Zachary Amir

I am a quantitative wildlife ecologist who uses and develops novel statistical methods coupled with research computing to understand species interactions and how wildlife communities are impacted by a wide range of contemporary disturbances. I am currently a Principal Data Scientist working on developing the Wildlife Observatory of Australia (WildObs) that aims to bring together siloed camera trap data into a user-friendly continental database. I recently completed my PhD in wildlife ecology and conservation at the University of Queensland in the Ecological Cascades Lab where I studied food web dynamics among Southeast Asian tropical forest vertebrates. Before moving to Australia, I worked towards the conservation of several different threatend reptile and amphibian species in the USA. When I am not stuck behind my computer, you can find me outdoors looking for wildlife, biking, hiking, camping, and surfing. Quantitative wildlife ecology, statistical methods, research computing, species interactions, wildlife communities, contemporary disturbances, food web dynamics, Southeast Asian tropical forest vertebrates, conservation of threatened reptile and amphibian species

[2026] Integrated modelling reveals widespread distribution of invasive wild pigs across Australia. Rees, Matthew W., Mitchell, David J., Ng, Katherina, Parsons, Sandra K., Proft, Kirstin M., Foster, Scott D., Peel, David, Amir, Zachary, Bruce, Tom, Luskin, Matthew S. and Froese, Jens G. (2026). Integrated modelling reveals widespread distribution of invasive wild pigs across Australia. Biological Conservation, 320 111917. doi: 10.1016/j.biocon.2026.111917 [2026] AI and computer vision for wildlife identification in camera trap images: fine-tuning SpeciesNet outperforms local models for species classification. Rajmohan, Prakash Palanivelu, Sharma, Renuka, Amir, Zachary, Bruce, Tom, Brook, Barry W., Morris, Dan and Luskin, Matthew Scott (2026). AI and computer vision for wildlife identifica