Can local landscape attributes explain species richness patterns at macroecological scales?. Issue 4 (13th September 2013)

• Record Type: Journal Article
• Authors: Xu, Chi; Huang, Zheng Y. X.; Chi, Ting; Chen, Bin J. W.; Zhang, Mingjuan; Liu, Maosong
• Is Part Of: Global ecology & biogeography. Volume 23:Issue 4(2014:Apr.)
• Page Start: 436
• Page End: 445
• Publication Date: 2013-09-13
• Subjects: Amphibians -- biodiversity -- birds -- China -- climate -- habitat heterogeneity -- human influence -- mammals -- reptiles -- terrestrial vertebrates; Ecology -- Periodicals; Biogeography -- Periodicals; Biodiversity -- Periodicals; Macroevolution -- Periodicals; 577
• DOI: 10.1111/geb.12108
• Languages: English
• ISSNs: 1466-822X

Abstract

Abstract: Aim: Although the influence on species richness of landscape attributes representing landscape composition and spatial configuration has been well documented at landscape scales, its effects remain little understood at macroecological scales. We aim to assess the role of landscape attributes, and their relative importance compared with climate, habitat heterogeneity and human influence (CHH) in particular, in shaping broad‐scale richness patterns. Location: Mainland China. Methods: Species richness data for mammals, birds, reptiles and amphibians were derived from the China Species Information Service. Together with the richness data, CHH variables and class‐ and landscape‐level landscape metrics were calculated using grain sizes of 50 km × 50 km, 100 km × 100 km and 200 km × 200 km. At these multiple scales, the species richness of each taxonomic group was correlated with CHH and landscape variables using both ordinary least square (OLS) and simultaneous autoregressive (SAR) models; variation partitioning was used to assess the relative strength of landscape attributes versus CHH variables. Results: In general, climate is the most influential factor shaping richness patterns. Landscape attributes, especially class‐level attributes, can also explain considerable variation in richness. Variation partitioning showed largely overlapped fractions of explained variation between landscape attributes and CHH variables. The pure explanatory power of landscape attributes was small for mammals, reptiles and amphibians, showing R 2 of 1–3%, while it was considerably larger for birds, showing R 2 of 5–10%. The environment–richness correlations showed scale dependency, but the pure explanatory power of landscape attributes appeared to show small changes across the scale range used in this study. Main conclusions: In addition to CHH variables, landscape attributes can explain some broad‐scale richness patterns, especially for birds. The incorporation of landscape attributes will be conducive to better understanding the drivers of richness patterns and modelling species richness at macroecological scales.