Using individual time varying covariantes in JS model

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Using individual time varying covariantes in JS model

Postby jaas0991 » Wed Sep 19, 2018 11:37 pm

Hi, greetings to everyone. My name is Joel Arredondo. I'm doing a study on the abundance of a fin whale population on a region of the Gulf of California, Mexico. I assembled the capture histories from photo-ID comparisons. I've been reading the manual and surfing the forums for a while, but this is my first post.

I've analyzed my data using closed and open models. Now, I'm searching for a way to use time-varying individual covariates in the JS model.

The data consists of 360 capture histories, collected over eight years. Each digit represents a year. During each year the survey team went out at least once per week for almost 10 months. When possible, they applied photo-ID, after which they registered the following covariates:
I. Sea surface temperature (continuous)
II. Beaufort (categorical)
III, Swell (categorical and binary, presence or absence)
IV. Depth (continuous)
V. Visibility (continuous, "how far is it possible to see clearly?" )
VI. Cloudiness (continuous, percentage of cloud cover)

One extra complication is that for one year I might have several different values of all of those covariates, because an individual could have been seen more than once in a year, for example by being photographed in January, March, and November.

I've found some online articles relating to the use of time-varying individual covariates in mark-recapture, but I'm wondering if someone could give some additional guidance on how to proceed.
Besides reading the manual here are some articles i've found:
Trinomial model in MARK https://besjournals.onlinelibrary.wiley ... 12.00265.x
Continuous covariates: comparison of methods https://onlinelibrary.wiley.com/doi/abs ... 10.01390.x

Thank you :)
jaas0991
 
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