FigurecaptionsFigure1Mapofthetopographicwetnessindex.pptVIP

Figure captions Figure 1 Map of the topographic wetness index calculated using the FD8 (multiple flow direction) algorithm. The inset shows the location of the study area in Western Europe. Figure 2 Occurrence frequency of the four passerine species, all species (4-species), and all species but the Whinchat (3-species) observed in 64 transects. Figure 3 Probability of presence for the Whinchat and the 3-species (Yellow wagtail, Corn bunting and Reed bunting) represented as a logistic function of topographic wetness index. The TWI setting used here are D8 algorithm and 250m DEM. Table 1 Corrected Akaike information criterion (AICc) and Aka?ke weight (w) values for logistic regressions between the occurrence of either individual bird species or the 3-species combination (Yellow wagtail, Corn bunting, Reed bunting) and topographic wetness indices including eigenvectors. We used four algorithms (D8, FD8, MD∞, SWI) and two resolutions (250m and 50m pixel). AICc1 correspond to the null model with spatial eigenvectors and AICc2 to the model with spatial eigenvectors including TWI. Bold values are used to indicate DAICc larger than 2. w1 is the weight of the null model and w2 the weight of the model including TWI. AUC (Area Under the Curve) and coefficient and standard error are indicated for candidate models selected by AIC. Whinchat AICc1 AICc2 DAICc(1-2) w1 w2 AUC Coef +-SE 250 m D8 81.83 70.03 11.80 0.00 1.00 0.82 1.78 0.56 FD8 81.83 71.84 9.99 0.01 0.99 0.81 1.76 0.57 MD∞ 81.83 70.26 11.57 0.00 1.00 0.82 1.86 0.59 SWI 81.83 75.98 5.85 0.05 0.95 0.79 1.59 0.69 50 m D8 81.83 72.56 9.27 0.01 0.99 0.81 1.76 0.59 FD8 81.83 73.92 7.91 0.02 0.98 0.80 1.95 0.69 MD∞ 81.83 72.75 9.08 0.01 0.99 0.81 1.78 0.60 SWI 81.83 80.84 0.99 0.38 0.62 Yellow Wagtail 250 m D8 83.77 82.82 0.95 0.38 0.62 FD8 83.77 82.00 1.77 0.29 0.71 MD∞ 83.77 83.16 0.61 0.42 0.58 SWI 83.77 83.76 0.01 0.50 0.50 50 m D8 83.77 85.37 -1.60 0.69 0.31 FD8 83.77 85.73 -1.96 0.73 0.27 MD∞ 83.7