Equal contributors to this work.
Can local landscape attributes explain species richness patterns at macroecological scales?
Article first published online: 13 SEP 2013
© 2013 John Wiley & Sons Ltd
Global Ecology and Biogeography
Volume 23, Issue 4, pages 436–445, April 2014
How to Cite
Xu, C., Huang, Z. Y. X., Chi, T., Chen, B. J. W., Zhang, M. and Liu, M. (2014), Can local landscape attributes explain species richness patterns at macroecological scales?. Global Ecology and Biogeography, 23: 436–445. doi: 10.1111/geb.12108
Editor: Joshua Lawler
- Issue published online: 3 MAR 2014
- Article first published online: 13 SEP 2013
- National Natural Science Foundation of China. Grant Number: 41271197
- China Scholarship Council
- habitat heterogeneity;
- human influence;
- terrestrial vertebrates
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.
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.
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 R2 of 1–3%, while it was considerably larger for birds, showing R2 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.
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.