{"paper_id":"3cbbd4b8-3322-4816-9a8a-d488136956a4","body_text":"Optimising grass-legume mixtures based on growth strategies for high N-yield and low N-loss in fertilised grasslands | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimising grass-legume mixtures based on growth strategies for high N-yield and low N-loss in fertilised grasslands Arlete S. Barneze, Natalie J. Oram, Willeke Weewer, Diego Abalos, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6512158/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Aug, 2025 Read the published version in Plant and Soil → Version 1 posted 6 You are reading this latest preprint version Abstract Aims: Managed grasslands are important agro-ecosystems, consisting of grass monocultures with high nitrogen (N) fertiliser inputs. This management results in low N use efficiency and high N losses to the environment. Growing mixtures of plant species with diverse N acquisition strategies can reduce N losses and maintain high grassland productivity, yet determining the best mixture remains a challenge. The aim of this study was to investigate how grass-legume mixtures with contrasting growth strategies affect plant productivity, N use efficiency, N uptake, and soil mineral N, and how these effects depend on the N-fertilisation level. Methods: Two complementing field experiments were established: the first determined how monocultures and mixtures (two and four grass-legume mixtures) with contrasting growth strategies (fast- vs . slow-growing) affect productivity and N-cycling. The second determined the effect of fertilisation level on productivity and N-cycling in monocultures and two-species mixtures. Results: We found that productivity and N uptake of the four-species mixture was as high as the most productive monoculture and two-species mixtures. This was associated with an increase in legume N-fixation and high N use efficiency of the plant community. Fast-growing grass and legume combination increased productivity and reduced soil mineral N, thereby the risk of N loss for both N-fertilisation levels, while combining a fast-growing grass with a slow-growing legume promoted high legume N-fixation under low N-fertilisation. Conclusions: This study shows that productivity and N-cycling decreases via complementarity effects when growing mixtures of fast- and slow-growing grasses and a fast-growing legume at moderate level of N-fertilisation. grass-legume mixtures growth strategies managed grassland nitrogen cycling nitrogen use efficiency plant productivity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1 Introduction Managed grasslands are globally important ecosystems, essential for food production, biodiversity maintenance, and soil carbon storage (Bengtsson et al., 2019 ). However, intensification by growing monocultures of high-yielding grass species together with large inputs of inorganic nitrogen (N) fertiliser causes negative environmental effects due to substantial N losses via nitrate leaching and nitrous oxide emissions (Ledgard et al., 2009 ; Peeters, 2009 ). A promising way for more sustainable management and increased N use efficiency in fertilised grasslands is to increase plant species richness, functional groups richness, or functional trait diversity of grassland plant communities (Abalos et al., 2021 ). However, the relative importance of these plant community factors on grassland primary productivity, N cycling and N use efficiency is not fully understood. A better understand of how plant community composition and diversity affect N losses is important to attain the goals of modern agriculture: maintaining high productivity, producing quality fodder, and reducing reliance on N fertilisers. Increasing plant species richness promotes primary productivity in semi-natural grasslands due to complementarity effects, i.e. when the primary productivity of mixtures is on average higher than expected based on the average productivity of the monocultures (Cardinale et al., 2007 ; Schaub et al., 2020 ). The diversity-productivity relationship has also been shown in fertilised grasslands, where increasing the number of plant species from one to two, four or six, increases plant productivity (De Deyn et al., 2009 ; Lüscher et al., 2014 ; Suter et al., 2021 ). However, the increase in plant productivity may depend on plant functional group composition rather than species richness per se (De Deyn et al., 2009 ; Abalos et al., 2014 ). Legumes play an important role in grassland N cycling by increasing soil N via biological N fixation and increasing N uptake of neighbouring plants (Pirhofer-Walzl et al., 2012 ). Thus, at a given soil fertility level, grass-legume mixtures are generally more productive than grass monocultures (Nyfeler et al., 2011 ). In addition, differences in root architecture between grasses and legumes could promote plant species complementarity, increase nutrient acquisition, and thereby plant community productivity (Abalos et al., 2014 ). Thus, designing grass-legume mixtures with specific traits that can enhance complementarity effects may provide a key to enhance resource utilisation (Nyfeler et al., 2011 ; Mason et al., 2020 ) and primary productivity (Finn et al., 2013 ; Suter et al., 2015 ), and minimise N loss to the environment. Plant traits can be used to characterise plant growth strategies, i.e. the trade-off between prioritising growth or defence (Wright et al., 2004 ). Species with a fast-growing strategy typically have high specific leaf area (SLA) and leaf N content, and low leaf dry matter content (LDMC), and show a high growth rate but do not persist long over time. In contrast, species with a slow-growing strategy typically have low leaf N content and SLA, a high LDMC, and have a slow growth rate, but persist longer (Wright et al., 2004 ). Studies have shown that combining slow-growing legumes with grasses enhances plant productivity (Finn et al., 2013 ). However, the extent of enhanced productivity in legume-grass mixtures can depend on the plant growth strategies of the species in both functional groups. The traits of grasses and legumes characterise their growth strategies and therefore can be used to predict their interactions in species mixtures (Mason et al., 2016 ). The increase in productivity in specific plant-species combinations can be due to complementarity in inherently different traits between the plant species, and also due to shifts in traits via intraspecific trait plasticity. This is because the values of specific traits of an individual species are not static and can differ between individuals grown in a species mixture compared to when grown in monoculture. For example, when grown in mixtures, plant species have been shown to shift their N uptake (Nyfeler et al., 2011 ), leaf N content (Thein et al., 2008 ), SLA (Roscher et al., 2015 ), and traits associated with light acquisition and N nutrition in forbs mixtures (Lipowsky et al., 2015 ). Trait plasticity in grass species can often be seen in response to reductions in grass N limitation in grass-legume mixtures by legumes, which lowers leaf C:N ratio (Chen et al., 2005 ) and increases SLA (Al Haj Khaled et al., 2005 ) in grass species. In contrast, legumes tend to maintain their leaf C:N ratio when grown in mixtures with grasses, which is enabled by regulating their level of N-fixation (Nyfeler et al., 2011 ), and also by increasing SLA in mixtures compared to monocultures (Roscher et al., 2011 ). Shifts in plant traits due to plant species composition and plant species interactions can also influence ecosystem processes, such as soil N cycling, with potential consequences for the environment through N losses. For instance, fast-growing grasses may reduce soil mineral N levels by increasing plant N uptake, thereby reducing nitrous oxide emissions (Abalos et al., 2018 )d leaching (de Vries and Bardgett, 2016 ). Conversely, slow-growing plant species with low plant N uptake can result in higher risk of soil mineral N loss in the short term (Abalos et al., 2018 ). When combining fast- and slow-growing grasses, soil mineral N can be lower compared to grass monocultures (van Eekeren et al., 2010 ), and decrease nitrous oxide emissions compared to legume monocultures, whilst maintaining high forage quality (Abalos et al., 2021 ). The optimum plant community composition to increase productivity and N use efficiency and reduce N losses likely depends on the level of N fertilisation. Grass-legume mixtures may promote a better use of N resources compared to grass or legume monocultures, thereby reducing the need for N-fertiliser to obtain high forage yield (Suter et al., 2015 ; Fuchs et al., 2018 ), and consequently reducing N losses (Fuchs et al., 2018 ; Suter et al., 2021 ). However, legumes regulate the amount of N they fix from the air depending on the level of soil fertility (Vitousek et al., 2002 ), and this regulation is species-specific (Pirhofer-Walzl et al., 2012 ). Despite the differences in growth strategies and capacity to fix N in response to N availability, only a few studies have considered more than one legume species in mixtures with grasses (Nyfeler et al., 2009 ; Finn et al., 2013 ; Suter et al., 2015 ), and the interaction between N fertilisation and legume growth strategies or trait plasticity is not well known. In this study, we investigated how mixtures of grass and legume species with contrasting growth strategies affect plant productivity, plant N uptake, and soil mineral N availability at two levels of N fertilisation. We tested the following hypotheses: H1. Increasing the diversity in plant strategies in species mixtures will relate positively with higher complementarity, N use efficiency and productivity; H2. Plant communities with a more acquisitive resource acquisition strategy will have higher N use efficiency and maintain productivity with lower N fertilisation inputs. We tested our hypotheses in two complementing field experiments: 1) to determine the effect of plant growth strategy we grew two grass and two legume species with different growth strategies (fast- vs. slow-growing species) in mixtures of two and four-species with one level of N-fertilisation (100 kg N ha − 1 ), and 2) to determine the effect of fertiliser level in interaction with different plant growth strategies we grew two legumes (fast- vs. slow-growing species) and the fast-growing grass species in monocultures and two-species mixtures each at two levels of N-fertilisation (50 and 100 kg N ha − 1 ). 2 Materials and methods 2.1 Study site The experimental site was located at Nergena, Wageningen, the Netherlands (51° 59' 43.3\" N, 5° 39' 17.6 \"E, 9 m a.s.l.). The site is under maritime temperate climatic conditions, with mean annual temperature of 9.4°C and mean annual precipitation of 780 mm (Fig. S1 ). The soil is a typic endoaquoll (Soil Survey Staff, 2014 ) with 84% sand, 10% silt and 6% clay. Initial analyses of the properties of the upper 15 cm of the soil profile were: total N content 1.5 g kg − 1 , total organic C content 21 g kg − 1 , C:N ratio 14, plant available P 7.2 mg kg − 1 , pHCaCl 2 5.6, and bulk density 1.25 g cm − 3 . 2.2 Experimental design The field experiment was established in September 2019 and consisted of two complementing studies each following a full-factorial, randomised block design. In Experiment 1, we tested the effects of plant community composition (11 plant communities with species richness ranging from 1 to 4) on productivity and N uptake at one level of fertilisation (100 kg N ha − 1 ). In Experiment 2, we tested the potential interactive effects of plant community composition (five plant community compositions) and N fertilisation level (50 and 100 kg N ha − 1 ) (Table 1 ). Both experiments comprised five replicates per treatment, randomly allocated across five blocks. Each block consisted of 16 plots of 9 m 2 each, totalling 80 plots (Fig. S2). Seeds of two grasses ( Lolium perenne cv Barhoney and Festuca arundinacea cv Bardoux) and two legumes ( Trifolium pratense cv Lemmon and Lotus corniculatus cv Lotar) were sown in monocultures, all two-species combinations, and a four-species mixture. Seeds were sourced from Barenbrug Holland B.V. (the Netherlands). The seeding density was 1,500 viable seeds m − 2 , divided equally among the species of each mixture (i.e. 750 seeds m − 2 for each species in the two-species mixtures, and 375 seeds m − 2 for each species in the four-species mixture). The species are common in European grasslands and have contrasting growth strategies and traits (Oram et al., 2021 ). The two slow-growing species were L. corniculatus and F. arundinacea , while the fast-growing species were L. perenne and T. pratense . The two legumes differ in their capacity to fix N via biological N-fixation (Oram et al., 2021 ). After sowing, the field experiment was weeded by hand to remove the non-target plant species as needed (primarily in March-April 2020) to maintain the original plant community composition. The plots were harvested three times during the growing season by cutting the vegetation on May 11, 2020 (T0), July 6, 2020 (T1), and August 10, 2020 (T2). We applied N-fertiliser at two timepoints namely shortly after the harvests in May and July. We added calcium ammonium nitrate at a rate of 25 kg N ha − 1 in the low fertilisation treatment (totalling 50 kg N ha − 1 ) or 50 kg N ha − 1 in the high fertilisation treatment (totalling 100 kg N ha − 1 ). In May 2020 the plots were also fertilised with potassium sulphate at a rate of 31.5 kg K ha − 1 in the low fertilisation treatment and 63 kg K ha − 1 in the high fertilisation treatment. Table 1 Overview of the treatment factors of the two complementing experiments. Experiment 1: plant community composition effects, and Experiment 2: plant community composition and fertilisation level effects on plant and soil response variables. All treatments were replicated five times. Plant species: grasses Lolium perenne (Lp) and Festuca arundinacea (Fa); legumes Lotus corniculatus (Lc) and Trifolium pratense (Tp). Treatment factor Experiment 1 Experiment 2 Plant community composition 11 different communities 5 different communities monocultures 4: Lolium perenne , Festuca arundinacea , Trifolium pratense , Lotus corniculatus 3: Lolium perenne , Trifolium pratense , Lotus corniculatus two-species mixtures 6: Festuca arundinacea + Lolium perenne , Lolium perenne + Trifolium pratense , Lolium perenne + Lotus corniculatus , Festuca arundinacea + Trifolium pratense , Festuca arundinacea + Lotus corniculatus , Trifolium pratense + Lotus corniculatus 2: Lolium perenne + Trifolium pratense , Lolium perenne + Lotus corniculatus four-species mixture 1: Festuca arundinacea + Lolium perenne + Trifolium pratense + Lotus corniculatus --- Fertilisation level (kg N ha − 1 ) 100 50 and 100 2.3 Plant productivity and leaf traits To quantify plant productivity of each species in the different plant communities, aboveground biomass was harvested at T0, T1, and T2 by clipping the vegetation 2 cm above ground level, sorting per plant species, drying at 70°C, and weighing. To quantify the C and N content in the above-ground biomass and the level of N derived from N-fixation from harvest at T2, dried samples were dried, ground (ball-milled) and analysed for leaf C and N content, and for natural abundance of δ 15 N (‰) and δ 13 C (‰) using a PDZ Europa ANCA-GSL elemental analyser interfaced to a PDZ Europa 20–20 IRMS (Sercon Ltd., Cheshire, UK). Species-specific plant N uptake was calculated for the T2 sampling by multiplying the N concentration (%) by the above-ground biomass of each plant species. The N use efficiency (NUE) was estimated as the total biomass produced per unit plant N (An et al., 2005 ; Egan et al., 2019 ): NUE= \\(\\:\\frac{biomass\\:\\left(i\\right)}{biomass\\:\\left(i\\right)*total\\:N\\:\\left(i\\right)}\\) Eq. (1 ) Where biomass refers to above-ground biomass, and total N refers to leaf N concentration for each sample. The percent of N derived from biological N-fixation (Ndfa) was calculated using the δ 15 N method (Boddey et al., 2000 ) from T2 only: \\(\\:{\\%N}_{dfa}=\\:\\frac{\\left({\\delta\\:}^{15}{N}_{ref-\\:}{\\delta\\:}^{15}{N}_{legume\\:}\\right)}{\\left({\\delta\\:}^{15}{N}_{ref-\\:}B\\right)}\\:\\times\\:100\\) Eq. (2 ) Where δ 15 N ref is the mean δ 15 N value of the monoculture grasses, δ 15 N legume is the δ 15 N value of the legumes in our experiment, and B is the δ 15 N value of legumes inoculated with rhizobia and grown in N-free quartz sand, values from (Oram et al., 2021 ). The %Ndfa for mixtures containing both legume species were calculated as the average between the two legumes. Specific leaf area (SLA, cm 2 g − 1 ) was determined at T2 by sampling the youngest, fully expanded leaf from seven plants per plant species per plot, according to Pérez-Harguindeguy et al. ( 2013 ). Leaves were saturated by placing in moist paper towels in plastic containers, storing at 4°C overnight, blotting dry and weighed. Saturated leaves were then scanned (Epson Perfection V700/750), area was determined with ImageJ ( https://imagej.nih.gov/ij/ ), and dried leaves (70°C for 48 hours) were weighed. 