Crop diversification and parasitic weed abundance: a global meta-analysis

Abstract

Parasitic weeds cause huge annual losses to food production globally. A small number of species from the genera Cuscuta, Orobanche, Phelipanche and Striga have proliferated across many agroecological zones. Their control is compromised due to the lack of efficacy of conventional herbicides and their rapid adaptation to new resistant crop cultivars. A broad range of studies suggest consistent reductions in parasitic weed densities owing to increased spatial (intercropping) and temporal diversity (crop rotation). However, to date, no synthesis of this body of research has been published. Here we report the results of a meta-analysis using 1525 paired observations from 67 studies across 24 countries, comparing parasitic weed density and crop yields from monocrop and more diverse cropping systems. We found both spatial and temporal crop diversification had a significant effect on parasitic weed density reduction. Furthermore, our results show effects of spatial diversification are stronger in suppressing parasitic weeds than temporal effects. Furthermore, the analysis indicates intercrops which alter both microclimate and soil chemistry (e.g. Crotalaria, Stylosanthes, Berseem clover and Desmodium) are most effective in parasitic weed management. This analysis serves to underline the viability of crop diversification as a tool to enhance food security globally.

Figure 1

Maps of weed species locations for studies used for this meta-analysis. As the majority of studies focus on sub-Saharan Africa, the lower map has been used to further identify their distribution within this region. Basemap: Open Street Map Basic base map (obtained through QuickMapServices QGIS plugin), Map data: Open StreetMap contributors.

Figure 2

(A) Log weed densities in intercrops grouped by family, (B) Mean crop yields in intercrops, (C) Log weed densities in crop rotation and (D) Mean crop yields in rotation crops. Fallow is also included. The same set of figures grouped by crop species are included in Appendix 4.

Figure 3

(A) The effect of cropping system (intercrop/rotation) on weed density. (B) The effect of cropping system (intercrop/rotation) on crop yield with crops grouped by family. Effect size (ES) expressed by Hedges g, multiplied by -1 to aid interpretation.

Figure 4

(A) Intercrop effects on weed density ordered by effect size ± SE. Faba beans: n = 4, Wheat n = 30, Sesbania sesban n = 6, Pigeon pea n = 6, Cowpea/Mucuna n = 8, Triticale n = 9, Common bean n = 27, Barley n = 7, Ricebean n = 8, Okra n = 4, Groundnut n = 54, Celosia argentea n = 8, Cowpea n = 66, Soya bean n = 21, Mung bean n = 24, Oat n = 21, Bambara n = 9, Cotton n = 4, Sunflower n = 4, Crotalaria ochroleuca n = 24, Fenugreek n = 27, Stylosanthes guianensis n = 8, Lupin n = 5, Sesame n = 4, Desmodium spp. n = 204, Berseem n = 23. (B) The effects of rotation crops on crop on weed density ordered by effect size ± SE. Fallow n = 11, Sorhgum n = 7, Cereal n = 9, Sesbania spp. n = 11, Winter wheat n = 6, Garden pea n = 4, Rapeseed n = 8, Crotalaria spp. n = 4, Cowpea n = 10, Groundnut n = 14, Sunflower n = 4, Barley n = 4, Coriander n = 4, Cumin n = 4, Alfalfa n = 6, Broccoli n = 5, Mung bean n = 4, Berseem n = 6, Foxtail millet n = 6, Chickpea n = 4, Sugar beet n = 6, Common bean n = 8, Sesame n = 10, Soya bean n = 30, Flax n = 8, Pepper n = 13, Fenugreek n = 6, Maize n = 22, Wheat n = 4, Cotton n = 6. Effect size (ES) expressed by Hedges g. Crops with ≤ 3 data points were omitted for concise presentation.

Figure 5

(A) Parasitic weed densities and mean annual rainfall ± SE, (B) Weed densities and precipitation seasonality (coefficient of variation for rainfall) ± SE, (C) Weed densities and altitude ± SE, (D) Weed densities and mean annual temperature ± SE. The effects of climatic altitude and altitude on weed densities were significant for several linear models (see Table 2). Data were obtained from non-manipulated initial weed densities in field/farm trials or landscape studies.