GEOG 442

Biogeography

Testing Natural and Sexual Selection among Feral Pigeons

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Background:

In this lab, you'll test a hypothesis about natural and sexual selection among feral pigeons, based on data collected by your peers following the Cornell Ornithology Lab's PigeonWatch protocol.

PigeonWatch is a citizen science project, designed to collect data on the prevalence of different pigeon morphs (blue-bars, red-bars, spreads, reds, checkers, pied, and white) and observations of pigeon males courting other pigeons. The question is why are feral pigeon flocks so diverse in color? Natural selection in natural habitats tends to encourage the propagation of the morph best suited for a given habitat (think of all those identical mourning doves, crows, and seagulls!). One possible exception is sexual selection, where sexual preferences can actually counter natural selection, as long as the animal is so popular with the opposite sex that it leaves more offspring than a more boring but physically fitter animal (e.g., peacocks, cichlid fish, Irish elk). The Cornell lab would like to learn if sexual selection is somehow maintaining the diversity of feral pigeon flocks.

Data:

So, your colleagues who couldn't make the Palos Verdes field trips went out on their own and did six PigeonWatches for each trip they had to miss. The result is a ton of pigeon data. Here are their raw data:

Hypotheses:

  • Hypothesis 1: Natural selection favors significantly different mixes of pigeon morphs in different habitats (data are all pigeons counted in six different habitats, grouped into urban versus beach/park/"natural" habitats)
  • Hypothesis 2: Sexual selection favors a significant difference between the morphs male pigeons were observed courting versus the supply of pigeon morphs available at the sites where courting was observed (are the males hitting up more of the exotic colors, such as red, white, or pied?)
  • Hypothesis 3: Pigeon males of particular morphs may sexually select targets similar (or different) from them in coloring (we're matching courting male morphs with target morphs)
Method:

You'll select one (only one) of the three links above and perform a Chi-square test on the data provided. You have data in two columns and five rows (in cells arbitrarily named a, b, c, d, e, f, g, h, i, and j). Row totals and column totals are also provided.

  • Your first task is to calculate expected counts for each of the ten cells, counts you would get if there were a random association between each row total and each column total. To do that, for each cell, multiply the row total by the column total and then divide the answer by the total number of birds or "n" (it's in the lower right corner, where the row totals and the column totals intersect). Put the answer (to three decimal places of accuracy) in the expected cell count matrix below (making sure to keep the cell letters consistent!).
  • Your second task is to square each of the observed values in the original table. Probably the best place to keep track of them is in the third little table which was originally the key to the cell names.
  • Your third task is to divide each of those squared observations by the expected value for that particular cell. So, the number of pigeons in cell a is squared and put in the third little table. Then, it is divided by the expected value for cell a in the second table. Put the answer next to the right cell name in the rightmost column (again, to three decimal levels of accuracy).
  • Your fourth task is to sum that column on the right.
  • Your fifth task is to subtract the grand total of pigeons (n) from that sum. This answer is called Chi-square. Put it in the space provided.
  • Your sixth task is to figure out how many "degrees of freedom" your table entails (so you can figure out the significance of your results). Chi-square degrees of freedom are (r-1) x (c-1), or number of observation columns (2) minus one times number of observation rows (5) minus one.
  • Your seventh task is to figure out the probability that just random stuff could have created your Chi-square value. To do that, click on the Chi-square prob-value table I created for my GEOG 200 class. Look up your calculated Chi-square value on the left axis and read across to the column under your degrees of freedom. That number at the intersection is your prob-value.

Results:

To interpret your prob-value, any prob-value less than the normal alpha for most scientific research (0.05) can be considered a significant association. If the prob-value is at or bigger than 0.05, then the association is not significant (the chance that random sorting could do this is too big). Is your association significant?

  • Is there a significant association between pigeon morphs and their habitats (urban versus beach/park?
  • Is there a significant difference between the available pigeon morphs and the ones males court?
  • Is there a significant association between the morphs of the hopeful males and the morphs of their targets?
Autograph your sheet and bring it to class on the day of the final (14 December, 5-7 p.m.). Or put it in the Digital Dropbox in BeachBoard.

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first placed on the web: 12/08/11
last revised: 12/08/11
© Dr. Christine M. Rodrigue

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