Microhabitat selection of meadow and steppe vipers enlightened by digital photography and image processing to describe grassland vegetation structure

• Published in: Journal of zoology (1987) 2024-02, Vol.322 (2), p.168-178
• Main Authors: Mizsei, E., Budai, M., Rák, G., Bancsik, B., Radovics, D., Szabolcs, M., Móré, A., Vadász, C., Dudás, G., Lengyel, S.
• Format: Article
• Language: English
• Subjects: Aggregation; Automation; Biodiversity; biodiversity monitoring; Digital imaging; Ecological distribution; Ecosystems; Foliage; Grasslands; habitat diversity; Habitat selection; Habitats; Height; Image processing; Leaf area; Loess; Meadows; Microenvironments; Microhabitat; Microhabitats; parallel photography method; Photography; reptile; Risk reduction; Snakes; Statistical models; Steppes; Vegetation; Viperidae; visual obstruction reading; Wildlife conservation
• ISSN: 0952-8369; 1469-7998
• DOI: 10.1111/jzo.13129

Understanding animals' selection of microhabitats is important in both ecology and biodiversity conservation. However, there is no generally accepted methodology for the characterization of microhabitats, especially for vegetation structure. We studied microhabitat selection of three 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 standardized 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 (MHV) 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 MHV in V. ursinii, and negatively to HCV in V. ursinii. Our results demonstrate that vegetation structure variables derived from automated image processing significantly relate to viper microhabitat selection. Our method minimizes the risk of subjectivity in measuring vegetation structure, enables the aggregation of adjacent pixel data and is suitable for comparison of or extrapolation across different vegetation types or ecosystems. This study assesses microhabitat selection by Vipera snakes, focusing on grassland ecosystems where the endangered V. ursinii complex species are found. The researchers employed a novel method involving photographs of vegetation against a whiteboard for objective analysis of habitat characteristics. They found that specific vegetation structure variables influenced the occurrence of these grassland specialist vipers and highlight the method's objectivity and applicability for similar studies across species and ecosystems.