Abstract
Maintaining yield when reducing inputs is one prime objective of sustainable agriculture. In this context, cereal-legume intercropping is a practice that can achieve increased yield under low-input conditions through the complementary use of abiotic resources and facilitation mechanisms. Many management options exist to design cereal-legume intercropping systems, among which the choice of the species intercropped and the level of nitrogen (N) fertilization are essential. In this study, we collected the results of 35 field experiments across Europe of cereal-grain legume intercrops that combined various intercropped species and N fertilization levels. We first assessed the intensity of the biodiversity effect and its components in unfertilized intercrops. Then, we focused on a subset of systems to analyze how N fertilization influenced biodiversity effects on three intercrops (durum wheat/pea, soft wheat/pea, and durum wheat/faba bean). The biodiversity effect represents the gap between the observed and expected yields of a mixture. The complementarity effect is the performance of mixtures relative to the performance of the component monocultures. The selection effect captures the extent to which a species with a high monoculture yield dominates a mixture at the expense of the other intercropped species. Our results confirmed an overall positive biodiversity effect under unfertilized conditions and various climate conditions (0.86 ± 0.04 t.ha−1). Complementarity effect was the main driver as it represented 76% of the biodiversity effect, confirming intercropping as a useful practice in low-input systems. N fertilization lowered the complementarity effect in durum wheat/pea intercrops, did not influence these effects in soft wheat/pea intercrops, and increased only the selection effect in durum wheat/faba bean intercrops. These results highlight the need for a sufficiently competitive legume in intercrops when N fertilizers are applied in order to avoid too much disruption of plant–plant interactions.
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1 Introduction
From 1960 to 2000, the use of fertilizers, irrigation, and pesticides mitigated effects of climatic hazards, soil heterogeneity, and pest pressure, and had a large and positive impact on crop yield (Tilman et al. 2002). More recently, especially in Europe, the growing trend of reducing inputs in agricultural systems, due to environmental and social concerns, and the climatic uncertainty caused by climate change have increased the variability in cropping conditions compared to that of the intensive agriculture practiced in the late twentieth century. To reduce the negative consequences of climatic uncertainty and continue to produce enough food while reducing the use of inputs (Sadras and Denison 2016), a promising avenue is to favor functional complementarity of abiotic resource use and biological regulations between plants by designing innovative agricultural practices and systems (Duru et al. 2015). This can be achieved by selecting relevant plant phenotypes (Lynch 2019) and/or using positive biodiversity effects through plant mixtures, also known as the biodiversity–ecosystem function (BEF) effects (Brooker et al. 2021).
Positive BEF effects on ecosystem services have been widely studied in natural communities (Cardinale et al. 2012), and interest in using them in cropping systems has increased in the past several years (Gurr et al. 2016; Martin-Guay et al. 2018; Brooker et al. 2021). Analyzing the diversity–productivity relationship enables the effect of biodiversity on primary production of a given system to be estimated and can divide it into complementarity and selection effects (Loreau and Hector 2001). The former measures the effect due to niche complementarity and/or facilitation, while the latter measures the effect due to the dominance of a given species that fits well with the growth environment. Thus, BEF effects should be viewed as resulting from particularly positive specific interactions rather than explaining underlying processes themselves (Maier 2012). As Brooker et al. (2021) highlight, a collaboration gap between BEF scientists and crop scientists has led to a poor understanding of “the operation of positive diversity effects in intensive agricultural systems” and thus of how to enhance them.
In agricultural systems, plant diversity can be promoted by a range of intercropping practices (i.e., combining at least two crop species in the same field for most of their growing periods), which may improve crop yield (Li et al. 2020a). Several mechanisms can, for example, improve nitrogen (N) acquisition by the intercrops, including complementary distribution of roots in soil volumes (Postma and Lynch 2012), use of distinct forms of N in soils (McKane et al. 2002), and fixation of atmospheric N2 by one species in the intercrop (Jensen et al. 2020). In a context of input reduction, the use of N2-fixing legumes is particularly promising. In Europe, this has been widely demonstrated in low-input cereal-legume intercrops, with an increase in total yield and cereal grain quality compared to those of sole crops (Bedoussac et al. 2015). However, supplying too much N fertilizer can cause the cereal to dominate the legume, which decreases positive plant–plant interactions in intercropping systems (Pelzer et al. 2012). Thus, the extent to which N fertilization can be used without compromising BEF effects in such systems remains unclear. More particularly, while recent meta-analyses and reviews generally agree upon positive BEF effects when multiple experiments are assessed, the results of individual experiments have high variability (Bedoussac et al. 2015; Gurr et al. 2016; Raseduzzaman and Jensen 2017; Martin-Guay et al. 2018). Few recent studies underline a positive effect on intercrops’ yield, via temporal niche differentiation (Yu et al. 2015, 2016; Dong et al. 2018; Li et al. 2020b).
In this study, using a database of 35 field experiments (Fig. 1) from five European countries, we first assessed the intensity of the biodiversity effect in winter and spring cereal-grain legume intercrops under unfertilized conditions. Then, focusing on a subset of three winter intercrops—durum wheat (Triticum turgidum L.)/pea (Pisum sativum L.), soft wheat (Triticum aestivum L.)/pea, and durum wheat/faba bean (Vicia faba L.)—we tested the influence of two levels of N fertilization (moderate and high) on the biodiversity effect depending on the intercropped species considered.
