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Hello phidot,

I am working on neckbanded Greylag Geese with SOVON in the Netherlands.

The geese have either:
- a metal leg ring
- a metal leg ring + colour leg ring + neckband

And they are resighted very frequently. But neckbands are resighted far more often than metal leg rings.
Ideally, we want to make 2 groups according to ring type.

Now there is a problem: Some geese loose their neckband, and subsequently have lower resighting probability, because they have only leg rings. In addition, captured juvenile geese get only a metal ring. When they are recaptured later as fully grown, they receive their neckbands.

In these 2 cases, the geese cannot be assigned to one of the 2 groups, but partially to one group (till the change in ring type) and then partially to the other group. Could this be incorporated in the model?

Or do you see an other solution for this problem?

Your help is very appreciated!

Best regards,
Kees Schreven

kschreven wrote:Hello phidot,

I am working on neckbanded Greylag Geese with SOVON in the Netherlands.

The geese have either:
- a metal leg ring
- a metal leg ring + colour leg ring + neckband

And they are resighted very frequently. But neckbands are resighted far more often than metal leg rings.
Ideally, we want to make 2 groups according to ring type.

Now there is a problem: Some geese loose their neckband, and subsequently have lower resighting probability, because they have only leg rings. In addition, captured juvenile geese get only a metal ring. When they are recaptured later as fully grown, they receive their neckbands.

In these 2 cases, the geese cannot be assigned to one of the 2 groups, but partially to one group (till the change in ring type) and then partially to the other group. Could this be incorporated in the model?

Or do you see an other solution for this problem?

Your help is very appreciated!

Best regards,
Kees Schreven

This sort of problem has received a lot of attention, across multiple taxa. Even with geese (as a specific taxonomic group), *lots* of papers. First step: think 'multi-state'. Second step: read the following (and references cited therein).

A Capture–Recapture Model with Double-Marking, Live and Dead Encounters, and Heterogeneity of Reporting Due to Auxiliary Mark Loss (2010) C Juillet, R Choquet, G Gauthier, R Pradel, Journal of Agricultural Biological and Environmental Statistics, Volume: Online Fir, Issue: 1, Publisher: Springer New York, Pages: 88-104

A general model for the analysis of mark-resight, mark-recapture, and band-recovery data under tag loss.
Conn PB, Kendall WL, Samuel MD. Biometrics. 2004 Dec;60(4):900-9.

Alisauskas, R.T., and M.S. Lindberg. 2002. Effects of neckbands on survival and fidelity of white‑fronted and Canada geese captured as non‑breeding adults. Journal of Applied Statistics 29:521-538.

Ok, Thank you very much!
I did not know that multi-state models could handle this.

Kees

kschreven wrote:Ok, Thank you very much!
I did not know that multi-state models could handle this.

Kees

Multi-state models are extremely flexible, and can handle almost any design where you have discrete groups (classes) of individuals, and where individuals can transition ('move') between classes. For example, tag loss is simply moving from one class (ringed) to another class (without rings).

Programs M-SURGE and E-SURGE are specifically designed to work with MS models in a very general way. You can do many of the same models in MARK (with some tricks, in some cases), but if you're starting 'from scratch', there may be some advantages in working with M-SURGE or E-SURGE from the outset.