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Seed sourceSeeds of a segregating GR B. scoparia population identified from a wheat field (45°54′54.76″N; 108°14′44.15″W) in 2013 in Hill County, Montana, USA (designated as MT009) were used. The field was under a continuous no-till wheat-fallow rotation for  > 8 years and had a history of repeated glyphosate use (at least 3 applications per year) for weed control during the summer fallow phase prior to winter wheat planting. The permission of land owner was obtained prior to B. scoparia seed collection. All experimental research and field studies on plants, including the collection of plant material complied with the Montana State University guidelines and state/US legislation. Seeds of the field-collected population were used to generate GS and GR B. scoparia subpopulations through recurrent group selection procedure as described below.Development of GS and GR subpopulationsField collected seeds of MT009 population were sown on the surface of plastic trays (53 by 35 by 10 cm) filled with commercial potting soil (VERMISOIL, Vermicrop Organics, 4265 Duluth Avenue, Rocklin, CA, USA) in a greenhouse in the fall of 2013 at the Montana State University Southern Agricultural Research Center (MSU-SARC) near Huntley, MT, USA. Growth conditions in greenhouse were maintained at 25/22 ± 2 °C day/night temperatures and 16/8 h day/night photoperiods supplemented with metal halide lamps (450 μmol m-2 s-1). After emergence, approximately 200 uniform seedlings were individually transplanted in plastic pots (10-cm diam) containing the same potting mixture and grown for 6 weeks. A set of three clones (3 shoot cuttings) from each plant were then prepared and transplanted in plastic pots (10-cm diam) as described by Kumar and Jha22. At the 8- to 10-cm height, all cloned seedlings were separately treated with 435 (0.5×), 870 (1×), and 1740 (2×) g ae ha−1 of glyphosate (Roundup Powermax, Bayer Crop Science, Saint Louis, MO, USA) where 1× = field-use rate of glyphosate. All three glyphosate treatments included ammonium sulfate (2% w/v). Glyphosate applications were made using a cabinet spray chamber (Research Track Sprayer, De Vries Manufacturing, RR 1 Box 184, Hollandale, MN, USA) equipped with an even flat-fan nozzle tip (Teejet 8001EXR, Spraying System Co., Wheaton, IL, USA), calibrated to deliver 140 L ha−1 of spray solution at 276 kPa. Treated seedlings were returned to the greenhouse, watered as needed, and fertilized [Miracle-Gro water soluble fertilizer (24-8-16), Scotts Miracle-Gro Products Inc., 14111 Scottslawn Road, Marysville, OH, USA] bi-weekly to maintain good plant growth. At 21 days after treatment, clones surviving the 2× rate of glyphosate were considered as ‘glyphosate-resistant (GR)’ and the clones that did not survive 1× rate of glyphosate were considered as ‘glyphosate-susceptible (GS)’. The parent B. scoparia plants corresponding to survived (resistant) or not-survived (susceptible) clones were transplanted separately in 20-L plastic pots (group of 3 to 4 plants pot−1) containing same potting soil for seed production. All 3- to 4 plants in each pot were collectively covered with a single pollination bag (DelStar Technologies, Inc., 601 Industrial drive, Middletown, DE, USA) prior to flower initiation to restrict cross-pollination between GR and GS plants. At maturity, seeds from the respective GR and GS parent plants were collected and cleaned separately using an air column blower. The collected seeds from GR plants were subjected to three generations of recurrent group selection with the 2× rate of glyphosate in each generation. Seeds of GS plants were also subjected to recurrent group selection for three generations without glyphosate. Progenies of the GS plants were grown and sprayed with 1× rate of glyphosate to confirm the susceptibility to glyphosate in each generation23. This procedure allowed the development of relatively genetically homogenous GR and GS subpopulations from within a single B. scoparia population.Determination of EPSPS gene copy numberPreviously established protocols were adopted to estimate the relative EPSPS gene copy number in seedlings of GR and GS subpopulations through quantitative real-time polymerase chain reaction (qPCR)16,17,18. The ALS gene was used as reference since the relative ALS gene copy number and transcript abundance did not vary across B. scoparia samples17,18,29. Relative EPSPS:ALS gene copy number is a ratio of EPSPS to ALS PCR product