Seasonal space-use and resource limitation in free-ranging black rhino
The spatio-temporal distribution of forage and surface water shapes space-use for many herbivore species. Herbivores must make trade-offs between critical resources such as water and forage under resource-limited conditions. The species-specific strategy employed to do so, however, varies with nutritional requirements, thermoregulation and body size. The black rhinoceros (Diceros bicornis (Linnaeus, 1758)) is a browsing megaherbivore that requires upwards of 50kgs of forage per day and is considered water-dependant. Contrasting evidence regarding surface water dependence and forage selectivity in black rhino, however, makes it unclear which exerts the primary influence on space-use under resource-limited conditions. We used telemetry data to calculate and compare seasonal home range sizes, utilisation overlap and site fidelity for black rhino in the Kruger National Park, South Africa, and use the results to infer the primary limiting resource in a semi-arid savanna ecosystem. Our findings demonstrate seasonal differences in space-use by black rhino, both in home range size and utilisation. Smaller home ranges and higher site fidelity in the dry season suggest that surface water is the primary resource driving these differences, i.e. black rhino restrict their range rather than expand it under resource-limited conditions. This has management implications for understanding the limitations of black rhino re-introduction programmes and the population capacity of small reserves.
KeywordsHome range Animal movement Telemetry Herbivore ecology Wildlife tracking
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- Anderson, T.M., Ngoti, P.M., Nzunda, M.L., Griffith, D.M., Speed, J.D.M., Fossøy, F., Røskaft, E., Graae, B.J., 2018. The burning question: does fire affect habitat selection and forage preference of the black rhinoceros Diceros bicornis in East African savannahs? Oryx, https://doi.org/10.1017/S0030605318000388.Google Scholar
- Atkinson, S., 1995. Maintenance of Captive Black Rhinoceros (Diceros bicornis) on Indigenous Browse in Zimbabwe: Energetics, Nutrition and Implications for Conservation. University of Zimbabwe.Google Scholar
- Barton, K., 2018. MuMIn: Multi-Model Inference.Google Scholar
- Bates, D., Mächler, M., Bolker, B.M., Walker, S.C., 2015. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, https://doi.org/10.18637/jss.v067.i01.
- Bhattacharyya, A., 1943. On a measure of divergence between two statistical populations defined by their probability distributions. Bull. Calcutta Math. Soc. 35, 99–109.Google Scholar
- Bolker, B.M., Brooks, M.E., Clark, C.J., Geange, S.W., Poulsen, J.R., Stevens, M.H.H., White, J.S.S., 2009. Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol. Evol. 24, 127–135, https://doi.org/10.1016/j.tree.2008.10.008.PubMedCrossRefPubMedCentralGoogle Scholar
- Börger, L, Franconi, N., De Michele, G., Gantz, A., Meschi, F., Manica, A., Lovari, S., Coulson, T., 2006. Effects of sampling regime on the mean and variance of home range size estimates. J. Anim. Ecol. 75, 1393–1405, https://doi.org/10.1111/j.1365-2656.2006.01164.x.PubMedCrossRefPubMedCentralGoogle Scholar
- Bucini, G., Saatchi, S., Hanan, N., Boone, R.B., Smit, I., 2009. Woody cover and heterogeneity in the savannas of the Kruger National Park, South Africa. IEEE International Geoscience and Remote Sensing Symposium, 334–337.Google Scholar
- Cromsigt, J.P.G.M., 2006. Large Herbivores in Space: Resource Partitioning Among Savanna Grazers in a Heterogeneous Environment. University of Groningen.Google Scholar
- Emslie, R.H., Adcock, K., 2013. Diceros bicornis, black rhinoceros. In: Kingdon, J., Hoffmann, M. (Eds.), Mammals of Africa, Volume V: Carnivores, Pangolins, Equids and Rhinoceroses. Bloomsbury Publishing, London, pp. 455–466.Google Scholar
- Hitchins, P.M., 1969. Influence of vegetation types on sizes of home ranges of black rhinoceros in Hluhluwe Game Reserve, Zululand. Lammergeyer 10, 81–86.Google Scholar
- Hitchins, P.M., Anderson, J.L., 1983. Reproduction, population characteristics and management of the black rhinoceros Diceros bicomis minor in the Hluhluwe/Comdor/Umfolozi Game Reserve Complex. S. Afr.J. Wildl. Res. 13, 78–85.Google Scholar
- Iason, G., van Wieren, S.E., 1999. Digestive and ingestive adaptations of mammalian herbivores to low-quality forage. In: Olff, H., Brown, V.K., Drent, R.H. (Eds.), Herbivores: Between Plants and Predators. Blackwell Science Ltd., Oxford, pp. 337–370, https://doi.org/10.1046/j.1365-2664.1999.00459-6.x.Google Scholar
- Joubert, E., 1971. Notes on the ecology and behaviour of the black rhinoceros Diceros bicornis Linn. 1758 in South West Africa. Madoqua 1, 5–53.Google Scholar
- Mukinya, J.G., 1977. Feeding and drinking habits of the black rhinoceros in Masai Mara game Reserve. Afr. J. Ecol. 15, 125–138, https://doi.org/10.1111/j.1365-2028.1977.tb00386.x.CrossRefGoogle Scholar
- R Core Team, 2018. R: a Language and Environment for Statistical Computing.Google Scholar
- Smit, I.P.J., Grant, C.C., Devereux, B.J., 2007. Do artificial waterholes influence the way herbivores use the landscape? Herbivore distribution patterns around rivers and artificial surface water sources in a large African savanna park. Biol.Google Scholar
- Valeix, M., Loveridge, A.J., Chamaillé-Jammes, S., Davidson, Z., Murindagomo, F., Fritz, H., Macdonald, D.W., 2009. Behavioral adjustments of African herbivores to predation risk by lions: spatiotemporal variations influence habitat use. Ecology 90, 23–30, https://doi.org/10.1890/08-0606.1.PubMedCrossRefPubMedCentralGoogle Scholar
- van Lieverloo, R.J., Schuiling, B.F., de Boer, W.F., Lent, P.C., de Jong, C.B., Brown, D., Prins, H.H.T., 2009. A comparison of faecal analysis with backtracking to determine the diet composition and species preference of the black rhinoceros (Diceros bicornis minor). Eur. J. Wildl. Res. 55, 505–515, https://doi.org/10.1007/s10344-009-0264-5.CrossRefGoogle Scholar
- White, G.C., Garrott, R.A., 1990. Analysis of Wildlife Radio-tracking Data. Academic Press, New York.Google Scholar