Hostname: page-component-76fb5796d-45l2p Total loading time: 0 Render date: 2024-04-26T19:58:24.271Z Has data issue: false hasContentIssue false
  • English
  • Français

Local Conditions, Not Regional Gradients, Drive Demographic Variation of Giant Ragweed (Ambrosia trifida) and Common Sunflower (Helianthus annuus) Across Northern U.S. Maize Belt

Published online by Cambridge University Press:  20 January 2017

Sam E. Wortman ,
Adam S. Davis ,
Brian J. Schutte ,
John L. Lindquist ,
John Cardina ,
Joel Felix ,
Christy L. Sprague ,
J. Anita Dille ,
Analiza H. M. Ramirez  and
Graig Reicks
...Show all authors
Sam E. Wortman*
Affiliation:
Department of Agronomy and Horticulture, University of Nebraska–Lincoln, Lincoln, NE 68583-0915
Adam S. Davis
Affiliation:
U.S. Department of Agriculture–Agricultural Research Service Global Change and Photosynthesis Research Unit, 1102 South Goodwin Avenue, Urbana, IL 61801
Brian J. Schutte
Affiliation:
U.S. Department of Agriculture–Agricultural Research Service Global Change and Photosynthesis Research Unit, 1102 South Goodwin Avenue, Urbana, IL 61801
John L. Lindquist
Affiliation:
Department of Agronomy and Horticulture, University of Nebraska–Lincoln, Lincoln, NE 68583-0915
John Cardina
Affiliation:
Ohio State University, OARDC–Wooster, 116 Gourley Hall, Wooster, OH 44691
Joel Felix
Affiliation:
Ohio State University, OARDC–Wooster, 116 Gourley Hall, Wooster, OH 44691
Christy L. Sprague
Affiliation:
Department of Crop and Soil Sciences, Michigan State University, A466 Plant and Soil Sciences Building, East Lansing, MI 48824
J. Anita Dille
Affiliation:
Department of Agronomy, Kansas State University, 2004 Throckmorton Plant Sciences Center, Manhattan, KS 66506
Analiza H. M. Ramirez
Affiliation:
Department of Agronomy, Kansas State University, 2004 Throckmorton Plant Sciences Center, Manhattan, KS 66506
Graig Reicks
Affiliation:
Department of Plant Science, South Dakota State University, Agricultural Hall Box 2207A, Brookings, SD 57007
Sharon A. Clay
Affiliation:
Department of Plant Science, South Dakota State University, Agricultural Hall Box 2207A, Brookings, SD 57007
*
Corresponding author's E-mail: sam.wortman@huskers.unl.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Knowledge of environmental factors influencing demography of weed species will improve understanding of current and future weed invasions. The objective of this study was to quantify regional-scale variation in vital rates of giant ragweed and common sunflower. To accomplish this objective, a common field experiment was conducted across seven sites between 2006 and 2008 throughout the north central U.S. maize belt. Demographic parameters of both weed species were measured in intra- and interspecific competitive environments, and environmental data were collected within site-years. Site was the strongest predictor of belowground vital rates (summer and winter seed survival and seedling recruitment), indicating sensitivity to local abiotic conditions. However, biotic factors influenced aboveground vital rates (seedling survival and fecundity). Partial least squares regression (PLSR) indicated that demography of both species was most strongly influenced by thermal time and precipitation. The first PLSR components, both characterized by thermal time, explained 63.2% and 77.0% of variation in the demography of giant ragweed and common sunflower, respectively; the second PLSR components, both characterized by precipitation, explained 18.3% and 8.5% of variation, respectively. The influence of temperature and precipitation is important in understanding the population dynamics and potential distribution of these species in response to climate change.

Keywords

Giant ragweed, Ambrosia trifida L. AMBTRcommon sunflower, Helianthus annuus L. HELANmaize, Zea mays Lsoybean, Glycine max (L.) MerrVital ratesweed demographyplant distributionclimate changeenvironmental clinespopulation dynamics
Type
Weed Biology and Ecology
Information
Weed Science , Volume 60 , Issue 3 , September 2012 , pp. 440 - 450
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.)

