Justification of Investigation
It is important that the temperature of each shoreline is monitored as it can have a direct influence on the height and width (morphology). Evaporation will occur on the shore as it is highly exposed in the sunlight. This can lead to cooling of the fronds as water is released. This will affect the optimum conditions needed for maximum growth of the Fucus Serratus. Also, with regards to temperature is that fronds within the water will retain heat better than those which are located above water level. This is due to the fact that water acts as a good conductor of heat and will therefore aid the growth of the Fucus Serratus.
From preliminary work conducted prior the actual investigation it was found that the Fucus Serratus fronds that I will be investigating is a very large population and is situated all among the shores and the different zones I would be investigating. By looking at each zonation it will be easier to see the differences between two extremes and any anomalies within the data obtained.
Analysing Data
- Statistical Test = t-test
- Graph analysis
Apparatus
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Measuring tape – to measure the Fucus Serratus fronds
- 50cm by 50cm Quadrat - to collect data from the square grid
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Measuring callipers – to measure the length and width of the Fucus Serratus fronds
- Materials to record results – pens, pencils to record the data
- Thermometer – to constantly check that the temperature is maintained throughout the experiment
- Scientific calculator – to use as a random number generator and to hold data
Safety Issues to consider
- Whilst placing the quadrat in certain areas and measuring the fronds ensure that there aren’t any other living species around, which could be damaged/harmed in the process. This includes crabs and limpets etc.
- The tide is a danger which I could be exposed to due to its varying size and force. To ensure it is a low tide the internet and support staff will be consulted to choose a day which will have a low tide.
- Protective clothing should be worn; this includes; rain resistant coat, flexible leg wear and boots to protect all areas of the foot and legs.
Field Sites
Rocky Shore, Abbotsham, Devon, UK - Exposed
Using Equipment
Modified Calliper
Method
For Lower and Upper Shore
- Choose random number co-ordinates from random number generator (scientific calculator) and then place the quadrat on the specific co-ordinates
- Measure the temperature of water in the quadrat. The temperature of each quadrat should be approximately within 5˚C of each other, this ensures that all fronds are exposed to similar conditions. This will keep results as accurate as possible
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Locate the longest looking frond in each Fucus Serratus grouping area
- With the measuring tape measure from base to tip and record results in millimetres (mm)
- With the measuring callipers, measure the width of the frond centre in millimetres (mm) to 2 decimal places and record results.
Repeat this process until a large number of data has been collected for both height and width on both lower and upper shores.
Table of Results
Upper Shore
Statistical Test
For greater reliability, analysis and to interpret my results I have chosen to conduct a T-test this is a type of statistical test. This will show the relationship between the height and width of the Fucus Serratus fronds. It is worth mentioning however, that at this stage certain conclusions can be drawn from the raw data that has already been collected.
The statistical test that will be used is the student t-test. It has been chosen because it will determine the amount of overlap between two sets of data (height and width) also, the data is continuous.
Two tests will be carried out, one for the length and one for the width. This will help me in looking at the relationship between the Fucus Serratus fronds.
Null Hypothesis – There is no significant difference between the length and width of Fucus Serratus fronds.
The t-test formula that will be used is:
Where:
s1 = variance of data set 1
s2 = variance of data set 2
n1 = size (number of observations) in data set 1
n2 = size (number of observations) in data set 2
= mean of data set 1
= mean of data set 2
t-value for length = 0.7399
t-value for width= 1.12102
Critical value = 1.860
Levels of significance = 0.05
Conclusion: As calculated t-value is smaller than the critical value, the experimental hypothesis is rejected and the null hypothesis is accepted.
The degrees of freedom:
DoF= 10 – 2 = 8
Critical T-Value Table
0.10 0.05 0.025 0.01 0.005 0.001
1. 3.078 6.314 12.706 31.821 63.657 318.313
2. 1.886 2.920 4.303 6.965 9.925 22.327
3. 1.638 2.353 3.182 4.541 5.841 10.215
4. 1.533 2.132 2.776 3.747 4.604 7.173
5. 1.476 2.015 2.571 3.365 4.032 5.893
6. 1.440 1.943 2.447 3.143 3.707 5.208
7. 1.415 1.895 2.365 2.998 3.499 4.782
8. 1.397 1.860 2.306 2.896 3.355 4.499
9. 1.383 1.833 2.262 2.821 3.250 4.296
10. 1.372 1.812 2.228 2.764 3.169 4.143
Now I can analyse my results and work out the critical value by looking across the table at 8 degrees of freedom and looking at the 0.05 level of significance: the critical value is 1.860. The t-test result for both length and width are both smaller than this critical value and therefore it shows there is no significant difference between the length and width of Fucus Serratus fronds (mm) in the two different zones. Therefore, it shows that I am able to accept my null hypothesis and reject the experimental hypothesis.
Analysis
The data which was collected has now been represented graphically, so I am now able to analyse the data and identify any significant trends.
