Animal Farm : An Analysis of Interspecies Interactions and Responses to Anthropogenic Influences at the UBC Farm

The most significant danger to animals around the world is the loss of their habitat, which is occurring due to the growth and expansion of the human population. The construction of new buildings such as the Brock Commons Residence at the University of British Columbia (UBC)are occurring near a mixed forest area can disrupt and fragment natural habitats, posing a threat to biodiversity for the local wildlife. This study seeks to evaluate the impact of human activities on animals and their habitats at the UBC Farm. To achieve this, we analyze camera trap data to investigate the spatial distribution of mammals and study the interactions between different species and behavioural trends through the changes in population. The primary aim of the research is to develop a more comprehensive understanding of how human actions affect animals in this particular area. Camera trap data has been collected since 2019. The camera trap data was sorted into different categories based on habitat and whether it was a market or non-market day. An occupancy model was then employed to make predictions about the likelihood of occurrence. Our findings revealed, coyotes were predominantly detected in the Annual Production Areas which is an area where human activities occur such as farming and market days, whereas squirrels and raccoons were more commonly found in the Mixed Forest Area. Furthermore, the study revealed that the interactions between coyotes and their prey were consistent across different habitats, however, there was no observable impact of human presence on mammal behaviour. Despite this outcome, our research findings indicate that mammal habitats are affected by human activities such as construction projects. The report puts forth several recommendations aimed at enhancing future research to produce definitive findings on mammal behaviour trends. These include facilitating access to the photo database to enable the use of machine learning algorithms for animal tagging, gathering covariate data on external factors that affect mammal behaviour, exploring the impact of noise pollution on mammal behaviour, and increasing the volume of data to improve detection rates for less frequently observed animals. To achieve these goals, the report suggests deploying additional camera traps, positioning them strategically, and extending their observation period. The study has the potential to enhance ecological and environmental sustainability at UBC, and hope that the insights gained can help shape development projects at UBC to minimize their impact on local biodiversity.Science, Faculty ofEarth, Ocean and Atmospheric Sciences, Department ofUnreviewedUndergraduat