Linkages between farming practices, crop yield and weed communities in rainfed Mediterranean agroecosystems

Linkages between farming practices, crop yield and weed communities in rainfed Mediterranean agroecosystems | 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 Linkages between farming practices, crop yield and weed communities in rainfed Mediterranean agroecosystems M Remedios Alarcón Víllora, Ana M Sánchez Álvarez, Luis Navarrete Martínez, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8768054/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract For rainfed cropping systems in semiarid regions to be sustainable, they should provide multiple agroecosystem services simultaneously while accounting for the environmental constraints inherent to these areas. Achieving this may require a reevaluation of the main farming practices, including the choice of tillage system and fertilization rates. In this study, we present, for the first time, an integrative evaluation of these practices that considers crop performance, weed management, and the conservation of weed community diversity. Over four crop seasons in a cereal–legume rotation, we compared the effect of three tillage systems (conventional, minimum, and no-till) and two fertilization rates (full NPK vs. 50% reduction) on crop yield, weed abundance, and weed diversity -both species diversity (inverse Simpson index) and functional diversity (mean pairwise distance of six traits; MPD)- using Structural Equation Modelling. The effects of fertilization and of the choice of tillage system were more pronounced on cereal than on legume crops. In cereals, reduced fertilization rates and lower tillage intensity increased yields, consistent with previous studies on crop performance under water-limited conditions. Weed abundance and trait composition were more responsive to tillage than to fertilization: reducing tillage increased abundance and the diversity of resource acquisition traits but decreased species diversity and the diversity of regenerative strategies. These findings show the potential of reducing fertilization rates without compromising crop yields, enhancing farmer’s profitability and sustainability. Further, our results reveal a disconnection between tillage effects on crop yield and on weed management and diversity, each of which is better achieved by no-till or by conventional systems. Minimum tillage could be a ready-to-use strategy to combine both goals, but we acknowledge that a research and technical gap exists to maximize crop yield, weed management and soil structure maintenance in these systems. agroecosystems cereal-legume rotation ecosystem services fertilization functional diversity Mediterranean annual crops piecewise-SEM tillage system weed abundance crop yield Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Agroecosystems are closely driven by management practices that strongly influence nutrient cycles as well as biotic and abiotic interactions, ultimately affecting crop productivity and ecosystem sustainability. The technological developments of the 20th century supposed the abandonment of traditional practices and the adoption of novel managements especially in relation with tillage, pesticides and fertilizers, that lead in most geographical context to increasing crop yields. However, the intensification of management has also had negative effects on the agroecosystem services and on the farm’s biodiversity, leading to the homogenization of agricultural landscapes (Tamburini et al, 2020). However recent studies have shown that increase yields has not been always the rule, especially in marginal areas where abiotic restrictions related with climate, topography or soil conditions limits the ecosystem productivity and consequently crop yields. On top of that, climate change in these marginal areas is compromising farms sustainability or farmer’s profitability. To overcome these negative effects alternative management schemes, propose to focus on ensuring the simultaneously provision of various agroecosystem services (i.e., provisioning and regulating services; Bommarco et al., 2013). These proposals include the use and maintenance of agrobiodiversity, the reduction of disturbance from agricultural practices and the decrease in the dependence on external inputs (Tamburini et al., 2020). In the case of rainfed crops located on semiarid lands, which cover 80% of the world agricultural land area and provide large part of the main staple foods (FAOSTAT, 2023), these proposals should also take into account other environmental stressors. For example, in the Iberian Peninsula, rainfed cereal-based systems cover about 50% of the agricultural land and are characterized by a low soil organic matter content (Romanyà and Rovira, 2011), low rainfall and high inter-annual variability in the environmental conditions (Peña-Gallardo et al., 2019). These environmental factors challenge crop production and force to adapt farming practices to allow cultivation in these semiarid lands. Currently, two main practices that drive the functioning of these rainfed cereal systems are on debate: the tillage system and the amount of fertilization needed to assure crop yields. On the one hand, periods of water deficit reduce the availability of soil nutrients and the capacity of plants to uptake them (Guo et al., 2012), thereby questioning the effectiveness of increasing fertilization rates as the main strategy to increase crop yields. On the other hand, tillage was the default practice for managing weeds until the advent of herbicides, which opened the opportunity to no-tillage systems. While these systems have proven benefits for soil functionality, they remain highly dependent on broad- spectrum herbicides, which reduce weed diversity (Carmona et al., 2020). Weed communities that are (functionally) diverse have shown to exert a lower impact on crop production than those dominated by one or a few species (Adeux et al., 2019). Therefore, management recommendations should also consider the maintenance of weed diversity, not only because of its positive effect on yields relative to that produce by species poor weed communities, but also because many ecosystem services rely on weed diversity (MacLaren et al., 2020). In this study, we evaluate the most common tillage systems and crop fertilization in Mediterranean rainfed cereal-based systems, focusing on their effects on crop yield and weed communities. We hypothesize that a reduction in management intensity, achieved by reducing tillage intensity and fertilization rates, will maintain crop yields and support weed diversity without increasing weed abundance. To assess this hypothesis, we constructed a conceptual model illustrating the effects of three main tillage systems -moldboard (inversion) tillage, minimum tillage (non-inversion), and no-tillage with pre-sowing herbicide application- and two fertilization levels (full NPK vs. 50% reduction) on crop and weed communities (Fig. 1 ). The model considers the effect of tillage and fertilization on crop yield, as well as their effects on weed abundance and taxonomic and functional diversity. We also include the relationship among different aspects of weed communities as well as their relation to crop yield (Fig. 2 ). To test this conceptual model, we use structural equation models (SEM) with data from a four-year long experiment under Mediterranean conditions, including years with contrasting rainfall patterns. The experiment consisted on a rotation of cereal and legume, the two main types of crops in these rainfed cereal-based systems. We fitted different models separately for each type of crop and year in order to identify the better practices in terms of both economic and environmental sustainability (Devkota et al., 2022). 