“…Use of machine learning (Tabak et al, 2019) and citizen science (Swanson et al, 2015), or combinations of the two (Green et al, 2020;Willi et al, 2019), is reducing the time required for tagging images and data analysis is becoming simpler with packages like CamtrapR (Niedballa et al, 2016) providing full image to analysis workflows. Camera traps have already been used to answer questions about animals foraging on anthropogenic sources, providing data on the species (Abrahams et al, 2018;Findlay, 2016), numbers, identity, age, and sex distribution of foraging animals (Ranjeewa et al, 2015;Smit et al, 2019), as well as the effectiveness of deterrents (Branco et al, 2019;Findlay & Hill, 2021b;Ngama et al, 2018;Pozo et al, 2019;Ranjeewa et al, 2015), and the diurnal (Findlay & Hill, 2021a;Ranjeewa et al, 2015;Smit et al, 2019;Zak & Riley, 2017) and seasonal timings of crop-foraging (Zak & Riley, 2017). However, where camera traps have been used to assess crop-foraging in the past, what they can and cannot measure is often assumed.…”