availability, and therefore the timing of supply problems, is of utmost importance. Detailed time resolution within the long-term horizon is necessary, to address timing in design of strategies. Consequently, the 80-year horizon was divided into 2-year steps for forecasting forest development and for tracking perform- ance indicators. For purposes of this chapter, it was decided not to consider the impact of spruce budworm on the forest and not to consider the numerous other issues that pervade real forest management. The budworm has played a major role in the development of the New Brunswick forest, as reflected in the present age-class structure of the forest. Yields from forest lands also are influenced by the sizes of budworm populations. Nonetheless, attempting to capture the complexities of the budworm-forest interaction would so dominate the analysis as to obscure the central issue considered here assessing the cumulative effects of harvesting practices. (For an overview of the budworm problem, see Baskerville, 1976.) Study Strategy Development A clear understanding of population dynamics at two levels is required for strategy formulation. At the stand level, dynamics are governed by the density-dependent forces that influence growth of individual trees. At the forest level, dynamics are governed by the structure and development patterns of the various types of stands that make up a forest. Density- dependent stand development and age-dependent forest development must be functionally integrated to provide a path for local intervention to be projected to the forest level.

OPTIMIZING TIMBER YIELDS IN NEW BRUNSWICK FORESTS 2s0 200 - ~ 150 ~ ' c E ~ _ ~100 a, 50 1 14 ,,, 1 2 E In 10 8 6 Sta nd age ( yea rs ) 281 initial Trees /ha 25 / / 50 75 100 Stand age (years) \\ 4000 \ 2000 '500 \\\ Initial \ \ \ Trees/ha my\ 4000 t25 ~ 500 75 100 2000 FIGURE 1 Stand development over time characterized by merchantable volume (above) and stems/m3 (below) for various initial stand densities. The results of density-dependent tree competition in plantation devel- opment can be captured in two stand variables and their change over time: salable volume per hectare (m3/-ha) and average tree size (trees/m31. Typ- ical patterns for stands of three different initial densities are shown in Figure 1. Within limits, the density dependence of tree growth shifts the patterns up in higher-density stands and down in lower-density stands. For each stand type or plantation in the forest, these relationships must be quantitative. For a stand to be considered economically available for harvest, minimal thresholds in salable volume per hectare and average tree size must be satisfied. These thresholds are the criteria that stands must meet to be

282 SELECTED CASE STUDIES 250 E ~200 o ~ c 1 50 c' c ~ 100 50 14 ,,, 12 ~10 in 8 6 \ Starr, hip wi ndow ~ \ / I / 1 / 1 --to l-~ / 1 1 25 \ 50 Stand age (years) - \ 100 150 - 50 S1a nd age ( yea rs ) 100 1 50 FIGURE 2 Determination of operable window for stand that defines its time of availability for harvest. Broken horizontal lines represent operability constraints of 100 m3/ha (above) and 9 stems/m3 (below). Broken vertical lines indicate earliest age at which both constraints are satisfied. recruited into the operable (or available) volume inventory. The age range over which these thresholds are satisfied defines the timing of a stand's availability for harvest (Figure 2~. For a given set of volume and tree-size thresholds, initial stand density can be silviculturally controlled to influ- ence the timing of the stand's availability for harvest (Figure 31. The potential power of stand-level control of availability becomes readily apparent in the context of forest-level dynamics. Because of forces of origin, species mixture, site fertility, and stocking, each of the many stands in a forest has its own pattern of development. A description of a forest shows the stage (age class) of each stand in its development pattern. Forest

OPTIMIZING TIMBER YIELDS IN NEW BRUNSWICK FORESTS 250 E - o a' D 150 c' tic c) 200 100 __ 14 2 10 in E 8 - u) 6 ~_1__ _ _ l I ~ 1 1 5~0 l 25 Stand age ( years ) \\ ~"\~ \i Initial Trees /ha 4000 - 2000 500 75 100 1 1 1 1 \ - - 500 Initial Trees/ ha ~ 4000 2000 25 50 75 100 Stand age (years ) 283 FIGURE 3 Effect of initial stand density on timing of stand availability for harvest. Operability thresholds, indicated by broken horizontal lines, are 100 m3/ha (above) and 9 stems/m3 (below). Broken vertical lines represent earliest time of availability for stands at each initial density. dynamics are generated by the collective development of the constituent stands as they progress (age) along their own patterns of development. Stands do not influence one another's growth, but they are linked at other levels. First, there is an analytical relationship between stands, in that the abundance of each developmental stage collectively constitutes an age- class structure for the forest. Second, interventions, such as harvesting and silviculture, performed in one place can force the withholding of such interventions in some other place. Managing the forest for wood supply is primarily a matter of regulating