2. Materials and Methods The study was carried out at the El Encín Experimental Farm (40°31'N; 3°17'W, 610 m) in Alcalá de Henares (Madrid, Spain) under a loamy Calcic Haploxeralf soil. Field seasons (September-June) are characterized by an average temperature of 12.13 ± 0.98 ºC and a precipitation of 408.2 ± 97.56 mm (data from 1986–2016 recorded at El Encín weather station), with a marked dry period in summer in each of the four study seasons (Fig. 3 and Fig. S1 ). The tillage factor consisted of three levels (8 plots per level): Inversion tillage, commonly referred as mouldboard tillage (CT), minimum tillage (MT), and no-tillage (NT). Inversion tillage was performed using a moldboard plough working at a depth of 30 cm. In minimum tillage plots a chisel plough was used, working at a depth of 15 cm, without inverting the soil profile (vertical tillage). In both cases, a secondary vertical tillage was done with a cultivator at a depth of 15 cm after primary tillage. No-tillage implied direct sowing after the use of herbicide, glyphosate © (0.9 L a.i. ha-1) 4 to 6 days before sowing. Fertilization consisted of two levels (12 plots per level): full fertilization (FF), corresponding to the rate more frequently use in conventional farms in the region, and reduced fertilization (RF), which was 50% of the full rate. Fertilizer (N, P and K) was applied at the time of sowing in both cereal and legumes. In cereal a top-dressing nitrogen fertilisation was also applied. Table S1 (see supplementary material) shows the rates and fertilizers used in each crop and year. All crops were sown with a driller at a row spacing of 17 cm. 2.2. Weeds and crop yield sampling In each crop season, we counted the number of individuals of each weed species in 10 quadrats of 0.1 m2 per plot. Sampling was carried out at the seedling stage of the weeds, coinciding with the beginning of tillering in cereals and stem elongation in legumes. The quadrats were arranged systematically in the plot in an M-shaped itinerary, always with a spacing of 2 m from the plot edge and 7 m between quadrats (for more details on sampling procedure, see Alarcón et al., 2018). Crop yield (grain weight) was determined at crop maturation stage. To do that, in cereals, three bands (1.40 m x 10 m) in each plot were harvested with a micro-harvester, whereas in legumes, crop was collected from 4 quadrats (0.25 m2) in each plot. 2.3. Weed Diversity Indices The abundance of weed species in each plot was obtained as the sum of the individuals recorded in the 10 sampled quadrats. These data were used to calculate: i) the inverse Simpson index (1/D), as a species diversity metric, and; ii) mean pairwise distance (MPD) as a functional diversity index (Clarke and Warkwick, 1998). MPD explains the average distance between pairs of species randomly selected from an assemblage without replacement. MPD was computed independently for six functional traits. Specific leaf area (SLA), plant height at maturity, and growth habit (creepy, erect, rosulate) were considered resource acquisition traits. Additionally, seed weight, emergence time (indicated by month of emergence), and seed cover (present or not) were considered regenerative traits. SLA, plant height and seed weight values were measured following standardized protocols as described in Alarcón et al. (2019), whereas trait values of growth habit, emergence time and seed cover, were retrieved from literature (Supplementary material Table S2). We included 176 values representing the 6 traits in the 30 species. Only four data were missing (2.2%). Diversity metrics were calculated using the vegan package (Oksanen et al., 2020) and the “melodic” function of picante package (De Bello et al. 2016) in R (R Development Core Team, 2020). 2.4. Statistical analysis To evaluate our conceptual model (Fig. 2 ), we used Structural Equation Modelling. SEM is a technique that allows the analysis of direct and indirect effects of multiple interacting factors, permitting the identification of the correlations, and their causality, among variables. We fit the SEM models using the piecewise method (local estimation), in the piecewiseSEM package (Lefcheck, 2016) in R. This method is an alternative approach to variance-covariance-based SEM, which allows for a low number of observations and does not assume a multinormal distribution. The overall fit of each SEM model was evaluated with d-generalized separation test based on Fisher's C statistics (Shipley, 2009). The trend and magnitude of the relationship between the variables were obtained from the standardized regression coefficients, considering their significance with a p-value less than 0.05. To test the consistency of results in different crops and at distinct environmental conditions, we constructed four SEM models (two type of crops and two years). In each model, the relationships were specified using general linear mixed effects models (nlme package; Pinheiro et al., 2020). The tillage system was coded considering a gradient of disturbance from no-tillage (NT = 0) to conventional tillage with soil inversion (CT = 2), being the intermediate disturbance level the minimum tillage (MT = 1). Thus, high values of the tillage factor reflect a higher soil disturbance level. Reduced fertilization was coded as 1 and full fertilization as 2. Weed abundance was transformed using natural logarithms. Block was considered a random effect in all cases. The marginal coefficient of determination (Nakagawa et al., 2013), expressing the variance explained by the fixed factors, was also calculated for each of the individual equations. 3. Results and Discussion Our data show the pivotal role of tillage system and annual climate conditions on both crop yields and weed communities. On the contrary, soil fertilization, did not show an effect on the studied rainfed systems. Data also highlight the intricate relationship between, abundance, diversity and functional structure of weed communities. 