2.4 Soil mineral N analysis We quantified soil mineral N at T0, T1, and T2 by taking four soil cores (Ø = 1.5 cm, depth = 25 cm) from each plot directly after each plant biomass harvest and before N fertilisation. Soil mineral N (NH 4 + and NO 3 − ) availability was determined by extracting 40°C oven-dried soil with 0.01 M CaCl 2 (Houba et al., 2000 ) in a 1:10 ratio (soil weight: extractant volume, dry weight basis) and analysed by colorimetry (Brann en LuebbeTrAAcs 800 Autoanalyzer, Skalar Analytical B.V. Breda). Soil gravimetric moisture content was determined after drying fresh soil at 105°C for 24 h. 2.5 Data analysis Functional trait diversity was calculated as ‘functional dispersion’ according to Laliberté and Legendre ( 2010 ) with the R function fd_fdis from the package fundiversity (Grenié and Gruson, 2022 ). We included the following traits in the functional dispersion calculation: SLA, LDMC, leaf N concentration, leaf C concentration, leaf δ 15 N and leaf δ 13 C. Community resource acquisition strategy was calculated by including the community weighted mean (CWM) of SLA, LDMC, and leaf N in a principal component analysis using the rda function from the R package vegan (Oksanen et al., 2017 ). All traits were sourced from a greenhouse experiment using the same plant species grown in monoculture (Oram et al., 2021 ). Plant resource acquisition strategy was determined using principal component analysis of the CWM of SLA, LDMC, and leaf N measured in the field, using the function rda from the R package vegan (Oksanen et al., 2017 ). CWM traits were scaled. Scores were extracted and PC1 was used as a measure of plant community resource acquisition strategy. The relative mixture effect on plant species trait changes (i.e. trait shifts due to growing in a species mixture vs. in monoculture) was based on the trait values quantified on plant samples collected in the field experiments and calculated following Jung et al. ( 2010 ) for leaf N concentration, leaf C concentration, leaf C:N ratio, SLA, leaf δ 13 C (a constant was added to negative values to make them positive) and Ndfa as shown below: \\(\\:Relative\\:mixture\\:effect\\:species\\:i=\\frac{mixture\\:trait\\:value\\:speciesi-monoculture\\:trait\\:value\\:speciesi}{monoculture\\:trait\\:value\\:speciesi}\\) Eq. (3 ) Diversity effects were calculated based on Loreau and Hector ( 2001 ). A positive net diversity effect occurs if species productivity in a mixture is on average higher than expected based on the average of the monoculture productivity of the component species. The net diversity effect results from complementarity and selection effects. A positive selection effect occurs when a species with high monoculture yields dominates a mixture. A positive complementarity effect occurs when species are generally more productive than expected in mixtures. The complementarity was calculated as the difference between the net effect and the selection, and the selection effect was assessed by determining the covariance between the species monoculture productivity and their relative trait change in above-ground biomass from monoculture to mixture. The expected mixture productivity (PE) was calculated based on Loreau and Hector ( 2001 ) as shown in Eq. (4 ): \\(\\:PE=\\sum\\:\\left({RP}_{E,i\\:}X\\:{M}_{i}\\right)\\) Eq. (4 ) Where PE is the expected productivity of a mixture, based on the productivity of the monocultures of the component species; RP E,i is the expected relative contribution of species i to productivity in the mixture (the expected contribution of each species was assumed to be proportional to the proportion of seed sown for each species in the species mixture, i.e. 1:2 in the two-species mixtures and 1:4 in the four-species mixtures); Mi is the productivity of species i in monoculture. 2.6 Statistical analyses Experiment 1 Linear mixed effects (LME) models ( nlme package, Pinheiro et al. ( 2017 ) were used to test the effect of plant species richness (monoculture, two, and four-species mixtures) or plant community composition on above-ground biomass (separately for T0, T1, T2, and the cumulative biomass of the three harvests combined), plant N uptake, overyielding, N use efficiency, Ndfa, soil NH 4 + -N and NO 3 − -N concentrations (mean of two sampling times), and diversity effects (complementarity, selection and net effect). Fixed effects were species richness or plant community composition, and the random effect was block. Two out of ten above-ground biomass samples of L. corniculatus at T2 ( L. corniculatus in the four-species mixture and in the mixture with L. perenne ) were too small to be analysed for C, N, δ 13 C and δ 15 N, thus these were not included in the analyses of plant N uptake, Ndfa and N use efficiency of these plots. LME models were also used to test the effect of plant functional group (grass or legume) and growth strategy (fast- and slow-growing species) and time-point (T0, T1, and T2) on above-ground biomass in Experiment 1. Fixed effects were functional group or plant strategy, time-point and their interaction, and random effect was block/plot. LM models were used to test the relative importance functional traits and growth strategy. Fixed effects were functional traits and growth strategy. Experiment 2 We used LME models to test the interactive effect of plant community composition (five plant communities) and fertiliser level (low or high) on overyielding, soil mineral N (NH 4 + -N + NO 3 - − N, T2), N use efficiency, and Ndfa. Fixed effects were plant community composition and fertiliser level, and random effect was block. Experiments 1 & 2 All data were checked for normality and equal variances using residual plots and log-transformed where necessary before analysis (i.e. above-ground biomass, plant N uptake, N use efficiency). We used the weight function varIdent from R package nlme (Pinheiro et al., 2017 ) to account for unequal residual variances following (Zuur et al. 2011 ). This was necessary to improve model fit for the following response variables: above-ground biomass, plant N uptake, Ndfa, soil NH 4 + -N and diversity effects (net, complementarity, and selection effects). The significance of the fixed effects was determined by comparing models with and without the factor of interest using a likelihood ratio test. We determined pairwise comparisons with Tukey post hoc using emmeans (Lenth, 2020 ). All statistical analysis was carried out in the R version 4.0.2 (R Core Team, 2020 ). 3 Results 3.1 Functional dispersion and plant species richness explaining diversity effects We found that increasing species richness from one to four species significantly increased above-ground biomass, plant N uptake, N use efficiency, Ndfa (Fig. 1 abcd, Table S2), and decreased soil NO 3 − -N (Fig. 1 f, Table S2). Furthermore, increasing species richness from two to four species significantly increased complementarity effects (Fig. S3, Table S2). Above-ground biomass and complementarity effects significantly increased with increasing functional trait dispersion (Fig. 2 ac) but were not related with plant community resource acquisition strategy (Fig. 3 ab). Functional trait dispersion of traits or strategies was not related with N use efficiency (Fig. 2 ef), nor did plant community resource acquisition strategy influence N use efficiency (Fig. 3 c). Functional dispersion was more important in explaining above-ground biomass, plant N uptake, N use efficiency, Ndfa and soil mineral N compared to growth strategy (Table 2 ). There was no difference in the explanatory power of functional traits or strategies on complementarity effects (Table 2 ). Table 2 Effect of functional groups versus growth strategy on above-ground biomass, plant N uptake, nitrogen use efficiency, Ndfa (%), complementarity effects and soil mineral N concentration from T2-end of experiment. Linear models were used to test the relative importance functional traits and growth strategy. Fixed effects were functional traits and growth strategy (significant effects are in bold, P < 0.05). Factor Above-ground biomass Plant N uptake Nitrogen use efficiency Ndfa Complementarity effects Soil mineral N Functional group F 7.27 9.22 18.6 15.4 4.1 30.8 P 0.0001 0.00001 < 0.0001 < 0.0001 0.03 < 0.0001 Growth strategy F 4.43 5.72 2.1 0.8 7.0 4.3 P 0.008 0.002 0.11 0.51 0.004 0.02 R 2 0.39 0.46 0.60 0.53 0.40 0.71 3.2 Specific plant community composition and its effect on trait plasticity The cumulative plant productivity across all harvests was highest in the mixture F. arundinacea + T. pratense (1249 g m − 2 ), exceeding that of most other plant communities (1134 g m − 2 ), although it was not significantly higher than that of the other treatments in which T. pratense was present (Fig. 4 a). Plant N uptake was higher in both legumes, and in combinations with the fast-growing legume T. pratense (Fig. 4 b). Nitrogen use efficiency was higher in four-species mixture, followed by mixtures containing the slow-growing grass F. arundinacea ( F. arundinacea + L. perenne and F. arundinacea + L. corniculatus ) (Fig. 4 c). Plant community composition did not affect soil NH 4 + -N levels (Fig. 4 d). However, levels of NO 3 − -N in the soil differed significantly and legume monocultures and combinations containing T. pratense had higher soil NO 3 − -N (Fig. 4 e). Combinations of T. pratense with either fast- or slow-growing grass species, and the four-species mixture, resulted in overyielding ( P < 0.05, Table S2c). The complementarity effect was highest in combinations with T. pratense ( P < 0.05, Table S2). Mixtures including L. corniculatus and either the fast- or slow-growing grass, or the mixture with both grasses had the lowest soil mineral N and also the lowest plant N uptake (Fig. 5 ). The mixture of T. pratense and L. corniculatus had the highest plant N uptake and the highest soil mineral N (Fig. 5 ). In contrast, combining T. pratense with either F. arundinacea or L. perenne had high plant N uptake, and relatively low soil mineral N (Fig. 5 ). Plant species differed in their trait values and for several species there was also an intraspecific shift in trait values for several plant traits between individual plants growing in mixture compared to when grown in monoculture (Fig. 6 ). The slow-growing grass F. arundinacea had a higher leaf N content, SLA, and lower leaf C:N ratio when growing with T. pratense compared to F. arundinacea grown in monoculture ( P < 0.05, Fig. 6 ). F. arundinacea also had lower leaf C:N ratio, leaf δ 13 C, and higher SLA when growing in the four-species mixture compared to F. arundinacea grown in monoculture ( P < 0.05, Fig. 6 ). The slow-growing legume L. corniculatus increased Ndfa when growing with grasses and in the four-species mixture and decreased it when growing with T. pratense . The fast-growing legume T. pratense had higher Ndfa in grass mixtures compared to monocultures ( P < 0.05, Fig. 6 ). 3.3 Interactions between plant community composition and fertiliser level Both above-ground biomass and plant N uptake were higher when 100 kg N ha − 1 was applied compared to 50 kg N ha − 1 , regardless of plant community composition ( P < 0.05, FERT, Table 3 ). Monocultures of T. pratense and L. corniculatus had the highest above-ground biomass in both fertiliser treatments ( P < 0.05, Table 3 ). The mixture of L. perenne and T. pratense was as productive as the monoculture T. pratense , and twice as productive as L. perenne in monoculture ( P < 0.05, Table 3 ). There was an interactive effect between fertilisation rate and plant community composition on overyielding of plant N uptake. The two-species mixture L. perenne and T. pratense showed N overyielding, at the high level of fertilisation (100 kg N ha − 1 ) but not at low fertilisation level ( P = 0.04, FERT * PLANT COMP, Fig. S6, Table 3 ). Soil mineral N (NH 4 + -N + NO 3 − -N) concentrations were highest in the legume monocultures, irrespective of fertilisation level ( P < 0.05, PLANT COMP, Table 3 ). Table 3 Effects of fertilisation level (FERT) and plant community composition (PLANT COMP) on cumulative above-ground biomass (sum of three harvests), plant N uptake (last harvest), overyielding, soil mineral N (last soil sampling, T2), N use efficiency, and N derived from atmosphere (Ndfa), in Experiment 2. Data are mean ± SE (n = 5). Lolium perenne (Lp), Festuca arundinacea (Fa), Lotus corniculatus (Lc), Trifolium pratense (Tp). Significance tests using likelihood ratio test (LRT) comparing models with or without parameter of interest where degree of freedom shows the difference in degrees of freedom between the models. Significant effects (P < 0.05) are shown in bold. Letters indicate per response variable significant differences between the plant communities ( P < 0.05) based on Tukey posthoc test. Interactions between fertilisation level (FERT) and plant community composition (PLANT COMP) on overyielding, nitrogen use efficiency and Ndfa are shown in Fig. S6. Cumulative above-ground biomass Plant N uptake Overyielding net effect Soil mineral N (NH 4 + -N + NO 3 − -N) N use efficiency Ndfa g m − 2 g N m − 2 g m − 2 g N m − 2 mg kg − 1 % % FERT 50 661.4 ± 48 6.3 ± 0.7 15.7 ± 29 -0.3 ± 0.9 8.7 ± 1.1 60.4 ± 5.3 53.4 ± 8.0 100 825.6 ± 58 9.4 ± 1.1 51.3 ± 44 1.2 ± 1.9 12.7 ± 2.3 51.3 ± 4.5 49.4 ± 7.4 PLANT COMP Lp 453.6 ± 23 a 2.8 ± 0.4 a - - 4.0 ± 0.4 a 57.1 ± 2.9 - Tp 1063.8 ± 47 c 11.8 ± 0.7 b - - 20.3 ± 3.6 c 32.3 ± 0.4 34.3 ± 6.2 Lc 749.9 ± 59 b 10.3 ± 1.5 b - - 15.1 ± 2.9 bc 31.6 ± 1.2 16.0 ± 3.5 LpLc 530.6 ± 49 a 3.7 ± 0.7 a -40.4 ± 19 a -2.9 ± 0.7 4.3 ± 0.7 a 88.5 ± 4.9 87.8 ± 8.3 LpTp 919.6 ± 67 bc 10.7 ± 1.3 b 107.5 ± 35 b 3.4 ± 1.2 9.9 ± 0.9 b 74.2 ± 3.5 71.2 ± 4.4 FERT LRT = 18, P < 0.0001 LRT = 15, P = 0.0001 LRT = 1, P = 0.35 LRT = 0.1, P = 0.7 LRT = 4, P = 0.03 LRT = 7, P = 0.008 LRT = 0.5, P = 0.4 PLANT COMP LRT = 74, P < 0.0001 LRT = 48, P < 0.0001 LRT = 10, P = 0.0008 LRT = 12, P = 0.0004 LRT = 61, P < 0.0001 LRT = 118, P < 0.0001 LRT = 57, P < 0.0001 FERT * PLANT COMP LRT = 3, P = 0.54 LRT = 6, P = 0.18 LRT = 1, P = 0.2 LRT = 4, P = 0.04 LRT = 4, P = 0.3 LRT = 11.5, P = 0.02* LRT = 8, P = 0.05 * The N use efficiency of the plant communities was dependent on the interaction between plant species composition and fertilisation rate ( P < 0.05, FERT * PLANT COMP, Table 3 ). Both mixtures with L. perenne (combined with either T. pratense or L. corniculatus ) and L. perenne monoculture decreased N use efficiency with an increase in N fertiliser level (100 kg N ha − 1 ), while both legumes were not affected (Fig. S6). There was a significant interactive effect between plant community composition and fertiliser rate on the level of N-fixation as quantified by Ndfa ( P = 0.05 , FERT * PLANT COMP, Table 3 ). In the grass-legume mixture, L. perenne and T. pratense , the legume maintained its level of N-fixation irrespective of the level of N fertilisation, whereas L. corniculatus (in the L. corniculatus and L. perenne mixture) showed higher levels of N-fixation at lower level of N fertilisation (Fig. S6, Table 3 ). 