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Innovative Approaches to Seedbank Studies

Published online by Cambridge University Press:  12 June 2017

Diane L. Benoit,
Douglas A. Derksen and
Bernard Panneton
Diane L. Benoit
Affiliation:
Agric. Canada Res. Stn., Saint-Jean-sur-Richelieu, QUE, Canada J3B 3E6
Douglas A. Derksen
Affiliation:
Agric. Canada Exp. Farm., Indian Head, SK., Canada S0G 2K0
Bernard Panneton
Affiliation:
Agric. Canada Res. Stn., Saint-Jean-sur-Richelieu, QUE, Canada J3B 3E6
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Abstract

Seedbank studies often suffer from major methodological inadequacies such as absence of appropriate statistical data analysis and low sampling intensity. Multivariate analysis and computer mapping are innovative ways to treat seedbank data. Computer contour mapping was used to visualize spatial patterns of a population of common lambsquarters at three intervals during a growing season. At one site, high spring seed density of 600 000 seed m-2 was decreased to 18.3% of its original size by July, while at another site, low spring seedbank of common lambsquarters of 25 000 seed m-2 increased to 40 000 seed m-2 by autumn. Seedbank studies usually report results on total seed density or on densities of the most abundant species because of difficulties in analyzing large species matrices using parametric statistics. Multivariate analysis and specifically canonical discriminant analysis (CDA) are well suited for seedbank populations. The seedbanks of six agricultural habitats were demonstrated to be floristically different based on the analysis of the relative abundance of weed species in each site using CDA. Organic soils either under grassland or cultivated had significantly larger total seedbanks than mineral soils. If seedbanks are to be used in predictive population models, quantitative data that are reliable, rapidly obtained with limited resources, and logistically feasible for large sampling protocols are needed. Image analysis may be a potential rapid technique for weed seed recognition of washed soil samples.

Keywords

Common lambsquarters Chenopodium album L. #3 CHEALComputer mappingcontour mappingmultivariate analysiscanonical discriminant analysisseed recognitionimage analysisCHEAL

Information

Type
Special Topics
Information
Weed Science , Volume 40 , Issue 4 , December 1992, pp. 660 - 669
Copyright
Copyright © 1992 by the Weed Science Society of America 

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