Elemental homeostasis and soil microbiota of forage grasses under drought and irrigation

Elemental homeostasis and soil microbiota of forage grasses under drought and irrigation | 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 Elemental homeostasis and soil microbiota of forage grasses under drought and irrigation Cíntia Cármen Faria Melo, Danilo Silva Amaral, Carlos Henrique Barbosa Santos, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8844252/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Aims Perennial forage systems in tropical regions are predominantly rainfed; however, increasing drought frequency associated with climate change has accelerated the adoption of irrigation. Selecting forage species capable of maintaining elemental balance and favorable plant-soil interactions is essential to sustain productivity. This study evaluated the drought tolerance of Mavuno and Zuri grasses under tropical field conditions, focusing on their responses to subsurface drip irrigation, plant carbon (C), nitrogen (N) and phosphorus (P) stoichiometry, and soil microbial dynamics. Methods A field experiment was conducted under rainfed and irrigated conditions, assessing forage biomass production, plant water status, leaf C, N, and P concentrations, and indicators of soil microbial activity and composition in rhizosphere and non-rhizosphere compartments. Results Under rainfed conditions, both grasses exhibited reductions in biomass production; however, Mavuno maintained greater elemental homeostasis and higher soil microbial activity, suggesting greater tolerance to seasonal water deficit. Irrigation restored plant water status, improved C:N:P ratios, and increased the abundance of key microbial groups, including sporulating bacteria, yeasts, and actinomycetes. Forage yield increased by approximately 10 Mg ha⁻¹ of dry matter under irrigation for both species. Under irrigated conditions, Zuri grass was associated with higher microbial biomass C and total soil organic C, indicating enhanced soil C inputs. Conclusion These findings demonstrate species-specific responses to water availability and show that irrigation modulates plant nutrient stoichiometry and soil microbial processes. The choice of forage species with stable elemental composition and favorable plant-soil interactions plays a key role in sustaining productivity. forage grasses soil microbiota C:N:P stoichiometry subsurface drip irrigation water deficit Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Tropical forage grasses from different species are widely cultivated in pastures to enhance livestock production efficiency (Nehring, 2024 ). However, seasonal drought in tropical regions with dry winters limits forage availability, concentrating production during the rainy season (Tulu et al., 2023 ; Santos et al., 2024 ). Beyond reducing yield, water deficits also alter soil microbial communities in pastures, with plant species influencing these interactions, as observed for forage legumes (Moreno et al., 2021 ; Dollete et al., 2024). While grass cultivation generally enhances soil microbial abundance (Momesso et al., 2022 ), the effects of different tropical forage grass species on soil microbiota under drought conditions, and how these microbial communities contribute to elemental homeostasis, remain underexplored under field conditions. Drought stress impacts plants by reducing leaf water potential and transpiration rates (Mganga et al., 2023 ) and by altering nutrient accumulation and the stoichiometric balance of carbon (C), nitrogen (N), and phosphorus (P) in leaf tissues (Olivera-Viciedo et al., 2024 ). Maintenance of C:N:P homeostasis optimizes nutrient conversion into dry matter (DM), yet abiotic stresses can disrupt this balance in grasses, impairing metabolism and potentially limiting the availability of organic substrates for soil microorganisms (Oliveira Filho et al., 2021 ; Melo et al., 2023 ; Pereira et al., 2021 ). Despite its importance for understanding biomass production under stress, the interaction between soil water availability and elemental stoichiometry has received limited attention in pastures. Additionally, microbial activity and biomass are sensitive indicators of environmental and management impacts on soil, which may in turn influence plant nutritional balance (Silva et al., 2024 ). Irrigation systems combined with fertilization are widely used to mitigate the negative effects of drought on forage production (Jesus et al., 2021 ). Subsurface drip irrigation is increasingly recommended due to its efficiency in reducing water loss by evaporation and surface runoff compared to sprinkler systems, although implementation costs are higher (Allen and MacAdam, 2020 ; Rocha et al., 2024 ; Cahn and Hutmacher, 2024 ). Irrigation not only alleviates water stress but also affects the biomass and activity of soil microbial groups (Gong et al., 2015 ; Fu et al., 2021 ). Since soil organic matter (SOM) accumulation is influenced by root deposition and microbial activity (Frene et al., 2022 ), irrigation may also modify soil C dynamics in well-managed pastures (Li et al., 2024 ). Understanding how different forage grass species influence soil microbiota and elemental homeostasis under drought and irrigation is therefore crucial. Based on these considerations, we tested the following hypotheses: i) Water availability influences soil microbial communities, elemental homeostasis (C:N:P), and forage biomass production in tropical grasses; ii) Forage grass species induce differences in soil microbial biomass, activity, composition, and elemental homeostasis under dryland and subsurface drip irrigation conditions. The objective of this study was to investigate how two tropical forage grass species interact with soil microbial communities and influence elemental homeostasis under drought and subsurface drip irrigation, and how these responses relate to biomass production. By focusing on mechanistic links between soil microbiota and plant nutritional balance, this study provides insight into short-term adaptations of tropical forage grasses to water availability under field conditions. Material and methods Experimental Conditions A field experiment was conducted at the experimental site of São Paulo State University (UNESP), in Jaboticabal, Brazil (21°14′54″ S, 48°17′06″ W; 560 m elevation). The region has a tropical wet climate with a dry winter (Aw, Köppen classification). The study was carried out from April to October 2023, encompassing the dry season, which in the region coincides with autumn, winter, and the beginning of spring, characterized by low (sporadic) or absent rainfall, leading to a progressive decrease in soil moisture. Meteorological data, including evapotranspiration, air temperature, global solar radiation, and rainfall, were recorded at the university’s weather station (Fig. 1 a, b). The soil was classified as Oxisol (Soil Survey Staff, 2022 ). It was sampled for initial chemical analysis (Raij et al., 2001 ), yielding the following results for the 0–20 and 20–40 cm soil layers, respectively: pH = 5.8 and 6.0, organic matter (SOM) = 22 and 22 g dm − 3 , phosphorus (P) = 78 and 51 mg dm − 3 , potassium (K) = 5.5 and 3.6, calcium (Ca) = 46 and 44, magnesium (Mg) = 15 and 15 mmol c dm − 3 , sulfur (S) = 3 and 4, boron (B) = 0.32 and 0.25, copper (Cu) = 3.4 and 3.5, iron (Fe) = 6 and 5, manganese (Mn) = 25.5 and 18.6, zinc (Zn) = 1.6 and 1.0 mg dm − 3 , H + Al = 21 and 18 mmolc dm − 3 , cation exchange capacity (CEC) = 88 and 81 mmol c dm − 3, base saturation (V = Ca + Mg + K/CEC) = 76 and 77%. Experimental design and management The experiment followed a 2 × 2 factorial design comprising two tropical forage grass species U. brizantha × U. ruziziensis cv. Mavuno and M. maximus cv. Zuri, grown under two water management conditions: dryland or irrigated. Treatments were arranged in a randomized block design with four replicates. In the irrigated treatments, a subsurface drip irrigation system was installed in April 2022 following soil preparation by harrowing. Drip lines were buried at a depth of 20 cm (Rocha et al., 2024 ) and spaced 80 cm apart. Emitters had a nominal discharge of 1.45 L h⁻¹ at 100 kPa and were positioned at 30 cm intervals. Preliminary testing confirmed uniform water distribution (Bernardo et al., 2009 ). Experimental plots measured 3 × 4.8 m. Forage grasses were sown manually at a rate of 10 kg ha⁻¹ of pure viable seed, distributed evenly across the soil surface. The forage grass seeds were donated by the commercial supplier WolfSeeds. After seedling emergence, a uniformity cut was performed to stimulate tillering using a brush cutter (Husqvarna 31R/330-2), and the removed biomass was discarded. Sprinkler irrigation was applied during the establishment phase to ensure uniform germination and pasture development. In April 2023, once the pasture was fully established, plots were standardized with a maintenance cut, leaving a residual height of 15 cm for Mavuno and 30 cm for Zuri (Barbosa et al., 2021 ; Silva et al., 2020 ). Water treatments were then implemented: either rainfed (no irrigation) or irrigated with subsurface drip. For irrigated plots, irrigation depth and frequency were calculated to fully replenish crop evapotranspiration, with a maximum allowable soil water deficit of 22 mm. This was based on the soil's water holding capacity (120 mm in the 0–40 cm layer), as determined from the soil water retention curve (Klute, 1986 ). Given that initial soil fertility was adequate for grass production, only maintenance fertilization was conducted after each cut. Nutrient replacement rates for N, P, K, and S were based on the quantities exported by the forage biomass under each treatment (Dubeux Jr. et al., 2007; Quaggio et al., 2022 ). Fertilizer sources included urea, potassium chloride, ammonium sulfate, and purified monoammonium phosphate (for fertigation), while simple superphosphate was used under rainfed conditions. Fertilizers were applied through fertigation in irrigated plots and broadcast manually in rainfed plots. Variables analyzed Forage sampling and data collection Data were collected between May 9 and October 2, 2023. Pasture cuts and biomass sampling were performed when grasses under optimal water supply (irrigated plots) reached the recommended pre-grazing heights: 85 cm for Zuri guineagrass and 35 cm for Mavuno grass (Barbosa et al., 2021 ; Silva et al., 2020 ). Plant height (cm) was recorded immediately prior to cutting at five points per plot using a graduated pasture ruler. Based on this criterion, five harvests were conducted in irrigated plots, whereas only one harvest was possible under rainfed conditions due to limited growth. Sixteen forage samples were collected per harvest cycle, resulting in a total of 96 forage samples over the experimental period. To assess dry matter (DM) yield, forage was harvested between 7 and 9 a.m. using a sickle, leaving a post-harvest residue height of 35 cm for Zuri and 15 cm for Mavuno. Forage was collected within metal quadrats of 2.25 m² for Zuri and 1.0 m² for Mavuno, placed within each plot. Fresh biomass was weighed immediately, and a subsample (~ 100 g) was oven-dried at 65 ± 5°C for 72 hours in a forced-air oven to determine DM yield (Mg ha⁻¹). After each cut, tiller density (tillers m⁻²) was estimated by counting both live and dead tillers within a 635 cm² frame (Bahmani et al. 2003 ). Forage mass density (kg ha⁻¹ cm⁻¹ DM) was then calculated by dividing the DM yield by pasture height. Volumetric soil water content Volumetric soil water content (VWC, cm³ cm⁻³) was measured at the peak of the dry season in September 2023 using Time Domain Reflectometry (TDR) with a portable soil moisture sensor (HydroSense II, 20 cm rods). Measurements were taken at three locations per plot. Sensor accuracy was confirmed by calibration against gravimetric soil moisture at the same sampling points, yielding an R² of 0.84 (y = 1.0294x – 3.2562) and a standard deviation of 1% (Gonzalez-Porras et al., 2024 ). Leaf water potential and relative water content Leaf water potential (Ψw, MPa) was measured between 3 and 5 a.m. in September using a Scholander pressure chamber (Model 3000F01, Soil Moisture Equipment). Measurements were taken from the middle third of the most recently expanded leaf (ligule fully emerged) by gradually increasing chamber pressure until sap exudation from the leaf midrib was observed (Turner, 1981 ). Relative water content (RWC, %) was determined from ten leaf discs (129 mm² each) collected from the same leaf. Fresh mass (FM) was recorded immediately, followed by 6 hours of rehydration in deionized water to obtain turgid mass (TM). Discs were then oven-dried at 80°C for 24 hours to determine dry mass (DM). RWC was calculated as: RWC = [(FM – DM) / (TM – DM)] × 100 (Barrs and Weatherley, 1962 ). Elemental stoichiometry in leaf of forage grasses To evaluate the C:N, C:P, N:P, and C:Si stoichiometric ratios in forage biomass, concentrations of C (C), nitrogen (N), phosphorus (P), and silicon (Si) in dry matter (DM) were first determined. For irrigated treatments, samples were pooled and homogenized from all collection dates. For rainfed treatments, a subsample was taken from the single cut, as described in Section 2.3.1. Nitrogen content was determined by the Kjeldahl method with titration following sulfuric acid digestion (Bataglia et al., 1983 ). C content was assessed via oxidation with potassium dichromate in sulfuric acid and titration with ammonium ferrous sulfate (Tedesco et al., 1995 ). Phosphorus was determined after nitric-perchloric digestion, followed by a colorimetric reaction with a metavanadate-molybdate reagent, and absorbance was measured at 420 nm using a spectrophotometer (Malavolta et al., 1997 ). For Si, alkaline digestion was carried out with hydrogen peroxide at 120°C, followed by a colorimetric reaction with ammonium molybdate and absorbance reading at 410 nm (Kraska and Breitenbeck, 2010 ). Elemental concentrations in DM were expressed in g kg⁻¹, and the respective stoichiometric ratios were then calculated. Microbiological and soil organic carbon analyses Soil samples were collected from the 0–10 cm layer in each plot in October 2023, at the end of the experimental period. A rooted soil clod was excavated using a hoe, and the loosely adhering soil was carefully removed. Rhizosphere soil was defined as the soil that remained attached to the root surface and was gently collected into a plastic tray. Non-rhizosphere soil was sampled from the original location of the excavated clod after root removal. In total, 32 samples were collected, comprising 16 rhizosphere and 16 non-rhizosphere soil samples. All samples were transferred to paper bags for transport, then sieved through a 2 mm mesh, placed into plastic bags, and stored at 4°C until analysis (Silva et al., 2007a ). Microbial biomass carbon (SMB-C) Microbial biomass C (SMB-C) was quantified using the fumigation-extraction method with 0.5 mol L⁻¹ potassium sulfate (K₂SO₄) as the extractant. Extracted organic carbon was oxidized with potassium dichromate (K₂Cr₂O₇) in acidic medium and quantified by titration with ammonium ferrous sulfate. SMB-C was calculated using the equation: SMB-C = FC x kc − 1 , where SMB-C is microbial C in mg kg − 1 soil; FC is the flux from the difference between the fumigated and non-fumigated samples, and kc is the correction factor (0.33) (Silva et al., 2007b ). Soil basal respiration (SBR) was measured using two soil subsamples: one for gravimetric moisture determination and another for CO₂ evolution (Jenkinson and Powlson, 1976 ; Silva et al., 2007a ). Approximately 50 g of moist soil was placed into a 100 mL glass jar, which was enclosed in a 2 L hermetically sealed glass container along with a second jar containing 10 mL of 1 mol L⁻¹ NaOH solution. Incubation was carried out in the dark at ambient temperature (25–28°C) for seven days. After incubation, 2 mL of 10% (w/v) barium chloride (BaCl₂) solution was added to the NaOH to precipitate CO₂. The remaining NaOH was titrated with standardized 0.5 mol L⁻¹ HCl using 1% phenolphthalein as an indicator. SBR was calculated using the equation: SBR (mg kg − 1 h − 1 ) = (((V b - V a ) x M x 6 x 1000) / Ps) / T, where: SBR = mg C-CO 2 released by microbial respiration per kg of soil per hour; V b (mL) = volume of acid used in the titration of the control (blank) solution; V a (mL) = volume used in the titration of the sample; M = exact molarity of the HCl solution; Ps (g) = mass of dry soil, and T = incubation time of the sample in hours. Metabolic quotient (qCO 2 ) was calculated using the equation: qCO 2 (mg g − 1 h − 1 ) = SBR / (SMB-C x 10 − 3 ), where qCO 2 is the metabolic quotient in mg of C-CO 2 per gram of SMB-C per hour, SBR is the basal soil respiration, and SMB-C is the microbial biomass C (Anderson and Domsch, 1993 ; Silva et al., 2007b ). Microbial population Microbial populations were quantified for sporulating bacteria, yeasts, actinomycetes, and phosphorus-solubilizing microorganisms in both rhizosphere and non-rhizosphere soils. For microbial enumeration, 10 g of soil were added to 95 mL Erlenmeyer flasks containing sterile 0.1% sodium pyrophosphate buffer. The flasks were incubated for 30 minutes at 200 rpm and 28°C to facilitate disaggregation of soil particles. Serial dilutions were prepared by transferring 1 mL of the suspension to test tubes containing 9 mL of the same buffer, continuing until suitable dilutions were obtained for plate counts (30–300 colony-forming units CFU per plate). Aliquots of 100 µL (0.1 mL) from each dilution were plated onto selective media specific to each microbial group and incubated at 28 ± 2°C. The CFU were counted after 72 h for sporulating bacteria and after 120–168 h for yeasts, actinomycetes, and phosphorus-solubilizing microorganisms. The culture media used were nutrient agar for sporulating bacteria, yeast–malt agar supplemented with antibiotics for yeasts, starch-casein agar for actinomycetes, and GES medium (glucose, soil extract, and inorganic salts) for phosphorus-solubilizing microorganisms (Vieira and Nahas, 2005 ). Total Organic Carbon in Soil It was determined by using 1 g of sample (non-rhizosphere soil) and oxidizing it through wet digestion with a potassium dichromate and sulfuric acid mixture. The dichromate solution was added in excess, so that during the reaction, part of the Cr was reduced, while another part remained in its oxidized form. The remaining reagent in the oxidized form was measured by titration with an ammonium ferrous sulfate solution. From the amount added and the excess reagent after the reaction, the amount of Cr that oxidized C was determined. This allowed for the calculation of the soil C content (g kg − 1 ). The procedure followed is based on the Walkley and Black method, as described by Raij et al. ( 2001 ). Statistical Analysis An analysis of data normality assumptions, homogeneity of variances, and independence of residuals was performed (Bartlett, 1937 ; Jarque and Bera, 1980 ), followed by analysis of variance (F-test, p < 0.05). For significant F, means were compared using Tukey test (p < 0.05) with SPEED Stat software version 3.4 (Carvalho et al., 2020 ). A Pearson correlation network among the variables was established, and principal component analysis was conducted based on the covariance matrix, overlapped by hierarchical clustering analysis using Euclidean distance and a cluster analysis by the single linkage method (Carvalho, 2024 ). All analyses were performed using R Studio version 4.3.3. Results Soil and plant water content, and elemental stoichiometry The results (Fig. 2 a-h) showed an interaction effect between water conditions and forage species (p < 0.05) for leaf water potential (Fig. 2 d) and for the C:P and N:P stoichiometric ratios in the biomass of the grazed stratum (Fig. 2 f, g). Irrigated cultivation, in comparison to dryland conditions, increased the VWC, which was reflected in higher RWC and increased Ψw for both Mavuno (87%) and Zuri (92%). Under dryland conditions, Zuri exhibited lower Ψw than Mavuno, whereas no differences were observed between the species under irrigation. The irrigation increased VWC compared to dryland conditions (Fig. 2 a, d). Zuri grass had a higher organic C content than Mavuno, regardless of water regime, with differences of + 10% under dryland and + 6% under irrigation. Irrigation increased soil organic C content compared to dryland conditions, independent of species (Fig. 2 b). Mavuno grass showed higher C:P, N:P, and C:Si ratios than Zuri grass, irrespective of irrigation (Fig. 2 f, g, h). Biomass and microbial activity in the soil Interaction effects were observed between water regimes and forage species (p < 0.05) for the variables SMBC and qCO 2 in both rhizosphereric and non-rhizospheric soils, and for SBR in non-rhizospheric soil, while SBR in rhizosphere soil did not show a significant interaction (Fig. 3 a-f). Interaction effects between water regimes and forage species (p < 0.05) were observed for SMBC and qCO2 in both rhizosphere and non-rhizosphere soils, and for SBR in non-rhizosphere soil, while SBR in rhizosphere soil did not show a significant interaction (Fig. 3 a-f). Irrigation increased SMBC in Mavuno grass (49% in rhizosphere soil) and Zuri grass (124% in rhizosphere soil and 21% in non-rhizosphere soil) (Fig. 3 a, d). In rhizosphere soil, irrigation increased SBR compared to dryland conditions, independent of species (Fig. 3 b). In non-rhizosphere soil, irrigation increased SBR under both forage species (Fig. 3 e). For qCO 2 , irrigation reduced its value in Zuri grass, both in rhizosphere (-65%) and non-rhizosphere (-52%) soils (Fig. 3 c, f). Differences between species under dryland conditions were observed for SBR in non-rhizospheric soil, with Mavuno grass exhibiting higher values than Zuri (Fig. 3 e). In irrigated pastures, Zuri grass showed higher SMBC in both rhizospheric (36%) and non-rhizospheric (27%) soils, while SBR in rhizospheric soil was reduced under irrigation compared to dryland, independent of species (Fig. 3 a, b, d, e). In the rhizosphere, qCO 2 was lower in Zuri grass compared to Mavuno (-52%) under irrigation (Fig. 3 c, f). Microbial community in soil The interaction between water regime and forage species was significant (p < 0.05) for most microbial groups analyzed, including total bacteria (SBac) and phosphate-solubilizing microorganisms (P-solub) in both rhizosphere and non-rhizospheric soils, as well as actinomycetes in non-rhizospheric soil (Fig. 4 a-h). Compared to dryland conditions, irrigation increased SBac counts in the rhizosphere soil of Zuri grass (+ 424%) and in the non-rhizospheric soil of Mavuno grass (+ 30%), while reducing SBac counts in the non-rhizospheric soil of Zuri grass (− 51%) (Fig. 4 a, e). Irrigation also increased yeast counts in non-rhizospheric soil cultivated with Mavuno (+ 35%) and Zuri grass (+ 41%), whereas no irrigation effect was observed in rhizospheric soil (Fig. 4 b, f). In non-rhizosphere soil, actinomycete counts increased by 71% under irrigation in Mavuno grass compared to dryland conditions (Fig. 4 c, g). Similarly, irrigation enhanced P-solub counts in the rhizospheric soil cultivated with Mavuno grass (Fig. 4 d, h). Regarding species effects, yeast counts did not differ between forage species irrespective of water regime. Under dryland conditions, SBac counts were higher in the rhizospheric soil of Mavuno grass than in Zuri grass (+ 60%), whereas in non-rhizospheric soil, SBac counts were lower in Mavuno than in Zuri grass (− 21%) (Fig. 4 a, e). In non-rhizospheric soil, actinomycete counts were 54% higher in Zuri grass than in Mavuno grass under dryland conditions (Fig. 4 g). Under dryland conditions, P-solub counts were higher in the rhizospheric soil of Zuri grass (+ 102%) but lower in non-rhizospheric soil (− 15%) compared to Mavuno grass. Under irrigation, SBac counts were higher in the rhizospheric soil of Zuri grass (+ 125%) but lower in non-rhizospheric soil (− 52%) compared to Mavuno grass. In rhizospheric soil, P-solub counts were higher in Mavuno grass than in Zuri grass under irrigated conditions (Fig. 4 d, h). Effects of water condition and forage species on biomass production Dry matter (DM) production was independently affected by water regime and forage