Rapid dung removal by beetles suggests higher duiker densities in Central African rainforests TOWA OLIVI ER WILLIAM KAMGAING,ZEU N ’ S CÉLESTI N B RICE DZEF ACK


NAGO CHARL EIN E BLONDÈL E DONGMO,MAT U R I N TC HATAT andHIROKAZU YASUOKA


Abstract For many mammal species, converting dung density into population density requires accurate estimates of defaecation rate and dung survival time. The latter pa- rameter probably varies seasonally. In Nki National Park, south-east Cameroon, we monitored 216 dung piles of the blue duiker Philantomba monticola and 373 of the red duiker group (Cephalophus spp.), major game animals in Central Africa, and estimated dung survival time across seasons. Mean survival time was 6.83 days in the major dry season and 1.21–1.81 in other seasons for the blue duiker, and 7.37 and 1.53–4.05 for red duikers, lower than the values conven- tionally used for density estimations in Central Africa (i.e. 18 days for the blue duiker and 21 days for red duikers). Overall, beetles removed half of the dung within 1 day of deposition. However, the proportion of dung piles that beetles removed was significantly lower in the major dry season, and other dung piles remained longer until they disappeared as a re- sult of other factors. As shorter dung survival time results in higher estimates of population density, our findings imply that in forests with intense beetle activity, duiker densities are higher than those based on the conventional values of dung survival time. Duiker densities and dung sur- vival time should be estimated simultaneously. To minimize the bias introduced by rapid removal of fresh dung by beetles, only fresh dung (,3 hours old) should be moni- tored when estimating mean dung survival time.


Keywords Bushmeat hunting, Cameroon, density estima- tion, duiker, dung decay, dung survival time, Nki National Park, wildlife management


Introduction


poachers and bushmeat traders (Robinson et al., 1999). Forest dwellers engage in the bushmeat trade to a greater or lesser extent (Yasuoka, 2006; Martin et al., 2020), and the depletion of wildlife populations and declining food supplies threaten people’s livelihoods and have resulted in the bushmeat trade becoming a global concern (Wilkie & Carpenter, 1999; Fa et al., 2002; van Vliet & Nasi, 2008; Ichikawa, 2014; Yasuoka et al., 2015). Against this background, conflicts have arisen between


T TOWA OLIVIER WILLIAM KAMGAING (Corresponding author, orcid.org/0000-


0002-5653-9019, kamgaing@jambo.africa.kyoto-u.ac.jp)and HIROKAZU YASUOKA (


orcid.org/0000-0001-5066-1534) Center for African Area Studies, Kyoto


University, 46 Yoshida-Shimoadachi, Sakyo, Kyoto, 606-8501, Japan ZEUN’S CÉLESTIN BRICE DZEFACK University of Dschang, Dschang, Cameroon


NAGO CHARLEINE BLONDÈLE DONGMO Centre Régional d’Enseignement Spécialisé en Agriculture Forêt-Bois, Yaoundé, Cameroon


MATURIN TCHATAT Institute for Agricutural Research and Development, Yaoundé, Cameroon


Received 23 February 2021. Revision requested 2 July 2021. Accepted 29 October 2021. First published online 18 March 2022.


local people and conservationists (Pyhälä et al., 2016). One of the reasons for these conflicts is the lack of reliable, and the sometimes controversial, information on the abundance of wild animals, including duikers, the major game animals in Central Africa (van Vliet & Nasi, 2008; Elenga et al., 2020). Estimated population densities of game species may differ by 10-fold or more depending on the survey methods used (Koster & Hart, 1988; Wilkie & Finn, 1990; Jost Robinson et al., 2017; Kamgaing et al., 2018). Management decisions based on unrealistic estimates could lead to unnecessary conflicts, and it is therefore essential that conservation agencies share accurate infor- mation with local people. In dense tropical forests, wildlife surveys are usually challenging because of poor visibility and the shyness of wild animals (Elenga et al., 2020). Therefore, rather than attempting to quantify numbers directly, indirect survey techniques such as counts of animal signs (e.g. dung piles of ungulates or nests of primates) are used (White & Edwards, 2000). Dung survey is the most frequently used method to estimate the population density of forest duikers. Of 65 published duiker densities in Central Africa, 33 were based on dung surveys (Supplementary Table 1), including in the Democratic Republic of the Congo (Koster & Hart, 1988; Wilkie & Finn, 1990), Cameroon (Payne, 1992; Ekobo, 1998; Yasuoka, 2006; Bobo et al., 2014; Nzooh-Dongmo et al., 2016; Kamgaing et al., 2018), Gabon (Koerner et al., 2017) and the Republic of the Congo (Breuer et al., 2021). To estimate animal density based on dung survey,


accurate values of dung density, defaecation rate and mean dung decay time are required. The number of animals in a given area is the number of observed dung piles divided by the number of dung piles that an individual defaecates


This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. 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


he expansion of the logging road network in West and Central Africa has facilitated access to forest for


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76  |  Page 77  |  Page 78  |  Page 79  |  Page 80  |  Page 81  |  Page 82  |  Page 83  |  Page 84  |  Page 85  |  Page 86  |  Page 87  |  Page 88  |  Page 89  |  Page 90  |  Page 91  |  Page 92  |  Page 93  |  Page 94  |  Page 95  |  Page 96  |  Page 97  |  Page 98  |  Page 99  |  Page 100  |  Page 101  |  Page 102  |  Page 103  |  Page 104  |  Page 105  |  Page 106  |  Page 107  |  Page 108  |  Page 109  |  Page 110  |  Page 111  |  Page 112  |  Page 113  |  Page 114  |  Page 115  |  Page 116  |  Page 117  |  Page 118  |  Page 119  |  Page 120  |  Page 121  |  Page 122  |  Page 123  |  Page 124  |  Page 125  |  Page 126  |  Page 127  |  Page 128  |  Page 129  |  Page 130  |  Page 131  |  Page 132  |  Page 133  |  Page 134  |  Page 135  |  Page 136  |  Page 137  |  Page 138  |  Page 139  |  Page 140