Download e-book for iPad: A Primer of Ecology with R (Use R!) by M. Henry Stevens

By M. Henry Stevens

ISBN-10: 0387898816

ISBN-13: 9780387898810

Offers uncomplicated causes of the real innovations in inhabitants and neighborhood ecology. offers R code all through, to demonstrate version improvement and research, in addition to appendix introducing the R language. Interweaves ecological content material and code in order that both stands by myself. Supplemental site for extra code.

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Additional resources for A Primer of Ecology with R (Use R!)

Example text

We then choose to attach the data frame, because it makes the code easier to read7 . > names(sparrows) [1] "Year" "Count" "ObserverNumber" > attach(sparrows) Now we plot these counts through time (Fig. 8). R 60 20 Count 100 > plot(Count ~ Year, type = "b") 1970 1980 1990 2000 Year 1965 1975 1985 1995 Year[−length(Count)] Fig. gov/bbs/). We see that Song Sparrow counts8 at this site (the DARRTOWN transect, OH, USA) fluctuated a fair bit between 1966 and 2003. They never were completely absent and never exceeded ∼ 120 individuals.

Each year, for two years, you sample in early summer when the fruits are on the plants (when the weather is pleasant and you can find interns and volunteers to help). In all plots you tag and count all first year plants (2–3 leaves), and all older plants (4+ leaves). You also are able to count fruits and have determined that there is one seed per fruit. Now that you have your data for two years, you would like to figure out how quickly the population growing. You could simply keep track of the total population size, N, or just the large adults.

95) [1] 0 19528 Here we see that the lower bound for the deterministic projection is the same (extinction) as the simulation, while the upper bound is much greater than that for the simulation. Why would that be? Perhaps we should examine the assumptions of our deteministic approach. We started by assuming that the log R could be approximated with the t distribution, one of the most pervasive distributions in statistics and life. Let’s check that assumption. We will compare the log R to the theoretical values for a t distribution.

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A Primer of Ecology with R (Use R!) by M. Henry Stevens

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