species, whereas canopy height, pasture density, and tiller number showed significant interactions between the analyzed factors (p < 0.05) (Fig. 5 a-d). Irrigation increased DM production compared to dryland conditions, regardless of forage species, and Mavuno grass exhibited higher DM yield than Zuri grass, irrespective of water regime. For canopy structure variables, significant species × water regime interactions were observed. In Mavuno grass, irrigation increased canopy height by 35% and tiller number by 147%, while reducing pasture density by 23% compared to dryland conditions. In Zuri grass, irrigation increased canopy height by 79% and tiller number by 94% relative to dryland conditions, without affecting pasture density (Fig. 5 a-d). Under dryland conditions, Mavuno grass exhibited higher canopy density and shorter canopy height than Zuri grass, with no differences in tiller number between species. Dry matter production was lower under dryland conditions than under irrigation, regardless of forage species. Under irrigated conditions, Mavuno grass showed greater canopy density and higher tiller number than Zuri grass (Fig. 5 b, c). Irrigation markedly increased DM production compared to dryland conditions, independent of species (Fig. 5 a). Correlation and Principal Component Analyses Pearson correlation (Fig. 6 a, c) revealed positive relationships between soil water content and leaf water potential (r = 0.85**) as well as dry mass (r = 0.93**). In the rhizosphere, P-solubilizing microorganisms were associated with the number of tillers (r = 0.66**) and dry mass (r = 0.62**), whereas this association was not observed in non-rhizosphere soil. In non-rhizosphere soil, a high C:N ratio was linked to lower microbial metabolic efficiency (r = 0.52**). Negative correlations were observed between soil water content and the C:N ratio (r = -0.90**), as well as between the C:N ratio and dry mass (r = -0.94**). The C:P and N:P ratios also showed a negative relationship with leaf water potential and dry mass. An increase in qCO₂ reduced microbial biomass C both in the rhizosphere and in non-rhizosphere soil. Principal component analysis (PCA) (Fig. 6 b, d) explained 67.5% of the variance in rhizosphere soil and 61% in non-rhizosphere soil. The main variables contributing to this variation were microbial biomass C, dry mass production, P-solubilizing microorganisms, and the C:N ratio. Cluster analysis highlighted that spore-forming bacteria had a significant influence, particularly in treatments with irrigated Mavuno grass and rainfed Zuri grass. The variables spore-forming bacteria and the C:N ratio primarily contributed to the variance observed in the rainfed Zuri grass treatment but also influenced the rainfed Mavuno and irrigated Zuri treatments. This was indicated by the overlap between groups, suggesting the relevance of these variables across all treatments. Discussion Differences in water relations and elemental homeostasis distinguish forage grasses and their productive potential under dryland or irrigated conditions Forage grass cultivars are adaptable to systems with varying technological inputs, making it essential to understand the physiological and nutritional traits that underpin their tolerance to dryland conditions and responsiveness to irrigation (Nehring et al., 2024). This study explored the contrasting performance of Mavuno and Zuri grasses in pastures managed with subsurface drip irrigation, highlighting key differences in their water status parameters and elemental homeostasis. Under dryland conditions, both forage grasses exhibited a common drought-avoidance strategy characterized by the coordination between leaf morphology and leaf rolling (Fig. 7 a, b), a mechanism that enhances water use efficiency by reducing transpiration (Havrilchak and West, 2024 ). However, this response entails stomatal closure, restricting CO₂ diffusion into the mesophyll, decreasing stomatal conductance, and limiting photosynthetic C assimilation, ultimately reducing biomass ac (Mastalerczuk and Borawska-Jarmułowicz, 2021 ). Consequently, dryland conditions resulted in reductions in plant height and dry matter (DM) yield in both species. Irrespective of water regime, Mavuno grass accumulated higher DM than Zuri grass under the experimental conditions, reflecting differences in short-term biomass response to water availability rather than general species superiority. This pattern was associated with higher leaf water potential (Ψw) in Mavuno grass under dryland conditions and higher soil volumetric water content under subsurface drip irrigation, reflecting differences in plant-water relations rather than a species-specific drought response (Liu et al., 2022 ). At the nutritional level, the study revealed shifts in C:N:P stoichiometry under water-limited conditions, with increases in C:N, C:P, and N:P ratios irrespective of forage species, likely due to reduced nutrient diffusion and limited uptake under low transpiration (Melo et al., 2025 ). These ratios were negatively correlated with DM production, indicating that nutrient imbalance constrains short-term biomass accumulation. Across water regimes, Mavuno grass exhibited greater C accumulation per unit of phosphorus, reflecting greater nutrient-use efficiency, a key trait for maintaining biomass under short-term water-limited conditions (Olivera-Viciedo et al., 2024 ; Melo et al., 2023 ; Rocha et al., 2022 ). In addition, differences in tiller density between species, independent of water regime, may contribute to contrasting growth strategies, as species with more upright growth forms, such as Zuri ( M. maximus cv. Zuri), generally exhibit lower tiller density and rely more on canopy height for biomass accumulation (Ongaro et al., 2023 ; Sbrissia et al., 2020 ). Under irrigated conditions, both species showed balanced Ψw values, confirming the efficiency of subsurface drip irrigation in maintaining optimal soil moisture during the dry season. This water availability supported short-term recovery of biomass accumulation from drought-induced limitations (Fig. 7 c, d), leading to increased plant height and tillering, as well as the resumption of cell division and expansion due to improved nutrient uptake (Oliveira et al., 2022 ). The restoration of C:N:P stoichiometric balance under subsurface drip irrigation occurred similarly in both species, supporting the hypothesis that irrigation mitigates elemental imbalances induced by water deficit and contributes to short-term recovery of biomass accumulation. Forage DM under subsurface drip irrigation increased by approximately 10 t ha⁻¹ regardless of species, compared to 1.3 t ha⁻¹ and 0.4 t ha⁻¹ under dryland conditions for Mavuno and Zuri grasses, respectively, consistent with previous reports on well-managed tropical pastures (Santos et al., 2024 ; Allen et al., 2020). These results demonstrate the effect of subsurface drip irrigation in mitigating reductions in biomass caused by short-term drought stress under field conditions. It is worth noting that during May, June, and July, minimum temperatures below 15°C were recorded on several days, with the lowest value of 6.6°C observed on July 15. Such conditions may temporarily limit biomass accumulation in cultivars sensitive to low temperatures, even under irrigation. Forage grass species and water availability influence the activity and composition of pasture soil microbiota Forage grass cultivation dominates pastures across tropical regions; however, field-based studies examining the interaction between forage species and soil microbiota under dryland and irrigated conditions remain limited. In this study, forage species influenced soil microbial parameters under dryland conditions, as evidenced by higher basal soil respiration associated with Mavuno grass, particularly in non-rhizospheric soil. The stimulatory effect of Mavuno on microbial activity is likely linked to its capacity to maintain higher leaf water potential, which enhances plant metabolism and the exudation of labile C compounds (Dijkstra and Cheng, 2007 ; Wang et al., 2014 ). Soils under Zuri grass exhibited lower microbial respiration, consistent with the higher total organic C observed in these soils under dryland conditions. Analysis of dryland effects on soil microbiota revealed associations among sporulating bacteria, phosphorus-solubilizing microorganisms, yeasts, and actinomycetes in soils under both forage species. These microbial groups may support plant responses to water deficit through functional associations, such as phytohormone production or osmotic adjustment (Bhatti et al., 2017 ; Yadav et al., 2022 ; Kour et al., 2020 ). Notably, phosphorus-solubilizing microorganisms in rhizosphere soils were positively correlated with tiller density (r = 0.66**), highlighting their potential functional role in maintaining plant productivity under limited water availability. Under irrigation, forage species continued to shape soil microbial composition and activity, in line with previous reports in grass-legume systems (Gong et al., 2015 ; Teixeira et al., 2025 ). Mavuno grass promoted the abundance of phosphorus-solubilizing microorganisms in the rhizosphere, increasing microbial metabolic activity and the metabolic quotient under favorable moisture conditions (Yang et al., 2023 ). In contrast, Zuri grass rhizosphere soils showed higher abundance of sporulating bacteria, which enhance microbial persistence and resilience (Li et al., 2024 ). These compositional shifts likely reflect increased root-derived C inputs under improved water availability. Thus, the second hypothesis was supported, as forage species modulated both the composition and functional activity of pasture soil microbiota under dryland and irrigated conditions. Irrigation further modified microbial parameters, with effects varying by microbial group and soil compartment. For example, irrigation reduced the microbial metabolic quotient (qCO₂) in soils under Zuri grass, while simultaneously increasing microbial biomass C (SMB-C) in both forage systems relative to dryland conditions. These patterns are consistent with enhanced plant physiological activity and root exudation under improved moisture, which may contribute to shifts in microbial activity (Ling et al., 2022 ), and warrant investigation in long-term studies. Under dryland conditions, restricted nutrient acquisition, lower root turnover, and reduced litter inputs limited substrate availability for microorganisms (Melo et al., 2025 ; Sanaullah et al., 2011 ). Increased basal respiration under irrigation indicates proliferation of copiotrophic microorganisms, which respond positively to resource-enriched environments (Yang et al., 2023 ). Microbial biomass C and total soil organic C were not constrained in Mavuno systems. Principal component analysis (PCA) showed that SMB-C and aboveground biomass were key contributors to variance in irrigated treatments for both forage species and soil compartments, reinforcing the observed effect of irrigation on microbial biomass and productivity (Fu et al., 2021 ; Rocha et al., 2024 ). The selective stimulation of sporulating bacteria, yeasts, and actinomycetes under irrigation indicates that the irrigation strategy maintained soil moisture within an optimal range without adversely affecting microbial communities (Li et al., 2024 ). Hierarchical clustering combined with PCA revealed that sporulating bacteria in rhizosphere soils significantly contributed to variance observed in irrigated Mavuno treatments. Thus, irrigation promotes soil C retention by increasing microbial biomass C and enhancing microbial metabolic efficiency. Consistent with previous reports (Gong et al., 2015 ; Fu et al., 2021 ), stimulation of specific microbial groups under irrigation is associated with increased plant-derived C inputs, favoring microbial growth and contributing to soil organic C accumulation in managed pastures. Overall, these findings support the third hypothesis, showing that irrigation mitigates drought-induced reductions in soil microbiota and enhances C efficiency in pasture systems. The contrasting microbial responses observed between Mavuno and Zuri grasses