No abstract

Road vehicle collisions are likely to be an important contributory factor in the decline of the European hedgehog (Erinaceus europaeus) in Britain. Here, a collaborative roadkill dataset collected from multiple projects across Britain was used to assess when, where and why hedgehog roadkill are more likely to occur. Seasonal trends were assessed using a Generalized Additive Model. There were few casualties in winter—the hibernation season for hedgehogs—with a gradual increase from February that reached a peak in July before declining thereafter. A sequential multi-level Habitat Suitability Modelling (HSM) framework was then used to identify areas showing a high probability of hedgehog roadkill occurrence throughout the entire British road network (∼400,000 km) based on multi-scale environmental determinants. The HSM predicted that grassland and urban habitat coverage were important in predicting the probability of roadkill at a national scale. Probabilities peaked at approximately 50% urban cover at a one km scale and increased linearly with grassland cover (improved and rough grassland). Areas predicted to experience high probabilities of hedgehog roadkill occurrence were therefore in urban and suburban environments, that is, where a mix of urban and grassland habitats occur. These areas covered 9% of the total British road network. In combination with information on the frequency with which particular locations have hedgehog road casualties, the framework can help to identify priority areas for mitigation measures.

No abstract

Sex identification of adult cetaceans is an important ecological parameter that should be incorporated into studies such as population dynamics and animal behavior. In Cuvier’s beaked whale ( Ziphius cavirostris ), sex determination may be achieved through genetics, observation of genitals, the presence/absence of erupted teeth, and calf association. However, these features are difficult to ascertain due to the shy behavior of this species. Therefore, this study aimed to create a robust sex identification method using only external characteristics. Particularly, this work analyzed pigmentation patterns and levels of natural marks from adult individuals of known sex in order to identify gender differences, using frequency analysis and generalized linear models. Photographic captures of 73 free-ranging animals were utilized. The frequencies of the individual pigmentation patterns were found to be sex dependent. The 63% of the animals could be classified into either a “soft” or “sharp” pigmentation cluster. The “soft” cluster was only displayed by females, while the “sharp” cluster was present in both the sexes. However, the model selection process indicated that natural marking is the best determinative factor for sex classification. The density of the visible intraspecific natural marks was found to differ between the sexes ( P value < 0.001) and was incorporated as a predictor variable into several candidate models. All candidate models had a high predictive power (mean area under the curve 0.973) and correctly predicted the sex, by means of a density threshold value, in 85–90% of the analyzed animals. The density threshold ranged from 4.1% to 6.4% according to the different body area analyzed. These density threshold values represent a robust post hoc sexing method to classify individuals to sex from opportunistic photos in the absence of other sexing methods.