Hi,

I am trying to better understand if the detection probability from single-season occupancy models is per night or per session?

Some context:

I did an analysis of camera data where the cameras were deployed for three nights (nocturnal species of interest) at all stations, for one sampling session. I repeated this each season (4 total) across the year. So each station has four detection histories, one for each season. I then analyzed the data and obtained a detection probability (that varied by season). My question is, if the detection probability, say for summer was given at .87, is that the probability of detecting the species across a three night deployment, or the probability of detecting the species each night of deployment?

I am trying to estimate the probability of not detecting the species if it was present at a site from one session (3 nights). Reviewing Mackenzie et al (2018) book, the example (ch4, blue-ridge salamanders) was conducted where each survey was one day, and there were five surveys, so they probability of not detecting if it was present is : (1-p)^k, where k = 5 for five surveys.

So my question is, if my survey session were 3 nights, then the detection probability I have obtained (0.87) is the probability of detecting the species should it be present for each night of camera deployment? So my probability of not detecting if it was present for on session would be : (1-.87)^3? . Likewise if it was not detected at a station for all four seasons, the probability of non detection if present would be (1-pSummer)^3(1-pWinter)^3(1-pSpring)^3(1-pFall)^3

Thanks in advance!