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Introducing an abundance index for assessing weed flora in survey studies
Author(s) -
MOEINI MEHDI M.,
BAGHESTANI MOHAMMAD A.,
MASHHADI HAMID R.
Publication year - 2008
Publication title -
weed biology and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 36
eISSN - 1445-6664
pISSN - 1444-6162
DOI - 10.1111/j.1445-6664.2008.00293.x
Subject(s) - weed , abundance (ecology) , flora (microbiology) , relative species abundance , biology , sampling (signal processing) , ecology , agronomy , physics , genetics , bacteria , detector , optics
This study was carried out to propose a simple abundance index (AI) of weed species, to describe the ranking of weeds in weed communities, and to evaluate weed flora. Based on a 4 year weed survey program conducted in Tehran province, the Thomas methodology for determining the relative abundance (RA) in weed communities was applied and a new, improved method (called the AI method) was introduced. Sixty‐one irrigated wheat fields were selected using a stratified sampling procedure. The boundaries of each county in the province formed the strata. For the Thomas method, the data were summarized for each county using five quantitative measures for determining the RA of each species. For the AI method, three quantitative measures were used, including frequency, uniformity, and mean field density. In the Thomas method, the mean field density had a significant role in determining the RA of a species, while the frequency and uniformity had a less significant role. However, for determining the AI, the frequency and uniformity had a higher value than the mean field density. Higher values for these two parameters for a particular species indicates that this species was more compatible with the soil and climate conditions in which it was growing, while higher values for the mean field density for a particular species indicates that the species had a higher competitive or reproductive ability than other species. In the Thomas method, the weed species with a low mean density were less abundant and not a serious weed for agroecosysytems but, in the AI method, an invasive weed could be detected before the colonization stage.