Survival estimates

questions concerning anlysis/theory using program DENSITY and R package secr. Focus on spatially-explicit analysis.

Survival estimates

Postby mldavis13 » Tue Dec 20, 2011 1:51 pm

I'm sorry to ask what I'm sure is a fairly obvious question. But I am currently considering whether or not to use MARK or SECR for my analysis. I've read documentation and not yet found the answer to my question stated explicity. So before I get too deep, does SECR provide any estimates of survival in the outputs? (Hopefully a quick answer at least).

Thanks for your time,

Miranda
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Re: Survival estimates

Postby murray.efford » Tue Dec 20, 2011 2:48 pm

Miranda
The package 'secr' is currently for closed populations; you should use RMark/MARK for survival analyses. However, (i) the latest version of secr (2.3.1 became available on CRAN a few hours ago) has a new function RMarkInput that makes it easy to flip data from `secr' to RMark (see ?RMarkInput) and (ii) secr 2.3.1 has an undocumented 'death-only' (survival but no recruitment) open population model that will be extended and documented next year. In the meantime, insider knowledge is needed!

Using nonspatial methods has a slight cost: CJS estimates of survival probability (as implemented in MARK) will be somewhat biased by the heterogeneous individual capture probabilities that usually result from spatial sampling. This is usually assumed to be negligible, but may not be. So, ultimately, 'spatial' survival estimation that models the spatial individual heterogeneity is a good idea, but the software is not quite there.

If you are not primarily interested in survival but rather in population trend then 'secr' will do the job, as it can fit a density trend across multiple closed population 'sessions'.

Murray
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Re: Survival estimates

Postby mldavis13 » Fri Jan 06, 2012 12:56 pm

Thank you, that was just what I needed to know! I'm currently looking into your 2009 ecology paper which may prove very useful.

Your advice is much appreciated,

Miranda
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