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Identifying early risks for environmental policies

May 13, 2016

A rusting ship on the dry Aral Sea. Image: kvitlauk | Creative Commons

We live in a world that never stays still.  People and places are ever more globally interconnected, dynamic and developing. Technological innovations feed into new cycles of use, waste and pollution.  Ecosystems flux over time and space through invasions and introductions, novel assemblages and emergent patterns.

Circling all of this, scientific consensus predicts an increasingly variable and warming climate in the century to come.  An age that could well be ratified later this year as a new geological epoch, fundamentally shaped by human activity and known as the Anthropocene.

How can environmental policy makers deal with such complexity and dynamism in a world they seek to positively influence?  How can environmental policies anticipate the changes of uncertain future worlds? And what research programs, early warning systems and governance structures are needed to make such ‘anticipatory policy making’ a reality?

A new Science for Environmental Policy ‘Future Brief’ addresses these questions by examining a range of tools and approaches that can be used to identify emerging environmental risks. The approaches examined include strategic foresight tools, scanning of the internet for information, citizen science and state-of-the-art monitoring technologies. Produced for the European Commission DG Environment by the Science Communication Unit, UWE in Bristol, the Future Brief then discusses the policy implications of this range of new approaches.

The Brief contains many examples of new developments from freshwater science and policy, and is summarised below.  It can be read in full here.


Two key terms can help us better understand the issues raised by the Future Brief. Risks may be predicted and/or detected by early warning systems such as river gauging networks and remote sensors. Identifying and quantifying the risk of flooding, for example, at an early stage gives environmental managers a better chance of mitigating its negative effects (e.g. through evacuation, temporary flood barriers, provision of clean water and food, and so on).

The UNEP defines four key elements for early warning systems: risk knowledge, monitoring and predicting, disseminating information, and responses.  However, the authors of the Future Brief suggest that one or more of these elements is usually lacking in the real world. The Brief outlines the many challenges in designing early warning systems, particularly in the trade-offs between rapidity of response and accuracy of risk detection; and the need for decision-making using partial or uncertain monitoring data.

Whist environmental monitoring is increasingly supported by the European Commission for identifying threats, such early warning systems need to be constantly developed and updated to account for emerging environmental risks. Emerging risks are risks that are new; or familiar risks that are presented in new or novel conditions.  An example of an emerging risk is the growing number of new chemical pollutants entering freshwater systems, as addressed by the EU SOLUTIONS project. Emerging risks can be organised by their ‘knowability’.  Using a NASA typology (made famous in a Donald Rumsfeld speech), emerging risks may be:

  • Known knowns: risks we are aware of and understand;
  • Known unknowns: risks we are aware of but do not understand, usually due to a lack of comprehensive research (as is the case for multiple stressors in aquatic ecosystems);
  • Unknown knowns: risks we understand but are not aware of;
  • Unknown unknowns: risks we are neither aware of nor understand.

Of these risks, ‘Unknown unknowns’ pose a big challenge. These are risks that emerge from new or unknown hazards (for example, new pollutants or rapid climatic changes) that if undetected may lead to major environmental problems.  Catastrophic examples of these (for example the 2004 Indian Ocean tsunami) are termed ‘black swans‘, or extremely rare and unpredictable events.

Despite this uncertainty, increasingly advanced and adaptive environmental monitoring systems allow us to predict emerging risks.  The new Future Brief examines five of these approaches.

Early warning signals from foresight approaches

Foresight approaches gather information on different future possibilities for natural and human systems to predict the range of trajectories they make take, and design suitable management strategies to mitigate emerging environmental risks. The two main foresight approaches are horizon scanning and scenario planning.

Horizon scanning involves compiling and reviewing all available research and monitoring data on an topic to identify emerging issues and knowledge deficiencies. For example, the UK based Cambridge Conservation Initiative undergo a yearly horizon scanning exercise for global conservation issues (download the latest one here).  Horizon scanning was used by the 2013-15 review panel for the Ramsar Convention, an international treaty for the conservation and sustainable utilisation of wetlands, to identify emerging issues for wetland policy and conservation.

Scenario planning is a broader and more speculative means of anticipating future environments.  Often based on a mix of historical data, expert judgement, stakeholder inputs and predictive models, scenario plans develop a range of narratives on how the world might develop in the future. Scenarios are particularly useful for imagining emerging low-probability ‘unknown unknown’ risks.  One recent freshwater example of scenario plans are those developed by the MARS project, predicting the future of Europe’s freshwaters.

