Cutting height shapes biomass yield but not herbage properties in semi-natural grasslands

Cutting height shapes biomass yield but not herbage properties in semi-natural grasslands | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Cutting height shapes biomass yield but not herbage properties in semi-natural grasslands Małgorzata W. Raduła, Grzegorz Swacha, Mateusz Meserszmit This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8618743/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The declining demand for biomass delivered from semi-natural grasslands, driven by rapid socio-economic change, is a major threat for grassland abandonment accelerating biodiversity loss. Developing management strategies that intentionally reduce biomass removal, such as increasing cutting height, may help overcome utilisation challenges in regions with limited demand for hay. This study represents the first phase of a long-term field project established in semi-natural grasslands. We tested the effect of three cutting heights (5, 15, and 25 cm) on biomass yields and herbage properties in mesic grassland. We further assessed the effects of functional groups (grasses versus forbs) and individual plant species on these parameters to disentangle cutting height effects from site-specific variation in plant species composition. Biomass declined by ~ 50% when cutting height increased from 5 to 25 cm. The proportion of grass biomass positively influenced fibre content and negatively influenced lipid concentrations, although these effects were attenuated at the highest cutting height. Despite reduced biomass, herbage nutritive value remained stable across cutting heights. We conclude that management strategies incorporating higher cutting heights can substantially reduce harvested biomass yield while maintaining herbage quality providing a practical tool to facilitate biomass utilisation and contribute to the prevention of semi-natural grassland abandonment. Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Biological sciences/Plant sciences sward sustainable management mesic grassland biodiversity fibre dry matter content Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Semi-natural grasslands are a base element in the chain of meat, milk, and natural fertiliser production. Besides the direct financial benefits from livestock farming, semi-natural grasslands provide a wide range of ecosystem services and represent critical reservoirs of biodiversity. They regulate the surrounding environment, including air humidity and temperature, surface and groundwater retention, as well as physical and chemical soil properties (Habel et al., 2013; Lindborg et al. 2023). Semi-natural grasslands also constitute one of the most aesthetically appealing components of agricultural landscapes, thereby enhancing their attractiveness for nature-based tourism and recreational activities (Tscharntke et al., 2005; Hopkins and Holz, 2006). These ecosystems provide niches for a wide range of organisms at a relatively small scale (Duelli and Obrist, 2003; Öckinger and Smith, 2007; Raduła et al., 2020) and are characterised by high species richness (Chytrý et al., 2015). The persistence and ecological functioning of semi-natural grasslands depend on regular biomass removal, which can be achieved through mowing, grazing, or a combination of both (Jacquemyn et al., 2011; Schneider & Hering, 2024). Regular management of low-intensity enables the temporal and spatial coexistence of differentiated niches, promoting the co-occurrence of less competitive plants, and enhancing overall biodiversity (Pykälä et al., 2005; Jacquemyn et al., 2011; Doležal et al., 2019). In many regions, the demand for grassland hay is limited due to the lower livestock density on extensive farmlands. This has resulted in the abandonment of semi-natural grasslands, triggering secondary succession and consequently causing biodiversity loss (MacDonald et al., 2000; Isselstein et al., 2005; Bignal & McCracken, 2000; Pellaton et al., 2022). Furthermore, extensively managed grasslands provide forage with highly varied quantity and quality (Schaub et al., 2020), which is dictated by local, varied environmental conditions, temporal changes in plant species composition, and diversified maturity stages of plant species (Donath et al., 2004; Bruinenberg et al., 2002). In contrast, cost-effective, intensively managed grasslands ensure high-quality and high-yield collections, as biomass characteristics are constant and predictable due to the simplified composition of seeded plants (Nyfeler et al., 2009; Finn et al., 2024). These grasslands are typically meliorated, levelled, re-sown, and fertilised, and all provide large amounts of nutrient-rich forage but are characterised by low species richness (Isselstein et al., 2005; Stoate et al., 2009; Bignal & McCracken, 2000). Services delivered by semi-natural grasslands reach far above forage production, yet economic