2 Materials and methods
2.1 Field experiments
To estimate the net biodiversity effect on intercrop productivity in a wide range of environmental conditions, we collected results from 35 factorial experiments conducted in five countries (France, Denmark, Italy, Germany, and the UK; Fig. 2A), as detailed hereafter.
We used the following criteria to include set of experiments in our database: (1) grain yield was measured for both species in sole- and intercropping conditions, (2) different species and genotypes were used among cereal and legumes, and (3) a given mixture was observed at least in two locations.
2.1.1 Environmental conditions
Climate conditions of each experiment were characterized using the following variables retrieved from the NASA POWER API: the sum of precipitation (mm) and mean temperature (°C) during the crop cycle (from sowing to harvest dates). The experiments were separated into two groups: winter crops, which had higher precipitation (280–712 mm) and lower mean temperature (6.8–11.3°C) during the crop cycle, and spring crops, which had lower precipitation (60–366 mm) and higher mean temperature (12.3–17.3°C) (Fig. 2B).
2.1.2 Agricultural management
All experiments included cereal-grain legume intercrops of two annual crop species and their corresponding sole crops for which grain yield (t.ha−1) was measured at harvest. Cereals and legumes were each represented by three species: barley (Hordeum vulgare L.), durum wheat and soft wheat for the cereals and faba bean, lentil (Lens culinaris L.), and pea for the legumes (Table 1). In the database, 39% and 61% of the intercrops were spring or winter crops, respectively. Intercropped species were sown and harvested at the same time. The sowing dates ranged from March 11 to May 3 for spring crops and from October 25 to December 15 for winter crops. The harvest dates for all crops ranged from June 6 to August 23.
In the database, 54% of the intercrops were grown in a substitutive design (i.e., the sum of the relative sowing densities of the two species intercropped equals 1), while 46% were grown in an additive design (i.e., the sum of relative sowing densities exceeds 1). A species’ relative density is its sowing density in the intercrop relative to that in its reference sole crop. Consequently, the database contained 199 sole crop experimental units and 307 intercrop experimental units (site × year × mix of genotypes × relative densities × N treatment), of which 140 were in an additive design and 167 in a substitutive design. Depending on the experiment, each experimental unit was replicated 2–8 times.
Additional details on experimental designs and management practices are reported in the reference publications of 33 of the 35 experiments (Knudsen et al. 2004; Corre-Hellou et al. 2006; Hauggaard-Nielsen et al. 2008, 2009; Launay et al. 2009; Bedoussac and Justes 2010a, b; Naudin et al. 2010, 2014; Pelzer et al. 2016; Tang et al. 2016; Viguier et al. 2018; Gaudio et al. 2021).
2.2 Estimating the biodiversity effect on intercrop performance
For each experimental unit, grain yield (t.ha−1) was measured for each species. We calculated the biodiversity effect (BE, Loreau and Hector 2001) as the observed grain yield minus expected grain yield in intercrops (Eq. 1):
where YOC and YOL are the observed yields of the cereal and legume grown in intercrop, respectively, and YEC and YEL are the expected yields of the cereal and legume grown in intercrop, respectively.
Expected yield was estimated from the yield of the species in sole crop weighted by its scaled relative density in intercrop (Eq. 2; Li et al. 2020a):
where Mc and ML are the yields of the cereal and legume in sole crop, respectively, and RDC and RDL are the relative densities of the cereal and legume in intercrop, respectively. Grain yield in sole crops and intercrops is calculated as the mean from each replicate of every experimental units, within each experiment.
As mentioned, the biodiversity effect can be divided into a selection effect (SE, Eq. 3) and a complementarity effect (CE, Eq. 4) (Loreau and Hector 2001; Li et al. 2020a):
These formulas, used to compute selection and complementarity effects, are only valid in bispecific mixtures.
The first term of Eq. 3 calculates the difference in increase or decrease in yield between the two species intercropped, while the second term calculates the difference between their sole crop yields. Thus, a positive selection effect means that the species with the higher yield in sole crop has a higher relative increase in yield in intercrop (i.e., benefits more from intercropping).
Into the equation for the complementarity effect (Eq. 4), we introduced the classic land equivalent ratio, which is used to calculate land-use efficiency (LER = YC/MC + YL/ML; Willey and Rao 1980). Thus, the complementarity effect equals the land equivalent ratio minus 1, multiplied by M, the mean yield in sole crops.
2.3 Experimental design, data processing, and analysis
The data were curated and formatted in a database. The data were ordered, reshaped, and homogenized using the collection of R packages tidyverse (Wickham et al. 2019).
The dataset was unbalanced (i.e., groups had different numbers of observations) because the experiments collected were conducted for different purposes and examined many factors (e.g., N fertilization, intercrop design) (Table 1). Thus, the influence of several of the factors on the biodiversity effect and its components could not be analyzed, especially due to the lack of certain treatments in some experiments and to the nesting of factors. For example, only 12 of the 35 experiments tested N fertilization levels, or the species effect also included site and year effects (e.g., spring barley/faba bean intercrops were grown only in Denmark, so they could not be analyzed properly). The statistical analysis performed was adjusted in response to this unbalanced structure.
