The projects below have been conducted by Don Morgan over the last five years

Including Stakeholders

Table of Contents

• Methods
• Results
• Discussion

Methods

Because this project aims to develop methodology (for analysing landscapes), we followed no specific methods, but rather use a set of general approaches for each objective:

• Data management
• Characterising natural landscapes
• Predicting long term consequences
• Linking scales
• Including stakeholders

We developed and applied methods in a series of pilot projects. We employ standard GIS technology, computer code and landscape modelling languages, using non-proprietary software when possible and developing modules rather than large integrated applications. Several reports describe the methods developed and the results of testing in case studies; these reports are referred to in the results section. Here we provide and overview of the methods used in the various projects.

Our original systems design philosophy was to use non-proprietary software to facilitate the free distribution of all computer models. Initially we relied on proprietary information systems software such as the PAMAP and the ARC/INFO GIS. Currently, the BC MoF does its data management using the ArcINFO and Oracle and we are dependent upon it for basic data management. However, most of the project application development has been based on free systems.

To facilitate public access we developed several Internet applications. Early in the project we developed a tool so that people could explore landscape pattern models. We successfully developed a prototype but ran into operational limitations. Instead we have focused our efforts on a set of landscape pattern models that can be downloaded from the internet (http://www.cs.sfu.ca/hre/SEED). In the latter part of the project, we have focussed our effort on developing a framework for involving stakeholders in land use planning, discussed below.

There is a clear need for a structured framework to guide the collaborative development of landscape models. This framework should be oriented to finding solutions for a given socio-economic and ecological problem, to maximise mutual understanding, and to improve decision-making.

The general framework we propose rests on the foundations of adaptive environmental planning, assessment and management and computer-supported collaborative work, but differs somewhat by emphasising opportunities for stakeholders to have a more extensive role in conceptual model development, thereby increasing opportunities to learn and to communicate. The framework targets situations in which stakeholders have issues and questions, and conceptual models to contribute to the process, but do not wish to be directly involved in model implementation. Thus, we focus on conceptual model development, rather than model implementation (e.g., collaborative model construction), as the hub for collaboration.

The framework relies on the participation of three overlapping groups in a series of workshops (Figure 1). Each group brings different talents and contributes to different phases of model development and use.

• Stakeholders set project objectives, defining the issues and questions at stake. They contribute conceptual models and describe the range of potential management actions to consider. The term stakeholder is being used broadly to include those who make or influence decisions.
• Topic experts provide information needed to formalise and parameterise the conceptual models. They help to interpret results. They include scientists (both local experts and topic specialists) familiar with the ecological processes involved, and land managers familiar with the local management regime.
• A core team (3-5 people) manages the framework. They organise and facilitate workshops and communication, gather required information, implement and test models, run simulations, analyse outputs and prepare documentation.

Figure 1. Collaborative modelling depends on three groups interacting through workshops.

The framework defines seven steps; different groups participate in different steps.

1. Issues and objectives aims to define the scope of the modelling project. An initial workshop brings together interested stakeholders to define project objectives, including potential participants, based on key issues, interest and available funding.

2. Conceptual models and scenarios aim to develop conceptual models, based on important resource values and issues, and scenarios, based on the range of reasonable management options. A set of workshops, each focusing on a specific aspect of the problem, define key ecological and management processes and specify management policies to model.

3. Formal Conceptual Model aims to create clear, formal descriptions of conceptual models (i.e., equations and logical constructs). Small workshops with topic experts focus on specific model components.

4. Model Implementation aims to encode the formal conceptual models, accurately and quickly, as a computer simulation. A core modelling team assembles the required GIS information, and implements the formal conceptual models.

5. Simulation experiments aim to verify equivalence between the implemented and the formal conceptual models, to assess uncertainty and to evaluate scenarios. A core modelling team runs multiple test cases and management scenarios.

Analysis aims to characterise differences between alternative management options, accounting for uncertainty. Documentation aims to describe the model both in simple terms and in specific detail. It aims to describe experimental results.

6. Review aims to discuss important findings with all participants. A final workshop is held with all participants to present results from the scenario experiments and to discuss the implications of the results, and the need for further analysis.

After simulation experiments begin, the core modelling team may revisit earlier steps in the framework , as necessary. Obvious coding and logic errors are fixed by the core team in successive coding revisions. Typically, a second round of workshops with topic experts (and interested stakeholders) is held with the goal of verifying model behaviour. Participants refine the formal conceptual models, and provide new information to help parameterise models. With successive iterations and increasing confidence in conceptual and implemented models, simulation analysis shifts from model testing towards sensitivity analysis, hypothesis testing and scenario evaluation. Discussion of results may lead participants to identify modifications to management scenarios and conceptual models. This completes a full iteration of the modelling cycle, where the final workshop may become the initial workshop of the subsequent iteration.

It is critical that the core team can move from conceptual model to results within the time frame allotted. The core team must balance the desire to incorporate more details and realism with the overall project goals.

Results

In this section we describe the reports, software products and database scripts generated by this project. We do not list all the workshops held. At one level, workshops are part of the research process, however, they also serve to pass methodology to an interested audience.

