Great! Having a machine with 120 GB of RAM (*envy*), you can certainly use parallelization to boost the turnover calculation.
Cheers! On Tue, Mar 10, 2020 at 5:40 PM Jens Ringelberg <jens.ringelb...@gmail.com> wrote: > Hi Torsten, > > Thank you very much for your answer! You're absolutely right, the problem > is the number of localities rather than species, so calculating turnover > separately for each pair of localities is a good (but slow) workaround. > > Best, > Jens > > On Fri, 6 Mar 2020 at 09:53, Torsten Hauffe <torsten.hau...@gmail.com> > wrote: > >> (sorry, I forgot to include the list) >> >> Hi, >> >> My guess is that the problem is not the size of the phylogeny but the >> dimension of the community matrix. How many localities and species per >> locality do you have? >> >> Does it work to calculate the dissimilarity between two localities? (Try >> with the most species-rich) >> If so, you could either do all pairwise comparisons manually or you >> replace the memory-hungry apply functions within phylo.beta.pair by >> (slower) for-loops. >> >> Cheers! >> >> On Thu, Mar 5, 2020 at 10:06 PM Jens Ringelberg < >> jens.ringelb...@gmail.com> wrote: >> >>> Dear list, >>> >>> Does anyone happen to have experience with calculating Simpson's >>> pair-wise >>> phylogenetic dissimilarity for large datasets? >>> >>> I have tried using betapart’s phylo.beta.pair function to calculate >>> phylogenetic turnover for a globally-distributed clade with about 1500 >>> taxa, but my machine, which has 125 GB RAM, quickly runs out of memory >>> while doing so. >>> >>> Other than increasing RAM, does anyone have any suggestions for >>> calculating >>> Simpson’s dissimilarity for large datasets? I'm aware of the >>> PhyloMeasures >>> package, which was designed to work with large datasets, but as far as I >>> can tell it does not allow one to partition the resulting dissimilarity >>> index into the true turnover (i.e., Simpson's dissimilarity) and richness >>> components. >>> >>> Many thanks in advance. >>> >>> >>> Jens >>> >>> PhD student >>> University of Zurich >>> >>> [[alternative HTML version deleted]] >>> >>> _______________________________________________ >>> R-sig-ecology mailing list >>> R-sig-ecology@r-project.org >>> https://stat.ethz.ch/mailman/listinfo/r-sig-ecology >>> >> [[alternative HTML version deleted]] _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
