Three things can hold photosynthesis back: light, carbon dioxide and temperature. At any moment one of them is the bottleneck — and the whole skill is designing an experiment where you know which one it is.
📚 What you need to know
A limiting factor is the one in shortest supply, and it alone sets the rate at that moment.
The three to know are light intensity, carbon dioxide concentration and temperature.
An aquatic plant such as Elodea or Cabomba is used because the oxygen it makes is visible as bubbles.
Light and carbon dioxide give the same graph shape: a rise, then a plateau where something else takes over.
Temperature gives a different shape: a rise to an optimum, then a sharp fall as enzymes denature.
Control the others carefully — a glass tank of water absorbs the lamp’s heat, and sodium hydrogencarbonate keeps carbon dioxide plentiful.
Light intensity follows an inverse square relationship with distance from the lamp.
What “limiting factor” means
Photosynthesis needs light, carbon dioxide and a workable temperature all at once. Supply plenty of two and starve it of the third, and the rate is set entirely by that third one. Improve it and the rate climbs. Improve anything else and nothing happens at all.
Definition
a limiting factor is the factor in shortest supply, which therefore sets the rate
This is why the graphs plateau. The line stops climbing not because the plant has hit a ceiling, but because a different factor has become the bottleneck.
A hypothesis first
A hypothesis is a proposed explanation that may turn out to be true or false. It is provisional: you test it, and repeated testing either supports it or forces you to change it.
A good one for this practical: increasing the light intensity will increase the rate of photosynthesis in Elodea. It is specific, it names the variable, and it can be tested.
The apparatus
An aquatic plant is the sensible choice here. A land plant releases oxygen too, but into the air where you cannot see or collect it. Pondweed releases it into water as countable bubbles.
Every part of this set-up exists to control something. If you can say what each piece is controlling, you can answer almost any question on the method.
🧩 Method for light intensity
Set up the pondweed cut-end upwards under an inverted funnel, with a water-filled boiling tube over the funnel neck.
Use boiled and re-cooled water, then add a set mass of sodium hydrogencarbonate so carbon dioxide is plentiful and not limiting.
Place the lamp a measured distance from the plant, with the glass tank of water in between.
Leave it to settle for a few minutes so the rate becomes steady before you start counting.
Count the bubbles released in three minutes, then divide to get bubbles per minute.
Repeat at several distances, at least three times each, and take a mean.
Variables
Type
What it is here
How it is handled
Independent
Light intensity, set by lamp distance
Changed deliberately, over a range of distances
Dependent
Bubbles per minute, or volume of oxygen
Measured at each distance
Control
Temperature
Glass tank of water absorbs lamp heat; an LED bulb emits little
Control
Carbon dioxide concentration
Boiled, re-cooled water plus a fixed mass of sodium hydrogencarbonate
Control
The plant itself
Same species, same length of cutting, same piece if possible
Improving it
Collect the gas in a gas syringe and measure a volume — bubbles vary in size, so counting them is crude.
Repeat each distance at least three times and take a mean.
Use a data logger with an oxygen sensor for continuous readings.
Use a light meter to measure the actual intensity reaching the plant, rather than relying on distance.
Light intensity and carbon dioxide
Both give the same shape, and for the same reason.
Whichever factor is on the x-axis, the reading is the same: on the sloping part that factor is limiting, on the flat part it is not.
On the slope, increasing the factor increases the rate, so that factor is the limiting one.
At the plateau, adding more makes no difference. Something else — carbon dioxide or temperature — has become the bottleneck.
To raise the plateau you must increase whatever the new limiting factor is.
The commonest exam question here is “why does the graph level off?” The answer is never “the plant is full”. It is that a different factor has become limiting.
Distance and the inverse square law
You control light intensity by moving the lamp, but intensity does not simply halve when you double the distance. It follows an inverse square relationship:
Light intensity and distance
light intensity ∝ 1 ÷ d2
Double the distance and the intensity drops to a quarter. Treble it and you are down to a ninth. That is why the x-axis should really be intensity, or 1/d2, rather than raw distance.
Temperature
Temperature behaves differently, because photosynthesis is a pathway of enzyme-controlled reactions.
Do not draw a plateau here. Temperature past the optimum destroys the active sites, so the rate falls rather than holding steady.
Below the optimum, higher temperature means more kinetic energy, more successful collisions between enzyme and substrate, and more enzyme–substrate complexes.
At the optimum the rate is highest.
Above it, the enzymes begin to denature, the active sites change shape, and the rate falls sharply.
Worked examples
WORKED EXAMPLE
A student counts 45 bubbles in 3 minutes with the lamp 10 cm away. Calculate the rate in bubbles per minute. The lamp is then moved to 20 cm. Predict the new rate, assuming light is the limiting factor.
Step 1: rate at 10 cm45 ÷ 3 = 15 bubbles per minuteStep 2: what doubling the distance does to intensityintensity ∝ 1 ÷ d², so 20 cm gives a quarter of the intensity at 10 cmStep 3: apply that to the rate15 ÷ 4 = 3.7515 bubbles per minute at 10 cm, about 3.75 at 20 cmthe prediction only holds while light is still the limiting factor
WORKED EXAMPLE
Calculate the relative light intensity at 10, 20 and 40 cm from a lamp, taking the value at 10 cm as 100.
Step 1: use 1 ÷ d² and scale so 10 cm gives 10010 cm: 10000 ÷ 10² = 100Step 2: repeat for the others20 cm: 10000 ÷ 400 = 2540 cm: 10000 ÷ 1600 = 6.25100, 25 and 6.25notice the fall is far steeper than the distances suggest — that is the inverse square at work
WORKED EXAMPLE
A graph of rate against light intensity has levelled off. The student increases the light further and sees no change, then warms the water from 15°C to 25°C and the rate rises. Explain both observations. [3]
Step 1: why more light did nothing
On the plateau, light is no longer the limiting factor.
Step 2: why warming worked
Temperature was the limiting factor, so raising it towards the optimum raised the rate.
Step 3: name the mechanism
More kinetic energy gives more successful collisions and more enzyme–substrate complexes.
Light was in excess; temperature was limiting, so only warming increased the ratewarming beyond the optimum would reverse this, as the enzymes denature
💡 Exam tip
For any plateau question, name the new limiting factor. “Something else is limiting” is half an answer.
Learn which shape goes with which factor: plateau for light and carbon dioxide, peak for temperature.
Explain the temperature graph with the enzyme reasoning — collisions up to the optimum, denaturation after it.
Mention the glass tank of water and why it is there. It is the neatest control-variable mark on the paper.
Say boiled and re-cooled water plus sodium hydrogencarbonate when asked how carbon dioxide was controlled.
If asked to improve the method, “use a gas syringe instead of counting bubbles” is the strongest single answer.
⚠ Common mix-up
Saying the plateau means the plant is “saturated” or “full”. It means another factor has taken over as the limit.
Drawing a plateau on the temperature graph. It peaks then falls.
Assuming intensity halves when distance doubles. It quarters.
Forgetting the lamp heats the water. Without the glass tank, temperature changes along with light.
Counting bubbles without timing them. A rate needs a time: bubbles per minute.
Treating bubble counting as precise. Bubbles differ in size, which is exactly why a gas syringe is better.
Confusing invalid with unreliable. Invalid means the wrong variable changed; unreliable means the repeats disagree.
Up next: Carbon Dioxide Enrichment Experiments — scaling this idea up from a beaker of pondweed to whole forests, and what that tells us about a warming world.
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