Animal populations are regulated by multiple factors, e.g. resource availability, diseases and predators. However, these factors can be significantly influenced by anthropogenic effects (e.g. biological invasions, mesopredator release) and either subserve populations or push them towards local extinction. The Hungarian meadow viper Vipera ursinii rakosiensis is an endangered reptile, with only a few surviving populations following recent alterations and fragmentation of their habitats. In Hungary, all documented populations are located within nature conservation areas. Significant practical conservation efforts have been made, including habitat reconstruction and development, as well as ex situ breeding and reintroductions. Nevertheless, the estimated overall population size of Hungarian meadow viper remains very low, and the impact of conservation interventions is practically immeasurable according to low densities. It is hypothesized that predation is the main factor interfering with conservation efforts of the vipers. Here, we analysed the diet of two mammalian predators (European badger and red fox) in a Hungarian meadow viper habitat. We found a high prevalence of viper remains in the processed faecal samples, indicating that a high number of individuals vipers are subject to predation even within a short period of time. We conclude that effective predator control might be necessary to increase the impact of standard conservation measures (e.g. habitat development, ex situ breeding and reintroduction) that target the restoration of Hungarian meadow viper populations.

1. 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. 2. Here we present a method that objectively characterises vegetation structure by using automated processing of images taken of the vegetation against a whiteboard under standardised conditions. We developed an R script for automatic calculation of four vegetation structure variables derived from raster data stored in the images: leaf area (LA), height of closed vegetation (HCV), maximum height of vegetation (MHC), and foliage height diversity (FHD). 3. We demonstrate the applicability of this method by testing the influence of vegetation structure on the occurrence of three viperid snakes in three grassland ecosystems: Vipera graeca in mountain meadows in Albania, V. renardi in loess steppes in Ukraine and V. ursinii in sand grasslands in Hungary. 4. We found that the variables followed normal distribution and there was minimal correlation between those. 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 FHD in V. renardi, and to HCV in V. ursinii. 5. Our results demonstrate that biologically meaningful vegetation structure variables can be derived from automated image processing. 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.