3.1. Reducing tillage intensity and fertilizer rates do not affect cereal and legume yields A reduction in the intensity of management practices—specifically fertilization and tillage—did not negatively impact crop yields. Wheat yield was negatively correlated with fertilizer application rates (standardized regression coefficients of -0.24 and − 0.32 in 2013/2014 and 2015/2016 respectively; (Fig. 4 and Supplementary Material Table S3 and Table S4). In contrast, fertilization had no significant effect on legume crop yields (Fig. 5 and Supplementary Material Table S5 and Table S6). Our results align with previous studies that have identified a small or no effect of fertilization on crop yield on water-limited contexts (Cantero-Martínez et al., 2016). In this case, spring precipitation (March–May) during the four experimental growing seasons ranged from 50 to 230 mm, while total seasonal precipitation remained below 400 mm (Fig. 2 and supplementary material Fig. S1 ), which is considered the threshold for efficient nutrient use in Mediterranean cropping systems (López-Bellido et al., 1998). Accordingly, our results suggest the potential for reducing the fertilizer rate (up to 50% in this study) without compromising cereal and legume crop yields. Moreover, given the inherent variability of Mediterranean rainfall patterns, soil fertility management should be oriented towards strengthening soil functionality and properties, rather than focusing solely on nutrient supply (Sun et al., 2020). In addition, reducing fertilizer rates may prevent nutrient accumulation in the soil, which could otherwise disrupt soil functioning through declines in microbial activity and diversity (Sradnick et al., 2013). Further, from an economic perspective, the reduction in fertilizer rates can enhance farmer’s profitability in these rainfed systems. Reducing tillage intensity also had a positive effect on wheat yields in both seasons (standardized regression coefficients values of -0.73 and − 0.87, respectively; Fig. 4 and supplementary material Table S3 and Table S4). The effect of different tillage systems on crop yields is still debated, making it challenging to provide a definitive recommendation. Previous works (Devkota et al., 2022; Su et al., 2021; Veresoglou et al., 2022) have shown that reduced-tillage systems (MT or NT) performed better than CT under water limited environments when crops are rotated and residues are not removed, which corresponds to the conditions of our experiment. Wheat results in our study support these conclusions. However, the effect of the tillage system in the legume crops showed a contrasting response (Fig. 5 and supplementary material Table S5 and Table S6). CT improved crop performance in the first season (2012 − 203; standardized regression coefficients value of 0.49), with no significant differences observed in the second. These results suggest that legumes may be particularly vulnerable to additional yield-limiting factors under no-tillage (Arvidsson and Håkansson, 2014), including soil compaction which could be more severe under a drier winter (as in 2014/2015 season, Fig. 3 ). In line with this, Muñoz-Romero et al. (2012) found that under dry conditions, CT promoted deeper root development compared to NT, which may explain improved water uptake and the higher yields observed under CT. Legume yields in the second season were practically negligible due to particularly harsh conditions (the water deficit was evident from January, Fig. 3 C), and in this case, the choice of tillage system had little effect (Fig. 5 B). These findings highlight the importance of adopting a flexible agronomic management strategy that alternates between no-till and reduced tillage practices, tailored to the specific requirements of each crop within the rotation. 3.2. Weed communities responded to the intensity of tillage but not to a reduction in the fertilizer rates The reduction in the fertilizer rate did not have an effect on the abundance or the diversity of weed communities. In contrast, reducing the intensity of tillage led to weed communities of higher abundance, lower species diversity and lower diversity of regenerative traits, but higher of resource acquisition traits (Fig. 4 , Fig. 5 and supplementary material, Tables S3, S4, S5 and S6). This may be explained by differences in how the three tillage systems distribute weed seeds throughout soil layers (Spokas et al., 2007). The absence of soil disturbance in NT determines that most of the seeds remain at the soil surface which benefits those species whose germination occurs promptly when conditions are optimal. This mostly refers to species with specific regenerative attributes: an early emergence time and lack of any seed coverings that may inhibit germination (e.g., pericarp). In contrast, soil inversion in CT systems allow a distribution of weeds seeds throughout all the soil profile disturbed by the mouldboard (Chauhan et al. 2006; Spokas et al. 2007). In this case, more diverse regenerative strategies are allowed to persist. In example, not only the seeds left in the surface, but those buried in the first centimeters, and with high seed weight, may have an opportunity to emerge. MT involves an intermediate situation, with more seeds located in the upper soil layers, but with some seeds buried on the first centimeters. 3.3. Tillage systems influence the relationships among various aspects of weed communities In wheat seasons, the model illustrates intricate interactions among the different facets of weed communities, including abundance, species diversity, and functional diversity, which are further influenced by tillage practices. Specifically, weed abundance was negatively related to weed diversity in both seasons (standardized regression coefficients value − 0.51 and − 0.69, first and second season respectively Fig. 4 and supplementary material Tables S3 and S4). In addition, the MPD of SLA and plant height were positively related to abundance (standardized regression coefficients value 0.47 and 0.35 both seasons) and negatively related to diversity (standardized regression coefficients value − 0.86 and − 0.59 both seasons), whereas the opposite pattern was found for the MPD of seed cover related to weed abundance (standardized regression coefficients value − 0.50 and − 0.67 both seasons). Overall, communities with high abundance and low species diversity were characterized by higher functional diversity of resource acquisition traits but lower functional diversity of regenerative traits. These relationships cannot be understood without considering the effect of tillage systems on weed communities, since abundant and less diverse communities were associated with reduced tillage intensity, as reported above. This is further supported by the positive covariation between crop yield and weed abundance in the second wheat year (standardized regression coefficients value 0.60), where crop yield is higher as the intensity of tillage reduces. Nonetheless, in this experiment, we cannot establish a causal relationship between weed communities and crop yield, as weed sampling was conducted at the seedling stage and prior to post-emergence herbicide application. 