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Can local landscape attributes explain species richness patterns at macroecological scales?
Author(s) -
Xu Chi,
Huang Zheng Y. X.,
Chi Ting,
Chen Bin J. W.,
Zhang Mingjuan,
Liu Maosong
Publication year - 2014
Publication title -
global ecology and biogeography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.164
H-Index - 152
eISSN - 1466-8238
pISSN - 1466-822X
DOI - 10.1111/geb.12108
Subject(s) - species richness , ecology , macroecology , habitat , ecoregion , geography , spatial ecology , body size and species richness , variation (astronomy) , mainland , spatial heterogeneity , biology , physics , astrophysics
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 C hina. Methods Species richness data for mammals, birds, reptiles and amphibians were derived from the C hina S pecies I nformation S ervice. 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.