Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-26T03:57:18.942Z Has data issue: false hasContentIssue false

Weed species and traits associated with organic grain crop rotations in the mid-Atlantic region

Published online by Cambridge University Press:  05 August 2019

John R. Teasdale*
Affiliation:
Biological Collaborator, Sustainable Agricultural Systems Lab, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD, USA
Steven B. Mirsky
Affiliation:
Research Ecologist, Sustainable Agricultural Systems Lab, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD, USA
Michel A. Cavigelli
Affiliation:
Research Soil Scientist, Sustainable Agricultural Systems Lab, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD, USA
*
Author for correspondence: John Teasdale, USDA-ARS, Building 001, Room 245, 10300 Baltimore Avenue, Beltsville, MD 20705. Email: [email protected]

Abstract

Organic cropping systems are characterized by soil-disturbance events that can be diversified over years through crop rotations and within seasons by varying planting dates. The Farming Systems Project at Beltsville, MD, USA, is a long-term experiment that includes three organic rotations, corn (Zea mays L.)–soybean [Glycine max (L.) Merr.], corn–soybean–wheat (Triticum aestivum L.), and corn–soybean–wheat–alfalfa (Medicago sativa L.). Analysis of weed presence and cover over the first 18 yr of this experiment revealed that the tall, erect annual broadleaf weeds smooth pigweed (Amaranthus hybridus L.), common lambsquarters (Chenopodium album L.), horseweed (Erigeron canadensis L.), jimsonweed (Datura stramonium L.), and/or velvetleaf (Abutilon theophrasti Medik.) were most prominent in corn and soybean. Generally, these species exhibited traits adapted to the disturbance regimes, nutrient availability, crop environment and duration, and local meteorological conditions associated with the summer annual corn and soybean crops. Abundance of A. hybridus, D. stramonium, and A. theophrasti were controlled primarily by rotation diversity, whereby presence and cover of these species were highest in the short corn–soybean rotation and lowest in the longer rotations that had more diverse seasonal soil-disturbance regimes. Early-season temperature was the primary factor controlling C. album presence and cover, which were higher at lower temperatures associated with earlier planting dates. Higher early-season precipitation was the primary factor associated with higher presence of annual grass species. The relative abundance of species in organic corn and soybean was determined primarily by the diversity of crops and disturbance operations in rotation, the timing of spring tillage and planting, and annual meteorological conditions driving emergence periodicity.

