Trial Number 1!!!

Yesterday I mated my first set of eight females with their first male. There were two irradiation control treatments in which one female was mated with one sterile male. Then the fertile fertile mating was supposed to control for multiply mating a female and not letting the males go to completion. Both the 25/75 and 75/25 splits were used here. Then the more interesting sterile, fertile and fertile, sterile groups were also mated with the same splits listed above. The matings went really well. Today I plan to mate the females with their second males unless they are in the irradiation control group. I also pithed the males that were mated yesterday and put them in the freezer so that I can look at the sperm remaining in their pedipalps and try to get an idea of how much sperm the male had to begin with. So by today I will have 16 less males to feed!! Cruel, huh? But after feeding the spiders each week for 3-5 hours, you get excited when the workload is reduced!!

Statistics Refined

A couple of days ago, Dr. Christenson and I met with Dr. Corey, the psychology statistics guru. We went over the spider design and he thought that it was really sound! He suggested that we do a two way ANOVA looking at the percent of eggs that hatch into spiderlings with the predictor variables being mate order and number of intromissions. I was glad that our control for the irradiation method is adequate even if we mate one female with just one sterile male! This could mean less animals. As far as the multiple egg sacs, Dr. Corey just said to do repeated measures, which was also suggested by Mike. Anyways, I am excited to get this rolling!

Multiple Egg Sacs

In breeding the females, I have noticed that they put out multiple egg sacs without having remated. They seem to be able to store sperm for long periods of time after mating with a single male. I am interested to see what sort of role this multiple egg sac laying will play in my manipulation. Will one of the male's sperm be used preferentially over another's? After that male's sperm is used up, will she then use the other's? Is the female able to influence the sperm used to fertilize eggs or does she use whatever is in her storage sac? I should be able to tell when I am able to see whether the percent of eggs hatched changes with each egg sac for the females mated with a sterile male and a fertile male. Maybe the mate order will play a role. This could be pretty interesting! I think I would use MANOVA here?

ANOVA and spiders

When I was going over Chapter 7 in G&E, I had a hard time getting through it because I kept trying to apply everything to my spider study. I even drew in my own little chart next to the one in the book showing a two-way layout in ANOVA. My two factors in this case will be mate order (whether the male is the 1st or 2nd to be mated with the female) and % of intromissions (20,50,80). These are my two categorical predictor variables. My response variable is the percent of eggs hatched. I hope to see a significant response from the % of intromissions, which supports the hypothesis that sperm number determines paternal advantage. I do not expect to see a main effect of mate order. If there was, this would support the hypothesis that the priority pattern is determined by sperm placement, in that the first male is able to place his sperm closer to the fertilization duct and therefore fathers more offspring. I think this will work. If you see any flaws, please feel free to point them out. Also, if I follow the Rule of 10, I will need 10 trial runs or replicates. There are 16 males per replicate (two pairs for sterile, sterile; two pairs for fertile, fertile; two pairs for fertile, sterile; and two pairs for sterile;fertile). The number of intromissions will be varied among the pairs with one being 50/50 and the other 20/80. Total this means I need 160 males!!!

Regression

I really liked working through some sample data sets with R on Tuesday. It helped me learned how varying some of the terms could change the coefficent of determination and the p-value. Here is the summary of what I learned:
Regression is used for two continuous variables (both independent and dependent). A regression assumes that there is a cause and effect relationship between x and y. Also, this technique asumes that the x variable is measured without error (can this be done?!?) As far as a linear relationship between two variables, the null hypothesis proposes that there is none and that the slope is 0. The alternative hypothesis depends on slope. Also, the slope, the coefficient of variation, and the sample size all affect the p-value. Remember the p-value is the probability that the slope of the line equals zero and that there is no relationship between variables (null hypothesis).

ANOVA

Heidi's presentation on Tuesday was very helpful. I especially liked how she covered the assumptions of ANOVA. I also thought that having Thursday's lab also be about ANOVA was well-planned. Though I think that I am getting a good grasp of this test, I think that it is pretty important for us ecology people to truly understand this well. I think that actually doing an ANOVA by hand with a real data set would help to make it more concrete in our minds. Back in ecology lab, this old-fashioned "work out the problem" method helped me to understand t-tests and chi-square tests. I know that it is old school but sometimes using computers does not equal understanding. Anyone of the same opinion?

