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Single‐trait functional indices outperform multi‐trait indices in linking environmental gradients and ecosystem services in a complex landscape
Author(s) -
Butterfield Bradley J.,
Suding Katharine N.
Publication year - 2013
Publication title -
journal of ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.452
H-Index - 181
eISSN - 1365-2745
pISSN - 0022-0477
DOI - 10.1111/1365-2745.12013
Subject(s) - trait , ecosystem , ecology , ecosystem services , context (archaeology) , biodiversity , species richness , range (aeronautics) , forage , plant community , specific leaf area , biology , paleontology , materials science , photosynthesis , botany , computer science , composite material , programming language
Summary Functional traits can be used to describe the composition of communities through indices that seek to explain the factors that drive community assembly, biotic effects on ecosystem processes or both. Appropriately representing functional composition is therefore essential for predicting the consequences of environmental context and management actions for the provisioning of multiple ecosystem services ( ES s) in heterogeneous landscapes. Functional indices can be constructed from single or multiple traits; however, it is not clear how they differ in information content or ability to predict biodiversity – ecosystem function relationships in complex landscapes. Here, we compare the utility of analogous single‐ and multi‐trait indices in linking environmental variation and functional composition to ES s in a heterogeneous landscape, relating functional indices based on three plant traits [height, relative growth rate and root density ( RD )] to variation in the physical environment and to two ES s (forage production and soil carbon) and their net ES level. Two orthogonal gradients, elevation and soil bulk density ( BD ), explained significant variation in several dimensions of functional composition comprised of single traits. These traits in turn significantly predicted variation in ES s and their net values. Only one index measured with multiple traits (functional richness) varied with the physical environment, while none predicted variation in ES or net ES levels. One ES , soil carbon, increased with the community‐average value of RD , while the other, forage production, was related to the range and community‐average value of height. In turn, average RD increased with soil BD while the average and range of height declined with elevation. Due to these environmental patterns, soil carbon and forage production did not covary strongly, leading to moderate net ES levels across the landscape. Synthesis : Single‐trait indices of functional composition best linked variation in environmental gradients with productivity and soil carbon. Because the environment–trait functioning relationships were independent of one another, the ES s were independently distributed across the landscape, providing little evidence of synergies or trade‐offs. Single‐ and multi‐trait indices contained unique information about functional composition of these communities, and both are likely to have a place in predicting variation in ES s under different scenarios.