Soil sampling studies for estimation of weed seedbanks

Rahman, A.; James, T.K.; Waller, J.E.; Grbavac, N.

doi:10.30843/nzpp.1997.50.11301

Cited by 7 publications

(8 citation statements)

References 9 publications

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“…Most of the authors who have dealt with sample size problems have agreed that to obtain Ôacceptable accu-racyÕ in the estimation of the average number of seeds per sampling unit, the sample size must be Ôextremely largeÕ in a practical field study (Goyeau & Fablet, 1982;Barralis et al, 1986;Lo´pez et al, 1988;Zanin et al, 1989;Dessaint et al, 1996;Ambrosio et al, 1997;Rahman et al, 1997;Clay et al, 1999). The accuracy depends on both the sampling error and the confidence level so that it is necessary to obtain good estimates of sampling error.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of sampling methods and assessment of the sample size to estimate the weed seedbank in soil, taking into account spatial variability

Ambrósio¹,

Iglesias²,

Marín³

et al. 2004

Weed Research

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Summary As field sampling is time consuming, it is necessary to develop efficient sampling techniques to obtain accurate estimates of the weed seedbank in soil. The relative efficiency between sampling schemes depends on the spatial variability in weed seed density across agricultural fields. Spatial variability of the weed seed density was characterized by theoretical correlograms. A systematic sampling (square grill) scheme was considered and it was found that, taking into account spatial variability, this sampling scheme was more efficient than simple random sampling. As a result, the sample size can be reduced in comparison with that given in previous studies, where spatial correlation was ignored. The reduction depends on the correlation structure defined as a function of the ratio, τ, between the nugget effect and the sill of the variogram. The maximum reduction of the sample size, without loss of either precision or confidence level corresponds to the case where there is no nugget effect, τ = 0. The opposite extreme case, where the reduction is nil, corresponds to the case of a pure nugget effect τ = 1. The abaci based on given expressions are provided to determine the sample size in species whose spatial pattern can be fitted either to a Poisson or to a negative binomial distribution.

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Section: Introductionmentioning

confidence: 99%

Evaluation of sampling methods and assessment of the sample size to estimate the weed seedbank in soil, taking into account spatial variability

Ambrósio¹,

Iglesias²,

Marín³

et al. 2004

Weed Research

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“…This may be a good starting point for an integrated weed management programme, however, estimating seedbank size of arable weeds is difficult. We have previously studied sampling methodologies and spatial distribution of weed seeds (Rahman et al 1997;1999) but lack local knowledge on the effect of soil disturbance on seed distribution and resulting weed populations.…”

Section: Introductionmentioning

confidence: 99%

Effect of cultivation methods on weed seed distribution and seedling emergence

Rahman¹,

James²,

Mellsop³

et al. 2000

NZPP

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The influence of four cultivation treatments viz ploughing rotary hoeing power harrowing and no soil disturbance on the distribution of weed seeds in the soil profile was investigated in a field trial Weed seeds were counted by dry sieving soil samples collected from 05 510 1015 and 1520 cm depths The density and species of weeds that emerged in field plots were also recorded at threeweekly intervals Samples from undisturbed plots showed a linear decline with depth Ploughing was the only treatment that caused a significant shift of seeds to the deeper profile Ploughed plots had significantly fewer weed seedlings than other treatments due to lower numbers of both summer grasses and broadleaf weeds Undisturbed plots contained significantly fewer broadleaf species and weed emergence was delayed Implications of these results for seedbank sampling methodology and weed management strategies are discussed

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“…Unfortunately their small size and location in the soil makes estimation of seed density difficult. To address this problem, many studies have been conducted during recent years to optimise soil seedbank sampling for collecting information on seed abundance and distribution (Dessaint et al 1996;Rahman et al 1997).…”

Section: Introductionmentioning

confidence: 99%

Spatial variability of fathen seeds in the soil under repeat maize cropping

Rahman¹,

James²,

Grbavac³

et al. 1999

pnzppc

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Variability in distribution of fathen seeds in the soil was investigated to develop sampling protocols. Vertical distribution of seeds was assessed at 0-2.5, 2.5-5.0, 5.0-10.0 and 10.0-15.0 cm depth. Horizontal distribution of seeds in the top 5cm of soil was assessed in a 20 by 2.5 m grid at 50 cm intervals. Seeds were extracted from the samples by sieving and their viability was assessed. The fathen seed numbers halved with each 5 cm increase in depth. Seed numbers declined along the row in some cases but there was little localised clumping (? 1 m) of the seed. The most efficient method of sampling the fathen seedbank in a large field would be to take samples on a rectangular grid pattern to a depth of 10 cm.

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Soil sampling studies for estimation of weed seedbanks

Cited by 7 publications

References 9 publications

Evaluation of sampling methods and assessment of the sample size to estimate the weed seedbank in soil, taking into account spatial variability

Evaluation of sampling methods and assessment of the sample size to estimate the weed seedbank in soil, taking into account spatial variability

Effect of cultivation methods on weed seed distribution and seedling emergence

Spatial variability of fathen seeds in the soil under repeat maize cropping

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