Spider Update

Sorry it has been so long since my last posting, but I am going to try to make up for it. The good news is that I am finally ready to do a run for my project. I have 16 mature males and 9 mature females ready to go. I am mating them tomorrow! I also will be meeting with my advisor. So I plan to talk about statistical design. As of now, it looks like I will be using ANOVA, ANCOVA, and some t-tests. I am sure this may change as I go along and get a better idea of what I am doing. Also, the males that I am planning to sterilize will have to be placed in a straw using cotton as the stoppers. I took from this class that I should also do this straw cotton treatment for the fertile males as well minus the irradiation of course. Something I am also planning to avoid is confounding my study with time/seasonal issues. Since I can't run all of my runs at once, I plan to have all of my treatment and control groups represented in each run!

Tuesday's Class

I really enjoyed class this Tuesday. Rebecca did a really great job of putting it all together. It was very useful to define a study, hypothesis, and design according to whether the dependent and independent variables were continuous or categorical. The exercise actually made us think about relevant biological variables and how we should test them. I learned a lot about when to use different tests. Ultimately, this will be very helpful for my independent project/honors thesis. Now if we could just do this with a Thursday lab, I feel like I would get so much out of R. By the way, based on the biostats test, I found R to be useful in running analyses but inputting data was a nightmare. Anyone have any good tips or is it just hard to do? It is just not as friendly as a spreadsheet like Excel.

JV Ch. 6

I found this chapter to be a little more enigmatic than previous ones. There seemed to be a lot of emphasis on trying to do exercises that supported the Central Limit Theorem. This exercise was less practical and a little too redundantly didactic. What can we actually use from this chapter? I guess the most useful thing to me was learning to do the loop. I figure that this will come in handy in the future. I guess I would like to see this course take a step towards practically applying the information in JV to a biological study. Is there anyway that we could use a different biological data set and manipulate it with what we learned in each JV chapter? I think that I would learn a lot more from this and be more motivated in doing the exercises. After all, the purpose of this course is to learn how to use statistics in our projects and studies, and as of now I don't think I am anywhere close. Let's put JV in a different context!! I don't want to learn about R for the sake of doing just that. I want to use R as a tool in my own studies, and the examples in the book have so far been too theoretical.

Spiders and Stats

I think that I have redefined my independent project pretty well (I hope, see last posts), but I guess I need to start thinking about what kind of statistics I want to use. I was thinking about some t-tests, chi-square, and maybe ANOVA. I guess I am just not all that familiar with trying to determine what kind of stats to use. Usually, people just tell me like for example, in ecology lab. I am sure that I will want to show a linear regression for number of sperm released per intromission, which I can find out by dissecting some males and counting sperm. But I am not sure how to compare number of offspring for each group (1. sterile, sterile 2. sterile, fertile 3. fertile, sterile 4. fertile, fertile) especially with varying numbers of sperm in each group. This would involve allowing each male equal number of intromissions and then varying the ratio of intromissions between first and second male(ie: 1:10). Does anyone have any suggestions?? Maybe if my hypothesis that the priority pattern is determined by a sperm number (more of a lottery, vs. placement of sperm) is supported, I could show that there is no difference between a fertile first male with a 10:1 advantage of sperm number and a fertile second male with the same advantage. I don't know, help!!

Evolutionary Psychologists Gone Awry

In my evolutionary psychology class, we have been looking at same papers attempting to explain short and long term mating strategies as well as differences in sexual jealousy among the sexes. It has been an extremely interesting pursuit and the starting theories have been very logical and well placed in the framework of sexual selection. The issue is that the data sets they are picking out to support their theories are not necessarily representative of a population. They are not so random so to speak. Also, some clearly seem to be interpreting data in light of their theory in a very subjective manner. The methods one uses and the statistics are important as well! You can have a brilliant theory, but it will not be well respected unless the sampling is random and unbiased and the interpretation is not skewed. It is a little scary to think about especially because human psychology is so programmed to see a pattern even when there is not one!

