Looking at the relationship between the number of bees present and the amount of vegetation at a location.



  • 3 years of data
  • 11 different sites (unbalanced across years)
  • 5 survey periods per year
  • measure total number of bees
  • 5-6 different trap types (currently aggregating over trap types)
  • currently looking at bee abundance


In each site, there are

  • 10 quadrats
  • measure coverage in each quadrat
  • currently averaging across the 10 quadrats


What is the relationship between coverage and bee abundance?


Poisson regression with fixed effects for

  • average coverage
  • survey period
  • year
  • coverage*period
  • coverage*year
  • period*year
  • coverageperiodyear

random effects for

  • site
  • site*year
  • siteyearperiod (observation specific)

Other models

Also considered normal regression models based on log and sqrt transforms.

Negative-binomials failed to converge.


Inidcation of overdispersion in a model without the observation-specific random effect.

Zero estimate for variance for year*site interaction in the model with the observation-specific random effect.


How to deal with overdispersion?


Pull all coverage interactions.


Fixed effects for

  • coverage
  • use year-period combination

Random effects for

  • site
  • site*year

Possibly add an observation-specific random effect in a Poisson model to deal with overdispersion.