Australasian Science: Australia's authority on science since 1938

Bias in Natural Resource Management

Natural resource managers must acknowledge the presence of bias and make a conscious effort to minimise its influence in their decisions.

People in all walks of life – from town planners to judges and financial regulators – are subject to bias in their perceptions and judgements. This applies to environmental managers too. We recently explored the influence of bias in natural resource management and found that we may be able to improve our performance if we recognise these influences and work to reduce them.

Decision-makers do not always perceive things accurately. 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 behaviours that compromise the achievement of objectives.

There is some research demonstrating a range of biases that influence people, but this has received little attention in the conservation literature. We set out to explore the consequences of these biases on natural resource management 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 effect and reference-point bias. Each bias can have an adverse impact on our capacity to undertake effective adaptive natural resource management.

For example, the planning fallacy is the tendency of project planners to be excessively optimistic about the performance of a project that they’re developing. It’s a very common bias, and we suspect that it has led to some very poor decisions about major natural resource management 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 in large infrastructure projects.

We believe that environmental managers and natural resource managers should be on the lookout for a range of common biases that have the potential to adversely impact natural resource management. Based on what we know about these biases there is evidence to expect that managers:

  • are likely to undertake on-ground actions even when these are not worthwhile;
  • could suffer from the cognitive illusion of being more in control of the system than they actually are;
  • could be overconfident about the expected outcome of their decisions;
  • may be overly optimistic about the expected completion time of the project;
  • might rely on a partial set of information for decision-making even when more complete information is available;
  • might rely 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
  • could try to achieve predefined goals rather than the best possible outcomes from a project.

There are many things that can be done to help minimise the impact of bias.

First, agencies need to promote a culture of learning. It needs to be recognised that both successful and failed projects generate valuable information about the future state and expected impacts of the management interventions. This could be done by providing appropriate incentives for the managers and decision-makers to consider the full range of options before making any decision, or asking managers to justify their decisions to external parties.

Second, adoption of a decision support system could facilitate the retention and storing of relevant information. It may also make learning from past projects easier and help in systematic evidence-based decision-making. Of course, relevant staff should be adequately trained and properly incentivised to use such systems.

Third, conducting benefit–cost analyses of planned options would help to refine and prioritise the options during the design phase of an adaptive management cycle. Benefit–cost analysis provides a systematic and objective framework to include all relevant costs and benefits related to a project.

Fourth, involvement of external third-party reviewers may also help in designing more realistic and feasible projects.

Finally, scenario analysis should be conducted as part of the assessment and design phase to anticipate the expected outcomes of different options. It’s advisable to consider the likely impacts of different types of biases and the effectiveness of potential remedial measures before making any final recommendation for use in decision-making about natural resources.

Sayed Iftekhar and David Pannell are members of the ARC Centre of Excellence for Environmental Decisions. They are based at the University of Western Australia.