Systems absorb a lot of pressure and then, at some point, stop absorbing it. The unnerving part is that you often cannot see where that point is until you have gone past it. This page is about what decides how much a system can take.
📘 What you need to know
A tipping point is a critical threshold beyond which a small further change causes significant knock-on effects.
Positive feedback pushes systems towards and past their tipping point, producing a regime shift to an alternative stable state.
The change is often irreversible, or very costly to reverse.
Tipping points are hard to predict: delays in feedback, uneven change, and often invisible until passed.
Resilience is a system’s ability to maintain stability and avoid tipping points.
Resilience depends on diversity and the size of storages.
Humans reduce resilience by cutting diversity and shrinking storages.
Named contrast: mangrove forests (high resilience) versus coral reefs (low resilience).
Tipping points
A tipping point is a critical threshold within a system. Once it is reached, any further small change will have significant knock-on effects and move the system away from its average state.
DefinitionTipping point — a critical threshold beyond which a small additional change causes a system to shift away from equilibrium to a new state.
In ecological systems, tipping points matter enormously because they mark the point beyond which serious, irreversible damage can occur. Positive feedback loops push a system towards and then past that threshold, at which point a new equilibrium is reached — sometimes called a regime shift to an alternative stable state. Eutrophication is the classic example of an ecological system crossing a threshold and accelerating into a new state.
At C the system is balanced on the crest, so even a minor push tips it. Between D and E positive feedback does the rest of the work on its own.
Why tipping points are hard to predict
Feedback loops involve delays of varying length, which makes systems harder to model.
Not all components or processes in a system change abruptly at the same time.
It may be impossible to identify a tipping point until after it has been passed.
Activities in one part of the globe can push a system elsewhere past its threshold. Burning fossil fuels in industrialised countries drives global warming, which is pushing the Amazon basin towards a tipping point of desertification. Continued monitoring, research and scientific communication are needed to identify these links.
Case study: melting polar ice caps and glaciers
The melting of polar ice caps and glaciers shows how human activity can push Earth’s systems past their limits, and the consequences extend well beyond the immediate environment.
Consequence
What happens
Rising sea levels
Meltwater adds to ocean volume, inundating low-lying areas and causing flooding, erosion and damage to infrastructure
Changes in ocean currents
Melting alters ocean salinity and temperature, which affects currents. This impacts global weather patterns and cascades through ecosystems
Loss of biodiversity
Polar species are adapted to extreme conditions; losing ice removes habitat and food sources, so populations decline
Release of greenhouse gases
Melting permafrost releases large amounts of methane and carbon dioxide, driving further warming and further melting
Changes in global temperature
Losing ice changes the reflective properties of Earth’s surface, so more sunlight is absorbed, raising temperatures and melting more ice
Spot the loops. The last two rows are positive feedback loops in disguise: melting releases gases that cause more melting, and melting darkens the surface which causes more melting. Pointing that out turns a list of consequences into an explanation.
Resilience
Every system — ecological, social or economic — has a certain amount of resilience: its ability to maintain stability and avoid tipping points. Two things determine it.
The right-hand panel has five identical circles and no lines between them. A single new pest reaches all of them at once.
Diversity
Systems with higher diversity are less likely to reach tipping points. A rainforest has high diversity in the complexity of its food webs, so when a disturbance hits, plants and animals have many different ways to respond and the ecosystem stays stable.
By contrast, agricultural monocultures contain a single species. That low diversity means low resilience: a new crop disease or pest species arrives and the system has nothing to counteract it.
Size of storages
Larger storages absorb change more easily. Compare a lake with a pond:
Disturbance
Lake (large storage)
Pond (small storage)
Pollutants enter
Dispersed and diluted by the volume, so the impact on water quality is reduced
Accumulate quickly, causing immediate and concentrated pollution
Evaporation
Water level barely changes; the volume buffers against rapid drying
Volume depletes quickly, leading to rapid drying and instability
Rainforests also hold large storages in long-lived tree species and high numbers of dormant seeds, which together promote steady-state equilibrium.
How humans reduce resilience
Reducing diversity in rainforests, through hunting species to extinction or destroying habitat by deforestation, makes the ecosystem increasingly vulnerable to further disturbance.
