Dataset Understanding animals’ selection of microhabitats is important in both ecology and biodiversity conservation. However, there is no generally accepted methodology for the characterisation of microhabitats, especially for vegetation structure. We studied microhabitat selection of Vipera snakes by comparing grassland vegetation structure between viper occurrence points and random points in three grassland ecosystems: V. graeca in mountain meadows of Albania, V. renardi in loess steppes of Ukraine, and V. ursinii in sand grasslands in Hungary. We quantified vegetation structure in an objective manner by automated processing of images taken of the vegetation against a vegetation profile board under standardised conditions. We developed an R script for automatic calculation of four vegetation structure variables derived from raster data obtained in the images: leaf area (LA), height of closed vegetation (HCV), maximum height of vegetation (MHC), and foliage height diversity (FHD). Generalized linear mixed models revealed that snake occurrence was positively related to HCV in V. graeca, to LA in V. renardi and to LA and MHC in V. ursinii, and negatively to to HCV in V. ursinii. Our results demonstrate that vegetation structure variables derived from automated image processing significantly influence viper microhabitat selection. Our method minimises the risk of subjectivity in measuring vegetation structure, allows upscaling if neighbouring pixels are combined, and is suitable for comparison of or extrapolation across different grasslands, vegetation types or ecosystems.

Dataset Understanding animals’ selection of microhabitats is important in both ecology and biodiversity conservation. However, there is no generally accepted methodology for the characterisation of microhabitats, especially for vegetation structure. We studied microhabitat selection of Vipera snakes by comparing grassland vegetation structure between viper occurrence points and random points in three grassland ecosystems: V. graeca in mountain meadows of Albania, V. renardi in loess steppes of Ukraine, and V. ursinii in sand grasslands in Hungary. We quantified vegetation structure in an objective manner by automated processing of images taken of the vegetation against a vegetation profile board under standardised conditions. We developed an R script for automatic calculation of four vegetation structure variables derived from raster data obtained in the images: leaf area (LA), height of closed vegetation (HCV), maximum height of vegetation (MHC), and foliage height diversity (FHD). Generalized linear mixed models revealed that snake occurrence was positively related to HCV in V. graeca, to LA in V. renardi and to LA and MHC in V. ursinii, and negatively to to HCV in V. ursinii. Our results demonstrate that vegetation structure variables derived from automated image processing significantly influence viper microhabitat selection. Our method minimises the risk of subjectivity in measuring vegetation structure, allows upscaling if neighbouring pixels are combined, and is suitable for comparison of or extrapolation across different grasslands, vegetation types or ecosystems.

Dataset Understanding animals’ selection of microhabitats is important in both ecology and biodiversity conservation. However, there is no generally accepted methodology for the characterisation of microhabitats, especially for vegetation structure. We studied microhabitat selection of Vipera snakes by comparing grassland vegetation structure between viper occurrence points and random points in three grassland ecosystems: V. graeca in mountain meadows of Albania, V. renardi in loess steppes of Ukraine, and V. ursinii in sand grasslands in Hungary. We quantified vegetation structure in an objective manner by automated processing of images taken of the vegetation against a vegetation profile board under standardised conditions. We developed an R script for automatic calculation of four vegetation structure variables derived from raster data obtained in the images: leaf area (LA), height of closed vegetation (HCV), maximum height of vegetation (MHC), and foliage height diversity (FHD). Generalized linear mixed models revealed that snake occurrence was positively related to HCV in V. graeca, to LA in V. renardi and to LA and MHC in V. ursinii, and negatively to to HCV in V. ursinii. Our results demonstrate that vegetation structure variables derived from automated image processing significantly influence viper microhabitat selection. Our method minimises the risk of subjectivity in measuring vegetation structure, allows upscaling if neighbouring pixels are combined, and is suitable for comparison of or extrapolation across different grasslands, vegetation types or ecosystems.