Competition and conflict in Victorian waterfowl management
In this paper Associate Professor Graham Hall and Alison Cash from the University of New England question where Victoria is heading with waterfowl hunting.
In the long and proud history of waterfowl hunting in Victoria, 2016 will surely go down as a year of poor decision making and very poor communications.
Much of the confusion can be directly attributed to the way the animal rights groups seduced the politicians and bureaucracy with misinformation, halftruths and downright lies, but some of the confusion also arose from hunters.
For example, during the annual collection of head and wing samples from harvested ducks we often observed amongst hunters that they viewed management, research and monitoring activities distinctly.
‘Management’ was typically viewed as the bureaucratic aspects of conservation: preserving and managing habitats, regulating harvest, and other aspects of government work.
‘Research’, although recognised as important, was often viewed as less important than monitoring, and certainly than management; somewhat as a luxury of outside academics that should be performed, but only if sufficient time and funding permit.
‘Monitoring’ was viewed as a way of assessing the status of populations, communities and ecosystems, but typically was not formally connected to conservation decisions.
Here, we suggest that management, research and monitoring are actually complementary, not competitive activities. All three are important to successful conservation, and loss of any one of the three disrupts the other two.
Management is simply taking an action to obtain some desired outcome. It requires a range of alternative actions that can be taken, and specification of an objective that we are trying to achieve. Examples of management include: the application of prescribed fire to increase or improve habitats and, presumably, sustain larger populations; the setting of harvest regulations to provide hunting opportunities; and the declaration and maintenance of game reserves to maintain species diversity and hunting opportunities.
Research is a process of inquiry that includes description of natural systems, but also involves addressing questions about how these systems function. Thus, research could include testing and quantifying the relationships between waterfowl numbers and water levels.
Monitoring involves the observation of various locations over time, and may be simply oriented toward establishing trends in waterfowl numbers, but may also be connected directly to research (by providing answers to testable predictions) or management (by providing feedback about the results of management actions).
Field & Game Australia is involved in all three activities through the waterfowl season-setting process (management), the duck head and wing program (research), and the twice-yearly waterfowl counts (monitoring).
The reality is that uncertainty nearly always confounds a simple decision. That is, the manager can never have 100 per cent certainty that any given decision will result in the desired outcome.
Management uncertainty comes in four basic types: environmental uncertainty, partial controllability, partial observability and structural uncertainty. One basic but important form of uncertainty is that habitats and populations are influenced by factors that may not be under management control.
For example, managers may decide to declare a hunting season, but an unusually severe summer may occur that results in a lower than predicted number of ducks.
Likewise, even if managers don’t declare a hunting season, favourable factors may cause the population to perform better than predicted.
The influence of factors in the environment that are unpredictable, and that add to the influence of the management decisions, is termed environmental uncertainty. A similar result
An excellent example of poor decision making because of uncertainty occurred in Victoria in 2016 when the appearance of protected blue-billed ducks resulted in the hasty closure of Lake Elizabeth Game Reserve to hunting.
can occur because the management itself is only partially controllable; for instance, as we saw in Victoria in 2016 the appearance of non-game species of ducks caused much anguish to hunters due to bureaucrats closing some Game Reserves.
This is referred to as partial controllability. In addition to these ‘real’ sources of uncertainty, monitoring programs generally will not be able to perfectly measure the systems response to any management. Especially when we are monitoring abundance and other population or habitat attributes, these will usually be based on some type of statistical sample, and thus subject to error. This is referred to as partial observability, or sometimes, statistical uncertainty.
Finally, in addition to all the above sources of uncertainty, current knowledge is based on past observation and research. However, this past knowledge is seldom completely accurate, and is often very incomplete. Unless we are absolutely certain about the basic mechanisms that determine our system, we should be honest and admit that our knowledge about how the system works is not perfect. We refer to this last source of uncertainty as structural uncertainty. Seen in this light, structural uncertainty is both a research issue — it occurs because our understanding is imperfect — and a management issue — resolving or reducing it leads to better decision making.