4. Conclusions Our findings highlight the pivotal influence of climatic conditions in rainfed systems, where annual variations in rainfall ultimately determine crop yield. Farming practices should be carefully designed taking into account the environmental constraints. In the Iberian Peninsula rainfed systems, our results suggest the opportunity to reduce fertilization rates, without largely compromise crop yields, increasing farmers profitability. In addition, our findings suggest a potential disconnection between the impacts of tillage on crop yields and their effects on the diversity of weed communities. Conventional tillage has been observed to favor weed (functional) diversity while reducing their overall abundance. However, it has also been associated with lower wheat yields and the degradation of soil structure. In contrast, no-tillage practices, currently dependent on the use of a broad-spectrum herbicide, do not address the challenge of herbicide resistance and the agronomic and ecological problems caused by reducing the diversity of weed communities. A readily available alternative to bundle different agroecosystem services could be based on reduce fertilizer rates and perform minimum tillage (a reduced number of passes of non-inversion tillage). However, we would like to note that, in these rainfed systems, a sustainability objective—both economic and ecological—would be to achieve direct sowing (no-till) without the use of herbicides. We acknowledge that this is a research and technical gap, which could be turned into an opportunity for these systems. Declarations Acknowledgements We would like to thank Noelia Rodríguez and Andrés Bermejo who for managing routine measurements and high-quality assistance dedicated our experimental research site. Funding The research leading t these results received funding from the Spanish Ministry of Economy and Competitiveness funds (Project AGL2012-39929-C03-01). Conflicts of interest, the authors have no conflicts of interest to declare that are relevant to the content of this article. Availability of data and material, the datasets during and/or analysed during the current study available from the corresponding author on reasonable request. Autors’ contributions Conceptualization, M.R.A.V., A.M.S.A., and M.E.H.P.; Methodology, M.R.A.V., A.M.S.A., and M.E.H.P..; Investigation, L.N.M. and M.R.A.V.; Data Analysis, M.R.A.V., A.M.S.A., and M.E.H.P.; Writing – Original Draft, M.R.A.V; Writing –Review & Editing, A.M.S.A., and M.E.H.P.; Funding Acquisition, L.N.M.; Supervision, A.M.S.A., and M.E.H.P. References Adeux G, Vieren E, Carlesi S, Bàrberi P, Munnier-Jolain N, Cordeau S (2019) Mitigating crop yield losses through weed diversity. Nat Sustain 2:1018–1026. doi: 10.1038/s41893-019-0415-y Alarcón R, Hernández-Plaza E, Navarrete L, Sánchez MJ, Escudero A, Hernanz JL, Sánchez-Giron V, Sánchez AM (2018) Effects of no-tillage and non-inversion tillage on weed community diversity and crop yield over nine years in a Mediterranean cereal-legume cropland. 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Sci Rep 11:3344. doi: 10.1038/s41598-021-82375-1 Sun W, Canadell JG, Yu L, Zhang W, Smith P, Huang Y (2020) Climate drives global soil carbon sequestration and crop yield changes under conservation agriculture. Glob Change Biol. doi: 10.1111/gcb.15001 Tamburini G, Bommarco R, Wanger TC, Kremen C, van der Heijden MGA, Liebman M, Hallin S (2020) Agricultural diversification promotes multiple ecosystem services without compromising yield. Sci Adv 6:eaba1715. doi: 10.1126/sciadv.aba1715 Veresoglou SD, Chen J, Du X et al. (2023) No tillage outperforms conventional tillage under arid conditions and following fertilization. Soil Ecol Lett 5:137–141. doi: 10.1007/s42832-022-0145-3 Supplementary Files SUPPLEMENTARYMATERIAL.docx Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-8768054","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":592800994,"identity":"3e33eb6e-cdcc-49e8-8ced-3d359a48e73d","order_by":0,"name":"M Remedios Alarcón Víllora","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0003-0078-8363","institution":"","correspondingAuthor":true,"prefix":"","firstName":"M","middleName":"Remedios Alarcón","lastName":"Víllora","suffix":""},{"id":592800995,"identity":"22c6c3b5-7eee-4728-bba6-f0e8a1a8b7d5","order_by":1,"name":"Ana M Sánchez Álvarez","email":"","orcid":"https://orcid.org/0000-0002-6220-3001","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"M Sánchez","lastName":"Álvarez","suffix":""},{"id":592800996,"identity":"7b68342e-9a03-4427-a756-f2d37fc776fa","order_by":2,"name":"Luis Navarrete Martínez","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Luis","middleName":"Navarrete","lastName":"Martínez","suffix":""},{"id":592800997,"identity":"048edc98-2fb2-4e88-8b08-8dcff1059ac4","order_by":3,"name":"M Eva Hernández Plaza","email":"","orcid":"https://orcid.org/0000-0002-2378-2602","institution":"","correspondingAuthor":false,"prefix":"","firstName":"M","middleName":"Eva Hernández","lastName":"Plaza","suffix":""}],"badges":[],"createdAt":"2026-02-02 18:10:57","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8768054/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8768054/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103212378,"identity":"18258223-0622-4259-b1f9-9a5bd36986f9","added_by":"auto","created_at":"2026-02-23 08:53:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1659039,"visible":true,"origin":"","legend":"\u003cp\u003eThe tillage system usual in rainfed based cereal systems: A) inversion tillage using a molboard plow; B) vertical tillage using a chisel plow; C) no-tillage or direct seeding; D) Panorama of the experiment during the cereal season.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8768054/v1/6838f1ca6bdfb83556e4b732.png"},{"id":103212379,"identity":"0d1bebc9-b02c-44ad-a8c9-1f19e4ee2d9f","added_by":"auto","created_at":"2026-02-23 08:53:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":248893,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual model illustrating the relationships between agricultural practices, crop yield, and weed communities. This is the complete model, showing all the relationships considered. Agricultural practices specifically fertilization and tillage simultaneously influence both the structure of weed communities (red lines) and crop yield (brown lines). Crop yield has a reciprocal relationship with weed communities (green lines), and the different aspects of weed community structure are also interrelated (blue lines).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8768054/v1/7985c80f8e24f4203d4afd83.png"},{"id":103212382,"identity":"18bcfd6c-f0b9-44a8-b31b-3a7092769aeb","added_by":"auto","created_at":"2026-02-23 08:53:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":273741,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly precipitation (mm) and temperature (ºC) at the experimental site, represented in an ombrothermic diagram during the four growing seasons: A) 2012/2013 pea season, B) 2013/2014 wheat season, C) 2014/2015 vetch season and, D) wheat 2015/2016 season.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8768054/v1/f470b19af919b3d0e728a0a8.png"},{"id":103212381,"identity":"ca7f49f2-2d3a-470b-89f8-7548359f5dce","added_by":"auto","created_at":"2026-02-23 08:53:09","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":469714,"visible":true,"origin":"","legend":"\u003cp\u003ePiecewise-SEM model showing relationships between agricultural practices (tillage and fertilization), crop yield, weed diversity of individual functional traits (MPD of traits: seed weight; seed with covers; emergence time; growth habit, plant height, specific leaf area, SLA, weed abundance and weed species diversity in two wheat seasons. A) Season 2013/2014; B) 2015/2016. R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003em\u003c/sub\u003e\u0026nbsp;indicates the coefficient of marginal determination. The values on the arrows correspond to the standardized regression coefficients of significant relationships. *** p\u0026lt;0.001, **p\u0026lt;0.01, *p\u0026lt;0.05.\u0026nbsp; The dashed lines represent negative coefficients, and the solid lines represent positive coefficients.