How would you test the hypothesis 'the distribution of invertebrates in a habitat depends on light intensity?

Answer 1

1. Place the choice chamber on the bench.

2. Cover sectors with different layers of translucent material. Leave one sector with no cover.

3. Place a bench lamp directly over the choice chamber and turn it on.

4. Put 20 invertebrates into the choice chamber.

5. Start a stopwatch and leave for two minutes.

6. Record the number of invertebrates in each sector.

Answer 2

To test this hypothesis, you could set up multiple sampling plots in the habitat with varying light intensities and systematically collect data on the abundance and diversity of invertebrates within each plot. Statistical analysis can then be performed to determine if there is a significant correlation between light intensity and the distribution of invertebrates. It's important to control for other factors that may influence invertebrate distribution, such as temperature or vegetation cover.

Answer 3

When testing the veracity of a proposed hypothesis, you use something called "statistical testing". To do this, you would first formulate two contradictory hypothesis. The first, called your null hypothesis, would assume that there was no variation between the number of invertebrates in areas of different light intensity. For example: your null hypothesis would be (# of invertebrates in light intense areas)=(#of invertebrates in areas of moderate light intensity). Next, you would construct your "alternative hypothesis", which would look like: (# of invertebrates in light intense areas) "is not equal to"(# invertebrates in areas of moderate light intensity). Once the null and alternative hyp. are determined, you would conduct research to collect data on the actual number of invertebrates in a light intense area, as well as the number of invertebrates in areas of low light. For instance, you might find that equatorial regions(high light) have 2000 bugs per square mile, while Canada(Low light/bad food) only has 500 per square mile. By plugging those numbers into your hypotheses, you will be able to determine which is true, the null or the alternate. If the alternate is true (which is the case with these example numbers), then the distribution is shown to depend upon light intensity. If the alternative hypothesis is false (i.e. Canada had just as many bugs as the Middle East), then your proposed hypothesis is most likely incorrect, and the distribution of invertebrates in a habitat is shown to be independent of light intensity. From here, you can use statistical analysis to determine the accuracy of your test, and the probability that what you concluded from the test is true(i.e. the test is true 95% of the time). This is the same as saying the probability that what you concluded is incorrect, and it was just a coincidence there were fewer bugs in the low light region, is 5%(called your "p-value"). P-values are included in the vast majority of scientific reports, and are commonly written as (p=.05). The more accurate the test, the smaller the p-value. I hope that is what you were looking for, good luck!

Answer 4

use a choice chamber, cover half with black paper and keep the other side clear and see which side has the most woodlice in.