284 SELECTED CASE STUDIES the availability of stands. That is achieved through a balancing of the liquidation of mature stands with the recruitment of immature ones across the lower threshold of operability. It requires a harvest schedule that defines the rate and sequence at which the harvest will proceed through the age structure of the forest. The rate of harvest is constrained by the timing of the availability of replacement stands as mature, operable ones are harvested. Availability of wood over time is a function of the initial forest age-class structure, particularly the relative abundance of stands in each age class, and the rate of development of these stands to operability. Consequently, any actions that hasten or retard availability of young stands for harvest have obvious implications for the rate at which mature ones can be harvested. That is the path by which density control at the stand level influences wood supply at the forest level. The forest age-class structure both determines availability and constrains the manner in which implemented stand-level actions translate into forest- level responses. As a result of the natural and man-made forces behind their development histories, New Brunswick forests have irregular and different age structures. A fixed set of stand actions, carried out on similar sites, will yield identical stand-level results that are wholly independent of the forest in which they are applied. However, the same set of stand actions might generate dramatically different responses, depending on the age structure of the forest. This case study deals with one such initial structure. Hypotheses The use of these conceptual tools to manage forest-level responses requires testing and evaluation of three hypotheses. · A quantitatively specific hypothesis must be made about how stand . ultimately, stand growth. It must be density affects tree growth and comprehensive enough to address such a question as: What will be the pattern of volume per hectare and average tree size over the life of a black spruce (Picea mariana (Mill.) B.S.P.) plantation established in northern New Brunswick at an initial density of 500, 1,000, 2,500, or 4,000 stems/ ha? The variables expressed in the forecast must be, at least, average tree size and volume per hectare, because of their important role in defining stand availability for harvest. · A hypothesis is necessary with respect to change over time in the minimal thresholds of tree size and stand volume required for stand op

OPTIMIZING TIMBER YIELDS IN NEW BRUNSWICK FORESTS 285 erability (utilization standards). Rapid changes in use indicate that oper- ability constraints change as a result of better technology in harvesting and product development. Instead of attempts to forecast how utilization standards would change, a range of reasonable future values was estab- lished, and the impact of these values on the forest-level indicators were analyzed. All the outcomes were incorporated into the impact statement in the form of a response surface, so that decision-makers could locate their own expectations with respect to changing operability limits and assess their significance. · A third hypothesis must relate development of the whole forest quan- titatively to that of the component stands, particularly those for which the plantation effort is contemplated. This hypothesis is also the basis for a forecast. The following are relevant and representative groups of questions: (1) How will the forest structure and resulting total growing stock change over time if no harvest is performed? If harvesting is carried out in the oldest stands first at a rate of, say, 400,000 m3/year? SOO,OOO m3/year? (2) How will forest structure and resulting growing stock change, if the same harvest schedules are attempted, but 4,000 stems are planted per hectare at a rate of 1,500 ha/year? 3,000 stems/ha at 3,000 ha/year? This second type of question is essential in designing a strategy of plantation use, and it highlights the necessary linkage between the local decision variables (planting rate and density) and the forest performance indicators (wood supply from the forest). Cumulative Effects To evaluate the cumulative effects of stand-level tactics on forest-level performance, the hypotheses with respect to stand development, opera- bility limits, and forest development were systematically knitted together. Plantation performance was forecast for each density alternative between 500 and 4,000 stems/ha. Various sets of operability constraints were im- posed on each of these, to establish the pattern of stand availability for harvest. Forest dynamics were then forecast iteratively as plantation tactics were systematically varied over all combinations of 0-4,000 hectares planted per year and 500-4,000 trees planted per hectare. For this purpose, the planting rate and density variables were changed at intervals of 500 ha/ year and 500 trees/ha, respectively, to generate 72 unique planting strat- egies, each with a pattern of future wood availability. Performance in- dicators were tracked, through a model of forest development, to describe the cumulative wood-supply effects resulting from each strategy.

- 286 SELECTED CASE STUDIES SOURCES OF KNOWLEDGE AND UNDERSTANDING Generally Accepted Ecological Facts Many empirical studies have described the effects of density on tree and stand growth for several species and locations in North America (e.g., Baskerville, 1965; Ker, 1981; Lundgren, 1981; Stiell and Berry, 19731. The findings, qualitatively displayed in Figure l, are generally accepted by foresters, although quantification has proved more difficult for partic- ular species and site conditions. Major planting programs were initiated only in the 1960s, so few com- prehensive data sources are available to help in quantifying the devel- opmental relationships in plantations in New Brunswick. For efficient use of the limited data, a plantation growth model, responsive to density control, was constructed for the species and sites relevant to this case study. The forest structure and natural stand growth are more adequately de- scribed by data sets available in the New Brunswick forest inventory and the records of the industrial land owner in this case. The forest-level characterization is presented in simplified form in Figure 4, which shows the present forest to comprise three types of stands: softwood stands dominated by fir (Abies balsamea (L.) Mill.), softwood stands dominated 1 5000 10000 5000 15000 10000 50CO 1 5000 1 OOCO 5000 E 150 o FIR 4, ,° 100 C E c 50 C' a, _ 1 DO 100 120 _ _ 20 40 60 20 40 60 80 100 120 Q) - C' _ SPRUCE ~ ~ 0 _ 1 To h ~ MIXED I WOOD 150 - 100 50 150 4 ~100 ' E c <' 50 / / \ 20 40 60 80 iOO 120 20 40 60 80 100 120 \ . . . . . . . 20 40 60 80 1 00 1 20 20 40 60 80 100 1 20 Stand age (years) Stand age (years) FIGURE 4 Age-class structures and yields for three stand types fir (top), spruce (middle), and mixed wood (bottom) that constitute forest used in case study.