We first investigated the overall behavior of mean biodiversity, complementarity and selection effects within the unfertilized cereal-legume intercrops in the 35 experiments, and the correlation between the biodiversity effect and each of its components. Thus, our goal was to assess the influence of N fertilization on the biodiversity effect and its components. N fertilization ranged from 0 to 180 kg N.ha−1, which we split into three levels: null, moderate (30–80 kg N.ha−1) and high (> 80 kg N.ha−1). A factorial design was then defined between the species intercropped and these levels of N fertilization. The subset of our database with a factorial design of species and N fertilization levels corresponded to three intercrops: durum wheat/pea, soft wheat/pea, and durum wheat/faba bean (70 experimental units, among which 62 are in substitutive design, all located in France, Table 1). Durum wheat/pea and durum wheat/faba bean intercrops were grown in experiments with moderate and high levels of N fertilization, while soft wheat/pea intercrops were grown only with a moderate level of N fertilization.
The effect of N fertilization on the biodiversity effect and its components in intercrops was assessed using the Bayesian approach. Bayesian inference is based on reallocating credible values for a parameter (posterior distribution) given prior knowledge (prior distribution) and the adequacy of the data to the model (likelihood). The Bayesian approach provides information about the probability of a hypothesis being true given the data (P(hypothesis|data)). Bayesian estimation for the difference in group means (Kruschke 2018) is an alternative to the classic Student’s t test to compare the means of two groups. This method calculates a posterior distribution for the mean differences between the two groups and derives a 95% highest density interval (HDI), which is defined as the 95% most credible values of the parameter. We performed Bayesian estimation for the difference in mean values of components of the biodiversity effect between N-fertilized (moderate and high) and unfertilized treatments for each of the three intercrops. The null hypothesis (H0) was defined as equal mean biodiversity effect components for N-fertilized and unfertilized intercrops. We applied the following decision rule to the position of the 95% HDI: reject H0 if the 95% HDI excludes 0 but do not reject H0 if it includes 0.
All indicator calculations and statistical analyses were performed with R software, v. 4.0.0 (R Core Team 2020). Bayesian statistical analyses were performed using the R package BEST (Kruschke and Meredith 2020).
2.4 Definition of references for fertilized legumes
A common assumption when calculating indicators to compare the performance of intercrops to that of sole crops is that N is not a limiting resource for legumes and does not influence their yield (e.g., Pelzer et al. 2012). To test this hypothesis, we performed Bayesian estimation for the difference in group means between N-fertilized and unfertilized legume sole crops. The database contained only three experiments (i.e., 11 experimental units) in which legume sole crops were N-fertilized, because the experiments we collected were designed to conform to agronomic practices of farmers, who rarely fertilize legume sole crops (Magrini et al. 2016). The Bayesian estimation confirmed that N fertilization had no significant influence on the yield of legume sole crops. Given this result and the lack of data on N-fertilized legume sole crops, we used the unfertilized legume sole crops as a reference when calculating the biodiversity effect and its components in all experimental units.
3 Results and discussion
3.1 Distribution of the biodiversity effect and its components in unfertilized intercrops
On the whole dataset, the mean (± 1 standard error) yield gain in unfertilized intercrops equaled 0.86 ± 0.04 t.ha−1 (1.04 ± 0.01 t.ha−1 for additive designs and 0.68 ± 0.00 t.ha−1 for substitutive designs) for a mean total intercrop yield of 3.54 ± 0.08 t.ha−1 (Fig. 3A). These results highlight an increase in the yield of cereal-legume intercrops in most experimental units under unfertilized conditions compared to those of the corresponding sole crops, which agrees with results of several studies (Pelzer et al. 2012, 2014; Yu et al. 2016) and confirms the ability of intercropping to increase grain yield in low-input farming systems (Bedoussac et al. 2015).
However, the increase in yield observed was influenced by the cropping conditions used as references to calculate the biodiversity effect. The unfertilized cereal sole crops used as references had lower grain yield (3.2 ± 0.08 t.ha−1, all cereals pooled) than cereals grown under conventional farming conditions, which are always N fertilized (i.e., a mean grain yield of 6.1 t.ha−1 for the cereals of interest in the five European countries considered for the period covered by the experiments (Food and Agriculture Organization of the United Nations; http://faostat.fao.org/)). Thus, the low yield observed for the unfertilized cereal sole crops contributed greatly to the positive biodiversity effect estimated (Garnier et al. 1997).
