Personal Engagement Statement:
I chose this topic because red clover used to be one of my favourite plants. When I was younger I used to try and find four-leaved clovers, as folklore says they are supposed to be a lucky charm. Its flower tops also used to be and are still used as a homeopathic remedy for coughs, bronchitis and asthma, among others (Zevin, 1997), as well as in agriculture, which I find very fascinating. This very simple looking plant is so miscellaneous and that is what caught my attention when looking for a project. When I looked online I could not find any proper information about its correlation to soil moisture though, which is why I made it my project.
EXPLORATION
Research Question (aim or problem):
How does soil moisture affect the abundance of red clover?
Hypothesis:
H1 Alternate hypothesis: There is a significant positive correlation between soil moisture and the abundance of red clover.
H0 Null hypothesis: There is no significant positive correlation between soil moisture and the abundance of red clover.
Table 1: Variables Selected for this Experiment
Units Range
Independent Variable Soil Moisture % 8.00 to 9.24
Dependent Variable Abundance of Red Clover –
Control Variables Units Possible effect on results
Light Intensity Lux More photosynthesis, therefore more flowers
Wind Speed m/s Damage to plants, therefore less flowers
Temperature ºC More photosynthesis, therefore more flowers
Soil Compaction Kg/cm2 Less root growth, therefore less flowers
Background Information:
Red clover (Trifolium pratense) is a legume used in agriculture, as it has a higher nutritional value than grass, has a higher tolerance to drought due to deep-growing roots, and is suitable as a break crop to improve soil structure and fertility in both conventional and organic farming (Frame, n.d.). On the roots of clovers are tiny nodules containing bacteria which can transform atmospheric nitrogen, which cannot be used by plants directly, into nitrate salts, which usually needs to be added to soil by fertilizers (The Reader’s Digest Association Limited, 1981). Planting clover saves a lot of money, because less nitrate fertilizer is needed. Red clover also contains substances called isoflavones, which are phytoestrogens – similar to the human estrogen (National Center for Complemetary and Integrative Health, 2016). Extracts are commonly used as dietary supplements for menopause symptoms, such as hot flashes, even though multiple studies have only shown a minor relief (Ghazanfarpour, et al., 2015), and premenstrual syndrome. Red clover is a widely used crop and herb and to be able to grow and maintain them in an effective and sustainable way, the conditions, including soil moisture, necessary to maintain them need to be determined.
Soil moisture affects photosynthesis, as it is needed in photolysis, in which water is split into and oxygen, protons and electrons.
2H_2 O → 0_2+4H^++4e^-
If the soil moisture is too low, it will become the limiting factor of the reaction and the rate of photosynthesis slows. If photosynthesis slows, there will not be enough hexose sugars available to break down for the energy needed for growth and production of gametes, which fuse to form seeds as it is usual for angiospermophyta.
Equipment List:
2 Tape Measures (10m)
Gridded Square (0.5m x 0.5m; 25 squares)
Soil Moisture Probe
Lux Meter
Anemometer
Penetrometer
Methodology (procedure):
I laid out two 10m tape measures to create a square. I used that square size, because it is large enough to give enough variation, but not so wide ranging that it becomes too spread out.
Figure 1: Tape Measure Square
I asked a person close by for two random numbers between 0 and 10. This guaranteed it would not be biased, as none of the people had taken a closer look at the field before.
The first number acted as the x coordinate and the second number acted as the y coordinate to make it consistent.
I put down my gridded square as close as possible to the coordinate with its bottom left corner. I used a 25-square grid, because that way it measures the spread better. If it were a 100-square grid or a 1-square grid, the numbers of the % Frequency Squares would be virtually the same as Density.
I measured the soil moisture in 9 spots within my square. I used a systematic method to measure this, because it gives a wide spread of data, which makes it very representative and therefore gives a more accurate average of the square’s soil moisture than a random method could.
I counted first the number of squares containing red clover and then its density within the whole square. Using two different methods of measuring abundancy gives more representative results, because one shows how spread out they are across the gridded square and the other shows the total number of red clovers within the square.