OPTIMIZING TIMBER YIELDS IN NEW BRUNSWICK FORESTS 287 by spruce (Picea spy, and mixed-wood stands with fir and spruce com- ponents. The development pattern of each type, in terms of wood yield, reflects the biological characteristics of the species that make it up. The present forest structure is a product of history and is obviously nonuniform, with a preponderance of mature stands, a moderate presence of newly regenerating stands, and a dearth of stands at stages of devel- opment between the extremes. This age structure bears the ecological imprint of the two main historical forces behind the forest's development- harvesting by man and harvesting by spruce budworm (Choristoneura fumiferana (Clem.~. Intensive harvesting by man over the last 30 years has created many stands in the regenerating category. The forest suffered severe "harvesting" as a result of defoliation by the spruce budworm between 1910 and 1920; large-scale destruction of the mature forest at that time resulted in a large number of regenerating stands that appear today as the sizable area in the 60- to 80-year age classes. Most of the current stands are at or very near their peak volume. The futures of these stands, particularly fir, will be characterized by substantial decrease in volume, owing to natural decadence and breakup. Thus, even in the absence of harvesting, there will be a decrease in growing stock for the whole forest as the individual stands age. The paucity of stands in the 30- to 60-year age classes means that little in the way of replacement stands will become available for harvest as the mature stands are eliminated through harvest or by natural decline. The wood-availability problem hinges on the latter point. To maintain a constant wood flow, harvest of mature stands must be paced so that they last until sufficient young stands are available for harvest. Together, these factors reveal that measures that hasten the entry of regenerating stands into the available inventory might have a powerful effect in overcoming the problem of continuity of available stands posed by the broken forest age structure. If cut-over sites are immediately re- stocked with desirable species, spatially arranged to use as much of each site as possible and to control intraspecies competition, individual stem growth will be more rapid than in untreated stands. The more rapid de- velopment of plantations increases the availability of replacement stands, which in turn permits a greater rate of liquidation of mature stands and therefore an increase in the annual wood supply. That is the principle that underlies the use of planting tactics to address the wood-supply problem for this particular forest. The model used to forecast plantation development is based on two general principles: in the absence of any competition, individual tree height and diameter growth are bounded by inherent upper limits that are func- tions of species and site conditions, and realized growth (less than these

288 SELECTED CASE STUDIES limits) is regulated by the amount of growing space afforded the individual tree and its competitive status within the canopy of the stand. Specific Models Two models were used to make the required forecasts of stand and forest dynamics. At the stand level, a simulation model was constructed by giving quantitative form to the principles stated above and using avail- able field data to define the maximal potential growth rates for black spruce in the region. The model views the stand as a population of trees described by a diameter and height distribution at any time. Growing space and com- petitive status for each size class are determined from this distribution and applied to potential dimension increments to obtain forecast increments for the current competitive situation. The growth-estimation process is iterative, each iteration taking into account the accumulating changes in stand structure in the computation of growing space and competitive status, the two growth-regulation factors. The model is therefore dynamic enough to grow stands in a structurally realistic manner and to allow incorporation of planting-density alternatives. Lack of long-term plantation growth data on New Brunswick made creation of the model and assessment of its predictive behavior particularly difficult. Comparisons were made against relevant data sets; in all cases, the model forecasts of volume per hectare and tree growth were qualita- tively in accord with the empirical studies. Model forecasts for four initial stand densities are shown in Figure 5. The model provides a specific focus for carrying out a plantation-growth monitoring program, and the explicit assumptions behind the model are in a form amenable to specific field- testing and revision. Forest development was forecast for various harvest and planting in- terventions with slight modification of an existing model. The original model was built by Erik Wang (Fraser Inc.) and parallels the concept behind the Wood Supply and Forest Productivity (WOSFOP) model of Hall (19781. This type of simulation model has seen extensive use in New Brunswick and other provinces (Cuff and Baskerville, 1982) and was used here because it was appropriate for the forest-level questions asked and because forest managers in the province are generally comfortable with it. The forest-development model accepts as input an array of stand growth types that constitute the initial description of the selected forest, by giving stand areas, age-class structures, and yield functions (as in Figure 41; operability limits (as in Figure 31; and a rate of harvest specifying the

