Soil Carbon

The meta-analysis conducted on 20 independent studies assessing the impact of CCs on SOC revealed a consistently positive effect across a range of cropping systems, climatic zones, and study durations (Supplementary Table S1). The average log response ratio (lnRR; Equations 1 and 2) for SOC was 0.39, with an SD of ±0.054; 95% CI: 0.280 to 0.492. This corresponds approximately to a 47.7% increase in SOC relative to control treatments without CCs (based on the exponential transformation: %change ≈ [e^(lnRR) − 1) × 100]. Although all studies reported positive SOC responses (Figure 1), the magnitude varied widely (lnRR ranging from approximately 0.03 to >1.0), resulting in very high heterogeneity (Cochran’s Q statistic was Q = 637.00, df = 19, P < 0.0001; I² = 97%; Equation 3). This high I² value confirms that SOC responses to cover cropping are context dependent and likely influenced by moderators such as cropping systems, climatic conditions, soil types, species mixtures, and sampling depths represented across experiments. Consequently, while the overall effect is positive, the magnitude of SOC change should be interpreted with caution and ideally stratified by these moderating factors in future analyses.

Figure 1. Forest plot showing the effects of cover crops (CCs) on soil organic carbon (SOC). Circles represent the log response ratio (lnRR; Equation 1) for individual studies, and horizontal bars indicate their 95% confidence intervals (CIs; Equation 2). The solid vertical line denotes the null effect (lnRR = 0), whereas the dashed vertical line indicates the overall pooled effect estimated using a random-effects model. The shaded vertical band represents the 95% CI of the pooled effect. Positive lnRR values indicate increases in SOC relative to control treatments.

Notably, studies that evaluated CCs over long-term periods (i.e., >8 yr) or that included multi-species mixtures combining grasses and legumes generally showed the greatest SOC gains (i.e., Chahal et al. Reference Chahal, Vyn, Mayers and Van Eerd2020; Higashi et al. Reference Higashi, Mu, Komatsuzaki, Miura, Hirata, Araki, Kaneko and Ohta2014). Grasses with high biomass production (i.e., cereal rye [Secale cereale L.], Brachiaria spp., and species mixtures) tend to contribute more carbon inputs to the soil, while legumes may stimulate microbial activity and soil aggregation that favor SOC stabilization. In contrast, short-duration experiments (≤3 yr) tended to show more modest increases in SOC (i.e., Bernaschina et al. Reference Bernaschina, Semmartin, Sainz Rozas and Echeverría2023; Duval et al. Reference Duval, Galantini, Capurro and Martínez2016), likely because measurable changes in SOC require sustained organic matter inputs over multiple growing seasons. These mechanisms help explain the broad gradient of SOC responses observed across studies.

Effect sizes varied widely across studies. The smallest SOC response (lnRR ≈ 0.05) was reported in evaluations emphasizing methodological constraints or conservative sampling frameworks, suggesting that narrow soil depth, short experimental duration, or limited biomass inputs can restrict detectable SOC gains (Chaplot et al. Reference Chaplot, Rumpel and Valentin2023; Duval et al. Reference Duval, Galantini, Capurro and Martínez2016). In contrast, the largest responses (lnRR ≈ 1.0) were observed in long-term systems with substantial annual CC biomass returns, particularly in temperate humid vegetable production systems. These strong effects likely reflect sustained organic matter inputs and favorable conditions for SOC accumulation. Intermediate responses were common and spanned a broad range of environments and management contexts, reflecting variation in CC species composition, residue quality, climate, soil type, and cropping system intensity. Intermediate effects were reported in global syntheses such as Joshi et al. (Reference Joshi, Sainju, Wang, Allen, Mikha, Lenssen and Sadeghpour2023), which focused specifically on maize-based systems, estimating a mean SOC increase of 0.88 Mg ha⁻¹ yr⁻¹, equivalent to a moderate lnRR of around 0.63. Importantly, all included studies (regardless of geographic scope or methodological emphasis) reported positive lnRR values, reinforcing the robustness of the effect.

In practical terms, our synthesis suggests that farmers can expect substantial and agronomically meaningful increases in SOC following CC adoption, especially when implementing multi-species mixtures, grass-based systems, or long-duration CC programs. While the variability of outcomes underscores the importance of site-specific management, the overall signal is robust: CCs are an effective strategy for enhancing soil carbon sequestration across a wide range of production systems.

