Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis

Abstract

Along with other resources, weeds compete for soil moisture with crops, which can impact the germination, growth, and seed production of weeds; however, this impact has not been systematically recorded and synthesized across diverse studies. To address this knowledge gap, a global meta-analysis was conducted using 1,196 paired observations from 86 published articles assessing the effect of water stress on weed germination, growth characteristics, and seed production. These studies were conducted and published during 1970-2020 across four continents (Asia, Australia, Europe, and North America). Imposed water stress was expressed as solution osmotic potential (ψ solution ), soil water potential (ψ soil ), or soil moisture as percent field capacity. Meta-analysis revealed that water stress inhibits weed germination, growth, and seed production, and the quantitative response intensified with increasing water stress. A ψ solution greater than -0.8 MPa completely inhibits germination of both grass and broadleaf weeds. A ψ solution between -0.09 to -0.32 MPa reduces weed germination by 50% compared with the unstressed condition. Moderate soil water stress, equivalent to 30-60% field capacity, inhibits growth characteristics (branches or tillers per plant, leaf area, leaves per plant, plant height, root, and shoot biomass) by 33% and weed seed production by 50%. Severe soil water stress, below 30% field capacity, inhibits weed growth by 51% and seed production by 88%. Although water stress inhibits weed growth, it doesn’t entirely suppress the ability to germinate, grow, and produce seeds, resulting in weed seedbank accumulation. This creates management challenges for producers because weed seeds can survive in the soil for many years, depending on weed species and environmental conditions. Quantitative information compiled in this meta-analysis can be instrumental to model the weeds’ multi-dimensional responses to water stress and designing integrated weed management strategies for reducing weed seedbank.

Does narrow row spacing suppress weeds and increase yields in corn and soybean? A meta-analysis

“…Observations with zero values for response variables were replaced with the minimum possible values (e.g., 0.1% for 0% weed control, 0.1 g for 0 g weed biomass). This is because response ratios cannot be calculated if the treatment value is zero (Singh et al 2022; Thapa et al 2018a).…”

“…The 99% CIs were calculated to lower the chances of experiment-wise type I errors. The mean effect of narrow row spacing was considered significant (P < 0.01) when 99% CIs of each subgroup did not contain zero; they were considered significantly different from one another when there was no overlap of their 99% CIs (Singh et al 2022; Thapa et al 2018a).…”

“…This prevented the creation of meaningful funnel plots to test publication bias. Therefore, an alternative, indirect, and visual approach was used in which density plots were used to assess the distribution of individual effect sizes for each response variable (Basche and DeLonge 2017; Singh et al 2022; Thapa et al 2018a). When creating density plots, imputed effect sizes (i.e., effect sizes where observed zero values were replaced with minimum possible values) were excluded.…”

“…However, this may result in non-independent effect sizes within and among the studies. To account for non-independence among individual effect sizes, a multilevel mixed-effects meta-analysis model was created using the NLME package in R (see Supplementary Materials for the R code) (Pinheiro et al 2023; Singh et al 2022; Thapa et al 2018b; Van den Noortgate et al 2013). In this model, effect sizes were included as a fixed effect, site-year/common control treatments were included as nested random effects, and w i values acted as weighting factors.…”