# How can I generate seasonal count data that has two different expected values?

The motivation for my question is modelling changes in abundance of a species whose population is estimated from survey data. The challenge for me would be to see if ignoring a food indicator masks any population trend. Especially because I won't have every day surveyed in reality. There are two aspects I want to capture:

1. the abundance should change over the year with a summer peak due to a breeding season.
2. the abundance should also change with an indicator variable that shows whether the animals were clumped due to the presence of food or not.

What I have so far gets at the second point but not the first:

library(tidyverse)

set.seed(123)
day <- c(1:365) # day of the year
precount <- rpois(365, 5) # basic counts when there's no food
indicator <- sample(0:1, 365, replace = TRUE) # presence or absence of food
extra <- rpois(365, 20) # additional number of individuals in the presence of food

df <- data.frame(cbind(day, precount, indicator, extra)) # group it together
df <- df %>% mutate(count = if_else(indicator == 1, precount + extra, precount)) %>%
select(day,count,indicator)