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Field sampling design
To determine if there was within-individual plasticity in floral traits between spring and summer conditions, 50 plants of each of four populations from SE Spain (Supplementary Table 1) were marked at the onset of the flowering period in late February–early March 2018. The phenotype of two flowers per individual was quantified (see below). We revisited each population during summer (June 2018) and the same floral traits were quantified in the summer flowers of those plants still flowering (117 plants; Supplementary Table 1).
Experimental design
We performed an experiment testing the effect of temperature and photoperiod in floral plasticity. It included three treatments: (1) Treatment 1, where 30 plants flowered first in conditions mimicking the spring temperature and photoperiod of Mediterranean Spain (day/night = 10/14 h, temperature = 20/10 °C, average daily temperature = 14.2 °C; see Supplementary Table 1), and afterwards in conditions mimicking a mild summer (day/night = 16/8 h, temperature = 30/20 °C, average daily temperature = 23.8 °C). (2) Treatment 2, where 30 plants flowered first in spring conditions and afterwards in hot summer conditions (day/night = 16/8 h, temperature = 35/25 °C, average daily temperature = 28.8 °C). (3) Treatment 3 (control) where 15 plants flowered first in spring conditions, and afterwards they flowered again in spring conditions. For all treatments, we removed flowers before starting the second round of flowering.
We experimentally tested the occurrence of reverse plasticity by performing a Treatment 4 in which 15 plants from Treatment 1 that flowered both during spring and summer conditions were again submitted to a period mimicking spring conditions (Supplementary Table 1).
Floral traits
We measured, both in field and experimental conditions, three floral traits during spring (or under experimental spring conditions) and in summer (or under experimental hot summer conditions). These traits were corolla size, corolla shape and corolla colour.
Corolla size of each studied flower was estimated by means of two traits: (1) corolla diameter, estimated as the distance in mm between the edge of two opposite petals. (2) Corolla tube length, the distance in mm between the corolla tube aperture and the base of the sepals. These variables were measured by using a digital calliper with ±0.1 mm of error.
Corolla shape variation was studied using geometric morphometric tools based on a landmark-based methodology43. For this, in each of the two selected flowers per individual plant studied in each of the four populations, we took a digital photo of the front view and planar position. We defined 32 co-planar landmarks covering the corolla shape and using midrib, primary and secondary veins and petal extremes and connections21,44. From the two-dimensional coordinates of landmarks, we extracted shape information and computed the generalized orthogonal least-squares Procrustes averages using the generalized procrustes analysis (GPA) superposition method. Due to the intrinsic symmetry pattern exhibited by Brassicaceae flowers, we did the analyses considering both the symmetric and asymmetric components of the shape45,46,47. We performed a principal component analysis (PCA) on the GPA-aligned specimens, and afterwards, we did a canonical variate analysis (CVA) to explore the difference in shape between season and populations43,47. Geometric morphometric analyses were performed in the R packages ‘geomorph’48, ‘Morpho’47 and ‘shapes’49,50.
To explore the relative position of the corolla shape of spring and summer flowers in the morphospace created by the species most related phylogenetically with M. arvensis, we performed a phylomorphospace. This analysis creates a plot of the main principal dimensions (the three first principal components in this case) of a tangent space for the Procrustes shape variables of the pool of species considered in the analysis and superimposed the phylogenetic tree relating this species in this plot51,52. By doing this, this analysis reveals how the shape evolves. To perform this analysis, we collected information on the corolla shape of 72 additional species belonging to the Brassicaceae tribe Brassiceae, the tribe to which M. arvensis belongs (Supplementary Table 3). We followed the same procedure as with M. arvensis, using the same number of landmarks and computing the generalized orthogonal least-squares Procrustes averages using GPA superposition method. In this analysis, we kept separate the spring and summer flowers of M. arvensis. The phylogenetic relationship between these 72 species was obtained by making a supertree using Brassicaceae trees hosted in the repository TreeBASE Web (TreeBase.org)53. We first downloaded individual phylogenetic trees from TreeBASE. Second, we concatenated all these individual trees and made a skeleton supertree. Finally, we pruned this supertree, keeping only the species included in the geometric morphometric analysis, and insert the two ‘pseudospecies’ of M. arvensis (spring and summer) as sister species. Afterwards, we projected the value of the three first components of each species on a 3D phylogenetically explicit plot. The phylogenetic analysis was performed in the R packages ‘treeman’54, ‘phangorn’55, ‘phytools’56 and ‘treebase’53, whereas the phylomorphospace analysis was performed in the R packages ‘geomorph’48.
