Learning from observational data to improve protected area management

Human-caused environmental destruction is a major challenge to the sustainability of life on earth. For effective solutions, we need to learn about damaging behaviours and discover how best to encourage change. Exciting developments in fields concerned with human behaviour (such as economics and psychology) are helping to explain why people make the decisions they do. In parallel, ecologists have developed sophisticated methods for analysing data collected by ordinary people ("citizen scientists"), aided by new technologies such as smart phones. Up to now, these developments have remained separate, but closer integration would benefit both science and practice. Behavioural scientists would gain from the adoption of powerful new analytical techniques from ecology, which enable them to use data collected in new ways to understand how humans interact with the environment. Ecologists would benefit from being able to include a solid theoretical model of human behaviour into their understanding of how ecological outcomes arise from human actions. Managers and policy-makers will benefit from evidence-based understanding of how to change behaviour in the real world.

To illustrate how powerful this combination of approaches can be, we will apply them to a key problem facing global conservation: how to manage protected areas so that they can act as effective refuges for endangered species in the face of illegal poaching and other threats. Learning about illegal behaviour is difficult because those involved are rarely willing to talk openly, so the 'conservation detective' must make deductions from other sources of information. Many conservation organisations now collect reports made by the rangers who patrol parks. This is potentially very informative, but also potentially very misleading. Consider snaring as an example: a ranger seeing a snare is the outcome of several interacting processes (where the poacher decides to lay their snare, where the ranger decides to patrol, and whether the ranger spots it in the undergrowth), and removing that snare may affect the future decisions of the poacher; so the data are the product of a game of cat-and-mouse played out in a dynamic landscape. This makes patrol data very hard to interpret.

To tackle this issue we will build two types of computer model to explore how rangers and poachers interact with one another and their environment: i) conceptual models of the underlying processes that lead to the observation of a snare, based on ecological and behavioural theory and our understanding of our system, with simulated patrol records as their outcome; ii) statistical models that start with the snare data, and see which combination of factors best explains it. Building both models means that each can be used to inform the other. We will test the models in two ways; firstly in an abstract system, where we can vary the behaviour of the patrollers and poachers and the environment in which they interact, and see how this affects the resultant patterns of snare observations, and secondly in a real-world system, the Seima Protection Forest in Cambodia. Here we have substantial existing knowledge to help us to build our models, and will collect new information to improve our understanding. Our work will also be able directly to inform their conservation strategy.

For the first time it will be possible to paint an accurate picture of illegal behaviour within parks and to give managers scientific advice about how to design their patrols. We will also explore how this novel approach can be used more widely to tackle other environmental issues. For example, large numbers of people participate in bird surveys each year, and local communities are increasingly collecting information so that they can manage their own resources; our work will lead to rules of thumb for how best to analyse these types of data. This could be useful to a wide range of ecologists and practical users of observational data.

The problem of improving enforcement in and around PAs currently has a very high profile (e.g. the issue of poaching was raised on the floor of the United Nations General Assembly as a "threat to the rule of law" during their 63rd annual meeting) and there is an increasingly strong desire to improve the evidence-base for conservation actions amongst donors, governments and conservation organisations. This project will produce tangible benefits for multiple user groups at local, national and international scales, including conservation practitioners, governments and international NGOs.

At the local scale, our research will directly benefit the managers of our case study site by providing them with guidance on the interpretation of ranger-based monitoring data and the robust, scientific evidence about the effectiveness of alternative enforcement strategies that they need to manage effectively. WCS Cambodia represents a key local user group for our research outputs, and has been closely involved in the development of our research proposal to ensure its relevance and acceptance.

At the national scale, the Cambodian government will benefit from the pragmatic guidelines we will produce which will show how the enforcement of protected area regulations can be optimised in order to achieve conservation goals and help to determine how the limited resources available for conservation should be deployed. Our partnership with WCS Cambodia will enable us to build on their excellent relationship with Cambodian government agencies.

The Convention on Biological Diversity recognises that PAs represent a global public good "[constituting] an important stock of natural, cultural and social capital, [and] yielding flows of economically valuable goods and services that benefit society, secure livelihoods, and contribute to the achievement of Millennium Development Goals" (www.cbd.int). The crucial contribution of PAs to quality of life throughout the world depends on them being effectively managed. At the international scale, our research will draw out general lessons for successful PA management. Even in the absence of rigorous understanding, patrol datasets are already used to make decisions about park management in many areas of the world, so the practical guidance that we produce can deliver immediate benefits.

The broad partnership contributing to the SMART programme demonstrates a clear commitment of the conservation community to adopting a more rigorous, scientific approach to enforcement. MIST has been implemented in countries across the globe and SMART is already being implemented in 120 protected areas (e.g. http://www.smartconservationsoftware.org/pilot), including Seima Protection Forest. By collaborating with the SMART consortium in development of our research, the outputs of this study will have unusually high potential to contribute directly to improvements in conservation practice.