The biodiversity effect was strongly and positively correlated with the complementarity effect (r = 0.86, p < 10−15), but it was not correlated with the selection effect (r = −0.01, p = 0.87) (Fig. 3B). Thus, the complementarity effect was the main driver of the yield gain in unfertilized cereal-legume intercrops, meaning that positive plant-plant interactions (i.e., facilitation and/or niche complementarity) rather than the dominance of one of the species increased intercrop yields (Pelzer et al. 2012). However, caution is needed when distinguishing complementarity causes (e.g., niche partitioning, facilitation) of the resulting complementarity effect (Barry et al. 2019). To quantify the relative importance of these processes, specific measurements would be needed, such as symbiotic N2 fixation to reflect differences in N use between cereals and legumes, or a lodging score to quantify mechanical facilitation (e.g., Podgórska-Lesiak and Sobkowicz 2013). As Brooker et al. (2021) highlight, explicitly distinguishing facilitation and niche partitioning would help when applying new analytical and conceptual frameworks to design intercrops. Nevertheless, differences in N use in cereal-legume intercrops is a well-known process in which the more competitive cereal usually takes disproportionally more soil mineral N than the legume, which is forced to compensate by increasing symbiotic N2 fixation (Rodriguez et al. 2020). In a low-input context, this complementarity of N use enables cereals in intercrops to have higher grain yield and quality than cereals in sole crops.
The complementarity effect contributed 76% of the biodiversity effect when the latter was positive (i.e., in 94% of the experimental units), but it contributed only 36% when the latter was negative (i.e., in 6% of the experimental units). In the few cases in which we observed a yield loss in intercrops, the relative contributions of complementarity and selection were reversed: −0.05 ± 0.02 and −0.16 ± 0.02 t.ha−1, respectively. In these cases, the total yield of intercrops were lower than those of corresponding sole crops because the competition between cereals and legumes exceeded the complementarity effect (also reported by Pelzer et al. (2016) for soft wheat/pea intercrops and Baxevanos et al. (2017) for oat/pea intercrops).
3.2 Influence of N fertilization on the biodiversity effect and its components
The biodiversity effect and its components were altered by N fertilization, which is a key practice in agricultural systems. While the biodiversity effect was positive in 100% of the unfertilized experimental units of the data subset considered (i.e., factorial designs of species and N fertilization levels), the percentage of experimental units with a positive biodiversity effect decreased with N fertilization (i.e., 92% and 67% of the experimental units under moderately and highly N-fertilized conditions, respectively) (Fig. 4). Overall, the total intercrop yield increased with N fertilization (4.16 ± 0.18, 5.09 ± 0.24, and 4.62 ± 0.21 t.ha−1 under unfertilized, moderately and highly N-fertilized conditions respectively); specifically, mean grain yield decreased for legumes (2.23 ± 0.12, 1.88 ± 0.19, and 1.84 ± 0.16 t.ha−1 under unfertilized, moderately and highly N-fertilized conditions respectively) but increased for cereals (1.93 ± 0.20, 3.21 ± 0.23, and 2.78 ± 0.15 t.ha−1 under unfertilized, moderately and highly N-fertilized conditions respectively) with N fertilization (Fig. 4). The same pattern was observed for the complementarity effect, which was positive in 96%, 83%, and 56% of the experimental units under unfertilized, moderately, and highly N-fertilized conditions, respectively. Conversely, the percentage of experimental units with a positive selection effect increased with N fertilization: 25%, 71%, and 61% of the experimental units, under unfertilized, moderately, and highly N-fertilized conditions, respectively. Thus, N fertilization tends to decrease positive plant-plant interactions within cereal-legume intercrops by acting on the balance between the two intercropped species to the benefit of the cereal (Pelzer et al. 2012).
The effect of N fertilization on the biodiversity effect and its components depended on the species intercropped (Fig. 5). In durum wheat/pea intercrops, even moderate N fertilization decreased the biodiversity effect significantly by 66% compared to that under unfertilized conditions. This moderate N fertilization increased the selection effect significantly by 0.21 t.ha−1 (99.1% of the posterior values for the difference in group means between N-fertilized and unfertilized conditions were positive), while the complementarity effect decreased by 0.65 t.ha−1 (99.1% of the posterior values for the difference in means were negative). These effects were emphasized under highly N-fertilized conditions (Fig. 5). When focusing on the yield of both species intercropped, N fertilization disadvantaged the legume, since pea yield decreased by a mean of 37% under N-fertilized conditions compared to that under unfertilized conditions, while the opposite was observed for durum wheat, whose yield increased by a mean of 94%. These results could explain the shift in complementarity and selection effects for durum wheat/pea intercrops between N-fertilized and unfertilized conditions. This behavior is usually highlighted in existing literature related to cereal-legume intercrops (e.g., Naudin et al. 2010). Under N-fertilized conditions, selection effect increases because durum wheat has a competitive advantage over the legume (Mariotti et al. 2009; Duchene et al. 2017). Our results showed, however, that choosing a different cereal or legume species can change this effect.
When soft wheat replaced durum wheat in wheat/pea intercrops, N fertilization did not influence the biodiversity effect or its components. Because the cereal and legume yields tended to increase slightly with N fertilization, the latter did not disrupt the balance between the two species (Fig. 5). Based on the soil and climate conditions considered, the level of N fertilization (45 kg N.ha−1) was probably too low, compared to usual N fertilization rates in conventional agriculture, to increase the yield of one or both species significantly, unlike that of durum wheat/pea intercrops (60–140 kg N.ha−1).
