Hello,
I would like to post a message, but I was wondering if I had to subscribe first?
Here is my message:
II performed over the seanson a census of butterflies on 8 sites . I have for
each date un number of individuals and of species. I would like to know which
function I could use to test if s
Dear sig-eco users,
I would like to investigate the changes in a species community along an
ecological gradient. I first thought about performing a Mantel test and infer
if differences in
species composition are related to differences in the ecological gradient. I
noticed that the function ado
Dear Martin,
Tank you very much. I thought about constrained ordination, but the distance
matrix I am using is not among the "usual" (Euclidian, Bray-Curtis,...). An
option
would be to use distance-based RDA, which is almost the same as adonis, but I
read that adonis should be even better (?)
Thank you very much for your explanations. So if I understood it correctly, a
significant outcome from adonis() (or capscale()) should indicate me that my
species community changes along the gradient? Nice that you also mention
betadisper, because I'd like also to look at variation in species co
Dear all, I am trying to test how the proportion of pollen of different plants
found in the brood cells of a wild bee changes over time. I conducted 4
sampling sessions
(thus time is a factor with 4 levels) and collected several pollen samples for
each time point (300 pollen grains counted for
Thank you very much for this suggestion. In fact I reconsidered my question and
I am not sure that zero-inflated model is what I need. If I understood it
properly,
a zero-inflated model is best suited when we don't know if zero values are true
or false absences (right?). In my case all zero val
Dear all,
I used adonis to perform a test of the pairwise site dissimilarity indices
proposed by Baselga (2010, 2012) in the package betapart. I am concerned about
my results
because I get some negative F-values. I read in another post that this may
happen because of the presence of negative ei
Thank you Liz,
I don't know tweedie, I'll have a look at it, but I have indeed some high
values. I know about the problems linked to the arcsine transformation. I won't
consider it
anyway. I'd like to use either the raw values of pollen grain counts or a
logistic quasibinomial model.
Best,
Va
Liz writes:
> Hi Valerie,
> The best advice I was ever given with regards to distribution was to choose
> the one with the best fit i.e. no pattern in the residuals.
> The 2 things to think about when fitting a GLM are the type of data you've
> collected (binomial, counts etc) so that you can get
I tried to use tweedie and it again worked very well for the most abundant
pollen types and when trying to fit the less abundant ones I got the error:
"glm.fit:
algorithm did not converge".
I have the impress that it is hopeless to try fitting a model...But anyway
thank you very much for making
Thank you very much for clarifying this point. My algorithm is certainly pretty
bad because as you say I am basically looking at zeros. One point I don't
really
understand is that for a pollen type I have a lot of pollen collected at date
1, some at time 2, few at time 3 and not at all at time
Dear all,
I am investigating diversity in different sites. I partitioned my measure of
diversity into to additive components (Baselga 2012) and get for each site a
value of overal
diversity change (between 0 and 1) and a value for each additive component,
such that for each site beta1+beta2=be
Dear Pierre,
Thank you very much for your answer. In fact I would like to make two different
analyses: one spatial and one temporal. For the spatial analysis, I will
compute the
dissimilarities in the way you suggested it, using beta.pair and dbRDA. For
temporal analysis of beta diversity betw
Dear all,
I would like to test changes in species dissimilarity matrices over time,
taking into account that the measurement are repeated in each site over years.
I used the
adonis function: adonis(diss.matrix~year, strata=site). However if I do the
same model entering site as an additional fi
Thank you for these explanations. If I put strata=site, this means that for
each site my dissimilarity matrix of year 1 and year 2 will be permuted and the
observed
changes compared to these random permutation? Adding site as a fixed factor
then ensure that I am testing changes in time site by
Thank you for these explanations. If I put strata=site, this means that for
each site my dissimilarity matrix of year 1 and year 2 will be permuted and the
observed
changes compared to these random permutation? Adding site as a fixed factor
then ensure that I am testing changes in time site by
Dear Steve,
Thank you very much. I do not exactly understand why the test for isolation
will be wrong, would you have some some explanation?
In a linear regression, you cannot assess the effect of single variable if the
interaction (in which your variable is part) is significant. So if I get a
Thank you very much for your explanations. I still would have a question about
the proportion explained. I got for example an R2 of 0.11 for years*isolation
and
0.46 for site. Does this mean that most of the variation in species composition
is between sites and within site variation (also from
Dear all,
I computed a binomial model with a proportion as response variable using
glm(cbind(realized, not realized)~x,family="binomial"). The output tells me
that the
dispersion parameter taken is 1. For comparison I computed the same model using
family="quasibinomial" and I get a dispersion p
Dear all,
I would like to implement a null model to test if nestedness of a matrix
departs from chance. There is an example in package "bipartite" with the
function "nullmodel":
obs <- unlist(networklevel(web, index="weighted NODF"))
nulls <- nullmodel(web, N=100, method=1)
null <- unlist(sappl
Thank you very much. Yes it is working with oecosimu, exept that it does not
seem to work for weighted data. There is the possibility to specify "weighted =
TRUE":
oecosimu(matrix,nestednodf, method = "quasiswap", nsimul = 999, order = FALSE,
weighted =TRUE)
However, I get only null values an
Dear Jari,
Thank you very much for this clear answer. I did not get that quasiswap only
concerned binary data. After reading your explanations, I think I'll stay to
binary
data and avoid the issue of weighted ones, which are much less straightforward
to interpret. Anyway, I will have a look at
Dear all,
I performed a census of insects at different sites and measured there size. I
would like to know if size is related to an environmental factor. I modelled
the size as a
fonction of the factor with site as a random variable to account for
within-site variability. However I have strong
Thank you very much for these explanations. It is quite technical and I am not
sure that I got it all, but I will try to find the book of Gelman&Hill to get
more insight into
shrinkage. I read the book of Zuur and as you said the topic is not extensively
covered.
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