- Soil samples from Non-trampled (Area 1) and Trampled area (Area 2) was obtained using an trowel, collected in a bag and the following tests were performed back at school-
- To measure Salinity of the samples- Firstly, the soil sample has to be dried out; small sample is weighted into an evaporating dish and then put in an oven (90°C). The dish was removed at intervals and allowed to cool and re-weighed until the mass doesn’t change. The dried soil is mixed in suitable volume of water (enough to wash the soil but not dilute the salt in it). Barium sulphate can be used to flocculate the particles, then the soil is filtered using filter paper in a funnel and conical flask. The concentration of salt is then measured in the filtrate using a salinity meter. A value in ‘g salt/100 g soil’ can be gained.
- Acidity of the samples- Add water to small soil samples in a test tube. Add barium sulphate to the sample, this causes the soil particles to stick together (flocculate) and sink to the bottom, leaving just the clear water to be tested. The test is done with a pH strip.
This was done through using a trowel, the soil was collected in a bag and the various tests were performed back at the school.
Changes to plan after Preliminary run-
I didn’t really make any major changes to my plan after the preliminary run, I used a point quadrat and I genuinely found it difficult to gauge a percentage cover. The preliminary reaffirmed by views that my plan was good to gain me the results I needed, accurately and efficiently. I also was more confident in using the clinometer gun.
Apparatus-
- Ranging Poles (× 2)
- Clinometers
- Measuring tape
- Square Quadrat
- Trowel
- Small plastic collection bags
- Protective clothing and wellington boots
- pH test strip
- Salinity meter
- Filter paper
- Evaporating dish
- Funnel and conical flask
- Barium sulphate
Presentation and Analysis of data-
The plant species data will be represented in a pie-chart, as this allows us to see collectively the types of the species present. As for statistical analysis- standard deviation was used as a descriptive statistical test to see how far the results lay from the mean thus, check their accuracy. Next, t-test, an analytical statistical test was used to compare the actual difference between two means in relation to the variation in the data (expressed as the standard deviation of the difference between the means). Finally, Simpsons Diversity Index was done to find the species diversity of the areas, in ecology; it is often used to quantify the biodiversity of a habitat. It takes into account the number of species present, as well as the abundance of each species.
Independent/Dependent Variables and Accuracy/Reliability-
Important Independent variables like the temperature, humidity, salinity, pH and tide levels were controlled by doing all the experiments on the same day. This minimised the chances of anomalies being introduced due to varying conditions. Furthermore, same equipments were used to maintain accuracy of samples and results. By controlling these independent factors, a lot of the dependant factors were effectively controlled e.g.- by using the same trowel, all soil samples were likely to be more even thus, when performing salinity tests equal samples could be used. Also, using the same quadrat introduced a certain consistency when recording the results; it decreased chances of anomalous data. Finally, I took 30 separate quadrat readings per area; this was done to increase accuracy and the reliability of the overall conclusion.
Safety and Ethical Implications-
- As large portions of the saltmarsh are underwater when the high tide comes in, the tide timetables should be checked very carefully before starting work on the marsh. It is unadvisable to work alone on the marsh, groups should stick together to prevent injury to their companions, there are hidden creeks that can cause serious injuries to the ankle or knee. In case of injury one member can rush back to get help while another stays behind with the injured.
- A mobile phone should be kept on person at all times with the number of the site manager to contact during emergencies.
- The ethics of this experiment would be that I am further trampling plant life as I do my various tests and I am taking soil samples away from the marsh. However, I tried by best to not trample excessively; I made sure my wellington boots weren’t very heavy so the least possible damage was caused. As for the soil sample, the amount of negligible and I wouldn’t have an effect on the environment.
How did I work safely?
- The site manager at Freiston shore (Simon) checked the timetables for us and informed us accordingly. He also gave us his phone number in case of an emergency. I worked in a group with five people just in case anything went wrong.
- The equipment we were using was not dangerous however; care was taken when carrying the ranging poles.
- We informed the supervisor of our whereabouts at regular intervals. I think by doing all these things I was able to ensure that I was working safely throughout project.
Adaption of the plan during the experiment-
As the experiment went on I realised that I needed help when measuring the distance and slope angle between the ranging poles because the wind was quite strong that day. I asked for help from my colleague to hold up the poles and hold the measuring tape, this was not originally included in the plan but I think these little changes allowed me to stay accurate.
Did I notice any trends while recording?
As I continued to record my results, some trends began to become clear for example, the population density was indeed very different. There were lot more plants present in the non-trampled area than the trampled regions. There was also a lot more bare soil in the trampled region as expected. Finally, the types of species also varied slightly. I shall know in the interpretation section whether these trends I noticed were compatible with my prediction.
OBSERVING AND RECORDING-
Only the relevant parts of the results associated with each of the comparable aspects are displayed here- the full results are in the data appendix, included at the end of this project. This includes the complete set of quadrat readings for both the areas.
Did I make sufficient measurement?
I did 30 separate quadrat readings in each area. This gave me a very accurate base of results to work from while doing each of my statistical analysis. Secondly, I also did 5 readings per area when measuring the salinity and pH of the soil, this was once again done for accuracy because the pH and salinity are independent variables that must be kept constant. Thus, I feel that my measurements were sufficient.
