Avian species distribution along elevation at Doon Valley (foot hills of western Himalayas), Uttarakhand, and its association with vegetation structure

Joshi, Kailash; Bhatt, Dinesh

doi:10.1016/j.japb.2015.04.002

Cited by 22 publications

(13 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3) was consistent with most previous studies on mammals (Hu et al, 2014), birds (Acharya et al, 2011; Joshi & Bhatt, 2015), reptiles (Chettri, Bhupathy & Acharya, 2010), and plants (Grytnes & Vetaas, 2002; Bhattarai, Vetaas & Grytnes, 2004; Acharya, Vetaas & Birks, 2011). The peak in richness is followed by a plateau at elevations of between 3,000 m and 3,900 m asl (Fig.…”

Section: Discussionsupporting

confidence: 92%

“…A study of songbirds in the eastern Himalayas demonstrated a hump-shaped elevational richness pattern and found that elevational distributions were well-explained by resource availability (Price et al, 2014). One study of birds in the western Himalayas showed a hump-shaped elevational richness pattern and a significant correlation between species richness and vegetation structure (Joshi & Bhatt, 2015). Considering that the mechanisms underlying elevational patterns vary even among gradients with similar biogeographic histories and fauna (Rowe, 2009), new, optimally designed elevational studies and integrative analyses of biodiversity along central Himalaya gradients in China are important for understanding these complex patterns and their underlying mechanisms (Grytnes & McCain, 2007; Wu et al, 2013a) and for the management and conservation of biodiversity.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Pan

Ding²,

et al. 2016

PeerJ

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

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

Pan

Ding²,

et al. 2016

PeerJ

View full text Add to dashboard Cite

show abstract

“…The Himalaya Mountains, the greatest mountain range in the world, offer a unique environment to conduct studies on the mechanisms of beta diversity patterns and the ecological theories of species distribution. However, numerous studies in this area mainly focused on the elevational patterns of species richness (Acharya, Vetaas, & Birks, 2011;Grytnes & Vetaas, 2002;Hu et al, 2017Hu et al, , 2018Hu et al, , 2014Joshi & Bhatt, 2015;Pan et al, 2016). Studies on beta diversity in the Himalayas have focused on plants in northwest Himalayan region (de Bello, Dolezal, Ricotta, & Klimesova, 2011;Saha, Rajwar, & Kumar, 2016) and trans-Himalayan region (Paudel & Vetaas, 2014).…”

Section: Introductionmentioning

confidence: 99%

Birds in the Himalayas: What drives beta diversity patterns along an elevational gradient?

Ding²,

Jiang

et al. 2018

Ecology and Evolution

View full text Add to dashboard Cite

Beta diversity patterns along elevational gradients have become a hot topic in the study of biogeography and can help illuminate the processes structuring mountain ecosystems. Although elevational species richness patterns have been well documented, there remains much uncertainty over the causes of beta diversity patterns across elevational gradients. We conducted bird surveys and obtained high‐resolution climatic data along an elevational gradient in Gyirong Valley in the central Himalayas, China, between 1,800 and 5,400 m elevation. In total, we recorded 182 bird species (including 169 breeding birds). We simulated beta diversity patterns with the mid‐domain effect (MDE) null model and conducted distance‐based redundancy analyses (db‐RDA) to relate beta diversity to dispersal limitations, spatial constraints, habitat complexity, contemporary climate, and historical climate. Mantel tests and variation partitioning were employed to identify the magnitude of independent statistical associations of environmental factors with beta diversity. Patterns of empirical and simulated beta diversity were both hump‐shaped, peaking at intermediate elevations. The db‐RDA indicated that beta diversity was correlated with changes in spatially structured environmental factors, especially with contemporary climate and habitat complexity. Mantel tests and variation partitioning also suggested that climate dissimilarity was the major independent correlate of beta diversity. The random community structure and spatial constraints may also contribute to the overall hump‐shaped pattern. Beta diversity of bird communities in Gyirong Valley could be explained by the combination of different factors but is mainly shaped by the spatially structured environmental factors, especially contemporary climate.

show abstract

“…Elevational studies in this region have mainly focused on plants Bhattarai & Vetaas, 2003Bhattarai, Vetaas, & Grytnes, 2004;Oommen & Shanker, 2005;, birds (Acharya, Sanders, Vijayan, & Chettri, 2011;Joshi & Bhatt, 2015;Li et al, 2013;Price et al, 2014) and reptiles (Chettri, Bhupathy, & Acharya, 2010;Pan et al, 2014). Most of these studies revealed hump-shaped biodiversity patterns along elevational gradients.…”

mentioning

confidence: 99%

Elevational patterns of non‐volant small mammal species richness in Gyirong Valley, Central Himalaya: Evaluating multiple spatial and environmental drivers

Jin

Huang³

et al. 2017

Journal of Biogeography

View full text Add to dashboard Cite

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.

show abstract

Avian species distribution along elevation at Doon Valley (foot hills of western Himalayas), Uttarakhand, and its association with vegetation structure

Cited by 22 publications

References 21 publications

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

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

Birds in the Himalayas: What drives beta diversity patterns along an elevational gradient?

Elevational patterns of non‐volant small mammal species richness in Gyirong Valley, Central Himalaya: Evaluating multiple spatial and environmental drivers

Contact Info

Product

Resources

About