Hello!
I'm using two-species multi season occupancy models to study species interaction with the psiBa/rBa parameterization. I have 33 sampling points, that have been surveyed 3 times within each season during year. I have built models testing different scenarios, evaluating within-season effects and an individual detection covariate.
I initially limited the analyses to patterns of detection because the site spacing was not distant enough to ensure spatial independence between survey units for species A. For this reason, parameters for occupancy probabilities (i.e. ΨA, ΨBA and ΨBa) were modelled independently. However, I'm not sure if it's right to build models testing different scenarios for psiBA and psiBa, given that for species B was ensure spatial independence between sampling points.
I built models that assumed that the detection probability of the subordinate species was influenced by the presence (pB≠rBa; pB≠rBA) or detection (rBa≠rBA) of the dominant species or was independent of the dominant species (pB = rBa = rBA). I also evaluate a set of models where, give than both species are present, the detection of the dominant species was influenced by the detection of the subordinate species (pA≠ rA) or independent (pA= rA). Preliminary results showed that the detection of the both species was independent of the detection of the other species (i.e., pA = rA, pB=rBa=rBA). However, I found no consistent interaction in the detection process at sites occupied by both species (δ = 0.29). I calculated the detection species interaction factor (δ) adapted from the formula for phi from Richmond et al (2010):
δ=(rA*rBA)/(rA*((rA*rBA)+((1-rA )*rBa))
It’s right? /Is there any other way of obtaining detection species interaction factor?
Thank you very much in advance for any comment!