1043-C1
R. Keith Jones and David W. Andinson 1
Over the past decade the Canadian Model Forest Network has devoted much of its effort to translating the concept of sustainable forest management (SFM) into practice. This work has involved a creative mixture of people, knowledge, tools and processes. Reflecting their particular ecological, social and economic setting, each model forest has contributed to the SFM challenge uniquely.
The McGregor Model Forest (MMF) in central British Columbia (BC) has developed a management planning framework and prototype system referred to as "the McGregor Approach to Sustainable Forest Management". The approach includes six integrated tools: 1) an adaptive management cycle; 2) a comprehensive information system; 3) a scenario planning process; 4) models to forecast future forest conditions; 5) an indicator system; and 6) reporting and visualization techniques.
The Foothills Model Forest (FMF) in west-central Alberta has focused its efforts in different but complementary areas of SFM. For example, it has developed and implemented a comprehensive program to help understand, communicate and integrate into management patterns and processes of historical disturbance. This work has provided a common conceptual theme and knowledge base which partners can use to make decisions. It also offers an additional and important seventh tool to the McGregor Approach.
In Phase III of the model forest program there is an opportunity to integrate the SFM approaches developed by the MMF and FMF. The anticipated result will be a more robust SFM framework and a set of tools to address social and economic values in the context of ecological sustainability.
Over the past decade, the Canadian Model Forest Network has contributed significantly to the discussion, definition, and practice of sustainable forest management (SFM). Across eleven model forests in Canada, these developments have helped the forest sector improve its understanding of the many dimensions of sustainability as it applies to the values ascribed to particular forestland areas (Brand et al. 1996). This has been achieved through a unique and creative mixture of people, knowledge, experience, information, tools, and processes.
Figures 1 illustrates our version of how these components work together to form a generalized framework for SFM. Driving the process are environmental, economic, and social values and expectations of the forest. These are interpreted into a set of high-level goals such as "to conserve the natural biological diversity of landscape ecosystems." These goals are then translated to specific strategies across a landscape (Gunn 1996). For example, a strategy for achieving the above biodiversity goal might be "to maintain the percentage of old forest within the historical range." The translation of goals into more specific management strategies and operational plans for a defined forest area is a challenge for agencies and forest companies trying to adopt SFM ideals. This is the primary focus of this paper.
We propose that the success of this translation lies in the degree to which three main SFM components are developed and brought together - a foundation of knowledge and experience, tools, and the adaptive management (AM) cycle.
The SFM foundation component is represented as the "core" of Figure 1 and includes scientific understanding, expertise, opinions, and information about ecological, social and, economic features and processes. We suggest the initial emphasis be placed on ecological knowledge, since to sustain ecosystem-dependent values, we need a healthy forest.
The second component is a set of seven tools for organizing, exploring, interpreting, and communicating our collective knowledge about resource values, management objectives, and their interactions in space and time. For example, information systems, a scenario planning process, indicator systems, forecasting and interpretive models, and visualization techniques collectively permit the exploration of alternative futures that recognize the inherent natural, spatial, and temporal dynamics of the system being managed.
The third integrative component is the AM cycle, forming the outermost circle in Figure 1. This is now accepted universally as an essential process and overarching philosophy to support SFM. It acknowledges that SFM knowledge is imperfect, and that management activities serve as an opportunity to learn and improve practices over time.
The model forest program has contributed significantly to the development of various aspects of the three basic SFM elements described above. This paper focuses on summarizing MMF and FMF experience, and how combining this experience may lead to a more robust system for deriving landscape-specific objectives from high-level goals.
The MMF's 180,000-hectare landbase is located in the sub-boreal ecological region near Prince George, BC. Managed as a Tree Farm License on provincial Crown land, the MMF Association was formed in 1993 as a non-profit society representing over thirty partners. In addition to research on the model forest area, pilot projects were also conducted elsewhere around BC (Wolfe 1994).
