Correcting for trap dependence

[André4]

Good day

I am relatively new with the program mark and in need of some advise to account for trap dependence.

I am working a frog genus Xenopus looking at their survival. I have ran a GOF test in U-care and it indicated that there is strong trap dependence in the females and less so in males.

My problem is I do not know how to incorporate this trap dependence into my model.
Some advise would be greatly appreciated

Thank you
André

[cooch]

Good day

I am relatively new with the program mark and in need of some advise to account for trap dependence.

I am working a frog genus Xenopus looking at their survival. I have ran a GOF test in U-care and it indicated that there is strong trap dependence in the females and less so in males.

My problem is I do not know how to incorporate this trap dependence into my model.
Some advise would be greatly appreciated

Thank you
André

First, 'new' and 'MARK' is a solvable problem to some extent -- provided you're willing to do a bit of 'self-instruction' -- starting point for this is generally 'the book':

http://www.phidot.org/software/mark/docs/book/

Solutions typically depend on the duration of the 'dependence'. For example, if the duration is over one sampling interval, then fitting a single TSM (an 'age model') is often quite effective. Structurally, the TSM models handle a specific form of 'heterogeneity', which is effectively what 'trap dependence is'. Have a look at Chapter 7, sections on 'transience' (for example).

[Bryan Hamilton]

I've been working on trap dependence for a few days. I think I have the time since marking (TSM) model figured out. Its just an age model (or an Age model), with the following PIMS. This allows p to vary as a function of time since capture. It could be trap dependence or trap avoidance. It took me some time to get here, so I just wanted to confirm that I'm interpreting TSM models correctly.

Code: Select all

p(~age)
     1981 1982 1983 1984 1985 1986
1980    2    3    4    5    6    7
1981         2    3    4    5    6
1982              2    3    4    5
1983                   2    3    4
1984                        2    3
1985                             2

Where I'm still a little confused (Ok a lot confused) is how the trap dependence model in the RMark appendix from the mark book differs (C-77). This seems more like a time model, with a different p for each time.

Code: Select all

p(~td)
     1981 1982 1983 1984 1985 1986
1980    2    3    4    5    6    7
1981         3    4    5    6    7
1982              4    5    6    7
1983                   5    6    7
1984                        6    7
1985                             7

In the model below, each first recapture occasion has the same value of p but then subsequent recaptures are time dependent.

Code: Select all

p(~td:adult)
     1981 1982 1983 1984 1985 1986
1980    2    3    4    5    6    7
1981         2    4    5    6    7
1982              2    5    6    7
1983                   2    6    7
1984                        2    7
1985                             2

I admit that I'm pretty much blown away by the code that created the time dependence function. I'll try again in the morning with fresh eyes.... I can imagine a model where a recapture would "reset" the time dependence. The animal might positively or negatively react to the recapture similarly to its initial capture. That might be what the time dependence function is doing? I still don't fully grasp what the dummy variable are doing. I need to spend some more time on that.