under the evaluated conditions highlight the importance of integrating forage species selection with irrigated or dryland management systems to optimize soil microbial function. By promoting microbial biomass and metabolic efficiency, particularly under irrigated conditions, these strategies contribute to improved soil health, resilience to climatic variability, and the sustainability of tropical pasture systems. Conclusions Water availability strongly influenced plant productivity, elemental balance, and soil microbial responses in tropical pasture systems. Mavuno grass showed greater tolerance to rainfed conditions, with higher biomass production during the dry season, linked to improved plant water status and nutrient balance, whereas Zuri grass favored greater soil organic C accumulation under irrigated conditions. Irrigation was related to increased forage biomass and microbial activity, with dry matter production increasing by approximately 10 Mg ha⁻¹ during the dry season for both species. The maintenance of plant C:N:P balance was closely related to biomass responses across contrasting water regimes, suggesting that elemental homeostasis may contribute to sustaining forage growth under variable moisture conditions. Together, these findings highlight the importance of aligning forage species selection with water availability to optimize plant performance and soil biological functioning in tropical pastures. The observed relationships between plant stoichiometry, microbial activity, and productivity indicate that C:N:P ratios have potential as indicators of plant–soil interactions, warranting further investigation under long-term field conditions. Declarations Funding Funding for this research was provided by the Brazilian National Council for Scientific and Technological Development (CNPq) (process 174069/2023-5). Competing Interests The authors have no competing interests to declare that are relevant to the content of this article. Author Contributions Cíntia Melo: Conceptualization, Data curation, Formal analyses, Writing – original draft; Danilo Amaral: Investigation, Data curation; Writing – review and editing; Carlos Santos: Methodology, Formal analyses; Everlon Rigobelo: Laboratory resources, Methodology; Mara Cruz: Laboratory resources, Formal analyses; Writing – review and editing; Renato Prado: Laboratory resources; Writing – review and editing, Supervision; Funding acquisition; Alexandre Dalri: Experimental resources; Writing – review and editing; Luís Drumond: Writing – review and editing. Acknowledgements We extend our sincere gratitude the support of UNESP, the Plant Nutrition Study Group (GENPlant), the team of professors and technicians at the Unesp Experimental Farm where the field experiment was developed, and the Plant Nutrition and Soil Microbiology laboratories. Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. References Allen LN, MacAdam JW (2020) Irrigation and Water Management in Forages. In: Moore KJ, Collins M, Nelson CJ, Redfearn DD (eds) Irrigation and Water Management in Forages. Wiley, pp 497–513. https://doi.org/10.1002/9781119436669.ch27 Anderson T, Domsch K (1993) The metabolic quotient for CO 2 (qCO 2 ) as a specific activity parameter to assess the effects of environmental conditions, such as pH, on the microbial biomass of forest soils. 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18:04:56","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8844252/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8844252/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104880952,"identity":"7763de4a-d1a1-4fc8-8f43-d6e09ef845f4","added_by":"auto","created_at":"2026-03-18 09:14:20","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2496717,"visible":true,"origin":"","legend":"\u003cp\u003eMeteorological data. \u0026nbsp;a) Meteorological data of air temperature, solar radiation and b) precipitation, irrigation, and evapotranspiration during the experimental period from April to October 2023.Jaboticabal, Brazil.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8844252/v1/41fcc2c7ba9a04d6c6e402ef.jpg"},{"id":105034298,"identity":"cb313aa7-4aef-4161-a8bc-a4b09cc20dc8","added_by":"auto","created_at":"2026-03-20 07:23:02","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1709951,"visible":true,"origin":"","legend":"\u003cp\u003eVolumetric soil water content (VWC) (a), total soil organic carbon content (b), relative water content in the leaf (RWC) (c), leaf water potential (Ψw) (d), and stoichiometric ratios C:N, C:P, N:P, and C:Si (e, f, g, h) in the grazing stratum biomass of Mavuno grass and Zuri grass under dryland or irrigated conditions. \u003csup\u003ens\u003c/sup\u003e , * and ** indicate non-significant F-test, and significant F-tests at 5 and 1% probability levels, respectively. S, C, and S×C denote species, water condition, and their interaction, respectively. Uppercase letters compare water conditions for each species, and lowercase letters compare species under each water condition according to the Tukey test (p\u0026lt;0.05), n=4.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8844252/v1/eee1c7add5361bbb17fbe1b5.jpg"},{"id":104880950,"identity":"de28be5b-ee1a-4b46-9b7d-0bce122a621c","added_by":"auto","created_at":"2026-03-18 09:14:20","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1432613,"visible":true,"origin":"","legend":"\u003cp\u003eSoil microbial biomass carbon (SMBC), soil basal respiration (SBR), and microbial metabolic quotient (qCO\u003csub\u003e2\u003c/sub\u003e) in rhizosphere soil (a, b, c) and non-rhizosphere soil (d, e, f) cultivated with Mavuno grass and Zuri grass under dryland or irrigated conditions. \u003csup\u003ens\u003c/sup\u003e , * and ** indicate non-significant F-test, and significant F-tests at 5 and 1% probability levels, respectively. S, C, and S×C denote species, water condition, and their interaction, respectively. Uppercase letters compare water regimes within each species, while lowercase letters compare species within each water regime, according to Tukey test (p\u0026lt;0.05), n=4.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8844252/v1/52c86d558051850df5533061.jpg"},{"id":104880947,"identity":"b8510ec9-71ae-4ece-b2af-a651b7fd170b","added_by":"auto","created_at":"2026-03-18 09:14:20","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1723839,"visible":true,"origin":"","legend":"\u003cp\u003eCounts of sporulating bacteria (SBac), yeasts, actinomycetes, and phosphate-solubilizing microorganisms (P-solub) in rhizosphere soil (a, b, c, d) and non-rhizosphere soil (e, f, g, h) cultivated with Mavuno grass and Zuri grass under dryland or irrigated conditions. \u003csup\u003ens\u003c/sup\u003e , * and ** indicate non-significant F-test, and significant F-tests at 5 and 1% probability levels, respectively. S, C, and S×C denote species, water condition, and their interaction, respectively. Uppercase letters compare water conditions within each species, and lowercase letters compare species within each water condition using Tukey test (p\u0026lt;0.05), n=4.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8844252/v1/e8a71b880f0ec7fffb3e6746.jpg"},{"id":104880951,"identity":"6d31fa9c-e637-4d1a-8e61-edfc85189009","added_by":"auto","created_at":"2026-03-18 09:14:20","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":941459,"visible":true,"origin":"","legend":"\u003cp\u003eCanopy height (a), pasture density (b), tiller number per square meter (c), and forage dry matter production (d) of Mavuno grass and Zuri grass under dryland or irrigated conditions. \u003csup\u003ens\u003c/sup\u003e , * and ** indicate non-significant F-test, and significant F-tests at 5 and 1% probability levels, respectively. S, C, and S×C denote species, water condition, and their interaction, respectively. Uppercase letters compare water conditions within each species, and lowercase letters compare species within each water condition using Tukey test (p\u0026lt;0.05), n=4.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8844252/v1/806ccd755e2b7bc938f2cdfb.jpg"},{"id":104880953,"identity":"01f368c9-4e04-47da-a1b1-6a39f188c6c8","added_by":"auto","created_at":"2026-03-18 09:14:20","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3506357,"visible":true,"origin":"","legend":"\u003cp\u003ePearson correlation network (a) and principal component analysis combined with cluster analysis using standardized data (b) among response variables studied in the field cultivation of Mavuno and Zuri grasses under rainfed and irrigated conditions, in rhizospheric and non-rhizospheric soil. BR, soil basal respiration; qCO₂, metabolic quotient; C/N, C/P, C/Si, N/P stoichiometry ratios in the biomass of the grazing stratum; VWC, volumetric soil water content; Ψw, leaf water potential; Til, number of tillers; DM, dry matter production; Sbc, sporulating bacteria; Act, actinomycetes; P sl, P-solubilizing; Yts, yeasts; MBC, microbial biomass carbon.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8844252/v1/382f958cc44a09119dbac073.jpg"},{"id":104880949,"identity":"299f3228-e8b1-484f-876d-080b6f181a0e","added_by":"auto","created_at":"2026-03-18 09:14:20","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":10797099,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eV\u003c/strong\u003eisual\u003cstrong\u003e \u003c/strong\u003eresponse of forage grasses to dryland and irrigated conditions.\u003cstrong\u003e \u003c/strong\u003e\u0026nbsp;Visual appearance of Mavuno and Zuri grasses pastures (a, b) illustrating leaf rolling and senescence under dryland conditions; (c, d) normal leaf morphology under irrigated conditions in Jaboticabal, São Paulo, Brazil.\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8844252/v1/9117e5191b4534ab77227f37.jpg"},{"id":105036533,"identity":"02e01d99-abb5-4bd6-a85f-e618a645470e","added_by":"auto","created_at":"2026-03-20 07:34:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":23667762,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8844252/v1/4f6f49db-1fe4-43a7-a849-769fa13d0a12.pdf"}],"financialInterests":"","formattedTitle":"Elemental homeostasis and soil microbiota of forage grasses under drought and irrigation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTropical forage grasses from different species are widely cultivated in pastures to enhance livestock production efficiency (Nehring, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, seasonal drought in tropical regions with dry winters limits forage availability, concentrating production during the rainy season (Tulu et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Santos et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Beyond reducing yield, water deficits also alter soil microbial communities in pastures, with plant species influencing these interactions, as observed for forage legumes (Moreno et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Dollete et al., 2024). While grass cultivation generally enhances soil microbial abundance (Momesso et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the effects of different tropical forage grass species on soil microbiota under drought conditions, and how these microbial communities contribute to elemental homeostasis, remain underexplored under field conditions.