Oikos. Appendix 1. Methods A1 OIK-03869

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1 Oikos OIK Fornoff, F., Klein, A.-M., Hartig, F., Benadi, G., Venjakob, C., Schaefer, H. M. and Ebeling, A Functional flower traits and their diversity drive pollinator visitation. Oikos doi: /oik Appendix 1 Methods A1 Detailed methods for nectar analysis Nectar of 34 flowering plant species of the Jena experiment species pool was sampled preferably in monocultures, in In the case of insufficient numbers flowering in monocultures at the sampling time, flowers of higher diversity plots where supplemented. Flowers were bagged with cotton gauze (mesh size mm) over night to prevent pollinator interventions (Klein et al. 2003). Sampling took place from 6 a.m. to 12 p.m. For nectar amino acid and sugar analysis a nectar volume of one µl was necessary, hence all available nectar was taken from each flower and in the case of insufficient amounts supplemented by nectar of flowers of the same plant individual and in rare cases neighboring plants of the same species. We used a microcapillary pipette to extract the nectar from flowers (Corbet 2003). This tool was a combination of a pipetting aid and a disposable capillary (minicaps, Hirschmann Laborgeräte GmbH & Co. KG, Eberstadt, Germany) with a holding volume of one µl. For each plant species ten samples were taken. Each was stored in a clean and autoclaved 1.5 ml Eppendorf tube (Safe-Lock Tubes, Eppendorf AG, Hamburg, Germany) which were first kept in a cool box and afterwards frozen at 20 C for storage. Plant species with too small flower openings could not be sampled (Achillea millefolium, Bellis perennis, Galium mollugo, Leucanthemum vulgare, Medicago lupulina, Trifolium dubium). Carum carvi was not available in the years 2011 and Resampling of some plant species in 2012 was necessary due to either heavy rain which diluted samples or due to insufficient nectar amounts for analyses. These plant species were Anthriscus sylvestris, Campanula patula, Glechoma hederacea, Primula veris, Ranunculus repens, Veronica chamaedrys. Nectar content was categorized into four classes, 1 representing no nectar and classes 2 4 representing evenly spaced increasing nectar amounts available per plant species. This was calculated from the mean ratio of collected nectar volume in µl and the mean number of single flowers used for each sample.

2 Nectar preparation In the laboratory, samples were diluted with 100 µl of 99.8 % ethanol for HPLC (CHROMASOLV, Sigma-Aldrich Laborchemikalien GmbH, Hannover, Germany), centrifuged for 5 min in a centrifuge (Mikro 22 R, Hettich Lab Technology, Schwerin, Germany) and washed out of the disposable capillaries into Eppendorf tubes. Afterwards, the Eppendorf tubes were stored in a DURAN -desiccator (CARL ROTH GMBH + CO. KG, Karlsruhe, Germany) to let the alcohol evaporate completely. Samples were resolved in 50 µl ultra-pure water (Siemens AG, Barsbüttel, Germany), centrifuged for 3 min and subsequently 48 µl supernatant were transferred into 250 μl pulled-point glass inserts (Agilent Technologies, Böblingen, Germany) which were positioned in one ml vials (Agilent Technologies, Böblingen, Germany) and put back into the freezer at 20 C. Amino acid and sugar analysis All samples were analyzed using high performance liquid chromatography (HPLC) from Agilent Technologies 1260 Series equipped with an Agilent 1260 Infinity Quaternary Pump (G1311C, Agilent Technologies, Böblingen, Germany), an Agilent 1260 Infinity Standard Autosampler (G1329B) and an Agilent 1260 Infinity Thermostatted Column Compartment (G1316A), for amino acids kept at 40 C and for sugars at 30 C. For amino acid analysis, the HPLC was coupled to a Zorbax Extend-C18 column ( mm, 3.5 µm, Agilent Technologies), protected by a guard column Zorbax Extend-C18 ( mm, 5 µm, Agilent Technologies), detected by an Agilent 1260 Infinity System Diode Array Detector (DAD, G4212B) with a flow rate of 1 ml min -1. Amino acids were analyzed after automatic precolumn derivatization with either ortho-phthalaldehyde (OPA, Agilent Technologies) or with 9-fluorenylmethyl chloroformate (FMOC, Agilent Technologies) for cyclic amino acids. The elution buffer contained a polar phase (mobile phase A: 1 liter ultra-pure water, 10 mm Na2HPO4, 10 mm Na2B4O7, 0.5 mm NaN3, ph 8.2) and a nonpolar phase (mobile phase B: 45% [vol/vol] acetonitrile (CHROMASOLV Plus, Sigma-Aldrich), 45% [vol/vol] methanol (CHROMASOLV, Sigma-Aldrich), and 10% [vol/vol] ultra-pure water). Further details were as given by Henderson and Brooks( 2010). Sugars were measured under isocratic conditions with a solvent consisting of 78% [vol/vol] acetonitrile and 22% [vol/vol] ultra-pure water. They were separated via a Zorbax NH2 column ( mm, 5 µm, Agilent Technologies) which was protected by a Zorbax NH2 guard column ( mm, 5 µm, Agilent Technologies). Both were coupled to an HPLC (Agilent Technologies

3 1260 Series) which was coupled to an Agilent 1260 Infinity Refractive Index Detector (RID, G1362 A) with a flow rate of 1.5 ml min-1. Protocol details were based on DIN 10758(1997). For either amino acid or sugar analysis every five samples 17 amino acids (Amino Acid Standard solution (alanine, arginine, aspartic acid, cystine, glutamic acid, glycine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, proline, serine, threonine, tyrosine, valine), Sigma-Aldrich Laborchemikalien GmbH) or three carbohydrates (sucrose, fructose and glucose, HPLC grade, Sigma-Aldrich Laborchemikalien GmbH) were used as external standards in four different concentrations. Total concentrations of amino acids and sugars were determined from those compounds that were identified. For data analyses and HPLC-control an Agilent ChemStation for LC 3D systems (Agilent Technologies) was used.