Reports

Morgan, D.G., D. Daust, K. Price and A. Fall. 1998. Description of the Iskut-Stikine Landscape Model. Unpublished Report. Research Branch. BC Ministry of Forests, Smithers, BC – (html) (pdf), Appendix 1 (html) (pdf)

Morgan, D.G. and A. Fall. 1998. Description of the Invermere Landscape Model. Unpublished Report. Research Branch. BC Ministry of Forests, Smithers, BC – (html) (pdf), Appendix 1 (html) (pdf)

Daust, D., K. Price, D.G. Morgan and A. Fall. 2000. Description of the Lakes Landscape Model. Unpublished Report. Research Branch. BC Ministry of Forests, Smithers, BC – (html) (pdf), Appendix 1 (html) (pdf), Appendix 2 (html) (pdf), Appendix 3 (html) (pdf), Appendix 4 (html) (pdf), Appendix 5 (html) (pdf)

Fall, A., Daust, D. and Morgan, D. 2001. A Framework and Software Tool to Support Collaborative Landscape Analysis: Fitting Square Pegs into Square Holes. Transactions in GIS. 5(1):67-86. – (pdf)

Software products

Morgan, D.G. 1997. Spatially Explicit Landscape Tool. Research Branch. BC Ministry of Forests, Smithers, BC

Hvezda, P. and J. Fall. 1998. Java SELES. Research Branch. BC Ministry of Forests, Smithers, BC (Download)

Discussions

In the past, modelling has failed to reach its potential as a decision-support tool in the forest management arena. Since the emergence of computer science, simulation modelling has defined a solid niche in many scientific fields, judging by the numerous published models. The application of models in forest management seems less successful—the calculation of timber-supply being the only consistent application of modelling. Yet the complexity and large spatial and temporal scales that characterise forest management problems suggest modelling should help. Land-use decisions can profoundly impact our economy and our ecology, with consequences that may reach forward several generations. Wise decisions seem essential. While the analysis methodologies and software discussed in this report aim to improve the quality of decisions, passable software and modelling expertise have existed for many years. We believe decision-support projects have failed primarily for two reasons. First, modellers and decision-makers do not understand each other’s objectives and limitations. Decision-makers must often decide quickly, using available information and subjective judgement, and they may have unreasonable expectations about what can be modelled. Modellers, on the other hand, often aim for efficient elegant models, backed by thorough research, and are not unduly constrained by time. Second, influential stakeholders have not been adequately included in modelling projects (McLain and Lee 1996, Selin et al. 1997). Thus, to support our analytical methods developed, we have developed a framework for involving stakeholders—the framework simply aims to align the objectives of the modellers and the decision-makers (including stakeholders). If this main aim is remembered, then we believe modelling can inform forestry decisions.

At the beginning of the project we built upon the spatially explicit landscape planning tool (Morgan et al. 1995) to integrate spatial analysis into the public participation planning process. From those beginnings we have evolved our stakeholder involvement methods to the landscape modelling framework that we have successfully applied in the Iskut-Stikine LRMP, Invermere, Lakes Pine Beetle Assessment, Robson Valley and Columbia Mountains. More recently the North Coast LRMP has chosen our modelling framework and modelling methodology for their LRMP scenario evaluation.

With our framework (Figure 3) we can tackle complex forest management problems. The framework aims to address relevant questions, involve appropriate people and use a format that promotes discussion and learning.

We have found that a fairly small core team (3-5 people) is essential to carry out this process, in order to combine a range of skills while maintaining streamlined communication among team members. Collectively, the core team must possess expertise in several disciplines, preferably with most required skills shared by more than one team member, including:

• Problem domain: to initiate the mutual learning process, the core team should have at least a basic knowledge of the problem domain, including the important ecological and management processes. The core team should have some information regarding important people to contact, domain experts, and data sources.
• People skills: Communication and facilitation are two critical skills, which are supported by good oral and written skills.
• Technical skills: A solid understanding of GIS, ecology, forestry, modelling, formal analysis, and statistics is critical to achieve credibility. It is particularly important for all team members to have a good understanding of the benefits and limitations of spatio-temporal modelling in order to help guide participants during model development.

· Figure 3. Nested, iterative model development process. Groups participate in all circles that surround them. All participants set objectives, develop conceptual models, select scenarios and discuss model results. Topic experts and the core team develop and verify the formal models and analyse and document simulation experiments. The core modelling team implements and verifies models and runs simulations.

Landscape simulation can illustrate some basic principles of landscape ecology. Our experience suggests that foresters and other participants in forest-use decisions have difficulty visualising the consequences of decisions over large spatial and temporal scales. Stands of trees, covering millions of hectares, change in structure and function over decades and centuries. In the field, foresters may explore a few hectares for a few days. They may make 5 to 20 year plans for several thousand hectares. Thinking about hundreds of thousands of hectares over hundreds of years requires a shift in perspective. The framework we propose assists learning about interactions between landscape processes, consequences of management actions, and cumulative effects over long time periods and large areas.

When using a collaborative framework, the indirect benefits of a project, including communication and learning, are often of great value even than tangible products (e.g. models and reports). Decisions for complex problems are based on information from a multitude of sources, of which concrete model results is just one. Increased understanding of the problem by stakeholders may be more critical to making good decisions.

We have not tested our framework in, nor do we recommend it for, high-conflict situations. Social obstacles to participatory frameworks include excessive levels of conflict that impedes constructive debate, exclusion of some stakeholders who have indirect influence on decision-making, and valuing some viewpoints more than others.

Figure 2. Data preparation and links

Overall we developed more sophisticated data management techniques through our pursuit of data warehousing. The work from this project was important in helping establish the Northwest Data Centre in Smithers BC. This data centre now provides data management and analysis services to both government and industry for a variety of projects including Innovative Forest Practices Agreements, spatial timber supply analysis, habitat supply analysis and landscape unit planning.

Acknowledgements

DULP is a BC Ministry of Forest Research Branch project with funding assistance from Forest Renewal BC.