Ants are ideal to examine how species richness changes across regions because they are important terrestrial omnivores. The species richness of ants is sensitive to the type of ecosystem, soil, and disturbances. In their 2002 paper in Ecology, Gotelli and Ellison investigated how ant species richness changes with a variety of environmental variables.

Data: The dataset contains ant species richness (the number of different species observed) sampled at 22 sites across New England. At each site with the same latitude and elevation, one forest and one bog were sampled. Variables include the site abbreviation, ecosystem type (forest or bog), species richness, latitude of the site (in decimal degrees North), and elevation of the site (in meters). We will analyze this dataset to investigate how ant species richness changes across a variety of environmental variables.

a. Create a scatterplot of elevation (explanatory variable) and ant species richness (response variable). Label the x- and y-axes with an appropriately, per usual. Describe what you see in the scatterplot in terms of its form, direction, and strength of relationship and any outliers you might notice. As elevation increases, what happens to ant species richness?

b. Create a scatterplot with latitude as the explanatory variable and ant species richness as the response variable. Describe what you see in the scatterplot in terms of its form, direction, and strength of relationship and any outliers you might notice. As latitude increases, what happens to ant species richness?

c. At each site, both a forest and bog were sampled. Again, we want to create a scatterplot with latitude as the explanatory variable and ant species richness as the response variable. However, this time we want to make the scatterplot show different colored points by ecosystem type (a categorical variable). All the forest data points should be one color and all the bog data points a separate color. To begin, insert a scatterplot like we have done before. When highlighting your data, however, only include the latitudes and species richness associated with the forest ecosystem. Type in the series name as "Forest" and click OK. Click Add to add another series. When selecting data, highlight the latitudes and species richness for only the bog ecosystems. Type in the series name as "Bog" and click OK. Click OK again. Per usual, go to the Quick Layout dropdown list and select the first option (this gives both axis label boxes, a title box, and a legend). Provide appropriate axis labels, delete the title box, ensure the legend is correct, and make any other cosmetic changes you prefer. In general, how does the species richness in bogs compare to forests?

d. Use a PivotTable to compute the mean and standard deviation of ant species richness by ecosystem type (forest vs. bog). Also, compute the coefficient of variation (CV) for each ecosystem type. Which ecosystem has higher ant species richness? Which ecosystem has more variability in species richness?

e. Refer back to your first two scatterplots (elevation and species richness) (latitude and species richness). To compute the correlation between these sets of variables, we use the Excel function '=CORREL'. The function wants two sets of data and returns the correlation coefficient (r). To compute the correlation between elevation and species richness, highlight elevation, then highlight species richness and click OK. Note: the order in which you highlight your data does not matter (e.g., highlighting species richness first then elevation would give the same result). Repeat the steps to obtain the correlation between latitude and species richness.

f. Do you have any concerns with using correlation to describe the strength and direction of either relationship (elevation and species richness or latitude and species richness)? Why or why not?

Site Ecosystem SppRich Lat Elev TPB Forest 6 41.97 389 HBC Forest 16 42 8 CKB Forest 18 42.03 152 SKP Forest 17 42.05 1 CB Forest 9 42.05 210 RP Forest 15 42.17 78 PK Forest 7 42.19 47 OB Forest 12 42.23 491 SWR Forest 14 42.27 121 ARC Forest 9 42.31 95 BH Forest 10 42.56 274 QP Forest 10 42.57 335 HAW Forest 4 42.58 543 WIN Forest 5 42.69 323 SPR Forest 7 43.33 158 SNA Forest 44.06 313 PEA Forest 44.29 468 CHI Forest 44.33 362 MOL Forest 6 44.5 236 COL Forest 8 44.55 30 MOO Forest 6 44.76 353 CAR Forest 6 44.95 133 TPB Bog 5 41.97 389 HBC Bog 6 42 8 CKB Bog 14 42.03 152 SKP Bog 42.05 1 CB Bog 4 42.05 210 RP Bog 8 42.17 78 PK Bog 42.19 47 OB Bog 3 42.23 491 SWR Bog 42.27 121 ARC Bog 8 42.31 95 BH Bog 42.56 274 QP Bog 4 42.57 335 HAW Bog 42.58 543 WIN Bog 42.69 323 SPR Bog 43.33 158 SNA Bog 44.06 313 PEA Bog 44.29 468 CHI Bog 44.33 362 U U N W N W W N MOL Bog 44.5 236 COL Bog 44.55 30 MOO Bog 44.76 353 CAR Bog 44.95 133