[R-sig-eco] Phylogenetic turnover using large datasets

[Jens Ringelberg]

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.hauffe using 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.ringelberg using 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
>>
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>>
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