Electric fishing demo
|Top Previous Next|
For this tutorial we will use the demonstration data set RemovalDemo.csv supplied with Removal Sampling 2. This data set was collected during an electric fishing survey of a small English chalk stream called the Chitterne Brook. A summary of the method used is as follows:
Quantitative electric fishing was undertaken at three sites on the Chitterne Brook on the 19th June 2001. This date was chosen to be prior to the introduction of stream support pumping. At each site a 30 m reach was isolated by stop nets and electric fished in an upstream direction. All of the fish captured were identified to species and standard lengths were measured to the nearest millimetre. Systematic fishing of the sites was repeated until the number of fish captured for all abundant species had declined over 3 successive passes. This was to allow a removal trapping method to be used to estimate population density. All the captured fish were subsequently released alive. Populations were estimated using the commercial software package Removal Sampling (Pisces Conservation Ltd.) to calculate population size using Zippin's method. This method assumes a constant probability of capture.
To open the data set use File|Open and select RemovalDemo.csv - stored by default in ..\My Documents\Removal Sampling Data\Demo Data
Removal Sampling 2 will open the data and display the data grid as shown below.
In this case we undertook 5 electric fishing sweeps of the 30 m stretch of stream. Only three species were caught; trout, eel and minnow. Because large trout are very much easier to catch than small trout, the trout numbers have been divided into fish more than 20 cm in length and those less than or equal to 20 cm in length.
When the data set was loaded Removal Sampling 2 immediately undertook a constant p method using the sum of all the fish.
Click on the Graph + Results tab and you will see at the bottom the estimate for the total number of fish in this 30 m reach of stream (the screen is shown below). The estimated population size is 172, with upper and lower 95% confidence intervals of 155 and 189. A glance at the graph indicates that the predicted number of captures is quite a good fit to the data, and the constant probability model was found to give a good fit (Chi-squared = 0.34, p > 0.9525)
Now we will examine the estimate for large trout alone.
First click on the Data tab again, and click on the title columns until only the > 20 cm trout column has a red dot in. It will look like this:
Now select the Constant p method from the Method drop-down menu. To look at the result click on the Graph + Results tab, and you will see the graph shown below. This gives a population estimate for large trout of 22 with upper and lower 95% confidence intervals of 22 and 23.4. A glance at the graph indicates that the predicted number of captures is quite a good fit to the data and the constant probability model was found to give a good fit (Chi-squared = 0.98, p = 0.8054)
Trout clearly fit the constant p model rather well; now we will look at the minnow data. The minnow is a small fish and, due to its size, it is difficult to sample well with electric fishing equipment. So we expect a much lower probability of capture.
First open the Data tab again and click on the title columns until you see a red dot in the Minnow column:
Now select the Constant p method from the Method drop-down menu. To look at the results, click on the Graph + Results tab and you will see the graph shown below.
This gives a population estimate for minnow of 51 with upper and lower 95% confidence intervals of 24 and 137. These confidence intervals are wide and reflect the fact that the graph shows that minnow numbers did not decline sharply with increased sampling. This is shown by looking at the Calculations tab which shows that the estimated probability of capture of a minnow on each sweep of the stream is only 0.118 or about 12%. In contrast the probability of capture of a large trout was about 59%.