Hi List,
I am trying to deal with observation data on groups of a species.
What i have is polygon maps of the species, with each polygon showing a
different group size.
So ideally i have a number of observed groups for each survey.
My main question is to identify suitable areas based on different group
sizes ( I guess one can also call it different polygons of abundance).
This data is biased, with some errors already identified. I wish to predict
suitable habitat based on the observed group size distributions and some
environmental variables of relevance, which i feel could be done using any
habitat suitability modelling algorithm (RSF, MD etc.) or a point process
model (spatstat) by sampling points based on the abundance/ group size
observed in each polygon. Following that i wish to back calculate the group
size distributions to include the error and  identify the actual group size
distributions in real space of suitable habitat by projecting these bias
removed estimates.
My questions then is:
Can anyone suggest me how i can project the bias removed estimates of group
sizes on habitat suitability model?
Can it be done in R?
or am i going in the right direction of identifying areas with larger and
smaller groups based on this habitat suitability modelling approach?
Comments are very welcome.
Thanks,
Navinder

n.singh@imperial.ac.uk

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