aspects have always driven human decisions (Lakner et al., 2020). Where mowing is retained in semi-natural grasslands, the biomass yields typically range from 2 to 8 t ha⁻¹ yr⁻¹ (Gigante et al., 2024; Heinsoo et al., 2010; Swacha et al., 2023), and often exceed local utilisation capacity in extensive farmland systems. Considerable practical and economic constraints regarding biomass valorisation frequently leads either to the complete cessation of mowing or to the retention of cut material on grassland. Although leaving biomass on site hinders woodland development; the its accumulation of uncollected biomass accelerates nutrient enrichment (particularly nitrogen and phosphorus), promotes tall, competitive grasses and shade-tolerant species, and further threatens the persistence of grassland specialists (Bohner et al. 2019; Pavlů et al. 2016). In recent years, the practice of baling cut biomass and storing it on site has become increasingly common, especially on grasslands enrolled in agri-environmental schemes that compensate farmers for the management and conservation of high-nature-value sites (Stalenga et al., 2016). Because mowing is a compulsory condition for receiving payments under these schemes, biomass is often cut but not subsequently utilised. To mitigate the adverse impacts of abandonment or inappropriate management on grassland biodiversity, management strategies could prioritise reducing the proportion of biomass removed during harvest, particularly through the implementation of higher cutting heights. The retention of taller stubble has often been advocated as a conservation measure to reduce mortality and injury risks for grassland fauna (von Berg et al., 2023). However, empirical evidence on the ecological consequences of cutting height from a plant-centred perspective remains limited. Previous research has primarily examined cutting heights ranging from 2 to 15 cm, focusing only on biomass yield and forage nutritive value (Dovel, 1996; Vranić et al., 2022). Yet, Dovel (1996) demonstrated that relationships between cutting height, biomass yield, and forage quality are not uniform, but are strongly mediated by local growing conditions (e.g., moisture stress, growing season) and plant community composition (e.g., dominance of grasses versus sedges). Reconciling the dual objectives of yield optimisation and ecosystem functioning therefore remains a persistent challenge across grassland systems. This study examines the ecological implications of varying cutting heights in mesic hay meadows, which are among the most ecologically significant semi-natural grassland types (Preislerová et al., 2022; Rodríguez-Rojo et al., 2017). These grasslands are widely distributed across temperate Europe and characterised by high species richness and structural complexity, but are increasingly threatened by agricultural intensification, land-use change, and abandonment (Török et al. 2018). Consequently, they are listed under Annex I of the EU Habitats Directive (Council Directive 92/43/EEC). Mesic temperate grasslands harbour plant species with diverse growth forms and height potentials, making them well-suited for assessing the ecological trade-offs of alternative cutting regimes. In our study, we implemented three cutting-height treatments (5 cm, 15 cm, and 25 cm). The inclusion of the 25 cm treatment was designed to test whether substantially reducing biomass removal could enhance conservation benefits and to allow for the evaluation of herbage properties across a broader range of cutting heights. Specifically, addresses the following research questions: ( 1 ) How increasing cutting height (15 cm and 25 cm) alters biomass yield relative to the conventional 5 cm regime? ( 2 ) Whether increasing cutting height affects herbage properties? ( 3 ) How plant species composition, expressed as the relative proportion of grasses versus forbs, and individual species contributions, influences biomass yield and herbage properties. 2. Material and methods 2.1. Study site and design The study (51.218372° N, 17.204805° E) was conducted in semi-natural grasslands near the Łosice village, Lower Silesia, Poland (Central Europe) (Fig. 1 A, B). The study site is located in a lowland area (135 m a.s.l.) within the temperate climate zone. The mean annual temperature is 10.8°C, with a sum of annual precipitation of 542 mm. The vegetation season lasts approximately 220 days (Karger et al. 2020). In 2023, the mean temperature in the warmest month (June) was 20.7°C, and in the coldest month (January) was 3.6°C, based on meteorological data from the Agro- and Hydrometeorology Observatory in Wrocław-Swojec, located 12.3 km from the site. The experiment consisted of four completely randomised blocks, each containing nine 1 m² plots surrounded by buffer zones. The total area of the plot, including its buffer zone, was 2 m² (1.41 x 1.41 m). The blocks and the plots (including buffer zones) were separated by 2 m