4 Discussion The aim of this study was to investigate how mixtures of plant species from different functional groups (grasses or legumes) with contrasting growth strategies (fast- or slow-growing species) affect plant productivity, N uptake, and soil mineral N, and how these effects depend on N fertilisation level in a managed grassland system. We found that increasing species richness from one to four species increased above-ground biomass and plant N uptake. The growth strategies of the legumes were of prime importance for these diversity effects; overyielding was only achieved when combining the fast-growing legume (higher Ndfa) with either slow- or fast-growing grass species, whereas the slow growing legume ( L. corniculatus ) biomass decreased in the mixtures at high N fertilisation (100 kg N ha − 1 ). At low level of N fertilisation, the slow-growing legume had very high N-fixation when growing in combination with the fast-growing grass compared to growing alone. This suggests that slow-growing legumes like L. corniculatus could contribute to reducing the reliance on N fertiliser in managed grasslands, provided they get a chance to establish well with sufficient time and optimal conditions to develop a strong root system. Functional traits and strategy as drivers of diversity effects (Experiment 1) We found that functional traits were more important in explaining above-ground biomass, plant N uptake, N use efficiency, Ndfa and soil mineral N compared to growth strategy (Table 2 ). Plant communities with a diverse range of functional trait values exhibit improved N response efficiency. This enhancement is primarily due to increased N uptake efficiency, attributed to the presence of functionally diverse species that optimise resource use. Plant communities with specific functional traits can regulate N cycling in intensively managed grasslands. For instance, incorporating legumes alongside grasses with particular root traits can enhance plant N uptake and reduce soil mineral N levels, leading to more efficient N cycling (Abalos et al., 2021 ). The four-species mixture had higher above-ground biomass and plant N uptake than the average of the monocultures. Over the entire experiment, mixtures had significantly higher productivity compared to the average of the four species monocultures (overyielding), and the combination between T. pratense and F. arundinacea had higher productivity compared to the most productive species’ monoculture ( T. pratense ), i.e. transgressive overyielding. These findings are consistent with other studies in fertilised grasslands that show overyielding effects (Kirwan et al., 2007 ; Nyfeler et al., 2009 ; Suter et al., 2015 ; Abalos et al., 2021 ). We suggest that the potential mechanism explaining this increase in productivity could be the increase in N use efficiency, and in complementarity use of soil N by the grasses and N obtained through N-fixation by the legumes. The positive diversity effects were due to positive complementarity effects (rather than the chance of including a highly productive species, i.e. selection effects), agreeing with previous studies in semi-natural and fertilised grassland (Barry et al., 2019 ; Mason et al., 2020 ). The increase in biological N-fixation can lead to a reduction in leaf C:N ratio of the species mixtures, indicating reduced competition for soil mineral N with a facilitative role for legumes (Temperton et al., 2007 ). In our fertilised grassland experiment, we found a decrease in the leaf C:N ratio of the grasses and thereby increased forage quality when growing in mixtures with the fast-growing legume, but this was not the case when grown with the slow-growing legume due to competition. Although there was only one four-species mixtures in our experiment at one fertilisation level (100 kg N ha − 1 ), and caution is needed when drawing general conclusions, our results align with other studies showing increases in N use efficiency and biological N-fixation with increasing plant species richness (Cummins et al., 2021 ; Grange et al., 2021 ). Effects of plant community composition on productivity and soil mineral N (Experiment 1) Legume growth strategy was a key driver of above-ground biomass and soil mineral N in our experiment. Combinations with T. pratense , the fast-growing legume, were associated with overyielding and could be explained by plant trait plasticity (Mason et al., 2020 ). Biological N-fixation by T. pratense increased when it was growing with grasses. This grass-legume combination resulted in reduced soil mineral N due to high soil N uptake by the grasses, which stimulated the fast-growing legume to fix more N from the atmosphere (i.e. increase Ndfa, Fig. 3 ). The overyielding observed in the specific combinations between T. pratense and F. arundinacea , and in the four-species mixture, could be influenced by intraspecific trait shifts. In these plant species combinations, F. arundinacea plants had lower leaf C:N ratio and higher SLA compared to its monoculture plants (Fig. 6 ), that could suggest lower N limitation and larger light interception for F. arundinacea in this plant community. This was also observed in other studies in N rich conditions: a decrease in leaf C:N in two dominant grass species(Chen et al., 2005 ) and an increase in SLA (Al Haj Khaled et al., 2005 ). Trait plasticity has been linked to overyielding in other studies (Thein et al., 2008 ; Roscher et al., 2018 ; Yang et al., 2022 ), although(Mason et al., 2020 ) found only a weak relationship between intraspecific trait plasticity and overyielding relative to resource use efficiency (water, N, and light). In our experiment, although L. corniculatus , the slow-growing legume, had high productivity in monocultures, it was supressed when grown in mixtures. This contrasts with the high productivity observed for this species in species mixtures in other experiments (De Deyn et al., 2009 ). Frequently, the mixtures performance can be closely related to the performance of individual species i.e. their establishment rate, and their different shoot and root traits (Egan et al., 2019 ). However, the slow establishment rate of L. corniculatus in our experiment may have allowed other species in the mixture (i.e. fast-growing species, T. pratense and L. perenne ) to out-compete it for light and nutrients. In addition, seeds were sown in our field experiment to represent agricultural practice, whereas in (De Deyn et al., 2009 ) the plant communities were not established by seeding but by planting seedlings, with an equal number of individuals per plant species per area, and plants were not fertilised during the experiment. These reasons could have contributed to the poor (but possibly more realistic) competitivity of L. corniculatus in species mixtures in our fertilised grassland experiment. Overall, taking into consideration plant N uptake and N loss to the environment, we found that legume monocultures and their combination ( T. pratense + L. corniculatus ) had the highest plant productivity, but they also had the highest soil mineral N levels (Fig. 5 ). This is not a surprise as many studies have shown that legume species can increase mineral N due to the release of fixed N from their roots via decomposition, and their inefficiency in acquiring soil mineral N alone (Niklaus et al., 2006 ; Barneze et al., 2020 ). Yet, we found that mixing the legumes with either grass species was an effective way to reduce soil mineral N strongly compared to legume monocultures, regardless of the grass growing strategy. This is an important finding, because decreasing soil mineral N availability is paramount for sustainable production systems, as this N pool is highly susceptible to be lost from the agroecosystem in the form of nitrate leaching or as nitrous oxide. Previous studies have shown reductions of soil mineral N with increasing plant biomass production (Abalos et al., 2014 , 2018 ). Although it is difficult to generalise and to transfer the results from our study to other fast- vs slow-growing grasses and N fixers because we only had two grasses and two legumes, the selected species are very common in managed grasslands and therefore these findings are relevant for on-farm applications in temperate grasslands. Fertiliser level determines the performance of legumes in grass-legume mixtures (Experiment 2) At low fertilisation level (50 kg N ha − 1 ) we did not observe an increase in plant productivity (or plant N uptake) in the plant community with a more acquisitive resource acquisition strategy ( L. perenne + T. pratense ), contradicting our second hypothesis. However, at the higher fertilisation level, the L. perenne + T. pratense combination (together with the legumes) showed the highest plant community productivity (above-ground biomass) and N uptake, yet with high soil mineral N level at potential risk of getting lost. There was an interaction effect between N use efficiency and N fertilisation level, at low fertilisation level, N use efficiency was higher in the mixtures ( L. perenne + T. pratense and L. perenne + L. corniculatus ) compared to the monocultures, partly agreeing with our second hypothesis. Overall, these results confirm the challenges of simultaneously achieving high plant biomass production quantity and quality and low soil mineral N levels, to reduce risks of N losses, in grasslands. Recommendations for optimum grass-legume mixtures will therefore depend on the specific priority for a given site: either a farmer-driven focus on production, or a policy-driven minimisation of N losses. Nevertheless grass-legume mixtures are preferable over grass monocultures as the N-fixation by the legumes especially in grass-legume combinations can (partly) replace the use of mineral N fertiliser and therefore the greenhouse gas emissions associated with fertiliser production. We observed higher overyielding in the mixture with the slow-growing legume ( L. perenne + L. corniculatus ) at low fertilisation level relative to high fertilisation level (Fig. S6). Although the grass-legume mixture with T. pratense had 1.6 times higher productivity compared to the mixture with L. corniculatus , the slow-growing legume was able to increase its N supply from atmospheric N by 11% in the treatment with 50 kg N ha − 1 compared to 100 kg N ha − 1 (Ndfa = 98%; Table 3 , Fig. S6). This increase in biological nitrogen fixation by L. corniculatus grown with L. perenne could allow for reductions in N fertilisation without reductions in plant community N uptake or plant productivity. A key knowledge gap is understanding the conditions (e.g. seeding rates, fertiliser application timing) allowing for a better establishment and development of species with lower competitive ability in the short-term but with high potential to contribute to plant productivity and N provisioning on the longer-term. Declarations Competing Interests The authors have no relevant financial or non-financial interests to disclose. Funding This work was supported by Dutch Research Council - NWO ALW grant awarded to Gerlinde B. De Deyn (grant number ALWOP.448). The authors declare no conflict of interest. Author Contributions A.S.B., W.W., N.J.O, D.A and G.B.D.D. designed the experiment; A.S.B. and W.W. conducted the experiment with input from N.J.O, D.A. and G.B.D.D., A.S.B. and N.J.O. analysed the data and wrote the manuscript with extensive input from W.W., D.A. and G.B.D.D. Acknowledgements This study was supported by an NWO ALW grant awarded to GBDD (grant number ALWOP.448). 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Funct Ecol 36:2163–2175. https://doi.org/10.1111/1365-2435.14115 Zuur AF, Ieno EN, Walker NJ, Saveliev AA, Smith GM (2011) Mixed Effects Models and Extensions in Ecology with R. Springer Supplementary Files BarnezeandOrametalsupplementaryinformationv5.docx Cite Share Download PDF Status: Published Journal Publication published 01 Aug, 2025 Read the published version in Plant and Soil → Version 1 posted Editorial decision: Major revisions 08 Jun, 2025 Reviewers agreed at journal 14 May, 2025 Reviewers invited by journal 09 May, 2025 Editor invited by journal 24 Apr, 2025 Editor assigned by journal 23 Apr, 2025 First submitted to journal 23 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-6512158\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":454288010,\"identity\":\"922d2931-181e-4fa0-827d-0e5c6ef36a22\",\"order_by\":0,\"name\":\"Arlete S. Barneze\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYFAC5gYQmcAPJguI0sLYwHAAqFgSpDPBgBQtBgdAHGK08M8+2Pj4Q0VdnvH51YkfHhgwyPOLHcCvReJcYrPBgTOHi81uvN0sAXSY4czZCQSsOcPYJnGw7UDithtnN4C0JBjcJqBF/gxj+4+D/+oSN884u/kHUVoMgLYwHGxgTtzA37uNOFsMzzA2S5w5drhY4gbvNosEAwnCfpE7w3zwQ0VNXR5//9nNN39U2MjzSxPQggASYJUSxCoHAf4DpKgeBaNgFIyCkQQAw5dLUexeqnwAAAAASUVORK5CYII=\",\"orcid\":\"https://orcid.org/0000-0001-5781-0424\",\"institution\":\"Wageningen University \\u0026 Research\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Arlete\",\"middleName\":\"S.\",\"lastName\":\"Barneze\",\"suffix\":\"\"},{\"id\":454288011,\"identity\":\"e128590d-585c-4e2b-bdfc-041b5840e53b\",\"order_by\":1,\"name\":\"Natalie J. Oram\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Natalie\",\"middleName\":\"J.\",\"lastName\":\"Oram\",\"suffix\":\"\"},{\"id\":454288012,\"identity\":\"24ae933a-a3ca-4f2b-b66f-683b6dcae93d\",\"order_by\":2,\"name\":\"Willeke Weewer\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Willeke\",\"middleName\":\"\",\"lastName\":\"Weewer\",\"suffix\":\"\"},{\"id\":454288013,\"identity\":\"a092a1c5-02c5-436a-8d2f-6b282f946dff\",\"order_by\":3,\"name\":\"Diego Abalos\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Diego\",\"middleName\":\"\",\"lastName\":\"Abalos\",\"suffix\":\"\"},{\"id\":454288014,\"identity\":\"9d784e06-b156-4a52-a9d4-83e01608ae63\",\"order_by\":4,\"name\":\"Gerlinde B. De Deyn\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Gerlinde\",\"middleName\":\"B.\",\"lastName\":\"De Deyn\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-04-23 11:32:56\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-6512158/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-6512158/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1007/s11104-025-07736-5\",\"type\":\"published\",\"date\":\"2025-08-01T16:38:11+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":82681712,\"identity\":\"bda30435-9118-4f6b-8716-c20def665539\",\"added_by\":\"auto\",\"created_at\":\"2025-05-14 06:03:07\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":467861,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003ePlant monoculture and species mixture (two and four-species) effects on a) above-ground biomass (cumulative for the three harvests), b) plant N uptake (final harvest), c) N use efficiency (final harvest), d) N-fixation, expressed as N derived from the atmosphere (Ndfa, %), e) soil NH\\u003csub\\u003e4\\u003c/sub\\u003e\\u003csup\\u003e+\\u003c/sup\\u003e-N and f) soil NO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003csup\\u003e-—\\u003c/sup\\u003eN (mean of two soil samplings). Bars are mean ± SE (n= 20 for monoculture, n= 30 for two-species and n= 5 for four-species mixtures, *plant N uptake, NUE, Ndfa n= 4) from Experiment 1. Dots indicate values of individual plots. Different letters above the bars indicate significant differences between species richness levels (\\u003cem\\u003eP\\u003c/em\\u003e \\u0026lt; 0.05) based on a Tukey posthoc test (ns: non-significant). Statistical analyses can be found in Fig. S1\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6512158/v1/94afc9a08de94bc2e817cdf4.png\"},{\"id\":82681713,\"identity\":\"115b88ee-d1c3-4bcf-a55b-712e5c5ca06a\",\"added_by\":\"auto\",\"created_at\":\"2025-05-14 06:03:07\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":190339,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eRelationship between above-ground biomass, complementarity effects (Loreau \\u0026amp; Hector, 2001), nitrogen use efficiency (NUE) on functional dispersion (Laliberté \\u0026amp; Legendre, 2010). Effects were tested with linear mixed effects models with block/plot as a random structure to account for variation across the field site (block) and pseudo replication (plot). Interactions with fertilisation (low/high) and timepoint (T0, T1, T2) were tested and were never significant. Thus, the remaining model contained only one explanatory variable. F- and P-values, and model R\\u003csup\\u003e2\\u003c/sup\\u003e (explanatory power of the model) are shown on each panel. Traits considered in functional dispersion were: specific leaf area (SLA), leaf dry matter content (LDMC), leaf C and N concentrations (% C and N in above-ground biomass), leaf natural abundance d\\u003csup\\u003e13\\u003c/sup\\u003eC and d\\u003csup\\u003e15\\u003c/sup\\u003eN. Functional dispersion of plant community strategy was calculated by determining the mean ‘strategy’ of each species (mean value of PC1, Figure S4). Traits were taken from a greenhouse experiment (Oram et al., 2021) and weighed by the relative abundance of above-ground biomass of each plant species in the field experiment.