Detectability Probabilities using Huggins Closed Capture

[linwhi]

Hi,

I’m new to the world of Program MARK. However, I’ve been tasked with determining detectability probabilities using Huggins closed capture in MARK. My input file includes an encounter history or detection by observers (11, 10 or 01) and 19 groups (representative of 19 species). The data was collected using a double observer method in which the two observers made simultaneous and independent observations. I’m having difficulties constraining the recapture probability such that C2=P2 in the design matrix. I would greatly appreciate any input on how to properly do this in the design matrix, or direction on where to find this information in “the book”.

Thanks

[Paul Lukacs]

See Chapter 15 on closed capture models

Paul Lukacs

[jlaake]

Alternatively you can use the MRDS analysis method in program DISTANCE to do your analysis. If you choose full independence it will limit the analysis to use the mark-recapture likelihood which is the same as the Huggins model. The MRDS software is written in R and is available separately from DISTANCE also. The code is freely available and you can look at how the computations are done. The method used is actually logistic regression with an offset. See ch 11 of the Advanced Distance Sampling book or Buckland et al 1992 in Marine Mammal Science. If you are using double observer with distance sampling then you'll want to see the recent article Borchers et al in Biometrics and in MRDS use the point indepdence assumption. Note that MRDS is currently limited to line transect data (not point transect) but if you use full independence it is simply mark-recapture and it will also work for point transects but the calculations of abundance would not be correct. But it sounds like you are only interested in detection probabilities.