Zoo Animals

Well good news is that I picked up some juvenile virgin males at the zoo. Now I am waiting for some juveniles to molt. Basically, I have 8 virgin females and I have 16 males. Soon, I should be able to run one trial run. I will mate two sterile males to one female. Then I will vary the number of intromissions allowed which will be a 1 to 5 first to second male ratio. Then I will do the same two manipulations for the other groups (the 1st sterile, 2nd fertile & 1st fertile, 2nd sterile & 1st fertile, 2nd fertile). Then I should have some data hopefully. The idea is to be able to manipulate number of sperm so that we can control priority pattern. Usually, in this species, the first male has the advantage because he plugs up the female. However, we are not allowing the male to form a plug. Therefore, if there is sperm mixing going on in the female's spermatheca (storage sac), then we should be able to influence the priority pattern. We also sat down and dissected a female the other day and the storage sac is perfectly round, which would seem to facilitate sperm mixing. The other hypothesis is that priority pattern is determined by placement of sperm (location in the spermatheca). I am excited and hope that this first run goes well.

Baby Spiders

Well lost another male to a voracious female the other day!! Oh, well. Anyways, I have finally figured out how to rear my spiderlings successfully! I have isolated them in screw cap vials. I feed them about once a week with a knat-like insect. These babies are about the size of your pencil point and they spin the much larger insect up in their web. It is pretty phenomenal! I should be doing some more collecting at the zoo with Dr. Christenson on Friday. Hopefully, I will be able to ask him some questions about the experimental design. More to come about the project after Mardi Gras...

JV Ch.3 in class

I really liked the way we worked on Chapter 3 in lab yesterday. It was extremely helpful to be able to target one problem and do it well. Then we could even move onto others if we finished. I thought that everyone presenting a problem was very helpful because everyone brought a different way of doing things. I feel like I learned so much more about UsingR in this week's session versus in the past. Keep it up Mike!!

Floating Islands

I am taking a Primate Behavior and Ecology course this semester, which has so far been really interesting. I am learning about the differences between apes and monkeys and all that jazz. New World monkeys or platyrrhines diverged from Old World monkeys about 35 mya, but South America split off of Africa much earlier around 100 mya. The earliest fossils were established 26 mya in the New World probably because fossils do not form as well in wet, tropical climates. The real question is: How did the platyrrhines get to South America? The best supported hypothesis is by rafting across on islands of floating vegetation.

A study by Alaine Houle was conducted to examine the effects of wind velocity and direction as well as current velocity and direction on the number of days that it would take take to cross a water barrier during the Paleogene. Very simple summary statistics were used like in G&E Chapter 3 like mean, variance, and standard deviation. Conclusions were that around 40 mya, it would have taken about 11 days to cross the Atlantic Ocean at a most conservative measurement. The shortest measurement was 7 days. In this light, this theory does not seem all that implausible because the survival limit of monkeys has been estimated to be 11-15 days. Rafting earlier would also have decreased the amount of time. It is likely that monkeys could survive this trip and find enough food on the island to sustain them for two weeks. Now, what sort of population size would be needed, I have no idea. But imagine that Houle did this study with just summary statistics!! By the way, the link is http://www.jstor.org/view/13669516/di005208/00p0189i/0.

Warming

I have been taking this ecosystem ecology class this semester, and we have been talking a lot about global warming. Apparently, the concentration of carbon dioxide in the atmosphere has risen 30% since the Industrial Revolution. It is around 380 ppm. Just for reference, the glacial maximum concentration of carbon dioxide is 180 ppm, while that of an interglacial period is 280 ppm. Scientists have gotten these measurements by directly measuring the carbon dioxide concentration from the Vostok ice core. Then they have manipulated this data to somehow look at the flux of temperature over millions of years ago. How they do this, I am not really sure. It seems like an unbiased statistician would have to take into account the natural cycles instead of just human impact. The temperature rise should not be solely based on the rise in carbon dioxide concentration because in the past great changes in climate have taken place before humans. Anyway, just a thought. I was just trying to think of ways to be less biased about global warming because a lot of people seem to think that ecologists have an agenda.

She Ate What?!

