Table S1. List of the studies investigating relationships between
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Table S1. List of the studies investigating relationships between functional diversity measures and ecosystem functioning. We surveyed the literature published up to the end of 2013 using ISI Web of Knowledge and Google Scholar (last accessed: 20 December 2013). We used combinations of the term “functional diversity*” with one of the following: “ecosystem function*” or “ecosystem service*” or “ecosystem process*”. We then scanned the cited literature in the articles we found. The criterion for including an article in the synthesis was that it had to evaluate effects of multivariate continuous functional diversity measures on ecosystem functioning (Fig.1c, d). In cases where a study compared single- and multi-trait indices, and species taxonomic diversity, we also recorded the measure or model that performed best in explaining ecosystem functioning. In addition, we recorded the direction of the effect (positive, negative, or no significant effect) and the explanatory power (R2) if reported, whether the study was observational or experimental, and the taxonomic identity of the study organisms. In cases where R2 was in a single study reported for different years, habitats, or different experimental designs we included only the highest R2. This is because our aim was to explore the best explanatory power that different diversity indices can achieve, rather than comparing average R2 across studies. We found 16 studies reporting relationships between multivariate functional diversity and ecosystem functioning (see Table below). All but one study focused on terrestrial plants or algae and none of them studied terrestrial animals. Furthermore, the majority of these studies (10 out of 16) were experimental. Some data-sets have been used repeatedly in different publications to test functional diversity and ecosystem functioning relationships, e.g., data from the BIODEPTH project and the Cedar Creek experiment. The most commonly investigated ecosystem functions were above- or below-ground biomass (13 studies), decomposition (5 studies), and carbon storage (3 studies). Some studies investigated more than one ecosystem function. Multi-trait functional diversity had significant positive effects on ecosystem functioning in 41% and negative in 38% of cases. A majority of the studies that tested for effects of both single- and multi- trait diversity indices found that selected single-trait indices performed better than multi-trait indices in predicting ecosystem functioning (73%). Species richness and abundances were generally poor at predicting ecosystem functioning (highest R2 = 0.37), while highest explanatory power for single-trait indices was R2= 0.54 for CWMx (Schumacher & Roscher 2009), and for multi-trait indices R2= 0.69 for FRdendr (Thompson et al. 2005). The most common significant multi-trait predictors measured functional divergence (FDdiv) and functional dispersion (FDrao, FDdis), with less prevalent effects of functional richness indices (FRdendr, FRminvol). Note that for single-trait measures (CWM, Fdvar-s, FRO, Range, FDRao-s,FDqs, ) the direction of the effect is not included because it is highly variable depending on the traits investigated and only the highest R2 is reported. If the authors did not report explained variation (R2) for single-variable models (SVM) we present the multi-variable model (MVM) with highest R2. Explained variation and slopes for the best model/variable corresponds to the ecosystem function in the same row. For structural equation models (SEM) only variables with direct links to the ecosystem function are presented. References 1. Griffin et al. 2009 Oikos Study organis m Macroa Experiment /Field study Experiment Index-Ecosystem function FAD Primary productivity 0.10 4 Species identity Primary productivity 0.79 6 FRO Aboveground biomass EV+CWM+Range (R2= 0.48) CWM