OPTIMIZING TIMBER YIELDS IN NEW BRUNSWICK FORESTS ^ 240 c E - Too - ' 160 a) c 120 G Cot a) 80 18 E 12 E 28g ,:~ I/ Initial Trees/ha -4000~- 3000 2000 1000 500 1 - . ~_ __ //1 / / --War ~ 1 car 1 1 1 45 so l -1--: 25 30 35 40 Plantation age (years) Initial Trees/ha 4000 \ 3000 \\ \ \\ 000 \ \ \\ \\ \ \\ \\\ \ \ \ ) ~1 \ 25 30 Plantat ion age (years) 35 So 45 50 FIGURE 5 Model forecasts of merchantable volume (above) and tree size devel- opment (below) for black spruce plantations at five initial densities. Broken vertical lines represent minimal time required to satisfy current operability thresholds of 115 m3/ha and 7 stems/m3 simultaneously. amount to be removed annually and the priority rules for allocating that harvest to the various stand types and to stages of development within a stand type. At 2-year intervals, the model advances the age-class structures for each stand type along their yield curves, performs the harvest and planting activities, and calculates forest-level indicators, such as total available growing stock, volume loss in mortality, and the evolving forest age structure. The two models are linked, in that the stand model is an input source

290 SELECTED CASE STUDIES for the forest model. Through this linkage, stand-level tactics are carried through to the forest-level performance indicators. CONTRIBUTION OF RESULTS TO ECOLOGICAL KNOWLEDGE The study shows that limited preliminary data, combined with basic ecological principles, can be systematically used to display the impacts of a range of management strategies. Several hundred simulations were performed by linking the plantation-development model with the forest- development model to evaluate the forest-level outcomes of various com- binations of planting rate and density. The results are presented as a set of response surfaces, or nomograms, in Figure 6. This format is partic- ularly useful when two decision variables are to be assessed via their control over the valued ecosystem components through several indicator variables (Peterman, 19751. Decision-makers can easily review outcomes of a wide range of strategies before setting a decision process (or optim- ization) in motion. In this case, the decision variables are local (stand- level) implementation options of plantation density and planting rate, shown on the Y and X axes, respectively. The surface evaluation, or Z variable, represents a forest-level performance indicator associated with each stand-level decision combination. This surface is a type of prediction containing not only absolute outcomes of a host of alternative combinations of stand tactics, but also the sensitivity of the forest indicators to those tactics. Figure 6 contains a number of noteworthy relationships between local stand actions and overall forest outcomes that have important implications for selection of a strategy. For example, Figure bA shows that increasing the area planted annually increases the sustainable harvest immediately available from the forest, regardless of planting density. The increase in forest response surface is nonlinear, however, as evidenced by the wid- ening intercontour gaps associated with increasing the planting rate. At the onset of horizontal contours (e.g., at 2,000 ha/year and 2,500 stems/ ha), the positive immediate impact of planting on wood supply disappears altogether. Obviously, at a given density, each additional hectare planted is growing identically with the rest, but the effect of the marginal hectare on total forest performance changes dramatically with the degree of ac- tivity. Each additional hectare is progressively less "productive" in pro- moting immediate increased harvest. Thus, increases in planting are not accompanied by proportional harvest increases, and, beyond particular amounts of planting, there is no immediate harvest increase at all. At this point, harvesting has so drastically altered the forest structure that the resulting low abundance of mature stands constrains further immediate

OPTIMIZING TIMBER YIELDS IN NEW BRUNSWICK FORESTS 291 A. Maximum sustainable harvest B. Cost per m3 of increased (103 m3/yr. ) harvest (#) ; 3000 Cl u, E 2000 (A 000 4m) . ___ 3000 U) 2000 E - ~n 1000 _ 144 ~ ~ I_ _380 4000 3000 c' E 20a) - ~n 1000 000 200C 3000 4000 10002000 3000 4000 ha/year ha /year C. Opera ble growing stock at D. year 60 ( I o6 ma) ~o Cost per ma of growing stock at year 60 ( C ) 30 ~ / ~ ~: coo 2000 3000 4000 1000 2000 3000 4000 ho /yea r ha ~ yea r FIGURE 6 Impact of planting rate (X axis) and plantation density (Y axis) on four indicators of wood supply. Indicators A and B are related to immediate impacts; indicators C and D are related to impacts 60 years later. harvest increases. Essentially, the biological limitation on wood supply switches from scarcity of young stands at low planting rates to scarcity of mature stands at high planting rates. The time to stand operability associated with each plantation density regulates the planting rate at which this switch occurs. This has two important implications. First, the powerful influence of forest structure on the effectiveness of planting is not evident

