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ib biology sl notes

The Effect Of Sunlight On Biomass

UPDATED ON - 15 APR 2020
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The Effect Of Sunlight On Biomass

Note IB Summary: The experiment is conducted in different conditions with many variables, Sunlight is the only constant variable. The grass was selected from two different areas of the field, one in shade and the other in direct sunlight. We conclude that biomass is an indirect measure of the productivity of the area.


Biomass is the weight of living organisms in a given area. Biomass can differ due to a variety of factors,

[Comment]: Definition limited, here it should be referred to as above-ground biomass.Limited scientific context.Research question not focused.

such as exposure to sunlight, proximity to human activity, mineral nutrient levels, and water availability. The first, sunlight exposure, will be the subject of this investigation.

Research Question: How does sun exposure affect above-ground dry biomass of grass?

[Comment]: Investigation remains trivial in content. Not much sign of engagement by the candidate.

In this experiment, the independent variable is sun exposure and the dependent variable is dry biomass, measured in grams (g). Other variables affect the biomass of grass, other than sun exposure. These include the amount of water each area of grass receives, proximity to footpaths and sidewalks, and the amount and mass of water in the grass. To control the last two variables, both areas sampled were the same distance from the main sidewalk and were left to dry before being measured.

[Comment]: Limited explanation of the method. How long? Where?


• 1 meter squared quadrat

• 10 centimetre squared quadrat

• 10 plastic resealable bags

• Scale




[Comment]: Method could be repeated though some details are missing.

[Comment]: No consideration of safety ethics or environmental impact


1. Two 1-meter2 grass areas around the school campus were chosen; one exposed to the sun throughout the day and one under the shade of a tree throughout the day. Each meter squared area was 5 meters from the front sidewalk of the school, controlling the variable of proximity to sidewalks.

[Comment]: Sample area controlled

[Comment]: No details of the distance of the tree or what species it is?

2. Once the areas were chosen, 1 meter2 quadrat was placed in each area.

3. Each meter2 was divided into 100 quadrants, each being 10cm x 10cm. Once it was divided into 100 quadrants, they were numbered 1-100, left to right, starting from the upper left corner.

4. Using a random number generator, 5 numbers were picked for each site (5 for the meter2 in the sun and 5 for the meter2 in the shade).

[Comment]: Sampling shows some elements of control.

5. The numbers generated represented the numbered quadrants. Samples of grass were taken from the quadrat numbers that were randomly generated and placed resealable plastic bags. A standard for collecting the sample was established; the grass was pinched at the stem right above the ground, and then plucked, leaving the roots intact in the soil.

[Comment]: OK though cutting with scissors would probably be more consistent.

6. Once 5 samples were collected from each square meter, the grass was then left to dry for two days. Drying out the grass allows the dry biomass to be taken. This controls the variable of different amounts of water in the grass.

[Comment]: The sample size is limited and small. Insufficient data collected.

[Comment]: This is better than the fresh mass but it ought to have been specified that it is above-ground biomass.

7. After two days of drying, the mass of each sample of grass was taken.
8. Once the masses were recorded, the t-test was performed to determine the average mass of grass in each area and to determine if the difference in masses were statistically significant, or due to chance.

[Comment]: Appropriate method of analysis chosen.





  •  Insufficient data to support the conclusion fully.
  •  Difficult to believe a precision of ±0.mg!
  •  Appropriate analysis (averages).Comm Layout could be improved but not incomprehensible
  •  Notation OK
  •  Conventions OK
  •  Qualitative observations made but what about the influence of the tree?



1 2 3 4 5 6 7 8 9 10
11 12 13 14 15 16 17 18 19 20
21 22 23 24 25 26 27 28 29 30
31 32 33 34 35 36 37 38 39 40
41 42 43 44 45 46 47 48 49 50
51 52 53 54 55 56 57 58 59 60
61 62 63 64 65 66 67 68 69 70
71 72 73 74 75 76 77 78 79 80
81 82 83 84 85 86 87 88 89 90
91 92 93 94 95 96 97 98 99 100

Sun Exposed

Sample & Quadrat


Sample 1 Quadrat


Sample 2 Quadrat


Sample 3 Quadrat


Sample 4 Quadrat 5


Sample 5 Quadrat


Average Mass



       Table 1: Biomass of grass in the sun


    Figure 1: Diagram of 1-meter squared quadrat divided into 100 ten meter squared quadrats. Yellow highlighted quadrats represent the location of sun samples and the blue highlighted quadrats represent the location of shade samples         