The corolla colour of M. arvensis is produced by the accumulation of flavonoids57,58. Anthocyanin and non-anthocyanin flavonoids present in the petals of M. arvensis were analysed by ultra-performance liquid chromatography (UPLC) (ACQUITY System I-Class, Waters) coupled with quadrupole time-of-flight mass spectrometry (SYNAPT G2 HDMS Q-TOF, Waters). Analytical separation of flavonoids was performed on an Acquity HSST33 analytical column (150 mm × 2.1 mm internal diameter, 1.8 μm). A mobile phase with a gradient programme combining deionized water with 0.5% of acetic acid as solvent A and acetonitrile with 0.5% of acetic acid as solvent B was used. The initial conditions were 95% A and 5% B and a linear gradient was then established to reach 95% (v/v) of B. The total run time was 15 min and the post-delay time was 5 min. The mobile phase flow rate was 0.4 mL min−1. After chromatographic separation, a high-resolution mass spectrometry analysis was carried out in positive electrospray ionization (ESI+). The ionization source parameters using high-purity nitrogen were set at 600 L h−1 for desolvation gas flow and 30 L h−1 for cone gas flow. Spectra were recorded over the mass/charge (m/z) range of 50–1500. Data were recorded and processed using MassLynx software. The flavonoids present in the petal extracts were characterized according to their retention times, mass spectra and molecular formula, and compared with published data when available. We calculated the relative abundance of each compound in both lilac and white petal samples (N = 5 and 2, respectively) using peak intensities.
Quantification of flavonoids present in flowers of M. arvensis was performed spectrophotometrically. Two flowers of each plant used in field and experimental studies were analysed in each blooming period. We collected the four petals of a flower. Flavonoids were extracted in 1.5 ml of MeOH:HCl (99:1% v-v) and stored at −80 °C in the dark, following the procedure described in ref. 34. Two replicas of 200 μL for each sample were measured in a Multiskan GO microplate spectrophotometer (Thermo Fisher Scientific Inc., MA, USA). Main flavonoid classes present in the petals of M. arvensis are anthocyanins (cyanidin derivatives) and flavonols (kaempferol, quercetin and isorhamnetin derivatives; Supplementary Table 4)57,58. Thus, total anthocyanins and flavonols were quantified as absorbance at 520 and 350 nm, respectively. Their concentrations were calculated using five-point calibration curves of cyanidin-3-glucoside chloride (Sigma-Aldrich, Steinheim, Germany) and kaempferol-3-glucoside standards (Extrasynthese, Genay, France) and expressed as cyanidin-3-glucoside and kaempferol-3-glucoside equivalents in fresh weight (mg g−1 FW), respectively.
Objective quantification of petal colour of lilac and white petals of M. arvensis was performed by measuring their UV–Vis spectral reflectance. A petal of a flower of each colour morph (N = 10) were measured with a Jaz portable spectrometer (Ocean Optics Inc., Dunedin, FL, USA) equipped with a deuterium–tungsten halogen light source (200–2000 nm) and a black metal probe holder (6 mm diameter opening at 45°). Reflectance, relative to a white standard (WS-1-SL), was analysed with SpectraSuite v.10.7.1 software (Ocean Optics). To maximize the amount of light used in reflectance measurements and to reduce occasionally erratic reflectance values at individual nm, we set an integration time of 2 s and smoothing boxcar width of 12, respectively59.
Foliar traits
We measured, both in field and experimental conditions, five leaf traits during spring (or under experimental spring conditions) and in summer (or under experimental hot summer conditions). These traits were the specific leaf area (SLA, m2 kg−1), the leaf dry matter content (LDMC, mg g−1), the carbon-to-nitrogen content of leaves (C:N ratio), the isotopic signature of 13C in leaves (δ13C, ‰), and the CO2 compensation point and the slope of the A–Ci curve.
SLA and LDMC were measured following standard protocols60. For SLA and LDMC we collected three fully expanded and mature leaves without any visible damage (e.g., herbivory, pathogen attack) from the base, midsection and apical part of outer stems (that is, leaves were not shaded by other leaves) and at random aspects. Leaves were rehydrated overnight in the dark and subsequently weighted and scanned. Leaf area was measured using the Midebmp software (Almería, Spain). Leaves were dried in the oven at 60 °C and weighted after 72 h. From these measurements, we calculated the SLA as the one-sided area of the fully rehydrated fresh leaf divided by its dry mass, while the LDMC is the ratio between the leaf dry mass and the fully rehydrated fresh mass.
Carbon isotopic signature (δ13C), as well as the C and N relative content in leaves, were analysed in a couple of fully expanded leaves per plant without any visible damage. Oven-dry leaves were ground in a ball mill MM400 (Retsch GmbH, Haan, Germany) at 3000 rpm for 1 min to obtain a fine powder, which was stored in Eppendorf tubes. We wrapped 0.003 g of each sample in tin capsules D1008 (Elemental Microanalysis, United Kingdom). Leaf δ13C and leaf C and N relative content (in mass percentage) were determined at the Stable Isotope Analysis Lab—Centro de Instrumentación Científica (CIC) of the University of Granada (Spain) with a GC IsoLink—MS—Delta V continuous flow mass spectrometer (MS) system that includes a ISQ-QD single quadrupole MS and a gas chromatographer Trace 1310 (Thermo Fisher Scientific™, Spain). The isotopic abundance was expressed in parts per thousand (‰) as

