This dataset comes from the UK-wide Farm Scale Evaluations (FSEs) conducted between 2000 and 2003 to assess the ecological effects of genetically modified (GM) herbicide-resistant versus conventional crop management in spring oilseed rape. Each field was divided into two half-fields that received either the GM or conventional treatment (Treatment), with a total of 62 fields sampled over three years (Year) on 37 different farms (Farm). Each field within a farm was uniquely numbered (Field), and half-fields were labelled (DHalf) according to their treatment allocation. For each half-field, the total abundance of weeds (variate Weeds) was recorded after the last GM herbicide application (“post-herbicide”), and baseline seedbank density (variate Seedbank) was measured before sowing. After excluding fields with missing or suspect seedbank data, the dataset comprises 118 half-field observations from 59 fields. This structure enables analysis of how GM and conventional management regimes impact weed abundance, controlling for initial differences in seedbank densities across a spatially and temporally replicated field trial.
Format
A data frame with 8 variables: ID, Farm, Field, DHalf, Year, Treatment, Weeds, Seedbank.
- ID
Factor. Unique identifier for each half-field observation.
- Farm
Factor. Identifier for each farm (37 farms in total).
- Field
Factor. Field number within each farm (usually 1–3, since different fields were used across years within farms).
- DHalf
Factor. Half-field number within each field (1 or 2), corresponding to experimental treatment allocation.
- Year
Integer. Year of the trial, coded chronologically as 1 (2000), 2 (2001), or 3 (2002).
- Treatment
Factor. Management regime applied to the half-field: "C" (conventional) or "GM" (genetically modified herbicide-resistant crop).
- Weeds
Integer. Total weed abundance recorded in the half-field after the last GM herbicide application.
- Seedbank
Integer. Seedbank density (initial seed count) measured in the half-field before sowing.
Source
Welham, S. J., Gezan, S. A., Clark, S. J., and Mead, A. (2015) Statistical Methods in Biology: Design and analysis of experiments and regression
Examples
summary(aov(log10(Weeds) ~ Year * Treatment + Error(Farm/Field/DHalf),
data = sosr |>
transform(Year = factor(Year))))
#> Warning: Error() model is singular
#>
#> Error: Farm
#> Df Sum Sq Mean Sq F value Pr(>F)
#> Year 2 0.503 0.2515 0.593 0.558
#> Residuals 34 14.419 0.4241
#>
#> Error: Farm:Field
#> Df Sum Sq Mean Sq F value Pr(>F)
#> Year 2 0.253 0.1263 0.57 0.575
#> Residuals 20 4.434 0.2217
#>
#> Error: Farm:Field:DHalf
#> Df Sum Sq Mean Sq F value Pr(>F)
#> Treatment 1 0.617 0.6166 5.415 0.0236 *
#> Year:Treatment 2 0.011 0.0055 0.048 0.9531
#> Residuals 56 6.376 0.1139
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1