[R-sig-eco] R-sig-ecology Digest, Vol 145, Issue 14

Sharath S.P @h@r@th@p93 @end|ng |rom gm@||@com
Mon Apr 27 16:12:01 CEST 2020


Dear all,

Greetings!

The Myristica malabarica is an economically important and threatened
species of central Western Ghats, India. Due to over-exploitation, there
exists a threat to the regeneration of the species

*I am trying to analyse the effect of maturity stage (Totally 6 stages),
storage treatments (room temperature and refrigerator), and fruits
collected from trees across the elevational gradient (3 gradients) on the
successful regeneration of Myristica malabarica fruit. *

I made *ANOVA and correlation plots* and found that trees across gradient *vary
significantly in terms of fruit parameters and regeneration*. I want to
further analyse the data, but not sure what kind of analysis might be
interesting in this case.

Would be looking forward to your kind suggestions. Thanks in advance.

Regards,
Sharath S P
Georg-August-Universitat Göttingen
Gottingen, Germany


On Mon, 27 Apr 2020 at 12:02, <r-sig-ecology-request using r-project.org> wrote:

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>    1. Re: clustering communities by an environmental variable
>       (Irene Adamo)
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Sun, 26 Apr 2020 12:06:00 +0200
> From: Irene Adamo <i.adamo90 using gmail.com>
> To: Pierre Thiriet <pierre.d.thiriet using gmail.com>
> Cc: Salvador SANCHEZ COLON <salvadorsanchezcolon using prodigy.net.mx>,
>         r-sig-ecology using r-project.org
> Subject: Re: [R-sig-eco] clustering communities by an environmental
>         variable
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>
> Hi all! Thanks a lot for all the suggestions! I will try with multivariate
> regression!
>
> Il giorno sab 25 apr 2020 alle 22:17 Pierre Thiriet <
> pierre.d.thiriet using gmail.com> ha scritto:
>
> > Hi
> > You might have a look to multivariate regression tree, formerly mvpart
> > packagé
> > Cheers
> > Le 24 avr. 2020, à 18:30, Salvador SANCHEZ COLON <
> > salvadorsanchezcolon using prodigy.net.mx> a écrit:
> >>
> >> Hi Irene,
> >>
> >>
> >> The approach that you are using -i.e., calculating the between-sample
> dissimilarity with the Bray-Curtis distance, followed by the UPGMA
> clustering technique- will group your samples based on the values of all
> the variables contained in your data matrix (which, in ecological studies,
> usually are species abundance or presence/absence data).
> >>
> >>
> >> I hope this helps but feel free to ask further details.
> >>
> >>
> >> Salvador SÁNCHEZ-COLÓN
> >> Independent consultant
> >>
> >>
> >> En Vie, 24 Abril, 2020 en 10:49, Irene Adamo <i.adamo90 using gmail.com>
> escribió:
> >>
> >>
> >> Para: r-sig-ecology using r-project.org
> >> Dear all,
> >> I am trying to do a dendrogram by trying to see if my communities by
> >> altitude but I am not sure on how to do it.
> >> lets say I have this example
> >>
> >> # calculate Bray-Curtis distance among samples comm.bc.dist <-
> vegdist(comm,
> >> method = "bray") # cluster communities using average-linkage algorithm
> >> comm.bc.clust <- hclust(comm.bc.dist, method = "average") # plot cluster
> >> diagram plot(comm.bc.clust, ylab = "Bray-Curtis dissimilarity")
> >>
> >> Now, I would like to cluster my communities by Altitude always using the
> >> distance matrix and the dendrogram.
> >> Is it possible?
> >>
> >> Thanks a lot for any help!
> >>
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