$$delta = left( {{R}_{{mathrm{sample}}}/{R}_{{mathrm{standard}}}-1} right) times 1000$$
(1)

where Rsample and Rstandard are the molar ratios of heavy (13C) to light (12C) stable isotopes of the sample (Rsample) and an international standard (Rstandard). MS precision was 0.15‰ for carbon, based on replicate analyses of standard reference materials.
We measured responses of CO2 assimilation rate (A) versus calculated substomatal or intercellular CO2 concentration (Ci) (henceforth, A–Ci curves) to determine the instantaneous photosynthetic metabolism of plants of the intermediate C3–C4 species M. arvensis on plants grown under the two experimental conditions (N= 22 plants, spring and hot summer conditions). Gas exchange measurements were performed on one to two mature, fully expanded leaves per plant and experimental condition using a LICOR 6400 (LI-COR Biosciences, Lincoln, USA) and following the standard recommendations to correct leakage errors61,62,63. Cuvette conditions were maintained at a constant photosynthetic photon flux density (PPFD) of 1500 µmol m−2 s−1, a vapour pressure deficit (VPD) that ranged from 1.0 to More

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European and Mediterranean Plant Protection Organization (EPPO)-Euphresco, Paris, France
Baldissera Giovani & Nico Horn

Austrian Agency for Health and Food Safety (AGES), Institute for Sustainable Plant Production, Vienna, Austria
Sylvia Blümel

Food Department, Ministry of Agriculture and Forestry of Finland, Helsinki, Finland
Ralf Lopian

Better Border Biosecurity (B3), Plant and Food Research, Christchurch, New Zealand
David Teulon

North American Plant Protection Organization (NAPPO), Raleigh, NC, USA
Stephanie Bloem

Comite Regional de Sanidad Vegetal del Cono Sur (COSAVE), Dirección de Protección Vegetal, del Servicio Nacional y Sanidad Vegetal y Semillas, Asuncion, Paraguay
Cristina Galeano Martínez

Comunidad Andina (CAN), Secretaría General de la Comunidad Andina, Lima, Peru
Camilo Beltrán Montoya

Organismo Internacional Regional de Sanidad Agropecuaria (OIRSA), San Salvador, El Salvador
Carlos Ramon Urias Morales

Asia and Pacific Plant Protection Commission (APPPC), Bangkok, Thailand
Sridhar Dharmapuri

Pacific Plant Protection Organization (PPPO), Pacific Community Land Resources Division, Suva, Fiji
Visoni Timote

Near East Plant Protection Organization (NEPPO), Rabat, Morocco
Mekki Chouibani

African-Union Interafrican Phytosanitary Council (IAPSC), Yaoundé, Cameroon
Jean Gérard Mezui M’Ella

Ministry of Primary Industries (MPI), Wellington, New Zealand
Veronica Herrera & Aurélie Castinel

Department of Agriculture, Water and the Environment (DAWE), Canberra, Australian Capital Territory, Australia
Con Goletsos, Carina Moeller & Ian Naumann

European Food Safety Authority (EFSA), Parma, Italy
Giuseppe Stancanelli, Stef Bronzwaer & Sara Tramontini

Canadian Food Inspection Agency (CFIA), Ottawa, Ontario, Canada
Philip MacDonald & Loren Matheson

French Agency for Food, Environmental and Occupational Health and Safety (ANSES), Plant Health Laboratory, Angers, France
Géraldine Anthoine

Research Institute for Agriculture, Fisheries and Food (ILVO), Merelbeke, Belgium
Kris De Jonghe

Netherlands Food and Consumer Product Safety Authority (NVWA), Wageningen, the Netherlands
Martijn Schenk

Julius Kühn Institute (JKI), Braunschweig, Germany
Silke Steinmöller

National Institute for Agricultural and Food Research and Technology (INIA), Madrid, Spain
Elena Rodriguez

National Institute for Agriculture and Veterinary Research (INIAV), Oeiras, Portugal
Maria Leonor Cruz

Plant Biosecurity Research Initiative (PBRI), Hort Innovation, Melbourne, Victoria, Australia
Jo Luck

Plant Health Australia (PHA), Deakin, Canberra, Australian Capital Territory, Australia
Greg Fraser

International Plant Protection Convention (IPPC), Food and Agriculture Organization of the United Nations, Rome, Italy
Sarah Brunel, Mirko Montuori, Craig Fedchock & Jingyuan Xia

Department for Environment, Food & Rural Affairs (DEFRA), London, UK
Elspeth Steel & Helen Grace Pennington

Centre for Agriculture and Bioscience International (CABI), Nairobi, Kenya
Roger Day

French National Institute for Agricultural Research (INRA), INRA-Montpellier-CBGP, Montferrier-sur-Lez, France
Jean Pierre Rossi

B.G. wrote the manuscript. S.B., R.L., D.T., S.B., C.G.M., C.B.M., C.R.U.M., S.D., V.T., N.H., M.C., J.G.M.M., V.H., A.C., C.G., C.M., I.N., G.S., S.B., S.T., P.M.D., L.M., G.A., K.D.J., M.S., S.S., E.R., M.L.C., J.L., G.F., S.B., M.M., C.F., E.S., H.G.P., R.D., J.P.R. and J.X. contributed to the manuscript. More

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