and 0.5 m-wide gaps, respectively (Fig. 1 C). Work presented here represent the first stage of a long-term research programme comprising three different permanent experiments established in two semi-natural grasslands. The semi-natural grassland studied has been continuously mown since the 1980s; earlier, it had been cultivated as arable land (historical topographic maps, www.wgik.dolnyslask.pl ). Nowadays, this area (2.2 ha) is mown once per year, in the third decade of June, for horse breeding purposes. The vegetation is dominated by Holcus lanatus with high coverage of Geranium pratense , Arrhenatherum elatius , Festuca rubra , Dactylis glomerata , and Rumex acetosa (Table 1 ). According to Chytrý et al. (2020) and Kącki et al. (2020), the vegetation of the grassland represents mesic grassland of the Arrhenatherion alliance. 2.2. Vegetation characteristics In the plots, the percentage cover of each plant species was visually estimated. The data on plant species composition were collected between June 26 and 29, 2023. The nomenclature was unified according to the Euro + Med PlantBase (Euro + Med, 2006). Additionally, the height of the tallest leaf and the highest inflorescence or fruit (if present) for each species was measured. The measurements were summarised in Table 1 . Table 1 Frequency (freq.), median non-zero cover (cover), vegetative height (veg. h.; height of the highest leaf), generative height (gen. h.), and phenological phase (V – vegetative, Fl – flowering, Fr – fruiting) of all vascular plant species recorded. freq. cover [%] veg. h. [cm] gen. h. [cm] phase Holcus lanatus 36 35 47.6 78.6 Fr Geranium pratense 36 22.5 39.8 - V Dactylis glomerata 36 5 49.6 76.4 Fr Festuca rubra 36 5 37.9 69.8 Fr Rumex acetosa 36 5 29.4 61.2 Fr Arrhenatherum elatius 35 7 66.2 111.1 Fr Veronica arvensis 34 0.1 17.5 - V Plantago lanceolata 28 1 22.4 39.3 Fr Schedonorus pratensis 25 1 37.8 89.0 Fr Achillea millefolium 24 0.5 21.0 22.0 Fl Vicia tetrasperma 23 0.5 35.9 35.1 Fl Artemisia vulgaris 14 0.5 31.1 - V Ranunculus acris 12 0.5 37.5 52.8 Fr Vicia hirsuta 12 0.5 37.1 37.1 Fl Cirsium arvense 11 1 34.5 46.5 Fl Poa pratensis 10 0.5 34.6 71.0 Fr Glechoma hederacea 9 0.5 7.9 - V Cerastium fontanum subsp. vulgare 9 0.1 11.4 25.3 Fl Galium mollugo 7 0.5 50.8 59.1 Fl Veronica serpyllifolia 7 0.1 6.0 8.0 Fl Elytrigia repens 6 0.5 39.9 - V Hieracium species 4 1.25 24.8 32.0 Fl Phleum pratense 4 0.5 52.0 - V Jacobaea vulgaris 3 1 32.0 - V Ranunculus repens 3 0.5 15.5 - V Prunus spinosa 3 0.1 31.0 - V Pastinaca sativa 2 0.5 23.0 - V Crepis capillaris 2 0.3 8.0 - V Solidago gigantea 2 0.3 75.0 - V Hypericum perforatum 1 4 65.0 65.0 Fl Veronica chamaedrys 1 2 18.5 22.5 Fr Arabis hirsuta 1 0.5 6.0 - V Erigeron annuus 1 0.5 64.0 66.0 Fl Hypochaeris radicata 1 0.5 4.0 - V Trifolium repens 1 0.5 16.0 - V Trifolium dubium 1 0.1 23.0 - V Vicia sativa subsp. nigra 1 0.1 35.0 52.0 Fl 2.3. Biomass yield and herbage properties Following vegetation data collection, the sward in each plot was manually cut to a predetermined height (5 cm, 15 cm, or 25 cm). For each cutting height, 12 biomass samples were collected (36 samples in total). The biomass was subsequently manually separated into two functional groups: grasses and forbs. All biomass samples were dried in a forced-air circulation oven to obtain constant weight. Samples of grasses and forbs biomass from each plot were weighed separately, and then mixed and homogenised in samples representing the given plot for further analysis. Homogenised biomass samples were subsequently subjected to a series of standard laboratory analyses conducted at the certified Laboratory of the Institute of Agroecology and Plant Production, Wrocław University of Environmental and Life Sciences. The laboratory analyses included: dry matter (DM) (drying at 105 ± 2°C for four h and weighting); nutrient content and nitrogen (N) concentration (Kjeldahl method, EN ISO 5983-1 standard); lipid content (defatted residue method using a Soxhlet apparatus); ash content (combustion of organic matter at 600°C in an electric furnace); crude fibre content (Henneberg–Stohmann method using a Velp extraction apparatus); neutral detergent fibre (NDF), acid detergent fibre (ADF) fractions, and lignin content (filter bag technique with the ANKOM Fibre Analyzer 200/A2000); phosphorus (P) and magnesium (Mg) concentrations (colorimetric method with a Spekol 10 spectrophotometer); potassium (K) and calcium (Ca) concentrations (flame photometry). Additional ratios between chosen micronutrients were calculated: nitrogen-to-phosphorus ratio (N/P), nitrogen-to-potassium ratio (N/K), potassium-to-phosphorus ratio (K/P), and calcium-to-magnesium ratio (Ca/Mg). 