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8768054/v1/63cf8d3e51badfc3e4cc551d.png"},{"id":103212386,"identity":"ce590fdc-7166-4f6a-9e20-a2693ea85618","added_by":"auto","created_at":"2026-02-23 08:53:11","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":416130,"visible":true,"origin":"","legend":"\u003cp\u003ePiecewise-SEM model showing relationships between agricultural practices (tillage and fertilization), crop yield, weed diversity of individual functional traits (MPD of traits: seed weight; seed with covers; emergence time; growth habit, plant height, specific leaf area, SLA, weed abundance and weed species diversity in two legume crop seasons. A) Pea season 2012/2013; B) Vetch seson2014/2015. R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003em\u003c/sub\u003e\u0026nbsp;indicates the coefficient of marginal determination. The values on the arrows correspond to the standardized regression coefficients of significant relationships. *** p\u0026lt;0.001, **p\u0026lt;0.01, *p\u0026lt;0.05.\u0026nbsp; The dashed lines represent negative coefficients, and the solid lines represent positive coefficients.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8768054/v1/46e7e0bc123bb01ab0da5f50.png"},{"id":107484864,"identity":"7c751323-8aa1-4654-a883-4a39e37d8217","added_by":"auto","created_at":"2026-04-22 02:33:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3320035,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8768054/v1/5ab1436c-38f5-46be-a047-7a5d4ef016b6.pdf"},{"id":103212380,"identity":"a47837c5-4c4c-4ac8-8243-6c107613c2ba","added_by":"auto","created_at":"2026-02-23 08:53:09","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":109686,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPLEMENTARYMATERIAL.docx","url":"https://assets-eu.researchsquare.com/files/rs-8768054/v1/45e4b878ff11aac1b01f2c8e.docx"}],"financialInterests":"","formattedTitle":"Linkages between farming practices, crop yield and weed communities in rainfed Mediterranean agroecosystems","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAgroecosystems are closely driven by management practices that strongly influence nutrient cycles as well as biotic and abiotic interactions, ultimately affecting crop productivity and ecosystem sustainability. The technological developments of the 20th century supposed the abandonment of traditional practices and the adoption of novel managements especially in relation with tillage, pesticides and fertilizers, that lead in most geographical context to increasing crop yields. However, the intensification of management has also had negative effects on the agroecosystem services and on the farm\u0026rsquo;s biodiversity, leading to the homogenization of agricultural landscapes (Tamburini et al, 2020). However recent studies have shown that increase yields has not been always the rule, especially in marginal areas where abiotic restrictions related with climate, topography or soil conditions limits the ecosystem productivity and consequently crop yields. On top of that, climate change in these marginal areas is compromising farms sustainability or farmer\u0026rsquo;s profitability. To overcome these negative effects alternative management schemes, propose to focus on ensuring the simultaneously provision of various agroecosystem services (i.e., provisioning and regulating services; Bommarco et al., 2013). These proposals include the use and maintenance of agrobiodiversity, the reduction of disturbance from agricultural practices and the decrease in the dependence on external inputs (Tamburini et al., 2020). In the case of rainfed crops located on semiarid lands, which cover 80% of the world agricultural land area and provide large part of the main staple foods (FAOSTAT, 2023), these proposals should also take into account other environmental stressors. For example, in the Iberian Peninsula, rainfed cereal-based systems cover about 50% of the agricultural land and are characterized by a low soil organic matter content (Romany\u0026agrave; and Rovira, 2011), low rainfall and high inter-annual variability in the environmental conditions (Pe\u0026ntilde;a-Gallardo et al., 2019). These environmental factors challenge crop production and force to adapt farming practices to allow cultivation in these semiarid lands. Currently, two main practices that drive the functioning of these rainfed cereal systems are on debate: the tillage system and the amount of fertilization needed to assure crop yields. On the one hand, periods of water deficit reduce the availability of soil nutrients and the capacity of plants to uptake them (Guo et al., 2012), thereby questioning the effectiveness of increasing fertilization rates as the main strategy to increase crop yields. On the other hand, tillage was the default practice for managing weeds until the advent of herbicides, which opened the opportunity to no-tillage systems. While these systems have proven benefits for soil functionality, they remain highly dependent on broad- spectrum herbicides, which reduce weed diversity (Carmona et al., 2020). Weed communities that are (functionally) diverse have shown to exert a lower impact on crop production than those dominated by one or a few species (Adeux et al., 2019). Therefore, management recommendations should also consider the maintenance of weed diversity, not only because of its positive effect on yields relative to that produce by species poor weed communities, but also because many ecosystem services rely on weed diversity (MacLaren et al., 2020).\u003c/p\u003e \u003cp\u003eIn this study, we evaluate the most common tillage systems and crop fertilization in Mediterranean rainfed cereal-based systems, focusing on their effects on crop yield and weed communities. We hypothesize that a reduction in management intensity, achieved by reducing tillage intensity and fertilization rates, will maintain crop yields and support weed diversity without increasing weed abundance. To assess this hypothesis, we constructed a conceptual model illustrating the effects of three main tillage systems -moldboard (inversion) tillage, minimum tillage (non-inversion), and no-tillage with pre-sowing herbicide application- and two fertilization levels (full NPK vs. 50% reduction) on crop and weed communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe model considers the effect of tillage and fertilization on crop yield, as well as their effects on weed abundance and taxonomic and functional diversity. We also include the relationship among different aspects of weed communities as well as their relation to crop yield (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). To test this conceptual model, we use structural equation models (SEM) with data from a four-year long experiment under Mediterranean conditions, including years with contrasting rainfall patterns. The experiment consisted on a rotation of cereal and legume, the two main types of crops in these rainfed cereal-based systems. We fitted different models separately for each type of crop and year in order to identify the better practices in terms of both economic and environmental sustainability (Devkota et al., 2022).