292 SELECTED CASE STUDIES if planting is evaluated solely on the basis of local, stand-level perfor- mance, as is common in investment approaches. Stand-level assessment would indicate that, if some planting is good, then more is better, and it is better in direct proportion to the extent of effort. Clearly, that is not the case: the linearity breaks down when plantations are viewed in the context of the whole forest. Second, the forest-structure constraint on planting effectiveness necessitates plantation tactic design specific to the forest in question. The surface in Figure 6A would be different if the same stand response were applied to a forest of different initial age structure from the one used here. Thus, management strategies embodying design of stand tactics are not freely transportable between forests. The maximal sustainable harvest for this forest is 480,000 m3/year (Figure 6A) and can be attained by planting 1,500 stems/ha at a rate of 3,000 ha/year. This combination, of course, pertains to a specific set of operability constraints and an 80-year horizon. The maximum resides in a very sensitive area in Figure 6A. The tightly packed contours in the lower third of the figure form a "cliff" that represents a high-risk zone for the decision-maker. If strategies at the edge of the cliff are pursued to maximize the harvest, then substandard plantation performance, poor competition control, ineffective protection, or bad model forecasts could have disastrous consequences. Such occurrences would mean that the sustainable harvest was over the brink and either a severely reduced sus- tainable harvest or an unexpected disruption in wood flow would result from implementing a harvest rate set in accordance with plantation yields that never materialize. Strategies in this high-sensitivity zone might be chosen by the risk-taking decision-maker, whereas one with a more con- servative approach to risk might opt for a higher plantation density (2,000- 3,000 stems/ha) and accept a slightly lower sustainable harvest to ensure a less sensitive response. At the stand level, the highest-yield-per-hectare option is planting at a density of 4,000/ha (Figure 51. This does indeed keep stands in the most productive state, which is seen as a desirable goal by some foresters, but, as shown in Figure 6A, devastates the productivity of the forest as a whole, because it severely delays availability of plantations by reducing growth rates of individual trees. Again, this exposes the important dif- ference between local stand response and overall forest response to selected sets of tactics. Figure 6C contains information relevant to possible future increases in harvest, showing the growing stock available 60 years from now. Appre- ciable gains in growing stock occur at planting rates higher than those needed to achieve the maximal immediate harvest. Furthermore, with respect to future increases, the greatest gains are realized at higher densities

OPTIMIZING TIMBER YIELDS IN NEW BRUNSWICK FORESTS 293 than those which generate the maximal immediate harvest. Thus, high present harvests and high future harvests cannot be ensured simultaneously through the implementation of one plantation tactic. The decision-maker faces a trade-off between immediate gains and future gains. It can be resolved by striking a compromise between the two or by using a strategy with two simultaneous tactics: a low-density one aimed at immediate harvest gains and a high-density one aimed at future harvest gains. Re- gardless of the choice, failure to link stand and forest performance would not even reveal the problem to the decision-maker, let alone suggest potential solutions. To illustrate the impact of operability limits on the decision-maker, several stand- and forest-level simulations were performed in which the minimal acceptable operability standards were systematically altered. The annual planting rates were fixed at the number of hectares required to maximize the current harvest for each planting density (e.g., 1,500 ha/ year at 4,000 stems/ha and 3,000 ha/year at 1,500 stems/ha). The results are presented in nomogram form in Figure 7. The X, Y. and Z axes show minimal Or. tress. ~i7.e plantation density, and maximal sustainable lllillAlAl~$ ~ ~ _ it_ ~, ~ ~ r- harvest, respectively. Each of the four surfaces in Figure 7 represents a different minimal- volume-per-hectare requirement. It is clear that the desirability of alter- native densities, with respect to wood supply, varies considerably with the tree-size constraints that will be in effect. In Figure 7B, for example, under the stringent requirement of 6 stems/m3, plantation densities of 1,000-1,500 stems/ha provide the maximal harvest. However, as the tree- size constraint is relaxed, both the maximal sustainable harvest and the plantation density at which the maximal harvest is realized increase. This is evidenced by the ridge that runs through the surface in the figure. That the surface elevation increases with relaxation of tree-size constraint is a reflection of the decreased time to stand operability and the consequent increased availability of stands when harvest of smaller trees is acceptable. That the ridge has a positive slope in the X-Y plane is indicative of the earlier achievement of these lower operability thresholds by higher-density (and consequently higher-volume) plantations when the tree-size constraint is reduced. Examination of all four surfaces reveals that the increase in harvest associated with relaxed tree-size constraints holds for the minimal-volume- per-hectare constraint as well. The maximal possible harvest increases as the minimal volume per hectare is decreased from 205 m3/ha (Figure 7D) to 70 m3/ha (Figure 7A). Similarly, the planting density that yields the greatest harvest increases as the volume-per-hectare constraint increases. That is consistent with Figure 5, which shows the advantages of low and

