Predictive theory on how plant diversity promotes herbivore suppression through movement patterns, host associations, and predation promises a potential alternative to pesticide-intensive monoculture crop production. We used meta-analysis on 552 experiments in 45 articles published over the last 10 years to test if plant diversification schemes reduce herbivores and/or increase the natural enemies of herbivores as predicted by associational resistance hypotheses, the enemies hypothesis, and attraction and repellency model applications in agriculture. We found extensive support for these models with intercropping schemes, inclusion of flowering plants, and use of plants that repel herbivores or attract them away from the crop. Overall, herbivore suppression, enemy enhancement, and crop damage suppression effects were significantly stronger on diversified crops than on crops with none or fewer associated plant species. However, a relatively small, but significantly negative, mean effect size for crop yield indicated that pest-suppressive diversification schemes interfered with production, in part because of reducing densities of the main crop by replacing it with intercrops or non-crop plants. This first use of meta-analysis to evaluate the effects of diversification schemes, a potentially more powerful tool than tallies of significant positive and negative outcomes (vote-counting), revealed stronger overall effects on all parameters measured compared to previous reviews. Our analysis of the same articles used in a recent review facilitates comparisons of vote-counting and meta-analysis, and shows that pronounced results of the meta-analysis are not well explained by a reduction in articles that met its stricter criteria. Rather, compared to outcome counts, effect sizes were rarely neutral (equal to zero), and a mean effect size value for mixed outcomes could be calculated. Problematic statistical properties of vote-counting were avoided with meta-analysis, thus providing a more precise test of the hypotheses. The unambiguous and encouraging results from this meta-analysis of previous research should motivate ecologists to conduct more mechanistic experiments to improve the odds of designing effective crop diversification schemes for improved pest regulation and enhanced crop yield.

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High‐throughput sequencing technologies have revolutionized the study of plant‐associated microbial populations, but they are relatively expensive. Molecular fingerprinting techniques are more affordable, yet yield considerably less information about the microbial community. Does this mean they are no longer useful for plant microbiome research? In this paper, we review the past 10 years of studies on plant‐associated microbiomes using molecular fingerprinting methodologies, including single‐strand conformation polymorphism (SSCP), denaturing gradient gel electrophoresis (DGGE), amplicon length heterogeneity PCR (LH‐PCR), ribosomal intergenic spacer analysis (RISA) and automated ribosomal intergenic spacer analysis (ARISA), and terminal restriction fragment length polymorphism (TRFLP). We also present data juxtaposing results from TRFLP methods with those generated using Illumina sequencing in the comparison of rhizobacterial populations of Brazilian maize and fungal surveys in Canadian tomato roots. In both cases, the TRFLP approach yielded the desired results at a level of resolution comparable to that of the MiSeq method, but at a fraction of the cost. Community fingerprinting methods (especially TRFLP) remain relevant for the identification of dominant microbes in a population, the observation of shifts in plant microbiome community diversity, and for screening samples before their use in more sensitive and expensive approaches.