2.2. Study design
We selected 189 points using a random sampling method (minimum distance
between points was 473 m; Fig. 1), stratified according to the main
three land-uses: agricultural, n = 86; forest, n = 50; and urban = 53.
To characterise the landscape around each point, we considered
composition and configuration variables within a buffer of 500 m radius.
Composition was expressed as the percentage cover of seven categories of
land-use (Carta de Ocupação do Solo maps available for Portugal; IGP,
2020) that were a priori considered as potentially relevant to
bird distributions within different (decreasing) levels of human
disturbance: i) urban and industrial, ii) intensive agriculture, iii)
rice-fields, iv) extensive agriculture, v) shrubland, vi) plantation
forest, and vii) native forest (e.g. montado). Landscape configuration
was calculated using the Shannon-Weiner diversity index of the seven
land use categories (SHDI). Landscape composition and configuration
variables were calculated using QGIS 3.26.3-Buenos Aires andlandscapemetrics R package (Hesselbarth et al., 2019). We scaled
all landscape variables to better evaluate collinearity (Cade, 2015),
testing for multicollinearity through the Spearman correlation
coefficient. We retained all variables since Spearman’s Rho was lower
than 0.63 in all cases (Dormann et al., 2013). For a more detailed
description, see Supporting Information 1.