fluorescence. Due to small differences in amplicon size, qPCR run conditions, and fluorescence detection, the values presented were estimates of relative gene copy number29.A total of 600 seedlings from the GR (450 seedlings) and GS (150 seedlings) B. scoparia subpopulations (developed by recurrent group selection) were grown in a greenhouse at MSU-SARC near Huntley, MT, USA in 2015 and 2016 to select enough plants for the field study each year. At 4-to 6-cm height, young leaf tissues (100 mg) from each seedling were sampled, frozen with liquid nitrogen and ground into powder using mortar and pestle. Genomic DNA were extracted from the tissue samples using the protocol from Qiagen Dneasy plant mini kit (Qiagen Inc., Valencia, CA, USA). Genomic DNA quantity and quality were determined using a Smartspec Plus spectrophotometer (Bio-Rad Company, CA, USA) and gel electrophoresis with 1% agarose, respectively. High quality genomic DNA (260/280 ratio of ≥ 1.8) were used to determine the relative EPSPS gene copy number. Two sets of primers to amplify the EPSPS and ALS genes, the final reaction volume and reagents used for each qPCR reaction, and the qPCR conditions used in this study were the same as previously described by Kumar and Jha22. Each qPCR reaction was performed on a Bio-Rad 96-well PCR plate in triplicates and fluorescence was detected using CFX Connect Real-Time PCR detection system. A negative control consisting of 250 nM of each forward and reverse primer, 1× Perfecta SYBR Green supermix, and deionized water with no DNA template was included. The EPSPS genomic copy number relative to ALS gene was estimated by ΔCT method (ΔCT = CT, ALS-CT, EPSPS)18,29. The relative increase in the EPSPS gene copy number was calculated as 2ΔCT.Survival and fecundity traits of GR and GS B. scoparia subpopulationsSeedlings (4- to 6-cm tall) of GR and GS B. scoparia subpopulations with known EPSPS gene copy numbers were transplanted into a fallow field in the summer of 2015 and 2016 at the MSU-SARC near Huntley, MT, USA. All transplanted B. scoparia seedlings were equally spaced at 1.5 m apart from each other and all plants were fertilized biweekly [2 to 3 g of MIRACLE-GRO water soluble fertilizer (24-8-16)] and irrigated as and when needed to avoid moisture stress. Experiments were conducted with a factorial arrangement of treatments (Factor A and Factor B) in a randomized complete block design, with 6 replications. Each transplanted B. scoparia seedling was an experimental unit. The factor A (4 levels) was comprised of B. scoparia plants with 1, 2–4, 5–6, and ≥ 8 EPSPS gene copy numbers, which were categorized as susceptible, low, moderate, and highly resistant plants, respectively based on their percent visible injury response to glyphosate. The factor B (ten levels) was comprised of increasing rates of glyphosate applied as single or sequential applications. Current labels of glyphosate allow a total of 3954 g ae ha−1 in split POST applications in GR sugar beet. As per the label, the maximum glyphosate rate of 2214 g ae ha−1 is allowed from crop emergence to 8-leaf stage of sugar beet and 1740 g ae ha−1 of glyphosate from 8-leaf stage to canopy closure or 30 days prior to sugar beet harvest. Hence, the tested total glyphosate rates were 0, 108, 217, 435, 870, 1265, 1740 [870 followed by ( +) 870], 2214 [1265 + 949], 3084 [1265 + 949 + 870], and 3954 [1265 + 949 + 870 + 870] g ae ha−1 along with ammonium sulfate (2% w/v). Sequential applications were made at 7- to 14-day intervals, with first application at 8- to 10-cm tall B. scoparia seedlings using a CO2-operated backpack sprayer fitted with a single AIXR 8001 flat-fan nozzle calibrated to deliver 94 L ha−1. Glyphosate rates and applications timings were selected to simulate the 2-leaf, 6-leaf, 8–10 leaf, and the canopy closure stage of GR sugar beet.Data collectionPercent visible control (relative to the non-treated) on a scale of 0 to 100 (0 means no control and 100 means complete plant death30) for each individual plant (240 plants total each year) were assessed at 7, 14, and 21 days after glyphosate treatment. Data on number of days from transplanting to 50% flowering (half of the inflorescences from each plant were covered with visible flowers) and seed set (seeds on half of the inflorescences from each plant were turned brown) were recorded for an individual plant. Each plant was covered with a pollination bag (DelStar Technologies, Inc., 601 Industrial drive, Middletown, DE, USA) prior to flowering to prevent any cross-pollination. At the time of flowering, pollens from each survived plant were collected in early morning hours (between 8 to 10 am). At maturity, each individual plant was harvested and threshed to determine 1000-seed weight and seeds plant−1.Pollen and progeny seed viabilityPollens and seeds collected from individual B. scoparia plants (240 plants total each year) were tested for viability using a tetrazolium test. Pollens were collected in petri dishes by shaking the whole plant at the time of flowering. Four sub-samples of pollens from each petri dish were transferred into glass slides. The pollens in the glass slides were soaked with a tetrazolium chloride solution (10 g L−1), sealed with a cover slip using a nail polish and were incubated at room temperature for an hour. Viable (red) and non-viable pollens (yellow/white) were counted using a simple microscope. The physical structure of viable and non-viable pollens was also checked for any deformity using a compound microscope. Pollen viability for individual plants (240 plants total each year) was calculated as percent viable pollens of the total number of pollens counted.For seed viability test, twenty-five intact seeds collected from each individual plant (240 plants total each year) from the field were evenly placed in between two layers of filter papers (WHATMAN Grade 2, SigmaAldrich, St Louis, MO, USA) inside a 10-cm-diameter petri dish. Seeds were soaked with a 5-ml of distilled water and the filter papers were kept moist for the entire duration of the germination test. Light is not required for B. scoparia seed germination31, so the petri dishes were wrapped with a thin aluminum foil and placed inside an incubator (VMR International, Sheldon Manufacturing, Cornelius, OR, USA) with alternating day/night temperatures set to 20/25 °C23. Seeds with a visible uncoiled radicle tip longer than the seed diameter was considered germinated32,33. Radicle length was measured from three randomly selected germinated seeds 24 h after incubation to test the seedling vigor. The number of germinated seeds in each petri dish were counted daily until no further germination was observed for 10 consecutive days. Non-germinated seeds were tested for viability by soaking the seeds with tetrazolium chloride solution (10 g L−1) for 24 h23,34. Seeds with a red-stained embryo examined under a dissecting microscope (tenfold magnification) were considered viable35. Seed viability was expressed as the percentage of total viable seeds.Relative fitness (w)Fitness is the evolutionary potential for success of a genotype based on survival, competitive ability, and reproduction. Individuals with the greatest number of offspring and with the most genes contributing to the gene pool of a population are considered most fit genotypes36. Fitness of a genotype is determined by comparison of its vigor, productivity or competitiveness relative to the other genotype by quantifying specific traits such as seed dormancy, flowering date, seedling vigor, seed production, and other factors that can possibly influence the survival and reproductive success of a genotype36,37. In this study, relative fitness (w) of GR B. scoparia was calculated as the reproductive rate (seed production plant−1) of a resistant genotype (B. scoparia plants with 2–4, 5–6, and ≥ 8 EPSPS gene copies) relative to the maximum reproductive rate of the susceptible genotype (B. scoparia plants with 1 EPSPS gene copy) in the population. The relative fitness (w) of susceptible plants was assumed to be one.Statistical analysesA natural logarithm transformation was performed on data for time to 50% flowering, time to seed set, seeds plant−1. An arcsine square root transformation was performed on data for pollen viability, visible control, seed viability, and relative fitness (w) before subjecting to analysis of variance, however all data were presented in their back-transformed values. No transformation was needed for 1000-seed weight and radicle length data. Experimental year, B. scoparia plants with different EPSPS copy number groups, glyphosate rate, and their interactions were considered fixed effects and replication nested within a year was considered as a random effect in the model. Data on percent visible control, time to 50% flowering, pollen viability, time to seed set, 1000-seed weight, and seeds plant−1, seed viability and radicle length were subjected to ANOVA using Proc Mixed in SAS (SAS version 9.4, SAS Institute, Cary, NC, USA) to test the significance of experimental run, treatment factors, and interactions. The ANOVA assumptions for normality of residuals and homogeneity of variance were tested using Proc Univariate and PROC GLM in SAS. Means were separated using Tukey–Kramer’s HSD with α = 0.05. Furthermore, data on percent visible control and seeds plant-1 for each group of B. scoparia plants with different EPSPS gene copy number were regressed against total glyphosate rates using a four-parameter log-logistic model Eq. (1)38,39:$$Y=c+{d-c/{1+mathrm{exp}[bleft(mathrm{log}left(xright)-mathrm{log}left(ED50right)right)]}$$
(1)
where Y is the percent visible control or seed production plant−1 (% of nontreated); d is the upper asymptote (the highest estimated % control or % seed reduction); c is the lower asymptote (the lowest estimated % control or % seed reduction); ED50 is the effective rate of glyphosate needed to achieve 50% control or 50% reduction in seed production; and b denotes the slope around the inflection point “ED50.” Slope parameter (b) indicates the response rate of each group of B. scoparia plants with different EPSPS gene copy number to glyphosate rates (i.e., a slope with a large negative value suggests a rapid response of selected B. scoparia group). The Akaike Information Criterion (AIC) was used to select the nonlinear four-parameter model. A lack-of-fit test (P  > 0.10) was used to confirm that the nonlinear regression model Eq. (1) described the response data for each B. scoparia group38. Parameter estimates, ED90, and SR99 values (i.e. effective rate required for 90% control or effective rate required for 99% reduction in seed production) for each group of B. scoparia plants with different EPSPS gene copy number were determined using the ‘drc’ package in R software37,39. Parameter estimates of B. scoparia groups were compared using the approximate t-test with the ‘compParm’ and ‘EDcomp’ functions in the ‘drc’ package of the R software39,40. More

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Institute of Silviculture, University of Natural Resources and Life Sciences, Vienna (BOKU), Peter-Jordan Str. 82, 1190, Wien, AustriaElisabeth PötzelsbergerEuropean Forest Institute, Platz der Vereinten Nationen 7, 53113, Bonn, GermanyElisabeth PötzelsbergerForest Entomology, Swiss Federal Research Institute WSL, Zürcherstrasse 111, 8903, Birmensdorf, SwitzerlandMartin M. GossnerETH Zurich, Department of Environmental Systems Science, Institute of Terrestrial Ecosystems, 8092, Zurich, SwitzerlandMartin M. GossnerForest Protection, Swiss Federal Research Institute WSL, Zürcherstrasse 111, 8903, Birmensdorf, SwitzerlandLudwig Beenken & Sophie StrohekerFaculty of Forestry, University of Agriculture, Al. 29 Listopada 46, 31-425, Kraków, PolandAnna Gazda & Srđan KerenForest Research, Forestry Commission, Northern Research Station, Roslin, EH25 9SY, Great BritainMichal PetrNatural Resources Institute Finland, Luke, Latokartanonkaari 9, 00790, Helsinki, FinlandTiina YliojaFEM Research and Innovation Centre, Fondazione Edmund Mach, Via E. Mach 1, 38010, San Michele all’Adige, ItalyNicola La PortaThe EFI Project Centre on Mountain Forests MOUNTFOR, Via E. Mach 1, 38010, San Michele all’Adige, ItalyNicola La PortaForest Research Institute, Hellenic Agricultural Organization Demeter, Vassilika, 57006, GreeceDimitrios N. AvtzisWalloon Public service (SPW), 23 av Maréchal Juin, 5030, Gembloux, BelgiumElodie Bay & Marjana WestergrenSlovenian Forestry Institute, Vecna pot 2, 1000, Ljubljana, SloveniaMaarten De Groot & Nikica OgrisInstitute of Forestry and Rural Engineering, Estonian University of Life Sciences, Fr. R. Kreutzwaldi 5, 51006, Tartu, EstoniaRein DrenkhanFaculty of Forestry, “Ștefan cel Mare” University of Suceava, Universității Street 13, 720229, Suceava, RomaniaMihai-Leonard DudumanInstitute for Plant Protection in Horticulture and Forests, Julius Kuehn Institute (Federal Research Centre for Cultivated Plants), Messeweg 11/12, 38104, Braunschweig, GermanyRasmus EnderleDepartment of Entomology, Phytopathologyy and Game fauna, Forest Research Institute – Bulgarian Academy of Sciences, St. Kliment Ohridski 132, 1756, Sofia, BulgariaMargarita GeorgievaDepartment of Fungal Plant Pathology in Forestry, Agriculture and Horticulture, Norwegian Institute of Bioeconomy Research (NIBIO), Innocamp Steinkjer, skolegata 22, 7713, Steinkjer, NorwayAri M. HietalaInstitute for National and International Plant Health, Julius Kuehn Institute (Federal Research Centre for Cultivated Plants), Messeweg 11/12, 38104, Braunschweig, GermanyBjörn HoppeBiodiversité, Gènes et Communautés (BioGeCo), French National Institute for Agriculture, Food, and Environment (INRAE), University Bordeaux, F-33610, Cestas, FranceHervé JactelDepartment of Forestry and Renewable Forest Resources, Biotechnical Faculty, University of Ljubljana, Vecna pot 83, 1000, Ljubljana, SloveniaKristjan JarniFaculty of Forestry, University of Banja Luka, Bulevar vojvode Stepe Stepanovica 75A, 51000, Banja Luka, Bosnia and HerzegovinaSrđan KerenForest Research Institute, National Agricultural Research and Innovation Centre, Farkassziget 3, H-4150, Püspökladány, HungaryZsolt KeseruDepartment of Ecology and Biogeography, Nicolaus Copernicus University, Lwowska 1, PL-87-100, Toruń, PolandMarcin Koprowski & Radoslaw PuchalkaCentre for Climate Change Research, Nicolaus Copernicus University, Lwowska 1, PL-87-100, Toruń, PolandMarcin Koprowski & Radoslaw PuchalkaInstitute of Plant Genetics and Biotechnology SAS, Akademicka 2, P. O. Box 39A, SK-950 07, Nitra, SlovakiaAndrej KormuťákUnidade de Xestión Ambiental e Forestal Sostible, Universidade de Santiago de Compostela, Campus de Lugo, 27002, Lugo, SpainMaría Josefa LombarderoLaboratory of Environmental Toxicology, National Institute of Chemical Physics and Biophysics (NICPB), Akadeemia tee 23, 12618, Tallinn, EstoniaAljona LukjanovaFaculty of Forest Science and Ecology, Agriculture Academy, Vytautas Magnus University, Studentu 11, Akademija, 53361, Kaunas, LithuaniaVitas MarozasMediterranean Facility, European Forest Institute, Sant Pau Art Nouveau Site, Sant Antoni M. Claret 167, 08025, Barcelona, SpainEdurad MauriCentro di Ricerca Foreste e Legno, Council for agricultural research and analysis of the agricultural economy (CREA), Viale Santa Margherita, 80, 52100, Arezzo, ItalyMaria Cristina MonteverdiNorwegian Institute of Bioeconomy Research (NIBIO), P.O. Box 115, NO-1431, Ås, NorwayPer Holm Nygaard“Marin Drăcea” National Research-Development Institute in Forestry, Station Câmpulung Moldovenesc, Calea Bucovinei, 73bis, 725100, Câmpulung Moldovenesc, RomaniaNicolai OleniciEFI Atlantic, European Forest Institute, 69, Route de Arcachon, F-33610, Cestas, FranceChristophe OrazioIEFC Institut Européen de la Forêt Cultivée, 69, Route de Arcachon, F-33610, Cestas, FranceChristophe OrazioDepartment of Forest Protection, Austrian Federal Research Centre for Forests, Natural Hazards and Landscape (BFW), Seckendorff-Gudent-Weg 8, 1131, Vienna, AustriaBernhard PernyCentre for Environmental and Marine Studies (CESAM) & Department of Biology, University of Aveiro, 3810-193, Aveiro, PortugalGlória PintoCoillte Unit 27, Coillte Forest, Danville Business Park, Kilkenny, R95 YT95, IrelandMichael PowerDepartment of Geosciences and Natural Resource Management, University of Copenhagen, Rolighedsvej 23, DK-1958, Frederiksberg C., GermanyHans Peter RavnUCD Forestry, School of Agriculture and Food Science, University College Dublin, UCD Forestry, School of Agriculture and Food Science, University College Dublin, D04 V1W8, Dublin, IrelandIgnacio SevillanoForest Research, Forestry Commission, Northern Research Station, Roslin, Midlothian, EH25 9SY, Great BritainPaul TaylorInstitute of Mediterranean Forest Ecosystems, Hellenic Agricultural Organization “Demeter”-, Terma Alkmanos, 11528, Athens, GreecePanagiotis TsopelasFaculty of Forestry and Wood Technology, Mendel University, Zemědělská 3, 613 00, Brno, Czech RepublicJosef UrbanSiberian Federal University, Svobodnyy Ave, 79, 660041, Krasnoyarsk, RussiaJosef UrbanInstitute of Forestry and Rural Engineering, EstonianUniversity of Life Sciences, Kreutzwaldi 5, 51006, Tartu, EstoniaKaljo VoolmaSouthern Swedish Forest Research Center, PO Box 49, SE-230 53, Alnarp, SwedenJohanna WitzellPolissya Branch, Ukrainian Research Institute of Forestry and Forest Melioration, Neskorenych st. 2, Dovzhik, UkraineOlga ZborovskaInstitute of Lowland Forestry and Environment (ILFE), University of Novi Sad, Antona Cehova 13d, 21 000, Novi Sad, SerbiaMilica ZlatkovicE.P., A.G, M.P., T.Y. and N.L.P. developed the concept and design of the study and organised the data collection, E.P., M.M.G. and L.B. managed the database, homogenised and cleaned the data, E.P. and M.M.G. performed the analysis and all other co-authors collected and synthesised the information for their respective countries. E.P., M.M.G. and L.B. wrote the paper and all other co-authors reviewed the paper. More