Finally, in durum wheat/faba bean intercrops, N fertilization did not influence the biodiversity effect or its complementarity effect, but it did increase the selection effect significantly by 0.3 t.ha−1 and 0.2 t.ha−1 under moderately and highly N-fertilized conditions, respectively (95.5% and 95.2% of posterior values for the difference in group means were positive, respectively) (Fig. 5). This increase was due to an increase in durum wheat yield, since faba bean yield changed little in intercrops as N fertilization increased. This behavior contrasts with that of pea yield when intercropped with durum wheat: pea yield decreased as N fertilization increased. Height and biomass differences between two intercropped species have been shown to influence their yields (Gaudio et al. 2021). Since the faba bean is taller and larger than the pea (Guinet et al. 2018), it showed greater competitive ability (but whether aboveground for light capture or belowground for nutrient and water acquisition remains to be tested), which explains the lack of shift in the biodiversity effect observed in durum wheat/faba bean intercrops.
3.3 Pathway to applications
Because cereal-legume intercrops are used mainly to decrease the use of agricultural inputs, most are managed without synthetic inputs. In this way, our study confirmed an increase in productivity under a wide range of unfertilized cropping conditions, with a balance between the two species intercropped (i.e., no species clearly dominated), although the increase depends on the species intercropped (Cheriere et al. 2020). N fertilization can disrupt this balance, shifting positive plant-plant interactions to a dominance of the cereal at the expense of the legume (e.g., in durum wheat / pea intercrops). This shift appeared at moderate N fertilization levels and even led to lower productivity of intercrops than that of sole crops at the high N fertilization levels applied to wheat sole crops in conventional agriculture (> 100 kg N.ha−1).
It would thus be interesting to identify the level of moderate N fertilization that provides benefits from positive effects of intercropping and positive plant-plant interactions, while increasing the total yield by increasing the cereal yield, as farmers often perform in winter intercrops (Verret et al. 2020). Because this N level is likely to differ among species, future research should focus on the interaction between N fertilization and the intercrop species chosen. For instance, recent meta-analysis (Li et al. 2020b) shows high advantages of N fertilization on mixtures including maize (Zea mays L.).
In our study, only one combination of species × N fertilization had a positive interaction on yield (i.e., durum wheat/faba bean intercrops): cereal yield increased and legume yield remained the same, while in durum wheat/pea intercrops, legume yield decreased. Thus, our results suggest that the legume chosen can be a management mechanism, with the idea that the legume should be sufficiently competitive to counterbalance the increased competition from the N-fertilized cereal (Duchene et al. 2017). Probably, it is the balance of competition between the two components rather than competitiveness of the legume that matters. However, we also observed that the cereal yield stagnated if the N fertilization level was not sufficient (e.g., soft wheat/pea intercrops). Thus, the optimal N fertilization level should depend on the proportion of legume biomass in the intercrop (Naudin et al. 2010). As highlighted by other studies, the species chosen are a relevant mechanism for controlling intercrops’ yield (Cheriere et al. 2020) and suitability for the cropping environment in which they grow (Baxevanos et al. 2017). Finally, it is worthwhile to recall that many barriers to adoption of intercrops in Europe exist, beyond the scope of this article, such as technical and economical ones (Bonke and Musshoff 2020). Different possibilities (e.g., better communication of scientific results, breeding adapted to intercrops) exist to overcome these barriers (Meynard et al. 2018) and allow intercrops to be more widely cultivated.
4 Conclusion
This study highlights that the complementarity between intercropped species is the main driver of the positive biodiversity effect on the performance of cereal-legume intercrops under diverse cropping conditions. If the biodiversity effect depended instead mainly on the selection effect (i.e., if one intercropped species strongly dominated), growing the dominant species alone would be more practical agronomically, which would shift the balance towards sole crops.
While multiple meta-analyses and reviews highlighted the overall yield gain in intercrops, analysis and tools to derive specific management recommendations for farmers from this general knowledge are still lacking (Brooker et al. 2021). We argue that it may be counterproductive to emphasize that biodiversity has this broad beneficial effect while the specific positive interactions between pairs of species and even more so, cultivars, remain to be identified (Maier 2012).
The key question remains how to secure complementarity while intensifying or increasing productivity. When focusing on the response of complementarity processes to N fertilization, we found that behavior differed depending on the species chosen. We highlighted that N fertilization does not always depress complementarity processes as long as the legume species can also benefit from it. Therefore, such shifts in balance need to be understood through the prism of community ecology to develop the use of intercrops in a wider range of agricultural systems besides low-input agriculture.
