182 T. O. W. Kamgaing et al.


FIG. 1 The study area in Nki National Park, south-east Cameroon, with the location of villages, and transects (T1–4) established for monitoring the disappearance of the dung of blue duiker Philantomba monticola and red duikers Cephalophus spp.


observed dung beetles removing fresh pellets completely within a few hours of detection and therefore when fresh dung disappeared within a day, we considered beetles had removed them. In contrast, decomposition was gradual. Rainfall can wash away dung, but we could distinguish this from removal by beetles. When a dung pile disappeared rapidly, we checked whether it had been covered by fallen leaves, recording ‘leaf cover’ if this was the case. Cover by fallen leaves will affect density estimation in the same way as removal by beetles, as such dung is unlikely to be recorded during a dung survey. Inspecting dung piles twice daily allowed us to record


survival time with precision. To facilitate this monitoring, we camped near the paths for c. 8 days at a time, with 3–4 day breaks between surveys. In total, individual dung piles were visited 2–34 times, in contrast to retrospective surveys, in which animal signs are marked and revisited once to record whether they have disappeared or not (Laing et al., 2003). A dung pile was categorized as disappeared when it was no longer recognizable as a dung pellet group (Marques et al., 2001; van Vliet et al., 2009). We determined the main factor causing each dung pile to disappear by examining the dung remnants or the spot where each dung pile was dropped and, when necessary, by comparing these observations with photographs of the pellets taken at each visit.


Data analysis


As there were 3-to 4-day intervals between each 8-day sur- vey, we occasionallymissed the exact date when some dung piles disappeared, but knew the two dates between which they disappeared. In these cases, we used the mid point of


the two dates for calculating the survival time. The impact of these mid-point data on the variance of survival time es- timates is probably negligible because such data comprised only 7% of the observations and because of the short inter- vals between observations (Bogaerts et al., 2018, chapter 4). To visualize the relationship between the estimate of


dung survival time and age class at detection, we categorized dung piles into four overlapping age classes at detection: 0–3 hours, 0–6, 0–12 and 0–24. To evaluate any effect of age at detection, we fitted a generalized linear model (GLM) to dung survival time with absolute age at detection as the single explanatory variable. Mid-point data were excluded from this analysis. Because age at detection had a significant effect on survival time estimates, we discarded dung piles detected at an older age (i.e. dung piles that were not fresh upon detection) before further analysis. In addition, we dis- carded the top 0–4%of outliers that did not decay for longer periods (in total, five dung piles of the blue duiker and eight of red duikers), to avoid a substantial decrease in the preci- sion of mean survival time estimates but maintain accuracy (Viquerat et al., 2013). We then calculated mean dung survival time for each


season using two approaches: a GLM including only season as the explanatory variable, and simple arithmetic means. Mid-point data were excluded from calculation of arith- metic means but included for the analysis using a GLM. To evaluate the effect of season, the main factor causing


dung disappearance and dung pile diameter (the latter log10 transformed) on dung survival time, we fitted GLMs with a gamma error distribution and log-link function as the response variable (survival time) was non-negative. Spatial autocorrelation of factors causing disappearance, in parti- cular of beetle attack, on neighbouring dung was probably


Oryx, 2023, 57(2), 180–187 © The Author(s), 2022. Published by Cambridge University Press on behalf of Fauna & Flora International doi:10.1017/S0030605321001599


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