[Basta-users] Different detection probabilities for different cohorts

Simon Lamb simon at wmil.co.nz
Tue Oct 4 01:30:30 CEST 2022


Hi Basta team,

Thank you for writing such a great package!

I am wondering if you could provide any guidance on my situation below:

I have a situation where I'm looking at a survival of a species of gull over an approximately ten year period. Birds (all birds were ringed as pulli, so year of birth is known) from the first cohort were ringed with only a metal band (quite hard to read even with binoculars - impossible without unless in the hand), and then every cohort after that was ringed with a metal band and a numbered darvic colour band (easy to read and distinguish individuals with binoculars). Over the years birds from that first cohort when caught again were also given a darvic band to help with re-sightings.

There's obviously a difference in detection probability of that early cohort that stems from the lack of the ringing equipment available at the time of the initial study. Effort through the years towards re-sightings have been relatively similar over time. The recaptTrans argument I feel does not quite apply in this context - as birds may subsequently be caught again later in the study and be ringed and thus the detection probability would become relatively even with the other cohorts.

So, the question for me was how to account for this in the model. My initial thought was to include a categorical variable (yes/no) of whether the bird was ringed with this extra darvic band or not, or potentially a categorical variable for each cohort? I'm just not sure how to proceed.

Any guidance would be much appreciated it!

Kind regards,
Simon

Simon Lamb
Apprentice Ecologist

Wildlife Management International Limited.
PO Box 607, Blenheim 7240. Mobile: 0273059170
www.wmil.co.nz/<https://apc01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.wmil.co.nz%2F&data=04%7C01%7Cpascale.lubbe%40postgrad.otago.ac.nz%7C1c1af8b1999d4c522cca08d8d2ea3d51%7C0225efc578fe4928b1579ef24809e9ba%7C1%7C0%7C637491250803282577%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=iAjnwvpJNn%2FVbpvWKp9qg2D2L%2FXpu9HxU49O8H4HUuY%3D&reserved=0>
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