The following discussion outlines the McGregor Approach to SFM, with a focus on four of the seven SFM tools shown in Figure 1. Descriptions of the information systems and indicator systems, along with other MMF program accomplishments, can be found in other reports (e.g., McGregor Model Forest Association 2001). The natural range of variation tool is described in the FMF section below.
The McGregor Approach to SFM adopts the six-step AM cycle developed for BC as an overarching philosophy. AM is described as "a systematic process for continually improving management policies and practices by learning from the outcomes of operational programs." (Nyberg 1998).
The scenario planning process creates a series of narratives about how different future forest conditions might unfold and appear (Schoemaker 1995). Scenario planning formally includes a number of steps, as detailed in Figure 2. It helps stakeholders to assess opportunities, identify alternatives, and design and chose a management strategy that meets their collective objectives. Unlike more data-driven analytical approaches, scenario planning considers a number of factors simultaneously, drawing upon shared human experience.
Figure 3 illustrates the current condition of the MMF area in comparison to two scenarios, intensive forestry and one with a biodiversity emphasis at year 2100. The scenarios are illustrated using visualization and a planimetic map. Indicators are shown for timber volume, mature seral stage forest, and large patch sizes. During the exploration stage much was learned about inter-relationships between resource values, management objectives, future trends and uncertainties, and their effects on outcomes. Once final decision scenarios were prepared, the participants had a broad appreciation for different resource interests and for spatial and temporal forest dynamics. They were able to understand and "see" how different sets of objectives could realize acceptable tradeoffs when considered across the entire MMF area over timeframes exceeding 200 years. Recent applications of this scenario planning approach are creating broad buy-in to and ownership of the process. Having participated fully in the design of shared future outcomes, local communities are also feeling greater empowerment through the process.
Models play an essential role in the scenario planning process. A treatment model automates the delineation of potential treatment units based on species composition, slope, and other spatial and operational constraints. Then a scheduling model creates a sequence of management treatments and portrays future conditions for several rotations, thereby enabling different scenarios to be projected and compared. Competing management objectives can be addressed through standard near-optimization modeling techniques that allow multiple values, objectives, and constraints to be evaluated against desired outcomes. Constraints relate mainly to regulatory rules or policies. Outputs from the model include spatially explicit schedules and associated reports for all treatment units, at any scale of planning, from strategic to operational.
With large forest areas and long timeframes, being able to convey alternative scenarios effectively is a challenge. This is especially difficult for SFM participants, who are most familiar with timeframes of a single human generation and who have little or no experience reading maps, graphs and tables. While GIS tools can generate many useful outputs, a key accomplishment has been the development of visualization techniques. The visualization tool provides tangible representations of future conditions, much like a motion picture time machine. It can also be used to "fly" virtually over an entire area, by integrating remote sensing images, 3-D digital elevation models, a GIS database, and rendering tools. Figure 3 shows three visualizations from a fixed location today and for two future scenarios at year 2100.
At over 2 ½ million hectares, the FMF is one of the largest model forests in Canada. It is also one of the most diverse, including portions of the Foothills, Montane, Sub-alpine and Alpine ecological zones (Beckingham et al. 1996). The landbase includes 1,000,000 hectares of working forest (managed by Weldwood of Canada Ltd, Hinton Division), although the majority of land is managed by federal, (e.g., Jasper National Park) provincial (e.g., Willmore Wilderness Area), and municipal governments. The management goals for the FMF landbase are understandably diverse, and it now includes over 80 partners.
The difficulty of developing a single SFM system for all partners at the FMF is obvious. Given the diversity of partner needs, the FMF approach to SFM was to develop a wide range of tools available to, and valuable for all partners. For example, the FMF has been involved in research on a wide range of species including grizzly bears, caribou, and Harlequin ducks. It has also implemented experimental prescribed burn programs, and coordinated the creation of a provincial biodiversity monitoring program (Foothills Model Forest 2001).
