Summary1. The loss of species diversity due to habitat fragmentation has been extensively studied. In contrast, the impacts of habitat fragmentation on functional diversity remains relatively poorly understood. We conducted bird functional diversity studies on a set of 41 recently isolated land-bridge islands in the Thousand Island Lake, China. 2. We analysed differences in bird species richness and a recently developed suite of complementary functional diversity indices (FRic, volume of functional space occupied; FEve, evenness of abundance distribution in the functional trait space; FDiv, divergence in the distribution of abundance in the trait volume) across different gradients (island area and isolation). 3. We found no correlations between FRic and FEve or FEve and FDiv, but negative correlations between FRic and FDiv. As predicted, island area accounted for most of the variation in bird species richness, whereas isolation explained most of the variation in species evenness (decreasing species evenness with increasing isolation). Functional diversity appears to be more strongly influenced by habitat filtering as opposed to limiting similarity. More specifically, across all islands, both FRic and FEve were significantly lower than expected for randomly assembled communities, but FDiv showed no clear patterns. FRic increased with island area, FEve decreased with island area and FDiv showed no clear patterns. 4. Our finding that FEve decreases with island area at TIL may indicate low functional stability on such islands, and as such large islands and habitat patches may deserve extra attention and/or protection. These results help to demonstrate the importance of considering the effects of fragmentation on functional diversity in habitat management and reserve design plans.

This study examines the relative importance of six variables: area, the mid-domain effect, temperature, precipitation, productivity, and habitat heterogeneity on elevational patterns of species richness for breeding birds along a central Himalaya gradient in the Gyirong Valley, the longest of five canyons in the Mount Qomolangma National Nature Reserve. We conducted field surveys in each of twelve elevational bands of 300 m between 1,800 and 5,400 m asl four times throughout the entire wet season. A total of 169 breeding bird species were recorded and most of the species (74%) were small-ranged. The species richness patterns of overall, large-ranged and small-ranged birds were all hump-shaped, but with peaks at different elevations. Large-ranged species and small-ranged species contributed equally to the overall richness pattern.Based on the bivariate and multiple regression analyses, area and precipitation were not crucial factors in determining the species richness along this gradient. The mid-domain effect played an important role in shaping the richness pattern of large-ranged species. Temperature was negatively correlated with overall and large-ranged species but positively correlated with small-ranged species. Productivity was a strong explanatory factor among all the bird groups, and habitat heterogeneity played an important role in shaping the elevational richness patterns of overall and small-ranged species. Our results highlight the need to conserve primary forest and intact habitat in this area. Furthermore, we need to increase conservation efforts in this montane biodiversity hotspot in light of increasing anthropogenic activities and land use pressure.

How communities assemble is a central and fundamental question in ecology. However, it has been mired by conflicting conclusions about whether community assembly is driven by environmental filtering, biotic interactions, and/or dispersal processes. Elevational gradients provide an ideal system for exploring the biotic and abiotic forces influencing the processes of community assembly, as these both change dramatically on mountains over short spatial distances. Here, we explored bird taxonomic, functional and phylogenetic diversity, and assessed the role of spatial (area) and environmental factors (temperature, precipitation, plant richness, habitat heterogeneity, the Normalized Difference Vegetation Index (NDVI)) in shaping bird distributions and community structure along a 3600 m elevational gradient in the central Himalayas, China. Our results showed that the three dimensions of diversity consistently showed hump‐shaped patterns with similar peaks. Richness‐controlled functional diversity decreased with elevation, while richness‐controlled phylogenetic diversity showed a Mid Valley pattern. Mean pairwise functional distance decreased linearly with elevation, and mean pairwise phylogenetic distance was nearly constant along the elevation gradient but increased rapidly at higher elevations (above 3900–4200 m a.s.l). The functional structure of bird communities was more clustered relative to source pools (i.e. species more similar to one another) across the elevation gradient, suggesting abiotic or habitat filtering likely governed the assembly processes. However, phylogenetic structure was more clustered relative to source pools at mid‐elevations and more overdispersed (i.e. species are less related) at low and high elevations. In addition, primary productivity (NDVI and/or habitat heterogeneity and/or plant richness) was a good predictor of variation for most diversity metrics. Taken together, our study demonstrated contrasting elevational patterns assessed from functional and phylogenetic measures and highlighted the necessity of considering multiple measures of biodiversity when assessing community structure.

Aim Documenting the elevational species richness patterns of non‐volant small mammals and assessing the roles of pure spatial factors and spatial structured environmental factors in shaping the elevational richness patterns. Location Gyirong Valley in the Mount Qomolangma National Nature Reserve, located in the southern Himalayas, China. Methods Field surveys were conducted at each of twelve 300‐m elevational bands along a gradient from 1,800 to 5,400 m above sea level (a.s.l). For the pure spatial variables, we calculated area and the spatial null model named MDE (cf. below). For spatial structured environmental variables, we calculated mean annual temperature, mean annual precipitation, mean annual temperature range, potential evapotranspiration (PET), the normalized difference vegetation index, plant species richness and habitat heterogeneity. Multivariate models of species richness against eight factors (excluding PET) for different species groups were used to test the explanatory power of both the spatial structured environmental variables and the pure spatial variables. In addition, mean annual precipitation and potential evapotranspiration were used to test the water–energy dynamics model for each species groups. Results Seven hundred and fifty‐five individuals of 22 species were documented over 21,600 trap nights. The elevational species richness pattern for all non‐volant small mammals was hump‐shaped with the highest richness occurring at 2,700–3,300 m a.s.l. Endemic and non‐endemic species as well as two elevational range size categories of small mammals also generally showed hump‐shaped species richness patterns. In most data sets, spatial structured environmental variables played more important roles than the pure spatial variables in shaping the elevational species richness patterns than the pure spatial factors, while the MDE contributed to richness patterns for large‐ranged species. The water–energy dynamics model explained 66% of the variation in all the non‐volant small mammals, 56% for endemic species, 88% for the non‐endemic species, 59% for the large‐ranged species, and 53% for the small‐ranged species. Main conclusions Although no single key factor can explain all species richness patterns, we found that spatial structured environmental variables correlate well with the elevational species richness pattern of non‐volant small mammals. The water–energy dynamics model was found to explain non‐volant small mammal species richness along the Gyirong Valley.