Arable weed vegetation of the northeastern part of the Czech Republic: effects of environmental factors on species composition

Abstract

Factors determining changes in species composition of arable field weed vegetation in the northeastern part of the Czech Republic were studied. Gradsect sampling, i.e. a priori stratified selection of sampling sites, was used for the field research. Using this method, a data set of 174 vegetation plots, covering a whole range of basic environmental characteristics in the study area, was compiled in 2001-2003. A set of environmental variables (altitude, annual precipitation, mean annual temperature, soil type, soil pH and crop type) together with date of sampling was obtained for each plot. Ordination methods were used to determine the effects of variables on arable weed composition. For each variable, the gross and net effect on weed species composition were calculated. All variables considered in this study had a significant effect on weed species composition and explained 7.25% of the total variation in species data. Major changes in weed species composition in the study area were associated with different crop types. The second most important gradient in the variability of weed vegetation in the study area was associated with altitudinal and climatic changes followed by seasonal changes and different soil types and pH. Our results show that on a regional scale, the relative importance of different crop types and their associated management on changes in arable weed species composition is higher than the relative importance of climatic variables. The relative importance of climatic variables decreases with their decreasing length of gradient.

Diversity of current weed vegetation on arable land in selected areas of the Czech Republic

“…One of the priority factors considered in this regard is the effect of altitude, which is associated with many other ecological habitat parameters and the types of farming used in certain regions (Lososová et al 2004). However, Cimalová and Lososová (2009) show that on regional scale, the relative importance of different crop types and their associated management on changes in arable weed species composition is higher than the relative importance of climatic variables.…”

Effects of environmental factors on weed species composition of cereal and stubble fields in western Hungary

“…Recent investigations undertaken in central and southern Europe indicated that the most important factor in determining weed species composition in arable fields was the type of crop [1][2][3]. Primarily, the different timing of soil cultivation and sowing related to crop species determined the growth of different weed communities [4].…”

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

“…On the one hand, this could be due to the specificity of each region; on the other hand, there are at least some indications for general trends. Firstly, the relative importance of climatic variables and altitude was found to decrease with decreasing length of gradients and thus potentially decreases with smaller spatial scale of a study (Lososová et al 2004;Cimalová and Lososová 2009). However, the same variables are also known to decrease in their relative importance towards southern Europe as they are generally more favourable for the weed vegetation there (Holzner and Immonen 1982;Šilc et al 2009;Pinke et al 2010Pinke et al , 2012.…”

“…The majority of surveys that targeted the species composition of weed communities found similar factors to be important. In different surveys across Europe (Andersson and Milberg 1998;Hallgren et al 1999;Lososová et al 2004;Fried et al 2008;Cimalová and Lososová 2009;Šilc et al 2009;Hanzlik and Gerowitt 2011;Pinke et al 2012) and even on other continents (Tamado and Milberg 2000;Qiang 2005), weed species composition was most affected by the crop, edaphic factors (especially soil pH and soil texture), season, altitude and climate. However, rankings of these factors are highly inconsistent between studies.…”

“…The interpretation of ordination results in indirect methods such as CA or DCA (abbreviations see Table 2) can be simplified by a posteriori and passively projecting the effects of explanatory variables onto the ordination diagram which is widely used (e.g. Cimalová and Lososová 2009;Šilc et al 2009;Májeková et al 2010). However, canonical methods go one step further as they include the possibility to compute the respective importance of environmental factors both as gross effect and, by applying partial ordination (e.g.…”