Type
Research Article
Creative Commons
This is a work of the U.S. Government and is not subject to copyright protection in the United States.
Copyright
© Weed Science Society of America, 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Anderson, RL (2010) A rotation design to reduce weed density in organic farming. Renew Agric Food Syst 25:189195 CrossRefGoogle Scholar
Angerta, AL, Huxman, TE, Chesson, P, Venable, DL (2009) Functional tradeoffs determine species coexistence via the storage effect. Proc Natl Acad Sci USA 106:1164111645 CrossRefGoogle Scholar
Baker, BP, Mohler, CL (2015) Weed management by upstate New York organic farmers: strategies, techniques and research priorities. Renew Agric Food Syst 30:418427 CrossRefGoogle Scholar
Bernstein, ER, Stoltenberg, DE, Posner, JL, Hedtcke, JL (2014) Weed community dynamics and suppression in tilled and no-tillage transitional organic winter rye–soybean systems. Weed Sci 62:125137 CrossRefGoogle Scholar
Booth, BD, Swanton, CJ (2002) Assembly theory applied to weed communities. Weed Sci 50:213 CrossRefGoogle Scholar
Bouwmeester, HJ, Karssen, CM (1993) Seasonal periodicity in germination of seeds of Chenopodium album L. Ann Bot 72:463473 CrossRefGoogle Scholar
Cavigelli, MA, Mirsky, SB, Teasdale, JR, Spargo, JT, Doran, J (2013) Organic grain cropping systems to enhance ecosystem services. Renew Agric Food Syst 28:145159 CrossRefGoogle Scholar
Chesson, P, Huntly, N (1997) The roles of harsh and fluctuating conditions in the dynamics of ecological communities. Am Nat 150:519553 CrossRefGoogle ScholarPubMed
Cordeau, S, Smith, RG, Gallandt, ER, Brown, B, Salon, P, DiTommaso, A, Ryan, MR (2017) Timing of tillage as a driver of weed communities. Weed Sci 65:504514 CrossRefGoogle Scholar
Crawley, MJ (2004) Timing of disturbance and coexistence in a species-rich ruderal plant community. Ecology 85:32773288 CrossRefGoogle Scholar
DeDecker, JJ, Masiunas, JB, Davis, AS, Flint, CG (2014) Weed management practice selection among midwest U.S. organic growers. Weed Sci 62:520531 CrossRefGoogle Scholar
Dinnage, R (2009) Disturbance alters the phylogenetic composition and structure of plant communities in an old field system. PLoS ONE 4:e7071 CrossRefGoogle Scholar
Facelli, JM, Chesson, P, Barnes, N (2005) Differences in seed biology of annual plants in arid lands: a key ingredient of the storage effect. Ecology 86:29983006 CrossRefGoogle Scholar
Fried, G, Norton, LR, Reboud, X (2008) Environmental and management factors determining weed species composition and diversity in France. Agric Ecosyst Environ 128:6876 CrossRefGoogle Scholar
KC, KB, Dias, GM, Veeramani, A, Swanton, CJ, Fraser, D, Steinke, D, Lee, E, Wittman, H, Farber, JM, Dunfield, K, McCann, K, Anand, M, Campbell, M, Rooney, N, Raine, NE, et al. (2018) When too much isn’t enough: does current food production meet global nutritional needs? PLoS ONE 13:e0205683 CrossRefGoogle ScholarPubMed
Miller, AD, Roxburgh, SH, Shea, K (2012) Timing of disturbance alters competitive outcomes and mechanisms of coexistence in an annual plant model. Theor Ecol 5:419432 CrossRefGoogle Scholar
Mohler, CL, Caldwell, BA, Marschner, CA, Cordeau, S, Maqsood, Q, Ryan, MR, DiTommaso, A (2018). Weed seedbank and weed biomass dynamics in a long-term organic vegetable cropping systems experiment. Weed Sci 66:611626 CrossRefGoogle Scholar
Myers, MM, Curran, WS, VanGessel, MJ, Calvin, DD, Mortensen, DA, Majek, BA, Karsten, HD, Roth, GW (2004) Predicting weed emergence for eight annual species in the northeastern United States. Weed Sci 52:913919 CrossRefGoogle Scholar
Patterson, DT, Flint, EP (1983) Water relations, photosynthesis, and growth of soybean (Glycine max) and seven associated weeds. Weed Sci 31:318323 CrossRefGoogle Scholar
Pickett, STA, Bazzaz, FA (1976) Divergence of two co-occurring successional annuals on a soil moisture gradient. Ecology 57:169176 CrossRefGoogle Scholar
Rees, M, Condit, R, Crawley, M, Pacala, SW, Tilman, D (2001) Long-term studies of vegetation dynamics. Science 293:650655 CrossRefGoogle ScholarPubMed
Ryan, MR, Smith, RG, Mirsky, SB, Mortensen, DA, Seidel, R (2010) Management filters and species traits: weed community assembly in long-term organic and conventional systems. Weed Sci 58:265277 CrossRefGoogle Scholar
Seibert, AC, Pearce, RB (1993) Growth analysis of weed and crop species with reference to seed weight. Weed Sci 41:5256 CrossRefGoogle Scholar
Smith, RG (2006) Timing of tillage is an important filter on the assembly of weed communities. Weed Sci 54:705712 CrossRefGoogle Scholar
Spargo, JT, Cavigelli, MA, Mirsky, SB, Maul, JE, Meisinger, JJ (2011) Mineralizable soil nitrogen and labile soil organic matter in diverse long-term cropping systems. Nutr Cycl Agroecosyst 90:253266 CrossRefGoogle Scholar
Storkey, J, Moss, SR, Cussans, JW (2010) Using assembly theory to explain changes in a weed flora in response to agricultural intensification. Weed Sci 58:3946 CrossRefGoogle Scholar
Teasdale, JR (2018) The use of rotations and cover crops to manage weeds. Pages 227260 in Zimdahl, R, ed. Integrated Weed Management for Sustainable Agriculture. Cambridge, UK: Burleigh Dodds Science Publishing Google Scholar
Teasdale, JR, Cavigelli, MA (2017) Meteorological fluctuations define long-term crop yield patterns in conventional and organic production systems. Sci Rep 7:688 CrossRefGoogle ScholarPubMed
Teasdale, JR, Mangum, RW, Radhakrishnan, J, Cavigelli, MA (2004) Weed seedbank dynamics in three organic farming crop rotations. Agron J 96:14291435 CrossRefGoogle Scholar
Teasdale, JR, Mirsky, SB (2015) Tillage and planting date effects on weed dormancy, emergence and early growth in organic corn. Weed Sci 63:477490 CrossRefGoogle Scholar
Teasdale, JR, Mirsky, SB, Cavigelli, MA (2018) Meteorological and management factors influencing weed abundance during 18 years of organic crop rotations. Weed Sci 66:477484 CrossRefGoogle Scholar
Trewavas, A (2004) A critical assessment of organic farming and food assertions with particular respect to the UK and the potential environmental benefits of no-till agriculture. Crop Prot 23:757781 CrossRefGoogle Scholar
Tuomisto, HL, Hodge, ID, Riordan, P, Macdonald, DW (2012) Does organic farming reduce environmental impacts? A metaanalysis of European research. J Environ Manag 112:309320 CrossRefGoogle Scholar
Ullrich, SD, Buyer, JS, Cavigelli, MA, Seidel, R, Teasdale, JR (2011) Weed seed persistence and microbial abundance in long-term organic and conventional cropping systems. Weed Sci 59: 202209 CrossRefGoogle Scholar
Wallace, JM, Keene, CL, Curran, W, Mirsky, S, Ryan, MR, VanGessel, MJ (2018) Integrated weed management strategies in cover crop–based, organic rotational no-till corn and soybean in the mid-Atlantic region. Weed Sci 66:94108 CrossRefGoogle Scholar
Warwick, SI, Black, LD (1988) The biology of Canadian weeds. 90. Abutilon theophrasti . Can J Plant Sci 68:10691085 CrossRefGoogle Scholar
Weaver, SE (2001) The biology of Canadian weeds. 115. Conyza canadensis L. Cronquist. Can J Plant Sci 81:867875 CrossRefGoogle Scholar
Weaver, SE, Warwick, SI (1984) The biology of Canadian weeds. 64. Datura stramonium L. Can J Plant Sci 64:979991 CrossRefGoogle Scholar
Wiese, AF, Vandiver, CW (1970) Soil moisture effects on competitive ability of weeds. Weed Sci 18:518519 CrossRefGoogle Scholar
Werle, R, Sandell, LD, Buhler, DD, Hartzler, RG, Lindquist, JL (2014) Predicting emergence of 23 summer annual weed species. Weed Sci 62:267279 CrossRefGoogle Scholar