2.4 Data analysis Differences in total biomass (TB), grass biomass (GB), and forb biomass (FB) between three cutting heights (5 cm, 15 cm, and 25 cm) were compared using a one-way ANOVA followed by Tukey’s post-hoc test. The normality of the data was confirmed using the Shapiro–Wilk test. The assumption of equal variances was met according to Levene’s test. Additionally, coefficients of variation (CV; the ratio of standard deviation to mean) were calculated for FB and GB as well as for species richness and percentage cover of forbs and grasses in the plots. The relationships between the proportion of grass biomass and the corresponding herbage properties of the samples (DM, nutrient content, lipid content, ash content, crude fibre content, NDF, ADF, lignin, N, P, K, Mg, Ca, N/P, N/K, K/P, and Ca/Mg) were analysed using simple linear regression. For each response variable, a separate linear regression model was fitted. Adjusted R-squared values and p -values, along with residual diagnostics, were used for assessing the fit. ANOVA and linear regression analyses were performed using Past 4.03 software (Hammer & Harper, 2001). A redundancy analysis (RDA) was performed to visually explore dependencies between dominant plant species cover, cutting height, and herbage properties. The response variables datasets included values of DM, nutrient content, lipid content, ash content, crude fibre content, NDF fractions, ADF fractions, lignin content, N, P, K, Mg, Ca, N/P, N/K, K/P, and Ca/Mg. The response variables were log-transformed (log1p(x)) prior to analysis. The explanatory variables included the percentage cover of plant species with 100% frequency (present in each plot) ( Dactylis glomerata , Festuca rubra , Geranium pratense , Holcus lanatus , Rumex acetosa ), and cutting height (5 cm, 15 cm, and 25 cm). The analysis was conducted using the rda () function from the vegan package in R (Oksanen et al., 2022). Significance of the overall model and canonical axes was tested using permutation tests (anova.cca with 999 permutations). The direct effect of cutting height on herbage properties was examined using generalised linear mixed models (GLMMs), fitted separately for each response variable representing a herbage property. Cutting height (5 cm, 15 cm, 25 cm) was included as a fixed effect, and block ( 1 – 4 ) as a random effect. Given the distributional characteristics of the response variables, the models were specified with a Gamma distribution and a log link function. Models were fitted using the glmer() function from the lme4 package (Bates et al., 2015). The significance of fixed effects was assessed with Type II ANOVA F-tests from the car package (Fox & Weisberg, 2019). When a fixed effect was significant, pairwise post-hoc comparisons were performed with Tukey’s adjustment, using estimated marginal means from the emmeans() function in the emmeans package (Lenth, 2024). Figures were produced with the ggplot2 package (Wickham, 2016). The RDA and GLMMs were performed using R version 4.5.1 (R Core Team, 2024). The dataset containing herbage quantity and quality data is provided in Table A.1. Information on vascular plant species cover within the plots is presented in Table A.2. Both datasets are included in the Supplementary Material. 3. Results Mean total biomass (TB) collected from 1 m 2 plot decreased with increasing cutting height, from 333.3 g at 5 cm to 226.3 g at 15 cm and 156.7 g at 25 cm. A similar trend was observed for grass and forb biomass. Grass biomass (GB), with mean values of 267.3 g, 175.2 g, and 126.8 g at 5 cm, 15 cm, and 25 cm, respectively. Forb biomass (FB) also declined with increasing cutting height, with mean values of 65.9 g at 5 cm, 51 g at 15 cm, and 30 g at 25 cm. TB, GB and FB decreased significantly with cutting height. Increasing the cutting height from 5 cm to 15 cm reduced the TB by 32%, and increasing it from 5 cm to 25 cm reduced the average TB by 53%. The reductions in TB, GB, and FB were statistically significant between cutting heights (Fig. 2 A). GB decreased by 34% and 53% when cutting height was increased from 5 cm to 15 cm and 25 cm, respectively. Similar to TB, a decrease in GB was statistically significant among the groups studied (Fig. 2 B). FB decreased by 23% when cutting height increased from 5 cm to 15 cm, and decreased by 56% when it increased from 5 cm to 25 cm. The decrease was statistically significant between 5 cm and higher cuts, whereas it did not differ significantly between 15 cm and 25 cm cuts (Fig. 2 C). Variation in biomass expressed by the coefficient of variation (CV) was similar across cutting heights. The variation of GB and FB was higher than the variation in the covers of the respective plant groups. This pattern was universal for all cutting heights. The highest values of variation were characteristic for FB as well as cover and richness of forbs in plots studied (Table 2 ). Table 2 Variation in biomass, vascular plant species cover and richness among plots under different cutting regimes (cuts at 5 cm, 15 cm, and 25 cm), expressed as the coefficient of variation (ratio of standard deviation to mean). The underlined values exceed 0.2. ALL GRASSES FORBS cutting