optimal study period for Robust Design

questions concerning analysis/theory using program MARK

optimal study period for Robust Design

Postby Globice974 » Fri Jan 06, 2023 7:38 am


I want to estimate abundance of the spinner dolphins population off Reunion island through mark-recapture method. I have photoID data from 2012 to 2022. Because the closure tests show me that the population is open from a year to another (i.e., primary period), but closed across June-October of each year (i.e. secondary period), I decided to use a Robust Design method. Depending on the period chosen, I find quite different results:
* study period: 2012-2017 => {φ(.), ɣ”(.), ɣ’(.), p(T), c(T), N(.)}, with N=275 individuals (265-285)
* study period: 2012-2019 => {φ(.), γ"(.), γ'(.), p(t, T), c(t, T), N(T)}, with N varying from 97 ± 36,5 individuals (48 – 198) in 2017 to 211 ± 68,8 individuals (113 – 393) in 2012;
* study period: 2013-2021 => {Φ(.), gamma”(.), gamma’(T), p(t, T), c(t,T), N(T)} with N varying from 76 ± 12,3 individuals (56 – 105) in 2014 to 128 ± 29,4 individuals (82 – 200) in 2021

My question is then, what is the best study period? Is it necessary to have as many data as possible, or do I need to focus on a short period of time?

Thank you for your response.

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Re: optimal study period for Robust Design

Postby Eurycea » Tue Jan 10, 2023 4:53 pm

I'm going to go out on a limb here and suggest that how you structure your periods should not be determined by trying different period configurations in a closure test. My advice would be to first determine what periods you can experimentally justify as being closed and use the closure test as guidance on whether your assumption was met or not. But I would not advise using it as an exploratory test to partition your time periods. Perhaps someone else would advise you differently but this seems to be putting the cart before the horse. The experimental design of the data collection and details of the biological system should drive the decisions you make here. Just my 2 cents :D
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