Printing:

Customizing the Content:

Introduction

Aim• We aim on investigating asymmetrical and symmetrical seeds to identify which can travel further. We will

use a series of experimental methods to investigate our hypothesis. We will measure the symmetry of the seeds using CAD (Computer Aided Design). After gathering the data, we will release the sycamore seeds from a fixed height in a controlled environment. We will then measure the distance the seeds travel from the replicated parent plant.

Hypothesis

• Our hypothesis was that the more asymmetric the seeds were the further they would travel.

MaterialsMaterials & equipment used

Seeds Camera

Graph Paper Envelopes

Leaf Blower Computer

Measuring Tape Computer Programs

Ruler

Procedure

Results

Conclusion

• It is clear that there is a correlation between the average % asymmetry length of the

sycamore seeds and the distance that they travel.

This can be shown in our results as when we did a Pearson co-efficient on our Ardee, Ardgillan, Louth

Village and Dundalk seeds we got correlations of 1%, 10%, 28% , 17% respectively.

Our results have also shown that there is a correlation between the average %

asymmetry width and the distance they travelled.

Our Pearson Co-efficient results showed that there is a correlation between these two variables of 14%,

9%, 9%, 59% respectively.

• After measuring all of our 383 seeds from spatially isolated areas from Dundalk to Dublin

we conclude that as a species, Acer pseudoplatanus seeds are asymmetrical in terms of

both seed length and seed width.

We believe they have evolved this way in order to increase their chances of germination.

What’s next?

• We have many more experiments to carry out to further our investigation:We will repeat the experiment on a larger scale. We would use a greater sample size and take representative samples from numerous locations. Our samples were taken from the East of Ireland, we would like investigate seeds from all over the country.We acknowledge that the distance the seeds travel correlates with the degree of symmetry , but we also acknowledge that there are other important factors that influence the distance the seeds travel from the parent tree. We agree that one of these factors is mass. We will take the mass of the seeds into account as a variable factor. We will also conduct an experiment manipulating the wing to a certain degree of asymmetry and measure the distance it travels. We also plan on investigating if this correlation is due to causation.

y = 1.2986x + 158.73

0

200

400

600

800

1000

1200

0 10 20 30 40 50 60 70

Distance travelled

(cm) (n = 98)

% Seed Length Asymmetry (n = 98)

Graph 1: Effect of Ardgillan Sycamore Seed Length % Asymmetry on Distance travelled in "Wind"

(Scatter Graph with Linear Regression)

y = 0.802x + 160.59

0

200

400

600

800

1000

1200

0 20 40 60 80 100 120

Distancetravelled

(cm)(n = 98)

% Seed Width Asymmetry (n = 98)

Graph 2: Effect of Ardgillan Sycamore Seed Width % Asymmetry on Distance travelled in "Wind"

(Scatter Graph with Linear Regression) Standard Deviation -17.40659459-Standard Error -1.75833158195%

y = 0.2185x + 179.73

0

500

1000

1500

2000

2500

0 50 100 150 200 250 300

Distance Travelled

(cm) (n=248)

% Seed Length Asymmetry (n=248)

Graph 3: Affect of Ardee Sycamore Seed Length % Asymmetry on Distance travelled in "Wind"

(Scatter Graph with Linear Regression)Standard Deviation - 11.92830666Standard Error -0.77319727995% Confidence Interval -1.51543882Pearson Co-efficient: 0.00906843

0

500

1000

1500

2000

2500

0 50 100 150 200 250 300

DistanceTravelled

(cm)(n=248)

% Seed Width Asymmetry (n=248)

Graph 4: Affect of Ardee of Sycamore Seed Width % Asymmetry on Distance Travelled in "Wind"

(Scatter Graph with Linear Regression)Standard Deviation -15.85433199Standard Error -1.02339272995% Confidence Interval -2.005812892Pearson Co-efficient:0.136747

y = 2.9591x + 109.14

0

100

200

300

400

500

0 5 10 15 20 25 30

DistanceTravelled

(cm)(n=29)

% Seed Asymmetry Length (n=29)

Graph 5: Affect of Louth Village of Sycamore Seed Length % Asymmetry on Distance travelled in

"Wind" (Scatter Grapth with Linear Regression)

Standard Deviation -7.568396196Standard Error -1.40541589195% Confidence Interval -2.75456453Pearson Co-efficient:0.2748501

y = 0.547x + 128.37

0

50

100

150

200

250

300

350

400

450

500

0 10 20 30 40 50 60 70

DistanceTravelled

(cm) (n = 29)

% Seed Asymmetry (n = 29)

Graph 6: Affect of Louth Village Sycamore Seed Width % Asymmetry on Distance Travelled in "Wind"

(Scatter Graph with Linear Regression) StandardDeviation -13.0953StandardError - 2.431795% ConfidenceInterval -4.7661Pearson Co-efficient-0.0879016

y = 1.9994x + 119.85

0

50

100

150

200

250

300

350

0 5 10 15 20 25

Distance Travelled

(cm)(n = 8)

Seed Length % Asymmetry (n = 8)

Graph 7: Affect of Dundalk Sycamore Seed Length % Asymmetry on Distance Travelled in "Wind"

(Scatter Graph with Linear Regression)

Standard Deviation7.087957346 -Standard Error -2.50597135295% Confidence Interval -4.911613597Pearson Co-efficient: 0.17202

y = 4.1171x + 82.712

0

50

100

150

200

250

300

350

0 5 10 15 20 25 30 35 40

Distance Travelled

(cm) (n = 8)

% Seed Width Asymmetry (n = 8)

Graph 8: Affect of Dundalk Sycamore Seed Width % Asymmetry on Distance Travelled in "Wind"

(Scatter Graph with Linear Regression)Mean = 13.7323STDEV = 11.8414SE = 4.186695% CI = 8.2055Pearson = 0.5918

These graphs show that there is a correlation between the degree of asymmetry of the seedsand the distance they travel from the parent plant.