\u003c/p\u003e \u003cp\u003eDrought stress impacts plants by reducing leaf water potential and transpiration rates (Mganga et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and by altering nutrient accumulation and the stoichiometric balance of carbon (C), nitrogen (N), and phosphorus (P) in leaf tissues (Olivera-Viciedo et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Maintenance of C:N:P homeostasis optimizes nutrient conversion into dry matter (DM), yet abiotic stresses can disrupt this balance in grasses, impairing metabolism and potentially limiting the availability of organic substrates for soil microorganisms (Oliveira Filho et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Melo et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Pereira et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Despite its importance for understanding biomass production under stress, the interaction between soil water availability and elemental stoichiometry has received limited attention in pastures. Additionally, microbial activity and biomass are sensitive indicators of environmental and management impacts on soil, which may in turn influence plant nutritional balance (Silva et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIrrigation systems combined with fertilization are widely used to mitigate the negative effects of drought on forage production (Jesus et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Subsurface drip irrigation is increasingly recommended due to its efficiency in reducing water loss by evaporation and surface runoff compared to sprinkler systems, although implementation costs are higher (Allen and MacAdam, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Rocha et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Cahn and Hutmacher, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Irrigation not only alleviates water stress but also affects the biomass and activity of soil microbial groups (Gong et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Fu et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Since soil organic matter (SOM) accumulation is influenced by root deposition and microbial activity (Frene et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), irrigation may also modify soil C dynamics in well-managed pastures (Li et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Understanding how different forage grass species influence soil microbiota and elemental homeostasis under drought and irrigation is therefore crucial.\u003c/p\u003e \u003cp\u003eBased on these considerations, we tested the following hypotheses: i) Water availability influences soil microbial communities, elemental homeostasis (C:N:P), and forage biomass production in tropical grasses; ii) Forage grass species induce differences in soil microbial biomass, activity, composition, and elemental homeostasis under dryland and subsurface drip irrigation conditions. The objective of this study was to investigate how two tropical forage grass species interact with soil microbial communities and influence elemental homeostasis under drought and subsurface drip irrigation, and how these responses relate to biomass production. By focusing on mechanistic links between soil microbiota and plant nutritional balance, this study provides insight into short-term adaptations of tropical forage grasses to water availability under field conditions.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExperimental Conditions\u003c/h2\u003e \u003cp\u003eA field experiment was conducted at the experimental site of S\u0026atilde;o Paulo State University (UNESP), in Jaboticabal, Brazil (21\u0026deg;14\u0026prime;54\u0026Prime; S, 48\u0026deg;17\u0026prime;06\u0026Prime; W; 560 m elevation). The region has a tropical wet climate with a dry winter (Aw, K\u0026ouml;ppen classification). The study was carried out from April to October 2023, encompassing the dry season, which in the region coincides with autumn, winter, and the beginning of spring, characterized by low (sporadic) or absent rainfall, leading to a progressive decrease in soil moisture. Meteorological data, including evapotranspiration, air temperature, global solar radiation, and rainfall, were recorded at the university\u0026rsquo;s weather station (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, b).\u003c/p\u003e \u003cp\u003eThe soil was classified as Oxisol (Soil Survey Staff, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It was sampled for initial chemical analysis (Raij et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), yielding the following results for the 0\u0026ndash;20 and 20\u0026ndash;40 cm soil layers, respectively: pH\u0026thinsp;=\u0026thinsp;5.8 and 6.0, organic matter (SOM)\u0026thinsp;=\u0026thinsp;22 and 22 g dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, phosphorus (P)\u0026thinsp;=\u0026thinsp;78 and 51 mg dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, potassium (K)\u0026thinsp;=\u0026thinsp;5.5 and 3.6, calcium (Ca)\u0026thinsp;=\u0026thinsp;46 and 44, magnesium (Mg)\u0026thinsp;=\u0026thinsp;15 and 15 mmol\u003csub\u003ec\u003c/sub\u003e dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, sulfur (S)\u0026thinsp;=\u0026thinsp;3 and 4, boron (B)\u0026thinsp;=\u0026thinsp;0.32 and 0.25, copper (Cu)\u0026thinsp;=\u0026thinsp;3.4 and 3.5, iron (Fe)\u0026thinsp;=\u0026thinsp;6 and 5, manganese (Mn)\u0026thinsp;=\u0026thinsp;25.5 and 18.6, zinc (Zn)\u0026thinsp;=\u0026thinsp;1.6 and 1.0 mg dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, H\u0026thinsp;+\u0026thinsp;Al\u0026thinsp;=\u0026thinsp;21 and 18 mmolc dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, cation exchange capacity (CEC)\u0026thinsp;=\u0026thinsp;88 and 81 mmol\u003csub\u003ec\u003c/sub\u003e dm\u003csup\u003e\u0026minus;\u0026thinsp;3,\u003c/sup\u003e base saturation (V\u0026thinsp;=\u0026thinsp;Ca\u0026thinsp;+\u0026thinsp;Mg\u0026thinsp;+\u0026thinsp;K/CEC)\u0026thinsp;=\u0026thinsp;76 and 77%.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExperimental design and management\u003c/h3\u003e\n\u003cp\u003eThe experiment followed a 2 \u0026times; 2 factorial design comprising two tropical forage grass species \u003cem\u003eU. brizantha\u003c/em\u003e \u0026times; \u003cem\u003eU. ruziziensis\u003c/em\u003e cv. Mavuno and \u003cem\u003eM. maximus\u003c/em\u003e cv. Zuri, grown under two water management conditions: dryland or irrigated. Treatments were arranged in a randomized block design with four replicates. In the irrigated treatments, a subsurface drip irrigation system was installed in April 2022 following soil preparation by harrowing. Drip lines were buried at a depth of 20 cm (Rocha et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and spaced 80 cm apart. Emitters had a nominal discharge of 1.45 L h⁻\u0026sup1; at 100 kPa and were positioned at 30 cm intervals. Preliminary testing confirmed uniform water distribution (Bernardo et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eExperimental plots measured 3 \u0026times; 4.8 m. Forage grasses were sown manually at a rate of 10 kg ha⁻\u0026sup1; of pure viable seed, distributed evenly across the soil surface. The forage grass seeds were donated by the commercial supplier WolfSeeds. After seedling emergence, a uniformity cut was performed to stimulate tillering using a brush cutter (Husqvarna 31R/330-2), and the removed biomass was discarded. Sprinkler irrigation was applied during the establishment phase to ensure uniform germination and pasture development.\u003c/p\u003e \u003cp\u003eIn April 2023, once the pasture was fully established, plots were standardized with a maintenance cut, leaving a residual height of 15 cm for Mavuno and 30 cm for Zuri (Barbosa et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Silva et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Water treatments were then implemented: either rainfed (no irrigation) or irrigated with subsurface drip. For irrigated plots, irrigation depth and frequency were calculated to fully replenish crop evapotranspiration, with a maximum allowable soil water deficit of 22 mm. This was based on the soil's water holding capacity (120 mm in the 0\u0026ndash;40 cm layer), as determined from the soil water retention curve (Klute, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1986\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven that initial soil fertility was adequate for grass production, only maintenance fertilization was conducted after each cut. Nutrient replacement rates for N, P, K, and S were based on the quantities exported by the forage biomass under each treatment (Dubeux Jr. et al., 2007; Quaggio et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Fertilizer sources included urea, potassium chloride, ammonium sulfate, and purified monoammonium phosphate (for fertigation), while simple superphosphate was used under rainfed conditions. Fertilizers were applied through fertigation in irrigated plots and broadcast manually in rainfed plots.\u003c/p\u003e\n\u003ch3\u003eVariables analyzed\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eForage sampling and data collection\u003c/h2\u003e \u003cp\u003eData were collected between May 9 and October 2, 2023. Pasture cuts and biomass sampling were performed when grasses under optimal water supply (irrigated plots) reached the recommended pre-grazing heights: 85 cm for Zuri guineagrass and 35 cm for Mavuno grass (Barbosa et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Silva et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Plant height (cm) was recorded immediately prior to cutting at five points per plot using a graduated pasture ruler. Based on this criterion, five harvests were conducted in irrigated plots, whereas only one harvest was possible under rainfed conditions due to limited growth. Sixteen forage samples were collected per harvest cycle, resulting in a total of 96 forage samples over the experimental period.\u003c/p\u003e \u003cp\u003eTo assess dry matter (DM) yield, forage was harvested between 7 and 9 a.m. using a sickle, leaving a post-harvest residue height of 35 cm for Zuri and 15 cm for Mavuno. Forage was collected within metal quadrats of 2.25 m\u0026sup2; for Zuri and 1.0 m\u0026sup2; for Mavuno, placed within each plot. Fresh biomass was weighed immediately, and a subsample (~\u0026thinsp;100 g) was oven-dried at 65\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u0026deg;C for 72 hours in a forced-air oven to determine DM yield (Mg ha⁻\u0026sup1;). After each cut, tiller density (tillers m⁻\u0026sup2;) was estimated by counting both live and dead tillers within a 635 cm\u0026sup2; frame (Bahmani et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Forage mass density (kg ha⁻\u0026sup1; cm⁻\u0026sup1; DM) was then calculated by dividing the DM yield by pasture height.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eVolumetric soil water content\u003c/h3\u003e\n\u003cp\u003eVolumetric soil water content (VWC, cm\u0026sup3; cm⁻\u0026sup3;) was measured at the peak of the dry season in September 2023 using Time Domain Reflectometry (TDR) with a portable soil moisture sensor (HydroSense II, 20 cm rods). Measurements were taken at three locations per plot. Sensor accuracy was confirmed by calibration against gravimetric soil moisture at the same sampling points, yielding an R\u0026sup2; of 0.84 (y\u0026thinsp;=\u0026thinsp;1.0294x \u0026ndash; 3.2562) and a standard deviation of 1% (Gonzalez-Porras et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLeaf water potential and relative water content\u003c/h2\u003e \u003cp\u003eLeaf water potential (Ψw, MPa) was measured between 3 and 5 a.m. in September using a Scholander pressure chamber (Model 3000F01, Soil Moisture Equipment). Measurements were taken from the middle third of the most recently expanded leaf (ligule fully emerged) by gradually increasing chamber pressure until sap exudation from the leaf midrib was observed (Turner, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1981\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRelative water content (RWC, %) was determined from ten leaf discs (129 mm\u0026sup2; each) collected from the same leaf. Fresh mass (FM) was recorded immediately, followed by 6 hours of rehydration in deionized water to obtain turgid mass (TM). Discs were then oven-dried at 80\u0026deg;C for 24 hours to determine dry mass (DM). RWC was calculated as: RWC = [(FM \u0026ndash; DM) / (TM \u0026ndash; DM)] \u0026times; 100 (Barrs and Weatherley, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1962\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eElemental stoichiometry in leaf of forage grasses\u003c/h3\u003e\n\u003cp\u003eTo evaluate the C:N, C:P, N:P, and C:Si stoichiometric ratios in forage biomass, concentrations of C (C), nitrogen (N), phosphorus (P), and silicon (Si) in dry matter (DM) were first determined. For irrigated treatments, samples were pooled and homogenized from all collection dates. For rainfed treatments, a subsample was taken from the single cut, as described in Section 2.3.1.