Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-22T19:52:33.089Z Has data issue: false hasContentIssue false
  • English
  • Français

Quantifying seed and establishment limitation to seedling recruitment of arable weeds: an example of barnyardgrass (Echinochloa crus-galli)

Published online by Cambridge University Press:  22 October 2021

Christian Selig Open the ORCID record for Christian Selig [Opens in a new window] ,
Friederike de Mol ,
Paula R. Westerman  and
Bärbel Gerowitt
Christian Selig*
Affiliation:
PhD Student, Faculty of Agricultural and Environmental Science, Crop Health Group, University of Rostock, 18051 Rostock, Germany
Friederike de Mol
Affiliation:
Researcher, Faculty of Agricultural and Environmental Science, Crop Health Group, University of Rostock, 18051 Rostock, Germany
Paula R. Westerman
Affiliation:
Researcher, Faculty of Agricultural and Environmental Science, Crop Health Group, University of Rostock, 18051 Rostock, Germany
Bärbel Gerowitt
Affiliation:
Professor, Faculty of Agricultural and Environmental Science, Crop Health Group, University of Rostock, 18051 Rostock, Germany
*
Author for correspondence: Christian Selig, Faculty of Agricultural and Environmental Science, Crop Health Group, University of Rostock, 18051 Rostock, Germany. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

The establishment of plants in an ecosystem is limited by the availability of seeds and the availability of suitable sites for establishment. Describing plant population dynamics through the relative strength of seed and establishment limitation is an important concept in the study of natural ecosystems. To date, it is unclear whether this concept can be applied to describe populations of annual weeds in agricultural fields. Using a recruitment function, we show that limitation parameters prove valuable in describing seedling recruitment in weed populations. We conducted a seed addition experiment in three cornfields (Zea mays L.) and recorded seedling recruitment in populations of the economically important weed barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.]. Seed predation, competition with other weeds, and seed burial were prevented. We estimated the strength of seed and establishment limitation in the population with two parameters: n, which is the number of microsites, and b, which is the suitability of those sites to support a seedling. We further estimated the relative proportions of density-dependent and density-independent establishment limitation in the seedling population. Recruitment rates of E. crus-galli ranged from 31% to 36% across all evaluated seed densities and fields, which is high compared with results from other seed addition studies. Two of the three monitored populations were predominantly establishment limited at the highest evaluated seed density of 2,400 added seeds m−2. Further knowledge about the relative strength of limitations in other weed populations will provide important information on how effective different weed management strategies can be.

Keywords

Corndensity dependencedensity independencemaizepopulation dynamics
Type
Research Article
Information
Weed Science , Volume 70 , Issue 1 , January 2022 , pp. 87 - 94
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the 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: Muthukumar V. Bagavathiannan, Texas A and M University

