Peter,

I have repeated visits, so detection error should not be a problem
(abundances were summed over visits). The zero-inflation is due to the
seldomness of my species. Actually, I am thinking if it would be sensible
to  transform the response to absence/presence..
Another issue is the preferantial sampling that was used for data
collection as mentioned in my original post.

Many thanks for your advise,
Kay

Am 15.02.2012 19:11 schrieb "Peter Solymos" <solymos@ualberta.ca>:
>
> Kay and Alexandre,
>
> INLA approach might be fine, but given the data you described, I would
> rather think about what might cause the zero inflation (90% zeros) and
> the spatial autocorrelation and pick a model accordingly. For example
> if the zero inflation might be caused by low abundance related to low
> habitat suitability, underlying occupancy/range pattern, or detection
> error, or some combination of these. Depending on the cause of the
> zeros, the treatment of autocorrelation might change. If you have all
> nonzero counts clumped together, it might be explained by a spatial
> covariate effect. If not, 10% nonzero count in the range of 1-6 won't
> necessarily allow a meaningful estimation of spatial autocorrelation
> (of course depending on sample size). On the other hand, if you have
> nonzero counts scattered in the landscape, estimating autocorrelation
> again will be difficult as it roughly decreases at a rho^distance
> rate.
>
> Detection error is a whole other can of worms, but using single visit
> (without temporal replication) to sites actually allow to correct for
> detection error as long as covariates are available (see svabu
> function in detect package and references on svabu help page, this
> implements ZIP model with detection error and without spatial
> autocorrelation).
>
> Cheers,
>
> Peter
>
> Péter Sólymos
> Alberta Biodiversity Monitoring Institute
> and Boreal Avian Modelling project
> Department of Biological Sciences
> CW 405, Biological Sciences Bldg
> University of Alberta
> Edmonton, Alberta, T6G 2E9, Canada
> Phone: 780.492.8534
> Fax: 780.492.7635
> email <- paste("solymos", "ualberta.ca", sep = "@")
> http://www.abmi.ca
> http://www.borealbirds.ca
> http://sites.google.com/site/psolymos
>
>
>
> On Tue, Feb 14, 2012 at 5:25 PM, Kay Cichini <kay.cichini@gmail.com>
wrote:
> > Alexandre, many thanks, there seems to be plenty of useful content on
the
> > linked site!
> >
> > Am 14.02.2012 14:56 schrieb "Alexandre Villers" <
villers.alexandre@gmail.com
> >>:
> >>
> >> I answered by mistake on the R SIG GEO.... sorry for cross posting.
> >>
> >> ---------------------------------------------------------------------
> >>
> >> Hi,
> >>
> >>
> >> If you are not afraid to switch to Bayesian methods (but fast ones !),
> > the INLA package could do that for you. ( www.r-inla.org )
> >> Cheers
> >>
> >>
> >> Alex
> >>
> >> On 14/02/2012 15:36, Kay Cichini wrote:
> >>>
> >>> Hi all,
> >>>
> >>> I'd very much appreciate pointers at methodology/R-packages/functions
> >>> suited for modelling zero inflated species abundance data (counts)
that
> >>> most likely will show spatial autocorrelation. Species abundances
range
> >>> between 0 and 6, the proportion of zeroes is about 90%. I have about 6
> >>> nominal covariables (partly heavily unbalanced).
> >>>
> >>> Yours,
> >>> Kay
> >>>
> >>>        [[alternative HTML version deleted]]
> >>>
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> >>> R-sig-ecology@r-project.org
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> >>>
> >>
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> >
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> >
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> >

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