\u003c/p\u003e \u003cp\u003eNitrogen content was determined by the Kjeldahl method with titration following sulfuric acid digestion (Bataglia et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1983\u003c/span\u003e). C content was assessed via oxidation with potassium dichromate in sulfuric acid and titration with ammonium ferrous sulfate (Tedesco et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Phosphorus was determined after nitric-perchloric digestion, followed by a colorimetric reaction with a metavanadate-molybdate reagent, and absorbance was measured at 420 nm using a spectrophotometer (Malavolta et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). For Si, alkaline digestion was carried out with hydrogen peroxide at 120\u0026deg;C, followed by a colorimetric reaction with ammonium molybdate and absorbance reading at 410 nm (Kraska and Breitenbeck, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Elemental concentrations in DM were expressed in g kg⁻\u0026sup1;, and the respective stoichiometric ratios were then calculated.\u003c/p\u003e\n\u003ch3\u003eMicrobiological and soil organic carbon analyses\u003c/h3\u003e\n\u003cp\u003eSoil samples were collected from the 0\u0026ndash;10 cm layer in each plot in October 2023, at the end of the experimental period. A rooted soil clod was excavated using a hoe, and the loosely adhering soil was carefully removed. Rhizosphere soil was defined as the soil that remained attached to the root surface and was gently collected into a plastic tray. Non-rhizosphere soil was sampled from the original location of the excavated clod after root removal. In total, 32 samples were collected, comprising 16 rhizosphere and 16 non-rhizosphere soil samples. All samples were transferred to paper bags for transport, then sieved through a 2 mm mesh, placed into plastic bags, and stored at 4\u0026deg;C until analysis (Silva et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2007a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eMicrobial biomass carbon (SMB-C)\u003c/b\u003e Microbial biomass C (SMB-C) was quantified using the fumigation-extraction method with 0.5 mol L⁻\u0026sup1; potassium sulfate (K₂SO₄) as the extractant. Extracted organic carbon was oxidized with potassium dichromate (K₂Cr₂O₇) in acidic medium and quantified by titration with ammonium ferrous sulfate. SMB-C was calculated using the equation: SMB-C\u0026thinsp;=\u0026thinsp;FC x kc\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, where SMB-C is microbial C in mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e soil; FC is the flux from the difference between the fumigated and non-fumigated samples, and kc is the correction factor (0.33) (Silva et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2007b\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSoil basal respiration (SBR)\u003c/b\u003e was measured using two soil subsamples: one for gravimetric moisture determination and another for CO₂ evolution (Jenkinson and Powlson, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Silva et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2007a\u003c/span\u003e). Approximately 50 g of moist soil was placed into a 100 mL glass jar, which was enclosed in a 2 L hermetically sealed glass container along with a second jar containing 10 mL of 1 mol L⁻\u0026sup1; NaOH solution. Incubation was carried out in the dark at ambient temperature (25\u0026ndash;28\u0026deg;C) for seven days. After incubation, 2 mL of 10% (w/v) barium chloride (BaCl₂) solution was added to the NaOH to precipitate CO₂. The remaining NaOH was titrated with standardized 0.5 mol L⁻\u0026sup1; HCl using 1% phenolphthalein as an indicator. SBR was calculated using the equation: SBR (mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) = (((V\u003csub\u003eb\u003c/sub\u003e - V\u003csub\u003ea\u003c/sub\u003e) x M x 6 x 1000) / Ps) / T, where: SBR\u0026thinsp;=\u0026thinsp;mg C-CO\u003csub\u003e2\u003c/sub\u003e released by microbial respiration per kg of soil per hour; V\u003csub\u003eb\u003c/sub\u003e (mL) = volume of acid used in the titration of the control (blank) solution; V\u003csub\u003ea\u003c/sub\u003e (mL) = volume used in the titration of the sample; M\u0026thinsp;=\u0026thinsp;exact molarity of the HCl solution; Ps (g) = mass of dry soil, and T\u0026thinsp;=\u0026thinsp;incubation time of the sample in hours.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMetabolic quotient (qCO\u003c/b\u003e \u003csub\u003e \u003cb\u003e2\u003c/b\u003e \u003c/sub\u003e \u003cb\u003e)\u003c/b\u003e was calculated using the equation: qCO\u003csub\u003e2\u003c/sub\u003e (mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;SBR / (SMB-C x 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e), where qCO\u003csub\u003e2\u003c/sub\u003e is the metabolic quotient in mg of C-CO\u003csub\u003e2\u003c/sub\u003e per gram of SMB-C per hour, SBR is the basal soil respiration, and SMB-C is the microbial biomass C (Anderson and Domsch, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Silva et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2007b\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eMicrobial population\u003c/strong\u003e \u003cp\u003eMicrobial populations were quantified for sporulating bacteria, yeasts, actinomycetes, and phosphorus-solubilizing microorganisms in both rhizosphere and non-rhizosphere soils. For microbial enumeration, 10 g of soil were added to 95 mL Erlenmeyer flasks containing sterile 0.1% sodium pyrophosphate buffer. The flasks were incubated for 30 minutes at 200 rpm and 28\u0026deg;C to facilitate disaggregation of soil particles. Serial dilutions were prepared by transferring 1 mL of the suspension to test tubes containing 9 mL of the same buffer, continuing until suitable dilutions were obtained for plate counts (30\u0026ndash;300 colony-forming units CFU per plate). Aliquots of 100 \u0026micro;L (0.1 mL) from each dilution were plated onto selective media specific to each microbial group and incubated at 28\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C. The CFU were counted after 72 h for sporulating bacteria and after 120\u0026ndash;168 h for yeasts, actinomycetes, and phosphorus-solubilizing microorganisms. The culture media used were nutrient agar for sporulating bacteria, yeast\u0026ndash;malt agar supplemented with antibiotics for yeasts, starch-casein agar for actinomycetes, and GES medium (glucose, soil extract, and inorganic salts) for phosphorus-solubilizing microorganisms (Vieira and Nahas, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eTotal Organic Carbon in Soil\u003c/strong\u003e \u003cp\u003eIt was determined by using 1 g of sample (non-rhizosphere soil) and oxidizing it through wet digestion with a potassium dichromate and sulfuric acid mixture. The dichromate solution was added in excess, so that during the reaction, part of the Cr was reduced, while another part remained in its oxidized form. The remaining reagent in the oxidized form was measured by titration with an ammonium ferrous sulfate solution. From the amount added and the excess reagent after the reaction, the amount of Cr that oxidized C was determined. This allowed for the calculation of the soil C content (g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). The procedure followed is based on the Walkley and Black method, as described by Raij et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAn analysis of data normality assumptions, homogeneity of variances, and independence of residuals was performed (Bartlett, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1937\u003c/span\u003e; Jarque and Bera, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1980\u003c/span\u003e), followed by analysis of variance (F-test, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). For significant F, means were compared using Tukey test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) with SPEED Stat software version 3.4 (Carvalho et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). A Pearson correlation network among the variables was established, and principal component analysis was conducted based on the covariance matrix, overlapped by hierarchical clustering analysis using Euclidean distance and a cluster analysis by the single linkage method (Carvalho, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). All analyses were performed using R Studio version 4.3.3.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSoil and plant water content, and elemental stoichiometry\u003c/h2\u003e \u003cp\u003eThe results (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-h) showed an interaction effect between water conditions and forage species (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) for leaf water potential (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed) and for the C:P and N:P stoichiometric ratios in the biomass of the grazed stratum (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef, g). Irrigated cultivation, in comparison to dryland conditions, increased the VWC, which was reflected in higher RWC and increased Ψw for both Mavuno (87%) and Zuri (92%). Under dryland conditions, Zuri exhibited lower Ψw than Mavuno, whereas no differences were observed between the species under irrigation. The irrigation increased VWC compared to dryland conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, d).\u003c/p\u003e \u003cp\u003eZuri grass had a higher organic C content than Mavuno, regardless of water regime, with differences of +\u0026thinsp;10% under dryland and +\u0026thinsp;6% under irrigation. Irrigation increased soil organic C content compared to dryland conditions, independent of species (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Mavuno grass showed higher C:P, N:P, and C:Si ratios than Zuri grass, irrespective of irrigation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef, g, h).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eBiomass and microbial activity in the soil\u003c/h2\u003e \u003cp\u003eInteraction effects were observed between water regimes and forage species (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) for the variables SMBC and qCO\u003csub\u003e2\u003c/sub\u003e in both rhizosphereric and non-rhizospheric soils, and for SBR in non-rhizospheric soil, while SBR in rhizosphere soil did not show a significant interaction (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-f). Interaction effects between water regimes and forage species (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were observed for SMBC and qCO2 in both rhizosphere and non-rhizosphere soils, and for SBR in non-rhizosphere soil, while SBR in rhizosphere soil did not show a significant interaction (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-f). Irrigation increased SMBC in Mavuno grass (49% in rhizosphere soil) and Zuri grass (124% in rhizosphere soil and 21% in non-rhizosphere soil) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, d). In rhizosphere soil, irrigation increased SBR compared to dryland conditions, independent of species (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). In non-rhizosphere soil, irrigation increased SBR under both forage species (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee). For qCO\u003csub\u003e2\u003c/sub\u003e, irrigation reduced its value in Zuri grass, both in rhizosphere (-65%) and non-rhizosphere (-52%) soils (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, f).\u003c/p\u003e \u003cp\u003eDifferences between species under dryland conditions were observed for SBR in non-rhizospheric soil, with Mavuno grass exhibiting higher values than Zuri (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee). In irrigated pastures, Zuri grass showed higher SMBC in both rhizospheric (36%) and non-rhizospheric (27%) soils, while SBR in rhizospheric soil was reduced under irrigation compared to dryland, independent of species (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, b, d, e). In the rhizosphere, qCO\u003csub\u003e2\u003c/sub\u003e was lower in Zuri grass compared to Mavuno (-52%) under irrigation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, f).