Early warning signals for monitoring supplies

Q: Data integration and systemic barriers

9. In the UK , data and models听largely remain听siloed across climate, biodiversity, hydrology,听agriculture听and forestry, which prevents consideration of routine, integrated听early鈥憌arning听indicators at national scale. a. Many universities, businesses,听non-governmental organisations (NGOs)听and citizen science groups already听monitor听environmental data. An effective early warning system should draw on and compile these听sources, and听not rely solely on government datasets. 10. Government鈥慶ollected听environmental datasets are often not听open access. They can lack consistency and be fragmented across different projects and ecosystems. Data usability is a major barrier, with many datasets difficult to access or interpret without specialist training. This reduces their value for researchers and policymakers and hinders听evidence鈥慴ased听decisions. a. For example, satellite remote sensing can already detect droughts, heatwaves,听floods听and peatland water loss, but access to government data (for example,听National Forest Inventory) is constrained, which hinders calibration and measurement of uncertainty. 11. International examples show that integrated, rapid monitoring is feasible, but the UK lacks equivalent systems and infrastructure to manage growing data volume, data diversity (the different types of data required to fully support modern ecosystem monitoring) and complexity (including novel ecosystem and microbial data). a. Improving domestic recycling and processing capability would reduce reliance on imported raw materials and overseas processing.

Question 1

Summary of roundtable findings

Accepted Answer

Single indicators of risk to ecosystems often miss cascading disruptions across food,听water听and timber supplies.

Complex ecosystems, such as boreal forests, are especially difficult to听monitor听using existing indicators.

Monitoring sudden changes to ecosystems poses听a different set听of challenges to听monitoring听long鈥憈erm听ecosystem degradation. Future approaches should, however,听seek听to combine tracking of both kinds of risk to provide a more holistic judgement of an ecosystem鈥檚 stability.

Indicators add most value when they听have clear owners and听pre鈥慳greed听thresholds for response, so that听subsequent听actions can be proportionate and听timely.

The UK has rich monitoring of its own ecosystems, but siloed datasets with limited access undermine integrated, national early warning practices. Other countries have shown that operationally relevant monitoring is听feasible.

There are promising monitoring methods that use continuously updated modelling: these blend satellite,听hydrology听and field observations to deliver rolling short听and听medium鈥憈erm听forecasts of ecosystem stress, akin to weather forecasting.

Question 2

Reliability of available indicators for signalling disruption

Accepted Answer

1. There is no single, dependable approach to monitoring changes across food, water and timber ecosystems combined.听

2. Traditional early-warning systems (such as those tracking changes in ecological populations) cannot听anticipate听cascading disruptions 鈥� past behaviour and trends in ecosystems are not a good predictor for听the听future.

3. There has been promising use of using natural-capital indicators (for example changes to soil quality, species, vegetation; Lenton and others, 2022) to judge whether ecosystems can still deliver services we rely on. This approach links ecosystem听monitoring听directly to service delivery risk and highlights where degradation is likely to affect policy goals.

a. In the forest estate, a composite Forest Biodiversity Index (Forest Research, no date given) is already used as a biodiversity condition metric, illustrating how听natural鈥慶apital听indicators can be assembled from available datasets.

4. Complex ecosystems, such as those prioritised in Defra鈥檚 current assessment, are especially difficult to听monitor听using existing indicators.

a. Available monitoring tools have been designed for detecting changes to more simple forest ecosystems, for example, where satellite and field indicators align well, and anomalies are easier to interpret (for example, NOAA Climate Resilience Toolkit, no date given).

b. By contrast, boreal forests are complex ecosystems of听different types听of trees interspersed with peatlands/lakes. They span multiple owners, with听long periods听of darkness and frequent cloud/snow. Both ground data and satellite sensing are inconsistent in such an ecosystem, leading to missed changes or false alarms.

Question 3

Tipping points versus gradual ecosystem changes

Accepted Answer

5. Different indicators are听required听to detect abrupt tipping points versus evidence of long-term degradation (Global Tipping Points, 2025a). These 2 challenges also require different monitoring strategies and policy responses.

6. Abrupt tipping points are sudden shifts where an ecosystem flips to a new state and does not, or cannot, easily recover (Global Tipping Points, 2025b), such as rapid forest die-off (Rotbarth and others, 2024) or outbreak-driven food supply chain disruption.

a. Indicators for this look for loss of resilience (for example, slower recovery after minor drought, De Keersmaecker and others, 2015) which are typically easier to study. There is a higher chance of irreversible outcomes under these circumstances, which lowers the threshold for evidence needed to escalate actions from early warning signals (EWS).

b. The Atlantic听Meridional听Overturning Circulation (AMOC1) is a good example of a well-understood EWS; warning signs can be risk assessed effectively to inform decision making (Van Westen and others, 2024; Richie and others, 2019;听Carnicer听and others, 2019).