One of the cornerstones of the FMF Phase II program has been the Natural Disturbance Program. Understanding natural disturbance as an ecological process has been gaining favour across Canada as an alternative way of managing biodiversity values. The more traditional species (or "fine filter") approach to understanding and managing biodiversity values has served us well until now, and the FMF has invested heavily in this type of research. However, the number of species is (for all intents and purposes) limitless, and maximizing the needs of one species often comes at the cost of minimizing or eliminating others. Furthermore, local extinctions, periodic high mortality levels, and other perturbations are a part of natural cycles (Bunce and Jongman 1993). The danger of adopting fine filter strategies alone is that this may result in biodiversity becoming a constantly moving, subjectively defined goal.
Alternatively, landscapes can be managed through an understanding of the available resources provided by a dynamic landscape over time and space (Merriam and Wegner 1992). By first understanding, and then managing for the natural range in variation of the ecological processes most active on a landscape, the risk of losing biological function is minimized, since the rate, intensity, and magnitude of the processes are familiar (Noss 1994). In northern forest landscapes, wildfire, flooding, windthrow, and insect outbreaks are the ecological processes that largely define landscape dynamics. This suggests that a tenable strategy for forest management is to approximate the range of structures that natural landscapes exhibit through an understanding of natural disturbance processes and patterns (Gauthier et al. 1995). This more holistic approach to biodiversity is commonly known as a "coarse filter" strategy, although the term "natural range of variation", or NRV, is often used synonymously.
The FMF Natural Disturbance Program was designed as a package to include NRV research, communications, and integration (Figure 4). This more integrated strategy was designed specifically to address several specific partner needs as they relate to SFM (Andison 2001). First, it generates for all partners a defendable, quantifiable foundation of knowledge of how forest landscapes operate as systems. As illustrated in Figure 2, the first step in any SFM decision-making process is gathering the best available knowledge, since such knowledge informs decision-making, policy, operational guidelines, and monitoring efforts.
Second, the program has demonstrated (through presentations, tours, workshops and reports) how integral disturbance is to forests. Seeing forest landscapes as "dynamic" entities is a difficult concept, and decades of "Smokey the Bear" messages are well ingrained in people's thoughts. For example, Jasper National Park has used the research to help design and defend prescribed burn programs meant to reduce extremely high fuel-loads caused by decades of fire control.
Third, the investment in the natural patterns study has provided an objective, easily measurable foundation on which to build sustainable management planning scenarios. For example, Weldwood used seral-stage NRV output from a simulation modeling exercise as the natural "baseline" against which various management alternatives were compared in their most recent long-term forest management plan (Andison 1998). This tool is also represented in Figure 2.
Fourth, because NRV research output is usually expressed in terms of vegetation pattern, it is ideally suited to defining indicators and targets for monitoring programs. For example, patch sizes, area disturbed, and even the structure of a disturbance edge, are all ecologically meaningful, and easily quantifiable coarse-filter indicators.
Although the FMF has been successfully studying natural patterns, and integrating them into forest management in various ways, the full potential for using this information within a more formal SFM system has not yet been realized. For example, while the integration of a scenario or visualization models are part of the long-term plan (Figure 4), they have not yet been developed. On the other hand, FMF partners can now benefit from the work already done by the MMF on these and other initiatives, using the NRV work as the foundation.
The different settings and priorities of the McGregor and Foothills Model Forests led to a different emphasis in each case in addressing the SFM challenge. The MMF had a strong focus on developing a new approach to forest planning within a dominantly industrial forest setting. Up until recently, the resource management regime was prescriptive in nature and strongly dictated by BC's Forest Practices Code (FPC). When coupled with multiple planning levels and mandates, management occurred within a complex and relatively inflexible policy, planning, and regulatory framework. In response, the MMF focused its attention on developing multi-participant planning approaches aimed at striking a balance between meeting the stringent requirements of the FPC and aligning with the intent of higher level plans.
The FMF was motivated by a different set of circumstances. Given the task of having to provide support for a broader range of partner expectations including both working and non-working forest, and responding to the Alberta government's desire to have land management organizations assume greater levels of responsibility, the FMF took more of a bottom-up approach. They defined their role by identifying and developing key individual components of the SFM picture, which were commonly valuable.
