Abstract Large hydroelectric dams have become a major driver of habitat loss and fragmentation worldwide. The small-island effect (SIE) and nestedness are two general biogeographical patterns that have important implications for biodiversity conservation in fragmented systems. In this study, we tested for the existence of the SIE and nestedness patterns in medium- and large-bodied mammals (>1 kg) (hereafter mammals) on land-bridge islands created by a large hydroelectric dam in the Thousand Island Lake, China. We used the camera trapping method to determine the distribution of mammals on 32 study islands from May 2011 to March 2014. To evaluate whether an SIE exists in mammals, we used the information-theoretic multimodel inference approach to compare the fit of a simple logarithmic model with two most widely used breakpoint regression models. Model selection based on corrected Akaike’s information criterion (AICc) identified the left-horizontal SIE model and the continuous two-slope SIE model as the two best models. Thus, we found strong evidence for the existence of an SIE in our study system. The SIE in mammal assemblages may result from episodic disturbances, stochastic events and nutrient subsidies from the lake. We used the metric NODF to quantify nestedness and found that mammal assemblages were significantly nested. The nestedness of mammal assemblages was significantly correlated with island area and species traits linked to extinction risk (i.e. minimum area requirement). Our results indicate that conservation priorities should be on protecting large islands and species with large area requirement for the effective conservation of mammals in this fragmented reservoir system.
The small-island effect and nestedness in assemblages of medium- and large-bodied mammals on Chinese reservoir land-bridge islands
Chuanwu Chen,Aichun Xu,P. Ding,Yanping Wang
Published 2019 in Basic and Applied Ecology
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- Publication year
2019
- Venue
Basic and Applied Ecology
- Publication date
2019-06-27
- Fields of study
Geography, Environmental Science
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