I then recorded light intensity in the middle of the square. Measuring it in the same place every time gives more accurate results. But because I was not able to measure the light intensity at the same time, the number varied due to changes in weather. That day the sky was fairly cloudy, so there was a frequent change between direct sun and the sun being hidden behind clouds, making my results pretty inaccurate.
The wind speed and temperature I measured by holding the anemometer about an inch above my head when sitting up straight. This method caused the measurements to be taken at a consistent height and made them more accurate. Just like with the light intensity the measurements varied over time, making the less accurate after all.
The soil compaction I measured in the left bottom square of my grid.
I repeated steps 2 to 9 a total of 13 times.
I started by taking my samples systematically, by going in a line from the edge of a swamp to the side of a road in the assumption that soil moisture would decrease along it. I wanted to do one measurement every meter. After the first four squares I changed my method, because that line, just like all others, had barely any red clover in its way, so I made the grid in an area in which the red clover was more abundant.
Safety, ethical or environmental issues:
Table 2: Risk Assessment
Risk Further Dangers Affected Prevention
Insect bites Bites can lead to infection and transmission of diseases. They can also cause redness, stinging and itchiness. Anyone working in natural areas, especially close to fresh water, but also in woodland and grassland Using insect repellent and wearing long clothing
Sunburn Causes redness and pain. Can also lead to an increased risk of skin cancer and other dermatological diseases Anyone working directly in the sun, especially in an open field without trees to give shade Using sunscreen, wearing long clothing and ideally a cap
Allergies Causes sneezing, running nose and itchy skin in most cases, but can cause more severe allergic reactions including infections such as conjunctivitis and swelling of the throat, etc. Anyone affected by hay fever and other allergies Taking reaction suppressing medicines, using eye drops and tissues. Avoiding areas with flowering plants that cause especially strong reactions
Working alone Getting lost, losing the group, inability to seek help when a problem arises Whenever being out of eyesight of the group Having a map of the area, telling a member of staff and the group were you go, have the right emergency contacts and a phone if cell service is available
To have as little impact on the environment as possible I used paths to get to the location I worked in to cause as little soil compaction and other damage as possible. When I counted the plants, I tried touching them as little as possible and made sure not to harm any flowers and other plants when laying my grid to the ground.
ANALYSIS
Raw Data
Table 3: Measurements taken on soil moisture squares 1 to 6
Sample Square 1 Square 2 Square 3 Square 4 Square 5 Square 6
1 in % to 1dp 7.7 8.7 9.1 9.8 8.1 7.1
2 in % to 1dp 8.1 9.3 8.4 8.0 8.3 8.2
3 in % to 1dp 8.0 8.9 9.5 9.4 8.2 9.1
4 in % to 1dp 8.4 10.1 10.4 8.7 8.2 8.3