References

Literature Cited

Andreasen, C., Streibig, J. C., and Haas, H. 1991. Soil properties affecting the distribution of 37 weed species in Danish fields. Weed Res. 31:181–187.Google Scholar
Bauer, T. A. and Mortensen, D. A. 1992. A comparison of economic and economic optimum thresholds for two annual weeds in soybeans. Weed Technol. 6:228–235.Google Scholar
Baysinger, J. A. and Sims, B. D. 1991. Giant ragweed (Ambrosia trifida L.) interference in soybeans (Glycine max). Weed Sci. 39:358–362.Google Scholar
Beerling, D. J. 1993. The impact of temperature on the northern distribution limits of the introduced species Fallopia japonica and Impatiens glandulifera in North-West Europe. J. Biogeogr. 20:45–53.Google Scholar
Brainard, D. C., Bellinder, R. R., and DiTommaso, A. 2005. Effects of canopy shade on the morphology, phenology, and seed characteristics of powell amaranth (Amaranthus powellii). Weed Sci. 53:175–186.Google Scholar
Bridges, D. C. and Baumann, P. A. 1992. Weeds causing losses in the United States. Pages 75–147 in Bridges, D. C., ed. Crop Losses due to Weeds in the United States. Champaign, IL Weed Science Society of America.Google Scholar
Burton, M. G., Mortensen, D. A., and Marx, D. B. 2005. Environmental characteristics affecting Helianthus annuus distribution in a maize production system. Agr. Ecosyst. Environ. 111:30–40.Google Scholar
Burton, M. G., Mortensen, D. A., Marx, D. B., and Lindquist, J. L. 2004. Factors affecting the realized niche of common sunflower (Helianthus annuus) in ridge-tillage corn. Weed Sci. 52:779–787.Google Scholar
Byers, D. L. and Quinn, J. A. 1998. Demographic variation in Alliaria petiolata (Brassicaceae) in four contrasting habitats. J. Torrey Bot. Soc. 125:138–149.Google Scholar
Carrascal, L. M., Galván, I., and Gordo, O. 2009. Partial least squares regression as an alternative to current regression methods used in ecology. Oikos. 118:681–690.Google Scholar
Chen, I-C., Hill, J. K., Ohlemüller, R., Roy, D. B., and Thomas, C. D. 2011. Rapid range shifts of species associated with high levels of climate warming. Science. 333:1024–1026.Google Scholar
Colautti, R. I., Maron, J. L., and Barrett, S. C. H. 2009. Common garden comparisons of native and introduced plant populations: latitudinal clines can obscure evolutionary inferences. Evol. Appl. 2:187–199.Google Scholar
Cousens, R. and Mortimer, M. 1995. Dynamics of Weed Populations. New York Cambridge University Press. Pp. 86–216.Google Scholar
Dale, M.R.T., Thomas, A. G., and John, E. A. 1992. Environmental factors including management practices as correlates of weed community composition in spring seeded crops. Can. J. Bot. 70:1931–1939.Google Scholar
Davis, A. S. 2006. When does it make sense to target the weed seed bank? Weed Sci. 54:558–565.CrossRefGoogle Scholar
Davis, A. S., Cardina, J., Forcella, F., Johnson, G. A., Kegode, G., Lindquist, J. L., Luschei, E. C., Renner, K. A., Sprague, C. L., and Williams, M. M. II. 2005. Environmental factors affecting seed persistence of annual weeds across the U.S. corn belt. Weed Sci. 53:860–868.Google Scholar
Davis, A. S., Dixon, P. M., and Liebman, M. 2004. Using matrix models to determine cropping system effects on annual weed demography. Ecol. Appl. 14:655–668.Google Scholar
Diaz, S., Cabido, M., and Casanoves, F. 1998. Plant functional traits and environmental filters at a regional scale. J. Veg. Sci. 9:113–122.Google Scholar
Dieleman, J. A., Mortensen, D. A., Buhler, D. D., Cambardella, C. A., and Moorman, T. B. 2000a. Identifying associations among site properties and weed species abundance. I. Multivariate analysis. Weed Sci. 48:567–575.Google Scholar
