Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-11T08:52:35.806Z Has data issue: false hasContentIssue false
  • English
  • Français

The Absolute-Log Method of Quantifying Relative Competitive Ability and Niche Differentiation

Published online by Cambridge University Press:  20 January 2017

Michael F. Carpinelli
Michael F. Carpinelli*
Affiliation:
United States Department of Agriculture, Agricultural Research Service, Burns, OR 97720
*
Corresponding author's E-mail: carpinelli_michael@yahoo.com
Get access Rights & Permissions [Opens in a new window]

Abstract

Plant competition studies designed to quantify interference between species provide valuable information on competitive interactions and on the effects of agronomic practices on those interactions. The effect of each species' density on the growth of itself and on the growth of the other species is quantified in a series of regression models. Traditionally, the models' regression coefficients have been combined in a series of ratios to quantify relative competitive ability and niche differentiation. Coefficients that are negative (positive interference—facilitation, mutualism) or zero (neutral interference or nonsignificant coefficient) do not lend themselves well to ratio-based methodology because of sign cancellation or undefined values, respectively. As a result, ratio-based methodology is limited to using only positive coefficients (negative interference—amensalism, competition). Rather than using ratios, the absolute-log method uses addition and subtraction of coefficients converted to a pseudologarithmic scale, thus allowing for use of coefficients with values that are negative or zero. As a result, the absolute-log method can be used to quantify relative competitive ability and niche differentiation involving all types of interference—negative, positive, and neutral. The absolute-log method includes an optional statistical procedure constructing confidence intervals for the estimates of relative competitive ability and niche differentiation.

Keywords

InterferencecompetitionamensalismfacilitationmutualismSpittersreciprocal yield lawA-A, absolute-antilogAND, absolute-antilog function corollary to NDARC, absolute-antilog function corollary to RCCI, confidence intervalLND, absolute-log method corollary to NDLRC, absolute-log method corollary to RCND, niche differentiation valueRC, relative competitive ability valueSE, standard error
Type
Research Article
Information
Weed Technology , Volume 19 , Issue 4 , December 2005 , pp. 972 - 978
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

Current address: Rangeland Management Specialist, United States Department of Agriculture, Natural Resources Conservation Service, Grants Soil Survey Office, 1041 Mesa Blvd., Suite C, Grants, NM 87020.

References

Literature Cited

Bertness, M. D. and Callaway, R. 1994. Positive interaction in communities. Trends Ecol. Evol. 9:191–193.Google Scholar
Caldwell, M. M., Dawson, T. E., and Richards, J. H. 1998. Hydraulic lift: consequences of water efflux from the roots of plants. Oecologia 113:151–161.Google Scholar
Carpinelli, M. F., Sheley, R. L., and Maxwell, B. D. 2004. Revegetating weed-infested rangeland with niche-differentiated desirable species. J. Range Manage. 57:97–105.Google Scholar
Choler, P., Michalet, R., and Callaway, R. M. 2001. Facilitation and competition on gradients in alpine plant communities. Ecology 82:3295–3308.Google Scholar
Hunter, A. F. and Aarssen, L. W. 1988. Plants helping plants. Bioscience 38:34–40.Google Scholar
Jacobs, J. S., Sheley, R. L., and Maxwell, B. D. 1996. Effect of Sclerotinia sclerotiorum on the interference between bluebunch wheatgrass (Agropyron spicatum) and spotted knapweed (Centaurea maculosa). Weed Techol. 10:13–21.Google Scholar
Mangold, J. M. 2004. Investigating the potential of using R* theory to manage nonindigenous plant invasions. Ph.D. thesis. Montana State University, Bozeman, MT. 136 p.Google Scholar
Pugnaire, F. I. and Haase, P. 1996. Facilitation between higher plant species in a semiarid environment. Ecology 77:1420–1426.Google Scholar
Roush, M. L. 1988. Models of a four-species annual weed community: growth, competition, and community dynamics. Ph.D. thesis. Oregon State University, Corvallis, OR. 218 p.Google Scholar
Sheley, R. L. and Larson, L. L. 1994. Comparative growth and interference between cheatgrass and yellow starthistle seedlings. J. Range Manage. 47:470–474.CrossRefGoogle Scholar
Sheley, R. L. and Larson, L. L. 1996. Emergence date effects on resource partitioning between diffuse knapweed seedlings. J. Range Manage. 49:241–44.Google Scholar
Spitters, C. J. T. 1983. An alternative approach to the analysis of mixed cropping experiments. I. Estimation of competition effects. Neth. J. Agric. Sci. 31:1–11.Google Scholar
Wilson, J. B. and Agnew, A. D. Q. 1992. Positive switches in plant communities. Advances Ecol. Res. 23:263–336.Google Scholar