I have run a power analysis on my occupancy models that says for a power of 0.85, and using 204 sample units with 11 replicates, the detection probability would need to be about 0.096.
How can I convert this detection probability to tell me how many detections (1's) would need to be in my detection history for that to be the detection probability?
Thanks for any help!
The detection probability seems pretty low, and I am positive with 11 replicates this could be established. However you do have a good question, maybe put up this question in the occupancy forum (http://www.phidot.org/forum/index.php) and maybe some of the experts can answer this accurately.
Detection probability indicates that for each occasion that you go sampling, you have that chance of finding the individuals when they are alive and present in your sampling area. If your detection probability is 0.096, that means you need to find your individuals at least 9.6% of the time each time you go - for 204 "sampling units" (individuals?), you'd need to find ~20 (0.096*204) each time, which is quite low, so that shouldn't be too much of a problem. Keep in mind that if individuals die or disperse out of the area, your 204 will change. Good luck!
I think it's circular reasoning because the detection probability is calculated using your criteria, which already include the detections!
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