294 A. Maximum harvest (103m3/yr) at 70 m3/ha volume constraint 40a) - An/ / o~ Jl1117° ~,~ E 2000 - cn - - //// /~/// ~o 1 OOt) 4000 3000 C, ~ ID E - 1 000 SELECTED CASE STUDIES B. Maximum harvest (103m3/yr) at 115m~ha volume constraint 4003 3000 /// ~ 6 8 10 12 Required stems /m3 C. Maximum harvest (103m3/yr) at 160 m3/ha volume constraints J in E 2000 in ooo 14 6 4009 101~ / / ~/j2/ / J/ 460- 1COO / c 6 8 10 12 14 Required stems / ma -500 - 3C~ E On 360 /~/ 440 / Jl74 / 480 /~ 8 10 12 14 Required stems/ ma D. Maximum harvest (103rn3/yr) at 205 m3/ha volume constraint 10/ - Ad/ / 1 ~/420/ / //~ 6 8 10 12 14 Required stems /m3 FIGURE 7 Impact on wood supply of plantation density (Y axis) and minimal ac- ceptable tree size (X axis) at four constraints on minimal volume per hectare. high densities to be rapid tree-size development and rapid volume-per- hectare development, respectively. Of importance to decision-making in Figure 7 is the powerful influence that utilization constraints can have over forest-level outcomes. The actual biological response underlying each surface in Figure 7 is identical. What generates the marked differences in forest outcome is a logistical harvesting constraint that the decision-maker imposes on the biological system, which regulates the availability of stands

OPTIMIZING TIMBER YIELDS IN NEW BRUNSWICK FORESTS 295 for harvest- this is no mere detail, inasmuch as utilization constraints are largely under the decision-maker's control. Figure 7 reveals likely out- comes that the decision-maker might achieve by exercising that control. APPLICATION OF THE TOOL The modeling process captured in Figures 6 and 7 constitutes a useful tool in policy design. Nomograms like those shown are powerful aids in structuring policy questions so that detailed modeling and analysis can be directed incisively. The diagrams are not used to choose a "best" planting policy. Rather, they are displayed to senior decision-melters, first to dis- cover how they weight various indicators and second to discover where the decision-makers would like to be within the possible policy domain. Detailed analyses can then proceed with the indicators of choice within limits in terms of the policy variables. Thus, the nomograms are not used to answer operational questions, but rather to structure management ques- tions. In this context, they make the scientific advisor more efficient both in the use of his own time and in establishing an understanding of the problems between advisor and decision-maker. CONCLUSION The case study presented here shows how a wide range of stand-level actions would influence forest-level outcomes. The purpose is to make the decision-maker aware of the importance of linking the two levels of consideration. No recommendations of optimal planting densities or plant- ing rates are presented, because such decisions are strongly influenced by specific industrial strategies and objectives and by the degree of risk aversion of decision-makers. Furthermore, the decision-making picture is incomplete. Analysis becomes more complex as wood value, harvesting cost, and additional silvicultural tactics (such as spacing and thinning) are considered. Once the range of impacts is understood, more sophisticated analytical tools, like mathematical programing, might be effectively brought to bear on strategy design. Different planting alternatives, applied at the stand level, generate dif- ferent forest-level outcomes, because of the interaction of stand and forest dynamics. These differences highlight risks, sensitivities, and trade-offs that, although of prime importance in decision-making, would not be readily evident from stand-level or forest-level analyses alone. As a pack- age, the analytical framework and the results it provides form a rich body of information relevant to the forest management problem of evaluating the impact of interventions on wood supply.

296 SELECTED CASE STUDIES The techniques described in this study have been applied in the design of New Brunswick's silvicultural program. Effective control over planting is possible, because about 50% of forest land in the province is Crown land and the large timber companies need access to Crown land to maintain economical operations. Of the remaining land, half is owned by large companies and half has varied ownership. Thus, about three-fourths of the forest land in the province has been readily incorporated into a har- vesting program suggested by the analysis as necessary to even the flow of timber and counteract the unfavorable age distribution of the stands. There is not yet a firm link between stand dynamics and budworm population dynamics. Therefore, it is not possible to predict the effects of the harvesting and planting program now being implemented on pop- ulation dynamics of the insect. Whether the program will have to be modified to accommodate problems generated by the budworm remains to be seen. REFERENCES Baskerville, G. L. 1965. Dry matter production in immature balsam fir stands. For. Sci. Monogr. 9:1-42. Baskerville, G. L. 1976. Report of the Task Force for Evaluation of Spruce Budworm Control Alternatives. New Brunswick Cabinet Committee on Economic Development, Fredericton, N.B. Baskerville, G. L. 1982. The Spruce/Fir Wood Supply in New Brunswick. New Brunswick Department of Natural Resources, Fredericton, N.B. Baskerville, G. L. 1983. Good Forest Management-A Commitment to Action. New Brunswick Department of Natural Resources, Fredericton, N.B. Bird, J. W. 1980. Forest management A provincial perspective. Pp. 33-37 in The Forest Imperative. Proc. Can. For. Congr., Toronto, Ont., September 22-23, 1979. Canadian Pulp and Paper Association, Montreal. Brodie, J. D., and C. Kao. 1979. Optimizing thinning in Douglas-fir with three descriptor dynamic programming to account for accelerated diameter growth. For. Soc. 25:665- 674. Cuff, W., and G. L. Baskerville. 1982. Ecological Modelling and Management of Spruce Budworm Infested Fir-Spruce Forest of New Brunswick, Canada. Paper presented at 3rd Int. Conf. on State-of-the Art in Ecological Modelling, Colo. State Univ., May 24-28, 1982. Hall, T. H. 1978. Toward a Framework for Forest Management Decision-Making in New Brunswick. Report TRI-78. New Brunswick Department of Natural Resources, Fred- ericton, N.B. Hann, D. W., J. D. Brodie, and K. H. Riitters. 1983. Optimum stand prescriptions for ponderosa pine. J. For. 81:595-598. Ker, M. F. 1981. Early Response of Balsam Fir to Spacing in Northwestern New Brunswick. Maritime Forest Research Center Information Report M-X-129. Canadian Forest Service, Fredericton, N.B. Lundgren, A. L. 1981. The Effects of Initial Number of Trees Per Acre and Thinning