Dieleman, J. A., Mortensen, D. A., Buhler, D. D., and Ferguson, R. B. 2000b. Identifying associations among site properties and weed species abundance. II. Hypothesis generation. Weed Sci. 48:576–587.Google Scholar
Dunlop, E. A., Wilson, J. C., and Mackey, A. P. 2006. The potential geographic distribution of the invasive weed Senna obtusifolia in Australia. Weed Res. 46:404–413.Google Scholar
Ehleringer, J. R. 1988. Changes in leaf characteristics of species along elevational gradients in the Wasatch Front Utah USA. Am. J. Bot. 75:680–689.Google Scholar
Forcella, F. 1992. Prediction of weed seedling densities from buried seed reserves. Weed Res. 32:29–38.Google Scholar
Forcella, F., Wilson, R. G., Dekker, J., Kremer, R. J., Cardina, J., Anderson, R. L., Alm, D., Renner, K. A., Harvey, R. G., Clay, S., and Buhler, D. D. 1997. Weed seed bank emergence across the corn belt. Weed Sci. 45:67–76.CrossRefGoogle Scholar
Forcella, F., Wilson, R. G., Renner, K. A., Dekker, J., Harvey, R. G., Alm, D. A., Buhler, D. D., and Cardina, J. A. 1992. Weed seedbanks of the U.S. cornbelt: magnitude, variation, emergence, and application. Weed Sci. 40:636–644.Google Scholar
Gaston, K. J. 2009. Geographic range limits: achieving synthesis. Proc. R. Soc. Lond. B. 276:1395–1406.Google Scholar
Gotelli, N. J. and Ellison, A. M. 2004. A Primer of Ecological Statistics. Sunderland, MA Sinauer. 150 p.Google Scholar
Grundy, A. C., Mead, A., Burston, S., and Overs, T. 2004. Seed production of Chenopodium album in competition with field vegetables. Weed Res. 44:271–281.Google Scholar
Harrison, S. K., Regnier, E. E., Schmoll, J. T., and Harrison, J. M. 2007. Seed size and burial effects on giant ragweed (Ambrosia trifida) emergence and seed demise. Weed Sci. 55:16–22.Google Scholar
Harrison, S. K., Regnier, E. E., Schmoll, J. T., and Webb, J. E. 2001. Competition and fecundity of giant ragweed in corn. Weed Sci. 49:224–229.Google Scholar
High Plains Regional Climate Center. 2012. Climate Information for Management and Operational Decisions. http://climod.unl.edu/. Accessed: March 21, 2012.Google Scholar
Hogg, R. V. and Craig, A. T. 1995. Introduction to Mathematical Statistics, 5th ed. Englewood Hall, NJ Prentice Hall. Pp. 251–252.Google Scholar
Hopkins, A. D. 1919. Periodical Events and Natural Law as Guides to Agricultural Research and Practice. Supplement 9. Washington, DC U.S. Bureau of Entomology.Google Scholar
Horvitz, C. C. and Schemske, D. W. 1995. Spatiotemporal variation in demographic transitions for a neotropical understory herb: projection matrix analysis. Ecol. Monogr. 65:155–192.Google Scholar
Jordan, N. 1993. Simulation analysis of weed population dynamics in ridge-tilled fields. Weed Science. 41:468–474.Google Scholar
Joshi, J., Schmid, B., Caldeira, M. C., Dimitrakopoulos, P. G., Good, J., Harris, R., Hector, A., Huss-Danell, K., Jumpponen, A., Minns, A., Mulder, C. P. H., Pereira, J. S., Prinz, A., Scherer-Lorenzen, M., Siamantziouras, A. S. D., Terry, A. C., Troumbis, A. Y., and Lawton, J. H. 2001. Local adaptation enhances performance of common plant species. Ecol. Lett. 4:536–544.Google Scholar
Keddy, P. A. 1992. Assembly and response rules: two goals for predictive community ecology. J. Veg. Sci. 3:157–164.Google Scholar
Keller, S. R., Sowell, D. R., Neiman, M., Wolfe, L. M., and Taylor, D. R. 1999. Adaptation and colonization history affect the evolution of clines in two introduced species. New Phytol. 183:678–690.Google Scholar
