Increasing disease outbreaks and declining biodiversity underscore the need for understanding the impact pathogens have on wildlife populations. To understand how zoonoses impact wild animal welfare, we created a severity index. Using signs of disease information from a bacterial zoonotic disease database, we quantified severity of each sign of disease combined with the number of welfare domains and body systems the pathogen impacts to find the severity index value (SIV) of each unique host-pathogen relationship. We then investigated the effects of host-pathogen richness and conservation status against SIV. We found there to be a strong, negative correlation between increasing pathogen richness and SIV. Species of least concern (LC) were not significantly more likely to have higher SIV than species of conservation concern (CC), but CC species did not have a significant decline of SIV with increasing pathogen richness. This study provides an insight into the relationships between pathogen richness and the risk of pathogen infections to wildlife.

The Autonomous Navigation System (ANS) constitutes a critical key enabling technology required for operating Maritime Autonomous Surface Ships (MASS). To assure the safety of MASS operations, the effective identification of potential objects and target ships interacting with the own MASS is quintessential. This study proposes a systematic method to identify the items interacting with the own MASS. This method is based on a similar approach previously employed for the encountering items’ identification in robotics, which is customised herein for the MASS needs. The developed method is applied to a short-sea shipping MASS. The environmental features, agents and objects related to her navigation are identified and ranked based on the frequency of encounter and the potential collision consequences. The results demonstrate the ability of the method to identify additional items in comparison to Automatic Identification System based data. The interactions with the small ships are considered as the most critical, due to their potential accidental consequences and their exhibited high frequency of encounter. This study results are employed to support the ANS design and testing of the investigated ship.