IB ESS SL1.2 SystemsPaper 1 & 2Core idea~13 min read
Resilience and Tipping Points
Systems can take a certain amount of abuse and bounce back. Then, at some point, one more small push does something completely different — the system stops bouncing back and settles somewhere new. Knowing where that line sits is one of the hardest and most important jobs in environmental science.
📚 What you need to know
A tipping point is a critical threshold. Past it, a small change causes big knock-on effects and moves the system away from its average state.
Positive feedback loops push systems towards and past their tipping points.
Once past, a new equilibrium is reached. This is called a regime shift to an alternative stable state.
The change is often irreversible, or very expensive to reverse.
Tipping points are hard to predict because of delays in feedback loops and links between distant places.
Resilience is a system’s ability to stay stable and avoid tipping points.
Resilience comes from diversity and the size of storages. Humans usually reduce both.
Tipping points
Definition
A tipping point is a critical threshold in a system. Once it is crossed, further small changes have large knock-on effects and the system moves away from its equilibrium.
In ecosystems these matter enormously, because a tipping point marks the moment serious, often irreversible damage begins. Eutrophication is the classic example: a lake absorbs nutrient pollution for years with little visible change, then flips into a low-oxygen, algae-dominated state and stays there.
The grey dashed arrow is the recovery journey. Notice it is uphill and much longer than the slide down.
Reading that diagram in an exam
The system starts in its original equilibrium, sitting quietly in the first dip.
Pressure is applied — pollution, hunting, warming, whatever the question gives you.
The pressure pushes the system up towards the tipping point at the top of the hill. Balanced there, even a tiny nudge is enough.
Positive feedback loops then accelerate the slide down the other side.
The system settles into a new equilibrium in a deeper dip. Climbing back out needs a huge amount of effort, and often it never happens.
Why tipping points are hard to predict
Feedback loops contain delays of different lengths, which makes any model of the system messy.
Not every part of a system changes abruptly at the same time.
It is often impossible to identify a tipping point until after it has already been passed.
Activity in one part of the world can push a system somewhere else over the edge. Burning fossil fuels in industrialised countries drives the warming that is pushing the Amazon towards desertification.
Because of that last point, continued monitoring, research and scientific communication are needed to spot the links at all.
“We will know when we get there” is not a plan. That is why questions about tipping points nearly always want you to mention uncertainty and the need for monitoring. Write it in and you are answering the question they actually asked.
Case study: melting ice caps and glaciers
Human activity is pushing the cryosphere towards a tipping point. The consequences reach well beyond the ice itself.
Consequence
What happens
Rising sea levels
Meltwater adds to ocean volume, flooding low-lying land and damaging infrastructure through inundation and erosion
Changing ocean currents
Melting alters the salinity and temperature of the sea, which shifts currents and therefore global weather patterns
Loss of biodiversity
Polar species adapted to extreme cold lose habitat and food sources, so populations decline
Release of greenhouse gases
Thawing permafrost releases stored methane and carbon dioxide, causing further warming and further melting
Higher global temperatures
Less ice means lower albedo, so more sunlight is absorbed instead of reflected
Look at the last two rows again. Both are positive feedback loops, which is exactly why this system is capable of tipping rather than drifting gently.
Resilience
DefinitionResilience is the ability of a system to maintain stability, absorb disturbance and avoid reaching a tipping point.
Every system — ecological, social or economic — has some resilience. Two things decide how much.
Diversity. More species and more links in a food web mean more different ways to respond to a disturbance.
The size of storages. Bigger stores absorb shocks and slow the system’s response to change.
Systems with higher diversity and larger storages are less likely to reach a tipping point.
Same ball, same push, different outcome. Resilience is a property of the system, not of the disturbance.
Diversity: rainforest against monoculture
A rainforest has an extremely complex food web. If a disturbance hits one part of it, animals and plants have many alternative routes to feed and survive, so the ecosystem holds together.
It also has large storages — long-lived trees and huge numbers of dormant seeds in the soil.
Together these keep the rainforest in a steady-state equilibrium.
An agricultural monoculture is the opposite. One species, no alternatives. A single new pest or crop disease can wipe out the entire system, because nothing else is there to take up the slack.