Mack, R. N. and Pyke, D. A. 1983. The demography of Bromus tectorum: variation in time and space. J. Ecol. 71:69–93.Google Scholar
Meehl, G. A., Stocker, T. F., Collins, W. D., Friedlingstein, P., Gaye, A. T., Gregory, J. M., Kitoh, A., Knutti, R., Murphy, J. M., Noda, A., Raper, S.C.B., Watterson, I. G., Weaver, A. J., and Zhao, Z. C. 2007. Global climate projections. in Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., eds. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, United Kingdom, and New York Cambridge University Press. Pp. 749–844.Google Scholar
Milbau, A., Graae, B. J., Shevtsova, A., and Nijs, I. 2009. Effects of a warmer climate on seed germination in the subarctic. Ann. Bot. 104:287–296.Google Scholar
National Oceanic and Atmospheric Administration. 2012. Earth Systems Research Laboratory, Physical Sciences Division. http://www.esrl.noaa.gov/psd/data/usclimdivs/index.html. Accessed: March 21, 2012.Google Scholar
Pearson, R. G. and Dawson, T. P. 2003. Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Global Ecol. Biogeogr. 12:361–371.Google Scholar
Pearson, R. G., Dawson, T. P., Berry, P. M., and Harrison, P. A. 2002. SPECIES: a spatial evaluation of climate impact on the envelope of species. Ecol. Model. 154:289–300.Google Scholar
Peters, J., ed. 2000. Tetrazolium Testing Handbook. Contribution No. 29 to the Handbook on Seed Testing. Lincoln, NE Association of Official Seed Analysts. Pp. 1–18, 151–154.Google Scholar
Santamaria, L., Figuerola, J., Pilon, J. J., Mjelde, M., Green, A. J., De Boer, T., King, R. A., and Gornall, R. J. 2003. Plant performance across latitude: the role of plasticity and local adaptation in an aquatic plant. Ecology. 84:2454–2461.Google Scholar
Savolainen, O., Pyhajarvi, T., and Knurr, T. 2007. Gene flow and local adaptation in trees. Annu. Rev. Ecol. Evol. S. 38:595–619.Google Scholar
Schafer, M. and Kotanen, P. M. 2003. The influence of soil moisture on losses of buried seeds to fungi. Acta Oecol. 24:255–263.Google Scholar
Schutte, B. J., Regnier, E. E., Harrison, S. K., Schmoll, J. T., Spokas, K., and Forcella, F. 2008. A hydrothermal seedling emergence model for giant ragweed (Ambrosia trifida). Weed Sci. 56:555–560.Google Scholar
Snow, A. A., Pilson, D., Rieseberg, L. H., Paulsen, M. J., Pleskac, N., Reagon, M. R., Wolf, D. E., and Selbo, S. M. 2003. A Bt transgene reduces herbivory and enhances fecundity in wild sunflowers. Ecol. Appl. 13:279–286.Google Scholar
Thuiller, W. 2003. BIOMOD–optimizing predictions of species distributions and projecting potential future shifts under global change. Global Change Biol. 9:1353–1362.Google Scholar
Walther, G., Post, E., Convey, P., Menzel, A., Parmesan, C., Beebee, T. J. C., Fromentin, J., Hoegh-Guldberg, O., and Bairlein, F. 2002. Ecological responses to recent climate change. Nature. 416:389–395.Google Scholar
Wang, R. and Gao, Q. 2003. Climate-driven changes in shoot density and shoot biomass in Leymus chinensis (Poaceae) on the North-east China Transect (NECT). Global Ecol. Biogeogr. 12:249–259.Google Scholar
Wiles, L. J., Barlin, D. H., Schweizer, E. E., Duke, H. R., and Whitt, D. E. 1996. A new soil sampler and elutriator for collecting and extracting weed seeds from soil. Weed Technol. 10:35–41.Google Scholar
Woodward, F. I. 1987. Climate and plant distribution. Cambridge, United Kingdom Cambridge University Press. 174 p.Google Scholar
Wortman, S. E., Davis, A. S., Schutte, B. J., and Lindquist, J. L. 2011. Integrating management of soil nitrogen and weeds. Weed Sci. 59:162–170.Google Scholar