Hello everyone!

I am working on a project that requires me to use occupancy modeling. I am trying to incorporate camera trap data with single-season occupancy modeling. I have 25 sites with camera traps and 3 camera trap replicates in each site. I am using four covariates in the analysis as well which I have normalized.

I analyzed the data in PRESENCE. First, I ran the global model (will all the four covariates) in order to determine the best model for detection probability. I placed all the covariates in Occupancy and changed the detection section with covariates and constant. This resulted in the model with global in occupancy and a constant in detection as the top model.

While viewing the model output, the untransformed estimates of coefficients for covariates (Beta's) shows extremely high values for psi and the standard error shows -1.#IND00. I have attached the Beta file below:

estimate std.error

A1 psi.a1 : -96.760763 -1.#IND00

A2 psi.crown_cover : 637.571835 -1.#IND00

A3 psi.slope : 879.662465 -1.#IND00

A4 psi.presence_termite : 753.653862 -1.#IND00

A5 psi.distance_road : 1666.162959 -1.#IND00

B1 P[3].b1 : -0.570545 0.346989

I wanted to show the how the covariates have influenced the detection of the species from this output from the detectability model, But the estimates as well as the standard error values does not seem to be interpretable.

And while viewing the individual site estimates of psi, I have been constantly getting the similar issues

Individual Site estimates of <psi>

Site estimate Std.err 95% conf. interval

psi 1 site1 : 0.0000 -1.#IND 1.#QNB - 1.#QNB

psi 2 site2 : 1.0000 -1.#IND 1.#QNB - 1.#QNB

[This is listed for just the first two sites. The rest 23 sites has the similar estimates]

Can anyone help me out with this issue?

Looking forward to hear your advise.

Thank you very much for your time in advance.