I have a data set of repeated abundance counts over time.  I am
investigating whether count data reduced to presence-absence (presence) data
will reveal similar population trends.  I am using a negative binomial
distribution for the glm (package MASS) because the count data contains many
zeros and extreme values.  "count" and "presence" are annual sums for each
metric.  I have also included sampling effort (visits) as an independent
variable because sampling varies between 29-33 visits per year.  My models
are:

glm.nb(count ~ year + visits) and
glm.nb(presence ~ year + visits)

I would like to test whether the coefficients for "year" are significantly
different between models.  Please advise me on the best method to make such
a comparison.

Thank you,
Kayce

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