By Joslin Moore (This article was first published in the March 2013 issue of Decision Point, The Monthly Magazine of the Environmental Decisions Group)
How much should we invest in learning as opposed to doing when it comes to conservation management? Keep in mind that investing in learning is taking resources away from the management itself, and may even lead to delays in getting on with the job. Of course, if you have a good idea of the nature of the problem you’re managing and the benefits of learning then it’s relatively easy to weigh up your options. However, if there’s substantial uncertainty around the issue, as there is with most conservation problems, then it’s a different story.
A common response to this vexed issue of learning versus doing in the face of great uncertainty is simply to ignore the issue – we make the best decision that we can based on what we know (or don’t know) and trust our intuition. Unfortunately, intuition is usually a poor guide in dealing with complex conservation issues in the face of high uncertainty.
A better way is to apply a framework of structured decision making together with a value-of-information analysis to identify robust management strategies. How does this work? Consider how we applied this approach to develop a long-term management strategy for the invasive gray sallow willow up on the Bogong High Plains (Moore & Runge, 2012). The stakes are high (see box 1) with the prospect of this very invasive willow taking over an endangered alpine ecosystem. There is great uncertainty surrounding the available options and, looking into the future, this is compounded by a changing climate and shifting fire regimes.
Structured decision making involves working with key stakeholders involved in a problem to create an agreed framework around the decisions they need to make. The process we use comprises seven steps (outlined in figure 1). It involves setting a context, agreeing on objectives, listing the various available options to meet these objectives and devising ways to compare the costs and benefits of those options
Supporting decisions around willow management
To go through this process with the willows problem we ran a three- day structured decision making workshop. It emerged during this time that the major decision faced by the willow managers was where to focus their control effort. The removal of willows from EPBC listed alpine bogs was identified as the main objective of management so the control of willows in bogs seemed a good place to start.
“Intuition is usually a poor guide in dealing with complex conservation issues in the face of high uncertainty. A better way is to apply a framework of structured decision making together with a value-of-information analysis to identify robust management strategies.”
However, willow establishment is facilitated by wildfires which are predicted to increase with climate change. Should some effort be allocated to removing mature seed-producing willows in nearby waterways to prevent invasions in the future? If so, how much effort? In the absence of a strategy, managers had been allocating effort to bogs and waterways guided by a combination of intuition and available resources.
We used structured decision making to formally describe this decision (figure 1). We built a stochastic model of the spread of willow onto the Bogong High Plains and used it to calculate how different management strategies would affect the amount of willow in bogs over the next 200 years. The model contained approximately 40 factors or parameters, most had never been measured and were highly uncertain. We incorporated this uncertainty into the model by choosing parameters from probability distributions (that represented our uncertainty about the parameter values) and re- running the model 10,000 times.
Box 1 Gray sallow willows on the high plain
In 2003, a severe wildfire burned out half of the Bogong High Plains, Australia’s largest contiguous area of alpine and subalpine vegetation. The event was followed by the widespread establishment of seedlings of the gray sallow willow (Salix cinerea), a multi-stemmed invasive shrub native to Europe.
That spells big trouble for the Plains. The gray sallow is one of the few willow species able to produce seed in Australia. It can inhabit a wider variety of environments than other introduced willows and is the only Salix known to have colonized Australia’s alpine regions. The species reproduces predominantly by seed but does not form a persistent seed bank. Seeds are wind dispersed and can disperse tens of kilometres, and the species is also able to regenerate after fire.
The big fear is that willows will destroy the precious bogs found in the Bogong High Plains. The bogs are listed as endangered under the EPBC Act and invading willows compromise them by reducing available water (these willows use large amounts of water compared with native species), displacing native vegetation, and disruption of aquatic nutrient cycles. Parks Victoria, the agency responsible for management of the Bogong High Plains, considers the invasion by gray sallow willow as one of the main threats to persistence of the bogs.