\ OPTIMIZING TIMBER YIELDS IN NEW BRUNSWICK FORESTS 297 Densities on Timber Yields from Red Pine Plantations in the Lake States. Forest Service Research Paper NS-193. U.S. Department of Agriculture, Washington, D.C. Peterman, R. M. 1975. New techniques for policy evaluation in ecological systems: Meth- odology for a case study of Pacific salmon fishenes. J. Fish. Res. Bd. Can. 32:2179- 2188. Stiell, W., and A. B. Berry. 1973. Development of Unthinned White Spruce Plantations to Age 50 at Petawawa Forest Experiment Station. Publication 1317. Canadian Forest Service, Ottawa, Ont. Commi`;tee Comment The work reported in this case study provides a concrete example of how to assess the long-term, regional consequences of immediate, local forest-management actions in a manner useful for the design of sustainable strategies for resource development. The story is interesting as a partic- ularly simple and clear case of effective assessment of cumulative effects, and it has proved useful in actual practice by the Department of Natural Resources (DNR) of New Brunswick. Indeed, Baskerville initiated the analysis described here to deal with the practical difficulties he encountered as assistant deputy minister in DNR; Erdle is now responsible for applying the results of the analysis in DNR's Forest Management Branch. The problem addressed here is widespread in forest management. A forest is a large-scale mosaic of individual stands of trees. Different stands can generally be characterized by age distributions, species mixtures, and habitat. The forest therefore is also a mosaic of stand-development tra- jectories, different stands reaching maturity at different times and rates. Management actions can alter those trajectories. Although wood is considered the only valued ecosystem component in this model, additional components, such as control of spruce budworm and maintenance of an aesthetically pleasing mosaic of forest patches, have been considered in other analyses of the system (Baskerville, 1976; Clark et at., 19791. The focus developed in this study was the result of a consensus that emerged among government, industry, and academic participants in the forest-management debate that, if the wood-supply problem were solved, most other concerns would be met automatically. Interestingly, the supply of wood is from the outset defined in cumulative terms over the regional scale and long periods relevant to the economics of the provincial forest industry. What matters ultimately is not the pro- duction from an individual stand of trees, but rather how the production from all the stands of the forest, taken together, can best be managed to meet society's needs.

298 SELECTED CASE STUDIES Erdle and Baskerville studied the cumulative effects of alternative man- agement actions by integrating local models of stand growth, regional models of forest age-structure dynamics, and a detailed inventory of the forest's existing age structure. They used available models of the relations among site quality, tree density, and growth rates of individual trees as the major sources of ecological knowledge. In essence, a commonly used wood-supply and forest-productivity model was taken "off the shelf" and provided with data relevant to the New Brunswick situation. This pro- cedure made their task simpler and made their results more acceptable to managers already familiar with the models. The forest model used by Erdle and Baskerville is essentially a book- keeping one that tracks the aging of forest stands as they respond to additions to wood (through planting and natural regeneration) and removals of wood (through harvest, insect damage, and natural death). The under- lying ecological theories are simple. Growth rates are assumed to be density-dependent, and the yield curve has a maximum. These results have been empirically determined, but they can also be derived theoret- ically from basic principles of plant competition. The simplicity of these demographic accounting models is also their main strength. They are robust, and, if solid biological data are available, they can be readily used for a wide variety of situations (see also Chapter 121. More complex, general, and rigorously tested stand models (Shugart, 1984) could have been used in the analysis and probably would have afforded improved credibility in academic circles. But there is no reason to believe that these more elegant models would have appreciably improved the results obtained by Erdle and Baskerville. An additional aspect of ecological knowledge central to the success of the Erdle and Baskerville analysis was the existence of an accurate de- scription of the present age distribution of provincial forests. Such baseline data on the heterogeneity of tree stands with respect to age distribution, species mixture, and growth potential are necessary to coordinate local, short-term management actions in a way that achieves desired regional cumulative consequences. Unfortunately, such data are extremely rare, especially in the case of age distribution, in inventories of forests and other renewable resources. New Brunswick has a forest inventory data base that is one of the most accurate and useful for forecasting purposes in North America. This is in part because of the data-base shortcomings uncovered in Baskerville's earlier modelings and analyses and his later tenure in DNR. Generally speaking, however, useful background data are difficult and unglamorous to obtain, monitor, and update, although a characteristic feature of the