Although there are several possible ways of dealing with uncertainty, ignoring uncertainty can have severe consequences. Failing to deal with uncertainty may lead to a false sense of security in decision making and ultimately compromises our ability to reach our conservation objectives. But the converse is also true. If we allow uncertainty to paralyse or stop decision making, this too will lead to poor conservation outcomes.
An excellent example of poor decision making because of uncertainty occurred in Victoria in 2016 when the appearance of protected blue-billed ducks resulted in the hasty closure of Lake Elizabeth Game Reserve to hunting.
Instead of allowing the lake to remain open to hunting, and monitor any effect of hunting on disturbing non-game ducks, the lake was closed, thus depriving managers of valuable information for future management. Alternatively, an exclusion zone could have been established around the deep water part of Lake Elizabeth where the blue-billed ducks had congregated and where hunting or disturbance would have been specifically prohibited.
Such adaptive and proactive management would have been preferred to the heavy-handed response of a hunting ban and closure of the entire Lake Elizabeth State Game Reserve.
Some types of uncertainty, such as environmental uncertainty, are essentially impossible to control. These must be considered in decision making, but in all likelihood cannot be reduced. Others can be at least partially reduced by better field techniques that may reduce (but likely not eliminate) partial controllability and better survey methods may reduce partial observability.
The use of unmanned aerial vehicles to monitor waterfowl populations is a good example of better, safer and cheaper survey methods.
Special attention should be devoted to structural uncertainty, because it is the one source of uncertainty that 1) is very frequently ignored, and 2) can be reduced through time via an adaptive approach.
Before discussing adaptive approaches, two other major approaches deserve mention that can be used to reduce structural uncertainty, because the public is likely more familiar with these approaches, they have occurred more frequently, and they continue to have merit.
Experiments — which are defined as involving control, randomisation, and replication of independent subjects — are the “gold standard” of scientific inquiry. Experiments are ideally capable of reducing uncertainty very quickly, and thus are attractive. However, realistic experiments at any meaningful scale are difficult or impossible to conduct in most conservation systems.
In addition, because experiments are directed at scientific hypotheses, rather than management objectives, they are not necessarily efficient means of reducing uncertainty for decision making.
In contrast to experiments, retrospective studies are based on an examination of patterns in data that have been collected in the past; thus they are analysed “retrospectively”.
These often can provide a good initial basis for the construction of alternative hypotheses and predictive models used in conservation.
Without denying the importance of both experimentation and retrospective analysis, we advocate a third approach, called adaptive resource management (ARM), as being generally more suited to conservation decision making.
ARM can be implemented in virtually any resource system, and has the advantage of being directed at meeting the conservation objective, not at meeting a scientific objective. ARM is the method advocated for waterfowl management in 2009 with the publication of Developing a sustainable harvest model for Victorian waterfowl. (Arthur Rylah, Institute for Environmental Research Technical Report Series No. 195)
Hunters are entitled to ask why, after the passage of seven years and the establishment of the Game Management Authority, is ARM not yet implemented in Victoria?
ARM consists of three essential components. The first is explicit predictions of the effect of management actions on population size and harvest under two or more models. These models provide the means for comparing the relative support for different management actions. Here, structural uncertainty is expressed in the form of alternative models. Predictions are made under each alternative model,
weighted by the relative support for the model, and decisions then are made based on comparing the predictions associated with each management action.
Sequential decision making is another requirement of ARM and involves tracking a population or habitat through time and making decisions based, in part, on the observed status of the population or habitat condition.
The set of management objectives and actions are usually constant, so that the same decisions are continuously revisited. In theory this is the season-setting process in Victoria whereby duck numbers and waterbodies are monitored.
Unfortunately, politics and weak bureaucracy often inhibits such an obvious and crucial process!
Sequential decision making need not take place on an annual basis and can occur in space as well as in time. The former is particularly useful in situations where decisions will not be revisited at a particular site on a short time scale but are made over a number of sites — for example, the whole of Victoria.
