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Aim: An area threshold is usually considered as the point of abrupt change in the species–area relationship (SAR). Despite their widespread existence, few studies have considered the influence of data transformations on their presence or the mechanisms that generate them. The aims of this study were thus to test for the existence of an area threshold in butterfly assemblages and to compare trait–environment associations between small and large islands split by the threshold. Location: Zhoushan Archipelago, China. Taxon: Butterflies. Methods: We used the line‐transect method to survey butterflies on 42 islands from July to August 2014. We also collected data on three commonly used ecological traits of butterflies (wingspan, wing loading and body weight). We transformed the butterfly datasets into three types (log‐log, semi‐log and untransformed) and fitted each of them using a set of breakpoint regression models. We then split all islands into small and large islands based on the area threshold and analysed the trait–environment associations for each island group. Results: Two‐slope breakpoint models performed best for log‐log and semi‐log transformed datasets. However, the former exhibited a steep‐shallow shape with an area threshold of 0.820 km2 and the latter was in shallow‐steep shape with a threshold of 17.022 km2. By contrast, no threshold was detected when using the untransformed power model. Moreover, for small islands, small area and large isolation were positively correlated with species with large wing loading and body weight. For large islands, however, the perimeter to area ratio (PAR) was significantly and positively related to wing loading. Main conclusions: We found that data transformations may influence the detection of area thresholds. Trait–environment analyses can further provide novel and mechanistic insights into processes generating area thresholds. We urge that the influence of data transformations and ecological traits of species should be explicitly considered in future studies. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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