2.2 Study area and species distribution data
The study area comprises approximately 31 200 km2 in the southeast part of Poland, which extends from latitude 50.2° to 49°N and longitude from 19° to 23°E (Figure 1). This area is diversified due to environmental conditions mostly shaped by the altitude ranging from 160 to 2503 m a.s.l. Additional factors underlying diversity are correlated with climate, land use systems, land relief, and human population density. In the northern part, the lowland areas are used for agriculture and the foothills are dominated by forests, and the southern part has high mountains with alpine vegetation. In addition to the north–south altitudinal gradient, there is also a climatic gradient of continentality, with higher temperature range in the eastern part of the study region (Szabo-Takacs, Farda, Zahradníček, & Štěpánek, 2015) which, in the studied region, correlated strongly with decreasing eastward precipitation (Appendix, Tab S.3.). The study area includes a densely populated industrial landscape (Silesia), urban agglomerations (largest city Kraków), and moderately populated agricultural areas, as well as sparsely populated areas in the mountains. The detailed characteristics of the study area (climate, topography, land use structure, and human population density) were previously described by Szymura et al. (2018).
FIGURE 1 The study region location (green) on a background of land relief (a), and distribution of communication network and settlements on the background of altitude within the study region (b).
The data on distribution of the studied Solidago species were obtained from the atlas Distribution of Kenophytes in the Polish Carpathians and their Foreland (Zając & Zając, 2015), which shows maps of species presence or absence in a 2 × 2 km grid in the Polish part of the Carpathian Mountains and their foreland, Central Europe. The fieldwork designed for the purpose of compiling the atlas was based on a survey of flora in particular regions (e.g., mountain ranges, particular towns and surrounding areas) and exploration focused exclusively on neophytes in given regions. These observations were supplemented with additional data from phytosociological relevés, herbarium records, and published materials. The fieldwork was carried out by several dozen professional botanists as well as graduate students, focusing on a predefined 2 × 2 km grid for sampling (Zając A., personal information). This work represents a ‘survey’ type of data, according to Elith et al. (2020) nomenclature. Such data, with true absence records, enable species distribution models to be less biased and to perform better, compared with presence-only records, the ‘collection’ data type (Barbet-Massin et al., 2012; Elith et al., 2020). This distinction is of particular importance for examination of wide-ranging and tolerant species (Brotons, Thuiller, Araújo, & Hirzel, 2004). To reduce the possible effect of lower sampling effort in some regions (Bailey, Boyd, Hjort, Lavers, & Field, 2017; Yang, Ma, & Kreft, 2013), the potentially undersampled squares were excluded from modelling. For this purpose, we used a ‘target group approach’ (Chapman, Pescott, Roy, & Tanner, 2019; Phillips et al., 2009) and a previously established model which explains neophyte richness (the ‘target group’ in this case) as a function of environmental and socio-economic variables in the studied region (Szymura et al., 2018). We assumed that the squares with the highest negative model residuals (i.e., squares where recorded neophyte richness was much lower than predicted by the model) indicated potentially undersampled regions. After preliminary testing, we decided to exclude from modelling 25% of squares (1950 squares) with the highest negative residual values and simultaneously without any invasiveSolidago records (for details of this calculation see Appendix 1).