Training & Education

An Introductory Guide to Adaptive Management for Project Leaders and Participants

Step 1. Assess and Define the Problem

This step may be done in a workshop or series of workshops that bring together people with a variety of perspectives, skills, and areas of expertise. It is important to involve those who will implement, monitor and be affected by plans, as well as managers and scientists. For example, a workshop could bring together: forest managers, policy advisors, forest workers, scientists, First Nations, other forest users and people from local community groups. Simple problems will typically involve fewer people than complex problems.

For complex or contentious issues, it may be valuable to bring in 1-2 outside facilitators who, between them, speak the language of the relevant disciplines, are skilled at managing people, bring a systems perspective to issues, and are unbiased about the outcome. Facilitators should be involved early in the process and can help with both workshop preparation and follow-up.

In the workshop, participants first synthesize existing knowledge by developing a model of the system, and then use the model to explore different management options. For simple problems, the model may be a simple diagram or graph. For more complex problems (e.g., those where actions are projected over time and space), a computer simulation model is valuable. In some cases, it may be possible to modify an existing model. The steps outlined below are applicable regardless of the type of model used.

Although the key points below are presented in a numbered sequence, keep in mind that problem assessment is an iterative process. Be willing to return to earlier steps if necessary. For example, the exercise of exploring the effects of management alternatives may suggest new objectives, different management alternatives, or even that the problem should be addressed at a different spatial or temporal scale.

The elements of an assessment workshop are described in more detail in Appendix 1.

1.1 Define scope of management problem.

• Define spatial scale, temporal scale, and range of factors (i.e., values) to be considered.
• Define sensitivity of resource values (e.g., consider risk of damage).
• Consider aspects of the system that affect indicators or that are likely affected by management actions.
• Avoid defining problem in terms of preconceived solutions, since this would limit the development of imaginative alternatives.
• Consider long-term, cumulative and large-scale effects of management actions.

1.2 Define measurable management objectives and list potential management actions.

1.3 Identify key indicators for each objective.

• Indicators are measurable attributes of system behaviour that allow you to weigh management options and, eventually, assess outcomes.
• Select indicators that are relevant to objectives and responsive to management actions.
• Take into account the cost and practicality of measuring each indicator.
• Select some indicators that respond in the short term, some in the medium term, and some in the long term. Select indicators that respond at different spatial scales (e.g., site, landscape, region).

1.4 Explore effects of alternative actions on indicators.

• Develop a conceptual model of the system: outline linkages and describe the functional relationships between actions and indicators (e.g., using box-and-arrow diagrams, graphs, equations).
• If warranted, modify an existing simulation model or build a new one to represent the conceptual model. Simulation models are particularly valuable for projecting changes over time and space and assessing the integrated consequences of a suite of actions.
• Use the model (whether it is a simulation model or conceptual model) to explore the effects of alternative actions.

1.5 Make explicit forecasts about response of indicators to alternative management actions.

• Forecasts can be based on outputs from simulation models or, for simple problems, on the graphs or diagrams used to describe the relationships between actions and indicators.

1.6 Identify and assess key gaps in understanding (key uncertainties).

• Through exploring alternatives and forecasting responses, key gaps in understanding of the system will emerge. Express these key uncertainties as alternative hypotheses of system function. Hypotheses can be expressed as simple graphs, or where appropriate simulation models exist, as functional relationships or sets of model parameters.
• Consider the relationship between action(s) and indicators over a range of conditions (i.e., how will an indicator respond to different degrees of a treatment?).
• Assess the sensitivity of forecasts and management choices to alternative hypotheses. If different hypotheses lead to different forecasts or management choices, then it is worthwhile designing a management experiment that will discriminate between them. (In modelling, this step is commonly referred to as "sensitivity analysis" because it involves assessing how sensitive model outputs are to different model assumptions or inputs).

Helpful tools & techniques

• AEAM workshops (see Appendix 1)
• conceptual models (e.g., box and arrow diagrams of potential impact pathways)
• simulation models

Note: Understanding of complex and dynamic ecological systems will always be incomplete. However, not all gaps in understanding necessarily need to be filled in order to decide between alternative management actions. For example, where different assumptions lead to the same forecast, or to the same choice of management action, there is no need to resolve the uncertainty about which assumption is "correct". Adaptive management guide