Put algal balls in a suitable carbon dioxide indicator, or an approved equivalent, at different distances from a lamp. Use a defined indicator change to estimate photosynthesis rate. Compare it with lamp distance or measured light intensity.Labelled apparatus schematic; not to scale. Follow the measurements and connections, not the drawn dimensions.
Hydrogencarbonate indicator is yellow at increased CO₂, red/orange around its usual starting condition, and purple when CO₂ falls. Photosynthesis removes CO₂; respiration releases it.
Control ball number/size, indicator volume/composition, initial colour, time, temperature and ambient light. The same number of balls is not enough for a fair comparison if their sizes differ.
Measure distance consistently from lamp to sample centre; a light sensor gives a better intensity measure. Set the lamp securely and manage hot lamps, glass and electrical equipment safely.
Method and interpretation
Allow equal samples to reach the same starting temperature and indicator colour. Place tubes at a range of measured distances from the lamp.
Expose for equal times and record colour at fixed intervals, or use a validated colorimeter method with a suitable filter and matched blank.
Use indicator without algae as a control to check for colour changes not caused by living organisms. Keep another algal sample in darkness to show respiration without photosynthesis.
Time how long each sample takes to reach the same chosen colour. Compare relative rates using 1/time: a shorter time gives a higher rate estimate. If you have calibrated CO₂ concentrations, rate = CO₂ change ÷ time. A colour alone, without a time measurement, does not give a rate.
Near an ideal point source, intensity is approximately proportional to 1/d². Doubling distance gives one-quarter intensity; room light and lamp geometry can make this approximation imperfect.
In bright light, photosynthesis can remove CO₂ faster than respiration releases it, turning the indicator purple. In darkness, respiration can turn it yellow. At the compensation point, photosynthesis and respiration happen at equal rates, so there is no overall CO₂ change.
At high light intensity, the response may level off (reach a plateau) because carbon dioxide supply or temperature limits the rate. Do not assume that increasing light will always keep increasing the rate.
Quality and additional pondweed method
Control temperature using suitable shielding or a water bath while keeping optics consistent. A closer lamp can increase heat as well as light; even LEDs should be checked.
Use independent equal samples and compare repeat spread. Keep ball size and clumping similar so light penetration and diffusion are comparable.
A colorimeter makes colour readings less dependent on personal judgement if the method has been checked. A blank sets a reference reading, but you still need standards to convert readings into CO₂ concentrations.
Pondweed oxygen production is an additional useful method, not a replacement for the core algal-ball setup. Measure gas volume/time where possible; bubbles have unequal volumes.
For pondweed, match species/length, CO₂ supply, temperature and observation time, and allow the pondweed to adjust to the new conditions after moving the lamp.
CO₂ exchange with air, respiration and the indicator’s sensitivity and starting colour can affect results. State exactly what you measured as an estimate of rate and the range of conditions you tested.
Exam skills: planning, precision and evaluation
State what you change (the independent variable), what you measure (the dependent variable) and what you keep the same (control variables). Explain how you keep each control variable constant, rather than just saying “make it fair”.
Accuracy means how close a result is to the true value. Precision means how close repeated measurements are to each other. Resolution is the smallest change an instrument can show. More digits on a display do not automatically mean a more accurate result.
Repeat measurements for each condition, calculate a mean and describe how spread out the results are. This helps assess and reduce the effect of random errors. Repeating cannot fix an error that pushes results consistently in one direction (a systematic error), such as closer samples being heated more by the lamp.
Repeatability means getting similar results when the same person repeats the same method with the same equipment. Reproducibility means getting similar results when someone else, or different suitable equipment, repeats the experiment. Results can be consistent but still inaccurate.
Check that instruments read zero correctly and are calibrated where needed. Read scales at eye level: looking from an angle can give a wrong reading (parallax error). Choose suitable ranges, measurement intervals and scale divisions (resolution).
Write down the original readings straight away in a table, with units in the headings. Use decimal places that match the instrument’s resolution. Keep the original data and round only when needed. Do not discard a result just because it differs from your prediction.
An anomalous result does not fit the pattern of the other results. Repeat that measurement and check the method. Only leave it out of a mean if you have a clear reason; state which result you excluded and why.
For continuous variables, plot the independent variable on the horizontal axis and the dependent variable vertically. Use sensible scales, units and a best-fit line or curve; do not automatically join every point or force the graph through zero.
Find the gradient of a straight best-fit line using a large triangle: vertical change ÷ horizontal change. For a curve, draw a tangent to estimate the gradient at one point. Explain what the gradient shows in this experiment, include its units and use measured values to support your conclusion.
Uncertainty describes the possible range around a measurement. For one reading on a scale, half the smallest division is a useful classroom estimate unless the question says otherwise. If you subtract two readings, both have uncertainty. Percentage uncertainty = absolute uncertainty ÷ measured value × 100. Follow the method specified in the question.
Use results as evidence and then explain what they mean. A pattern linking variables (a correlation) does not prove that one causes the other. If the ranges of repeat results overlap, a claimed difference may be less convincing. Keep conclusions within the range tested and suggest an improvement that tackles a specific error.
Mr Kidman's Classroom