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003eThe study was carried out at the El Enc\u0026iacute;n Experimental Farm (40\u0026deg;31'N; 3\u0026deg;17'W, 610 m) in Alcal\u0026aacute; de Henares (Madrid, Spain) under a loamy Calcic Haploxeralf soil. Field seasons (September-June) are characterized by an average temperature of 12.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98 \u0026ordm;C and a precipitation of 408.2\u0026thinsp;\u0026plusmn;\u0026thinsp;97.56 mm (data from 1986\u0026ndash;2016 recorded at El Enc\u0026iacute;n weather station), with a marked dry period in summer in each of the four study seasons (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe tillage factor consisted of three levels (8 plots per level): Inversion tillage, commonly referred as mouldboard tillage (CT), minimum tillage (MT), and no-tillage (NT). Inversion tillage was performed using a moldboard plough working at a depth of 30 cm. In minimum tillage plots a chisel plough was used, working at a depth of 15 cm, without inverting the soil profile (vertical tillage). In both cases, a secondary vertical tillage was done with a cultivator at a depth of 15 cm after primary tillage. No-tillage implied direct sowing after the use of herbicide, glyphosate \u0026copy; (0.9 L a.i. ha-1) 4 to 6 days before sowing. Fertilization consisted of two levels (12 plots per level): full fertilization (FF), corresponding to the rate more frequently use in conventional farms in the region, and reduced fertilization (RF), which was 50% of the full rate. Fertilizer (N, P and K) was applied at the time of sowing in both cereal and legumes. In cereal a top-dressing nitrogen fertilisation was also applied. Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e(see supplementary material) shows the rates and fertilizers used in each crop and year. All crops were sown with a driller at a row spacing of 17 cm.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Weeds and crop yield sampling\u003c/h2\u003e \u003cp\u003eIn each crop season, we counted the number of individuals of each weed species in 10 quadrats of 0.1 m2 per plot. Sampling was carried out at the seedling stage of the weeds, coinciding with the beginning of tillering in cereals and stem elongation in legumes. The quadrats were arranged systematically in the plot in an M-shaped itinerary, always with a spacing of 2 m from the plot edge and 7 m between quadrats (for more details on sampling procedure, see Alarc\u0026oacute;n et al., 2018). Crop yield (grain weight) was determined at crop maturation stage. To do that, in cereals, three bands (1.40 m x 10 m) in each plot were harvested with a micro-harvester, whereas in legumes, crop was collected from 4 quadrats (0.25 m2) in each plot.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Weed Diversity Indices\u003c/h2\u003e \u003cp\u003eThe abundance of weed species in each plot was obtained as the sum of the individuals recorded in the 10 sampled quadrats. These data were used to calculate: i) the inverse Simpson index (1/D), as a species diversity metric, and; ii) mean pairwise distance (MPD) as a functional diversity index (Clarke and Warkwick, 1998). MPD explains the average distance between pairs of species randomly selected from an assemblage without replacement. MPD was computed independently for six functional traits. Specific leaf area (SLA), plant height at maturity, and growth habit (creepy, erect, rosulate) were considered resource acquisition traits. Additionally, seed weight, emergence time (indicated by month of emergence), and seed cover (present or not) were considered regenerative traits. SLA, plant height and seed weight values were measured following standardized protocols as described in Alarc\u0026oacute;n et al. (2019), whereas trait values of growth habit, emergence time and seed cover, were retrieved from literature (Supplementary material Table S2). We included 176 values representing the 6 traits in the 30 species. Only four data were missing (2.2%). Diversity metrics were calculated using the vegan package (Oksanen et al., 2020) and the \u0026ldquo;melodic\u0026rdquo; function of picante package (De Bello et al. 2016) in R (R Development Core Team, 2020).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Statistical analysis\u003c/h2\u003e \u003cp\u003eTo evaluate our conceptual model (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), we used Structural Equation Modelling. SEM is a technique that allows the analysis of direct and indirect effects of multiple interacting factors, permitting the identification of the correlations, and their causality, among variables. We fit the SEM models using the piecewise method (local estimation), in the piecewiseSEM package (Lefcheck, 2016) in R. This method is an alternative approach to variance-covariance-based SEM, which allows for a low number of observations and does not assume a multinormal distribution. The overall fit of each SEM model was evaluated with d-generalized separation test based on Fisher's C statistics (Shipley, 2009). The trend and magnitude of the relationship between the variables were obtained from the standardized regression coefficients, considering their significance with a p-value less than 0.05.\u003c/p\u003e \u003cp\u003eTo test the consistency of results in different crops and at distinct environmental conditions, we constructed four SEM models (two type of crops and two years). In each model, the relationships were specified using general linear mixed effects models (nlme package; Pinheiro et al., 2020). The tillage system was coded considering a gradient of disturbance from no-tillage (NT\u0026thinsp;=\u0026thinsp;0) to conventional tillage with soil inversion (CT\u0026thinsp;=\u0026thinsp;2), being the intermediate disturbance level the minimum tillage (MT\u0026thinsp;=\u0026thinsp;1). Thus, high values of the tillage factor reflect a higher soil disturbance level. Reduced fertilization was coded as 1 and full fertilization as 2. Weed abundance was transformed using natural logarithms. Block was considered a random effect in all cases. The marginal coefficient of determination (Nakagawa et al., 2013), expressing the variance explained by the fixed factors, was also calculated for each of the individual equations.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cp\u003eOur data show the pivotal role of tillage system and annual climate conditions on both crop yields and weed communities. On the contrary, soil fertilization, did not show an effect on the studied rainfed systems. Data also highlight the intricate relationship between, abundance, diversity and functional structure of weed communities.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Reducing tillage intensity and fertilizer rates do not affect cereal and legume yields\u003c/h2\u003e \u003cp\u003eA reduction in the intensity of management practices\u0026mdash;specifically fertilization and tillage\u0026mdash;did not negatively impact crop yields. Wheat yield was negatively correlated with fertilizer application rates (standardized regression coefficients of -0.24 and \u0026minus;\u0026thinsp;0.32 in 2013/2014 and 2015/2016 respectively; (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Supplementary Material Table S3 and Table S4). In contrast, fertilization had no significant effect on legume crop yields (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Supplementary Material Table S5 and Table S6).