Hi Steven Are you aware of the package "vegan" for community ecology? There is a function in this package called specaccum, which calculates species accumulation curves for you. Various methods can be specified, including "random".
I must admit I have not used this particular function (yet!) but it seems like it could be useful to you. Regards Karen ------- Karen Kotschy Centre for Water in the Environment University of the Witwatersrand Johannesburg South Africa On Tue, 28 Jun 2005, Steven K Friedman wrote: > > Hello, > > I have a data set with 9700 records, and 7 parameters. > > The data were collected for a survey of forest communities. Sample plots > (1009) and species (139) are included in this data set. I need to determine > how species are accumulated as new plots are considered. Basically, I want > to develop a species area curve. > > I've included the first 20 records from the data set. Point represents the > plot id. The other parameters are parts of the information statistic H'. > > Using "Table", I can construct a data set that lists the occurrence of a > species at any Point (it produces a binary 0/1 data table). From there it > get confusing, regarding the most efficient approach to determining the > addition of new and or repeated species occurrences. > > ptcount <- table(sppoint.freq$species, sppoint.freq$Point) > > From here I've played around with colSums to calculate the number of species > at each Point. The difficulty is determining if a species is new or > repeated. Also since there are 1009 points a function is needed to screen > every Point. > > Two goals are of interest: 1) the species accumulation curve, and 2) an > accumulation curve when random Points are considered. > > Any help would be greatly appreciated. > > Thank you > Steve Friedman > > > Point species frequency point.list point.prop log.prop > point.hprime > 1 7 American elm 7 27 0.25925926 -1.3499267 > 0.3499810 > 2 7 apple 2 27 0.07407407 -2.6026897 > 0.1927918 > 3 7 black cherry 8 27 0.29629630 -1.2163953 > 0.3604134 > 4 7 black oak 1 27 0.03703704 -3.2958369 > 0.1220680 > 5 7 chokecherry 1 27 0.03703704 -3.2958369 > 0.1220680 > 6 7 oak sp 1 27 0.03703704 -3.2958369 > 0.1220680 > 7 7 pignut hickory 1 27 0.03703704 -3.2958369 > 0.1220680 > 8 7 red maple 1 27 0.03703704 -3.2958369 > 0.1220680 > 9 7 white oak 5 27 0.18518519 -1.6863990 > 0.3122961 > 10 9 black spruce 2 27 0.07407407 -2.6026897 > 0.1927918 > 11 9 blue spruce 2 27 0.07407407 -2.6026897 > 0.1927918 > 12 9 missing 12 27 0.44444444 -0.8109302 > 0.3604134 > 13 9 Norway spruce 8 27 0.29629630 -1.2163953 > 0.3604134 > 14 9 white spruce 3 27 0.11111111 -2.1972246 > 0.2441361 > 15 12 apple 2 27 0.07407407 -2.6026897 > 0.1927918 > 16 12 black cherry 1 27 0.03703704 -3.2958369 > 0.1220680 > 17 12 black locust 1 27 0.03703704 -3.2958369 > 0.1220680 > 18 12 black walnut 1 27 0.03703704 -3.2958369 > 0.1220680 > 19 12 lilac 3 27 0.11111111 -2.1972246 > 0.2441361 > 20 12 missing 2 27 0.07407407 -2.6026897 > 0.1927918 > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
