# Activity May Not Reflect the Numbers: An Assessment of Capture Rate and Population Density of Dingoes ( Canis familiaris ) Within Landscape‐Scale Cell‐Fencing

## TL;DR

This study shows that camera trap activity metrics may not accurately reflect dingo population sizes, which is important for managing dingo control programs in Australia.

## Contribution

The study experimentally demonstrates that camera trap capture rates are unreliable for assessing dingo population size variations.

## Key findings

- Dingo activity correlated with estimated density at only two of six study sites.
- Annual dingo density estimates were below sustainable thresholds at one site in the first year but higher in the second year.
- Fence level and prey occurrence significantly influenced dingo activity.

## Abstract

Most human‐carnivore conflicts arise from the impact of predation on livestock. In Australian rangelands, considerable resources are allocated to constructing exclusion fences and implementing control measures to manage dingo populations for sustainable livestock enterprise. Assessing the effectiveness of these measures is crucial for justifying the investment. We used a replicated experimental design to examine the effect of landscape‐scale dingo‐proof exclusion fences (‘cell‐fencing’) on activity and population density of dingoes in the Southern Rangelands of Western Australia. We monitored dingo populations for 22–24 months across six study sites nested within a landscape of about 75,000 km2 and defined ‘fence level’ as the number of dingo‐proof fences enclosing each study site. We used camera trap capture rate (number of independent capture events per 100 trap nights) as a metric for dingo activity (including the availability of resources as other potential covariates), estimated dingo density using spatially explicit mark‐resight models, and tested the relationship between capture rate and estimated density of dingoes for each study site. Significant variation in both metrics was observed between sites and across time. Fence level and prey occurrence significantly influenced dingo activity. The annual mean dingo density estimate across study sites was below two dingoes per 100 km2 (i.e., 0.02 dingoes per km2; the maximum value believed to be compatible with small livestock) at only one study site in the first year, but it was higher across all sites during the second year of monitoring. Dingo activity correlated with estimated dingo density at only two sites, suggesting differences in dingo behaviour and detection across the six study sites. This study provides experimental evidence that camera trap capture rate is not a reliable method for assessing variations in the population size of dingoes. These results have implications for monitoring outcomes of dingo control programs across Australia.

This study addresses a critical question: How reliable is the activity metric (here we used camera trap capture rate) to assess variations in population size of dingoes across diverse habitats in Australia? Through experimental evidence, we demonstrate that activity metrics can lead to inaccuracies in assessing changes in dingo population size. Our findings highlight the need to assess dingo population size from identified individuals, which is particularly relevant for effective dingo control programs across Australia.