Bio 120 Lab 07 Population Size.docx

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Feb 20, 2024

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Bio 120 Nature Lab 07 Estimating Population Size Full Name: Atlas Cummins Animal Code (password): Coyote Mark-Recapture Data Analysis and Questions Expand space between questions to accommodate your answers. Sample Black White Total 1 9 61 70 2 7 78 85 3 6 75 81 4 5 83 88 5 6 80 86 6 7 69 76 7 8 81 89 8 6 76 82 9 6 82 88 10 9 78 87 Total 69 763 832 Using the Lincoln-Petersen Index, calculate the beanie animal population size from data for each sample taken. Sample 1: 778 Sample 2: 1214 Sample 3: 1350 Sample 4: 1760 Sample 5: 1433 Sample 6: 1086 Sample 7: 1112 Sample 8: 1367 Sample 9: 1467 Sample 10: 967 Using the Lincoln-Petersen Index, calculate the beanie animal population size from the TOTALS of the ten samples Sample Black White Total Total of Samples 1-10 69 763 832 Estimate from Total of Samples 1-10: 1206 Count all of the beanie animals in your population (all black and white beans). How many beanie animals (total of both black and white) actually were in your beanie animal population? 1,042 Questions: 1. Depending on the population and the habitat, ecologists generally claim that a sample size should be at least 30 observations --often more, never less. Describe the results of individual samples and total of all samples in light of this claim. When I first counted the actual total and compared it to the total I got using the Lincoln-Petersen Index my reaction was “Oh, that’s pretty close!” (math has never been my strong suit) But upon thinking about it further, if this were a practical field study, the numbers would be off by a lot, leaving almost 200 animals of the population unaccounted for. This lab has spiked some curiosity in me, and I’m left wondering how much more accurate my calculation of the population would’ve been had I had 30 samples instead of 10, and how many samples I would’ve had to take for it to get as close to the real number as possible. I have yet to separate my bag of beans from the lab and might take the time to explore this idea further out of my own curiosity. 2. Describe pertinent assumptions of mark-recapture theory that would not be true and might lead to less accurate results because of the nature of each of the following populations. a. Monarch (Danaus plesxippus) A mark on a wing, to an untrained eye, could be a lot harder to identify than something like a band around the foot of a bird, which is pretty hard to miss in comparison. While looking into Monarch mark and recapture, I found a website that allows anybody to purchase a kit to allow them to partake in the collection of data. These kits have lightweight stickers as their tagging method. This allows the general population to collect their own data, however, with multiple tagging methods available, areas with higher Monarch migration numbers might have off data. A person tagging butterflies with the stickers won’t be keeping an eye out for butterflies with painted marks that were tagged by another individual. This could throw off the population estimate. b. California Ground Squirrel (Otospermophilus beecheyi) These squirrels are very smart, being able to recognize threats relatively easily and only foraging during certain hours. A proper sample could be taken by setting up food traps during the hours in which they are inactive near their burrows, then leaving and returning after their foraging hours have passed. This will limit their sight of humans, keeping them from being overly cautious while also providing motivation to enter the trap (food).
c. California Mouse (Peromyscus californicus) Due to the nurturing nature of both the male and female mice, it is likely that they would return to their nests as opposed to mixing with the population the way animals with less nurturing instincts might. This could be avoided by sampling from many different parts of the area where the population is located. 3. Assume that a predator entered your beanie animal population after you added the marked individuals to the population and before the time you sampled the population and that the predator ate some of the members of the population at random (eating any beanie regardless of color) . a. Would your later sampling estimate of population size be too high or too low or the same? Choose one. I believe it would be a bit too high. b. Explain precisely how the predator removing animals in this manner would affect your estimate. If the predator ate at random without regard to the marking of the animal, and without us knowing of this and being able to adjust the study accordingly, I believe the population estimate would be a bit higher than the original calculations. Instead of the number of either marked or unmarked individuals going down, both are decreasing. The ratios of calculations will differ and have a snowball effect on the final population estimate, whether or not the differences in individual calculations seem to have that large of a difference. Using data from sample number 4 as an example, if I had 4 marked beanies and 72 unmarked beanies (as opposed to the 5 marked beanies and 83 marked beanies from the original sample), using the Lincoln-Peteresen index my resulting estimate for that sample would be 1,900. The original sample calculated was 1,760. 3. Assume that emigration and immigration occurred after you added the marked individuals to the population and before the time you sampled the population. Assume that a quarter (25 percent) of all (both black and white) beanie animals moved away (emigrated) and the same number moved in (immigrated) but all the immigrants were white beanie animals. a. Would your estimate of population size be too high or too low or the same? Choose one. Too high. b. Explain precisely how this population change would affect your estimate. The samples I’ve gathered would no longer provide accurate data. While sampling, I am under the impression that there are 100 marked individual animals in the population, when in reality there are less than that. When calculating my estimate of population size, I am still calculating for the 100 marked individuals instead of the new decreased number. In addition to that, there is an increased number of unmarked animals, throwing off the number even further with this new abundance of unmarked individuals. My original numbers, which show that my population is 90.4% unmarked animals and 9.6% marked animals, would now be thrown askew. Without the knowledge of this immigration, the numbers would likely reflect a higher population estimate than what is accurate. Using the data from sample 5 as an example, if I had 4 marked beanies and 82 unmarked beanies (as opposed to the original 6 marked beanies and 80 unmarked beanies) the calculated population estimate from that sample would’ve been 2,150 instead of 1,433. With this pattern continuing, it would drastically impact my estimate of the total population size.
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