\u003c/p\u003e \u003cp\u003eOur results align with previous studies that have identified a small or no effect of fertilization on crop yield on water-limited contexts (Cantero-Mart\u0026iacute;nez et al., 2016). In this case, spring precipitation (March\u0026ndash;May) during the four experimental growing seasons ranged from 50 to 230 mm, while total seasonal precipitation remained below 400 mm (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and supplementary material Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), which is considered the threshold for efficient nutrient use in Mediterranean cropping systems (L\u0026oacute;pez-Bellido et al., 1998). Accordingly, our results suggest the potential for reducing the fertilizer rate (up to 50% in this study) without compromising cereal and legume crop yields. Moreover, given the inherent variability of Mediterranean rainfall patterns, soil fertility management should be oriented towards strengthening soil functionality and properties, rather than focusing solely on nutrient supply (Sun et al., 2020). In addition, reducing fertilizer rates may prevent nutrient accumulation in the soil, which could otherwise disrupt soil functioning through declines in microbial activity and diversity (Sradnick et al., 2013). Further, from an economic perspective, the reduction in fertilizer rates can enhance farmer\u0026rsquo;s profitability in these rainfed systems.\u003c/p\u003e \u003cp\u003eReducing tillage intensity also had a positive effect on wheat yields in both seasons (standardized regression coefficients values of -0.73 and \u0026minus;\u0026thinsp;0.87, respectively; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and supplementary material Table S3 and Table S4). The effect of different tillage systems on crop yields is still debated, making it challenging to provide a definitive recommendation. Previous works (Devkota et al., 2022; Su et al., 2021; Veresoglou et al., 2022) have shown that reduced-tillage systems (MT or NT) performed better than CT under water limited environments when crops are rotated and residues are not removed, which corresponds to the conditions of our experiment. Wheat results in our study support these conclusions. However, the effect of the tillage system in the legume crops showed a contrasting response (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and supplementary material Table S5 and Table S6). CT improved crop performance in the first season (2012\u0026thinsp;\u0026minus;\u0026thinsp;203; standardized regression coefficients value of 0.49), with no significant differences observed in the second. These results suggest that legumes may be particularly vulnerable to additional yield-limiting factors under no-tillage (Arvidsson and H\u0026aring;kansson, 2014), including soil compaction which could be more severe under a drier winter (as in 2014/2015 season, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In line with this, Mu\u0026ntilde;oz-Romero et al. (2012) found that under dry conditions, CT promoted deeper root development compared to NT, which may explain improved water uptake and the higher yields observed under CT. Legume yields in the second season were practically negligible due to particularly harsh conditions (the water deficit was evident from January, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC), and in this case, the choice of tillage system had little effect (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). These findings highlight the importance of adopting a flexible agronomic management strategy that alternates between no-till and reduced tillage practices, tailored to the specific requirements of each crop within the rotation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e3.2. Weed communities responded to the intensity of tillage but not to a reduction in the fertilizer rates\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe reduction in the fertilizer rate did not have an effect on the abundance or the diversity of weed communities. In contrast, reducing the intensity of tillage led to weed communities of higher abundance, lower species diversity and lower diversity of regenerative traits, but higher of resource acquisition traits (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and supplementary material, Tables S3, S4, S5 and S6). This may be explained by differences in how the three tillage systems distribute weed seeds throughout soil layers (Spokas et al., 2007). The absence of soil disturbance in NT determines that most of the seeds remain at the soil surface which benefits those species whose germination occurs promptly when conditions are optimal. This mostly refers to species with specific regenerative attributes: an early emergence time and lack of any seed coverings that may inhibit germination (e.g., pericarp). In contrast, soil inversion in CT systems allow a distribution of weeds seeds throughout all the soil profile disturbed by the mouldboard (Chauhan et al. 2006; Spokas et al. 2007). In this case, more diverse regenerative strategies are allowed to persist. In example, not only the seeds left in the surface, but those buried in the first centimeters, and with high seed weight, may have an opportunity to emerge. MT involves an intermediate situation, with more seeds located in the upper soil layers, but with some seeds buried on the first centimeters.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Tillage systems influence the relationships among various aspects of weed communities\u003c/h2\u003e \u003cp\u003eIn wheat seasons, the model illustrates intricate interactions among the different facets of weed communities, including abundance, species diversity, and functional diversity, which are further influenced by tillage practices. Specifically, weed abundance was negatively related to weed diversity in both seasons (standardized regression coefficients value\u0026thinsp;\u0026minus;\u0026thinsp;0.51 and \u0026minus;\u0026thinsp;0.69, first and second season respectively Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and supplementary material Tables S3 and S4). In addition, the MPD of SLA and plant height were positively related to abundance (standardized regression coefficients value 0.47 and 0.35 both seasons) and negatively related to diversity (standardized regression coefficients value\u0026thinsp;\u0026minus;\u0026thinsp;0.86 and \u0026minus;\u0026thinsp;0.59 both seasons), whereas the opposite pattern was found for the MPD of seed cover related to weed abundance (standardized regression coefficients value\u0026thinsp;\u0026minus;\u0026thinsp;0.50 and \u0026minus;\u0026thinsp;0.67 both seasons). Overall, communities with high abundance and low species diversity were characterized by higher functional diversity of resource acquisition traits but lower functional diversity of regenerative traits. These relationships cannot be understood without considering the effect of tillage systems on weed communities, since abundant and less diverse communities were associated with reduced tillage intensity, as reported above. This is further supported by the positive covariation between crop yield and weed abundance in the second wheat year (standardized regression coefficients value 0.60), where crop yield is higher as the intensity of tillage reduces. Nonetheless, in this experiment, we cannot establish a causal relationship between weed communities and crop yield, as weed sampling was conducted at the seedling stage and prior to post-emergence herbicide application.