Information feedback, in this sense, is used to improve future decisions at sites that have yet to be managed. Regardless of whether sequential decision making is through space or time, the key is to provide feedback on the effects of management actions in a timely manner to improve future decision making.
Monitoring is the third required component of ARM. It provides information that is used to resolve key uncertainties. To resolve this uncertainty, it is important to determine the model that best approximates the system dynamics and then update the model to reflect newfound knowledge.
Operationally, this is accomplished by comparing model predictions to subsequent observations of the population size. The general approach is to use modelling to account for these factors. This is important, both because it gives a more honest picture of the rates of learning under ARM, and helps to direct research and monitoring priorities for reducing uncertainty.
Although ARM is a useful approach to managing gamebirds, to our knowledge, curiously ARM has only been formally applied to waterfowl harvest decision making in non-australian jurisdictions.
The failure to implement ARM in Australia is partly due to institutional resistance, but we think it is also attributable to widespread misconceptions.
Perhaps the most common misunderstanding is that ARM is research. First and foremost, it is management.
The primary objective of ARM is to make the best decision with respect to management objectives. Learning occurs as a by-product of management rather than experimentation. In fact, experimentation can be suboptimal because the population or habitat can be driven to a state that is undesirable. In ARM, the goal of learning is to reduce the uncertainty that has the greatest direct impact on decision making. Thus, learning is targeted on those key components that result in improved decision making and presumably, greater gains.
Another common ARM myth is that it is too risky. We contend that natural resource decision making is inherently risky, and decision making is always fraught with uncertainty. Hence, all management actions (or inactions) can have unintended and unanticipated consequences. Uncertainty can be reduced by the acquisition of greater knowledge through study and experimentation, which can take considerable time. Management decisions, however, should not be delayed until sufficient knowledge has been acquired. This is the fallacy of the Precautionary Principle which bureaucrats often hide behind, claiming that without perfect knowledge no management decision can be made.
Beliefs that ARM is costly and complicated also are unfounded. Given the right attitudes most agencies can perform most of the tasks required for ARM now, so it should not require additional expenditure.
Management, research and monitoring are all crucial for natural resource conservation and the loss of any one of these elements reduces the effectiveness of the others. The elimination of research often results in stagnation, where new scientific ideas do not become part of management. This also perpetuates a false separation of “management” from “science,” thereby reducing the effectiveness of the former and eliminating the context for the latter.
Similarly, the elimination of monitoring reduces the effectiveness of management because decision makers no longer have a basis for judging the effectiveness of different management objectives. Without the feedback provided by monitoring, there is no ability to assess model predictions with data, which eliminates the potential for learning about how systems operate.
Management, research and monitoring programs should be viewed as mutually supportive of conservation goals, where the loss of any one of the three is disruptive to the remaining two.
Management explicitly includes the goals of the decision maker and other stakeholders in evaluating the possible consequences of any potential action. Research allows us to explore the possible consequences of management actions, which can be used to compare alternatives and select the most appropriate action. This leads to a decision that appears most likely (taking into account uncertainty) to achieve the desired outcomes. Monitoring provides information to assess if stated goals are being achieved or if a divergence has occurred. It also provides information feedback that allows testing of the predictions of decision models, and reduce uncertainty through time.
This “closed loop” process, known as ARM, formally integrates management, research and monitoring for more effective natural resource decision making.
All three of these legs — management, research and monitoring — are essential to sound conservation. Removal of any one of the legs is disruptive to conservation, and ultimately counterproductive. In particular, actionoriented management is sometimes pitted against research and monitoring in the competition for limited funds. This sets up a false choice, a bit like asking whether children need food or education in order to become productive adults.
In contrast, under ARM, research and monitoring have explicit value for their contributions to decision making. Conversely, we “learn by doing”, with management actions providing the grist for the testing of critical assumptions, ultimately reducing uncertainty and improving decision making.
Associate Professor Graham Hall observing ducks at Lake Elizabeth near Kerang