Data availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
Barry KE, Mommer L, van Ruijven J, Wirth C, Wright AJ, Bai Y, Connolly J, de Deyn GB, de Kroon H, Isbell F, Milcu A, Roscher C, Scherer-Lorenzen M, Schmid B, Weigelt A (2019) The future of complementarity: disentangling causes from consequences. Trends Ecol Evol 34:167–180. https://doi.org/10.1016/j.tree.2018.10.013
Baxevanos D, Tsialtas IT, Vlachostergios DΝ, Hadjigeorgiou I, Dordas C, Lithourgidis A (2017) Cultivar competitiveness in pea-oat intercrops under Mediterranean conditions. Field Crop Res 214:94–103. https://doi.org/10.1016/j.fcr.2017.08.024
Bedoussac L, Journet E-P, Hauggaard-Nielsen H, Naudin C, Corre-Hellou G, Jensen ES, Prieur L, Justes E (2015) Ecological principles underlying the increase of productivity achieved by cereal-grain legume intercrops in organic farming. A review. Agron Sustain Dev 35:911–935. https://doi.org/10.1007/s13593-014-0277-7
Bedoussac L, Justes E (2010a) Dynamic analysis of competition and complementarity for light and N use to understand the yield and the protein content of a durum wheat–winter pea intercrop. Plant Soil 330:37–54. https://doi.org/10.1007/s11104-010-0303-8
Bedoussac L, Justes E (2010b) The efficiency of a durum wheat-winter pea intercrop to improve yield and wheat grain protein concentration depends on N availability during early growth. Plant Soil 330:19–35. https://doi.org/10.1007/s11104-009-0082-2
Bonke V, Musshoff O (2020) Understanding German farmer’s intention to adopt mixed cropping using the theory of planned behavior. Agron Sustain Dev 40:48. https://doi.org/10.1007/s13593-020-00653-0
Brooker RW, George TS, Homulle Z, Karley AJ, Newton AC, Pakeman RJ, Schöb C (2021) Facilitation and biodiversity–ecosystem function relationships in crop production systems and their role in sustainable farming. J Ecol 109:2054–2067. https://doi.org/10.1111/1365-2745.13592
Cardinale BJ, Duffy JE, Gonzalez A, Hooper DU, Perrings C, Venail P, Narwani A, Mace GM, Tilman D, Wardle DA, Kinzig AP, Daily GC, Loreau M, Grace JB, Larigauderie A, Srivastava DS, Naeem S (2012) Biodiversity loss and its impact on humanity. Nature 486:59–67. https://doi.org/10.1038/nature11148
Cheriere T, Lorin M, Corre-Hellou G (2020) Species choice and spatial arrangement in soybean-based intercropping: levers that drive yield and weed control. Field Crop Res 256:107923. https://doi.org/10.1016/j.fcr.2020.107923
Corre-Hellou G, Fustec J, Crozat Y (2006) Interspecific competition for soil N and its interaction with N-2 fixation, leaf expansion and crop growth in pea-barley intercrops. Plant Soil 282:195–208. https://doi.org/10.1007/s11104-005-5777-4
Dong N, Tang MM, Zhang WP, Bao XG, Wang Y, Christie P, Li L (2018) Temporal differentiation of crop growth as one of the drivers of intercropping yield advantage. Sci Rep 8(1):1–11. https://doi.org/10.1038/s41598-018-21414-w
Duchene O, Vian J-F, Celette F (2017) Intercropping with legume for agroecological cropping systems: complementarity and facilitation processes and the importance of soil microorganisms. A review. Agric Ecosyst Environ 240:148–161. https://doi.org/10.1016/j.agee.2017.02.019
Duru M, Therond O, Fares M (2015) Designing agroecological transitions; a review. Agron Sustain Dev 35:1237–1257. https://doi.org/10.1007/s13593-015-0318-x
Garnier E, Navas M-L, Austin MP, Lilley JM, Gifford RM (1997) A problem for biodiversity-productivity studies: how to compare the productivity of multispecific plant mixtures to that of monocultures? Acta Oecol 18:657–670. https://doi.org/10.1016/S1146-609X(97)80049-5
Gaudio N, Violle C, Gendre X, Fort F, Mahmoud R, Pelzer E, Médiène S, Hauggaard-Nielsen H, Bedoussac L, Bonnet C, Corre-Hellou G, Couëdel A, Hinsinger P, Steen Jensen E, Journet E-P, Justes E, Kammoun B, Litrico I, Moutier N et al (2021) Interspecific interactions regulate plant reproductive allometry in cereal–legume intercropping systems. J Appl Ecol 00:1–11. https://doi.org/10.1111/1365-2664.13979
Guinet M, Nicolardot B, Revellin C, Durey V, Carlsson G, Voisin AS (2018) Comparative effect of inorganic N on plant growth and N2 fixation of ten legume crops: towards a better understanding of the differential response among species. Plant Soil 432:207–227. https://doi.org/10.1007/s11104-018-3788-1
Gurr GM, Lu Z, Zheng X, Xu H, Zhu P, Chen G, Yao X, Cheng J, Zhu Z, Catindig JL, Villareal S, van Chien H, Cuong LQ, Channoo C, Chengwattana N, Lan LP, Hai LH, Chaiwong J, Nicol HI et al (2016) Multi-country evidence that crop diversification promotes ecological intensification of agriculture. Nat Plants 2:1–4. https://doi.org/10.1038/nplants.2016.14
Hauggaard-Nielsen H, Gooding M, Ambus P, Corre-Hellou G, Crozat Y, Dahlmann C, Dibet A, von Fragstein P, Pristeri A, Monti M, Jensen ES (2009) Pea-barley intercropping for efficient symbiotic N-2-fixation, soil N acquisition and use of other nutrients in European organic cropping systems. Field Crop Res 113:64–71. https://doi.org/10.1016/j.fcr.2009.04.009
Hauggaard-Nielsen H, Jørnsgaard B, Kinane J, Jensen ES (2008) Grain legume–cereal intercropping: the practical application of diversity, competition and facilitation in arable and organic cropping systems. Renew Agric Food Syst 23:3–12. https://doi.org/10.1017/S1742170507002025
Jensen ES, Carlsson G, Hauggaard-Nielsen H (2020) Intercropping of grain legumes and cereals improves the use of soil N resources and reduces the requirement for synthetic fertilizer N: a global-scale analysis. Agron Sustain Dev 40:5. https://doi.org/10.1007/s13593-020-0607-x
Kammoun B (2014) Analyse des interactions génotype × environnement × conduite culturale de peuplement bi-spécifique de cultures associées de blé dur et de légumineuses à graines, à des fins de choix variétal et d’optimisation de leurs itinéraires techniques (PhD Thesis). Toulouse, INPT, Toulouse, France.
