AMP Toolbox

According to Williams (2009) not all decisions can or should be adaptive. In some cases there is no opportunity to apply learning; in others, there is little uncertainty about what action to choose; and in still others, there is disagreement about objectives. But the concept of adaptive management is so intuitively appealing that it has been applied indiscriminately, with the result that many management applications fail to achieve the improvements expected from adaptive management. This is evidenced by the fact that even after 40 years of application, there are relatively few success stories (Williams, 2014).
This activity provides guidelines to check if conditions are met to develop adaptive policies.
If not, other approaches for environment management are possible like hedging or optimal control, by the functioning of two main factors: uncertainty and controllability (Gregory, 2006).

Key questions

Key actions

According to Willams (2009), conditions identified from literature review and experience can be categorised in two groups depending on the operational and administrative contexts:

Conditions on the operational context of the future policy:
1. A real management choice is to be made. Thus, an application of adaptive management must involve a real choice among management alternatives that affect resource systems. The variability among alternatives must be consequential (i.e., different alternatives produce substantively different management impacts), and the alternatives must be ecologically, economically, politically and legally feasible.
2. There is an opportunity to apply learning. A condition of adaptive management is that resource management decisions can be revisited and modified over time or that multiple decisions of a similar nature can be made over time. That is, decision making needs to be iterative over time and possibly space; otherwise, learning cannot be applied.
3. Clear and measurable management objectives can be identified. Uncertainty about how to achieve objectives is what motivates adaptive management and drives the design of the monitoring system. To address this uncertainty, stakeholders must agree on the objectives. Adaptive management itself is not designed to resolve conflicts about management objectives. Objectives need to be measurable, so progress toward their achievement can be assessed and accordingly performance that deviates from objectives may trigger a change in management direction.
4. The value of information for decision making is high. Although uncertainty can be identified in almost any resource management problem, its reduction does not automatically lead to a better decision. An adaptive management application should target learning that will change management actions and improve the ability to achieve management objectives. Conversely, an adaptive approach is not warranted if the value of information is low, essentially because the potential improvement in management does not justify its costs.
5. Uncertainty can be expressed as a set of testable models to predict the effects of policy actions that are relevant to the objectives. But predictions require models, whether conceptual or quantitative. Models can be qualitative and conceptual, quantitative and highly detailed, or anywhere in between. In all cases, their function in an adaptive management context is to make predictions about how a natural system will respond to policy actions and to evaluate the consequences of uncertainty. Models are a means to encourage managers, scientists, and other stakeholders to think carefully about the structure and dynamics of the systems they are managing.
6. A monitoring system can be established to reduce uncertainty. Monitoring is fundamental for adaptive management, as a source of data to test predictive models and measure progress towards accomplishing management objectives. Simply put, adaptive policy is not possible without effective monitoring. Monitoring protocols should include choices about the ecological attributes to be monitored and the way to do it, together with the management context and decision making that motivates the monitoring in the first place. Data collection that is guided by monitoring protocols provides the necessary information for both learning and evaluation of management effectiveness. The monitoring programme should also include the institutional resources needed to sustain the monitoring (and analysis of the resulting data) over the time frame required to inform management.

Conditions on the institutional context of the future policy

For adaptive policy to be successful:

There are situations where its application may not be appropriate.

Tools & methods

Further reading