I've been following along with the eBird best practices workbook using the occupancy modelling section as help for a PhD chapter that I am completing using eBird data. Essentially I am trying to assess the impact of urbanisation on raptors across Australia using occupancy modelling and pland_13_urban as my only site-level covariate. I am using multiple years of data, however, I would like to stack these years into a single season model like the one laid out in the best practices workbook. An example of the stacked data can be laid out here (https://kenkellner.com/blog/ubms-vignette.html#3_Example:_%E2%80%9CStacked%E2%80%9D_model_with_random_effect), which is treating site-year combinations as sites. I then plan to account for the pseudo-replication by having site as a random effect using the ubms package, which behaves like the unmarked package.
Is this something that is achievable with the eBird data?
Hi there,
I've been following along with the eBird best practices workbook using the occupancy modelling section as help for a PhD chapter that I am completing using eBird data. Essentially I am trying to assess the impact of urbanisation on raptors across Australia using occupancy modelling and pland_13_urban as my only site-level covariate. I am using multiple years of data, however, I would like to stack these years into a single season model like the one laid out in the best practices workbook. An example of the stacked data can be laid out here (https://kenkellner.com/blog/ubms-vignette.html#3_Example:_%E2%80%9CStacked%E2%80%9D_model_with_random_effect), which is treating site-year combinations as sites. I then plan to account for the pseudo-replication by having site as a random effect using the ubms package, which behaves like the unmarked package.
Is this something that is achievable with the eBird data?
Thanks,
Taylor