I want to go into a little more detail for my study so that I can relay an interesting occurrence that took place yesterday. A priority pattern study investigates the multiple mates of a female and their respective reproductive successes. Most insects have a second male advantage meaning that the second male with whom a female mates fathers more of the offspring than the first male. In spiders, however, there is usually a first male advantage. I am going to directly (I hope) test the priority pattern for Nesticodes rufipes. The design for the experiment includes controlling the number of intromissions (insertions) the male makes when mating, which linearly correlates with the amount of sperm that he releases. I will have two types of males: 1) Normal fertile ones and 2) Sterile ones. The sterilization process is an interesting one in itself. Basically we irradiate the male, which leaves his sperm intact, but scrambles the DNA of the sperm leading to infertility. I will have four groups. The first control group will involve mating a virgin female with two fertile males. Then the control for the irradiation process will involve mating a female with two sterile males. The last two groups involve alternating the mating order of one sterile and one fertile male. Then the amount of offspring produced in the experimental groups will help to elucidate the priority pattern. I might try varying some of the number of percentage of intromissions of the two males (ie: 50/50, 25/75 & 75/25) just to see the results.

I currently have been in the process of trying to foster a breeding colony for my spiders so that I can produce a large enough sample size for controls and manipulations. Nesticodes rufipes is a species that is generally found indoors of laboratories, prey rooms of zoos, and perhaps barns. E.O. Wilson had these babies in his lab when he was doing his ant research. Anywho, these spiders mate for a total of 3 hours!! Talk about stamina! What takes so long? Well, the sperm producing organs are found in the lower abdomen of the male, but his organ of copulation are palps on his antennae. He has to build a sperm web and then dab his palps in it (called induction) so that he can then inseminate the female. It is a curious process because during intromission, he inserts one palp and basically turns the female in a semicircle. Then he switches palps and turns her the other way. Imagine a much bigger female just calmly putting up with this turbulence! Anyways, I put in a male with my most aggressive female yesterday and came back three hours later. She had mated with him, and then decided she was hungry and spun him up in her web. This is not the most common behavior but it does happen on rare occasions. I guess I am glad to be breeding some hearty stocks, but males are hard to come by and I would rather my females not consume their mates. Thought you all would find this amusing!

Hamilton and Altruism

In my evolutionary psychology seminar, I just got the chance to read one of W.D. Hamilton's papers. This is the first time that I have actually read him directly. Of course, he is a staple in evolution and ecology courses with his theory of inclusive fitness as a means to explain "altruistic" behavior. I have always found his exploration of natural selection at the level of the gene and its effect on social behavior quite fascinating. The great thing about reading him was his very straightforward writing style. Imagine such complex ideas with mathematical models and all being lucid! The man is a good writer. Anywho, I know that a lot of mathematical manipulations have been done to test his theory of altruism with current ecological data and that it holds up pretty well. Anyone have an idea of what these statistics look like? How exactly would you assign a numerical value to the cost to the altruist or the benefit to the recipient? These, unlike a coefficient of relatedness, very hard to quantify. It would be really interesting to examine an ecological study that tests Hamilton's theories. Anybody know of a good one?

Science and the ladder of progression

While reading G&E Chapter 1, I very much enjoyed the footnote about molecular biologists and how uncomfortable they are with uncertainty. The funny thing is that I continually have the hard vs. soft science debate on a regular basis. My boyfriend was a biochem major who is getting his PhD in Molecular Biology. So when I get excited about what I think to be a great experimental design for some ecological phenomena, he just picks it apart. There aren't enough controls or it cannot be manipulated directly! And blah, blah, blah! It drives me crazy. I continually tell him that the study of macro organisms in biology has a lot more variation. There is much more unknown. The uncertainty drives him crazy, but I find it so interesting. It makes interpretation so much more complex and many ideas must be considered and explored. Perhaps we may never know the answer. Obnoxious or thrilling? If everything was consistent and predictable, what puzzles would we grapple with? Not that molecular biologists don't have puzzles, I just think I find them a little on the boring side.

Independent Research

I think I want to do my project for this class on the priority pattern study on Nesticodes rufipes that I happen to be conducting for my honors thesis. Nesticodes are spiders by the way. I think looking at potential methods of analyzing data with statistics could really improve my design. Wow, and to think that this project will help me with something I already need to do!