height biomass biomass cover* species biomass cover* species richness richness 5 0.15 0.2 0.16 0.18 0.4 0.25 0.21 15 0.17 0.19 0.17 0.14 0.38 0.25 0.24 25 0.17 0.21 0.13 0.16 0.5 0.23 0.28 *sum of percentage cover of all species of grasses or forbs The linear regressions revealed a statistically significant impact of the proportion of grasses on herbage properties. The forb proportion had a mirroring reverse impact on the same characteristic; therefore, it is not shown. An increasing proportion of grass in the herbage was associated with a reduction in lipid content at cutting heights of 5 cm and 15 cm (Fig. 3 A, B), as well as a decrease in potassium (K) content at 15 cm (Fig. 3 E). Conversely, a higher proportion of grass biomass corresponded to an increase in crude fibre content at 15 cm (Fig. 3 H), and in neutral detergent fibre (NDF) fractions in biomass collected from all studied cutting heights (Fig. 3 J–L). The remaining relationships—grass biomass and lipid content at 25 cm (Fig. 3 C); K at 5 cm and 25 cm (Fig. 3 D, F); and fibre content at 5 cm and 25 cm remained insignificant (Fig. 3 G, I). The RDA model was not statistically significant (p = 0.14) and explained 3.3% of the total variation. The first axis accounted for 2.0% of the variation (p = 0.07), while the second axis explained 1.4% (p = 0.09). Among statistically significant explanatory variables were: the coverage of Festuca rubra (p = 0.014), and marginally significant coverage of Dactylis glomerata (p = 0.069), Geranium pratense (p = 0.072). Statistically significant differences in herbage properties between cutting heights, revealed by GLMMs, were observed for: N/K (χ²( 2 ) = 13.27, p = 0.001), lipids (χ²( 2 ) = 9.31, p = 0.01), and DM (χ²( 2 ) = 9.10, p = 0.01) (Table 3 ). A marginal effect was found for NDF (χ²( 2 ) = 5.99, p = 0.05) (Table 3 ). No significant effects were found for the remaining properties of herbage (p > 0.05). The high marginal R² values for DM (0.67) and lipids (0.12) suggest that height explains a substantial proportion of the variance in these traits (Table 3 ). DM decreased between the 5 cm and 15 cm cutting height (Fig. 5 A), similarly, lipid content decreased with the cutting height (Fig. 5 B). The ratio of the N to K content increased with the cutting height (statistically significant differences between 5 cm and 25 cm cutting height; Fig. 5 C). Table 3 Results of generalised linear mixed models (GLMMs) showing the effect of cutting height on biomass parameters. All models included block number as a random effect. Results are sorted in descending order by marginal R² value. For each dependent variable, the marginal R², the conditional R², AIC, log-likelihood (logLik), and the Chi² statistic from the anova Type II test are also presented. Dependent Variable Marginal R² Conditional R² AIC logLik Chi² p-value DM 0.67 1.00 36.80 -13.40 9.10 0.01 lipids 0.12 0.45 35.90 -13.00 9.31 0.01 ash 0.11 0.12 63.30 -26.60 4.15 0.13 K 0.09 0.25 -69.70 39.90 0.06 0.97 N/K 0.08 0.16 -5.60 7.80 13.27 0.00 NDF 0.05 0.19 209.70 -99.80 5.99 0.05 fibre 0.02 0.14 178.30 -84.20 1.03 0.60 nutrients 0.02 0.03 110.90 -50.40 0.73 0.69 N 0.02 0.03 -14.70 12.30 0.59 0.75 P 0.02 0.07 -171.00 90.50 4.58 0.10 K/P 0.01 0.12 116.20 -53.10 1.26 0.53 ADF 0.00 0.08 147.60 -68.80 2.32 0.31 Ca/Mg 0.00 0.03 -42.90 26.50 0.16 0.92 Mg 0.00 0.02 -91.30 50.70 0.76 0.68 Ca 0.00 0.10 -107.10 58.50 0.19 0.91 4. Discussion 4.1. Biomass yield at different cutting heights Biomass yield decreased significantly with increasing cutting height, indicating that harvest quantity can be effectively manipulated by adjusting the cutting height (Dovel, 1996; Vranić et al., 2022). Our findings demonstrated a strong decline in total biomass (TB) with increasing cutting height, from 333.3 g at 5 cm to 226.3 g at 15 cm (–32%) and 156.7 g at 25 cm (–53%). These results align closely with those reported by Dovel (1996), who also found substantial yield reductions in wetland meadow communities, ranging from − 33% to − 63% when cutting height was raised from 5 to 15 cm, depending on species composition. By contrast, Vranić et al. (2022) observed only modest declines in semi-natural Croatian grasslands, with dry matter yields decreasing by approximately − 10% when cutting height was increased from 2 to 13 cm. Collectively, these studies suggest that the magnitude of biomass reduction with higher cutting heights is highly context-dependent. In more productive or moisture-rich systems (e.g., wetland meadows and our study), raising the cutting height can remove a substantial portion of the harvestable biomass, whereas in semi-natural temperate grasslands, the decrease in yield appears comparatively minor. This divergence likely reflects differences in plant species trait composition (height diversity among species), and ecological conditions (e.g., water and nutrients availability), which determine the concentration of biomass in lower versus upper sward