5 in % to 1dp 8.5 8.1 9.7 8.1 8.5 8.1
6 in % to 1dp 9.0 8.9 9.5 8.3 8.7 8.4
7 in % to 1dp 9.3 10.1 9.0 7.6 8.4 8.9
8 in % to 1dp 9.5 10.0 9.5 7.6 8.4 9.2
9 in % to 1dp 9.1 9.1 9.5 7.5 7.9 7.9
Table 4: Measurements taken on soil moisture squares 7 to 13
Square 7 Square 8 Square 9 Square 10 Square 11 Square 12 Square 13
8.7 8.3 8.0 8.4 7.9 8.8 8.0
7.9 9.0 8.4 8.9 8.9 10.5 7.8
8.5 8.0 8.6 9.4 8.7 9.5 8.1
7.6 8.7 8.4 9.0 9.9 10.1 8.1
8 8.8 8.8 8.1 9.3 8.3 9.4
7.9 8.2 8.1 8.1 9.1 8.9 8.2
8.2 8.4 8.4 9.2 9.0 8.2 8.2
7.6 7.7 9.3 9.4 9.0 7.3 9.3
7.6 8.0 11.1 7.7 9.6 6.3 8.9
Table 5: Abundance of Red Clover as Density and Number of Squares out of 25 containing it
Square Number Density
Number of Squares out of 25
1 4 2
2 8 5
3 11 6
4 13 7
5 6 5
6 4 3
7 0 0
8 1 1
9 0 0
10 4 3
11 1 1
12 11 7
13 5 5
Table 6: Control Variables
Square Number Light Intensity (lux) to 3sgf
(+/-0/5lx) Wind speed (ms-1) to 1dp
(+/-0.05ms-1) Temperature (ºC) to 1dp
(+/-0.05 ºC) Soil compaction (kgcm-2) to 1 dp (+/-0.05kgcm-2)
1 871 2.0 22.6 2.4
2 505 1.4 21.5 4.3
3 886 1.8 22.6 3.3
4 718 2.0 24.1 1.7
5 966 1.3 28.1 3.2
6 621 1.3 31.7 3.3
7 881 3.0 30.0 4.5
8 1180 0.0 25.7 4.0
9 427 0.0 27.0 3.9
10 367 0.0 27.3 4.4
11 401 0.8 24.5 4.4
12 307 0.7 23.2 3.0
13 272 1.0 28.6 4.4
Processing Raw Data
Table 7: Means of the 9 soil moisture samples collected in each square
Square Number Mean Soil Moisture Value (%) to 2dp
1 8.62
2 9.24
3 9.40
4 8.33
5 8.30
6 8.36
7 8.00
8 8.34
9 8.79
10 8.69
11 9.04
12 8.66
13 8.44
Table 8: Numbers of Squares containing red clover to % Frequency Squares
Square Number % Frequency Squares
1 8
2 20
3 24
4 28
5 20
6 12
7 0
8 4
9 0
10 12
11 4
12 28
13 20
Presenting Processed Data
Figure 2: Soil Moisture plotted against Density
Figure 3: Soil Moisture against % Frequency Squares
Statistical Analysis
I chose Spearman’s Rank Correlation for my statistical analysis, because it measures the monotonic relationship, rather than only the linear, like the Pearson correlation does, between two variables, making it more general.
Rs=1-(6∑▒D^2 )/(n^3-n)
D = difference between R1 and R2
n = number of samples
Table 9: Rank Differences in Soil Moisture and Density
Square Number Soil Moisture Rank 1 (R1) Density
Rank (R2)
Difference (R1-R2) D2
1 8.62 7 4 6 1 1
2 9.24 12 8 10 2 4
3 9.40 13 11 11.5 1.5 2.25
4 8.33 3 13 13 -10 100
5 8.30 2 6 9 -7 49
6 8.36 5 4 6 -1 1
7 8.00 1 0 1.5 -0.5 0.25
8 8.34 4 1 3.5 0.5 0.25
9 8.79 10 0 1.5 8.5 72.25
10 8.69 9 4 6 3 9
11 9.04 11 1 3.5 7.5 56.25
12 8.66 8 11 11.5 -3.5 12.25
13 8.44 6 5 8 -2 4
∑▒D^2 =311.5
〖Rs〗_Density=1- (6*311.5)/(〖13〗^3-13)
〖Rs〗_Density=0.144
Critical Value=0.566
Table 10: Rank Differences in Soil Moisture and % Frequency Squares
Square Numbers Soil Moisture Rank 1 (R1) % Frequency Squares Rank 2 (R2) Difference (R1-R2) D2
1 8.62 7 8 5 2 4
2 9.24 12 20 9 3 9
3 9.40 13 24 11 2 4
4 8.33 3 28 12.5 -9.5 90.25
5 8.30 2 20 9 -7 49
6 8.36 5 12 6.5 -1.5 2.25
7 8.00 1 0 1.5 -0.5 0.25
8 8.34 4 4 3.5 0.5 0.25
9 8.79 10 0 1.5 8.5 72.25
10 8.69 9 12 6.5 2.5 6.25
11 9.04 11 4 3.5 7.5 56.25
12 8.66 8 28 12.5 -4.5 20.25
13 8.44 6 20 9 -3 9
∑▒D^2 =323
〖Rs〗_(% Frequecy Squares)=1- (6*323)/(〖13〗^3-13)
〖Rs〗_(% Frequency Squares)=0.113
Critical Value=0.566