In biological systems, biological diversity often displays a rapid turn-over across elevations. This defining feature has made mountains classic systems for studying the spatial variation in diversity. Because patterns of elevational diversity can vary among lineages and mountain systems it remains difficult to extrapolate findings from one montane region to another, or among lineages. In this study, we assessed patterns and drivers of avian diversity along an elevational gradient on the eastern slope of Mt. Gongga, the highest peak in the Hengduan Mountain Range in central China, and a mountain where comprehensive studies of avian diversity are still lacking. We surveyed bird species in eight 400-m elevational bands from 1200 to 4400 m a.s.l. between 2012 and 2017. To test the relationship between bird species richness and environmental factors, we examined the relative importance of seven ecological variables on breeding season distribution patterns: land area (LA), mean daily temperature (MDT), seasonal temperature range (STR), the mid-domain effect (MDE), seasonal precipitation (SP), invertebrate biomass (IB) and enhanced vegetation index (EVI). Climate data were obtained from five local meteorological stations and three temperature/relative humidity smart sensors in 2016. A total of 219 bird species were recorded in the field, of which 204 were recorded during the breeding season (April–August). Species richness curves (calculated separately for total species, large-ranged species, and small-ranged species) were all hump-shaped. Large-ranged species contributed more to the total species richness pattern than small-ranged species. EVI and IB were positively correlated with total species richness and small-ranged species richness. LA and MDT were positively correlated with small-ranged species richness, while STR and SP were negatively correlated with small-ranged species richness. MDE was positively correlated with large-ranged species richness. When we considered the combination of candidate factors using multiple regression models and model-averaging, total species richness and large-ranged species richness were correlated with STR (negative) and MDE (positive), while small-ranged species richness was correlated with STR (negative) and IB (positive). Although no single key factor or suite of factors could explain patterns of diversity, we found that MDE, IB and STR play important but varying roles in shaping the elevational richness patterns of different bird species categories. Model-averaging indicates that small-ranged species appear to be mostly influenced by IB, as opposed to large-ranged species, which exhibit patterns more consistent with the MDE model. Our data also indicate that the species richness varied between seasons, offering a promising direction for future work.

Aim: Mountain ecosystems harbour significant biodiversity across elevations and seasons. This biodiversity, however, is increasingly under threat from climate change and human land use. While much work has been done to characterize biodiversity in tropical mountains, far less is known about the environmental, seasonal and spatial factors that impact diversity and community structure in subtropical and temperate regions.Location: Mt. Gongga, Sichuan, China: the eastern‐most peak in Asia above 7000‐m elevation and the main peak of the Hengduan Mountains.Method: We examined elevational patterns and ecological variables underlying taxonomic diversity (TD), phylogenetic diversity (PD), functional diversity (FD) and community structure in birds on the eastern slope of Mt. Gongga between 1100‐ and 4400‐m elevation. We assessed biodiversity patterns between species with different elevational range sizes (small‐ vs. large‐ranged species) and between seasons (breeding vs. non‐breeding season).Results: We recorded 230 bird species across seven field surveys. TD, PD and FD showed similar hump‐shaped elevational patterns in both seasons. In the breeding season, TD, PD and FD for small‐ranged species were highly correlated with climatic factors (mean daily temperature, seasonal temperature range) and vegetation factors (enhanced vegetation index), while large‐ranged species were correlated with spatial factors (mid‐domain effect). In the non‐breeding season, TD, PD and FD for all species groupings were positively correlated with climate factors. For small‐ranged species in both seasons, community structure was more overdispersed at low and high elevations, and more clustered at middle elevations. For large‐ranged species, community structure differed between seasons, showing a general trend towards clustering as elevations increase in the breeding season and trends towards overdispersion and/or evenness as elevations increase in the non‐breeding season.Conclusions: We found that different factors shape elevational patterns of diversity for small‐ and large‐ranged species in the breeding season; small‐ranged species are shaped by climate and vegetation structure, while large‐ranged species are shaped by spatial factors. This difference is likely explained by differences in ecological niche breadth (physiological tolerance and/or habitat specialization) between small‐ranged species and large‐ranged species. In the non‐breeding season, however, when climate is seasonally harsher, we found that patterns of diversity for all range‐size groupings were driven by climatic factors. We also found that community structure generally becomes more overdispersed as resource availability decreases and environmental conditions become harsher, like at higher elevations and in the non‐breeding season, suggesting that competition for limited resources is important for shaping communities in seasonal environments. These findings highlight how avian diversity and community structure are dynamic across a local elevational gradient and seasonally, shifting across the annual cycle, which has implications for conservation strategies and land management.

Global climate change has had significant effects on animal distribution and population dynamics in mid-latitude alpine areas, but we know little about the basic ecology of high-altitude species due to the difficulties of conducting field research in the harsh climate and habitat present at high elevations. The Tibetan Snowcock (Tetraogallus tibetanus) is a little-known phasianid distributing in alpine areas at extremely high elevations in the mountains surrounding the Tibetan Plateau. Estimating the species occupancy rate and discussing the factors affecting its distribution based on infrared-triggered camera techniques would provide both a baseline to measure the influence of global warming and valuable information on its conservation and ecology. We used infrared-triggered cameras to investigate the Tibetan Snowcock on the western slope of Mt. Gongga from June to November 2016. We used the R package “overlap” to visualize its activity pattern, and used an occupancy model to both examine its habitat use as well as to determine the most influential variables affecting its habitat use. Using 103 camera traps over 9213 camera-days, we recorded 428 instances of Tibetan Snowcock. The diel activity peaks of Tibetan Snowcock occurred during the periods of 8:00‒10:00 am and 18:00‒20:00 pm. The model estimate of occupancy for Tibetan Snowcock (0.830) was slightly higher than the naïve site occupancy based on camera detections (0.663), indicating a wider use of habitat than the camera traps recorded. Elevation, slope, settlement density, road density, and EVI (enhanced vegetation index) were the most influential variables for its habitat use. The Tibetan Snowcock is confirmed to be diurnal. This species prefers an environment with a high elevation, gentle slope, and low EVI, apparently facing a trade-off between predator risk, foraging efficiency, and food availability. When human impact was low, there was a positive correlation between the habitat use of the Tibetan Snowcock and both its road and settlement densities. Infrared cameras and proper survey design are valuable for investigating extreme alpine phasianids.