Hostname: page-component-76fb5796d-22dnz Total loading time: 0 Render date: 2024-04-27T00:59:56.823Z Has data issue: false hasContentIssue false
  • English
  • Français

Weed Suppression Success Can Depend on Removal Pattern and Gene Dispersal Distance: Modeling Callery Pear

Published online by Cambridge University Press:  20 January 2017

Stephan Pelikan ,
Sam N. Heywood  and
Steven H. Rogstad
Stephan Pelikan
Affiliation:
Department of Mathematical Sciences, University of Cincinnati, Cincinnati, OH 45221 USA
Sam N. Heywood
Affiliation:
Department of Biological Sciences ML0006, University of Cincinnati, Cincinnati, OH 45221 USA
Steven H. Rogstad*
Affiliation:
Department of Biological Sciences ML0006, University of Cincinnati, Cincinnati, OH 45221 USA
*
Corresponding author's E-mail: steven.rogstad@uc.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Substantial resources are spent each year on weed control, but in many cases eradication projects are incomplete. Here we used the computer program NEWGARDEN to model whether alternate geometric patterns of incomplete removal (99% removed) of the increasingly invasive Callery pear from an isolated fragment differentially affect the rate of population recovery and genetic diversity retention. Geometric patterns of remaining founders within the fragment (1% of the fragment area) included: (A) a long rectangular strip centered on one edge; (B) a square at one corner; (C) a central square; or (D) scattered randomly throughout the entire fragment. Population re-growth and genetic diversity retention measures for each geometric removal pattern were modeled under two contrasting gene dispersal patterns (via both offspring and pollen): short versus long dispersal (both leptokurtic relative to the pistillate plant). After 14 bouts of mating, the greatest difference in census size among comparative recovery populations amounted to 393% (centered founders, long gene dispersal > scattered founders, short gene dispersal). The best pattern of removal for suppressing population regrowth was to leave founders scattered throughout the fragment when gene dispersal was short, or at one corner if gene dispersal was long. The only removal pattern that differed substantially in population genetics characteristics was when remnant individuals were left scattered throughout the fragment and dispersal was short (alleles continued to be lost; observed heterozygosity dropped 13.3% and was still rapidly declining; and inbreeding and/or subdivision were moderate (Fit = 0.12) and still rapidly increasing). Such comparative modeling can be used to suggest removal patterns that might greatly outperform other removal modalities in terms of suppressing the return of weed populations. The effectiveness of such modeling will be improved by acquisition of accurate life history information of targeted species.

Keywords

Callery pear, Pyrus calleryana DecneBiological suppressioninvasive controlplant population biologyplant population geneticsweed management
Type
Weed Management
Information
Weed Science , Volume 63 , Issue 3 , September 2015 , pp. 703 - 709
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

Blackwood, J, Hastings, A, Costello, C (2010) Cost-effective management of invasive species using linear-quadratic control. Ecol Econ. 69:519–527 Google Scholar
Culley, TM, Hardiman, NA (2007) The beginning of a new invasive plant: a history of the ornamental Callery pear in the United States. BioScience. 57:956–964 Google Scholar
Culley, TM, Hardiman, NA (2009) The role of intraspecific hybridization in the evolution of invasiveness: a case study of the ornamental pear tree Pyrus calleryana . Biol Invasions. 11:1107–1119 Google Scholar
Deen, W, Weersink, A, Turvey, C, Weaver, S (1993) Weed control decision rules under uncertainty. Rev Agric Econ. 15:39–50 Google Scholar
Epanchin-Niell, RS, Wilen, JE (2012) Optimal spatial control of biological invasions. J Environ Econ Manag. 63:260–270 Google Scholar
Finnoff, D, Potapov, A, Lewis, MA (2010) Control and the management of a spreading invader. Res Ener Econ. 32:534–550 Google Scholar
Gomulkiewicz, R, Shaw, RG (2012) Evolutionary rescue beyond the models. Phil Trans Roy Soc B. 368:1–9 Google Scholar
Hartl, DL (1987) A Primer of Population Genetics, 2nd edn. Sunderland, MA Sinauer Associates. 305 pGoogle Scholar
Hutchinson, TF, Vankat, JL (1997) Invasibility and effects of Amur honeysuckle in southwestern Ohio forests. Conserv Biol. 11:117–1124 Google Scholar
Kashimshetty, Y, Simkins, M, Pelikan, S, Rogstad, SH (2012) Founder placement and gene dispersal affect population growth and genetic diversity in restoration plantings of American chestnut. Pages 375–390 in Caliskan, M, ed. Genetic Diversity in Plants. Shanghai InTech Press. http://www.intechopen.com/articles/show/title/founder-placement-and-gene-dispersal-affect-population-growth-and-genetic-diversity-in-restoration-p. Accessed April 4, 2015Google Scholar
Moody, ME, Mack, RN (1988) Controlling the spread of plant invasions: the importance of nascent foci. J App Ecol. 25:1009–1021 Google Scholar
Murphy, JT, Johnson, MP (2013) Modelling spatial dynamics of plant coastal invasions. Pages 465–470 in Proceedings of the European Conference on Complex Systems 2012. New York Springer International Google Scholar
Pelikan, S, Rogstad, SH (2013) NEWGARDEN: A computer program to model the population dynamics and genetics of establishing and fragmented plant populations. Conser Gen Resources. 5:857–862. http://dx.doi.org/10.1007/s12686-013-9869-9. Accessed April 4, 2015Google Scholar
Pichancourt, JB, Chadès, I, Firn, J, van Klinken, RD, Martin, TG (2012) Simple rules to contain an invasive species with a complex life-cycle and high dispersal capacity. J App Ecol. 49:52–62 Google Scholar
Pimentel, D, Lach, L, Zuniga, R, Morrison, D (2000) Environmental and economic costs of nonindigenous species in the United States. BioScience. 50:53–65 Google Scholar
Pimentel, D, Zuniga, R, Morrison, D (2005) Update on the environmental and economic costs associated with alien-invasive species in the United States. Ecol Econ. 52:273–288 Google Scholar
Rogstad, SH, Pelikan, S (2011) Genetic Diversity in Establishing Plant Populations: Founder Number and Geometry. Boca Raton, FL Science Publishers. 357 pGoogle Scholar