Effect of known mortalities in CJS models

questions concerning analysis/theory using program MARK

Effect of known mortalities in CJS models

Postby Bryan Hamilton » Mon Mar 07, 2016 8:46 pm

I'm working through some CJS analyses and observed known mortalities of six marked individuals. This is out of a total of approximately 400 individuals in the analysis. I denoted these individuals with a "-1" in the freq column. All other individuals received a "1" in the freq column.

When I ran the analysis without the freq column (in other words did not denote the mortalities), the results were very close to the analysis with the mortalities included.

In Chapter 2 of the MARK book, I found some discussion of removing individuals "The negative values indicate to MARK that 23 and 25 individuals in both groups were marked on the 1rst occasion, not seen on the next 2 occasions,were encountered on the fourth occasion, at which time they were removed from the study. Clearly, if they were removed, they cannot have been seen again."

I'm trying to understand how MARK processes these individuals removed. Intuitively, I feel like the presence of mortalities should increase capture probability and decrease apparent survival. But this is apparently not happening in my case.

Can anyone offer some advice or references on how removing individuals affects CJS models in MARK?

Thank you.
Bryan Hamilton
 
Posts: 111
Joined: Thu Jun 15, 2006 11:36 am
Location: Great Basin National Park

Re: Effect of known mortalities in CJS models

Postby ganghis » Mon Mar 07, 2016 8:56 pm

HI Bryan,

The '-1' code is for removing individuals from the live marked population. This is usually reserved for losses on capture, and the idea is that you don't want to include these biologist-caused mortalities in the survival estimate.

If the known mortalities are natural, and are not associated with the capture even itself, you have two options to get unbiased survival estimates

1) pretend you never observed the mortalities
2) conduct a joint recapture-recovery analysis with these 6 individuals treated as recoveries

The second may afford slightly higher precision, but requires estimating more parameters. The easiest thing would be to ignore the extra info on known mortalities (i.e., just treat those individuals as regular releases that you never observe again).

-Paul
ganghis
 
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Joined: Tue Aug 10, 2004 2:05 pm

Re: Effect of known mortalities in CJS models

Postby Bryan Hamilton » Tue Mar 08, 2016 8:46 pm

Thank you. That helps a lot. Its interesting, the years I observed the most mortalities, have the lowest survivial....

I guess these things really work after all. :D
Bryan Hamilton
 
Posts: 111
Joined: Thu Jun 15, 2006 11:36 am
Location: Great Basin National Park


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