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eOur findings highlight the pivotal influence of climatic conditions in rainfed systems, where annual variations in rainfall ultimately determine crop yield. Farming practices should be carefully designed taking into account the environmental constraints. In the Iberian Peninsula rainfed systems, our results suggest the opportunity to reduce fertilization rates, without largely compromise crop yields, increasing farmers profitability. In addition, our findings suggest a potential disconnection between the impacts of tillage on crop yields and their effects on the diversity of weed communities. Conventional tillage has been observed to favor weed (functional) diversity while reducing their overall abundance. However, it has also been associated with lower wheat yields and the degradation of soil structure. In contrast, no-tillage practices, currently dependent on the use of a broad-spectrum herbicide, do not address the challenge of herbicide resistance and the agronomic and ecological problems caused by reducing the diversity of weed communities. A readily available alternative to bundle different agroecosystem services could be based on reduce fertilizer rates and perform minimum tillage (a reduced number of passes of non-inversion tillage). However, we would like to note that, in these rainfed systems, a sustainability objective\u0026mdash;both economic and ecological\u0026mdash;would be to achieve direct sowing (no-till) without the use of herbicides. We acknowledge that this is a research and technical gap, which could be turned into an opportunity for these systems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003eWe would like to thank Noelia Rodr\u0026iacute;guez and Andr\u0026eacute;s Bermejo who for managing routine measurements and high-quality assistance dedicated our experimental research site.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThe research leading t these results received funding from the Spanish Ministry of Economy and Competitiveness funds (Project AGL2012-39929-C03-01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest,\u0026nbsp;\u003c/strong\u003ethe authors have no conflicts of interest to declare that are relevant to the content of this article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material,\u0026nbsp;\u003c/strong\u003ethe datasets during and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAutors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003eConceptualization, M.R.A.V., A.M.S.A., and M.E.H.P.; Methodology, M.R.A.V., A.M.S.A., and M.E.H.P..; Investigation, L.N.M. and M.R.A.V.; Data Analysis, M.R.A.V., A.M.S.A., and M.E.H.P.; Writing \u0026ndash; Original Draft, M.R.A.V; Writing \u0026ndash;Review \u0026amp; Editing, A.M.S.A., and M.E.H.P.; Funding Acquisition, L.N.M.; Supervision, A.M.S.A., and M.E.H.P.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdeux G, Vieren E, Carlesi S, B\u0026agrave;rberi P, Munnier-Jolain N, Cordeau S (2019) Mitigating crop yield losses through weed diversity. 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Glob Change Biol. doi: 10.1111/gcb.15001\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTamburini G, Bommarco R, Wanger TC, Kremen C, van der Heijden MGA, Liebman M, Hallin S (2020) Agricultural diversification promotes multiple ecosystem services without compromising yield. Sci Adv 6:eaba1715. doi: 10.1126/sciadv.aba1715\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVeresoglou SD, Chen J, Du X et al. (2023) No tillage outperforms conventional tillage under arid conditions and following fertilization. Soil Ecol Lett 5:137\u0026ndash;141. doi: 10.1007/s42832-022-0145-3\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"agroecosystems, cereal-legume rotation, ecosystem services, fertilization, functional diversity, Mediterranean annual crops, piecewise-SEM, tillage system, weed abundance, crop yield","lastPublishedDoi":"10.21203/rs.3.rs-8768054/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8768054/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFor rainfed cropping systems in semiarid regions to be sustainable, they should provide multiple agroecosystem services simultaneously while accounting for the environmental constraints inherent to these areas. Achieving this may require a reevaluation of the main farming practices, including the choice of tillage system and fertilization rates. In this study, we present, for the first time, an integrative evaluation of these practices that considers crop performance, weed management, and the conservation of weed community diversity.\u003c/p\u003e \u003cp\u003eOver four crop seasons in a cereal\u0026ndash;legume rotation, we compared the effect of three tillage systems (conventional, minimum, and no-till) and two fertilization rates (full NPK vs. 50% reduction) on crop yield, weed abundance, and weed diversity -both species diversity (inverse Simpson index) and functional diversity (mean pairwise distance of six traits; MPD)- using Structural Equation Modelling.\u003c/p\u003e \u003cp\u003eThe effects of fertilization and of the choice of tillage system were more pronounced on cereal than on legume crops. In cereals, reduced fertilization rates and lower tillage intensity increased yields, consistent with previous studies on crop performance under water-limited conditions. Weed abundance and trait composition were more responsive to tillage than to fertilization: reducing tillage increased abundance and the diversity of resource acquisition traits but decreased species diversity and the diversity of regenerative strategies. These findings show the potential of reducing fertilization rates without compromising crop yields, enhancing farmer\u0026rsquo;s profitability and sustainability. Further, our results reveal a disconnection between tillage effects on crop yield and on weed management and diversity, each of which is better achieved by no-till or by conventional systems. Minimum tillage could be a ready-to-use strategy to combine both goals, but we acknowledge that a research and technical gap exists to maximize crop yield, weed management and soil structure maintenance in these systems.\u003c/p\u003e","manuscriptTitle":"Linkages between farming practices, crop yield and weed communities in rainfed Mediterranean agroecosystems","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-23 08:53:01","doi":"10.21203/rs.3.rs-8768054/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4b2609df-5908-46a5-9ea8-a4df455ef378","owner":[],"postedDate":"February 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-20T15:14:27+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-23 08:53:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8768054","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8768054","identity":"rs-8768054","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}