To manage animal populations, it is important to understand how many animals there are and where they are in the landscape. When considering a large area, such as the whole of Victoria, this can be a very difficult task, and counting every animal is not feasible. When a species is rare or hard to detect, this can be even more complicated.
To address these challenges, ARI researchers use population models to estimate the number of animals across large areas. They use carefully designed surveys to count animals through portions of the whole area of interest. Using these samples, researchers can then create statistical models that relate the animal counts to environmental factors that affect animal population numbers, such as climate, food and shelter. The resulting statistical models are then used to estimate animal numbers in areas that were not directly surveyed, allowing animal numbers to be assessed across large areas.
Another consideration is the difficulty of accurately counting the animals in the first place. For many reasons, such as dense bush or difficult terrain, it is unlikely all animals that are present in a survey area will be seen and counted. To overcome this, ARI researchers use a variety of methods to better assess the number of animals that are actually present, such as double observer counts or distance sampling.
researchers have implemented surveys using remote infrared cameras to record deer numbers at over 400 locations across the state. Researchers used distance markers, placed at various distances from the camera, to measure how far a deer was from the camera. This technique allowed for estimation of deer density at the camera location, instead of just counts of deer. The resulting data will be used to better assess the abundance and distribution of the major deer species across the state.
For more information, see this technical report (PDF).
Population modelling continues to be a critical part of wildlife management worldwide. Using the latest peer-reviewed methods, ARI can estimate population numbers to inform resource managers and measure confidence of model predictions.
This work has been funded by DEECA’s Biodiversity Division, and the New Zealand Department of Conservation.
For more information, contact David.ramsey@delwp.vic.gov.au.
Page last updated: 28/03/25