Effective conservation is all about making smart decisions

Prioritising what to do, where and when

By Kerrie Wilson (Director, CEED)

What? where? and when? If we could answer these three little questions when it comes to allocating our available limited resources to saving species and ecosystems then we would be going a long way towards fixing the biodiversity crisis as it unravels around us.

Smart decisions for the environment involve allocating available resources both efficiently and effectively. They are about answering the what?, where? and when? questions that face conservation policy makers and managers every day.

Yes, they are little questions but solving them requires careful consideration. These are, however, the very questions that can be solved using the principles of classic decision theory. This framework encapsulates the key elements of any problem, including the objective function, knowledge of the system, control variables, and constraints. This type of thinking is key for good environmental decision making yet, to my knowledge, most undergraduate and Masters programs rarely offer such teachings.

In its most basic form, ‘Decision Theory 101’ goes like this: In all problem formulations, the objective function reflects our goal. Importantly, it needs to include an explicit measure of performance. Conservation goals might be related to protecting species or preventing them going extinct. Often there is more than one objective, which means that trade-offs will likely be invoked and compromises must be made. Making those trade-offs explicit is key to good decisions because once they are clear the choices then become transparent.

What we are required to know about the system (the system knowledge) will depend on the particular problem at hand. In the context of conservation prioritisation, we might want to know where the species of interest occur, or the distribution of ecosystem types and the environmental and anthropogenic factors that determine these distributions, or the patterns of water flows through a catchment. We may also want to know what the threats are to the species and ecosystems, what actions can be taken to abate these threats, and the cost of carrying out those actions. And these factors may vary over the area of interest and through time.

The control variables reflect the options available to us. In the context of conservation prioritisation, we control how much money or resources we direct towards different conservation actions in any location and at a particular time.

The constraints limit the choice of control variables and may include a budget or how many parcels of land can be restored each year due to operational and seasonal limitations.

The overall aim of a prioritisation analysis is to find the best solution through manipulation of the control variables that has the highest possible value of the objective function subject to our constraints. While optimal solutions might be desired, multiple near-optimal solutions are often sought for the sake of flexibility and the ease of calculation and communication.

Now you know all the ingredients for solving a conservation problem. It’s not rocket science and, indeed, it’s not even new; decision theory has been around for centuries and can be applied to many problems (including how to organise your weekly shopping through to planning your next holiday). However, the application of decision theory to the environment (and specifically biodiversity conservation) is only a recent development, and CEED has made many important contributions to how decision theory can be applied to generate smart environmental decisions.

So, what types of actions might we undertake (and when) for the environment? In contemporary Western society, the creation of protected areas has traditionally been the primary action to achieve conservation goals. Natural resource managers routinely invest in a diverse array of activities such as fire management, invasive species control, and habitat restoration, either in protected areas, or on government-owned or privately owned land.

In many places, land acquisition simply isn’t feasible or appropriate. More recent approaches to conservation prioritisation seek to prioritise between multiple actions (and locations) to achieve conservation objectives. Some approaches are also dynamic, capable of prioritising actions through time as well as over space.

In dynamic versions of the multiple-action prioritisation problem our management decision is how much of our budget to allocate to each environmental action at each time step. For each action we need to know what it costs per unit area and the benefits that will be delivered. We can then generate dynamic investment schedules that reflect shifts in the allocation of funds as the return from investing in each conservation action diminishes and as uncertainty associated with the relative effectiveness of actions is reduced.

A significant next frontier in conservation prioritisation is the inclusion of predictive models of human behaviour to better capture socio-ecological dynamics.

All of which suggests there is considerable complexity and sophistication behind a truly smart decision. Though we should never lose sight of the fact that behind all of these calculations we are still answering those three basic questions in our decision making: What?, where? and when?

More info: Kerrie Wilson, k.wilson2@uq.edu.au

This is an edited excerpt from Kerrie Wilson’s recent reflection on ‘smart decisions on the environment’ (Wilson 2018).


Wilson K (2018). Smart decisions for the environment. Pacific Conservation Biology. https://doi.org/10.1071/PC18036

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