A dataset of meta-analyses on crop diversification at the global scale

Abstract

Numerous meta-analyses have been conducted in the last three decades to assess the productive and environmental benefits resulting from a diversification of cropping systems. These meta-analyses assessed one or several diversification strategies (e.g., rotations, cover crops, agroforestry) according to various outcomes (e.g., productivity, profitability, biodiversity). To date, no dataset has provided a comprehensive synthesis of existing experimental data on crop diversification. We present here a dataset containing 2382 effect sizes published in 99 meta-analyses covering 3736 experimental studies worldwide (https://figshare.com/s/c15a93e96c95f89ddd89). We also provide an extensive appraisal of the quality of each meta-analysis and a quantification of the redundancy of primary studies between meta-analyses. Our database hence provides (i) a quantification of the impacts of a variety of diversification strategies on crop production, the environment and economic profitability at the global scale and, (ii) a quality and redundancy assessment that may be used as a reference for future studies.

Keywords: Agroforestry; Cover crop; Intercropping; Meta-synthesis; Rotation; Systematic review; Variety mixture.

Fig. 1

Locations of the experimental trials of all primary studies (map) and strategies of crop diversification by regions (bars). On the map, the numbers of primary studies are represented by a blue color scale. Countries with no trials on crop diversification in the dataset are colored in grey. On the bar plots, we detail the distribution of the strategies of crop diversification for nine regions and for the world. The legend of the color can be found in the insert at the bottom left of the graphic. The countries of the nine regions are listed below: Central and Southern America: Argentina, Bolivia, Brazil, Chile, Costa Rica, Colombia, Dominican Republic, Ecuador, El Salvador, Guatemala, Guyana, Honduras, Nicaragua, Mexico, Panama, Peru, Uruguay; Eastern Asia: China, Japan, Mongolia, South Korea; Western and Eastern Europe: Austria, Belgium, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Romania, Russia, Serbia, Slovakia, Slovenia, Spain, Switzerland, Sweden, UK, Ukraine; Middle and Southern Africa: Eritrea, Ethiopia, Kenya, Madagascar, Malawi, Mozambique, Rwanda, Uganda, Tanzania, Zambia, Zimbabwe, Cameroon, Central African Republic, Republic of Congo, South Africa, Swaziland; Northern and Western Africa: Algeria, Egypt, Sudan, Western sahara Benin, Burkina Faso, Ivory Coast, Gambia, Ghana, Mali, Morocco, Niger, Nigeria, Senegal, Sierra Leone, Tunisia, Togo; Northern America: Canada, USA; Oceania: Australia, New Zealand; South Estern Asia: Indonesia, Malaysia, Myanmar, Nauru, New Caledonia, Papua New Guinea, Philippines, Samoa, Thailand, Vietnam, Timor-Leste; Western, Southern and Central Asia: Bangladesh, Cyprus, India, Iran, Israel, Jordan, Nepal, Pakistan, Sri Lanka, Syria, Turkey.

Fig. 2

Flowchart of literature search and screening process. Articles initially identified are presented in white. After screening and selection, 99 meta-analyses are included in the database (green). The values indicate the number (and the proportion) of articles excluded/included at each step. C1: Selection criterion 1 (several individual studies are analyzed); C2: Selection criterion 2 (assessment of the impact of at least one strategy of crop diversification). C3: Selection criterion 3 (control plots are present next to treatment plots).

Fig. 3

Compilation of effect sizes (ln(YT/YC), i.e., the log ratios of a measurement in a diversified treatment to its value in a less diversified control) for three diversification strategies: (a) rotation, (b) agroforestry, and (c) associated plant species. Each point corresponds to one effect size from one meta-analysis for one single category of outcome (note that several effect sizes may be affiliated to one single meta-analysis). The figure focuses on the following environmental and production outcomes: biodiversity (yellow), soil quality (grey) and productivity levels (blue). Vertical bars correspond to 95% confidence intervals. The number of data used to calculate each effect size are indicated at the bottom of each graph, when available. In some meta-analyses, the effect sizes were computed for a fraction of its total data sample (e.g., per covariate), but only global effect sizes are presented here. Note though that the totality of effect sizes is available in the table “Effect_size”. Effect sizes that were informed as relative distances were converted to log ratios and integrated in the figure whereas absolute differences and hedge's distances were not.

Fig. 4

Fourteen most frequent botanical families in the primary studies included in the 99 meta-analyses on crop diversification. The most frequent species are indicated in the bar plots (restricted to one species when the total number of species is below 4; and species included in more than 150 primary studies for Gramineae and Fabacea). One primary study can report data for different species and/or families. Gramineae: Barley, Maize, Millet, Oat, Other, Rice, Rye, Ryegrass, Sorghum, Wheat; Fabaceae: Alfalfa, Bean, ChickPea, Clover, Cowpea, Faba Bean, Field Pea, Groundnut, Lentil, Lupin, Other, Garden Pea, Pigeon Pea, Soybean, Vetch; Malvaceae: Cocoa, Cotton; Solanaceae: Potato, Tomato; Brassicaceae: Cabbage, Mustard, Oilseed.

Fig. 5

Dates of publication of the 99 selected meta-analyses (orange) and of their primary studies (green).

Fig. 6

Percentage of common primary studies between meta-analyses (upper plot) and total number of primary studies used in each meta-analysis (bottom plot). Each point corresponds to a pair of meta-analyses. We calculated the percentages of common primary studies between the meta-analyses reported in the x-axis (ID of the meta-analyses) and the others (level of redundancy). We identified the name (ID) of all the meta-analyses with a redundancy level higher than 25%. The numbers at the bottom of the upper plot refer to the percentage of meta-analyses with at least one common primary studies with the meta-analyses reported in the x-axis. For the bottom plot, we distinguished unique primary studies (darkgreen) and primary studies used in at least two meta-analyses (lightgreen).

Fig. 7

Percentage of meta-analyses satisfying each of the 20 quality criteria. Quality criteria are organized in three main groups: review and selection (grey bars), data and statistical analyses (yellow bars) and bias (blue bars).