Effects of landscape simplicity on crop yield: A reanalysis of a global database

Ecological theory on diversity suggests that agriculture requires sufficient biodiversity, ecological function, and critical ecosystem services to remain sustainable and resilient. As such, research related to the effect of ecosystem services and diversity on crop yields has increased significantly in the past decade. One such study by Dainese and colleagues that presented a global synthesis of a compiled database of 1,475 crop experiments related to pollination and pest control ecosystem services and crop yields quickly garnered attention in the literature with more than 540 citations since its publication in 2019. Given the strong influence of this study on the research on diversity and agricultural production, we conduct a reanalysis on the publicly available dataset from the global synthesis study to test the robustness of findings to modeling approach and assumptions. In our reanalysis we apply ordinary least squares regression methods rather than Bayesian path analysis to the same data to examine the robustness of observed field-scale landscape diversity-ecosystem services-crop yield relationships. The result of our reanalysis supports the findings of Dainese and colleagues, illustrating the robustness of findings that suggest that increasing landscape simplicity is associated with lower rates of pollination and pest control ecosystem service provisioning and lower crop yields. However, our analyses also suggest that provisioning of pollination and pest control services account for only a small fraction of the total effect of landscape simplicity on crop yields. Furthermore, we find that management and soil health may mediate the effects of landscape simplicity on ecosystem services and crop yields. While our results complement previous findings for landscape simplicity and ecosystem services, they also indicate that above and below ground ecosystem services are not mutually exclusive but concurrently contribute to support crop production in agriculture.