Meta-post

Thanks for all of your wonderful posts and comments! I hope this is useful and fun and not too overwhelming!

Regarding Thursday night exam- I was not able to get a computer lab so we will be meeting in the regular room and writing using pencils and pens!

Some general comments regarding issues that we have touched on but been too time-strapped to explore further:

What is equilibrium? One definition is that it is "the point at which forces cancel each other". To a community ecologist, the "forces" might be competition, predation, mutualisms etc. (biotic factors), which is, of course, a gross oversimplification of nature--- Comm. ecologists may integrate disturbances, as we saw with the Moretti paper and its investigation of fire. An example of a "theoretical equilibrium" is the abundances of two competing species that results in crossing of their zero-growth isoclines-- all other things (prey populations, parasatism, climate, floods, fires, etc.) being equal (never the case), the "community" would be at equilibrium. Also, the community might be locally stable if a small increase in either results in a move back towards the center. Generally however, more studies are debunking the idea of the "balance of nature" or any sort of stable system. Fluctuations and chaotic change in population numbers seems to be more the rule than the exception. I think this topic will continue to be discussed as we move forward in the class.

Species richness and other measures of diversity- Which is the best to use? A benefit of observed species richness is that it is easy to understand and convey. Diversity indices provide numbers that are only interpretable relative to each other. Estimators, while supposedly being more robust, take you one or more steps from your empirically observed data. As you keep fiddling with different estimators, indices, functional descriptions, etc. you can run into the problem of too many analyses (inflating type I error), and ultimate confusion! Best idea is to really read up on the literature beforehand and develop a compelling a priori dependent variable for your a priori hypotheses. Email scientists that have published these papers and ask them for ideas for good measures or diversity to use.

Lemaitre et al 2009- Did they just die of the cold? The authors state that the primary source of mortality was hypothermia and they also state that "the effect of temperature was additive to other variables influencing survival and did not interact with the presence of bot fly (Appendix 1, ESM; Table 1)." I did not see the interaction data in Table 1 and could not access the appendix to evaluate this claim (without seeing mean temp for bot fly + vs. -). They give this data for confinement time in the discussion.

Invasive species? Are they all that bad? Short answer: if they compete with you, no. If they eat you, yes. From Sax and Gaines 2008 (not a required reading):
"Among the 204 vertebrate species with listed causes of extinction, some form of predation (including human hunting, carnivory, and infectious disease) is cited as the sole factor responsible for species extinctions in 69 (33.8%) of extinctions, predation together with other
contributing factors is cited for 85 (41.7%) of extinctions, and competition together with other factors is listed for 18 (8.8%) of extinctions. In no case is competition listed as the sole cause of species extinction."

More evidence for the importance of predation relative to competition?

P-values irrelevant? I think so but keep following the increasing literature on this debate. All the techniques you learn in stats (regression, anova, ancova, etc) can be assessed in an information theory framework so are completely relevant to your development as ecologists. The "Pitfalls" article mentions that you should either use p-values or information theory but not both-- this seems a little dogmatic. Some reviewers will be more familiar with p-values and others with AIC--- if it you have space you may want to provide both. Just keep your inferences locked to one paradigm.