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6512158/v1/391903f03faf65a87b10b1d9.png\"},{\"id\":82681710,\"identity\":\"192c20ad-86e0-4184-ae8e-27dae0d93171\",\"added_by\":\"auto\",\"created_at\":\"2025-05-14 06:03:07\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":73492,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eRelationships between resource acquisition strategy (PC1) and (A) above-ground biomass, (B) complementarity effects, and (C) nitrogen use efficiency (NUE) at T2. A high PC1 value indicates a more acquisitive plant community (see Fig. S5). Ns: non-significant. F- and \\u003cem\\u003eP\\u003c/em\\u003e-values, and model R\\u003csup\\u003e2\\u003c/sup\\u003e (explanatory power of the model) are shown on the panel.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6512158/v1/8d5be6da2a45991221aa412d.png\"},{\"id\":82681716,\"identity\":\"21fc9fc7-37c1-4cd5-9b61-8eb8a3f4cc39\",\"added_by\":\"auto\",\"created_at\":\"2025-05-14 06:03:07\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1038017,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003ePlant species composition effect on a) above-ground biomass (sum of the three harvests), b) plant N uptake, c) N use efficiency, d) complementarity effect, e) soil NH\\u003csub\\u003e4\\u003c/sub\\u003e\\u003csup\\u003e+\\u003c/sup\\u003e-N and f) soil NO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003csup\\u003e-\\u003c/sup\\u003e-N. Dots indicate values of individual plots. Significance tests using a linear mixed effect model. \\u003cem\\u003eLolium perenne\\u003c/em\\u003e (Lp); \\u003cem\\u003eFestuca arundinacea\\u003c/em\\u003e (Fa); \\u003cem\\u003eLotus corniculatus\\u003c/em\\u003e (Lc); \\u003cem\\u003eTrifolium pratense\\u003c/em\\u003e (Tp). Different letters indicate significant differences between the plant communities within each panel (\\u003cem\\u003eP\\u003c/em\\u003e \\u0026lt; 0.05) based on a Tukey posthoc test. Statistical analyses can be found in Fig. S1.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6512158/v1/9ade972fe6a77554e04a2fd5.png\"},{\"id\":82681715,\"identity\":\"67ddd13c-adba-44c7-8c23-f64c47262e7e\",\"added_by\":\"auto\",\"created_at\":\"2025-05-14 06:03:07\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":35061,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eRelationship between plant N uptake (g N m\\u003csup\\u003e-2\\u003c/sup\\u003e) and soil mineral N (mg kg\\u003csup\\u003e-1\\u003c/sup\\u003e) for each plant community composition at the final harvest-T2 of Experiment 1. \\u003cem\\u003eLolium perenne\\u003c/em\\u003e (Lp), \\u003cem\\u003eFestuca arundinacea\\u003c/em\\u003e (Fa), \\u003cem\\u003eLotus corniculatus\\u003c/em\\u003e (Lc), \\u003cem\\u003eTrifolium pratense\\u003c/em\\u003e (Tp).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6512158/v1/25ac947955c2e85b3696ba56.png\"},{\"id\":82682576,\"identity\":\"3157c68c-753e-449e-afce-fe53e0e840d4\",\"added_by\":\"auto\",\"created_at\":\"2025-05-14 06:11:07\",\"extension\":\"png\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":131114,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe effect of growing in a species mixture on plant traits relative to the plant traits of the monoculture for A) \\u003cem\\u003eFestuca arundinacea\\u003c/em\\u003e (Fa), B) \\u003cem\\u003eLolium perenne\\u003c/em\\u003e (Lp), C) \\u003cem\\u003eTrifolium pratense\\u003c/em\\u003e (Tp), D) \\u003cem\\u003eLotus corniculatus\\u003c/em\\u003e (Lc) and E) \\u003cem\\u003eLotus corniculatus\\u003c/em\\u003e (Lc) for Ndfa only, from Experiment 1. Asterisks indicate a significant difference in the trait of that plant species between its monoculture and when grown in the plant species mixture. The reference trait value of the monoculture is indicated by the dashed line at x = 0. Values above 0 indicate that the trait value of the plant species is higher in the mixture than in the monoculture, and below 0 indicate that the trait value is lower.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage6.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6512158/v1/dc1cdc5591efa183e7c61e2e.png\"},{\"id\":88270390,\"identity\":\"64aa7c84-3006-4a6d-8355-a97380819c90\",\"added_by\":\"auto\",\"created_at\":\"2025-08-04 17:00:22\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":3914252,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6512158/v1/22c94f9e-7d2f-4378-8084-ffbdbfb1f381.pdf\"},{\"id\":82682579,\"identity\":\"695c73c5-8be6-4a57-874e-10bd236c7048\",\"added_by\":\"auto\",\"created_at\":\"2025-05-14 06:11:08\",\"extension\":\"docx\",\"order_by\":5,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":262241,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"BarnezeandOrametalsupplementaryinformationv5.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6512158/v1/e835fa17a8f8375a1ed008e0.docx\"}],\"financialInterests\":\"\",\"formattedTitle\":\"Optimising grass-legume mixtures based on growth strategies for high N-yield and low N-loss in fertilised grasslands\",\"fulltext\":[{\"header\":\"1 Introduction\",\"content\":\"\\u003cp\\u003eManaged grasslands are globally important ecosystems, essential for food production, biodiversity maintenance, and soil carbon storage (Bengtsson et al., \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). However, intensification by growing monocultures of high-yielding grass species together with large inputs of inorganic nitrogen (N) fertiliser causes negative environmental effects due to substantial N losses via nitrate leaching and nitrous oxide emissions (Ledgard et al., \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e; Peeters, \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e). A promising way for more sustainable management and increased N use efficiency in fertilised grasslands is to increase plant species richness, functional groups richness, or functional trait diversity of grassland plant communities (Abalos et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). However, the relative importance of these plant community factors on grassland primary productivity, N cycling and N use efficiency is not fully understood. A better understand of how plant community composition and diversity affect N losses is important to attain the goals of modern agriculture: maintaining high productivity, producing quality fodder, and reducing reliance on N fertilisers.\\u003c/p\\u003e \\u003cp\\u003eIncreasing plant species richness promotes primary productivity in semi-natural grasslands due to complementarity effects, i.e. when the primary productivity of mixtures is on average higher than expected based on the average productivity of the monocultures (Cardinale et al., \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e; Schaub et al., \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). The diversity-productivity relationship has also been shown in fertilised grasslands, where increasing the number of plant species from one to two, four or six, increases plant productivity (De Deyn et al., \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e; L\\u0026uuml;scher et al., \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e; Suter et al., \\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). However, the increase in plant productivity may depend on plant functional group composition rather than species richness \\u003cem\\u003eper se\\u003c/em\\u003e (De Deyn et al., \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e; Abalos et al., \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e). Legumes play an important role in grassland N cycling by increasing soil N via biological N fixation and increasing N uptake of neighbouring plants (Pirhofer-Walzl et al., \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e). Thus, at a given soil fertility level, grass-legume mixtures are generally more productive than grass monocultures (Nyfeler et al., \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e). In addition, differences in root architecture between grasses and legumes could promote plant species complementarity, increase nutrient acquisition, and thereby plant community productivity (Abalos et al., \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e). Thus, designing grass-legume mixtures with specific traits that can enhance complementarity effects may provide a key to enhance resource utilisation (Nyfeler et al., \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e; Mason et al., \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e) and primary productivity (Finn et al., \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e; Suter et al., \\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e), and minimise N loss to the environment.\\u003c/p\\u003e \\u003cp\\u003ePlant traits can be used to characterise plant growth strategies, i.e. the trade-off between prioritising growth or defence (Wright et al., \\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e). Species with a fast-growing strategy typically have high specific leaf area (SLA) and leaf N content, and low leaf dry matter content (LDMC), and show a high growth rate but do not persist long over time. In contrast, species with a slow-growing strategy typically have low leaf N content and SLA, a high LDMC, and have a slow growth rate, but persist longer (Wright et al., \\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e). Studies have shown that combining slow-growing legumes with grasses enhances plant productivity (Finn et al., \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e). However, the extent of enhanced productivity in legume-grass mixtures can depend on the plant growth strategies of the species in both functional groups. The traits of grasses and legumes characterise their growth strategies and therefore can be used to predict their interactions in species mixtures (Mason et al., \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eThe increase in productivity in specific plant-species combinations can be due to complementarity in inherently different traits between the plant species, and also due to shifts in traits via intraspecific trait plasticity. This is because the values of specific traits of an individual species are not static and can differ between individuals grown in a species mixture compared to when grown in monoculture. For example, when grown in mixtures, plant species have been shown to shift their N uptake (Nyfeler et al., \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e), leaf N content (Thein et al., \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e2008\\u003c/span\\u003e), SLA (Roscher et al., \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e), and traits associated with light acquisition and N nutrition in forbs mixtures (Lipowsky et al., \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e). Trait plasticity in grass species can often be seen in response to reductions in grass N limitation in grass-legume mixtures by legumes, which lowers leaf C:N ratio (Chen et al., \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e2005\\u003c/span\\u003e) and increases SLA (Al Haj Khaled et al., \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2005\\u003c/span\\u003e) in grass species. In contrast, legumes tend to maintain their leaf C:N ratio when grown in mixtures with grasses, which is enabled by regulating their level of N-fixation (Nyfeler et al., \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e), and also by increasing SLA in mixtures compared to monocultures (Roscher et al., \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eShifts in plant traits due to plant species composition and plant species interactions can also influence ecosystem processes, such as soil N cycling, with potential consequences for the environment through N losses. For instance, fast-growing grasses may reduce soil mineral N levels by increasing plant N uptake, thereby reducing nitrous oxide emissions (Abalos et al., \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e)d leaching (de Vries and Bardgett, \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e). Conversely, slow-growing plant species with low plant N uptake can result in higher risk of soil mineral N loss in the short term (Abalos et al., \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). When combining fast- and slow-growing grasses, soil mineral N can be lower compared to grass monocultures (van Eekeren et al., \\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e2010\\u003c/span\\u003e), and decrease nitrous oxide emissions compared to legume monocultures, whilst maintaining high forage quality (Abalos et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eThe optimum plant community composition to increase productivity and N use efficiency and reduce N losses likely depends on the level of N fertilisation. Grass-legume mixtures may promote a better use of N resources compared to grass or legume monocultures, thereby reducing the need for N-fertiliser to obtain high forage yield (Suter et al., \\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e; Fuchs et al., \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e), and consequently reducing N losses (Fuchs et al., \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e; Suter et al., \\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). However, legumes regulate the amount of N they fix from the air depending on the level of soil fertility (Vitousek et al., \\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e2002\\u003c/span\\u003e), and this regulation is species-specific (Pirhofer-Walzl et al., \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e). Despite the differences in growth strategies and capacity to fix N in response to N availability, only a few studies have considered more than one legume species in mixtures with grasses (Nyfeler et al., \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e; Finn et al., \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e; Suter et al., \\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e), and the interaction between N fertilisation and legume growth strategies or trait plasticity is not well known.\\u003c/p\\u003e \\u003cp\\u003eIn this study, we investigated how mixtures of grass and legume species with contrasting growth strategies affect plant productivity, plant N uptake, and soil mineral N availability at two levels of N fertilisation. We tested the following hypotheses: H1. Increasing the diversity in plant strategies in species mixtures will relate positively with higher complementarity, N use efficiency and productivity; H2. Plant communities with a more acquisitive resource acquisition strategy will have higher N use efficiency and maintain productivity with lower N fertilisation inputs. We tested our hypotheses in two complementing field experiments: 1) to determine the effect of plant growth strategy we grew two grass and two legume species with different growth strategies (fast- \\u003cem\\u003evs.\\u003c/em\\u003e slow-growing species) in mixtures of two and four-species with one level of N-fertilisation (100 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e), and 2) to determine the effect of fertiliser level in interaction with different plant growth strategies we grew two legumes (fast- \\u003cem\\u003evs.\\u003c/em\\u003e slow-growing species) and the fast-growing grass species in monocultures and two-species mixtures each at two levels of N-fertilisation (50 and 100 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e).