Hello,
I’m working on a project trying to estimate density of pumas and how it changes with the migration of their main prey. Sampling design was a two grid formation (north and south) and cameras were running for a total of 190 days. From the photos, I was able to ID 18 adult individuals from natural marks, but have more than 50% of the photos that I wasn’t able to ID.
I’m trying to run SMR models by splitting the data in four sessions (north_summer, north_winter, south_summer, south_winter) and 10 occasions of 19 days each.
First, I tried to run the model for all four sessions in a single capture file, but got the following error:
Error in `Tu<-`(`*tmp*`, value = integer(0)) : replacement of Tu for multisession object requires a list
To solved this, I separated all sessions and read them in separately and use MS.capthist() to combine the sessions together.
I was then able to run some models but, when running the model with predictor ts (lambda0~ts), to distinguish for marking and sighting occasions, I get the following error: Error in secr.design.MS(capthist, model, timecov, sessioncov, groups, : ts is appropriate only for mark-resight data
I was able to run this model (lambda0~ts) for each session separately, though.
To sum up, I’m able to run SMR models with predictor ts (lambda0~ts) independently by session, but not together after combining them with MS.capthist.
What would be the best way to solve this?
Thanks for any help,
Laura