Sayed Iftekhar NRMPeople in all walks of life – from town planners to judges and financial regulators – are subject to bias in their perceptions and judgements. Natural resource managers too are only human.

CEED researchers at the University of Western Australia have found that we may be able to improve the performance of natural resource management (NRM) if we recognise the influence of biases and work to reduce them.

“Decision makers do not always perceive things accurately,” says Sayed Iftekhar, the lead researcher on the study published in Conservation Letters. “It has been shown that, in making judgments dealing with uncertainty, decision makers are susceptible to different types of biases – beliefs that are inconsistent with reality or behaviors that compromise the achievement of objectives.”

Research which demonstrates that people are subject to a range of biases has received little attention in the conservation literature. Working with David Pannell, Iftekhar set out to explore the consequences of these biases on NRM in general and adaptive management in particular.

“Based on our survey of the economics and psychology literature we explored the impacts of action bias, the planning fallacy, reliance on limited information, limited reliance on systematic learning, framing effects, and reference-point bias,” explains Iftekhar.

“Each bias can have an adverse impact on our capacity to undertake effective adaptive natural resource management. The ‘planning fallacy’, for example, is the tendency of project planners to be excessively optimistic about the performance of a project that they are developing. It’s a very common bias and Iftekhar and Pannell suspect that it has led to some very poor decision about major NRM investments.

“A strategy to reduce the planning fallacy is to ask managers to forecast the completion time, cost, or benefits for a range of comparable projects rather than a single project. This strategy, known as Reference Class Forecasting, has been effective in reducing time and cost overruns of large infrastructure projects.”

The researchers point out that where the planning fallacy is in evidence, adaptive management may help to reduce its adverse consequences. Adaptive management, involving information collection and refinement of project design, helps in correcting decisions that were initially made on an excessively confident or optimistic basis. If necessary, targets can be modified or the project can be terminated following the collection of improved information.

Based on their survey of the economics and psychology literature, Iftekhar and Pannell believe that environmental managers and natural resource managers should be on the look out for the following common biases:

  1. undertaking on-ground actions even when these are not worthwhile;
  2. suffering from the cognitive illusion of being more in control of the system than they actually are;
  3. being overconfident about the expected outcome of their decisions;
  4. being overly optimistic in terms of expected completion time of the project;
  5. relying on a partial set of information for decision making even when more complete information is available;
  6. relying on trial-and-error learning and repeating their past successful choices instead of collecting and comparing information about the full set of decision options; and
  7. trying to achieve predefined goals rather than the best possible outcomes from a project.

Bias is a part of human life. The take home message from this study is that NRM agencies need to be aware of the influence of biases when management decisions are undertaken.


Iftekhar, M. S. and Pannell, D. J. (2015), “Biases” in Adaptive Natural Resource Management. CONSERVATION LETTERS. doi:10.1111/conl.12189

More information: Sayed Iftekhar This email address is being protected from spambots. You need JavaScript enabled to view it.

Image: Sayed Iftekhar, on the right, listens to an ecologist in a grassy woodland (a threatened ecosystem). Sayed has investigated how NRM managers are often influenced by unacknowledged biases in their decision making. Photo: David Salt

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