\\u003c/p\\u003e\"},{\"header\":\"2 Materials and methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1 Study site\\u003c/h2\\u003e \\u003cp\\u003eThe experimental site was located at Nergena, Wageningen, the Netherlands (51\\u0026deg; 59' 43.3\\\" N, 5\\u0026deg; 39' 17.6 \\\"E, 9 m a.s.l.). The site is under maritime temperate climatic conditions, with mean annual temperature of 9.4\\u0026deg;C and mean annual precipitation of 780 mm (Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e). The soil is a typic endoaquoll (Soil Survey Staff, \\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e) with 84% sand, 10% silt and 6% clay. Initial analyses of the properties of the upper 15 cm of the soil profile were: total N content 1.5 g kg\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e, total organic C content 21 g kg\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e, C:N ratio 14, plant available P 7.2 mg kg \\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e, pHCaCl\\u003csub\\u003e2\\u003c/sub\\u003e 5.6, and bulk density 1.25 g cm\\u003csup\\u003e\\u0026minus;\\u0026thinsp;3\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.2 Experimental design\\u003c/h2\\u003e \\u003cp\\u003eThe field experiment was established in September 2019 and consisted of two complementing studies each following a full-factorial, randomised block design. In Experiment 1, we tested the effects of plant community composition (11 plant communities with species richness ranging from 1 to 4) on productivity and N uptake at one level of fertilisation (100 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e). In Experiment 2, we tested the potential interactive effects of plant community composition (five plant community compositions) and N fertilisation level (50 and 100 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e) (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Both experiments comprised five replicates per treatment, randomly allocated across five blocks. Each block consisted of 16 plots of 9 m\\u003csup\\u003e2\\u003c/sup\\u003e each, totalling 80 plots (Fig. S2). Seeds of two grasses (\\u003cem\\u003eLolium perenne\\u003c/em\\u003e cv Barhoney and \\u003cem\\u003eFestuca arundinacea\\u003c/em\\u003e cv Bardoux) and two legumes (\\u003cem\\u003eTrifolium pratense\\u003c/em\\u003e cv Lemmon and \\u003cem\\u003eLotus corniculatus\\u003c/em\\u003e cv Lotar) were sown in monocultures, all two-species combinations, and a four-species mixture. Seeds were sourced from Barenbrug Holland B.V. (the Netherlands). The seeding density was 1,500 viable seeds m\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e, divided equally among the species of each mixture (i.e. 750 seeds m\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e for each species in the two-species mixtures, and 375 seeds m\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e for each species in the four-species mixture). The species are common in European grasslands and have contrasting growth strategies and traits (Oram et al., \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). The two slow-growing species were \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e and \\u003cem\\u003eF. arundinacea\\u003c/em\\u003e, while the fast-growing species were \\u003cem\\u003eL. perenne\\u003c/em\\u003e and \\u003cem\\u003eT. pratense\\u003c/em\\u003e. The two legumes differ in their capacity to fix N via biological N-fixation (Oram et al., \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). After sowing, the field experiment was weeded by hand to remove the non-target plant species as needed (primarily in March-April 2020) to maintain the original plant community composition. The plots were harvested three times during the growing season by cutting the vegetation on May 11, 2020 (T0), July 6, 2020 (T1), and August 10, 2020 (T2). We applied N-fertiliser at two timepoints namely shortly after the harvests in May and July. We added calcium ammonium nitrate at a rate of 25 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e in the low fertilisation treatment (totalling 50 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e) or 50 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e in the high fertilisation treatment (totalling 100 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e). In May 2020 the plots were also fertilised with potassium sulphate at a rate of 31.5 kg K ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e in the low fertilisation treatment and 63 kg K ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e in the high fertilisation treatment.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eOverview of the treatment factors of the two complementing experiments. Experiment 1: plant community composition effects, and Experiment 2: plant community composition and fertilisation level effects on plant and soil response variables. All treatments were replicated five times. Plant species: grasses \\u003cem\\u003eLolium perenne\\u003c/em\\u003e (Lp) and \\u003cem\\u003eFestuca arundinacea\\u003c/em\\u003e (Fa); legumes \\u003cem\\u003eLotus corniculatus\\u003c/em\\u003e (Lc) and \\u003cem\\u003eTrifolium pratense\\u003c/em\\u003e (Tp).\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTreatment factor\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eExperiment 1\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eExperiment 2\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePlant community composition\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e11 different communities\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5 different communities\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003emonocultures\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4: \\u003cem\\u003eLolium perenne\\u003c/em\\u003e, \\u003cem\\u003eFestuca arundinacea\\u003c/em\\u003e, \\u003cem\\u003eTrifolium pratense\\u003c/em\\u003e, \\u003cem\\u003eLotus corniculatus\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3: \\u003cem\\u003eLolium perenne\\u003c/em\\u003e, \\u003cem\\u003eTrifolium pratense\\u003c/em\\u003e, \\u003cem\\u003eLotus corniculatus\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003etwo-species mixtures\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6: \\u003cem\\u003eFestuca arundinacea\\u0026thinsp;+\\u0026thinsp;Lolium perenne\\u003c/em\\u003e,\\u003c/p\\u003e \\u003cp\\u003e\\u003cem\\u003eLolium perenne\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eTrifolium pratense\\u003c/em\\u003e,\\u003c/p\\u003e \\u003cp\\u003e\\u003cem\\u003eLolium perenne\\u0026thinsp;+\\u0026thinsp;Lotus corniculatus\\u003c/em\\u003e,\\u003c/p\\u003e \\u003cp\\u003e\\u003cem\\u003eFestuca arundinacea\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eTrifolium pratense\\u003c/em\\u003e, \\u003cem\\u003eFestuca arundinacea\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eLotus corniculatus\\u003c/em\\u003e, \\u003cem\\u003eTrifolium pratense\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eLotus corniculatus\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2: \\u003cem\\u003eLolium perenne\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eTrifolium pratense\\u003c/em\\u003e, \\u003cem\\u003eLolium perenne\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eLotus corniculatus\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003efour-species mixture\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1: \\u003cem\\u003eFestuca arundinacea\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eLolium perenne\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eTrifolium pratense\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eLotus corniculatus\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e---\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFertilisation level (kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e100\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e50 and 100\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3 Plant productivity and leaf traits\\u003c/h2\\u003e \\u003cp\\u003eTo quantify plant productivity of each species in the different plant communities, aboveground biomass was harvested at T0, T1, and T2 by clipping the vegetation 2 cm above ground level, sorting per plant species, drying at 70\\u0026deg;C, and weighing. To quantify the C and N content in the above-ground biomass and the level of N derived from N-fixation from harvest at T2, dried samples were dried, ground (ball-milled) and analysed for leaf C and N content, and for natural abundance of δ\\u003csup\\u003e15\\u003c/sup\\u003eN (\\u0026permil;) and δ\\u003csup\\u003e13\\u003c/sup\\u003eC (\\u0026permil;) using a PDZ Europa ANCA-GSL elemental analyser interfaced to a PDZ Europa 20\\u0026ndash;20 IRMS (Sercon Ltd., Cheshire, UK). Species-specific plant N uptake was calculated for the T2 sampling by multiplying the N concentration (%) by the above-ground biomass of each plant species. The N use efficiency (NUE) was estimated as the total biomass produced per unit plant N (An et al., \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2005\\u003c/span\\u003e; Egan et al., \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e): NUE= \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:\\\\frac{biomass\\\\:\\\\left(i\\\\right)}{biomass\\\\:\\\\left(i\\\\right)*total\\\\:N\\\\:\\\\left(i\\\\right)}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e \\u003cem\\u003eEq.\\u0026nbsp;(1\\u003c/em\\u003e)\\u003c/p\\u003e \\u003cp\\u003eWhere biomass refers to above-ground biomass, and total N refers to leaf N concentration for each sample.\\u003c/p\\u003e \\u003cp\\u003eThe percent of N derived from biological N-fixation (Ndfa) was calculated using the δ\\u003csup\\u003e15\\u003c/sup\\u003eN method (Boddey et al., \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2000\\u003c/span\\u003e) from T2 only:\\u003c/p\\u003e \\u003cp\\u003e \\u003cspan class=\\\"InlineEquation\\\"\\u003e \\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{\\\\%N}_{dfa}=\\\\:\\\\frac{\\\\left({\\\\delta\\\\:}^{15}{N}_{ref-\\\\:}{\\\\delta\\\\:}^{15}{N}_{legume\\\\:}\\\\right)}{\\\\left({\\\\delta\\\\:}^{15}{N}_{ref-\\\\:}B\\\\right)}\\\\:\\\\times\\\\:100\\\\)\\u003c/span\\u003e \\u003c/span\\u003e \\u003cem\\u003eEq.\\u0026nbsp;(2\\u003c/em\\u003e)\\u003c/p\\u003e \\u003cp\\u003eWhere δ\\u003csup\\u003e15\\u003c/sup\\u003eN\\u003csub\\u003eref\\u003c/sub\\u003e is the mean δ\\u003csup\\u003e15\\u003c/sup\\u003eN value of the monoculture grasses, δ\\u003csup\\u003e15\\u003c/sup\\u003eN\\u003csub\\u003elegume\\u003c/sub\\u003e is the δ\\u003csup\\u003e15\\u003c/sup\\u003eN value of the legumes in our experiment, and B is the δ\\u003csup\\u003e15\\u003c/sup\\u003eN value of legumes inoculated with rhizobia and grown in N-free quartz sand, values from (Oram et al., \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). The %Ndfa for mixtures containing both legume species were calculated as the average between the two legumes.\\u003c/p\\u003e \\u003cp\\u003eSpecific leaf area (SLA, cm\\u003csup\\u003e2\\u003c/sup\\u003e g\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e) was determined at T2 by sampling the youngest, fully expanded leaf from seven plants per plant species per plot, according to P\\u0026eacute;rez-Harguindeguy et al. (\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e). Leaves were saturated by placing in moist paper towels in plastic containers, storing at 4\\u0026deg;C overnight, blotting dry and weighed. Saturated leaves were then scanned (Epson Perfection V700/750), area was determined with ImageJ (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://imagej.nih.gov/ij/\\u003c/span\\u003e\\u003cspan address=\\\"https://imagej.nih.gov/ij/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e), and dried leaves (70\\u0026deg;C for 48 hours) were weighed.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.4 Soil mineral N analysis\\u003c/h2\\u003e \\u003cp\\u003eWe quantified soil mineral N at T0, T1, and T2 by taking four soil cores (\\u0026Oslash; = 1.5 cm, depth\\u0026thinsp;=\\u0026thinsp;25 cm) from each plot directly after each plant biomass harvest and before N fertilisation. Soil mineral N (NH\\u003csub\\u003e4\\u003c/sub\\u003e\\u003csup\\u003e+\\u003c/sup\\u003e and NO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003csup\\u003e\\u0026minus;\\u003c/sup\\u003e) availability was determined by extracting 40\\u0026deg;C oven-dried soil with 0.01 M CaCl\\u003csub\\u003e2\\u003c/sub\\u003e (Houba et al., \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e2000\\u003c/span\\u003e) in a 1:10 ratio (soil weight: extractant volume, dry weight basis) and analysed by colorimetry (Brann en LuebbeTrAAcs 800 Autoanalyzer, Skalar Analytical B.V. Breda). Soil gravimetric moisture content was determined after drying fresh soil at 105\\u0026deg;C for 24 h.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.5 Data analysis\\u003c/h2\\u003e \\u003cp\\u003eFunctional trait diversity was calculated as \\u0026lsquo;functional dispersion\\u0026rsquo; according to Lalibert\\u0026eacute; and Legendre (\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2010\\u003c/span\\u003e) with the R function \\u003cem\\u003efd_fdis\\u003c/em\\u003e from the package \\u003cem\\u003efundiversity\\u003c/em\\u003e (Greni\\u0026eacute; and Gruson, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e). We included the following traits in the functional dispersion calculation: SLA, LDMC, leaf N concentration, leaf C concentration, leaf δ\\u003csup\\u003e15\\u003c/sup\\u003eN and leaf δ\\u003csup\\u003e13\\u003c/sup\\u003eC. Community resource acquisition strategy was calculated by including the community weighted mean (CWM) of SLA, LDMC, and leaf N in a principal component analysis using the \\u003cem\\u003erda\\u003c/em\\u003e function from the R package vegan (Oksanen et al., \\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e). All traits were sourced from a greenhouse experiment using the same plant species grown in monoculture (Oram et al., \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003ePlant resource acquisition strategy was determined using principal component analysis of the CWM of SLA, LDMC, and leaf N measured in the field, using the function \\u003cem\\u003erda\\u003c/em\\u003e from the R package \\u003cem\\u003evegan\\u003c/em\\u003e (Oksanen et al., \\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e). CWM traits were scaled. Scores were extracted and PC1 was used as a measure of plant community resource acquisition strategy.\\u003c/p\\u003e \\u003cp\\u003eThe relative mixture effect on plant species trait changes (i.e. trait shifts due to growing in a species mixture \\u003cem\\u003evs.\\u003c/em\\u003e in monoculture) was based on the trait values quantified on plant samples collected in the field experiments and calculated following Jung et al. (\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e2010\\u003c/span\\u003e) for leaf N concentration, leaf C concentration, leaf C:N ratio, SLA, leaf δ\\u003csup\\u003e13\\u003c/sup\\u003eC (a constant was added to negative values to make them positive) and Ndfa as shown below:\\u003c/p\\u003e \\u003cp\\u003e \\u003cspan class=\\\"InlineEquation\\\"\\u003e \\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:Relative\\\\:mixture\\\\:effect\\\\:species\\\\:i=\\\\frac{mixture\\\\:trait\\\\:value\\\\:speciesi-monoculture\\\\:trait\\\\:value\\\\:speciesi}{monoculture\\\\:trait\\\\:value\\\\:speciesi}\\\\)\\u003c/span\\u003e \\u003c/span\\u003e \\u003cem\\u003eEq.\\u0026nbsp;(3\\u003c/em\\u003e)\\u003c/p\\u003e \\u003cp\\u003eDiversity effects were calculated based on Loreau and Hector (\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e2001\\u003c/span\\u003e). A positive net diversity effect occurs if species productivity in a mixture is on average higher than expected based on the average of the monoculture productivity of the component species. The net diversity effect results from complementarity and selection effects. A positive selection effect occurs when a species with high monoculture yields dominates a mixture. A positive complementarity effect occurs when species are generally more productive than expected in mixtures.\\u003c/p\\u003e \\u003cp\\u003eThe complementarity was calculated as the difference between the net effect and the selection, and the selection effect was assessed by determining the covariance between the species monoculture productivity and their relative trait change in above-ground biomass from monoculture to mixture. The expected mixture productivity (PE) was calculated based on Loreau and Hector (\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e2001\\u003c/span\\u003e) as shown in \\u003cem\\u003eEq.