Table 1.

Occupancy models fitted to investigate the distribution dynamic of mountain-dwelling songbirds throughout the breeding season.

Model
ψ(.), p(.)
ψ(.), p(session + autocov)
ψ(lc), p(session + autocov)
ψ(lc + t), p(session + autocov)
ψ(.), γ(.), ε(.), p(.)
ψ(.), γ(.), ε(.), p(session + autocov)
ψ(lc), γ(.), ε(.), p(session + autocov)
ψ(lc + t), γ(.), ε(.), p(session + autocov)
ψ(lc), γ(lc), ε(lc), p(session + autocov)
ψ(lc + t), γ(lc), ε(lc), p(session + autocov)
ψ(lc), γ(lc + t), ε(lc + t), p(session + autocov)
ψ(lc + t), γ(lc + t), ε(lc + t), p(session + autocov)

Dynamic models describe initial occupancy (ψ), settlement (γ), vacancy (ε) and detection probability (p), while static models describe a time-constant occupancy accounting for detection probability. We compared models based on constant parameters (.) and on the influence of land cover characteristics (lc) and fine-scale temperatures (t), while for modelling detection we used the sampling session (session) and a temporal autocovariate (autocov).