Soil organic carbon CWM+Stot/b (R2= 0.12) Range Net ecosystem service level EV+CWM+Range (R2= 0.38) lgae 2. Butterfield & Suding 2013 Journal of Ecology Plants Field study Fdvar-s FRminvol SVM R2 Slope MVM R2 Tested index* n.s FDeve FDdiv Stot/b EV 3. Conti & Diaz 2013 Journal of Ecology 4. Scherer-Lorenzen 2008 Functional Ecology 5. Thompson et al. 2005 Functional Ecology 6. Mouillot et al. 2011 PlosOne Plants Plants Plants Plants Field study Experiment (BIODEPTH) Field study Experiment (BIODEPTH) Individual abundances( IA) CWM Aboveground biomass Fdvar-s+CWM (R2= 0.73) Aboveground litter carbon Fdvar-s+IA (R2= 0.89) Fdvar-s Soil organic carbon FDdiv (negative)+CWM+IA (R2= 0.86) FDdiv Total ecosystem carbon Fdvar-s, CWM, IA(R2= 0.87) Srich FGR Cotton decomposition FDRao-m Cotton decomposition 0.15 positiv e FDRao-m Wood decomposition 0.12 positiv e FDRao-m Litter decomposition 0.38 positiv e FGR Litter decomposition Srich Aboveground biomass 0.17 5 negati ve FGR Aboveground biomass 0.10 1 negati ve Mean plant trait Aboveground biomass 0.20 2 FDdendr Aboveground biomass 0.69 Srich Cotton decomposition PCoA+ FDeve (negative) + FDdiv (positive) (R2= 0.42) Seve Litter decomposition Seve (negative)+ PCoA+ FDdiv (positive) (R2= 0.69) Functional identity (PCoA) FR Aboveground biomass Srich (positive)+PCoA+FDdiv (positive) (R2= 0.82) Nitrogen pool size PCoA+FRminvol(positive)+ FDdiv (positive) (R2 =0.84) FDeve Multifunctionality PCoA+FDdiv (positive) (R2 =0.80) minvol positiv e positiv e negati ve FDdiv 7. Cadotte et al. 2009 PlosOne 8. Mokany et al. 2008 Journal of Ecology Plants Plants Experiment Srich (Cedar Creek, MN) Trait variation Field study Aboveground biomass 0.36 9 positiv e FGR Aboveground biomass 0.33 8 positiv e NMDS Aboveground biomass 0.36 5 positiv e FDdendr Aboveground biomass 0.32 4 positiv e FAD Aboveground biomass 0.23 7 positiv e PD Aboveground biomass 0.41 5 positiv e Srich Green shoot biomass 0 n.s Seve Green shoot biomass 0 n.s Simpson’s diversity Green shoot biomass 0 n.s FGR Green shoot biomass 0 n.s FRdendr Green shoot biomass 0.07 8 positiv e FRO Green shoot biomass 0.07 positiv e FDRao-m Green shoot biomass 0.30 1 positiv e Fdvar-m Green shoot biomass 0.34 5 positiv e CWM Green shoot biomass 0.13 9 Srich Root biomass 0.05 4 n.s Seve Root biomass 0.07 4 negati ve Simpson’s diversity Root biomass 0.08 1 negati ve FGR Root biomass 0 FRdendr Root biomass 0.08 8 negati ve FRO Root biomass 0.01 2 n.s FDRao-m Root biomass 0.07 4 negati ve Fdvar-m Root biomass 0.12 4 negati ve CWM Root biomass 0.06 1 positiv e Srich Total plant biomass 0.07 8 negati ve Seve Total plant biomass 0.04 2 n.s Simpson’s diversity Total plant biomass 0.08 8 negati ve FGR Total plant biomass 0 FRdendr Total plant biomass 0.10 5 negati ve FRO Total plant biomass 0.06 4 positiv e FDRao-m Total plant biomass 0.16 2 negati ve Fdvar-m Total plant biomass 0.27 2 positiv e CWM Total plant biomass 0.33 Srich Litter biomass 0.07 1 negati ve Seve Litter biomass 0.04 8 n.s Simpson’s diversity Litter biomass 0.18 6 negati ve FGR Litter biomass 0 FRdendr Litter biomass 0.15 negati ve FRO Litter biomass 0.07 3 positiv e n.s n.s n.s FDRao-m Litter biomass 0.21 5 negati ve Fdvar-s Litter biomass 0.23 2 negati ve CWM Litter biomass 0.34 6 Srich Productivity 0.01 8 n.s Seve Productivity 0 n.s Simpson’s diversity Productivity 0.00 4 n.s FGR Productivity 0.04 2 n.s FRdendr Productivity 0.09 5 negati ve FRO Productivity 0.06 6 positiv e FDRao-s Productivity 0.17 5 negati ve Fdvar-s Productivity 0.18 8 negati ve CWM Productivity 0.22 5 Srich Litter decomposition rate 0 n.s Seve Litter decomposition rate 0 n.s Simpson’s diversity Litter decomposition rate 0 n.s FGR Litter decomposition rate 0 n.s FRdendr Litter decomposition rate 0.15 7 negati ve FRO Litter decomposition rate 0.08 3 negati ve FDRao-m Litter decomposition rate 0.25 9 positiv e Fdvar-m Litter decomposition rate 0.2 positiv e CWM Litter decomposition rate 0.32 Srich Mean soil