Methods to conduct and analyse weed surveys in arable farming: a review

Abstract

Arable weeds always accompany arable farming; however, species and abundances vary in space and change in time. Surveys assess weeds on a large spatial scale. The regional and national importance, the abundances in which weeds occur, is derived from surveys. Environmental and management background data assist to explain the weed vegetation. Arable weed surveys can have an agronomic, a botanical or an ecological purpose-we approach the agronomic viewpoint. Scientific value results from spatial data about the arable weed vegetation for modelling the dependencies and predicting future changes on a large scale. Researchers, botanists, farmers, advisors, herbicide manufacturers and other industry players engaged in weed control can get rationale spatial impressions of trends in the weed vegetation. This review focuses on methodical aspects of weed surveys. Forty-three surveys on farmed fields, mainly but not exclusively undertaken in Europe, done in up to nine crops per survey covering periods of 1 to 67 years and including 59 to 4423 fields were excerpted for suitable methods to conduct and analyse surveys. The methods reflect agronomic and other targets, e.g. from vegetation science. When accessing existing data, the interdependencies of the layout and all targets should be handled with care. When setting up surveys for agronomic purpose, it is worthwhile to include 3 years and apply stratified sampling. We recommend assessing abundances rather than presence only. Weed survey data is most suitable for applying multivariate statistics. We recommend using proven methods, without discouraging to explore others. To collect sound explanatory data demands for robust contacts with land managers. Explanatory variables are important in survey analyses to extract knowledge about the drivers of the weed vegetation. We conclude that extra value can be obtained from existing weed survey data. We propose to setup public-private partnerships as a way to carry on with arable weed surveys.

Management practices influence the competitive potential of weed communities and their value to biodiversity in South African vineyards

“…Weed community composition responds to environmental conditions, as well as to management (Hanzlik & Gerowitt, ), and in this study was observed to differ between drier areas with sandier soils low in nutrients and more humid areas with greater soil clay and silt content and higher nutrient availability (Fig. ).…”

“…Weed surveys took place over 7 weeks between 18 July 2016 and 31 August 2016 to avoid significant changes in composition from early‐season to late‐season weed species (Hanzlik & Gerowitt, ). Vineyards were surveyed at least 8 weeks after the most recent weed management event, to allow any weeds that were going to re‐establish following the control effort to do so.…”

“…Measures of environmental variables known to be important to weed community composition (Hanzlik & Gerowitt, ) were collected from each quadrat according to the methods in Table , on the same date as the winter weed survey of each vineyard. Also, on that date, information on management practices employed in each block of each vineyard was acquired by asking vineyard managers to fill out a questionnaire on what activities they undertook to manage weeds.…”

Factors associated with weed occurrence in Southwest region of Gois

“…According to a recent European study soil texture, soil pH and altitude were also among the most important factors determining weed species composition in conventional soybean fields (Pinke et al, 2016). In Europe and even on other continents weed species composition in different crops was most affected by edaphic factors (especially soil pH and soil texture) and altitude (Hanzlik and Gerowitt, 2016 …”

Maize‐dominated crop sequences in northern Germany: Reaction of the weed species communities

“…Surveys of various arable crops in Europe have revealed the effects of management, location and climate on ‘weeds’ (De Mol, von Redwitz, & Gerowitt, ; Fried, Norton, & Reboud, ; Hanzlik & Gerowitt, , ; Hyvönen, Ketoja, Salonen, Jalli, & Tiainen, ; Lososová et al., ; Pinke, Karácsony, Czúcz, Botta‐Dukát, & Lengyel, ). Crop sequences or the crops grown are regularly included as predictor variable in the management component.…”