From looking at the graphs, the main point to consider is the fact that the longer fronds exist mainly along the lower shore. Also, the widths of the fronds begin to decrease along the lower shore. One anomalous result which was discovered was in quadrat 8 where the width of the frond is much bigger than any other frond sample in the lower shore quadrats.
This could be due to the fronds on the lower shore are surrounded by water which is a very good conductor of heat. Water could move in by osmosis, causing some fronds to expand in size, but also some fronds to reduce their size. The heat can be retained for optimum growth temperatures and with a high supply of water and light then longer fronds at the lower shore were to be expected. As growth is controlled by enzyme activity, enzymes work best at higher temperatures, as they have most the kinetic energy. If the temperature is too high, the enzymes could denature as the bonds in the tertiary structure vibrate erratically so that they break. Altering the shape of the active site causes the enzyme not to work anymore. If the temperature is not high enough then the enzymes that control growth may be inactive or not performing at a maximum rate due to lack of kinetic energy. The temperature must be near optimum on the lower shore.
At the upper shore there is a higher rate of evaporation. This causes an increased level of salinity which can have an affect on plant growth. Enzymes favour a neutral ph, but changes in pH have a direct effect on the ionic bonds which hold the tertiary structure in place. This can once again alter the shape of the active site and cause the substrate not to fit.
Abiotic and human factors should also be put into consideration; this includes wind, rain, temperature, salinity and also human input. In these areas of the shore, people tend to walk here and come for sight-seeing. People could accidentally step on fronds causing them to damage and alter in shape and size which could have an overall affect on the morphology of the fronds.
Predation can also affect the number of fronds and the size of each frond. Birds, sea-animals, dogs etc. all are found within this environment and so there food source in such area would be plants. These plants could also be competing with other sea-weeds of different species, so there could be interspecific and intraspecific competition.
In today’s society there has been a huge increase in the carbon dioxide levels and an increase in pollution. Pollution can affect all living organisms. Sea-weeds of this kind can be affected as the sea is usually seen as an area which contains toxic wastes, and these toxins could be taken up by the fronds causing them to die out and alter in shape and size.
Overall, the upper shore contains fronds that are longer and thinner whereas on the lower shore, the fronds are shorter and wider. This statement can be supported by looking the graphs and results tables for the height and width on the upper and lower shores.
Evaluating
One factor which could question the significance of this investigation was the age scale. All were measured on the same day but this can be misleading as growth and age have a positive correlation i.e. the older you are generally the larger you will be. This means that many of the results could be only taking into account a limited number of age groups as opposed to the entire age spectrum but due to a limited time frame this was not possible.
A problem with this investigation is that the sample results were only obtained from one shore, Abbotsham, Devon, UK. Even though two different areas of the shore were used, this could still change the overall results. This means that the trends may only apply to this shore and be different when compared with others. This wasn’t possible due to the limited amount time. To increase the reliability of these results, the same sample size should be obtained from a different shore. Not only will that display trends on a broader scale but it will make it a fair test.
Other strategies could have been applied to obtain more reliable results. Temperature and pH measurements could be taken at each specific quadrat location; keeping the investigation fair and have a solid justification for anomalous results. However, this type of accuracy would require a lot of time consuming methods.
Abiotic factors such as salinity, wind speed, sun rays on each shore should be measured correctly in order for the results to be as accurate as possible. In this investigation such measurements weren’t taken as there was a time limitation. In future investigations, more time should be taken into preparing the investigation so that all types of variables can be controlled.
By having all these controls and all the variables controlled any anomalies which did arise in this investigation would be less likely to occur in future experiments. Anomalies only occur when there are inaccuracies within results and data obtained, however, by having much accurate data there would be fewer anomalies and the results more accurate.
In areas where there were lots of different species of sea-weed and other similar species, there would be more competition for light and nutrients. The areas which I studied were areas of very high competition and so the Fucus Serratus frond sizes may have differed. In future investigations, both areas of competition and non-competition should be taken into account; this would leave us with much more accurate frond sizes.
Random sampling avoids bias and during my investigation a random number generator method was chosen. This was a good and accurate method to use but in the future I would suggest trying some other type of sampling method; such as: line or belt transect. This type of sampling measures the distribution of species in a straight line across the habitat and the species are recorded.
In this investigation the only type of sea-weed investigated was Fucus Serratus but from preliminary experiments I found that there were many other types of species I could have looked at which may have given a more representative sample. Some sea-weed species may have been more common than others, so next time more research will have to be done on the species in the area.
Future investigations will have to be more research based. In this investigation they were measured based on their appearance as the common Fucus Serratus, no cross species variation was taken into consideration. Also, a wider range of data collected would make the research more accurate, so a minimum of 25 samples would be collected in the future.
Bibliography
- AS biology by Bill Indge – page 62 Enzymes
- A2 biology by Bill Indge – Enzyme Chapter
- Maths for advanced Biology Cafogan A & Sutton R. – T-test guide
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