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I'm using eBird count data to try and look at changes in bird distributions over time throughout the urban gradient. I'm an undergrad so my stats level is pretty limited. I took the relative count (observed count/total count in a year) of observations from 2003 to 2023. I'm trying to run a GLM poisson right now but it is not going very well. Any advice on this model or another model would be greatly appreciated.

Edit: I didn't transform my data, it is not normal

I tried running this code:

glm_interactions<-glmer(RelCount~ urban_category*year+ latitude + longitude + number_observers + day_of_year + (1|county) + (1|protocol_type), family="poisson", data = DF)

But it gave me

50+ warnings (1: In (function (fr, X, reTrms, family, nAGQ = 1L, verbose = 0L,  ... :
  non-integer x = 0.000321)
Eco10008
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  • To get better, faster help you should edit this question to provide a minimal reproducible example, see here for some tips on how to do that: https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example – jpsmith Apr 24 '23 at 02:39

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