Knudsen MT, Hauggaard-Nielsen H, Jornsgard B, Jensen ES (2004) Comparison of interspecific competition and N use in pea-barley, faba bean-barley and lupin-barley intercrops grown at two temperate locations. J Agric Sci 142:617–627. https://doi.org/10.1017/S0021859604004745
Kruschke JK (2018) Rejecting or accepting parameter values in Bayesian estimation. Adv Methods Pract Psychol Sci 1:270–280. https://doi.org/10.1177/2515245918771304
Kruschke JK, Meredith M (2020) BEST: Bayesian estimation supersedes the t-test. R package version 052 https://CRANR-project.org/package=BEST
Launay M, Brisson N, Satger S, Hauggaard-Nielsen H, Corre-Hellou G, Kasynova E, Ruske R, Jensen ES, Gooding MJ (2009) Exploring options for managing strategies for pea-barley intercropping using a modeling approach. Eur J Agron 31:85–98. https://doi.org/10.1016/j.eja.2009.04.002
Li C, Hoffland E, Kuyper TW, Yu Y, Li H, Zhang C, Zhang F, van der Werf W (2020a) Yield gain, complementarity and competitive dominance in intercropping in China: a meta-analysis of drivers of yield gain using additive partitioning. Eur J Agron 113:125987. https://doi.org/10.1016/j.eja.2019.125987
Li C, Hoffland E, Kuyper TW, Yu Y, Zhang C, Li H, Zhang F, van der Werf W (2020b) Syndromes of production in intercropping impact yield gains. Nature Plants 6(6):653–660. https://doi.org/10.1038/s41477-020-0680-9
Loreau M, Hector A (2001) Partitioning selection and complementarity in biodiversity experiments. Nature 412:72–76. https://doi.org/10.1038/35083573
Lynch JP (2019) Root phenotypes for improved nutrient capture: an underexploited opportunity for global agriculture. New Phytol 223:548–564. https://doi.org/10.1111/nph.15738
Magrini M-B, Anton M, Cholez C, Corre-Hellou G, Duc G, Jeuffroy MH, Meynard JM, Pelzer E, Voisin AS, Walrand S (2016) Why are grain-legumes rarely present in cropping systems despite their environmental and nutritional benefits? Analyzing lock-in in the French agrifood system. Ecol Econ 126:152–162. https://doi.org/10.1016/j.ecolecon.2016.03.024
Maier DS (2012) Theories of biodiversity value. In: What’s so good about biodiversity?. The International Library of Environmental, Agricultural and Food Ethics, vol 19. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-3991-8_6
Mariotti M, Masoni A, Ercoli L, Arduini I (2009) Above- and below-ground competition between barley, wheat, lupin and vetch in a cereal and legume intercropping system. Grass Forage Sci 64:401–412. https://doi.org/10.1111/j.1365-2494.2009.00705.x
Martin-Guay M-O, Paquette A, Dupras J, Rivest D (2018) The new Green Revolution: sustainable intensification of agriculture by intercropping. Sci Total Environ 615:767–772. https://doi.org/10.1016/j.scitotenv.2017.10.024
McKane RB, Johnson LC, Shaver GR et al (2002) Resource-based niches provide a basis for plant species diversity and dominance in arctic tundra. Nature 415:68–71. https://doi.org/10.1038/415068a
Meynard JM, Charrier F, Fares M et al (2018) Socio-technical lock-in hinders crop diversification in France. Agron Sustain Dev 38:54. https://doi.org/10.1007/s13593-018-0535-1
Naudin C, Corre-Hellou G, Pineau S, Crozat Y, Jeuffroy MH (2010) The effect of various dynamics of N availability on winter pea-wheat intercrops: crop growth, N partitioning and symbiotic N-2 fixation. Field Crop Res 119:2–11. https://doi.org/10.1016/j.fcr.2010.06.002
Naudin C, van der Werf HMG, Jeuffroy M-H, Corre-Hellou G (2014) Life cycle assessment applied to pea-wheat intercrops: a new method for handling the impacts of co-products. J Clean Prod 73:80–87. https://doi.org/10.1016/j.jclepro.2013.12.029
Pelzer E, Bazot M, Guichard L, Jeuffroy M-H (2016) Crop management affects the performance of a winter pea-wheat intercrop. Agron J 108:1089–1100. https://doi.org/10.2134/agronj2015.0440
Pelzer E, Bazot M, Makowski D, Corre-Hellou G, Naudin C, al Rifaï M, Baranger E, Bedoussac L, Biarnès V, Boucheny P, Carrouée B, Dorvillez D, Foissy D, Gaillard B, Guichard L, Mansard MC, Omon B, Prieur L, Yvergniaux M et al (2012) Pea–wheat intercrops in low-input conditions combine high economic performances and low environmental impacts. Eur J Agron 40:39–53. https://doi.org/10.1016/j.eja.2012.01.010