moisture 0.09 3 negati ve Seve Mean soil moisture 0.16 1 negati ve Simpson’s diversity Mean soil moisture 0.20 7 negati ve FGR Mean soil moisture 0 FRdendr Mean soil moisture 0.31 2 negati ve FRO Mean soil moisture 0.05 3 n.s FDRao-m Mean soil moisture 0.41 negati ve Fdvar-m Mean soil moisture 0.45 5 negati ve CWM Mean soil moisture 0.44 3 Srich Light interception 0.09 5 negati ve Seve Light interception 0.03 5 n.s n.s 9. Flynn et al. 2011 Ecology 10. Laliberte & Tylianakis 2012 Ecology Plants Plants Experiment s Experiment Simpson’s diversity Light interception 0.12 6 negati ve FGR Light interception 0 FRdendr Light interception 0.18 9 negati ve FRO Light interception 0.05 6 n.s FDRao-s Light interception 0.25 negati ve Fdvar-s Light interception 0.33 9 positiv e CWM Light interception 0.38 6 Srich Aboveground biomass 0.17 6 positiv e FGR Aboveground biomass 0.16 9 positiv e FRdendr Aboveground biomass 0.18 1 positiv e PD Aboveground biomass 0.19 6 positiv e CWM Aboveground biomass EV+CWM+EV:FDdis (R2= 0.77) FDdis Belowground biomass R2= 0 EV Litter decomposition rate Aboveground biomass (R2= 0.77) soil C (0-20cm) EV+CWM+Aboveground biomass + Belowground biomass (R2= 0.67) EV+Soil C (0-20cm) (R2= 0.77) n.s soil C (60-80cm) 11.Petchey et al. 2004 Ecology 12. Schumacher & Roscher 2009 Oikos 13.Bernardt-Römermann et al. 2011 Journal of Applied Ecology Plants Plants Plants Experiment (BIODEPTH) Field study Experiment Srich FGR Aboveground biomass (all sites and polycutures) Aboveground biomass 0.33 positiv e 0.4 positiv e FAD (all sites and polycutures) Aboveground biomass 0.4 positiv e FRdendr (all sites and polycutures) biomass Aboveground 0.55 positiv e Srich (all sites and polycutures) Aboveground biomass 0.1 CWM Aboveground biomass 0.54 1 FDRao-m Aboveground biomass 0.29 5 EV Aboveground biomass 0.50 1 Srich Aboveground biomass Seve Aboveground biomass positiv e/nega tive positiv FRminvol Aboveground biomass e/nega tive positiv n.s negati ve e FDeve FDdiv Aboveground biomass positiv e/nega tive EV 14. Wacker et al. 2009 Ecology Plants Experiment FDRao Aboveground biomass 0.04 9 n.s FDRao/d Aboveground biomass 0.12 7 positiv e 15. Frainer et al. 2013 JAE Aquatic insects Field study FDRao/b Aboveground biomass 0 FDRao/d Net biodiversity effect 0.08 Stot/n Decomposition positiv e/n.s Stot/b FDdis positiv e Decomposition positiv e/nega tive EV 16. Clark et al. 2012 PlosOne Plants n.s Experiment FRdendr/cv.ab un Aboveground biomass 0.36 2 positiv e (Cedar Creek, MN) FRdendr/abun Aboveground biomass 0.35 5 positiv e FDRao-m Aboveground biomass 0.38 7 positiv e FDRao-m/cv Aboveground biomass 0.38 7 positiv e FDdis Aboveground biomass 0.36 3 positiv e FDdiv Aboveground biomass 0.38 6 positiv e FRdendr/cv.joi nt.abun Aboveground biomass 0.25 4 positiv e FRdendr/joint. abun Aboveground biomass 0.25 4 positiv e FRdendr Aboveground biomass 0.23 5 positiv e FRdendr/cv Aboveground biomass 0.24 positiv e Strt Aboveground biomass 0.32 5 positiv e FGRtrt Aboveground biomass 0.33 1 positiv e FGRobs Aboveground biomass 0.26 6 positiv e Sobs Aboveground biomass 0.27 positiv e Hull Aboveground biomass 0.29 1 n.s Hull/cv Aboveground biomass 0.29 1 n.s FDeve Aboveground biomass 0.31 2 n.s Hull/cv.abun Aboveground biomass 0.31 3 n.s Hull/abun Aboveground biomass 0.31 3 n.s FRdendr/cv.ab un Belowground biomass 0.33 negati ve FRdendr/abun Belowground biomass 0.32 1 negati ve FGRobs Belowground biomass 0.26 2 positiv e FRdendr/cv Belowground biomass 0.25 4 positiv e FRdendr Belowground biomass 0.25 3 positiv e FRdendr/joint. abun Belowground biomass 0.25 1 positiv e FRdendr/cv.joi nt.abun Belowground biomass 0.24 9 positiv e Stot/b+EV (R2 =0.73) Hull Belowground biomass 0.24 4 positiv e Hull/cv Belowground biomass 0.24 4 positiv e Sobs Belowground biomass 0.24 7 positiv e FDdiv Belowground biomass 0.29 9 negati ve FDRao-m Belowground biomass 0.31 8 negati ve FDRao-m/cv Belowground biomass 0.31 8 negati ve FGRtrt Belowground biomass 0.24 