Exam 2 Review Sessions

Review sessions for the second exam will be held:

Sunday, 20 March, 7-9pm in the Walter Hall conference room
Monday, 21 March, 4-6pm in Salomon 202

Come prepared with questions!

Homework 2

Homework 2 is now available through MyCourses. It is due next Wednesday at 5pm.

You will need the Populus software to complete it. Populus can be downloaded here: http://www.cbs.umn.edu/populus.

Also, I changed my office hours to an hour earlier on Wednesdays.

Questions to consider while studying for Exam #1

Note: this is not by any means a comprehensive study guide. Answers will not be posted. These questions are meant to put you in the mindset of the kinds of topics you will need to think and write about on Thursday.

The best way to study is to get together with a study partner, and ask each other questions!

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What are the force equations? What kind of forces does a stationary organism experience in a moving fluid? Are these forces constant? Do they vary with height/distance from the organism? How? What are some examples of organisms experiencing forces in fluids that we have discussed in class or in section? For instance, take a look at the Trussell paper. What are consequences of organisms living in high-flow areas?

Why is scaling important? What is allometric scaling? Give an example of allometric scaling from the literature. What is isometric scaling? Give an example from the literature. What is Kleiber's Law and how does it relate to scaling? Under what circumstances might this ratio change? What are the other variables that scale with body mass? (ex: population density, latitude, home range). Give a quantitative description of the Energy Equivalence Rule. This may help: http://repository.unm.edu/bitstream/handle/1928/6927/Damuth.pdf?sequence=1

Continuing with the theme of scaling, why might we look at ecological processes at different spatial scales? What papers have we discussed that relate to spatial scales? (hint: Garcia et al, and White et al.) How do the following differ from one another: GSDR, LSDR, and CCSR?

From Gotelli:
What are the differences between stepwise (discrete) and a continuous population growth models? What are the assumptions of each model? How do these vary from assumptions of logistic models of population growth? Are these models realistic? For what organisms would you use these models? What is r? What is lamda? What does it mean if lamda >1? What does this tell you about the value of r? What is the doubling time? What is stochasticity? How can it be quantified? Under what circumstances (values of r and variance) will a population crash? Why does demographic stochasticity have a disproportionately greater effect on small populations?

What are the differences in optimal foraging between generalists and specialists? Give examples of each. Draw an optimal foraging curve and label key points: travel time, optimum travel time and energy gain (how does this relate to the marginal value theorem?), and axes. What are assumptions of the Optimum Foraging model? What are examples of optimum foraging from the literature (at least 2)? What is prey switching? Why would it occur? Give an example from the literature (hint: bluegill sunfish & daphnia).

What are two main life history strategies? Give examples of semelparous and iteroparous organisms. Why do we see episodically iteroparous trees? How does masting relate to seed dispersal? Relate to Hollbrook & Loiselle. How might seed dispersal strategies differ between k- and r-selected species? Give an example of each.

vocab:
stochasticity
Bergman's rule
specialist
generalist
semelparous
iteroparous
clonal
colonial
modular
concordance
fragmentation
PRC
gamete
colonization
n-dimensional hypervolume

Cool links

Hey all,
Prof. Witman asked me to put up these links. The first is a news article about rapid evolution of fish to toxins in the Hudson River, and the second is a Science podcast discussing the article.

article: http://green.blogs.nytimes.com/2011/02/18/speedy-evolution-indeed/#more-92356 and http://www.poughkeepsiejournal.com/article/20110220/NEWS01/102200362/Hudson-fish-adapts-fast-to-resist-PCBs

podcast: http://www.sciencemag.org/content/331/6019/956.2.full

Question about Scaling

Hi Everyone,

I received this question about scaling relationships and I figured that I would share the answer with everyone because it might be kind of useful to others who are confused by what they wrote down in their notes:

"I saw in notes that we need to know a general form of the scaling equation..i cannot find it in my notes or the slides...could youhelp me out with this?"

And here is my response:

The most general form of a scaling equation is simply referring to the relationship between two variables. In the context of what we have talked about, these are usually in logarithmic relationships and refer to things such as body mass, average population density, etc. - however, a scaling relationship doesn't have to fall within these categories.

For a basic logarithmic scaling relationship between any two variables, we can represent it with the generalized equation:
Y = Y0X^(b) [that is "Y equals Yzero times X to the b power"]

Prof Witman probably wrote it in class with an M instead of the X, because one of the variables is usually body mass. So again, the equation that you most likely should have seen on the board would look like:

Y = Y0M^(b)

which can be written in a logarithmic form by taking the log of everything (or the natural log):

log(Y)=log(Y0) + b*log(M)

[aside from the log bit, this should remind you of algebra class and everyone's favorite equation for a line "y=mx+b": this graph looks like a straight line; whereas the other form is a log graph, which can be harder to interpret.]

Okay. So that's the general equation logarithmic scaling equation. Hopefully you should have some ideas about what it means, but just in case I've confused you, here are some places to start thinking about it.

Y0 is a constant. It's like a starting point. In the log/log scale plot, it will, in fact, be the y-intercept of the graph.

b is also a constant, and it's the interesting part of the equation. It serves to relate the two variables - so ecologists want to find b and try to think about the implications of it,and why it is so. In the log/log plot, it will be the slope.

Therefore:

if b=1, the relationship between the variables is directly proportionate; the slope is 1; if mass increases by a certain amount, the Y also increases by the same amount. This isisometric scaling.

if b does not = 1, the relationship between the variables is not directly proportionate; the slope is not 1; and if the mass increases by a certain amount, the Y will change by a different amount. This is allometric scaling.

I think I will leave off there and hopefully your notes, and the White et al review paper can help you fill in the gaps as far as examples and relevance. Again, body mass is the variable that we talked about most, but this is actually a general concept, so it can be used for other ideas as well.

Let me know if you have more questions.

Populus software

The Populus software is available for download here: http://www.cbs.umn.edu/populus/. You will need it for the second homework assignment.

Exam 1 Review Sessions

The first exam will be held in class on Thursday, Feb 24.

The TAs will be holding two review sessions at the Science Center:
Monday, Feb 21, 7-9pm
Tuesday, Feb 22, 6-8pm

Please bring specific questions on lecture or discussion material!