Habitat loss and fragmentation are considered to be the leading drivers of biodiversity loss. The small-island effect (SIE) can be used to predict species extinctions resulting from habitat loss and has important implications for species conservation. However, to date, no study has explicitly evaluated the prevalence of SIEs in habitat islands. Here, we compiled 90 global datasets to systematically investigate the prevalence and underlying factors determining the ubiquity of SIEs in habitat island systems. Among the 90 datasets, SIEs were unambiguously detected in 36 cases. We found significant effects of habitat island types and taxon groups on the threshold area of SIEs. The number of islands, area range, species range, island type and taxon group were key variables that determined the prevalence of SIEs. Our study demonstrates that SIEs occur in 40% of cases and thus are common in habitat islands. We conclude that conservation biologists and applied ecologists should consider the prevalence of SIEs when making management strategies in fragmented landscapes.

Aim: China is one of the countries with the richest amphibian biodiversity in the world. Among the 408 Chinese amphibians, 174 species are considered threatened according to the China Biodiversity Red List in 2015. However, to date, which species traits or extrinsic factors are correlated with extinction risk in Chinese amphibians is rarely examined. The aims of this study were thus to identify the patterns and correlates of extinction risk in Chinese amphibians and to determine whether patterns and processes are similar between species with either small or large geographic distributions.Location: China.Methods: We obtained twelve species traits and four extrinsic factors that have been commonly linked to the extinction risk of amphibians. After phylogenetic correction, these factors were tested separately and in combination to identify their correlations with extinction risk in all Chinese amphibians, and in small‐ranged and large‐ranged species.Results: Geographic range size and elevational range were the most important predictors of extinction risk in all Chinese amphibians. Although extinction risk in small‐ranged amphibians was predominantly determined by small elevational range, in large‐ranged amphibians it was driven by geographic and elevational ranges, body size, human exploitation index and adult microhabitat. Small‐ranged amphibians had a higher percentage of threatened species than large‐ranged species. However, the body size distributions were not statistically different between these two amphibian subgroups.Main conclusions: Our findings suggest that conservation priority should be given to species with small geographic and elevational ranges. Small‐ranged and large‐ranged amphibians should be conserved with different strategies because the factors influencing extinction risk differ between these two groups. In specific, the reduction of habitat loss should be a primary focus of management efforts because species with small geographic and elevational ranges are particually vulnerable to habitat loss. Conservation efforts should also focus on protecting large‐bodied species and preventing human overexploitation for the effective conservation of large‐ranged amphibians.

Aim: Most studies of diversity changes along elevational gradients show a synchronous change in taxonomic, functional and phylogenetic diversity, such that all decline with elevation or show a mid‐elevation peak. However, some studies show asynchronous changes, which challenge us to explain their assembly. Here we used functional trait variation and niche spacing to test the roles of environmental filtering and competition‐driven niche separation in assembly and biodiversity patterns across an elevational gradient.Location: Nanling Mountains, southern China.Taxon: Birds (Timaliidae, Pycnonotidae and Sylviidae)Methods: Breeding birds were surveyed in 2012–2017 from 300 to 1900 m ASL. We tested bird diversity pattern and community structure relevant to environmental filtering and limiting similarity by integrating functional traits and evolutionary distances, as well as vegetation heterogeneity. A null modelling approach tested specific trait variation and niche spacing in relation to habitat associations and niche segregation.Results: Contrary to expectation, bird richness peaked at just below the highest site, and functional diversity declined significantly with elevation. Functional–phylogenetic distance metrics converged with increasing elevation, corresponding to strong environmental filtering and habitat change. For the spatial arrangement of specific traits, restricted dispersal ability, elevational range and clutch sizes were related to filtering effects, as indicated by trait convergence in clustered highland bird assemblages. Conversely, overdispersed lowland assemblages have evenly spaced trait values predicted by limiting similarity, including bill length, vertical stratum‐use and flocking propensity. In addition, bird functional diversity was highly correlated with both vegetation productivity and tree height, which reinforces the role of filtering in structuring local bird assemblages.Main conclusions: This study highlights how strong filtering can produce a counter‐intuitive, contrasting pattern of changes between species richness and functional diversity. Fundamental assembly processes and species roles in ecosystems are predictable through examining key traits of life‐history and foraging characteristics, and their associations with environmental variables.

The small‐island effect (SIE) has become a widespread pattern in island biogeography and biodiversity research. However, in most previous studies only area is used for the detection of the SIE, while other causal factors such as habitat diversity is rarely considered. Therefore, the role of habitat diversity in generating SIEs is poorly known. Here, we compiled 86 global datasets that included the variables of habitat diversity, area and species richness to systematically investigate the prevalence and underlying factors determining the role of habitat diversity in generating SIEs. For each dataset, we used both path analysis and breakpoint regressions to identify the existence of an SIE. We collected a number of system characteristics and employed logistic regression models and an information–theoretic approach to determine which combination of variables was important in determining the role of habitat diversity in generating SIEs. Among the 61 datasets with adequate fits, habitat diversity was found to influence the detection of SIEs in 32 cases (52.5%) when using path analysis. By contrast, SIEs were detected in 26 of 61 cases (42.6%) using breakpoint regressions. Model selection and model‐averaged parameter estimates showed that Number of sites, Habitat range and Species range were three key variables that determined the role of habitat diversity in generating SIEs. However, Area range, Taxon group and Site type received considerably less support. Our study demonstrates that the effect of habitat diversity on generating SIEs is quite prevalent. The inclusion of habitat diversity is important because it provides a causal factor for the detection of SIEs. We conclude that for a better understanding of the causes of SIEs, habitat diversity should be included in future studies.