4 Figure A1. The Jena Experiment in full flower in May Core areas (central cm) of main plots where monitored for pollinator flower interactions.

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6 Figure A2. Community weighted means of all potential traits in a correlation matrix depicted as Spearman correlation coefficients (upper right tiles), data distribution histogram (diagonal panele), pairwise plotting of raw data with LOESS smoother (lower right tiles). Abreviations represent: flower cover (cover), flower symmetry radial (sym.radm), nectar access open (a.openm), flower area (aream), flower height (heigm), flowering length (fllengthm), stamen location (stamlocm), stamen number (stamnrm), nectar amount (necm), pollen amount (pollm), amino acid volume (asm), sugar amount (sugarm), colour white (whitem), colour blue (bluem), colour green (greenm), colour yellow (yellow), colour red (redm), ultra violet (uvm). 7

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8 Figure A3. Diversity (FD trait ) of all potential traits in a correlation matrix depicted as Spearman correlation coefficients (upper right tiles), data distri bution histogram (diagonal panele), pairwise plotting of raw data with LOESS smoother (lower right tiles). Abbreviations represent: flower cover (c over) and FD trait of colour (colq), flower symmetry (sym.rq), nectar access (a.openq), flower area (areaq), flower height (heigq), flowering length (fllengthq), stamen location (stamlocq), stamen number (stamnrq), nectar amount (necq), pollen amount (pollq), amino acid volume (asq), sugar amount (sugq), ultra violet (uvq).

9 Table A1. Flower trait measures compiled for all 44 species used in this analyses.

10 Plant species name flower symm etry radial [yes/n o] nect ar acce ss ope n [yes/ no] mas s bloo m [mo nth - 4] inflores cence area [mm²] flo wer hei ght [cm ] Achillea millefolium ,23 22, 27 Ajuga reptans ,11 9,4 1 Anthriscus ,95 58, sylvestris 5 Bellis perennis ,3 9,7 4 Campanula ,04 29, patula 1 Carum carvi ,00 40, 00 Cardamine ,44 16, pratensis 2 Centaurea ,5 26, jacea 5 Cirsium ,79 46, oleraceum 65 Crepis biennis ,25 44, 95 Daucus carota ,25 34, 05 Galium ,49 21, mollugo 8 Geranium ,6 27, pratense 06 Glechoma ,69 5,0 hederacea 5 flowe ring lengt h [days ] positi on of stam ens out [yes/ no] stam ens num ber nect ar amo unt [low, med, high, very high ] polle n amo unt high [yes/ no] total nectar amino acid concent ration [nmol/m L] total nectar sugar concentration[ nmol/ml] flower reflect ance in white [yes/n o] flower peak reflect ance in blue [yes/n o] flower peak reflect ance in green [yes/n o] flower peak reflect ance in yellow [yes/n o] flower peak reflect ance in red [yes/n o] 51, NA NA , , , NA NA , NA NA NA , , , , , , NA NA , , uv reflect ance (biolflo r) [intege r]

11 Heracleum sphondylium ,79 34, 6 Knautia ,52 39, arvensis 5 Lathyrus ,68 7,1 pratensis 8 Leontodon ,54 28, autumnalis 25 Leontodon ,47 29, hispidus 84 Leucanthemu ,85 35, m vulgare 85 Lotus ,48 12, corniculatus 8 Medicago ,43 13, lupulina 62 Medicago ,14 37, varia 75 Onobrychis ,00 53, vicifolia 15 Pastinaca ,78 49, sativa 8 Pimpinella ,96 22, major 2 Plantago ,57 15, lanceolata 8 Plantago ,88 15, media 66 Primula veris ,87 6,9 1 Prunella ,73 13, vulgaris 57 Ranunculus ,73 16, acris 59 Ranunculus ,25 22, repens 3 9, , , , , , NA NA , , NA NA , , , , , NA NA , NA NA , , , ,

12 Rumex acetosa ,25 25, 73 Sanguisorba ,56 39, officinalis 85 Taraxacum ,36 8,9 officinale 6 Tragopogon ,23 35, pratensis 66 Trifolium ,88 14, campestre 74 Trifolium ,71 4,7 dubium 1 Trifolium ,22 13, fragiferum 00 Trifolium ,86 13, hybridum 24 Trifolium ,76 17, pratense 45 Trifolium ,62 10, repens 72 Veronica ,92 4,6 chamaedrys 2 Vicia cracca ,77 16, 87 21, NA NA , , , , , NA NA , , , , , ,

13 Figure A4. The probability of encountering a flower within a plot increases with increasing sown plant species richness. (Binomial linear model; DF = 737, z = 5.19, p < 0.001). Black line indicates model fit, grey shading represents ±1SE.To represent best the measured range (1, 2, 4, 8, 16 and 60) the x-axes is on log 10 scale. References Corbet, S. A Review article Nectar sugar content : estimating standing crop and secretion rate in the field. Apidologie 34: DIN Deutsches Institut Für Normierung. Henderson, J. W. and Brooks, A Improved amino acid methods using Agilent ZORBAX Eclipse Plus C18 columns for a variety of Agilent LC instrumentation and separation goals. Agilent Technologies, Wilmington. Klein, A.-M. et al Pollination of Coffea canephora in relation to local and regional agroforestry management. J. Appl. Ecol. 40: