Keeley, P. E., Carter, C. H. & Thullen, R. J. Influence of planting date on growth of Palmer amaranth (Amaranthus palmeri). Weed Sci. 35, 199–204 (1987).
Christoffers, M. J. Genetic aspects of herbicide-resistant weed management. Weed Technol. 13, 647–652 (1999).
Gressel, J. Low pesticide rates may hasten the evolution of resistance by increasing mutation frequencies. Pest Manage. Sci. 67, 253–257 (2011).
Dominguez-Valenzuela, J. A. et al. First confirmation and characterization of target and non-target site resistance to glyphosate in Palmer amaranth (Amaranthus palmeri) from Mexico. Plant Physiol. Biochem. 115, 212–218 (2017).
Gaines, T. A. et al. Gene amplification confers glyphosate resistance in Amaranthus palmeri. Proc. Natl. Acad. Sci. 107, 1029–1034 (2010).
Kaundun, S. S. et al. Evolution of target-site resistance to glyphosate in an Amaranthus palmeri population from Argentina and its expression at different plant growth temperatures. Plants 8, 512 (2019).
Lacoste, M. & Powles, S. Beyond modelling: considering user-centred and post-development aspects to ensure the success of a decision support system. Comput. Electron. Agric. 121, 260–268 (2016).
Culpepper, A., Whitaker, J., MacRae, A. & York, A. Distribution of glyphosate-resistant Palmer amaranth (Amaranthus palmeri) in Georgia and North Carolina during 2005 and 2006. J. Cotton Sci. 12, 306–310 (2008).
Patzoldt, W. L., Tranel, P. J. & Hager, A. G. A waterhemp (Amaranthus tuberculatus) biotype with multiple resistance across three herbicide sites of action. Weed Sci. 53, 30–36 (2005).
Kaundun, S., Hutchings, S. J., Dale, R., Bailly, G. & Glanfield, P. Syngenta ‘RISQ’ test: a novel in-season method for detecting resistance to post-emergence ACCase and ALS inhibitor herbicides in grass weeds. Weed Res. 51, 284–293 (2011).
Koger, C. H. et al. Assessment of two nondestructive assays for detecting glyphosate resistance in horseweed (Conyza canadensis). Weed Sci. 53, 559–566 (2005).
Norsworthy, J. K., Scott, R. C., Smith, K. L. & Oliver, L. R. Response of Northeastern Arkansas Palmer amaranth (Amaranthus palmeri) accessions to glyphosate. Weed Technol. 22, 408–413 (2008).
Mithila, J., Hall, J. C., Johnson, W. G., Kelley, K. B. & Riechers, D. E. Evolution of resistance to auxinic herbicides: historical perspectives, mechanisms of resistance, and implications for broadleaf weed management in agronomic crops. Weed Sci. 59, 445–457 (2011).
Spaunhorst, D. J. Utilization of dicamba for the control of glyphosate-resistant giant ragweed (Ambrosia trifida L.) and waterhemp (Amaranthus rudis Sauer.) Masters thesis, University of Missouri-Columbia, (2013).
Steckel, L. E., Craig, C. C. & Hayes, R. M. Glyphosate-resistant horseweed (Conyza canadensis) control with glufosinate prior to planting no-till cotton (Gossypium hirsutum). Weed Technol. 20, 1047–1051 (2006).
Lindsay, K. et al. PAM: decision support for long-term Palmer amaranth (Amaranthus palmeri) control. Weed Technol. 31, 915–927 (2017).
Neve, P., Norsworthy, J. K., Smith, K. L. & Zelaya, I. A. Modelling evolution and management of glyphosate resistance in Amaranthus palmeri. Weed Res. 51, 99–112 (2011).
Mohseni-Moghadam, M., Schroeder, J. & Ashigh, J. Mechanism of resistance and inheritance in glyphosate resistant Palmer amaranth (Amaranthus palmeri) populations from New Mexico, USA. Weed Sci. 61, 517–525 (2013).
Singh, S., Singh, V., Lawton-Rauh, A., Bagavathiannan, M. V. & Roma-Burgos, N. EPSPS gene amplification primarily confers glyphosate resistance among Arkansas Palmer amaranth (Amaranthus palmeri) populations. Weed Sci. 66, 293–300 (2018).
Beres, Z. T. et al. Target-site EPSPS Pro-106-Ser mutation in Conyza canadensis biotypes with extreme resistance to glyphosate in Ohio and Iowa, USA. Sci. Rep. 10, 7577. https://doi.org/10.1038/s41598-020-64458-7 (2020).
Palma-Bautista, C. et al. Reduced absorption and impaired translocation endows glyphosate resistance in Amaranthus palmeri harvested in glyphosate-resistant soybean from Argentina. J. Agric. Food Chem. 67, 1052–1060 (2019).
Brunharo, C. A. D. C. G., Morran, S., Martin, K., Moretti, M. L. & Hanson, B. D. EPSPS duplication and mutation involved in glyphosate resistance in the allotetraploid weed species Poa annua L.. Pest Manage. Sci. 75, 1663–1670. https://doi.org/10.1002/ps.5284 (2019).
Chen, J. et al. Glyphosate resistance in Eleusine indica: EPSPS overexpression and P106A mutation evolved in the same individuals. Pestic. Biochem. Physiol. 164, 203–208. https://doi.org/10.1016/j.pestbp.2020.01.014 (2020).
Kaundun, S. S. An aspartate to glycine change in the carboxyl transferase domain of acetyl CoA carboxylase and non-target-site mechanism (s) confer resistance to ACCase inhibitor herbicides in a Lolium multiflorum population. Pest Manage. Sci. 66, 1249–1256 (2010).
Lu, H., Yu, Q., Han, H., Owen, M. J. & Powles, S. B. Metribuzin resistance in a wild radish (Raphanus raphanistrum) population via both psbA gene mutation and enhanced metabolism. J. Agric. Food Chem. 67, 1353–1359 (2019).
Perotti, V. E. et al. A novel triple amino acid substitution in the EPSPS found in a high-level glyphosate-resistant Amaranthus hybridus population from Argentina. Pest Manage. Sci. 75, 1242–1251 (2019).
Heap, I. & Duke, S. O. Overview of glyphosate-resistant weeds worldwide. Pest Manage. Sci. 74, 1040–1049 (2018).
Koo, D.-H. et al. Extrachromosomal circular DNA-based amplification and transmission of herbicide resistance in crop weed Amaranthus palmeri. Proc. Natl. Acad. Sci. 115, 3332–3337 (2018).
Gaines, T. A., Patterson, E. L. & Neve, P. Molecular mechanisms of adaptive evolution revealed by global selection for glyphosate resistance. New Phytol. 223, 1770–1775 (2019).
Gressel, J. Perspective: present pesticide discovery paradigms promote the evolution of resistance—learn from nature and prioritize multi-target site inhibitor design. Pest Manage. Sci. 76, 421–425. https://doi.org/10.1002/ps.5649 (2020).
Liu, C. et al. A generalised individual-based algorithm for modelling the evolution of quantitative herbicide resistance in arable weed populations. Pest Manage. Sci. 73, 462–474 (2017).
Ashworth, M. B., Walsh, M. J., Flower, K. C., Vila-Aiub, M. M. & Powles, S. B. Directional selection for flowering time leads to adaptive evolution in Raphanus raphanistrum (Wild radish). Evol. Appl. 9, 619–629 (2016).
Bagavathiannan, M. V. & Davis, A. S. An ecological perspective on managing weeds during the great selection for herbicide resistance. Pest Manage. Sci. 74, 2277–2286 (2018).
Booth, B. D. & Swanton, C. J. Assembly theory applied to weed communities. Weed Sci. 50, 2–13 (2002).
Délye, C., Jasieniuk, M. & Le Corre, V. Deciphering the evolution of herbicide resistance in weeds. Trends Genet. 29, 649–658 (2013).
Heap, I. The International Herbicide-Resistant Weed Database (accessed 29 May 2020). www.weedscience.org.
Carroll, S. P., Hendry, A. P., Reznick, D. N. & Fox, C. W. Evolution on ecological time-scales. Funct. Ecol. 21, 387–393 (2007).
Neve, P. Gene drive systems: do they have a place in agricultural weed management?. Pest Manage. Sci. 74, 2671–2679 (2018).
Partel, V., Charan Kakarla, S. & Ampatzidis, Y. Development and evaluation of a low-cost and smart technology for precision weed management utilizing artificial intelligence. Comput. Electron. Agric. 157, 339–350 (2019).
Singh, V. et al. Chapter three—unmanned aircraft systems for precision weed detection and management: prospects and challenges. In Advances in Agronomy (ed. Sparks, D. L.) 93–134 (Academic Press, Cambridge, 2020).
Walsh, M. J. et al. Opportunities and challenges for harvest weed seed control in global cropping systems. Pest Manage. Sci. 74, 2235–2245 (2018).
Daszak, P. et al. Interdisciplinary approaches to understanding disease emergence: the past, present, and future drivers of Nipah virus emergence. Proc. Natl. Acad. Sci. 110, 3681–3688 (2013).
Phillipson, J. & Symes, D. Science for sustainable fisheries management: an interdisciplinary approach. Fish. Res. 139, 61–64 (2013).
Shaman, J., Solomon, S., Colwell, R. R. & Field, C. B. Fostering advances in interdisciplinary climate science. Proc. Natl. Acad. Sci. 110, 3653–3656 (2013).
Storch, I. et al. Evaluating the effectiveness of retention forestry to enhance biodiversity in production forests of Central Europe using an interdisciplinary, multi-scale approach. Ecol. Evol. 10, 1489–1509 (2020).
Totsche, K. U. et al. Biogeochemical interfaces in soil: the interdisciplinary challenge for soil science. J. Plant Nutr. Soil Sci. 173, 88–99 (2010).
Grimm, V. et al. CREAM: a European project on mechanistic effect models for ecological risk assessment of chemicals. Environ. Sci. Pollut. Res. 16, 614–617 (2009).
Cousens, R. D. A question of logic: experiments cannot prove lack of an herbicide-resistance fitness penalty. Weed Sci. 68, 197–198. https://doi.org/10.1017/wsc.2020.24 (2020).
Johnson, J. B. & Omland, K. S. Model selection in ecology and evolution. Trends Ecol. Evol. 19, 101–108 (2004).
Wilensky, U. NetLogo. (accessed 20 May 2020). http://ccl.northwestern.edu/netlogo/ (1999).
Patzoldt, W. L., Hager, A. G., McCormick, J. S. & Tranel, P. J. A codon deletion confers resistance to herbicides inhibiting protoporphyrinogen oxidase. Proc. Natl. Acad. Sci. U.S.A. 103, 12329–12334 (2006).
Rangani, G. et al. A novel single-site mutation in the catalytic domain of protoporphyrinogen oxidase IX (PPO) confers resistance to PPO-inhibiting herbicides. Front. Plant Sci. 10, 568. https://doi.org/10.3389/fpls.2019.00568 (2019).
Salas, R. A. et al. Resistance to PPO-inhibiting herbicide in Palmer amaranth from Arkansas. Pest Manage. Sci. 72, 864–869 (2016).
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