Crop Yield

We included in this analysis 18 studies that evaluated the effect of CCs on the yield of extensive cropping systems, such as maize, soybean, wheat, and barley (Hordeum vulgare L.) (Supplementary Table S2). The aggregated effect size was slightly positive but not statistically significant (P = 0.13), with a combined lnRR of 0.052 and a 95% CI of [−0.015; +0.119] (Equations 1 and 2). This result indicates that, on average (+5.3% [CI: −1.5% to +12.6%]), CCs did not significantly increase or decrease subsequent crop yield (Figure 2). However, study to study variability was high, as shown by a heterogeneity statistic of Q = 179.17 (df = 17) and I² = 90.5% (Equation 3), reflecting strong context dependence in yield responses to CCs. Most studies reported small but positive effects on yield (lnRR between −0.015 and 0.119), suggesting that CCs tend to enhance productivity modestly under many conditions. However, one study (Tennakoon and Hulugalle Reference Tennakoon and Hulugalle2006) showed a much larger effect (lnRR ≈ 0.55), likely due to improved soil fertility, water retention, or nutrient cycling in that specific production environment. In contrast, few studies reported negative yield responses (i.e., Abdin et al. Reference Abdin, Coulman, Cloutier, Faris, Zhou and Smith1998; Deines et al. Reference Deines, Kendall and Hyndman2022; Fiorini et al. Reference Fiorini, Maris, Abdala-Roberts and Moonen2022), with lnRR values around −0.05 to −0.15. Such reductions are often associated with competition for water or nitrogen, particularly in dry environments, coarse-textured soils, or when termination is late and residue persists into the early crop establishment period. This substantial heterogeneity suggests that the yield response is highly context dependent, influenced by factors such as CC species, agricultural management practices (termination method and timing), climate, and soil characteristics. Although the average effect is close to neutral, certain CC–crop combinations or environments may lead to yield benefits or trade-offs.

Figure 2. Forest plot showing the effects of cover crops (CCs) on successor crop yield. Points represent the natural log response ratio (lnRR; Equation 1) for individual studies, and horizontal bars indicate the corresponding 95% confidence intervals (CIs; Equation 2). The solid vertical line denotes the no-effect value (lnRR = 0), whereas the dashed vertical line indicates the overall pooled effect estimated using a random-effects model. The shaded vertical band represents the 95% CI of the pooled effect. Positive lnRR values indicate higher successor crop yield following cover cropping compared with control treatments without CCs.

Although the overall yield response to CCs is close to neutral, this outcome should not necessarily be viewed as negative. Maintaining yields while achieving soil, weed, or environmental benefits represents a desirable outcome for producers. In many cases, neutral yield effects indicate that CCs can deliver ecosystem services without compromising productivity. Moreover, yield stability under stressful conditions (i.e., drought or nutrient limitation) and potential reductions in input use may translate into net economic gains and improved system resilience. Identifying configurations that maximize soil benefits without compromising yield represents a key management challenge and an opportunity for site-specific, optimized cover-cropping strategies.

Weed Biomass

The CCs exerted a strong and highly consistent suppressive effect on weed biomass across the 17 studies included in this meta-analysis. The combined effect size was markedly negative, with a mean lnRR of −1.759 (Equations 1 and 2) and a 95% CI of −2.034; −1.485, indicating an average 82.8% reduction in weed biomass relative to control treatments without CCs (Figure 3). However, the heterogeneity was extremely high (Q = 2481.55, df = 19, I² = 99.2%; Equation 3), indicating that while suppression is consistent, its magnitude varies widely. Such variability may be attributed to differences in CC biomass production, species used (monocultures vs. mixtures), and timing of sowing or termination. For example, studies such as Malaspina et al. (Reference Malaspina, Altieri, García and Michelena2023) and Tennakoon and Hulugalle (Reference Tennakoon and Hulugalle2006) reported exceptionally large effects (lnRR ≈ −3.0), corresponding to >95% reduction in weed biomass. Such strong suppression likely reflects combinations of high CC biomass, rapid early-season establishment, or the presence of species with strong allelopathic traits. In contrast, moderate lnRR values (≈ −1.0 to −1.5) were observed in studies where CC biomass was lower, residues were thinner, or climatic conditions limited early canopy development.

Figure 3. Forest plot showing the effects of cover crops (CCs) on weed biomass. Points represent the natural log response ratio (lnRR; Equation 1) for individual studies, and horizontal bars indicate the corresponding 95% confidence intervals (CIs; Equation 2). The solid vertical line denotes the no-effect value (lnRR = 0), whereas the dashed vertical line indicates the overall pooled effect estimated using a random-effects model. The shaded vertical band represents the 95% CI of the pooled effect. Negative lnRR values indicate reductions in weed biomass under CCs compared with control treatments without CCs.