strata. Accordingly, considerable decrease in biomass was consistent across functional groups, both grass biomass (GB) and forb biomass (FB) declined markedly as cutting height increased. FB, as well as forb cover and species richness, varied considerably more than the GB. This confirms that, forbs in grassland communities are characterised by high functional, phylogenetic, and taxonomic diversity, and although play a key role in regulating grassland ecosystem functioning, their general contribution to ecosystem productivity is more varied than graminoids (Schaub et al., 2020; Bråthen et al., 2021; Swacha et al. 2023). The reduction in biomass yield may represent a promising management option for grassland managers whose primary aim is to preserve species-rich grasslands included in nature-conservation schemes, as lower yields reduce the costs associated with biomass utilisation. We further emphasize that the reductions in biomass yield do not inherently correspond to decreases in herbage quality. 4.2. Herbage properties at different cutting heights Our results highlighted an effect of plant species composition on herbage properties collected at three cutting heights, both at the level of functional groups (grasses vs. forbs) and individual plant species. According to general knowledge, grasses, compared with forbs, are characterized by grater proportions of cell wall fibre fractions and higher cellulose contents (Armstrong et al., 1950). Forbs, in turn, develop organs that require more stable structural support, leading to more intensive shoot lignification (Armstrong et al., 1950). Consequently, forbs are characterized by higher lignin and lignocellulosic fibre contents, as well as higher levels of fatty acids than grasses (Armstrong et al., 1950; Whetsell & Rayburn, 2022). Higher NDF content, associated with an increasing proportion of grasses, results in higher cellulose and lower lignin concentrations in lignocellulosic biomass (Bovolenta et al., 2008; Melts et al., 2014; Meserszmit et al., 2022). In our study, we found significant positive correlations between the proportion of grass biomass and NDF content across all cutting heights. This to some extent corresponds to the findings for Agropyron elongatum reported by Dickeduisberg et al. (2017), who found no significant differences in crude fibre, NDF, or ADF among single-species biomass harvested at different cutting heights, suggesting that fibre concentrations are relatively homogeneous across different plant parts. In our study, the relative proportion of grass biomass across cutting heights remained constant; therefore, the NDF concentration was influenced not by the dominant plant tissues in the herbage, but by the overall proportion of grasses relative to forbs. Studies suggest that the lipid content of grassland plants depends on soil conditions, management, and the contribution of individual plant species (Dandikas et al., 2015; Duan et al., 2023). Here, proportion of grass biomass is negatively correlated with lipid content in biomass collected from 5 cm and 15 cm cut. Accordingly, lipid content decreased with cutting height in homogenised biomass samples. According to vegetation analysis presented in this study, it could be assumed that higher lipid content is associated with the proportion of Geranium pratense in the sward (RDA graph, Fig. 4 ). The proportion of G. pratense is lower in biomass collected from the higher levels (Table 1 ). Taking into consideration that forb biomass variation is the highest at the 25 cm cutting level (Table 2 ), the correlation between grass biomass proportion and lipid content is not statistically significant (Fig. 3 C). Despite the visible effect of G. pratense on lipid content, biomass quality values obtained in our study were similar to other mesic grasslands belonging to lignocellulosic feedstocks with lipid contents in the range of 1.64 to 3.17% DM (Khalsa et al. 2014, Meserszmit et al. 2024). The concentration of key micro- and macronutrients in sward changes throughout the growing season, corresponding to overall plant maturity stages (Herrmann et al., 2014; Rodriguez et al., 2017). Specifically, the biomass of grassland plant species undergoes lignification and fibre content reduction as they mature (McEniry & O'Kiely, 2013; Seppälä et al., 2009). Our results suggest that herbage properties at different cutting heights partly reflect seasonal patterns in herbage properties throughout the growing season. These pattern is reflected in the lower DM content, and higher N:K ratios observed in herbage collected at higher cutting level, which are typically characteristic of herbage harvested at the beginning of the grassland growing season (Pavlů et al., 2021). Therefore, hay collected from greater heights yields could have even superior forage quality compared to herbage harvested through traditional mowing methods. Further testing is necessary to validate this claim, as the results could be confounded by the specific composition of plant species. Specifically, the contribution of plant tissues may vary. In mesic grasslands, the height of mature plants range from 0.11 m to over 1 m (Meserszmit et al., 2024); thus high abundance of low-growing plants that complete their annual life cycle at lower heights may further affect herbage properties and obscure the relationship observed in our study. 