Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-24T16:08:27.777Z Has data issue: false hasContentIssue false
  • English
  • Français

Weed Seed Banks Are More Dynamic in a Sod-Based, Than in a Conventional, Peanut–Cotton Rotation

Published online by Cambridge University Press:  20 January 2017

Ramon G. Leon ,
David L. Wright  and
James J. Marois
Ramon G. Leon*
Affiliation:
West Florida Research and Education Center, University of Florida, Jay, FL 32565
David L. Wright
Affiliation:
North Florida Research and Education Center, University of Florida, Quincy, FL 32351
James J. Marois
Affiliation:
North Florida Research and Education Center, University of Florida, Quincy, FL 32351
*
Corresponding author's E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Crop rotation promotes productivity, nutrient cycling, and effective pest management. However, in row-crop systems, rotation is frequently limited to two crops. Adding a third crop, especially a perennial crop, might increase crop-rotation benefits, but concerns about disruption of agricultural and ecological processes preclude grower adoption of a three-crop rotation. The objective of the present research was to determine whether weed seed banks differ between a sod-based rotation (bahiagrass–bahiagrass–peanut–cotton) and a conventional peanut–cotton rotation (peanut–cotton–cotton) and the importance of crop phase in weed seed-bank dynamics in a long-term experiment initiated in 1999 in Florida. Extractable (ESB) and germinable (GSB) seed banks were evaluated at the end of each crop phase in 2012 and 2013, and total weed seed or seedling number, Shannon-Weiner's diversity (H′), richness, and evenness were determined. ESB increased in H′ (36%), richness (29%), and total number of weed seeds (40%) for sod-based compared with conventional rotation, whereas GSB increased 32% in H′, 27% in richness, and 177% in total number of weed seedlings. Crop phase was a determinant factor in the differences between crop rotations. The first year of bahiagrass (B1) exhibited increases in weed seed and seedling number, H′, and richness and had the highest values observed in the sod-based rotation. These increases were transient, and in the second year of bahiagrass (B2), weed numbers and H′ decreased and reached levels equivalent to those in the conventional peanut–cotton rotation. The B1 phase increased the germinable fraction of the seed bank, compared with the other crop phases, but not the total number of weed seeds as determined by ESB. The increases in H′ and richness in bahiagrass phases were mainly due to grass weed species. However, these grass weed species were not associated with peanut and cotton phases of the sod-based rotation. The results of the present study demonstrated that including bahiagrass as a third crop in a peanut–cotton rotation could increase weed community diversity, mainly by favoring increases in richness and diversity, but the structure and characteristics of the rotation would prevent continuous increases in the weed seed bank that could affect the peanut and cotton phases.

Keywords

Bahiagrass, Paspalum notatum Flueggcotton, Gossypium hirsutum L.peanut, Arachis hypogaea L.Communitydormancygerminationintegrated weed managementlong-term researchpopulations
Type
Weed Biology and Ecology
Information
Weed Science , Volume 63 , Issue 4 , December 2015 , pp. 877 - 887
Copyright
Copyright © Weed Science Society of America 

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.)

Footnotes

Associate editor for this paper: Theodore M. Webster, USDA-ARS.

