Two-species single-season model and removal sampling design

questions concerning analysis/theory using program PRESENCE

Two-species single-season model and removal sampling design

Postby lenasmarques » Wed Aug 08, 2018 10:41 pm

I have occupancy data for two vole species, in 347 habitat patches. We only made one survey per patch, but we recorded time to first detection for presence signs of both species and stopped the survey once both species were detected (or continued to a maximum amount of time if at least one of the species was not detected). The maximum survey time was variable and dependent on the patch size.

Since the information that we have is the time to first detection, we opted to apply a removal sampling design to our data, by dividing the total survey time in each patch in equal intervals and consider each interval a different survey. Since the time to first detection for both species is different, we also have two distinct detection histories for each vole species. For example, in a single patch, if species A was detected in the first time interval, we have a history 1----- ; and if species B was not detected we can have a history 00000.

I tried to run a two-species, single-season model with this data. The input data was formatted by doubling the number of sites, with 694 records, where the first 347 were from species A and records 348-694 were from species B. With this input data, the resulting models (and different parameterizations) do not converge and give pretty strange results (in comparison with the single-species models, and even the naive occupancy estimates are wrong).

I tried a different approach, where I coded the data as 0 = no detection of either species, 1 = detection of species A only, 2 = detection of species B only, 3 = detection of both species. However, in this case, whenever I had a patch where both species were not detected in the same timey interval, I had to “force” false detections after the first detection of the first species to be detected, until the first detection of the second species. The results of this model were much better (and agree with single-species model results), but, as expected, the detection probability was overestimated (around 0.96 for both species, where the detectability in the single-species models was 0.79 and 0.82).

So my question is:
Is there any problem in applying removal sampling with two species models, or the problem is specifically with my dataset (too much variability in the number of time intervals between both species, maybe?)? How can I get around this?

Any advice will be greatly appreciated.

Helena Sabino-Marques
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Re: Two-species single-season model and removal sampling des

Postby darryl » Thu Aug 09, 2018 8:42 pm

Hi Helena,
The models were originally coded up assuming that each species is detectable so you can't have a missing value for one species, but not the other. I'm not sure if Jim has modified this more recently, but if not, that could be contributing to your problems.

A test would be to fit a 2-species model, but make it so that occupancy and detection are completely independent for both species. If everything is working ok, you should get the exact same estimates as fitting the model to the data for each species separately.

Did you really stop recording the detections for a species after first detection while still searching for the other species?

Darryl
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Re: Two-species single-season model and removal sampling des

Postby lenasmarques » Tue Aug 14, 2018 10:34 am

Hi Darryl,

Thank you so much for your quick response!

That´s what I was afraid of, that I could not have a missing value for one species, but not for the other…

I followed your suggestion, and fitted a 2-species model, but fixing phi and delta to 1, and additional ones where I made rA=pA and rB=pB, and with the alternative parameterization where I made psiBA=psiBa, rA=pA, rBA=rBa=pB. The only improvement was that the models no longer had numerical convergence problems, but the estimates were totally off. The naïve estimates were low (0.37, when it should be 0.56).

We really did stop recording the timing of the detections for a species after first detection, while still searching for the other species… I guess I just have to find a different way to analyze this data set.

Thank you for your help

Helena
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Re: Two-species single-season model and removal sampling des

Postby darryl » Tue Aug 14, 2018 3:44 pm

Hi Helena
Theoretically I'm pretty sure your situation can be modelled, it just looks like the current implementation in PRESENCE isn't set up to do so. Maybe you could talk really nicely to Jim Hines... ;-)
Cheers
Darryl
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Re: Two-species single-season model and removal sampling des

Postby jhines » Sat Aug 18, 2018 1:20 pm

Hi Helena,

I've modified Presence and RPresence to handle missing data for the case where one of the two species has missing data. Please download the latest version and give it a try. It worked well with some simulated data I tried, but I don't know how it will do with real data with low detection probabilities. If you still get weird results, I'd be happy to diagnose if you send me the data.

Cheers,

Jim
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Re: Two-species single-season model and removal sampling des

Postby lenasmarques » Tue Aug 21, 2018 6:48 pm

Hi Jim,

Yesterday I was about to send you an email to “talk really nicely with you”, as Darryl suggested, when I saw your reply. Thank you so much for the changes you made to Presence!

I downloaded the latest version and ran some models with the same dataset. The results now are much better and make much more sense. The only thing that keeps getting weird results is the naïve occupancy estimate. As I understand it, in this case the naïve estimate is the proportion of sites occupied by at least one of the species, right? Please correct me i´m wrong. But I keep getting the same low naïve estimates as I did with the previous version.

I´m sending some data by email so you can have a look.

Once again, thank you so much for your help.

Cheers,

Helena
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Re: Two-species single-season model and removal sampling des

Postby jhines » Wed Aug 22, 2018 9:17 am

The naive estimate of occupancy is sort of an average of naive occupancy for species A and naive occupancy for species B. I wouldn't pay much attention to it. I've modified the next version of Presence to print the two naive estimates for that model and will upload it soon.

Jim
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