4.3. Conservation benefits and potential ecosystem trade-offs The alternative cutting regimes evaluated in this study present a dual-faceted opportunity for enhancing nature conservation within European agroecosystems. Maintaining higher stubble levels on grasslands has been already widely promoted as a nature conservation practice to lower mortality and injury risks for grassland fauna. For example, the Polish agri-environment methodology guidelines (MRiRW/ARiMR, 2025) recommend mowing grassland swards at a height of 5–15 cm, with higher cutting heights particularly advised in habitats of rare butterflies and/or their host plants. Optimizing management parameters would reduce the energetic and logistical overhead of biomass utilisation, encouraging active management into semi-natural grasslands in regions where the demand for semi-natural grassland hay has diminished. Maintaining a very high stubble height (e.g., 25 cm) is unlikely to facilitate the encroachment of shrub or forest communities. However, because a substantial proportion of the biomass remains uncut, the progressive accumulation of litter over successive years may ultimately impair ecosystem diversity and functioning. To date, the influence of cutting height on regenerative patterns has been examined in individual species, such as Phleum pratense and Dactylis glomerata (Mislevy et al., 1977), Medicago sativa (Shen et al., 2013), and Festuca pratensis (Laihonen et al., 2022), but not at the grassland ecosystem level. Individual grassland plant species may respond differently to mowing at larger heights, which may depend on species-specific strategies of vegetative reproduction, phenology, and regeneration capacity. Therefore, further long-term research is being conducted to evaluate the effects of higher cutting regimes on ecosystem dynamics, including potential shifts in plant species composition and diversity, as well as changes in phenological and regenerative processes. 5. Conclusions This study examined biomass yield and herbage properties of semi-natural mesic grasslands under different cutting heights (5, 15, and 25 cm). We account for the site-specific effect of plant species composition, specifically plant functional groups (grasses vs. forbs), dominant species, and the quantitative distribution of plant parts at different stages of maturity. Increasing cutting height markedly reduced yield (by ~ 50% from 5 to 25 cm). However, differences in herbage properties associated with increasing cutting height were subtle (lower dry matter content, higher N:K ratio, and lower lipid content), suggesting that herbage properties at different cutting heights partly reflect seasonal patterns in herbage quality across the growing season. The cutting schemes evaluated here could provide nature conservation benefits in European agricultural landscapes in two ways: ( 1 ) through the direct positive effects of higher cutting heights on biodiversity (although further evidence is required), and ( 2 ) by expanding the area of managed grasslands through reduced costs of biomass utilisation, thereby helping to overcome utilisation constraints in regions with limited demand for semi-natural grassland hay. It should be emphasised that the data were collected over a single season at one site, which may limit the generalisability of our findings. Further studies across diverse semi-natural grassland types and agricultural landscapes are recommended. Declarations Author Contribution M.R. and G.S. conceived the study and wrote the main manuscript text. M.R. curated the data, conducted the statistical analyses, and prepared the figures. M.R. acquired institutional financial support. All authors collected field data and contributed to reviewing and editing the manuscript. Acknowledgement This work was financially supported by the Wrocław University of Environmental and Life Sciences [grant number N060/0009/23]. We are grateful to Sebastian Świerszcz for providing drone photography of the field plots, as well as to the technicians and students who assisted us during the fieldwork. Data Availability All raw data supporting the findings of this study are provided in the Supplementary Information. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8618743","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":596751011,"identity":"61edff97-c2f6-4d27-b272-e9dbd09c17da","order_by":0,"name":"Małgorzata W. 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Statistical test results are presented within the graphs. Points = means; whiskers = 95% confidence intervals of the standard error.