13.2.2—Effects of limiting factors

A limiting-factor graph shows how a measured photosynthetic rate changes as one factor is varied under stated conditions. The slope, plateau and any decline each provide different evidence about which factor is restricting rate in that range.

1. Check the axes: identify the independent factor on the x-axis, the measured rate or proxy on the y-axis, and the units and scale. Do not interpret a curve before knowing what was varied and measured.
2. Read the changing region: where the curve rises as the x-axis factor increases, that factor is limiting over that range. A steeper slope means a larger rate change per unit of the tested factor, not necessarily a universal ranking of factors.
3. Read the plateau: where the curve becomes approximately horizontal, further increases in the tested factor no longer raise the measured rate. Another requirement—such as light intensity, carbon-dioxide concentration or temperature—is limiting under those conditions.
4. Check a decline or peak: a fall after a peak can indicate an optimum range and an adverse effect at higher values, such as enzyme-controlled reactions responding to temperature. Do not call every peak a universal optimum without the tested conditions.
5. Compare fairly: compare curves only when the measurement, units, sample and control conditions are comparable. State conclusions as “limiting over this measured range”; do not infer a cause from one endpoint or extrapolate beyond the data.

Qualitative read-off: rising section = the x-axis factor is currently limiting; horizontal section = a different factor is limiting; peak then decline = an optimum range plus a possible adverse high-value effect. The graph describes the measured rate, so conclusions remain conditional on the proxy and experimental controls.

A plateau does not mean photosynthesis has stopped, and a single point does not prove that one factor always controls the process. Specific DCPIP and aquatic-plant methods belong to later investigation cards.