Natural grassland recovers fast from fire because of underground seed banks, nutrients and root systems, and because some species are adapted to regrow after burning. Convert it to cropland and that storage disappears, along with the resilience.
Storage size: pond against lake
Pollutants entering a lake become diluted and dispersed through a large volume, so the effect on water quality is small.
The same pollutants entering a pond accumulate quickly, so the pollution is concentrated and immediate.
Evaporation barely dents a lake’s water level. It can dry a pond out completely.
Bigger storage means changes in input or output have less immediate impact on the whole system.
Two ecosystems, two levels of resilience
Mangrove forest — high resilience
Coral reef — low resilience
Adaptability
Evolved to survive saltwater flooding, storm surge and rising sea levels
Very narrow tolerance for temperature and acidity
Recovery
Self-regenerates using propagules that sprout into new trees after storms
Corals grow slowly and are easily damaged again while recovering
Diversity
High, which buffers disturbance and keeps ecological processes running
High in species, but the reef depends on a few very sensitive coral builders
Pressures
Mainly clearance for development
Overfishing, pollution, coastal development and warming all at once
Result
Absorbs disturbance and returns to its previous state
Bleaching can cause mass mortality and a shift past a tipping point
Humans and resilience. Almost everything we do to natural systems reduces resilience, because it reduces either diversity or storage. Hunting species to extinction, deforestation, draining wetlands, replacing grassland with a single crop — each one makes the dip shallower and the tipping point closer.
Worked examples
WE 1
Explain what happens at a tipping point
Explain what is meant by a tipping point, and outline the role of positive feedback. (4 marks)
Point 1: the definition
A tipping point is a critical threshold in a system. Past it, small changes have large knock-on effects.
Point 2: the direction of travel
The system moves away from its average state rather than returning to it.
Point 3: the role of feedback
Positive feedback loops amplify the change, pushing the system towards and then past the threshold.
Point 4: the outcome
A new equilibrium is reached — a regime shift to an alternative stable state, often irreversible.
Threshold crossed, feedback takes over, new state locked inthe phrase “alternative stable state” is worth learning word for word
WE 2
Compare the resilience of two systems
Suggest why a rainforest is more resilient than a field of a single crop species. (3 marks)
Point 1: diversity
A rainforest has high diversity and a complex food web, so a disturbance to one species can be absorbed through alternative routes.
Point 2: storage
It holds large storages such as long-lived trees and dormant seed banks, which buffer change.
Point 3: the contrast
A monoculture has one species and little storage, so a single pest or disease can collapse the whole system.
Diversity plus storage equals resilienceanswer with both factors — diversity alone usually caps you at two marks
WE 3
Explain the difficulty of prediction
Explain why tipping points are difficult to predict. (3 marks)
Point 1: delays
Feedback loops contain delays of varying length, which makes systems hard to model accurately.
Point 2: uneven change
Not all parts of a system change abruptly at the same time, so warning signs are unclear.
Point 3: distance
Pressure applied in one part of the world can tip a system elsewhere, so links are easily missed and often only identified after the threshold has been crossed.
Delays, uneven responses and long-distance links — so monitoring mattersend with the need for continued monitoring and research; it is frequently the third mark
💡 Exam tips
Learn the phrase regime shift to an alternative stable state and use it.
Whenever you mention a tipping point, name the positive feedback loop driving it.
Resilience answers should always mention diversity and storage size.
Have one high-resilience example and one low-resilience example ready — mangroves and coral reefs work well.
Say that crossing a tipping point is often irreversible or very costly to reverse.
Ball-and-valley diagrams are worth sketching in longer answers. They are quick and they show understanding.
⚠ Common mistakes
Saying a tipping point is just a big change. It is a threshold beyond which the system behaves differently.
Thinking resilience means nothing happens. A resilient system is still disturbed; it just recovers.
Confusing resilience with resistance. Resilience is about coming back, not about refusing to change.
Forgetting storage. Diversity is only half the answer; the pond and lake example is the other half.
Assuming recovery is always possible. Once past the threshold, the new state is often permanent.
Ignoring the human role. Most exam scenarios involve people reducing diversity or storage.
Up next: Using Models in ESS — every diagram in these notes has been a model. Time to look at what models can and cannot tell you.
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