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Investigating the relationship between biodiversity and ecosystem multifunctionality: challenges and solutions

Jarrett E. K. ByrnesNational Center for Ecological Analysis and Synthesis 735 State Street Santa Barbara CA 93101 USALars GamfeldtDepartment of Biological and Environmental Sciences University of Gothenburg Box 461 SE‐40530 Gothenburg SwedenForest IsbellDepartment of Ecology, Evolution, and Behavior University of Minnesota St Paul MN 55108 USAJonathan S. LefcheckVirginia Institute of Marine Science College of William & Mary Gloucester Point VA 23062 USAJohn N. GriffinDepartment of Biosciences Swansea University Singleton Park Swansea SA2 8PP UKAndy HectorDepartment of Plant Sciences University of Oxford South Parks Road Oxford OX1 3RB UKBradley J. CardinaleSchool of Natural Resources & Environment University of Michigan Ann Arbor MI 48109 USADavid U. HooperDepartment of Biology Western Washington University Bellingham WA 98225‐9160 USALaura E. DeeBren School of Environmental Science and Management University of California Santa Barbara CA 93106 USAJ. Emmett DuffyVirginia Institute of Marine Science College of William & Mary Gloucester Point VA 23062 USA
2013en
ABI

Аннотация

Summary Extensive research shows that more species‐rich assemblages are generally more productive and efficient in resource use than comparable assemblages with fewer species. But the question of how diversity simultaneously affects the wide variety of ecological functions that ecosystems perform remains relatively understudied. It presents several analytical and empirical challenges that remain unresolved. In particular, researchers have developed several disparate metrics to quantify multifunctionality, each characterizing different aspects of the concept and each with pros and cons. We compare four approaches to characterizing multifunctionality and its dependence on biodiversity, quantifying (i) magnitudes of multiple individual functions separately, (ii) the extent to which different species promote different functions, (iii) the average level of a suite of functions and (iv) the number of functions that simultaneously exceeds a critical threshold. We illustrate each approach using data from the pan‐European BIODEPTH experiment and the R multifunc package developed for this purpose, evaluate the strengths and weaknesses of each approach and implement several methodological improvements. We conclude that an extension of the fourth approach that systematically explores all possible threshold values provides the most comprehensive description of multifunctionality to date. We outline this method and recommend its use in future research.

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