Early warning signals from technology

Technological advances allow scientists and policy makers to predict many emerging risks with increasing precision. Monitoring technologies can range in scale from tiny water pollution sensors in individual water bodies, to satellites orbiting the earth to detect global rainfall patterns.  Chemical monitoring of European freshwaters has historically focused on ‘known known’ priority substances in the Water Framework Directive: those which are known to cause harm to aquatic life and water quality.

Techniques to detect ‘unknown’ chemical pollutants in freshwaters include ‘non-target screening‘ using liquid chromatography to separate the elements found in a water sample, and bioindicators and bioassays which determine the presence of a pollutant through known effects on other biological elements.  Such monitoring systems can give continuous data-streams of information on pollutants in an ecosystem.

The EU SOLUTIONS project is working with new monitoring technologies in an effort to better assess and monitor clusters of emerging chemical pollutants in freshwaters.  Here, ‘multiple stressor‘ effects add another layer of uncertainty to our understanding of emerging risks.

Early warning signals from citizen science

Environmental citizen science involves members of the public monitoring patterns and processes in the natural world.  An evolution of historical amateur naturalist groups, citizen science programs often now take advantage of cutting-edge technologies such as smartphones, apps, GPS and portable microphones to allow the public to quantitatively document elements of the environment.  The data collected – species identifications and counts, invasive species monitoring, water levels, and so on – can then be brought together to give environmental managers up-to-date information on changes in the environment.

Such indicators – for example, the spread of an invasive species such as the signal crayfish – can provide early warning systems in areas not covered by scientific monitoring programs.  Citizen science is not without its challenges: often relying on public access to (often expensive) personal technologies, often focusing on terrestrial environments only, and requiring investment in digital training and infrastructure to ensure that the data collected is as accurate and appropriate as possible.

Early warning signals from online media monitoring

Like citizen science, media monitoring is an old approach that is being increasingly invigorated by modern technologies.  Scanning software is being developed to monitor keywords and phrases in online public communications such as social media, discussion boards and news-sites.  Details of emerging risks and threats to the environment can then be ‘crowdsourced’ through monitoring online discussions.

For example, MediSys is an internet monitoring and analysis system that scans information from the European Media Monitor software that gathers reports from worldwide news portals – in 60 different languages – to rapidly identify potential threats to public health. These threats include toxins, bioterrorism, bacteria and viruses, pesticides and nuclear threats amongst others. MediSys is used by the European Commission Health and Food Safety Directorate-General to provide automated early warnings of emerging threats to human health to policy makers and the public.

Early warning signals from rate-change theories

In recent decades, our theories of environmental processes have broadly shifted towards complexity, dynamism, chaos and uncertainty.  So called ‘state-shifts‘ have become a key topic for systems ecologists, describing how ecosystems can shift abruptly and irreversibly from one state to another (e.g. forest to savanna) in response to stress and alteration.  The biologist Paul Ehrlich used a ‘rivet popping’ metaphor to describe how an altered ecosystem may act like an aeroplane which is gradually having its rivets removed in flight.  In Ehrlich’s metaphor, species are the rivets holding an ecosystem together, and their extinctions are like rivet removals. The aeroplane is likely to stay in the air for some time, until a ‘tipping point‘ is reached when it falls apart and crashes (although metaphor has been questioned, for example by Richard Hobbs and colleagues).

Whilst it is difficult to accurately predict such tipping points, systems theorists are increasingly developing a theory known as Critical Slowing Down to give early warnings of when a system may be approaching a critical threshold.  For example, ecologist Steve Carpenter and colleagues undertook a long-term experiment in an American lake (pdf) to identify statistical early warning systems for state-shifts in the aquatic food web.  Over three years, they gradually added largemouth bass – a top predator – to the lake.  This caused a state-shift from an algae-filled ecosystem with abundant prey fish populations to a clear lake dominated by the bass.

Working with critical slowing down theory, Carpenter and colleagues identified changes in the food web in the year before the ecosystem’s tipping point.  Such research is extremely useful to environmental managers and policy makers seeking to implement continuous monitoring programs, providing new approaches for early warning systems which detect potential significant environmental changes.


The range of approaches outlined by the new Future Brief demonstrate how new technologies, theoretical advances and better monitoring data are all helping policy makers deal with an increasingly complex and dynamic world.  The challenge is to address the needs of current societies and environments, whilst anticipating how they might change in the future.  You can read the Future Brief in full here.

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