Pelzer E, Hombert N, Jeuffroy MH, Makowski D (2014) Meta-analysis of the effect of nitrogen fertilization on annual cereal–legume intercrop production. Agron J 106(5):1775–1786. https://doi.org/10.2134/agronj13.0590
Podgórska-Lesiak M, Sobkowicz P (2013) Prevention of pea lodging by intercropping barley with peas at different nitrogen fertilization levels. Field Crop Res 149:95–104. https://doi.org/10.1016/j.fcr.2013.04.023
Postma JA, Lynch JP (2012) Complementarity in root architecture for nutrient uptake in ancient maize/bean and maize/bean/squash polycultures. Ann Bot 110:521–534. https://doi.org/10.1093/aob/mcs082
R Core Team (2020) R: a language and environment for statistical computing
Raseduzzaman M, Jensen ES (2017) Does intercropping enhance yield stability in arable crop production? A meta-analysis. Eur J Agron 91:25–33. https://doi.org/10.1016/j.eja.2017.09.009
Rodriguez C, Carlsson G, Englund J-E, Flöhr A, Pelzer E, Jeuffroy MH, Makowski D, Jensen ES (2020) Grain legume-cereal intercropping enhances the use of soil-derived and biologically fixed nitrogen in temperate agroecosystems. A meta-analysis. Eur J Agron 118:126077. https://doi.org/10.1016/j.eja.2020.126077
Sadras VO, Denison RF (2016) Neither crop genetics nor crop management can be optimised. Field Crop Res 189:75–83. https://doi.org/10.1016/j.fcr.2016.01.015
Tang X, Placella SA, Dayde F et al (2016) Phosphorus availability and microbial community in the rhizosphere of intercropped cereal and legume along a P-fertilizer gradient. Plant Soil 407:119–134. https://doi.org/10.1007/s11104-016-2949-3
Tilman D, Cassman KG, Matson PA, Naylor R, Polasky S (2002) Agricultural sustainability and intensive production practices. Nature 418:671–677. https://doi.org/10.1038/nature01014
Verret V, Pelzer E, Bedoussac L, Jeuffroy M-H (2020) Tracking on-farm innovative practices to support crop mixture design: the case of annual mixtures including a legume crop. Eur J Agron 115:126018. https://doi.org/10.1016/j.eja.2020.126018
Viguier L, Bedoussac L, Journet E-P, Justes E (2018) Yield gap analysis extended to marketable grain reveals the profitability of organic lentil-spring wheat intercrops. Agron Sustain Dev 38:39. https://doi.org/10.1007/s13593-018-0515-5
Wickham H, François R, Henry L, Müller K (2019) dplyr: a grammar of data manipulation
Willey RW, Rao MR (1980) A competitive ratio for quantifying competition between intercrops†. Exp Agric 16:117–125. https://doi.org/10.1017/S0014479700010802
Yu Y, Stomph TJ, Makowski D, van der Werf W (2015) Temporal niche differentiation increases the land equivalent ratio of annual intercrops: a meta-analysis. Field Crop Res 184:133–144. https://doi.org/10.1016/j.fcr.2015.09.010
Yu Y, Stomph TJ, Makowski D, Zhang L, van der Werf W (2016) A meta-analysis of relative crop yields in cereal/legume mixtures suggests options for management. Field Crop Res 198:269–279. https://doi.org/10.1016/j.fcr.2016.08.001
Acknowledgements
The authors thank all the technical staff who helped acquire this vast dataset and our colleagues who provided us with the data: Laurent Bedoussac, Guénaëlle Corre-Hellou, Henrik Hauggaard-Nielsen, Erik Steen Jensen, Etienne-Pascal Journet, Eric Justes, Nathalie Moutier, Christophe Naudin, Elise Pelzer, and Loïc Viguier. We also thank Michael and Michelle Corson for their helpful comments and English revision.
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This study was supported by the French National Research Agency under the Investments for the Future Program (ANR-16-CONV-0004 and ANR-20-PCPA-0006) and by the INRAE AgroEcoSystem Division.
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“Funding acquisition: PC, NH, NG; data collection and formatting: NG, RM, PC; data analysis: RM, NH; writing original draft: RM, NG, PC, NH; writing, review and editing: all co-authors.”
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Mahmoud, R., Casadebaig, P., Hilgert, N. et al. Species choice and N fertilization influence yield gains through complementarity and selection effects in cereal-legume intercrops. Agron. Sustain. Dev. 42, 12 (2022). https://doi.org/10.1007/s13593-022-00754-y
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DOI: https://doi.org/10.1007/s13593-022-00754-y