Single-trait functional indices outperform multi-trait indices in linking environmental gradients and ecosystem services in a complex landscape

Authors

  • Bradley J. Butterfield,

    Corresponding authorCurrent affiliation:
    1. Merriam-Powell Center for Environmental Research and Department of Biology, Northern Arizona University, Flagstaff, AZ, USA
    • Department of Environmental Science, Policy and Management, University of California Berkeley, Berkeley, CA, USA
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  • Katharine N. Suding

    1. Department of Environmental Science, Policy and Management, University of California Berkeley, Berkeley, CA, USA
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Correspondence author. E-mail: Bradley.Butterfield@nau.edu

Summary

  1. 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 (ESs) in heterogeneous landscapes.
  2. 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 ESs 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 ESs (forage production and soil carbon) and their net ES level.
  3. 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 ESs 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.
  4. 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.
  5. 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 ESs 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 ESs under different scenarios.

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