Measuring of sufficient conditions-
As mentioned above, I felt that salinity and pH of the soil were something that should be constant, if the results were to be reliable. Thus, I took soil samples to measure the sufficient conditions, full results are in the appendix and they show a constant trend, but I have shown the mean below to give a basic idea. Finally, as mentioned earlier in the methodology, I did slope angle for both the area using the clinometer and ranging poles.
Salinity readings of the soil ‘g salt/100 g soil’-
Slope angles-
As the results show, the conditions were fair in both the areas and this would have only added to the accuracy of my overall project. The pH was constant, the reading was closer to acidic (5) because I did my tests in the high swamp area, where plant life had established itself, the aerobic respiration of these plants would have decreased the salinity of the area, as the plants use the salt. This was also the reason why the salinity was not very high.
Any Anomalous Data or Changes to the plan?
During my investigation, I was lucky not to come across any anomalous data when recording my results, I think this had added to the accuracy to my statistical analysis. This was because I made slight adjustments to my initial plan eg-
- I got a colleague to check my quadrat readings at random points, this was done to improve accuracy and minimise anomalous data.
- When doing the slope readings, a colleague held up the ranging poles to make sure they were straight.
INTERPRETING AND EVALUATING-
Population density-
The quadrat data is graphically presented above. The key for the species is in the appendix. Clear percentage differences can be viewed between species C, D, J and N. Also, as I predicted, there is a lot more mud (O) in the trampled area compared to the non-trampled area.
Overall mean of all the species (excluding mud (O)-
Species diversity-
n = total number of particular species
n-1 = 1 subtracted from n
N = total number of all the species
N-1 = 1 subtracted from N
This was gained for both the areas through using Simpson’s Diversity Index. 0 = no diversity and 1 = infinite diversity. After the index, D is gained (through the method shown above), its then subtracted by 1 (1-D), to give an overall diversity index.
Non-trampled Area-
Trampled Area-
The above results agree with my prediction that, even though the density of the areas differed, the diversity of plants are very similar, there is only a difference of 0.03 which is minimal. This proves my prediction that even though trampling causes disturbance in numbers, the diversity is still present.
Types of species found-
This was gained through using the t-test which is an analytical statistic between two sets of data, 5% is the accepted barrier, any percentage higher than that, shows that the probability of species being present is inaccurate. The T-test also takes in the degree of overlap between the two results and lets us see how certain we are in saying that the means are, or not, significantly different from each other.
T-test between the species found in Area 1 and Area 2-
Conclusion and Disproving the Null hypothesis-
Therefore, in conclusion, I would like to sum up my findings. The three different aspects that I was investigating were-
- Population density- The population density was certainly affected by the trampling, as I predicted it would. Overall, the species means were 110.67 (Area 1) and 84.63 (Area 2), this shows a considerable difference. It is worth mentioning that in the trampled area there was lot more mud (O), another sign of reduced population density. In biological terms, the increased pressure exerted by boots, kill plants and churn up the soil, this destroys the plant habitat and reduces density.
- Species diversity- The species diversity in both the areas where very similar 0.63 (Area 1) and 0.60 (Area 2), this proved that the trampling has no effect on the variety of species present, only the density. This agreed with my prediction, the biological reason being, the trampling might disturb the density of plants but as long as there are nutrients present in the soil and favourable weather conditions, plants will continue to grow and replace the dead ones.
- Types of species found- The types of species found were pretty unaffected by the trampling, the t-test proved that the chances of species randomly being present there was very minimum and this shows not only the accuracy of results but also the fact that even though trampling has occurred in one of the areas, the types of species found are still constant. This is because even though we are sampling to different area, we are still in the same marsh furthermore, the soil conditions in both areas were pretty similar and thus, both areas have the right conditions for species to grow. It is true that some species weren’t found in either area but this can be explained with the affects of succession, the plants that are found have evolved to exist in those conditions while others are perhaps pioneers or climax organisms.
Thus, I can disprove the null hypothesis to a certain extent because quite clearly trampling has an affect however, the null hypothesis is correct that only population density is affected, the other two aspects remain quite constant. Therefore, this proves that my hypothesis is correct- ‘Trampling has an effect on the salt marsh vegetation. However, the species diversity and types of species found are not as affected as population density.’
Limitations of results and Suggested modifications-
Random number generator should be used or perhaps GPS system. Marking out a square would also improve the sampling. More areas should be sampled on different days, different months etc.
DATA AND VISUAL APPENDIX-
KEY-
Development of a salt marsh-
Quadrat Readings for Non-trampled Area (Area 1)-
Quadrat Readings for Trampled Area (Area 2)-
Simpson’s Diversity Index-
Non-Trampled Area (Area 1)-
Trampled Area (Area 2)-
Soil Samples-
Salinity readings of the soil-
http://www.rspb.org.uk/reserves/guide/f/freistonshore/map.asp
http://www.theseashore.org.uk/theseashore/Saltmarsh%20section/Saltmarsh%20earliest%20stage.html
3 http://www.theseashore.org.uk/theseashore/Saltmarsh%20section/Saltmarsh%20earliest%20stage.html
4 http://www.theseashore.org.uk/theseashore/Saltmarsh%20section/Saltmarsh%20stage%202.html