Successive sheep grazing reduces population density of Brandt’s voles in steppe grassland by altering food resources: a large manipulative experiment
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Livestock grazing has shaped grassland ecosystems around the world. Previous studies indicated grazing showed various impacts on small rodents; however, most studies were conducted over 1–2 years without controlling for confounding factors such as immigration/emigration and predation in rodents. Brandt’s voles (Lasiopodomys brandtii) are generally recognized as pests because of food overlap with domestic herbivores, but are also important for biodiversity conservation because they provide nests or food to many birds. Fully understanding the ecological relationship between domestic herbivores and small mammals is essential to making ecosystem management decisions. To address these needs, we carried out a field experiment during the period 2010–2013 to assess the effects of sheep grazing on vegetation and the population density of Brandt’s voles along a gradient of three grazing intensities by using 12 large-scale enclosures. Responses of Brandt’s voles to livestock grazing varied with grazing intensity and year. As compared to the control group, sheep grazing had no effect on vole abundance in the first year but an overall negative effect on vole abundance in the following 3 years. Successive grazing caused decreases in survival and male body mass of voles, but had no significant effect on fecundity. Negative effects of grazing were associated with a grazing-induced deterioration in both food quantity (reflected by biomass and cover of less-preferred plants), and food quality (measured by tannin and total phenol content). Our findings highlight the urgent need for more flexible management of yearly rotational grazing to optimize livestock production while maintaining species diversity and ecosystem health.
KeywordsBiodiversity loss Food quality Food quantity Pest management Rotational grazing
We thank the Maodeng Pasture of Xilinhot City and the Grassland Station of Xilingol League for their kind help in our field experiments. We thank all the students and volunteers involved in the field work. We are grateful to Prof. Marcel Holyoak of the University of California Davis for his valuable assistance and comments on this manuscript. This study was supported by the State Basic Research Program of the Ministry of Science and Technology (2007CB109100) and the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB11050000).
Author contribution statement
Z. Z. designed the experiments. G. L., B. Y., X. W. and W. W. performed the experiments. G. L. analyzed the data. G. L. and Z. Z. wrote the manuscript; G. W. and C. J. K. contributed to the data analysis and manuscript writing.
- Anderson DR, Burnham KP, Gould WR, Cherry S (2001) Concerns about finding effects that are actually spurious. Wildlife Soc B 29:311–316Google Scholar
- Burnham KP, Anderson DR (2002) Model selection and multimodal inference: a practical information theoretic approach. Springer, New YorkGoogle Scholar
- Otis DL, Burnham KP, White GC, Anderson DR (1978) Statistical inference from capture data on closed animal populations. Wildlife Monogr 62:7–135Google Scholar
- Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team (2014) nlme: linear and nonlinear mixed effects models. R package version 3. 1–117. http://CRAN.R-project.org/package=nlme
- R Core Team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. ISBN 3-900051-07-0, URL http://www.R-project.org/
- Zhong WQ, Wang MJ, Wan XR (1999) Ecological management of Brandt’s vole (Microtus brandti) in Inner Mongolia, China. In: Singleton GRHL, Leirs H, Zhang Z (eds) Ecologically-based management of rodent pests. ACIAR, Canberra, pp 199–214Google Scholar