7. Indicators for gradual degradation are typically slow, cumulative declines in the condition and functioning of ecosystems, such as biodiversity loss, declining amounts of ground water in rivers, or forest health decline.

a. These changes do not require a formal tipping point to have major impacts on听supply, but听are harder to measure and can have less influence over decision makers.

b. Standard forestry production models handle gradual trends but are poor at capturing sudden disruptions (such as due to drought (Meyer and others, 2025), storms, pest outbreaks (Mohr and others, 2025)), which have the potential to erase decades worth of supply.

c. Standardised precipitation/streamflow indices are also effective at providing situational awareness for drought and water availability (UKCEH, 2025; UKCEH drought inventory, no date given).

d. Some ecosystem听monitoring听systems in the UK are on a multi-annual repeat cycle, such as the rolling 5-year National Forest Inventory. Such repeat cycles may not be enough to detect change early.

8. Future monitoring approaches should combine tracking of tipping point risks (sudden, often non-linear, and potentially irreversible; Seddon and听Milkoreit, 2025) as well as tracking of degradation (smoother, more gradual changes) to provide a more holistic judgment of an ecosystem鈥檚 stability.

Question 4

Data integration and systemic barriers

Accepted Answer

9. In the UK, data and models听largely remain听siloed across climate, biodiversity, hydrology,听agriculture听and forestry, which prevents consideration of routine, integrated听early鈥憌arning听indicators at national scale.

a. Many universities, businesses,听non-governmental organisations (NGOs)听and citizen science groups already听monitor听environmental data. An effective early warning system should draw on and compile these听sources, and听not rely solely on government datasets.

10. Government鈥慶ollected听environmental datasets are often not听open access. They can lack consistency and be fragmented across different projects and ecosystems. Data usability is a major barrier, with many datasets difficult to access or interpret without specialist training. This reduces their value for researchers and policymakers and hinders听evidence鈥慴ased听decisions.

a. For example, satellite remote sensing can already detect droughts, heatwaves,听floods听and peatland water loss, but access to government data (for example,听National Forest Inventory) is constrained, which hinders calibration and measurement of uncertainty.

11. International examples show that integrated, rapid monitoring is feasible, but the UK lacks equivalent systems and infrastructure to manage growing data volume, data diversity (the different types of data required to fully support modern ecosystem monitoring) and complexity (including novel ecosystem and microbial data).

a. Improving domestic recycling and processing capability would reduce reliance on imported raw materials and overseas processing.

Question 5

Improving indicator quality

Accepted Answer

12. Moving from static analysis to dynamic modelling can help to deliver more rolling hindcasts/forecasts and allows better measurement of uncertainty (Chan and others,听2026),听similar to听weather forecasting. Iterative ensemble prediction (that is running a model multiple times to get a range of听possible scenarios) and data assimilation (regularly pulling in new observational data) offer major advances, enabling improved assessment of biodiversity and ecosystem risks.

13. Deep Artificial Intelligence (AI) learning and advanced analytics can integrate multiple data streams (satellite, climate, hydrology, field data) to generate near听real鈥憈ime听indicators of ecosystem stress. These approaches are in use internationally, but are not yet routine or fully operational:

a. Brazil conducts deforestation monitoring, where satellite data are processed rapidly to detect forest loss and trigger enforcement action (Planet Labs PBC, 2025).

b. Czechia conducts听bark鈥慴eetle听detection, using听high鈥慺requency听remote sensing to guide forest management decisions (Planet Labs PBC, 2019).

Question 6

How indicators can be used to guide government decisions

Accepted Answer

15. Indicators should be designed to trigger decisions rather than just describe risk. There are ways, for example, of using听different levels听of indicator outputs to set thresholds for action (for example watch/alert/action), with each level having clear ownership and pre-agreed responses (for example听escalate inspections, activate drought measures).

16. Action should be taken whilst risks are still听emerging, not only once the evidence is beyond doubt. While some technical indicators still need development, especially for abrupt ecological change, policy officials already have sufficient warning to act on the drivers of risk, particularly in food and timber supply chains and in preparing for water-related risks (such as drought and scarcity).

a. When the consequences of inaction could be irreversible, scientific evidence needs to be framed in terms that clearly show what is at stake for food supplies, water availability, economic听stability听and national security so that decision makers can act in time.