\\u0026nbsp;(4\\u003c/em\\u003e):\\u003c/p\\u003e \\u003cp\\u003e \\u003cspan class=\\\"InlineEquation\\\"\\u003e \\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:PE=\\\\sum\\\\:\\\\left({RP}_{E,i\\\\:}X\\\\:{M}_{i}\\\\right)\\\\)\\u003c/span\\u003e \\u003c/span\\u003e \\u003cem\\u003eEq.\\u0026nbsp;(4\\u003c/em\\u003e)\\u003c/p\\u003e \\u003cp\\u003eWhere \\u003cem\\u003ePE\\u003c/em\\u003e is the expected productivity of a mixture, based on the productivity of the monocultures of the component species; \\u003cem\\u003eRP\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003eE,i\\u003c/em\\u003e\\u003c/sub\\u003e is the expected relative contribution of species \\u003cem\\u003ei\\u003c/em\\u003e to productivity in the mixture (the expected contribution of each species was assumed to be proportional to the proportion of seed sown for each species in the species mixture, i.e. 1:2 in the two-species mixtures and 1:4 in the four-species mixtures); \\u003cem\\u003eMi\\u003c/em\\u003e is the productivity of species \\u003cem\\u003ei\\u003c/em\\u003e in monoculture.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.6 Statistical analyses\\u003c/h2\\u003e \\u003cp\\u003e \\u003cem\\u003eExperiment 1\\u003c/em\\u003e \\u003c/p\\u003e \\u003cp\\u003eLinear mixed effects (LME) models (\\u003cem\\u003enlme\\u003c/em\\u003e package, Pinheiro et al. (\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e) were used to test the effect of plant species richness (monoculture, two, and four-species mixtures) or plant community composition on above-ground biomass (separately for T0, T1, T2, and the cumulative biomass of the three harvests combined), plant N uptake, overyielding, N use efficiency, Ndfa, soil NH\\u003csub\\u003e4\\u003c/sub\\u003e\\u003csup\\u003e+\\u003c/sup\\u003e-N and NO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003csup\\u003e\\u0026minus;\\u003c/sup\\u003e-N concentrations (mean of two sampling times), and diversity effects (complementarity, selection and net effect). Fixed effects were species richness or plant community composition, and the random effect was block. Two out of ten above-ground biomass samples of \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e at T2 (\\u003cem\\u003eL. corniculatus\\u003c/em\\u003e in the four-species mixture and in the mixture with \\u003cem\\u003eL. perenne\\u003c/em\\u003e) were too small to be analysed for C, N, δ\\u003csup\\u003e13\\u003c/sup\\u003eC and δ\\u003csup\\u003e15\\u003c/sup\\u003eN, thus these were not included in the analyses of plant N uptake, Ndfa and N use efficiency of these plots.\\u003c/p\\u003e \\u003cp\\u003eLME models were also used to test the effect of plant functional group (grass or legume) and growth strategy (fast- and slow-growing species) and time-point (T0, T1, and T2) on above-ground biomass in Experiment 1. Fixed effects were functional group or plant strategy, time-point and their interaction, and random effect was block/plot.\\u003c/p\\u003e \\u003cp\\u003eLM models were used to test the relative importance functional traits and growth strategy. Fixed effects were functional traits and growth strategy.\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eExperiment 2\\u003c/em\\u003e \\u003c/p\\u003e \\u003cp\\u003eWe used LME models to test the interactive effect of plant community composition (five plant communities) and fertiliser level (low or high) on overyielding, soil mineral N (NH\\u003csub\\u003e4\\u003c/sub\\u003e\\u003csup\\u003e+\\u003c/sup\\u003e-N\\u0026thinsp;+\\u0026thinsp;NO\\u003csub\\u003e3\\u003c/sub\\u003e-\\u003csup\\u003e\\u0026minus;\\u003c/sup\\u003eN, T2), N use efficiency, and Ndfa. Fixed effects were plant community composition and fertiliser level, and random effect was block.\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eExperiments 1 \\u0026amp; 2\\u003c/em\\u003e \\u003c/p\\u003e \\u003cp\\u003eAll data were checked for normality and equal variances using residual plots and log-transformed where necessary before analysis (i.e. above-ground biomass, plant N uptake, N use efficiency). We used the weight function \\u003cem\\u003evarIdent\\u003c/em\\u003e from R package \\u003cem\\u003enlme\\u003c/em\\u003e (Pinheiro et al., \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e) to account for unequal residual variances following (Zuur et al. \\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e). This was necessary to improve model fit for the following response variables: above-ground biomass, plant N uptake, Ndfa, soil NH\\u003csub\\u003e4\\u003c/sub\\u003e\\u003csup\\u003e+\\u003c/sup\\u003e-N and diversity effects (net, complementarity, and selection effects). The significance of the fixed effects was determined by comparing models with and without the factor of interest using a likelihood ratio test. We determined pairwise comparisons with Tukey post hoc using \\u003cem\\u003eemmeans\\u003c/em\\u003e (Lenth, \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). All statistical analysis was carried out in the R version 4.0.2 (R Core Team, \\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e).\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3 Results\",\"content\":\"\\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.1 Functional dispersion and plant species richness explaining diversity effects\\u003c/h2\\u003e \\u003cp\\u003eWe found that increasing species richness from one to four species significantly increased above-ground biomass, plant N uptake, N use efficiency, Ndfa (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e abcd, Table S2), and decreased soil NO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003csup\\u003e\\u0026minus;\\u003c/sup\\u003e-N (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003ef, Table S2). Furthermore, increasing species richness from two to four species significantly increased complementarity effects (Fig. S3, Table S2).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eAbove-ground biomass and complementarity effects significantly increased with increasing functional trait dispersion (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e ac) but were not related with plant community resource acquisition strategy (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e ab). Functional trait dispersion of traits or strategies was not related with N use efficiency (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e ef), nor did plant community resource acquisition strategy influence N use efficiency (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ec).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eFunctional dispersion was more important in explaining above-ground biomass, plant N uptake, N use efficiency, Ndfa and soil mineral N compared to growth strategy (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). There was no difference in the explanatory power of functional traits or strategies on complementarity effects (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eEffect of functional groups \\u003cem\\u003eversus\\u003c/em\\u003e growth strategy on above-ground biomass, plant N uptake, nitrogen use efficiency, Ndfa (%), complementarity effects and soil mineral N concentration from T2-end of experiment. Linear models were used to test the relative importance functional traits and growth strategy. Fixed effects were functional traits and growth strategy (significant effects are in bold, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05).\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"8\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFactor\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAbove-ground biomass\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003ePlant N uptake\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eNitrogen use efficiency\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eNdfa\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eComplementarity effects\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eSoil mineral N\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFunctional group\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e7.27\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e9.22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e18.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e15.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e4.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e30.8\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.0001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.00001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.0001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.0001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.03\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.0001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eGrowth strategy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4.43\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.72\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e7.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.008\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.002\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.11\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.51\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.004\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.02\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eR\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.39\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.46\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.60\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.53\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.40\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.71\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.2 Specific plant community composition and its effect on trait plasticity\\u003c/h2\\u003e \\u003cp\\u003eThe cumulative plant productivity across all harvests was highest in the mixture \\u003cem\\u003eF. arundinacea\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eT. pratense\\u003c/em\\u003e (1249 g m\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e), exceeding that of most other plant communities (1134 g m\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e), although it was not significantly higher than that of the other treatments in which \\u003cem\\u003eT. pratense\\u003c/em\\u003e was present (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ea). Plant N uptake was higher in both legumes, and in combinations with the fast-growing legume \\u003cem\\u003eT. pratense\\u003c/em\\u003e (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eb). Nitrogen use efficiency was higher in four-species mixture, followed by mixtures containing the slow-growing grass \\u003cem\\u003eF. arundinacea\\u003c/em\\u003e (\\u003cem\\u003eF. arundinacea\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eL. perenne\\u003c/em\\u003e and \\u003cem\\u003eF. arundinacea\\u0026thinsp;+\\u0026thinsp;L. corniculatus\\u003c/em\\u003e) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ec). Plant community composition did not affect soil NH\\u003csub\\u003e4\\u003c/sub\\u003e\\u003csup\\u003e+\\u003c/sup\\u003e-N levels (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ed). However, levels of NO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003csup\\u003e\\u0026minus;\\u003c/sup\\u003e-N in the soil differed significantly and legume monocultures and combinations containing \\u003cem\\u003eT. pratense\\u003c/em\\u003e had higher soil NO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003csup\\u003e\\u0026minus;\\u003c/sup\\u003e-N (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ee). Combinations of \\u003cem\\u003eT. pratense\\u003c/em\\u003e with either fast- or slow-growing grass species, and the four-species mixture, resulted in overyielding (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05, Table S2c). The complementarity effect was highest in combinations with \\u003cem\\u003eT. pratense\\u003c/em\\u003e (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05, Table S2).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eMixtures including \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e and either the fast- or slow-growing grass, or the mixture with both grasses had the lowest soil mineral N and also the lowest plant N uptake (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e). The mixture of \\u003cem\\u003eT. pratense\\u003c/em\\u003e and \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e had the highest plant N uptake and the highest soil mineral N (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e). In contrast, combining \\u003cem\\u003eT. pratense\\u003c/em\\u003e with either \\u003cem\\u003eF. arundinacea\\u003c/em\\u003e or \\u003cem\\u003eL. perenne\\u003c/em\\u003e had high plant N uptake, and relatively low soil mineral N (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003ePlant species differed in their trait values and for several species there was also an intraspecific shift in trait values for several plant traits between individual plants growing in mixture compared to when grown in monoculture (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e). The slow-growing grass \\u003cem\\u003eF. arundinacea\\u003c/em\\u003e had a higher leaf N content, SLA, and lower leaf C:N ratio when growing with \\u003cem\\u003eT. pratense\\u003c/em\\u003e compared to \\u003cem\\u003eF. arundinacea\\u003c/em\\u003e grown in monoculture (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05, Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e). \\u003cem\\u003eF. arundinacea\\u003c/em\\u003e also had lower leaf C:N ratio, leaf δ\\u003csup\\u003e13\\u003c/sup\\u003eC, and higher SLA when growing in the four-species mixture compared to \\u003cem\\u003eF. arundinacea\\u003c/em\\u003e grown in monoculture (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05, Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e). The slow-growing legume \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e increased Ndfa when growing with grasses and in the four-species mixture and decreased it when growing with \\u003cem\\u003eT. pratense\\u003c/em\\u003e. The fast-growing legume \\u003cem\\u003eT. pratense\\u003c/em\\u003e had higher Ndfa in grass mixtures compared to monocultures (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05, Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.3 Interactions between plant community composition and fertiliser level\\u003c/h2\\u003e \\u003cp\\u003eBoth above-ground biomass and plant N uptake were higher when 100 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e was applied compared to 50 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e, regardless of plant community composition (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05, FERT, Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). Monocultures of \\u003cem\\u003eT. pratense\\u003c/em\\u003e and \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e had the highest above-ground biomass in both fertiliser treatments (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05, Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). The mixture of \\u003cem\\u003eL. perenne\\u003c/em\\u003e and \\u003cem\\u003eT. pratense\\u003c/em\\u003e was as productive as the monoculture \\u003cem\\u003eT. pratense\\u003c/em\\u003e, and twice as productive as \\u003cem\\u003eL. perenne\\u003c/em\\u003e in monoculture (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05, Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). There was an interactive effect between fertilisation rate and plant community composition on overyielding of plant N uptake. The two-species mixture \\u003cem\\u003eL. perenne\\u003c/em\\u003e and \\u003cem\\u003eT. pratense\\u003c/em\\u003e showed N overyielding, at the high level of fertilisation (100 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e) but not at low fertilisation level (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.04, FERT * PLANT COMP, Fig. S6, Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). Soil mineral N (NH\\u003csub\\u003e4\\u003c/sub\\u003e\\u003csup\\u003e+\\u003c/sup\\u003e-N\\u0026thinsp;+\\u0026thinsp;NO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003csup\\u003e\\u0026minus;\\u003c/sup\\u003e-N) concentrations were highest in the legume monocultures, irrespective of fertilisation level (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05, PLANT COMP, Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eEffects of fertilisation level (FERT) and plant community composition (PLANT COMP) on cumulative above-ground biomass (sum of three harvests), plant N uptake (last harvest), overyielding, soil mineral N (last soil sampling, T2), N use efficiency, and N derived from atmosphere (Ndfa), in Experiment 2. Data are mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SE (n\\u0026thinsp;=\\u0026thinsp;5). \\u003cem\\u003eLolium perenne\\u003c/em\\u003e (Lp), \\u003cem\\u003eFestuca arundinacea\\u003c/em\\u003e (Fa), \\u003cem\\u003eLotus corniculatus\\u003c/em\\u003e (Lc), \\u003cem\\u003eTrifolium pratense\\u003c/em\\u003e (Tp). Significance tests using likelihood ratio test (LRT) comparing models with or without parameter of interest where degree of freedom shows the difference in degrees of freedom between the models. Significant effects \\u003cem\\u003e(P\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) are shown in bold. Letters indicate per response variable significant differences between the plant communities (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) based on Tukey posthoc test. Interactions between fertilisation level (FERT) and plant community composition (PLANT COMP) on overyielding, nitrogen use efficiency and Ndfa are shown in Fig. S6.