Fig 1.
Study area showing the distribution of the camera-trapping blocks (dots) within Andalusia and the distribution range assumed for the European wildcat [94].
Geographic areas considered in the present study: A Sierras Béticas, B Sierra Morena, C Doñana. Block 23 was carried out by Gómez-Chicano et al. [57]; and blocks 24, 25 and 26 by Soto and Palomares [43].
Table 1.
Details of the 26 systematic camera-trapping blocks (see Fig 1 for location of each).
Grey rows: sampling blocks with SCR calculations (N = 11, see details in Table 2); lure: (p) pigeon bait, (o) lynx urine, *data from Simón et al. [58].
Table 2.
Estimates of relative contributions of the environmental variables to the MaxEnt model.
Fig 2.
Wildcat potential distribution in the study area modelled with MaxEnt (patches of more than 228 hectares, see text for further details).
Table 3.
Density estimations (individual/km2) by Bayesian Spatial Explicit Capture Recapture models (block #18 to #14).
See Table 1 for details of each sampling block. λ0 is the baseline detection rate, and σ the parameter of scale from the half-normal distribution, related to the home range.
Table 4.
Upper bold line: best selected models in multimodel GLM with the wildcat density as a response variable and olive crop cover and precipitation as predictors.
We show the AICc values, ΔAICc and Akaike weights of each supported model. Lower bold line: model-averaged coefficients from the multimodel GLM with wildcat density as a response variable and olive crop cover and precipitation as predictors. We show parameter estimates and their standard errors, and the Z values.
Fig 3.
GLM-estimated density of the European wildcat in the UTM 5x5 squares with presence predicted by the MaxEnt model.
Table 5.
Wildcat population estimations in Andalusia, and percentages of the population under spatial protection by national and natural parks (n: number of 5x5 km squares).