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eMicrobial community in soil\u003c/h2\u003e \u003cp\u003eThe interaction between water regime and forage species was significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) for most microbial groups analyzed, including total bacteria (SBac) and phosphate-solubilizing microorganisms (P-solub) in both rhizosphere and non-rhizospheric soils, as well as actinomycetes in non-rhizospheric soil (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea-h).\u003c/p\u003e \u003cp\u003eCompared to dryland conditions, irrigation increased SBac counts in the rhizosphere soil of Zuri grass (+\u0026thinsp;424%) and in the non-rhizospheric soil of Mavuno grass (+\u0026thinsp;30%), while reducing SBac counts in the non-rhizospheric soil of Zuri grass (\u0026minus;\u0026thinsp;51%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, e). Irrigation also increased yeast counts in non-rhizospheric soil cultivated with Mavuno (+\u0026thinsp;35%) and Zuri grass (+\u0026thinsp;41%), whereas no irrigation effect was observed in rhizospheric soil (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb, f). In non-rhizosphere soil, actinomycete counts increased by 71% under irrigation in Mavuno grass compared to dryland conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec, g). Similarly, irrigation enhanced P-solub counts in the rhizospheric soil cultivated with Mavuno grass (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed, h).\u003c/p\u003e \u003cp\u003eRegarding species effects, yeast counts did not differ between forage species irrespective of water regime. Under dryland conditions, SBac counts were higher in the rhizospheric soil of Mavuno grass than in Zuri grass (+\u0026thinsp;60%), whereas in non-rhizospheric soil, SBac counts were lower in Mavuno than in Zuri grass (\u0026minus;\u0026thinsp;21%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, e). In non-rhizospheric soil, actinomycete counts were 54% higher in Zuri grass than in Mavuno grass under dryland conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg). Under dryland conditions, P-solub counts were higher in the rhizospheric soil of Zuri grass (+\u0026thinsp;102%) but lower in non-rhizospheric soil (\u0026minus;\u0026thinsp;15%) compared to Mavuno grass. Under irrigation, SBac counts were higher in the rhizospheric soil of Zuri grass (+\u0026thinsp;125%) but lower in non-rhizospheric soil (\u0026minus;\u0026thinsp;52%) compared to Mavuno grass. In rhizospheric soil, P-solub counts were higher in Mavuno grass than in Zuri grass under irrigated conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed, h).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eEffects of water condition and forage species on biomass production\u003c/h2\u003e \u003cp\u003eDry matter (DM) production was independently affected by water regime and forage species, whereas canopy height, pasture density, and tiller number showed significant interactions between the analyzed factors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-d). Irrigation increased DM production compared to dryland conditions, regardless of forage species, and Mavuno grass exhibited higher DM yield than Zuri grass, irrespective of water regime.\u003c/p\u003e \u003cp\u003eFor canopy structure variables, significant species \u0026times; water regime interactions were observed. In Mavuno grass, irrigation increased canopy height by 35% and tiller number by 147%, while reducing pasture density by 23% compared to dryland conditions. In Zuri grass, irrigation increased canopy height by 79% and tiller number by 94% relative to dryland conditions, without affecting pasture density (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-d).\u003c/p\u003e \u003cp\u003eUnder dryland conditions, Mavuno grass exhibited higher canopy density and shorter canopy height than Zuri grass, with no differences in tiller number between species. Dry matter production was lower under dryland conditions than under irrigation, regardless of forage species. Under irrigated conditions, Mavuno grass showed greater canopy density and higher tiller number than Zuri grass (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb, c). Irrigation markedly increased DM production compared to dryland conditions, independent of species (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation and Principal Component Analyses\u003c/h2\u003e \u003cp\u003ePearson correlation (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea, c) revealed positive relationships between soil water content and leaf water potential (r\u0026thinsp;=\u0026thinsp;0.85**) as well as dry mass (r\u0026thinsp;=\u0026thinsp;0.93**). In the rhizosphere, P-solubilizing microorganisms were associated with the number of tillers (r\u0026thinsp;=\u0026thinsp;0.66**) and dry mass (r\u0026thinsp;=\u0026thinsp;0.62**), whereas this association was not observed in non-rhizosphere soil. In non-rhizosphere soil, a high C:N ratio was linked to lower microbial metabolic efficiency (r\u0026thinsp;=\u0026thinsp;0.52**). Negative correlations were observed between soil water content and the C:N ratio (r = -0.90**), as well as between the C:N ratio and dry mass (r = -0.94**). The C:P and N:P ratios also showed a negative relationship with leaf water potential and dry mass. An increase in qCO₂ reduced microbial biomass C both in the rhizosphere and in non-rhizosphere soil.\u003c/p\u003e \u003cp\u003ePrincipal component analysis (PCA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb, d) explained 67.5% of the variance in rhizosphere soil and 61% in non-rhizosphere soil. The main variables contributing to this variation were microbial biomass C, dry mass production, P-solubilizing microorganisms, and the C:N ratio. Cluster analysis highlighted that spore-forming bacteria had a significant influence, particularly in treatments with irrigated Mavuno grass and rainfed Zuri grass. The variables spore-forming bacteria and the C:N ratio primarily contributed to the variance observed in the rainfed Zuri grass treatment but also influenced the rainfed Mavuno and irrigated Zuri treatments. This was indicated by the overlap between groups, suggesting the relevance of these variables across all treatments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cb\u003eDifferences in water relations and elemental homeostasis distinguish forage grasses and their productive potential under dryland or irrigated conditions\u003c/b\u003e \u003c/p\u003e \u003cp\u003eForage grass cultivars are adaptable to systems with varying technological inputs, making it essential to understand the physiological and nutritional traits that underpin their tolerance to dryland conditions and responsiveness to irrigation (Nehring et al., 2024). This study explored the contrasting performance of Mavuno and Zuri grasses in pastures managed with subsurface drip irrigation, highlighting key differences in their water status parameters and elemental homeostasis.\u003c/p\u003e \u003cp\u003eUnder dryland conditions, both forage grasses exhibited a common drought-avoidance strategy characterized by the coordination between leaf morphology and leaf rolling (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea, b), a mechanism that enhances water use efficiency by reducing transpiration (Havrilchak and West, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, this response entails stomatal closure, restricting CO₂ diffusion into the mesophyll, decreasing stomatal conductance, and limiting photosynthetic C assimilation, ultimately reducing biomass ac (Mastalerczuk and Borawska-Jarmułowicz, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consequently, dryland conditions resulted in reductions in plant height and dry matter (DM) yield in both species. Irrespective of water regime, Mavuno grass accumulated higher DM than Zuri grass under the experimental conditions, reflecting differences in short-term biomass response to water availability rather than general species superiority. This pattern was associated with higher leaf water potential (Ψw) in Mavuno grass under dryland conditions and higher soil volumetric water content under subsurface drip irrigation, reflecting differences in plant-water relations rather than a species-specific drought response (Liu et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt the nutritional level, the study revealed shifts in C:N:P stoichiometry under water-limited conditions, with increases in C:N, C:P, and N:P ratios irrespective of forage species, likely due to reduced nutrient diffusion and limited uptake under low transpiration (Melo et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These ratios were negatively correlated with DM production, indicating that nutrient imbalance constrains short-term biomass accumulation. Across water regimes, Mavuno grass exhibited greater C accumulation per unit of phosphorus, reflecting greater nutrient-use efficiency, a key trait for maintaining biomass under short-term water-limited conditions (Olivera-Viciedo et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Melo et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Rocha et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In addition, differences in tiller density between species, independent of water regime, may contribute to contrasting growth strategies, as species with more upright growth forms, such as Zuri (\u003cem\u003eM. maximus\u003c/em\u003e cv. Zuri), generally exhibit lower tiller density and rely more on canopy height for biomass accumulation (Ongaro et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sbrissia et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUnder irrigated conditions, both species showed balanced Ψw values, confirming the efficiency of subsurface drip irrigation in maintaining optimal soil moisture during the dry season. This water availability supported short-term recovery of biomass accumulation from drought-induced limitations (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ec, d), leading to increased plant height and tillering, as well as the resumption of cell division and expansion due to improved nutrient uptake (Oliveira et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The restoration of C:N:P stoichiometric balance under subsurface drip irrigation occurred similarly in both species, supporting the hypothesis that irrigation mitigates elemental imbalances induced by water deficit and contributes to short-term recovery of biomass accumulation.\u003c/p\u003e \u003cp\u003eForage DM under subsurface drip irrigation increased by approximately 10 t ha⁻\u0026sup1; regardless of species, compared to 1.3 t ha⁻\u0026sup1; and 0.4 t ha⁻\u0026sup1; under dryland conditions for Mavuno and Zuri grasses, respectively, consistent with previous reports on well-managed tropical pastures (Santos et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Allen et al., 2020). These results demonstrate the effect of subsurface drip irrigation in mitigating reductions in biomass caused by short-term drought stress under field conditions. It is worth noting that during May, June, and July, minimum temperatures below 15\u0026deg;C were recorded on several days, with the lowest value of 6.6\u0026deg;C observed on July 15. Such conditions may temporarily limit biomass accumulation in cultivars sensitive to low temperatures, even under irrigation.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eForage grass species and water availability influence the activity and composition of pasture soil microbiota\u003c/h2\u003e \u003cp\u003eForage grass cultivation dominates pastures across tropical regions; however, field-based studies examining the interaction between forage species and soil microbiota under dryland and irrigated conditions remain limited. In this study, forage species influenced soil microbial parameters under dryland conditions, as evidenced by higher basal soil respiration associated with Mavuno grass, particularly in non-rhizospheric soil. The stimulatory effect of Mavuno on microbial activity is likely linked to its capacity to maintain higher leaf water potential, which enhances plant metabolism and the exudation of labile C compounds (Dijkstra and Cheng, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Soils under Zuri grass exhibited lower microbial respiration, consistent with the higher total organic C observed in these soils under dryland conditions.