Hello,

I am having quite a bit of difficulty with model fitting and interpretation of a multi-state open robust-design model with state uncertainty in RMark.

EDIT

The data I am trying model is comprised of ~4 years of continuous remotely sensed data for a few thousand individuals. I have collapsed the continuous sensing data into capture histories with 4 primary periods (years) each with 4 secondary periods (seasons). Marking occurred at irregular intervals throughout the 4 years. The population comprises residents and transients which are indistinguishable upon initial capture.

END EDIT

I want to model seasonal movement patterns, so I have been reading the Ruiz-Gutierrez et al. (2016) paper for the state uncertainty application to transience and residency, as well as the Kendall et al. (2019) paper which compares demographic parameters among seasons. I am confused by the apparent simplicity of the models described in the paper when I compare them to the models implemented in RMark, which I would think use the appropriate numerical processes for parameter estimation. Let me explain first the Ruiz-Gutierrez confusion:

This MSORD-SU model is said to have 9 parameters though I only understand 7 of them being detailed. Meanwhile, the RMark model, Robust Design Multi-state Open with Mis-classification (RDMSOpenMisClass) has only 8 parameters. In the manuscript, they drop 2 annual parameters (S, Psi) to focus on within-season estimates. They utilize state structure (omega), probability of entry (pent), persistence (Phi), probability of detection (rho), and probability of correct classification (delta). This leaves me two short from their 9 or 1 parameter short of the 8 in the RMark model (Pi).

Next, in the Kendall et al. (2019) paper, I would have expected that they would use an extension of the above model like the Robust Design Multi-state Open with State Uncertainty and Seasonal Effects (RDMSOpenMCSeas) in RMark, but they used instead the Open Robust Design Multi-state which has 5 parameters rather than the 10. I imagine that the ‘data-hungry’ characteristic of MSORD models described by Boys et al. (2019) is the reason behind this choice but I also struggle to interpret these additional parameters: alpha, c, and d.

Based on the information I have provided, it makes sense that I use the season effects model (RDMSOpenMCSeas) in RMark, yes? The help files with RMark including ‘parameters.txt’ and ‘models.txt’, and reading chapters 10 and 15 didn’t help me very much unfortunately.

Thanks very much to anyone who is able to help me clear up some of this confusion.

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Ruiz-Gutierrez, V., Kendall, W. L., Saracco, J. F., & White, G. C. (2016). Overwintering strategies of migratory birds: a novel approach for estimating seasonal movement patterns of residents and transients. Journal of Applied Ecology, 53(4), 1035–1045.

Boys, R. M., Oliveira, C., Pérez-Jorge, S., Prieto, R., Steiner, L., & Silva, M. A. (2019). Multi-state open robust design applied to opportunistic data reveals dynamics of wide-ranging taxa: the sperm whale case. Ecosphere, 10(3), e02610.

Kendall, W. L., Stapleton, S., White, G. C., Richardson, J. I., Pearson, K. N., & Mason, P. (2019). A multistate open robust design: population dynamics, reproductive effort, and phenology of sea turtles from tagging data. Ecological Monographs, 89(1), e01329.