References

Aicher, RJ, Larios, L, Suding, KN (2011) Seed supply, recruitment, and assembly: Quantifying relative seed and establishment limitation in a plant community context. Am Nat 178:464–477 CrossRefGoogle Scholar
Bagavathiannan, MV, Norsworthy, JK (2013) Postdispersal loss of important arable weed seeds in the midsouthern United States. Weed Sci 61:570–579 CrossRefGoogle Scholar
Bajwa, AA, Jabran, K, Shahid, M, Ali, HH, Chauhan, BS, Ehsanullah (2015a) Eco-biology and management of Echinochloa crus-galli . Crop Prot 75:151–162 CrossRefGoogle Scholar
Bajwa, AA, Mahajan, G, Chauhan, BS (2015b) Nonconventional weed management strategies for modern agriculture. Weed Sci 63:723–747 CrossRefGoogle Scholar
Ball, DA (1992) Weed seedbank response to tillage, herbicides, and crop rotation sequence. Weed Sci 40:654–659 CrossRefGoogle Scholar
Blubaugh, CK, Kaplan, I (2016) Invertebrate seed predators reduce weed emergence following seed rain. Weed Sci 64:80–86 CrossRefGoogle Scholar
Bosnic, AC, Swanton, CJ (1997) Influence of barnyardgrass (Echinochloa crus-galli) time of emergence and density on corn (Zea mays). Weed Sci 45:276–282 CrossRefGoogle Scholar
Boyd, N, van Acker, RC (2004) Seed and microsite limitations to emergence of four annual weed species. Weed Sci 52:571–577 CrossRefGoogle Scholar
Brännström, A, Sumpter, DJT (2005) The role of competition and clustering in population dynamics. Proc Biol Sci 272:2065–2072 Google ScholarPubMed
Bullied, WJ, van Acker, RC, Bullock, PR (2012) Review: microsite characteristics influencing weed seedling recruitment and implications for recruitment modeling. Can J Plant Sci 92:627–650 CrossRefGoogle Scholar
Clark, CJ, Poulsen, JR, Levey, DJ (2013) Roles of seed and establishment limitation in determining patterns of afrotropical tree recruitment. PLoS ONE 8(5):e63330 CrossRefGoogle ScholarPubMed
Clark, CJ, Poulsen, JR, Levey, DJ, Osenberg, CW (2007) Are plant populations seed limited? A critique and meta-analysis of seed addition experiments. Am Nat 170:128–142 CrossRefGoogle ScholarPubMed
Crawley, MJ (1990) The population dynamics of plants. Philos Trans R Soc Lond B 330:125–140 Google Scholar
Daedlow, D, Westerman, PR, Baraibar, B, Rouphael, S, Gerowitt, B (2014) Weed seed predation rate in cereals as a function of seed density and patch size, under high predation pressure by rodents. Weed Res 54:186–195 CrossRefGoogle Scholar
Davis, AS (2006) When does it make sense to target the weed seed bank? Weed Sci 54:558–565 CrossRefGoogle Scholar
Davis, AS, Fu, X, Schutte, BJ, Berhow, MA, Dalling, JW (2016) Interspecific variation in persistence of buried weed seeds follows trade-offs among physiological, chemical, and physical seed defenses. Ecol Evol 6:6836–6845 CrossRefGoogle ScholarPubMed
Davis, AS, Taylor, EC, Haramoto, ER, Renner, KA (2013) Annual postdispersal weed seed predation in contrasting field environments. Weed Sci 61:296–302 CrossRefGoogle Scholar
de Mol, F, von Redwitz, C, Gerowitt, B (2015) Weed species composition of maize fields in Germany is influenced by site and crop sequence. Weed Res 55:574–585 CrossRefGoogle Scholar
[DWD] Deutscher Wetterdienst Climate Data Center (2017) Langjährige Stationsmittelwerte für die Klimareferenzperiode 1981–2010. https://www.dwd.de/DE/leistungen/kvo/mecklenburg-vorpommern.html. Accessed: November 21, 2017Google Scholar
Duncan, RP, Diez, JM, Sullivan, JJ, Wangen, SR, Miller, AL (2009) Safe sites, seed supply, and the recruitment function in plant populations. Ecology 90:2129–2138 CrossRefGoogle ScholarPubMed
Eriksson, O, Ehrlén, J (1992) Seed and microsite limitation of recruitment in plant populations. Oecologia 91:360–364 CrossRefGoogle ScholarPubMed
Fettig, CE, Hufbauer, RA (2017) Reproductive strategy, performance, and population dynamics of the introduced weed black henbane (Hyoscyamus niger). Weed Sci 65:83–96 CrossRefGoogle Scholar
Harper, JL (1977) Population Biology of Plants. London: Academic Press. 892 p Google Scholar
Kass, RE, Carlin, BP, Gelman, A, Neal, RM (1998) Markov chain Monte Carlo in practice. Am Stat 52:93–100 Google Scholar
Kruschke, JK (2010) Bayesian data analysis. WIREs Cogn Sci 1:658–676 CrossRefGoogle ScholarPubMed
Long, RL, Gorecki, MJ, Renton, M, Scott, JK, Colville, L, Goggin, DE, Commander, LE, Westcott, DA, Cherry, H, Finch-Savage, WE (2015) The ecophysiology of seed persistence. Biol Rev 90:31–59 CrossRefGoogle ScholarPubMed
Maun, MA, Barrett, SCH (1986) The biology of Canadian weeds: 77. Echinochloa crus-galli (L.) Beauv. Can J Plant Sci 66:739–759 CrossRefGoogle Scholar
Miller, AL, Diez, JM, Sullivan, JJ, Wangen, SR, Wiser, SK, Meffin, R, Duncan, RP (2014) Quantifying invasion resistance. Ecology 95:920–929 CrossRefGoogle ScholarPubMed
Osipitan, OA, Dille, JA, Bagavathiannan, MV, Knezevic, SZ (2019) Modeling population dynamics of kochia (Bassia scoparia) in response to diverse weed control options. Weed Sci 67:57–67 CrossRefGoogle Scholar
Pannwitt, H, Westerman, PR, de Mol, F, Gerowitt, B (2019) Using panicle dry weight to estimate seed production in Echinochloa crus-galli . Weed Res 59:437–445 CrossRefGoogle Scholar
Pannwitt, H, Westerman, PR, de Mol, F, Gerowitt, B (2021) Demographic processes allow Echinochloa crus-galli to compensate seed losses by seed predation. Agronomy 11:565 CrossRefGoogle Scholar
Pannwitt, H, Westerman, PR, de Mol, F, Selig, C, Gerowitt, B (2017) Biological control of weed patches by seed predators; responses to seed density and exposure time. Biol Control 108:1–8 CrossRefGoogle Scholar
Poulsen, JR, Osenberg, CW, Clark, CJ, Levey, DJ, Bolker, BM (2007) Plants as reef fish: fitting the functional form of seedling recruitment. Am Nat 170:167–183 CrossRefGoogle ScholarPubMed
R Core Team (2017) R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing Google Scholar
Shergill, LS, Bejleri, K, Davis, A, Mirsky, SB (2019) Fate of weed seeds after impact mill processing in midwestern and mid-Atlantic United States. Weed Sci:1–23 CrossRefGoogle Scholar
Skellam, JG (1951) Random dispersal in theoretical populations. Biometrika 38:196–218 CrossRefGoogle ScholarPubMed
Spiegelhalter, DJ, Best, NG, Carlin, BP, van der Linde, A (2002) Bayesian measures of model complexity and fit. J Roy Stat Soc B 64:583–639 CrossRefGoogle Scholar
Spotswood, EN, Mariotte, P, Farrer, EC, Nichols, L, Suding, KN (2017) Separating sources of density-dependent and density-independent establishment limitation in invading species. J Ecol 105:436–444 CrossRefGoogle Scholar
van Acker, RC (2009) Weed biology serves practical weed management. Weed Res 49:1–5 CrossRefGoogle Scholar
Westerman, PR, Borza, JK, Andjelkovic, J, Liebman, M, Danielson, B (2008) Density-dependent predation of weed seeds in maize fields. J Appl Ecol 45:1612–1620 CrossRefGoogle Scholar
White, SS, Renner, KA, Menalled, FD, Landis, DA (2007) Feeding preferences of weed seed predators and effect on weed emergence. Weed Sci 55:606–612 CrossRefGoogle Scholar