\u003c/p\u003e \u003cp\u003eAnalysis of dryland effects on soil microbiota revealed associations among sporulating bacteria, phosphorus-solubilizing microorganisms, yeasts, and actinomycetes in soils under both forage species. \u003cb\u003eThese microbial groups may support plant responses to water deficit through functional associations, such as phytohormone production or osmotic adjustment\u003c/b\u003e (Bhatti et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Yadav et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kour et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Notably, phosphorus-solubilizing microorganisms in rhizosphere soils were positively correlated with tiller density (r\u0026thinsp;=\u0026thinsp;0.66**), highlighting their potential functional role in maintaining plant productivity under limited water availability.\u003c/p\u003e \u003cp\u003eUnder irrigation, forage species continued to shape soil microbial composition and activity, in line with previous reports in grass-legume systems (Gong et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Teixeira et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Mavuno grass promoted the abundance of phosphorus-solubilizing microorganisms in the rhizosphere, increasing microbial metabolic activity and the metabolic quotient under favorable moisture conditions (Yang et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In contrast, Zuri grass rhizosphere soils showed higher abundance of sporulating bacteria, which enhance microbial persistence and resilience (Li et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These compositional shifts likely reflect increased root-derived C inputs under improved water availability. Thus, the second hypothesis was supported, as forage species modulated both the composition and functional activity of pasture soil microbiota under dryland and irrigated conditions.\u003c/p\u003e \u003cp\u003eIrrigation further modified microbial parameters, with effects varying by microbial group and soil compartment. For example, irrigation reduced the microbial metabolic quotient (qCO₂) in soils under Zuri grass, while simultaneously increasing microbial biomass C (SMB-C) in both forage systems relative to dryland conditions. These patterns are consistent with enhanced plant physiological activity and root exudation under improved moisture, which may contribute to shifts in microbial activity (Ling et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and warrant investigation in long-term studies. Under dryland conditions, restricted nutrient acquisition, lower root turnover, and reduced litter inputs limited substrate availability for microorganisms (Melo et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Sanaullah et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIncreased basal respiration under irrigation indicates proliferation of copiotrophic microorganisms, which respond positively to resource-enriched environments (Yang et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Microbial biomass C and total soil organic C were not constrained in Mavuno systems. Principal component analysis (PCA) showed that SMB-C and aboveground biomass were key contributors to variance in irrigated treatments for both forage species and soil compartments, reinforcing the observed effect of irrigation on microbial biomass and productivity (Fu et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Rocha et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe selective stimulation of sporulating bacteria, yeasts, and actinomycetes under irrigation indicates that the irrigation strategy maintained soil moisture within an optimal range without adversely affecting microbial communities (Li et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Hierarchical clustering combined with PCA revealed that sporulating bacteria in rhizosphere soils significantly contributed to variance observed in irrigated Mavuno treatments. Thus, irrigation promotes soil C retention by increasing microbial biomass C and enhancing microbial metabolic efficiency. Consistent with previous reports (Gong et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Fu et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), stimulation of specific microbial groups under irrigation is associated with increased plant-derived C inputs, favoring microbial growth and contributing to soil organic C accumulation in managed pastures.\u003c/p\u003e \u003cp\u003eOverall, these findings support the third hypothesis, showing that irrigation mitigates drought-induced reductions in soil microbiota and enhances C efficiency in pasture systems. The contrasting microbial responses observed between Mavuno and Zuri grasses under the evaluated conditions highlight the importance of integrating forage species selection with irrigated or dryland management systems to optimize soil microbial function. By promoting microbial biomass and metabolic efficiency, particularly under irrigated conditions, these strategies contribute to improved soil health, resilience to climatic variability, and the sustainability of tropical pasture systems.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWater availability strongly influenced plant productivity, elemental balance, and soil microbial responses in tropical pasture systems. Mavuno grass showed greater tolerance to rainfed conditions, with higher biomass production during the dry season, linked to improved plant water status and nutrient balance, whereas Zuri grass favored greater soil organic C accumulation under irrigated conditions. Irrigation was related to increased forage biomass and microbial activity, with dry matter production increasing by approximately 10 Mg ha⁻\u0026sup1; during the dry season for both species.\u003c/p\u003e \u003cp\u003eThe maintenance of plant C:N:P balance was closely related to biomass responses across contrasting water regimes, suggesting that elemental homeostasis may contribute to sustaining forage growth under variable moisture conditions. Together, these findings highlight the importance of aligning forage species selection with water availability to optimize plant performance and soil biological functioning in tropical pastures. The observed relationships between plant stoichiometry, microbial activity, and productivity indicate that C:N:P ratios have potential as indicators of plant\u0026ndash;soil interactions, warranting further investigation under long-term field conditions.\u003c/p\u003e "},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eFunding for this research was provided by the Brazilian National Council for Scientific and Technological Development (CNPq) (process 174069/2023-5).\u003c/p\u003e\u003ch2\u003eCompeting Interests\u003c/h2\u003e \u003cp\u003eThe authors have no competing interests to declare that are relevant to the content of this article.\u003c/p\u003e\u003ch2\u003eAuthor Contributions\u003c/h2\u003e \u003cp\u003eC\u0026iacute;ntia Melo: Conceptualization, Data curation, Formal analyses, Writing \u0026ndash; original draft; Danilo Amaral: Investigation, Data curation; Writing \u0026ndash; review and editing; Carlos Santos: Methodology, Formal analyses; Everlon Rigobelo: Laboratory resources, Methodology; Mara Cruz: Laboratory resources, Formal analyses; Writing \u0026ndash; review and editing; Renato Prado: Laboratory resources; Writing \u0026ndash; review and editing, Supervision; Funding acquisition; Alexandre Dalri: Experimental resources; Writing \u0026ndash; review and editing; Lu\u0026iacute;s Drumond: Writing \u0026ndash; review and editing.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe extend our sincere gratitude the support of UNESP, the Plant Nutrition Study Group (GENPlant), the team of professors and technicians at the Unesp Experimental Farm where the field experiment was developed, and the Plant Nutrition and Soil Microbiology laboratories.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAllen LN, MacAdam JW (2020) Irrigation and Water Management in Forages. 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Appl Soil Ecol 183:104743. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.apsoil.2022.104743\u003c/span\u003e\u003cspan address=\"10.1016/j.apsoil.2022.104743\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\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":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","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":"forage grasses, soil microbiota, C:N:P stoichiometry, subsurface drip irrigation, water deficit","lastPublishedDoi":"10.21203/rs.3.rs-8844252/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8844252/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eAims\u003c/h2\u003e \u003cp\u003ePerennial forage systems in tropical regions are predominantly rainfed; however, increasing drought frequency associated with climate change has accelerated the adoption of irrigation. Selecting forage species capable of maintaining elemental balance and favorable plant-soil interactions is essential to sustain productivity. This study evaluated the drought tolerance of Mavuno and Zuri grasses under tropical field conditions, focusing on their responses to subsurface drip irrigation, plant carbon (C), nitrogen (N) and phosphorus (P) stoichiometry, and soil microbial dynamics.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA field experiment was conducted under rainfed and irrigated conditions, assessing forage biomass production, plant water status, leaf C, N, and P concentrations, and indicators of soil microbial activity and composition in rhizosphere and non-rhizosphere compartments.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eUnder rainfed conditions, both grasses exhibited reductions in biomass production; however, Mavuno maintained greater elemental homeostasis and higher soil microbial activity, suggesting greater tolerance to seasonal water deficit. Irrigation restored plant water status, improved C:N:P ratios, and increased the abundance of key microbial groups, including sporulating bacteria, yeasts, and actinomycetes. Forage yield increased by approximately 10 Mg ha⁻\u0026sup1; of dry matter under irrigation for both species. Under irrigated conditions, Zuri grass was associated with higher microbial biomass C and total soil organic C, indicating enhanced soil C inputs.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThese findings demonstrate species-specific responses to water availability and show that irrigation modulates plant nutrient stoichiometry and soil microbial processes. The choice of forage species with stable elemental composition and favorable plant-soil interactions plays a key role in sustaining productivity.\u003c/p\u003e","manuscriptTitle":"Elemental homeostasis and soil microbiota of forage grasses under drought and irrigation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-18 09:14:03","doi":"10.21203/rs.3.rs-8844252/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2026-04-08T09:12:24+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-17T07:26:36+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Plant and Soil","date":"2026-03-02T10:27:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-02T09:06:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant and Soil","date":"2026-02-27T14:52:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","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":"b80eeb3d-8bdd-4b96-8703-a3cded7118be","owner":[],"postedDate":"March 18th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-18T09:14:03+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-18 09:14:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8844252","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8844252","identity":"rs-8844252","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}