Analyzing the relationship between wildfire and plant biodiversity
At UCSC’s Big Creek Reserve in Big Sur, California (http://bigcreek.ucnrs.org/), seasonal wildfires occur every few to several years during the dry summer months as a result of lightning and occasional ignition accidents, such as escaped campfires. These fires have burned different areas of the reserve at different times, removing vegetation and releasing carbon and nutrients from the soil. In the extensive grasslands on the reserve, fires burn off both the living vegetation and the accumulated dead litter on the ground. Plants recolonize these grasslands rapidly following the fire, changing over time in diversity and composition.
In this mini-study, you are investigating the effects of wildfire on the biodiversity of plants. Specifically, you are looking at areas on the reserve burned at different times in the past to ask about the effect of time elapsed (since the most recent fire) on grassland species density (the number of species per unit area). You have data from three areas burned 14, 9, and 5 years ago, respectively.
Q1. Write out a null hypothesis for the relationship between fire history (years since fire) and plant species richness.
Q2. Formulate a specific (alternate) biological hypothesis and a 1-3 sentence explanation of why you expect this relationship.
a. Download Dataset #1 from CANVAS
• Open and download the file to your computer, to a location you can find it in
• In JMP, choose File -> Open -> locate and select the burn_data file
The file has three columns: a column of line numbers (sites), a column of burn years, and column called “richness” that reports how many species were found per plot at the site in question.
b. Make burn year a continuous variable:
- In the middle left of the data window, under “columns,” click on the red icon next to “years since burn.” (Some of you may find that the icon next to “years since burn”
- When the window pops up, “nominal” is checked – the three burn years are being treated here as named categories. Choose “continuous.” The icon next to “years since burn” will change to a blue triangle.
You are going to test your hypothesized relationship between years since burn and richness.
Q3. Which will be the independent variable in this test?
Q4. Which is the dependent variable in this test?
c. Make a scatterplot of your data.
- Select “JMP Starter” from under the “Window” menu
- Select “Basic” in the small box on the left of that window, then “Bivariate” to look at the relationship between two continuous variables.
[What does the description of “bivariate” say?]
- Put your independent variable in the “x regressor” box by selecting the variable you want in the left box, then clicking the “x regressor” button. Put the dependent variable in the “y regressor” box in the same way.
- Click “OK.” You get a scatterplot with faint points.
d. Perform a linear regression of richness on burn year.
- Click the red triangle next to “Bivariate Fit of Richness by Years Since Burn” to get a dropdown menu of options.
- Click “fit line” to fit a regression line to the points, and inspect the line that JMP fits and the data that it displays about the statistical test.
- Change the line color to black by clicking the red triangle next to the legend (“linear fit” and a line) beneath the graph, selecting “line color,” and clicking on black.
Q5. What is your sample size? [This is the “observations” value.]
Q6. Write out a sentence reporting the value of your RSquare and describing what this number means.
Q7. Is the slope significantly different from zero?
Q8. Can you reject the null hypothesis (from Q1)?
Q9. Does the test support your alternate hypothesis? If not, do you have any ideas about why that could be, biologically speaking?
Q10. What is the value of the slope parameter in the regression equation?
Q11. Write out the linear equation that is the best fit to your line.
Q12. Write out your statistical result in the formal format of ecological findings: a single, precise sentence telling how time since wildfire affected the response variable, followed by a summary of statistical information in parentheses as follows:
A concise sentence describing the relationship supported by the statistical test (R2=XX, p=XX, linear regression equation).
Note: To save the graph for use in a report or other document (not required at this stage for the assignment, but useful for future reference):
1. Click the selection tool (white cross in the toolbar at the top of the bivariate fit window).
2. Highlight the area that you want to save – you might need to highlight each area of the graph, such as the axes, plot area, and title, while holding the shift key.
3. Select Edit > Save Selection As (Windows) or select File > Export (Macintosh).
4. Select the graphics file format to which you want to save the selection.
e. Perform an ANOVA test on the relationship between burn year and richness
Q13. Why does it make more sense to use an ANOVA test than a regression to evaluate the relationship between burn year and richness with this data set? (One sentence is fine.)
1. Change your data type for the test
- In the middle left of the data window, under “columns,” click on the blue triangular icon next to “years since burn.”
- When the window pops up, “continuous” is checked – the three burn years are being treated here as values from a continuous spectrum. Choose “ordinal.” This makes “burn year” a variable with categories that proceed from low to high values. The icon next to “years since burn” will change to a green bar chart.
2. Perform the ANOVA test.
- Select “JMP Starter” from under the “Window” menu.
- Select “Basic” in the small box on the left of that window, then “Oneway” to look at the relationship between a continuous variable and one or more categorical factors.
[What does the description of “oneway” say?]
- Put your independent variable in the “x grouping” box by selecting the variable you want in the left box, then clicking the “x grouping” button. Put the dependent variable in the “y response” box in the same way.
- Click “OK.” You get a graph with three years on the x-axis and points above each for your species richness data in each group.
- Click the small red triangle next to the graph title. Choose “Means/ ANOVA.”
Q14. What is your F value (ratio)?
Q15. What are the mean richness values for each burn year?
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