We believe that the different approaches taken at the two model forests are complementary and can be integrated to help translate high-level goals into landscape-specific, spatially and temporally explicit objectives. We demonstrate how this might occur by adapting the original SFM framework concept developed by the MMF.
Consistent with "science-based" decision-making (Gilmore 1997), the first task is to form a collective understanding of the ecological systems present ("Understand Ecological Systems" in Figure 2). NRV knowledge is a large part of this step, but it should embrace all biological information, including local ecological knowledge. Models, reports, maps, and visualizations are all used at this stage as tools for communication. Indicators are also identified and used for tracking and comparing landscape dynamics over time and space. Using this knowledge, an NRV "baseline" scenario can be described which shows landscape patterns when there is no management intervention. Considerable time is required at this point to develop "shared understandings", since disturbance processes often occur over long timeframes and are difficult to envision.
The next step is to build scenarios by manipulating the landscape using models. For example, we may impose extreme management actions on the landscape to help "bound" the decision-making process. The MMF refers to this step as generating "initial scenario themes" and introduces both social and economic factors. This process evolves into the development and testing of more complex, but also more plausible scenarios based on what was learned from the initial scenarios. With the high-level goals and management objectives in mind, various indicator target combinations are tested against each other. The NRV baseline scenario serves as a continual reference for historical levels of variation.
One of the advantages of using a scenario method of decision-making is the emphasis on "future forest condition" as opposed to only choosing among objectives. In other words, stakeholders choose how they want future states of the forest to look like in terms of individual and combinations of values. Since indicators have been used throughout the process, a final "decision scenario" is easily translated into a set of meaningful and feasible objectives. Subsequent monitoring and assessment are similarly facilitated using the same indicators and targets to measure progress and provide feedback as part of the AM cycle.
The concept of SFM is noble, and seldom contested. Translating the concept into practice, however, is more difficult than anyone imagined a decade ago. Part of the challenge is due to: 1) the complexity of the problem; 2) understanding the dynamics of nature; and 3) developing practical management planning systems that respect both the complexity of the problem and the dynamics of nature. Each model forest in Canada has responded to these challenges in different, but often complementary ways.
In this paper, we demonstrated how two SFM approaches developed at the MMF and FMF could be integrated to help resolve the specific challenge of translating high-level goals into landscape-specific objectives. This solution serves as an example of how integrating knowledge, experience, information, tools, and processes into a whole "system" can be more valuable than just the sum of its parts. A framework breaks the problem down into more manageable and concrete components, but also focuses on the connections between them. Ultimately, an integrated system helps to better inform decision-makers, practitioners, and communities about forest sustainability options for practices today and far into the future.
The programs discussed in this paper were made possible only through the efforts and support of a wide list of individuals and agencies. A long list of Foothills Model Forest partners have generously supported the Natural Disturbance Program at the Foothills Model Forest for several years. Likewise, the McGregor Model Forest Association's 30-plus partner organizations have supported the research and development of SFM systems in BC for more than 10 years. We would also like to thank the large number of individuals who have dedicated considerable effort and thought into making these respective model forest programs successful. Finally, we would like to thank Anne Scott and an anonymous reviewer for their helpful edits and comments on this manuscript.
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1 R. Keith Jones & Associates, c/o McGregor Model Forest Association, P.O. Box 2640, Prince George, British Columbia, Canada V2N 4T5. [email protected]; Website: www.mcgregor.bc.ca
Figure 1.
A proposed SFM framework for translating high-level goals into landscape-specific objectives comprising three integrated components: an SFM foundation, SFM tools, and an encompassing adaptive management cycle.
Figure 2.
Detail of the scenario planning tool and process which translates high-level goals to landscape-specific objectives and serves the "assess opportunities" and "design strategy" steps of the adaptive management cycle.
Figure 3.
McGregor Model Forest composite graphic showing the scheduling model interface (top left) and landscape visualizations, maps, and indicators for the present forest condition and two scenarios at the year 2100.
Figure 4.
Foothills Model Forest Natural Disturbance Program - long term map (adapted from Andison 2001).