                                                     Table 3: Observations                                                        Table 2: Biomass of grass in the shade                                       

Additional Observations

        • Grass in the shade was more

        • More dead grass in the sun
          exposed area

        • Grass in the sun-exposed
           the area was wetter than the
           grass in the shade

Shade Area

Sample & Quadrat

Mass/g ± 0.0001

Sample 1 Quadrat


Sample 2 Quadrat


Sample 3 Quadrat


Sample 4 Quadrat


Sample 5 Quadrat 2


Average Mass






Statistical analysis

P-value: 0.058
P> 0.05
Accept the null hypothesis                                                                                                                                                                                                                        
(the difference is due to chance and is not statistically significant)


































[Comment]: Graph fairly clear
[Comment]: Uncertainties (error bars)drawn well and explained.
[Comment]: Conventions appropriate

This is not easy to follow. Is it a t-test?                                                                                                       


Figure 2: Average biomass of grass in sun and shaded areas. The error bars represent ± 1 standard device




[Comment]: Methods of analysis seem appropriate but they are difficult to confirm because too many processing steps are missing.
[Comment]: Uncertainties calculated as Standard deviations (shown on the graph) but that’s all.



The data supports the null hypothesis that there is no difference in biomass of grass in the sun and the shade.

[Comment]: Interpretation weakened by the poor presentation of the analysis.

A possible explanation is as follows. The grass is a primary producer of biomass because it can fix inorganic matter (carbon dioxide). Biomass is, therefore, an indirect measure of the productivity of an area. Grass in the sun receives more sunlight to use for photosynthesis. During photosynthesis, light energy is converted into chemical energy. When there is more light, more light energy is absorbed and used for the production of more chemical energy. Productivity can then said to be greater in the

Comment [PB18]:
Ev: conclusion set in a scientific context

the area with greater biomass. In this experiment, the results did not show a statistically significant difference in biomass. Even though the average biomass of the grass in the sun was greater than that of the shaded area (table 1 and 2), it was not significant.

Comment [PB19]:
[Comment]: Relevant conclusion but difficult to support from the limited data

This could be due to the role of other variables, such as the amount of water and the limited sample size.

Comment [PB20]:
[Comment]: Consideration of uncertainties is too vague.



Other variables may have affected the biomass of the grass in each area. The amount of water each area receives could not be controlled. Quite often, sprinkles are watering the grass. The amount of water each area receives can affect the rate of photosynthesis, which will affect grass growth. If the grass in either area received more water, the results could be an overestimation in my procedure, the sample size was sufficient, however not large enough to show significant results. The data in the shaded area was more variable than the data in the sun-exposed area(Figure 2).

[Comment]: Not clear. Was the sample size big enough or not? The evidence suggests that it was not.

[Comment]: Ought to refer to standard deviations

The variation could be decreased if the sample sized was increased. Additionally, the 10 cm2 quadrats were sometimes difficult to determine and measure precisely. The shade sampling area was near a recreational area, where a cement 4-square court is built. The shaded area may experience more direct human contact and trample, resulting in less grass. The grass was patchier. This could result in an underestimation of the biomass of the grass in the shade. Also, due to the warm tropical climate and frequent sun, the shaded area may be used more than the sun-exposed area for shade to avoid sun exposure.

[Comment]: Identifies several factors that may also influence the outcome.




[Comment]]: The modifications do not the concern most of the weaknesses identified.

[Comment]: Did not consider the impact of management other than irrigation.

To be more precise with measurements, I would construct a meter-squared quadrat that is pre-divided into 100 ten centimetres squared quadrats. This would allow much more uniform precision, decreasing human error. When biomass was taken, some grass samples were still moist and did not dry fully. To ensure that water mass was not a factor affecting grass biomass, the grass would have been left longer to dry, if time permitted.

[Comment]: Or use an oven and repeat the measurement of mass until it is constant.

An experiment that controls the amount of water each area receives, as well as human contact, with more precise measuring methods, would be ideal and more accurate in determining if there is a difference in biomass of grass in the sun and the shade.

[Comment]: Too vague. Lacks concrete suggested improvements e.g. put a fence around the areas to keep out humans.





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