The Symmetry behind the seed and it’s common misconceptions. By looking at a “Helicopter” seed we assume the wings are symmetrical. This project looks at this so-called “symmetry” and the affect it has on wind dispersal. This investigation examines the science behind sycamore seeds (a)symmetry using statistics and data analysis. Are sycamore seeds symmetrical or asymmetrical? Does this affect the distance they travel? Ideally the seeds should travel as far as possible from the parent plant in order to increase the chances of successful germination. We chose to investigate sycamore seeds as they are unique with a very distinctive look. (Fig.1)

Fruit

Wing formed from ovary wall

Fig.1: Sycamore Seed

ANOVA: Comparing Average % Asymmetry width and Distance.

Source of Variation SS df MS F P-value F crit

Rows 4927.525 3 1642.508 1.175681 0.44865 9.276628

Columns 26059.75 1 26059.75 18.65315 0.022871 10.12796

Error 4191.21 3 1397.07

Total 35178.49 7

ANOVA: Comparing average % Asymmetry Length and Distance Travelled.

Source of Variation SS df MS F P-value F crit

Rows 5027.63 3 1675.877 1.226672 0.435305 9.276628

Columns 28232.79 1 28232.79 20.66523 0.019938 10.12796

Error 4098.593 3 1366.198

Total 37359.01 7

An Investigation into (A)symmetry of Sycamore Tree, Acer pseudoplatanus

“Helicopter” Seeds and its Effect on Dispersal Distances.

Ardee (n=248), 17.10357386

Ardgillan (n=98), 16.1280042

Louth Village (n=29),

11.3132879

Dundalk (n=8), 11.718

0

5

10

15

20

25

Ardee (n=248) Ardgillan (n=98) Louth Village (n=29) Dundalk (n=8)

Perc

enta

ge A

sym

met

ry

Area Seeds Collected from

A Comparison of the Average % Seed Asymmetry Length and the Average % Seed Width Asymmetry and Standard Deviation of the

distance travelled for Sycamore Seeds Collected from Spatially Isolated Areas.

% ASSYM L %ASSYM W stdev dist

We Picked the Seeds.

We choose trees in the specific areas that were the most elite sycamore trees. This was to ensure that we would havethe best specimen of sycamore seeds for our analysis. We took representative samples of seeds ie. we picked the seedsfrom different areas of the tree.

We took Photos of the Seeds.

We laid out the graph paper and put 10-12 seeds on each sheet. We labelled the seeds bywriting their number above each one. We also labelled the batch by putting their area on thetop of the pages. Once we labelled the seeds we used the iPad and iPhone to take photos ofeach page.

We Used Logger Pro 3.5 To Measure The Seeds.We used a computer software called Logger Pro 3.5 to measure the sycamore seeds. This allowed us to measure the length and width of each seed. We did this by drawing a line from the petiole of each seed to the furthest point on the left wing. This is our left length of the seed. We repeated this for the right length. We also measured the thickest part of the left and right width. We repeated this for all 383 of our seeds.

We Measured The Distance The Seeds Travelled:

Our second experiment was finding the distance the seed travelled from the parent plant.We carried out this experiment in our school gym. The balcony in our gym replicated theparent plant. We represented a gust of wind using a leaf blower. The wind was controlledby releasing the seeds into the “wind” after a set time.

We set a fixed point on the balcony: to put the leaf blower and to where the seeds wouldbe released from. Vertically under this point the measuring tape was set.

Inputting the data:

We created an excel document. We inputted the seed length and width from logger pro into excel.

We found the degree of asymmetry using the percentage difference formulae. We did this on an onlineapplication as it was quick and efficient. We inserted the results into the excel document.

The distance the seed travelled was inputted into the data.

We found the max, min, mean, median, mode, range, variance, standard deviation, standard error andconfidence interval of the seeds using excel formulas.

Observations We observed that the sycamore seeds that we collected in Ardgillan didn't travel as far as the other

seeds we collected. We think that this is because we collected them earlier than the other seeds. They

were greener in colour and this means that there is more chlorophyll and other photosynthetic pigments

in the seed and also more water. This means that they should have a higher mass than the other brown

seeds we used in our experiment. We think that these seeds didn’t travel as far as they had a higher

mass. We also believe that other climatic factors such as wind direction, wind speed, air temperature,

air humidity, precipitation and ultimately seed height (which we controlled by dropping seeds inside a

gym from the second floor) are variables that affect the distance the seeds travel.

Each seed was released into the replicated wind. The distance travelled was measured using the measuring tape and theresult was recorded.

Often the seeds broke in half, in such a case we measured the distance each of these travelled and averaged the twodistances.

.

Fig.4 Excel Document

Statistical Analysis using the ANOVA