References

Literature Cited

Beckie, HJ (2006) Herbicide-resistant weeds: management tactics and practices. Weed Technol 20:793–814 Google Scholar
Brown, D (1992) Estimating the composition of a forest seed bank: a comparison of the seed extraction and seedling emergence methods. Can J Bot 70:1603–1612 Google Scholar
Chauvel, B, Guillemin, JP, Colbach, N, Gasquez, J (2001) Evaluation of cropping systems for management of herbicide-resistant populations of blackgrass (Alopecurus myosuroides Huds.). Crop Prot 20:127–137 Google Scholar
Davis, AS, Hill, JD, Chase, CA, Johanns, AM, Liebman, M (2012) Increasing cropping system diversity balances productivity, profitability and environmental health. PLoS One 7:e4719. DOI: 10.1371/journal.pone.0047149Google Scholar
Gallandt, ER, Molloy, T, Lynch, RP, Drummond, FA (2005) Effect of cover-cropping systems on invertebrate seed predation. Weed Sci 53:69–76 Google Scholar
Gibson, KD, Johnson, WG, Hillger, DE (2006) Farmer perceptions of weed problems in corn and soybean rotation systems. Weed Technol 20:751–755 Google Scholar
Gross, KL (1990) A comparison of methods for estimating seed numbers in the soil. J Ecol 78:10479–1093Google Scholar
Hernandez Plaza, E, Kozak, M, Navarrete, L, Gonzalez-Andujar, JL (2011) Tillage system did not affect weed diversity in a 23-year experiment in Mediterranean dryland. Agric Ecosyst Environ 140:102–105 Google Scholar
Karlen, DL, Hurley, EG, Andrews, SS, Cambardella, CA, Meek, DW, Duffy, MD, Mallarino, AP (2006) Crop rotation effects on soil quality at three northern corn/soybean belt locations. Agron J 98:484–495 Google Scholar
Katsvairo, TW, Wright, DL, Marois, JJ, Hartzog, DL, Balkcom, KB, Wiatrak, PJ, Rich, JR (2007) Performance of peanut and cotton in a bahiagrass cropping system. Agron J 99:1245–1251 Google Scholar
Katsvairo, TW, Wright, DL, Marois, JJ, Hartzog, DL, Rich, JR, Wiatrak, PJ (2006) Sod-livestock integration into the peanut-cotton rotation: a systems farming approach. Agron J 98:1156–1171 Google Scholar
Katsvairo, TW, Wright, DL, Marois, JJ, Rich, JR, Wiatrak, PJ (2009) Comparative plant growth and development in two cotton rotations under irrigated and non-irrigated conditions. Crop Sci 49:2233–2245 Google Scholar
Liebman, M, Dick, E (1993) Crop rotation and intercropping strategies for weed management. Ecol Appl 3:92–122 Google Scholar
Liebman, M, Staver, C (2001) Crop diversification for weed management. Pages Pages 322–374 in Liebman M, Mohler CL, Staver CP, ed. Ecological Management of Agricultural Weeds. Cambridge, UK Cambridge University Press.Google Scholar
Menalled, FD, Gross, KL, Hammond, M (2001) Weed aboveground and seedbank community responses to agricultural management systems. Ecol Appl 11:1586–1601 Google Scholar
Owen, MDK (2008) Weed species shifts in glyphosate-resistant crops. Pest Manag Sci 64:377–387 Google Scholar
Ramsey, FL, Shafer, DW (2002) The Statistical Sleuth: A Course in Methods of Data Analysis. 2nd edn. Pacific Grove, CA Duxbury. 100 pGoogle Scholar
Smith, RG, Gross, KL (2006) Rapid change in the germinable fraction of the weed seed bank in crop rotations. Weed Sci 54:1094–1100 Google Scholar
Sanguankeo, PP, Leon, RG (2011) Weed management practices determine plant and arthropod diversity and seed predation in vineyards. Weed Res 51:404–412 Google Scholar
Sollenberger, LE, Ocumpaugh, WR, Euclides, VPB, Moore, JE, Quesenberry, KH, Jones, CS (1988) Animal performance on continuously stocked ‘Pensacola’ bahiagrass and ‘Floralta’ limpograss pastures. J Prod Agric 1:216–220 Google Scholar
Sosnoskie, LM, Herms, CP, Cardina, J (2006) Weed seed bank community composition in a 35-yr-old tillage and rotation experiment. Weed Sci 54:263–273 Google Scholar
Ward, SM, Webster, TM, Steckel, LE (2013) Palmer amaranth (Amaranthus palmeri): a review. Weed Technol 27:12–27 Google Scholar
Westerman, PR, Liebman, M, Menalled, FD, Heggenstaller, AH, Hartzler, RG, Dixon, PM (2005) Are many little hammers effective? velvetleaf (Abutilon theophrasti) population dynamics in two- and four-year crop rotation systems. Weed Sci 53:382–3922 Google Scholar
Zhao, D, Wright, DL, Marois, JJ (2009) Peanut yield and grade responses to timing of bahiagrass termination and tillage in a sod-based crop rotation. Peanut Sci 36:196–203 Google Scholar