Natural grasslands have high resilience thanks to large underground storages of seeds, nutrients and root systems, letting them recover quickly after a fire — especially where species adapted to regenerate after fire are present. Convert that grassland to crops and the lack of diversity and underground seed reserves leaves a system with low resilience to the same fire.
Two contrasting case studies
Mangrove forests — high resilience
Coral reefs — low resilience
Adaptation
Evolved to survive harsh coastal conditions including saltwater inundation from tides; able to adapt to sea-level rise and storm surges
Highly vulnerable to climate change; rising sea temperatures and acidification cause coral bleaching and mass mortality
Recovery
Self-regenerate through propagules that sprout into new trees, so they recover quickly from storms, hurricanes and tsunamis
Corals grow slowly and remain vulnerable while recovering, so recovery is slow and difficult
Diversity
Support high biodiversity, which buffers against disturbance and maintains ecological processes
Face multiple simultaneous stressors: overfishing, pollution and coastal development
Cycling
Efficient at cycling nitrogen and phosphorus, maintaining soil fertility and supporting growth
If disturbances continue, the reef may pass a tipping point beyond which it cannot recover
These two case studies are designed to be used together. If a question asks you to explain resilience, contrast them directly: mangroves regenerate fast and are diverse, reefs grow slowly and face several stressors at once. One comparison covers both halves of the answer.
Worked examples
WE 1
Defining a tipping point
Outline what is meant by a tipping point and explain the role of positive feedback. (3 marks)
Step 1: the definition
A tipping point is a critical threshold within a system, beyond which any further small change causes significant knock-on effects and moves the system away from its average state.
Step 2: the role of feedback
Positive feedback loops amplify change, pushing the system towards and then past that threshold.
Step 3: what follows
Once passed, a new equilibrium is reached — a regime shift to an alternative stable state, which is often irreversible or very costly to reverse.
A threshold, crossed under positive feedback, leading to a new stable statethe terms “critical threshold” and “regime shift” both earn credit
WE 2
Explaining resilience
Explain why a rainforest is more resilient than an agricultural monoculture. (4 marks)
Point 1: diversity in the rainforest
A rainforest has high diversity and complex food webs, so if a disturbance occurs, organisms have many alternative ways to respond and stability is maintained.
Point 2: storages in the rainforest
It also holds large storages: long-lived tree species and high numbers of dormant seeds, which buffer against change.
Point 3: the monoculture
A monoculture contains only a single species, so diversity is very low and there are no alternative pathways.
Point 4: the consequence
A single new crop disease or pest can therefore affect the whole system at once, and it cannot counteract the disturbance.
Diversity and large storages give a system more ways to absorb a shockname both factors — diversity alone is only half the answer
WE 3
Why prediction is difficult
Suggest why tipping points in environmental systems are difficult to predict. (4 marks)
Reason 1: delays
Feedback loops involve delays of varying length, which makes systems harder to model accurately.
Reason 2: uneven change
Not all components or processes within a system change abruptly at the same time, so warning signs are inconsistent.
Reason 3: only visible afterwards
It may be impossible to identify a tipping point until it has already been passed.
Reason 4: distance between cause and effect
Activities in one part of the world can push a system elsewhere past its threshold — fossil fuel burning in industrialised countries is driving the Amazon towards desertification.
Delays, uneven responses, hindsight, and causes far from their effectsthe Amazon example turns a general point into a specific one
💡 Exam tips
Define a tipping point as a critical threshold, and mention the regime shift that follows.
Always link tipping points to positive feedback. They are examined together.
Give both resilience factors: diversity and size of storages.
Use the paired case studies: mangroves high, coral reefs low.
Say that changes past a tipping point are often irreversible or very costly to reverse.
Keep eutrophication and the Amazon ready as named tipping-point examples.
⚠ Common mistakes
Treating a tipping point as just “a lot of damage”. It is a threshold beyond which a small change has large effects.
Giving diversity as the only resilience factor. Storage size matters just as much.
Saying resilient systems cannot change. They change and then return; they resist crossing thresholds.
Assuming a new equilibrium can simply be reversed. Recovery is often impossible or very expensive.
Using resilience only for ecosystems. Social and economic systems have resilience too.
Forgetting the delay problem. It is a key reason tipping points are hard to predict.
Up next: Using Models in ESS. Everything on this page — feedback, thresholds, resilience — is studied through models. The last page in this sub-topic asks how much you should trust them.
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