1 positiv e Strt Belowground biomass 0.24 1 positiv e FDdis Belowground biomass 0.30 3 negati ve Hull/cv.abun Belowground biomass 0.25 2 n.s Hull/abun Belowground biomass 0.25 2 n.s FDeve Belowground biomass 0.26 6 n.s Strt Light capture 0.26 negati ve FGRtrt Light capture 0.26 3 negati ve FRdendr/cv.joi nt.abun Light capture 0.24 2 negati ve FRdendr/joint. abun Light capture 0.24 1 negati ve FRdendr/cv Light capture 0.23 4 negati ve FRdendr Light capture 0.23 4 negati ve S Light capture 0.22 2 negati ve FDdis Light capture 0.28 4 negati ve FDRa-mo Light capture 0.28 9 negati ve FDRao-m/cv Light capture 0.28 9 negati ve Hull Light capture 0.23 5 negati ve Hull/cv Light capture 0.23 5 negati ve FGR Light capture 0.23 9 n.s FRdendr/cv.ab un Light capture 0.21 5 n.s FRdendr/abun Light capture 0.21 8 n.s FDdiv Light capture 0.22 8 n.s Hull/abun Light capture 0.24 6 n.s Hull/cv.abun Light capture 0.24 6 n.s FDeve Light capture 0.24 5 n.s *Index abbreviations: FDdendrTotal branch length of functional dendrogram (Petchey & Gaston 2002, 2006) FDdendr/abun Traits weighted by individual species abundances (Clark et al. 2012) FDdendr/joint.abun Distance weighted by the joint abundances of pairs of species (Clark et al. 2012) FDdendr/cv Trait axes scaled by variance (Clark et al. 2012) FDdendr/cv.abun Combination of FDrich_pg/abun and FDrich_pg/cv (Clark et al. 2012) FDdendr/cv.joint.abun Combination of FDrich_pg/joint.abun and FDrich_pg/cv (Clark et al. 2012) Hull Minimum volume circumscribed by species in multidimensional trait-space (Cornwell et al. 2006) Hull/abun Traits weighted by individual species abundances (Clark et al. 2012) Hull/cv Trait axes scaled by variance (Clark et al. 2012) Hull/cv.abun Combination of Hull/abun and Hull/cv (Clark et al. 2012) FDRao-s, FDRao-m single and multiple trait Rao’s quadratic entropy (Rao 1982, Botta-Dukát 2005, Mouillot et al. 2005, Ricotta 2005, Leps et al. 2006) FDRao/d,FDRao/b quadratic diversity of Rao without weights, densitiy-weighted, biomassweighted, respectively; Weigelt et al. 2008) FDRao-m/cv variance-weighted Rao’s quadratic entropy (Clark et al. 2012) FDeve Evenness of abundance distribution in the minimum spanning tree (Villéger et al. 2008) FDdiv Divergence of abundance distributions relative to the community centroid (Villéger et al. 2008) FDdis Mean distance of individual species to the community centroid (Laliberté & Legendre 2010) Sobs Observed species richness Strt Treatment species richness FGRobs Observed functional group richness FRGtrt Treatment functional group richness FAD functional attribute diversity (Walker et al. 1999) FRO functional regularity index (Mouillot et al. 2005) FDminvol functional richness (Villéger et al. 2008) Srich species richness FGR functional group richness Seve species evenness according to Smith & Wilson 1996 or Pielou index (Legendre & Legendre 1998), or Simpson’s evenness index PD phylogenetic diversity (Faith 1992, Cadotte et al. 2008) Simpson’s diversity (Maguuran 2004) SI Species identity CWM (Garnier et al. 2004, Violle et al. 2007) Range maximum trait value minus the minimum trait value of species within community (not weighted) Fdvar-s,Fdvar-m single and multiple trait functional diversity index (Mason et al. 2003) Stot/a Stot/b total numerical and total biomass abundabces IA Individual abundances Mean plant trait (not weighted) (Thompson et al. 2005) Functional identity (PCoA)-axes produced by Principal coordinate analysis on the trait matrix (Mouillot et al. 2011) Trait variation -coefficient of variation in trait values (Cadotte et al. 2009) NMDS -axes produced by Nonmetric multidimensional scaling performed on the trait matrix (Cadotte et al. 2009) References: Bernhardt-Römermann M, Römermann C, Sperlich S, Schmidt W. 2011 Explaining grassland biomass - the contribution of climate, species and functional diversity depends on fertilization and mowing frequency. 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