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"8\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCumulative above-ground biomass\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ePlant N uptake\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003eOveryielding net effect\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eSoil mineral N (NH\\u003csub\\u003e4\\u003c/sub\\u003e\\u003csup\\u003e+\\u003c/sup\\u003e-N\\u0026thinsp;+\\u0026thinsp;NO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003csup\\u003e\\u0026minus;\\u003c/sup\\u003e-N)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eN use efficiency\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eNdfa\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eg m\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eg N m\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eg m\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eg N m\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003emg kg\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e%\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e%\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFERT\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e50\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e661.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;48\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e6.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e15.7\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;29\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e-0.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e8.7\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e60.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e53.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;8.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e100\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e825.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;58\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e9.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e51.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;44\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.2\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e12.7\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e51.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e49.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;7.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePLANT COMP\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLp\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e453.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;23 \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2.8\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.4 \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e4.0\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.4 \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e57.1\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTp\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1063.8\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;47 \\u003csup\\u003ec\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e11.8\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.7 \\u003csup\\u003eb\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e20.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.6 \\u003csup\\u003ec\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e32.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e34.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;6.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLc\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e749.9\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;59 \\u003csup\\u003eb\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e10.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.5 \\u003csup\\u003eb\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e15.1\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.9 \\u003csup\\u003ebc\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e31.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e16.0\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLpLc\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e530.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;49 \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3.7\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.7 \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-40.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;19 \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e-2.9\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e4.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.7 \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e88.5\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e87.8\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;8.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLpTp\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e919.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;67 \\u003csup\\u003ebc\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e10.7\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.3 \\u003csup\\u003eb\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e107.5\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;35 \\u003csup\\u003eb\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e9.9\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.9 \\u003csup\\u003eb\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e74.2\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e71.2\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFERT\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;18, \\u003cb\\u003eP\\u003c/b\\u003e\\u0026thinsp;\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.0001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;15, \\u003cb\\u003eP\\u003c/b\\u003e\\u0026thinsp;\\u003cb\\u003e=\\u0026thinsp;0.0001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;1, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.35\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;0.1, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;4, \\u003cb\\u003eP\\u003c/b\\u003e\\u0026thinsp;\\u003cb\\u003e=\\u0026thinsp;0.03\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;7, \\u003cb\\u003eP\\u003c/b\\u003e\\u0026thinsp;\\u003cb\\u003e=\\u0026thinsp;0.008\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;0.5, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePLANT COMP\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;74, \\u003cb\\u003eP\\u003c/b\\u003e\\u0026thinsp;\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.0001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;48, \\u003cb\\u003eP\\u003c/b\\u003e\\u0026thinsp;\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.0001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;10, \\u003cb\\u003eP\\u003c/b\\u003e\\u0026thinsp;\\u003cb\\u003e=\\u0026thinsp;0.0008\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;12, \\u003cb\\u003eP\\u003c/b\\u003e\\u0026thinsp;\\u003cb\\u003e=\\u0026thinsp;0.0004\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;61, \\u003cb\\u003eP\\u003c/b\\u003e\\u0026thinsp;\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.0001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;118, \\u003cb\\u003eP\\u003c/b\\u003e\\u0026thinsp;\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.0001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;57, \\u003cb\\u003eP\\u003c/b\\u003e\\u0026thinsp;\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.0001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFERT * PLANT COMP\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;3, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.54\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;6, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.18\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;1, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;4, \\u003cb\\u003eP\\u003c/b\\u003e\\u0026thinsp;\\u003cb\\u003e=\\u0026thinsp;0.04\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;4, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;11.5, \\u003cb\\u003eP\\u003c/b\\u003e\\u0026thinsp;\\u003cb\\u003e=\\u0026thinsp;0.02*\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eLRT\\u0026thinsp;=\\u0026thinsp;8, \\u003cb\\u003eP\\u003c/b\\u003e\\u0026thinsp;\\u003cb\\u003e=\\u0026thinsp;0.05\\u003c/b\\u003e\\u003cem\\u003e*\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe N use efficiency of the plant communities was dependent on the interaction between plant species composition and fertilisation rate (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05, FERT * PLANT COMP, Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). Both mixtures with \\u003cem\\u003eL. perenne\\u003c/em\\u003e (combined with either \\u003cem\\u003eT. pratense\\u003c/em\\u003e or \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e) and \\u003cem\\u003eL. perenne\\u003c/em\\u003e monoculture decreased N use efficiency with an increase in N fertiliser level (100 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e), while both legumes were not affected (Fig. S6).\\u003c/p\\u003e \\u003cp\\u003eThere was a significant interactive effect between plant community composition and fertiliser rate on the level of N-fixation as quantified by Ndfa (\\u003cem\\u003eP\\u0026thinsp;=\\u0026thinsp;0.05\\u003c/em\\u003e, FERT * PLANT COMP, Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). In the grass-legume mixture, \\u003cem\\u003eL. perenne\\u003c/em\\u003e and \\u003cem\\u003eT. pratense\\u003c/em\\u003e, the legume maintained its level of N-fixation irrespective of the level of N fertilisation, whereas \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e (in the \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e and \\u003cem\\u003eL. perenne\\u003c/em\\u003e mixture) showed higher levels of N-fixation at lower level of N fertilisation (Fig. S6, Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"4 Discussion\",\"content\":\"\\u003cp\\u003eThe aim of this study was to investigate how mixtures of plant species from different functional groups (grasses or legumes) with contrasting growth strategies (fast- or slow-growing species) affect plant productivity, N uptake, and soil mineral N, and how these effects depend on N fertilisation level in a managed grassland system. We found that increasing species richness from one to four species increased above-ground biomass and plant N uptake. The growth strategies of the legumes were of prime importance for these diversity effects; overyielding was only achieved when combining the fast-growing legume (higher Ndfa) with either slow- or fast-growing grass species, whereas the slow growing legume (\\u003cem\\u003eL. corniculatus\\u003c/em\\u003e) biomass decreased in the mixtures at high N fertilisation (100 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e). At low level of N fertilisation, the slow-growing legume had very high N-fixation when growing in combination with the fast-growing grass compared to growing alone. This suggests that slow-growing legumes like \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e could contribute to reducing the reliance on N fertiliser in managed grasslands, provided they get a chance to establish well with sufficient time and optimal conditions to develop a strong root system.\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eFunctional traits and strategy as drivers of diversity effects (Experiment 1)\\u003c/em\\u003e \\u003c/p\\u003e \\u003cp\\u003eWe found that functional traits were more important in explaining above-ground biomass, plant N uptake, N use efficiency, Ndfa and soil mineral N compared to growth strategy (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Plant communities with a diverse range of functional trait values exhibit improved N response efficiency. This enhancement is primarily due to increased N uptake efficiency, attributed to the presence of functionally diverse species that optimise resource use. Plant communities with specific functional traits can regulate N cycling in intensively managed grasslands. For instance, incorporating legumes alongside grasses with particular root traits can enhance plant N uptake and reduce soil mineral N levels, leading to more efficient N cycling (Abalos et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eThe four-species mixture had higher above-ground biomass and plant N uptake than the average of the monocultures. Over the entire experiment, mixtures had significantly higher productivity compared to the average of the four species monocultures (overyielding), and the combination between \\u003cem\\u003eT. pratense\\u003c/em\\u003e and \\u003cem\\u003eF. arundinacea\\u003c/em\\u003e had higher productivity compared to the most productive species\\u0026rsquo; monoculture (\\u003cem\\u003eT. pratense\\u003c/em\\u003e), i.e. transgressive overyielding. These findings are consistent with other studies in fertilised grasslands that show overyielding effects (Kirwan et al., \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e; Nyfeler et al., \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e; Suter et al., \\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e; Abalos et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). We suggest that the potential mechanism explaining this increase in productivity could be the increase in N use efficiency, and in complementarity use of soil N by the grasses and N obtained through N-fixation by the legumes. The positive diversity effects were due to positive complementarity effects (rather than the chance of including a highly productive species, i.e. selection effects), agreeing with previous studies in semi-natural and fertilised grassland (Barry et al., \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e; Mason et al., \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). The increase in biological N-fixation can lead to a reduction in leaf C:N ratio of the species mixtures, indicating reduced competition for soil mineral N with a facilitative role for legumes (Temperton et al., \\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e). In our fertilised grassland experiment, we found a decrease in the leaf C:N ratio of the grasses and thereby increased forage quality when growing in mixtures with the fast-growing legume, but this was not the case when grown with the slow-growing legume due to competition. Although there was only one four-species mixtures in our experiment at one fertilisation level (100 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e), and caution is needed when drawing general conclusions, our results align with other studies showing increases in N use efficiency and biological N-fixation with increasing plant species richness (Cummins et al., \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; Grange et al., \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eEffects of plant community composition on productivity and soil mineral N (Experiment 1)\\u003c/em\\u003e \\u003c/p\\u003e \\u003cp\\u003eLegume growth strategy was a key driver of above-ground biomass and soil mineral N in our experiment. Combinations with \\u003cem\\u003eT. pratense\\u003c/em\\u003e, the fast-growing legume, were associated with overyielding and could be explained by plant trait plasticity (Mason et al., \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). Biological N-fixation by \\u003cem\\u003eT. pratense\\u003c/em\\u003e increased when it was growing with grasses. This grass-legume combination resulted in reduced soil mineral N due to high soil N uptake by the grasses, which stimulated the fast-growing legume to fix more N from the atmosphere (i.e. increase Ndfa, Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). The overyielding observed in the specific combinations between \\u003cem\\u003eT. pratense\\u003c/em\\u003e and \\u003cem\\u003eF. arundinacea\\u003c/em\\u003e, and in the four-species mixture, could be influenced by intraspecific trait shifts. In these plant species combinations, \\u003cem\\u003eF. arundinacea\\u003c/em\\u003e plants had lower leaf C:N ratio and higher SLA compared to its monoculture plants (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e), that could suggest lower N limitation and larger light interception for \\u003cem\\u003eF. arundinacea\\u003c/em\\u003e in this plant community. This was also observed in other studies in N rich conditions: a decrease in leaf C:N in two dominant grass species(Chen et al., \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e2005\\u003c/span\\u003e) and an increase in SLA (Al Haj Khaled et al., \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2005\\u003c/span\\u003e). Trait plasticity has been linked to overyielding in other studies (Thein et al., \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e2008\\u003c/span\\u003e; Roscher et al., \\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e; Yang et al., \\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e), although(Mason et al., \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e) found only a weak relationship between intraspecific trait plasticity and overyielding relative to resource use efficiency (water, N, and light).