Advice on handling unequal temporal coverage in IPM
Nguvan Agaigbe
I am currently fitting an Integrated Population Model (IPM) spanning 33 years, but I am struggling with reconciling the unequal temporal coverage of my different data sources.
My survival model, which was collected using telemetry, has empirical data from 1992–2002 and 2012–2017. The productivity model covers 1992–2001 and 2012–2017, while my count data spans 2012–2024.
While chapter 6 of the IPM textbook has been helpful in dealing with this in a way, I still find it difficult to handle this mismatch in data coverage effectively. Would it be best to allow for missing data in certain years, use priors to inform the missing periods, or take a different approach altogether? Also, given that my survival data comes from two separate periods, would you recommend treating them as distinct periods in the model, or should I combine them in some way to improve estimation?
Any insights you can share would be greatly appreciated.
Thank you.
Mercy.
Michael Schaub
Hi Mercy,
I think the main problem is that your count data does not cover the whole period, in fact you have none for the first 20 years. When you start your model you need a prior for the population size in 1992, which is likely to be difficult to develop, and your estimated population sizes are likely to be very inaccurate. I also expect the result to be quite sensitive to the choice of prior in 1992. So I'm afraid it will be very difficult to develop an IPM for the whole period. Perhaps you can find a population count or index of population size elsewhere and use that, assuming the dynamics were the same. Otherwise, limit your IPM to data from 2012 to 2024. This should not be a problem.
Kind regards
Michael
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