An Introductory Guide to Adaptive Management

Appendix 1

Adaptive Environmental Assessment and Management (AEAM) Workshops

AEAM is a process where participants with a diversity of skills and expertise are brought together in a workshop or series of workshops to assess a management problem and explore management options. Usually, participants work with modellers to develop a computer simulation model that they then use to explore various "what if..?" scenarios and evaluate potential outcomes of different management actions. In addition, significant benefits are derived from the process of building the model. The workshops are intended to encourage debate about system response to management actions and to stimulate a creative search for new solutions, rather than build consensus around a single solution. In some cases, the scope of the problem and the options explored will be bounded by prior decisions about land-use (for example, those defined in Land and Resource Management Plans, or other regional or local land-use plans).

The AEAM workshops are valuable for:

• building a common understanding of the problem;
• synthesizing existing knowledge;
• highlighting key uncertainties and clarifying assumptions;
• stimulating creativity and generating new management options.

The model allows participants to:

• project potential effects over time and space;
• forecast potential effects of cumulative management actions; and it
• provides a consistent basis for participants to discuss and evaluate management options.

AEAM workshops typically involve the steps outlined below, although they can be tailored to suit the management problem and available budget. In some cases these steps will be done in a single workshop, over one or several days; in other cases, they may be done in a series of workshops, with some participants working on particular aspects of the problem in between. Work is done in both plenary sessions and sub-groups.

While model-building is valuable for focusing discussion, workshops where time or budget constraints preclude computer modelling can still be useful. The development of conceptual models is itself a very worthwhile exercise. To maximize the value of the workshop, objectives and expectations must be clearly understood by all participants, including the modellers and facilitators.

AEAM is an iterative process - later steps may lead to reevaluation and reiteration of earlier steps. For example, it may be useful to model the problem at several different spatial scales. Similarly, exploring the effects of management options may suggest alterations to model parameters or relationships, or new options to try.

Steps that were outlined in section 1 (Assessing Problem) are noted.

Prior to the first workshop, typically in a meeting between the facilitator(s) and the project leader(s):

1. Identify key participants.

The first workshop may involve 20-30 people, including:

• modellers/facilitators
• forest managers and planners
• "knowledge experts" from a range of disciplines (e.g., hydrologists, wildlife biologists, fisheries biologists, social scientists, etc.)
• policy-makers
• forest workers
• people with local knowledge
• other stakeholders

Participants can be drawn from government agencies, industry, community groups, environmental organizations, First Nations or other groups with expertise to contribute or who will be affected by management decisions. The mix and quality of participants is critical to workshop success. Participants should not only have relevant expertise, but should also be creative, innovative thinkers.

2. Define the initial scope of the problem and key problem features.

(e.g., spatial and temporal scale, range of factors to consider, key indicators)

• This can help keep the workshop on track.
• For some problems it also may be useful to summarize existing, accepted knowledge about the system. This can "jump start" the process and minimize time spent on issues about which their is already general agreement.
• It is critical that participants not feel constrained by this initial problem scoping; leaders/facilitators must be prepared to alter or abandon any boundaries or framework developed prior to the workshop.
• In some cases, the scope of the problem will be influenced by land-use decisions made by other bodies (e.g., LRMPs). Decisions made by AEAM participants should not conflict with or supersede those made by other decision-making bodies.

During the workshop(s): In the group as a whole:

3. Define scope of problem (see section 1).

• The participants in the workshop should have the opportunity to revise the scope defined by the facilitator(s) and project leader(s) prior to the workshop, to ensure that issues of concern are addressed. This is the first step in building a common understanding of the problem.

4. Define measurable management objectives (see section 1)

5. Identify key indicators for each objective (see section 1).

6. Identify possible management actions (see section 1).

Actions and indicators are then grouped into logical sub-groups (e.g., based on theme or scale). Participants are assigned to these sub-groups based the knowledge and skills they can contribute. In each sub-group:

7. Draw impact hypothesis diagrams(for given group of actions and indicators).

• These "box and arrow" diagrams outline the linkages between management actions and indicators and represent a synthesis of existing knowledge on each subsystem.
• Impact hypothesis diagrams are not intended to show detailed links between all components of the system - only those that affect management outcomes/decisions.

8. Identify and assess key information gaps (see section 1).

• Evaluate links in impact hypothesis diagram, considering: quality of existing information, level of influence on outcome, feasibility of filling information gap. One suggested system for assessing alternative hypotheses is:
  1. unlikely, not worth testing
  2. already tested
  3. possible, too difficult to test
  4. uncertain, research needed
  5. likely, worth testing

Work in sub-groups alternates with discussion in plenary sessions. This ensures that the sub-groups understand and have a chance to comment on each other's assumptions, and ensures that the diagrams form a coherent whole. "Outputs" of one diagram will be "inputs" to another.

9. Modify an existing simulation model or develop a new one.

• In some cases there may be an existing model that captures the relevant pathways and conceptual model expressed in step 7 above. If so, this model can be used to explore alternative actions. If a suitable model is not available, develop a new one based on the impact hypothesis diagrams.
• While a crude model can be developed in the workshop, typically it will have to be refined before it can be used for exploring scenarios and forecasting outcomes.

10. Test and validate the model; do sensitivity analysis on model parameters.

• Test model to determine how sensitive outcomes are to variations in model parameters.
• Sensitivity analysis helps narrow in on those areas of uncertainty that most affect management outcomes.

11. Explore alternative scenarios/management options.

• Develop a range of plausible management options.
• Use the model to explore the effects of these options on indicators.
• This "gaming" with the model is usually done in the group as a whole.

A reminder: AEAM is an iterative process- not sequential as summarized above. The model will be continuously refined and tested, new options developed and explored, and new predictions made.

The AEAM process should provide participants with:

• a common understanding of the problem;
• a list of key indicators;
• documented assumptions about how the system functions, how variables respond (i.e., the model);
• predictions about the effects of alternative management actions;
• a list of key uncertainties in model parameters and relationships (i.e., those that have most influence on outcomes);
• a list of plausible alternative hypotheses that should be tested, in order to improve understanding of system behaviour and its representation in the model, and thus improve management decisions;
• an idea of what "probing actions" can be taken to test these alternative hypotheses.

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