search for: bioclimatic

Dear list, I am trying to predict species volume from bioclimatic data, I have various sites and I have a data frame with species volume and the corresponding bioclimatic data for each site. I read on a discussion forum that you can use ordination to predict species abundance (in my case volume) from 'new' climate data for sites where you do not know the...

...code sdat <- read.csv (paste(data.dir,"/summary.data.csv", sep="")) year <-c("1", "2", "3") for (y in year) { sdat2 <- sdat[sapply(strsplit(as.character(sdat$GCM), ""), function(zzz)zzz[5] == y),] Thanks Daisy Englert Duursma Bioclimatic Modeller Macquarie University Sydney, NSW, Australia

...appreciate advice on the following: I've written an R function that uses 3 vectors (temperature, precipitation and potential evapotranspiration) for a given site, calculates a water budget (which implies few (<4) iterations), and, from thresults of this water budget, calculates a number of bioclimatic indices. Now I want to calculate these indices for a large number of sites (arranged as cells in a raster map), using monthly raster maps (m rows x n cols) of temperature, precipitation and potential evapotranspiration. I do not see any other way than using two nested for loops and calling the...

...21:48, Soufianou Abou wrote: > Thank you for advice, Rolf Turner > > My question is as follows: > > I'd use maxent to model the potential distribution of cowpea on the > basis of the only presence data. Indeed, I have acquired a number of > environmental variables and bioclimatic regarding my area of study. But > to choose the most contributive variables in the model; I would like to > make a correlation analysis of these. On this, could you explain to me > the step by step procedures to follow in R? I would like to say scripts > for:- compile and call all e...