I will use kick sampling for 1 minute as a method of collecting my data.
Kick sampling involves standing in front of a sweep net, and disturbing the sedimentary so that any species present are carried into the net. The nature of kick sampling means that I must stand in front of a net and kick the sedimentary downstream.
Once I have my sedimentary, I will empty the net into a white tray full of water. Then for 5 minutes I will count the number of species present.
Method
In the pilot study, it was found that the pH and temperature was constant throughout the river. Certain areas of the river that were measured in the river will be chosen for the main project because conditions such as depth, and velocity were similar, and variables could be mitigated. However, because the experiment was carried out on a different day, the sites were still measured so the variables that may have changed can be recorded.
In the main method, there were 2 stages that were carried out in order (so the data could be logically processed). First, the attributes of the environment were recorded. This involved measuring the various different aspects of the river. So that any reasons for anomalous results that were obtained could be traced. Measuring the river – a larger river may contain a larger number of organisms (not necessarily a larger number of species). A tape measure was used to find the width of the river, because an accuracy of 2 decimal places was enough to calculate the location of the depth measurements. A meter rule was used to find the depth of the river, because it is rigid, and so could be placed on the riverbed and read off. 4 measurements of the depth were taken across the width of the river. To work out where these measurements must be taken, the width of the river was divided by 4. Only an accuracy of 1 decimal place was used, because the river is constantly moving, and a more accurate measurement would be impossible. Measuring the Velocity (so that a riffle or a pool can be identified if not visibly obvious).
A meter rule was placed into the river and dye dropped at the top. The time taken for the dye to travel the length of the ruler was measured using a stopwatch. The formula Speed = Distance ÷ Time, was used to convert results obtained into meters per second. By keeping the distance to 1 meter each time, distance becomes a constant and speed is easier to work out.
pH may affect what species are present. If the pH is not constant then it may need to be taken into consideration when showing the correlation of the species present and the BMWP score of the environment. A pH tablet was placed in sample of the river, and the colour compared to a colour chart. After carrying out preliminary work, it was decided that 16 samples would be an appropriate amount of data to collected in the allotted time. Kick sampling and a net were used to collect each sample. 10 kicks were used each time to collect the sample so that organisms collected for analysing. 5 minutes was spent counting different species. The BMWP scores of the various species found will be added up per riffle or pool. This data will be used to work out the Spearman’s Rank co-efficient along with the number of species found.
Risk Assessment
A risk assessment will need to be carried out:
- Be careful in river, the water may be contaminated with gastrointestinal diseases (wash hands before eating etc).
- Wear appropriate clothing to be safe in river (stay dry, wont slip over on the bed), on road (so vehicles can see you).
Results
Working out Spearman’s Rank
Step 1#
plotting a scatter graph to show the relationship between the BMWP of the environment, and the number of species found there.
step 2
all of the data is given a rank number. To do this, data from one of the variables is put in numerical order (to make numbering easier) and then all the data is given a rank number. The rank number is assigned in numerical order except where there are repetitive sets of data, e.g. 2 of the same number. Then the average of the rank number is assigned:
Would become:
Step 3
Calculating the difference between the ranks; D is worked out by subtracting one rank from the other. The sum of all D values should equal zero:
ΣD= 4.5-0.5-1+4.5-2.5-1-1+5+3+1-6-3-3
=0
Step 4
Calculate a ΣD2 value; square all values of D and add together
ΣD2=20.25+0.25+1+20.25+6.25+1+1+25+9+1+36+9+9
= 139
Step 5
Calculate the spearman’s rank coefficient. Where n = the number of samples that I collected;
Spearman's Rank Coefficient (rs)= 1-
= 0.80441
Step 6
The critical value of an n value of 16 is 0.506. Because the value of Rs is greater than this, then there is significant positive correlation between the two variables.
Analysis
The scatter graph shows that there is positive correlation between BMWP and number of species present, however there are significant differences where I have collected the same number of species, but the BMWP differs greatly. For example, there are 3 areas where 4 species were found:
This graph suggests that the BMWP is NOT directly related to the species, and that another variable is affecting results.
As this table shows, the 2 sites where the BMWP score is significantly lower are pools. These pools exhibit very low dissolved oxygen levels.
This graph shows that generally, the riffles contain more oxygen than the pools. The species with higher BMWP scores would be expected to be found in the riffles
Discussion and Evaluation
Generally there is some evidence that my hypothesis is correct, however there is too much variation in my results for it to be reliable.
For example, in area 7, no species at all were collected. This area had been recently subjected to a chemical waste spillage. In areas 3 and 4, the species and BMWP were higher in areas where BMWP score would be expected to be lower, i.e. pools. This suggests that my experiment does not fully show what species are present in different areas of the river. The number of species which have adapted to the conditions of the riffle will be lower than that of pools.
Overall I have found many more species in the pools than in the riffles. I am convinced this is because pools have more sediment to kick up, so therefore I am more likely to pick up species. I have only been able to collect up to 6 species at a time. I cannot have collected all species that were present in the river, so the BMWP score that I have collected cannot be true. This makes my results extremely unreliable. The conditions of the river are not true for other rivers; in that there seems to be little diversity present. Although I found this on my pilot experiment, it was impossible to select another river to study to compare my results to.
Limitations of methods
Due to the tentative nature of this small experiment, there are several large errors that could occur with methods used. For example: kick sampling, as a method is very inaccurate. It is very hard to replicate same results each time such as the same number of kicks, kicking up the same amount of sediment each time, kicking with the same strength each time, kicking all sediment into the sweep net etc.
The method used to calculate the velocity is very inaccurate. The red dye travelling the river was only “judged” to have crossed the meter rule. It was also impossible to place the dye in the same part of the river, other methods such as dropping an orange in the river along a meter rule proved no more accurate.