\\u003c/p\\u003e \\u003cp\\u003eIn our experiment, although \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e, the slow-growing legume, had high productivity in monocultures, it was supressed when grown in mixtures. This contrasts with the high productivity observed for this species in species mixtures in other experiments (De Deyn et al., \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e). Frequently, the mixtures performance can be closely related to the performance of individual species i.e. their establishment rate, and their different shoot and root traits (Egan et al., \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). However, the slow establishment rate of \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e in our experiment may have allowed other species in the mixture (i.e. fast-growing species, \\u003cem\\u003eT. pratense\\u003c/em\\u003e and \\u003cem\\u003eL. perenne\\u003c/em\\u003e) to out-compete it for light and nutrients. In addition, seeds were sown in our field experiment to represent agricultural practice, whereas in (De Deyn et al., \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e) the plant communities were not established by seeding but by planting seedlings, with an equal number of individuals per plant species per area, and plants were not fertilised during the experiment. These reasons could have contributed to the poor (but possibly more realistic) competitivity of \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e in species mixtures in our fertilised grassland experiment.\\u003c/p\\u003e \\u003cp\\u003eOverall, taking into consideration plant N uptake and N loss to the environment, we found that legume monocultures and their combination (\\u003cem\\u003eT. pratense\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eL. corniculatus\\u003c/em\\u003e) had the highest plant productivity, but they also had the highest soil mineral N levels (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e). This is not a surprise as many studies have shown that legume species can increase mineral N due to the release of fixed N from their roots via decomposition, and their inefficiency in acquiring soil mineral N alone (Niklaus et al., \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e2006\\u003c/span\\u003e; Barneze et al., \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). Yet, we found that mixing the legumes with either grass species was an effective way to reduce soil mineral N strongly compared to legume monocultures, regardless of the grass growing strategy. This is an important finding, because decreasing soil mineral N availability is paramount for sustainable production systems, as this N pool is highly susceptible to be lost from the agroecosystem in the form of nitrate leaching or as nitrous oxide. Previous studies have shown reductions of soil mineral N with increasing plant biomass production (Abalos et al., \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). Although it is difficult to generalise and to transfer the results from our study to other fast- \\u003cem\\u003evs\\u003c/em\\u003e slow-growing grasses and N fixers because we only had two grasses and two legumes, the selected species are very common in managed grasslands and therefore these findings are relevant for on-farm applications in temperate grasslands.\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eFertiliser level determines the performance of legumes in grass-legume mixtures (Experiment 2)\\u003c/em\\u003e \\u003c/p\\u003e \\u003cp\\u003eAt low fertilisation level (50 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e) we did not observe an increase in plant productivity (or plant N uptake) in the plant community with a more acquisitive resource acquisition strategy (\\u003cem\\u003eL. perenne\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eT. pratense\\u003c/em\\u003e), contradicting our second hypothesis. However, at the higher fertilisation level, the \\u003cem\\u003eL. perenne\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eT. pratense\\u003c/em\\u003e combination (together with the legumes) showed the highest plant community productivity (above-ground biomass) and N uptake, yet with high soil mineral N level at potential risk of getting lost. There was an interaction effect between N use efficiency and N fertilisation level, at low fertilisation level, N use efficiency was higher in the mixtures (\\u003cem\\u003eL. perenne\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eT. pratense\\u003c/em\\u003e and \\u003cem\\u003eL. perenne\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eL. corniculatus\\u003c/em\\u003e) compared to the monocultures, partly agreeing with our second hypothesis.\\u003c/p\\u003e \\u003cp\\u003eOverall, these results confirm the challenges of simultaneously achieving high plant biomass production quantity and quality and low soil mineral N levels, to reduce risks of N losses, in grasslands. Recommendations for optimum grass-legume mixtures will therefore depend on the specific priority for a given site: either a farmer-driven focus on production, or a policy-driven minimisation of N losses. Nevertheless grass-legume mixtures are preferable over grass monocultures as the N-fixation by the legumes especially in grass-legume combinations can (partly) replace the use of mineral N fertiliser and therefore the greenhouse gas emissions associated with fertiliser production.\\u003c/p\\u003e \\u003cp\\u003eWe observed higher overyielding in the mixture with the slow-growing legume (\\u003cem\\u003eL. perenne\\u003c/em\\u003e\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003eL. corniculatus\\u003c/em\\u003e) at low fertilisation level relative to high fertilisation level (Fig. S6). Although the grass-legume mixture with \\u003cem\\u003eT. pratense\\u003c/em\\u003e had 1.6 times higher productivity compared to the mixture with \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e, the slow-growing legume was able to increase its N supply from atmospheric N by 11% in the treatment with 50 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e compared to 100 kg N ha\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e (Ndfa\\u0026thinsp;=\\u0026thinsp;98%; Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e, Fig. S6). This increase in biological nitrogen fixation by \\u003cem\\u003eL. corniculatus\\u003c/em\\u003e grown with \\u003cem\\u003eL. perenne\\u003c/em\\u003e could allow for reductions in N fertilisation without reductions in plant community N uptake or plant productivity. A key knowledge gap is understanding the conditions (e.g. seeding rates, fertiliser application timing) allowing for a better establishment and development of species with lower competitive ability in the short-term but with high potential to contribute to plant productivity and N provisioning on the longer-term.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e \\u003ch2\\u003eCompeting Interests\\u003c/h2\\u003e \\u003cp\\u003eThe authors have no relevant financial or non-financial interests to disclose.\\u003c/p\\u003e \\u003c/p\\u003e\\u003ch2\\u003eFunding\\u003c/h2\\u003e \\u003cp\\u003eThis work was supported by Dutch Research Council - NWO ALW grant awarded to Gerlinde B. De Deyn (grant number ALWOP.448). The authors declare no conflict of interest.\\u003c/p\\u003e\\u003ch2\\u003eAuthor Contributions\\u003c/h2\\u003e \\u003cp\\u003eA.S.B., W.W., N.J.O, D.A and G.B.D.D. designed the experiment; A.S.B. and W.W. conducted the experiment with input from N.J.O, D.A. and G.B.D.D., A.S.B. and N.J.O. analysed the data and wrote the manuscript with extensive input from W.W., D.A. and G.B.D.D.\\u003c/p\\u003e\\u003ch2\\u003eAcknowledgements\\u003c/h2\\u003e \\u003cp\\u003eThis study was supported by an NWO ALW grant awarded to GBDD (grant number ALWOP.448). The authors thank Barenbrug BV, The Netherlands for the seeds used in this experiment. Thanks to the staff of the Unifarm, especially, John van der Lippe and Frans Bakker for their support in the field. Thanks also to Peter Garamszegi and Lorenzo Mento for their help with the practical work. Thanks to Jan Willem van Groenigen for valuable discussions during the whole experiment. The authors declare no conflict of interest.\\u003c/p\\u003e\\u003ch2\\u003eData Availability\\u003c/h2\\u003e \\u003cp\\u003eThe datasets generated during the current study are available from the corresponding author on reasonable request.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eAbalos D, De Deyn GB, Kuyper TW, van Groenigen JW (2014) Plant species identity surpasses species richness as a key driver of N2O emissions from grassland. 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Funct Ecol 36:2163\\u0026ndash;2175. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1111/1365-2435.14115\\u003c/span\\u003e\\u003cspan address=\\\"10.1111/1365-2435.14115\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZuur AF, Ieno EN, Walker NJ, Saveliev AA, Smith GM (2011) Mixed Effects Models and Extensions in Ecology with R. Springer\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":true,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"plant-and-soil\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"plso\",\"sideBox\":\"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)\",\"snPcode\":\"11104\",\"submissionUrl\":\"https://submission.nature.com/new-submission/11104/3\",\"title\":\"Plant and Soil\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false},\"keywords\":\"grass-legume mixtures, growth strategies, managed grassland, nitrogen cycling, nitrogen use efficiency, plant productivity\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6512158/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6512158/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cem\\u003eAims: \\u003c/em\\u003eManaged grasslands are important agro-ecosystems, consisting of grass monocultures with high nitrogen (N) fertiliser inputs. This management results in low N use efficiency and high N losses to the environment. Growing mixtures of plant species with diverse N acquisition strategies can reduce N losses and maintain high grassland productivity, yet determining the best mixture remains a challenge. The aim of this study was to investigate how grass-legume mixtures with contrasting growth strategies affect plant productivity, N use efficiency, N uptake, and soil mineral N, and how these effects depend on the N-fertilisation level.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eMethods:\\u003c/em\\u003e Two complementing field experiments were established: the first determined how monocultures and mixtures (two and four grass-legume mixtures) with contrasting growth strategies (fast- \\u003cem\\u003evs\\u003c/em\\u003e. slow-growing) affect productivity and N-cycling. The second determined the effect of fertilisation level on productivity and N-cycling in monocultures and two-species mixtures.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eResults:\\u003c/em\\u003e We found that productivity and N uptake of the four-species mixture was as high as the most productive monoculture and two-species mixtures. This was associated with an increase in legume N-fixation and high N use efficiency of the plant community. Fast-growing grass and legume combination increased productivity and reduced soil mineral N, thereby the risk of N loss for both N-fertilisation levels, while combining a fast-growing grass with a slow-growing legume promoted high legume N-fixation under low N-fertilisation.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eConclusions:\\u003c/em\\u003e This study shows that productivity and N-cycling decreases via complementarity effects when growing mixtures of fast- and slow-growing grasses and a fast-growing legume at moderate level of N-fertilisation.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Optimising grass-legume mixtures based on growth strategies for high N-yield and low N-loss in fertilised grasslands\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-05-14 06:03:02\",\"doi\":\"10.21203/rs.3.rs-6512158/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Major revisions\",\"date\":\"2025-06-08T23:09:18+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"\",\"date\":\"2025-05-14T08:56:01+00:00\",\"index\":0,\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-05-09T10:48:08+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvited\",\"content\":\"Plant and Soil\",\"date\":\"2025-04-24T09:14:49+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-04-24T03:33:10+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Plant and Soil\",\"date\":\"2025-04-23T07:32:11+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"plant-and-soil\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"plso\",\"sideBox\":\"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)\",\"snPcode\":\"11104\",\"submissionUrl\":\"https://submission.nature.com/new-submission/11104/3\",\"title\":\"Plant and Soil\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false}}],\"origin\":\"\",\"ownerIdentity\":\"841b3311-133b-4a00-ba59-c228b1f417b1\",\"owner\":[],\"postedDate\":\"May 14th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-08-04T16:46:39+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-6512158\",\"link\":\"https://doi.org/10.1007/s11104-025-07736-5\",\"journal\":{\"identity\":\"plant-and-soil\",\"isVorOnly\":false,\"title\":\"Plant and Soil\"},\"publishedOn\":\"2025-08-01 16:38:11\",\"publishedOnDateReadable\":\"August 1st, 2025\"},\"versionCreatedAt\":\"2025-05-14 06:03:02\",\"video\":\"\",\"vorDoi\":\"10.1007/s11104-025-07736-5\",\"vorDoiUrl\":\"https://doi.org/10.1007/s11104-025-07736-5\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6512158\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6512158\",\"identity\":\"rs-6512158\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}