# Cross-over with sequence effect

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

## Data

### Bees

- 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

### Vegetation

In each site, there are

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

### Question

What is the relationship between coverage and bee abundance?

## Model

Poisson regression with fixed effects for

- average coverage
- survey period
- year
- coverage*period
- coverage*year
- period*year
- coverage
*period*year

random effects for

- site
- site*year
- site
*year*period (observation specific)

### Other models

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

Negative-binomials failed to converge.

### Results

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.

### Question

How to deal with overdispersion?

## Advice

Pull all coverage interactions.

### Model

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.