A global dataset to analyse results and quality of meta-analyses on crop diversification

The DiverIMPACTS project developed a dataset providing a comprehensive synthesis of existing experimental data on crop diversification worldwide. The dataset includes the results of 99 meta-analyses assessing the impacts of seven types of crop diversification strategies on the environment, production, and profitability. It is the first comprehensive synthesis of the impacts of crop diversification.

Number of data and of primary studies on crop diversification (Beillouin, Ben-Ari and Makowski, 2019)

Numerous meta-analyses have been conducted in the last three decades to assess the productive and environmental benefits resulting from diversifying cropping systems. These meta-analyses assessed one or several diversification strategies (e.g., rotations, intercropping, 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. The DiverIMPACTS project developed a dataset containing the values of 2382 effect sizes (measures of impact of diversification strategies) published in 99 meta-analyses covering 3736 primary studies worldwide. We also provide an extensive appraisal of the quality of each meta-analysis and accounted for primary studies that were included in more than one meta-analysis.

The database

  • identifies the aggregate impacts identified for a variety of diversification strategies on crop production, the environment and economic profitability at the global scale and,
  • includes a quality and redundancy assessment that may be used as a reference for future synthesis.

The dataset allows scientists and decision makers to quantify and compare the impacts of various crop diversification strategies on the environment (e.g., soil carbon, biodiversity), agricultural production (e.g., crop yield, incidence of plant diseases) and economic profitability. Our dataset can be used to identify knowledge gaps, i.e. combinations of crop diversification strategies and outcomes with a low number of published meta-analyses. Finally, the in-depth quality assessment of the meta-analyses reported in our dataset can help weight evidence on the expected benefits of different types of diversification strategies.

The dataset was recently published in an open access data journal. It will be updated on a regular basis.

Further information