OPTIMIZING TIMBER YIELDS IN NEW BRUNSWICK FORESTS 299 few success stories in resource management is the existence and intelligent use of such data bases (see, for example, Chapter 12~. One final aspect of the Erdle and Baskerville analysis, the method of presenting results, is relevant not only to the assessment of cumulative effects, but also to a wide variety of efforts to provide usable ecological knowledge. They use nomograms to illustrate the trade-offs in valued ecosystem components that are likely to result from alternative manage- ment actions or other development interventions. In this forest-manage- ment case, as in many other environmental problems, interpretations of what is important vary considerably within and among government agen- cies, private interest groups, and the ecological profession. Moreover, as Erdle and Baskerville point out, these perceptions of significance change with time. Rather than adopting a single definition that would render their analysis usable from only a single perspective, Erdle and Baskerville have devised a framework in which users can specify (and indeed often discover) their own definitions of significance and explore the implications of their definitions for a wide range of possible decisions. An added benefit of the nomogram approach, used to good effect in this case study, is that the spacing of the nomograms' contours of valued ecosystem components indicates the sensitivity of a predicted outcome to errors or incompleteness in implementing the decisions. Peterman (1981) has shown how minor modifications of the nomogram technique can be used to show the significance of uncertainties in the ecological models for the expected effects on valued ecosystem components. An analysis of the uncertainties inherent in the regional demographic and local compe- tition models underlying this case study would have increased its useful- ness even more. Nomograms of this sort have been applied to environmental problem- solving in cases of renewable-resource management (e.g., Holling, 1978; Peterman, 1975, 1977; Regier, 1976), river-basin planning (e.g., Rabi- novich, 1978), and regional development (e.g., Miller, 19821. They have a long history of application in business and industrial management. Nom- ograms are not a cure-all, especially given their restriction to two or at most three simultaneous trade-offs. But they are useful in appropriate circumstances, and they deserve wider application. Not all the approaches and techniques for cumulative-effects assessment described by Erdle and Baskerville are relevant to the more complicated situations of, say, river-basin planning, or even to the more closely anal- ogous situations of regional fisheries management. As difficult as forest age structure is to deal with, it is nonetheless measurable, and it provides a firm handle on the assessment of future forest development a handle

300 SELECTED CASE STUDIES that most cumulative-effects studies will not have. In addition, the mere existence of a forest-level "planning authority" (the province's Depart- ment of Natural Resources) makes the case reviewed here much easier than the more typical one in which no agency is either solely responsible for or has sole power over the long-term, regional impacts of a class of related development decisions. More generally, it is worth emphasizing with the authors that a great proportion of their analysis involved the careful "tuning" to local conditions of a few relatively simple ecological concepts and models. No general precr~ptions for cumulative-effects as- sessment or management emerged from this study, nor are they likely to emerge from others. References Baskerville, G. L. 1976. Report of the Task Force for Evaluation of Spruce Budworm Control Alternatives. New Brunswick Cabinet Committee on Economic Development, Fredericton, N.B. Clark, W. C., D. D. Jones, and C. S. Holling. 1979. Lessons for ecological policy design: A case study of ecosystem management. Ecol. Model. 7:1-53. Holling, C. S., ed. 1978. Adaptive Environmental Assessment and Management. John Wiley & Sons, Chichester, Eng. Miller, P. C. 1982. Simulation of socio-ecological impacts. Environ. Manage. 6:123-144. Peterman, R. M. 1975. New techniques for policy evaluation in ecological systems: Meth- odology for a case study of Pacific salmon fisheries. J. Fish. Res. Bd. Can. 32:2179- 2188. Peterman, R. M. 1977. Graphical evaluation of environmental management options: Ex- amples from a forest-insect pest system. Ecol. Model. 3:133-148. Peterman, R. M. 1981. Form of random variation in salmon smolt-to-adult relations and its influence on production estimates. Can. J. Fish. Aquat. Sci. 38:1113-1119. Rabinovich, J. E. 1978. An analysis of regional development in Venezuela. Pp. 243-278 in C. S. Holling, ed. Adaptive Environmental Assessment and Management. John Wiley & Sons, Chichester, Eng. Regier, H. A. 1976. Science for scattered fisheries of the Canadian interior. J. Fish. Res. Bd. Can. 33:1213-1232. Shugart, H. H. 1984. A Theory of Forest Dynamics. Springer, New York.

Next: 20. Control of Eutrophication in Lake Washington »
Ecological Knowledge and Environmental Problem-Solving: Concepts and Case Studies Get This Book
×
Buy Paperback | $110.00
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

This volume explores how the scientific tools of ecology can be used more effectively in dealing with a variety of complex environmental problems. Part I discusses the usefulness of such ecological knowledge as population dynamics and interactions, community ecology, life histories, and the impact of various materials and energy sources on the environment. Part II contains 13 original and instructive case studies pertaining to the biological side of environmental problems, which Nature described as "carefully chosen and extremely interesting."

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  6. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  7. ×

    View our suggested citation for this chapter.

    « Back Next »
  8. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!