The variability in weed biomass reduction also reflects differences in weed communities and in the functional composition of the CCs used. Most of the studies included in this meta-analysis targeted early-emerging annual weeds such as redroot pigweed (Amaranthus retroflexus L.), common lambsquarters (Chenopodium album L.), barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.], and large crabgrass [Digitaria sanguinalis (L.) Scop.], which are typical of temperate cropping systems (Supplementary Table S3). These species are highly responsive to shading and residue interference, making them particularly sensitive to CC biomass and canopy development. Regarding CC type, approximately 60% of the studies involved fall-seeded species (rye, vetch, clover [Trifolium spp.], and radish [Raphanus sativus L.]), 25% spring-seeded species (buckwheat [Fagopyrum esculentum Moench], mustard [Sinapis alba L.], oat [Avena sativa L.]), and 15% multi-season or perennial covers. Monoculture represented about two-thirds of the dataset, while mixtures, mainly combinations of grasses and legumes, accounted for the remainder. In general, fall-seeded and mixed CCs provided more consistent weed suppression (average lnRR ≈ −0.45) than spring-seeded or single-species covers (≈ −0.30), highlighting the influence of seasonal timing and functional diversity on weed control outcomes (Baraibar et al. Reference Baraibar, Hunter, Schipanski, Hamilton and Mortensen2018; Osipitan et al. Reference Osipitan, Dille, Assefa, Radicetti, Ayeni and Knezevic2019).

The consistent suppression of weed biomass by CCs has significant implications for the long-term dynamics of weed populations. By interspecific competition, CCs reduce aboveground weed growth and limit seed production, resulting in reduced seed rain and progressively depleting the soil seedbank, particularly in annual species (Baraibar et al. Reference Baraibar, Hunter, Schipanski, Hamilton and Mortensen2018; Mirsky et al. Reference Mirsky, Ryan, Teasdale, Curran, Reberg-Horton, Spargo and Wells2010). Over successive seasons, this can lead to a notable decline in weed recruitment (Nichols et al. Reference Nichols, Verhulst, Cox and Govaerts2015). In parallel, CCs often suppress dominant or early-emerging weed species more effectively than no-CC controls (managed either with tillage or herbicides), potentially shifting weed community composition toward small-seeded, shade-tolerant, or late-emerging species that are more likely to escape suppression (Smith et al. Reference Smith, Atwood and Warren2020; Sosnoskie et al. Reference Sosnoskie, Herms and Cardina2012). The physical shading and chemical interference (i.e., allelopathy) caused by CCs can also disrupt the synchrony between weed life cycles and optimal environmental cues, reducing reproductive success and weakening population persistence (Teasdale and Mohler Reference Teasdale and Mohler2000; Weston and Duke Reference Weston and Duke2003). Moreover, by reducing reliance on herbicides, cover-cropping strategies lessen the evolutionary pressure driving herbicide resistance, contributing to more sustainable weed control (Mortensen et al. Reference Mortensen, Egan, Maxwell, Ryan and Smith2012; Norsworthy et al. Reference Norsworthy, Ward, Shaw, Llewellyn, Nichols, Webster, Bradley, Frisvold, Powles, Burgos, Witt and Barrett2012). However, this same pressure may select for weeds with strong dormancy, long-term persistence traits, non-dormant weeds or perennials, highlighting the need to diversify CC species and management practices to prevent enrichment of harder to control populations (Darmency et al. Reference Darmency, Colbach and Le Corre2017; Gallandt Reference Gallandt2006). This analysis provides a solid agronomic basis for incorporating CCs as a reliable tool to suppress early-season weeds, reduce interference with the cash crop, and improve the overall efficiency of weed management programs.

Economic Evaluation

To complement the agronomic findings, we incorporated a qualitative economic evaluation based on published cost–benefit data (Basche et al. Reference Basche, Miguez, Kaspar and Castellano2016; CTIC-SARE 2021; Lu et al. Reference Lu, Watkins, Teasdale and Abdul-Baki2000; Mirsky et al. Reference Mirsky, Ackroyd, Cavigelli, Ryan and Teasdale2012). The analysis highlights that although establishment and management costs (∼US$150 ha⁻¹) represent a clear investment, these can be offset by savings in herbicide and fertilizer inputs (up to ∼US$90 ha⁻¹), improved weed and fertility control (∼US$60 ha⁻¹), and gains in land value over time (∼US$25 ha⁻¹). Taken together, these values suggest that cover cropping can be economically favorable relative to conventional weed management strategies when evaluated over multiyear horizons. While the economic assessment was not included in the statistical synthesis, it provides essential context by illustrating how the short-term costs of CC implementation can be balanced by sustained agronomic, environmental, and financial benefits at the farm level.

Overall, this meta-analysis shows that CCs provides a consistent and substantial reduction in weed biomass across studies, with an average suppression of approximately 83%, despite high context-dependent variability. In contrast, yield responses of subsequent cash crops were neutral on average (lnRR = 0.052, P = 0.13), while increases in SOC were positive but heterogeneous, with mean gains of 47.7% strongly influenced by CC species, biomass inputs, and duration of adoption. Together, these results indicate that the most reliable agronomic benefit of CCs is early-season weed suppression, whereas effects on SOC and yield are more variable and system specific. Future research should prioritize long-term, field-based experiments that integrate weed dynamics, soil processes, and cash crop performance to better quantify trade-offs and optimize management strategies across contrasting environments.