## 2 Materials and Methods
### Human, Geographical, Climatological, and Vegetation Factors  
The counts of capture peaks for primary workers and for secondary workers were used as the dependent variables (DVs) in Poisson models fitted using the following independent variables (IVs):  
Human-dependent: number of beehives in the apiary, and population density; Climatological: directional albedo, aridity index, mean annual precipitation, mean annual precipitation seasonality, mean annual temperatures, mean annual temperatures seasonal  
Figure 3: Placement of the baited traps close to the entrance of the beehives.  
Figure 2: Examples of artisanal (**A**) and commercial (**B**) traps.  
ity, and average wind speed; Geographical: distance to the sea, distance to a main river, elevation, slope; Natural: normalised difference vegetation index (NDVI).  
The information about the number of beehives in the apiary was obtained directly from the beekeeper. The human population density expressed as residents/km\({}^{2}\) (year 2020) was obtained from the Gridded Population of the World, Version 4 [30]. The directional albedo quantifies the fraction of irradiance reflected by the surface of the Earth. The dataset used was obtained from Copernicus, is dimensionless and is defined as the \"integration of the bi-directional reflectance over the viewing hemisphere\" [31]. The Aridity Index indicates the relationship between precipitation and evapotranspiration, representing the water demand of vegetation, calculated on an annual basis. In this context, higher Aridity Index values correspond to more humid environments, while lower values indicate more arid conditions. In the dataset used [32], the values have been multiplied by 10,000 to enhance the precision without resorting to the use of decimal points.  
The mean annual precipitation (mm) dataset was obtained from [PERSON] and [PERSON] [33]. The mean annual precipitation seasonality is calculated as the ratio of the standard deviation to the mean. Therefore, higher seasonality indicates higher differences in minimums and maximums. The dataset was obtained from the same authors [33]. The mean annual temperature (\({}^{\circ}\)C/10) is defined as the mean of the maximum and minimum temperatures of the hottest and the coldest months of the year. The mean annual temperature seasonality is calculated as the standard deviation of mean annual temperatures multiplied by 100. Therefore, higher seasonality indicates higher differences between minimums and maximums. Both temperature datasets were obtained from [PERSON] and [PERSON] [33]. The average wind speed (m/s) is a scalar average defined as the mean of the wind magnitudes (speed), not considering the wind direction. The dataset used was developed by [PERSON] et al. [34].  
The distance to a main river dataset is available from the European Environment Agency [35]. Data are originally given in meters and was transformed to km. Elevation (m) is the altitude in relation to the sea level. The dataset was obtained from Copernicus [36]. The slope is defined as the steepness of the ground locally and is derived from the same dataset; the data are given in dN and were transformed to an angle measured in degrees through the equation degrees = arcsin (dN/250) \(\times\) 180/\(\pi\). The normalised difference vegetation index describes the contrast between visible and near-infrared reflectance of vegetation cover. The higher the index, the higher the vegetation cover. The dataset was obtained from Copernicus [37].  
The sampling points were geographically referenced and entered into a geographical information system. Different layers of information for the variables considered were used to extract the values observed in the sampled points. The information about the existence of transhumance and the number of beehives in the apiary was obtained from the beekeepers. Data were then exported for an Excel sheet for further analysis.  
The software used to collect these data was ArcGIS Pro version 3.2.1.