So what’s to be done given limited resources and enormous uncertainty about how the threat will develop? Parks Victoria wished to identify a practical and effective long-term strategy to eradicate (or minimize) willows in bogs on the Bogong High Plains. The key decision to be made was the proportion of resources to allocate to the management of existing populations of willow in bogs and to source populations of willow that may serve as sources of colonists in the future.
There is also substantial uncertainty regarding the demographics of gray sallow willow populations and the source of the current invasion. Given this uncertainty, the management agency wished to decide where to focus control effort and whether the management strategy could be improved through learning
Using the model, we identified where control effort should be focused to minimise the abundance of willows in bogs over the longer term. This was done by calculating which management alternative worked best on average across the 10,000 possible scenarios.
The optimal strategy was to allocate all available effort to the bogs until the budget exceeded 2,000 work days per year. It needs to be noted that 2,000 work days per year is four times the current budget levels. Beyond this point it was optimal to allocate some effort (20-60% total budget) to eliminate populations of seed- producing willows in nearby rivers. Effort was allocated to the closest populations first and then to more distant waterways as the budget increased.
We also identified which parameters had the biggest influence on the spread of willows (using sensitivity analysis). The analysis showed that the most important factors in determining the spread of willow was the frequency of fires, the mean dispersal distance of willow seeds and the rate that bog vegetation recovered after fire.
Should we invest in improving our knowledge?
Finally, we calculated the value-of-perfect-information. The value-of-perfect-information is a deceptively simple calculation that enables us to identify how much we could improve our management decision if we had perfect knowledge prior to making it (in this case if we actually knew what the parameter values were in the model before we made our decision). It measures the maximum amount that we could expect to improve the outcome if we could resolve all the uncertainty.
The results of the value-of-information analysis were quite surprising for managers. It revealed that learning more about the system is unlikely to improve the ability to manage willows unless current budgets are substantially increased. The increase in performance if information is perfect is negligible for small to medium budgets because the same strategy (only treat willows in bogs) is optimal for the majority of the 10,000 scenarios. When budgets are large, the best location to control willows depends on the specific scenario (parameter values) although the improvement was modest (~10%). In these cases, learning about willow seed dispersal distance was the most important.
Although the most effective management strategy was clear, there was substantial uncertainty about the effectiveness of the strategy even when the best management action was taken. Sometimes, there were scenarios when any of the proposed management interventions would fail. This uncertainty makes it difficult to justify budget allocations to willow management when there are competing demands for resources. Improving understanding of fire frequency, bog recovery rates, and dispersal from source populations would contribute most to informing decisions about budget allocation to willow.
Did the process help?
Taken together the key conclusions of the workshop and analysis were that the objective of management was to protect endangered bogs from willow invasion. The best way to achieve this (given current budgets) was to focus exclusively on controlling willows within bogs although there was substantial uncertainty regarding how successful management would be.
Unless budgets increased substantially, investing in research or adaptive management to learn about the system and resolve key uncertainties (fire frequency, willow seed dispersal distance, bog vegetation recovery rate) would not improve our ability to manage the system. If budgets did increase substantially, learning about willow seed dispersal distance would contribute the most to improving management.
While these conclusions may seem obvious in retrospect they were not obvious to managers prior to the workshop. Less than 50% of control effort was focused on bogs when the willow control program was first instigated.
Despite enthusiasm from managers, it has taken approximately 18 months for the results to be fully integrated into the management process. Although managers started to allocate increased effort in bogs in the 6 months following dissemination of the workshop results, it was not until the second control season that all control effort was allocated to bogs.
Structured decision making and value-of-information analysis can be applied to any problem where a decision needs to be made. Together they provide a relatively simple way to make a decision in the face of uncertainty and evaluate the need for learning.
Of course, it helps if you have a decision scientist assisting you in building the models and running the analysis. So, if you have a tough and important decision coming up, see if you can interest a decision analyst in your problem today!
Moore, J. L. & Runge, M. C. (2012). Combining Structured Decision Making and Value-of-Information Analyses to Identify Robust Management Strategies. Conservation Biology, 26, 810-820
- Saving Aus wetlands from willows (sciencealert.com.au)