Elevational pattern of bird species richness and its causes along a central Himalaya gradient, China

Abstract

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.

<b>The ecology of Harwood’s Francolin <I>Pternistis harwoodi</I> (Aves: Galliformes: Phasianidae) at Merhabete District, central highlands of Ethiopia: implications for conservation</b>

“…Because there are flat, less vegetation diversity and settlements at the plateau of the areas in which any sightings were not recorded. But based on DEM analysis, the species showed a marked preference at mid elevation level, such as Block A, Block B and Block C. This finding agrees with Acharya et al (2011) and Pan et al (2016) that bird richness in the eastern and central Himalaya region was higher at middle elevation gradients.…”

Factors determining species richness patterns of breeding birds along an elevational gradient in the Horn of Africa region

“…In our study, the effect of area was variable (Table 3). This is the case with our results in the eastern slope subregion, which lack significant relationship, McCain (2007) and Pan et al (2016) found that the area is not identified as a main driving force and is not a crucial factor in determining species richness. In our case, the main factor is that the diversity in a certain elevational zone is strongly influenced by very local "hotspots," with many species restricted to places with riparian forest or cloud forest.…”

“…while it exhibited a hump-shaped pattern on the western slope and wet side(Figure 3). However, precipitation, as measured for the different elevational zones, is not a crucial predictor for elevational diversity(Pan et al, 2016). The relationship is positive in the wet side and negative in the dry side.…”

“…Thus, AMT and TAR data were square-transformed to meet assumptions of normality. We performed variance inflation factors (VIF) for all data and used variables with VIF (VIF < 10; Neter, Wasserman, & Kutner, 1984). The relationship between species richness and independent variables was also checked (Table S2).…”

Different responses of avian feeding guilds to spatial and environmental factors across an elevation gradient in the central Himalaya

“…Several drivers have been proposed to explain these patterns, including the current climate, space, evolutionary history, and biotic processes (reviewed in McCain, ). However, spatial (e.g., area, mid‐domain effect (MDE)) (Colwell, Rahbek, & Gotelli, ; Rahbek, ) and environmental drivers (e.g., climatic variables, productivity, and habitat heterogeneity) are cited most frequently (e.g., Nogués‐Bravo, Araújo, Romdal, & Rahbek, ; Sanders & Rahbek, ; Wu et al, ; Pan et al, ; Hu et al, ; Elsen, Tingley, Kalyanaraman, Ramesh, & Wilcove, ). For example, McCain () conducted a meta‐analysis of global elevational patterns of birds, and found both water and temperature variables were important drivers of elevational diversity gradients.…”