The red fox ( Vulpes vulpes ) is a major invasive predator in Australia, and camera traps are increasingly used to monitor it and evaluate control programs. These devices generate large datasets, but turning them into abundance estimates requires statistical and programming skills that many land managers lack. Detection data are therefore often reduced to naïve counts that ignore detection probability. We developed FoxWatch, a Shiny R application that estimates fox abundance with Simultaneous‐Count Models through a guided point‐and‐click interface. It sorts detection records into 10‐day blocks and fits the model by Markov Chain Monte Carlo sampling, returning abundance estimates with quantified uncertainty. We tested FoxWatch on 5 years of data from 35 camera traps at Oolambeyan National Park, Australia. It processed the dataset in under 5 minutes, versus 2–3 hours by hand. FoxWatch lowers the analytical barrier so practitioners without programming skills can assess fox abundance and support predator management.
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Dissanayake et al. (2026) studied this question.
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