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-8618743/v1/5bd6e4ed1d0638f5c8f5ea69.png"},{"id":103498924,"identity":"e9931fb0-f76b-42c6-96a2-3ae62239a1eb","added_by":"auto","created_at":"2026-02-26 11:46:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":532392,"visible":true,"origin":"","legend":"\u003cp\u003eLinear regression plots illustrating the relationships between the proportion of grass biomass collected from three cutting height (5cm, 15 cm, 25 cm) and the percentage [%] content of lipids, potassium (K), crude fiber, and neutral detergent fiber (NDF) at three different cutting heights (5 cm, 15 cm, and 25 cm). Plots are presented for variables that exhibited statistically significant correlations at one or more of the cutting heights. Statistical parameters of the regression models are presented within each graph.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-8618743/v1/740f1e8fae61ee9fd80e292e.png"},{"id":103498928,"identity":"ddd1a944-7778-4c79-9d7d-96ce5ffaaede","added_by":"auto","created_at":"2026-02-26 11:46:44","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":113503,"visible":true,"origin":"","legend":"\u003cp\u003eRedundancy Analysis (RDA) plot showing the relationship between herbage properties—Dry Matter Content (DM), Nitrogen (N) content, lipid content, ash content, crude fiber content, neutral detergent fiber (NDF) fractions, acid detergent fiber (ADF) fractions, lignin content, and the concentrations of phosphorus (P), potassium (K), magnesium (Mg), and calcium (Ca)—and explanatory variables including plant species with 100% occurrence: Dactylis glomerata (Dac_glom), Festuca rubra (Fes_rubr), Geranium pratense (Ger_prat), Holcus lanatus (Hol_lana), Rumex acetosa (Rum_acet), as well as cutting height (height).\u003c/p\u003e","description":"","filename":"Fig.4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8618743/v1/949586a9d06836bafb495213.jpeg"},{"id":103508056,"identity":"69e9e93b-15c0-494c-a807-096bdbc5fd6b","added_by":"auto","created_at":"2026-02-26 13:47:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":190360,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots of GLMM analysis showing statistically significant differences between cutting heights (5 cm, 15 cm, 25 cm) on herbage properties traits (dry matter concentration, lipid content, ratio of the N to K contents). Different letters indicate significant pairwise differences between treatments (p \u0026lt; 0.05; Tukey post-hoc test on estimated marginal means).\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-8618743/v1/ee61632bd79e9377d435c395.png"},{"id":108805541,"identity":"5418251a-3d34-4289-bed9-36561cd4b87b","added_by":"auto","created_at":"2026-05-08 15:26:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2514627,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8618743/v1/72b3bb05-b728-44d8-8eaf-880ef5cc5ba5.pdf"},{"id":103508288,"identity":"8ca57573-b3f4-4bdf-a93c-98c4f8a79ee3","added_by":"auto","created_at":"2026-02-26 13:48:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":200891,"visible":true,"origin":"","legend":"","description":"","filename":"TableA.1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8618743/v1/789067efd1180ab6160e33d5.pdf"},{"id":103498925,"identity":"e3f3e015-e71a-4958-a71d-3342edfde17a","added_by":"auto","created_at":"2026-02-26 11:46:44","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":315105,"visible":true,"origin":"","legend":"","description":"","filename":"TableA.2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8618743/v1/db95423e6f4a37388a89a5cf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cutting height shapes biomass yield but not herbage properties in semi-natural grasslands","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSemi-natural grasslands are a base element in the chain of meat, milk, and natural fertiliser production. Besides the direct financial benefits from livestock farming, semi-natural grasslands provide a wide range of ecosystem services and represent critical reservoirs of biodiversity. They regulate the surrounding environment, including air humidity and temperature, surface and groundwater retention, as well as physical and chemical soil properties (Habel et al., 2013; Lindborg et al. 2023). Semi-natural grasslands also constitute one of the most aesthetically appealing components of agricultural landscapes, thereby enhancing their attractiveness for nature-based tourism and recreational activities (Tscharntke et al., 2005; Hopkins and Holz, 2006). These ecosystems provide niches for a wide range of organisms at a relatively small scale (Duelli and Obrist, 2003; \u0026Ouml;ckinger and Smith, 2007; Raduła et al., 2020) and are characterised by high species richness (Chytr\u0026yacute; et al., 2015).\u003c/p\u003e \u003cp\u003eThe persistence and ecological functioning of semi-natural grasslands depend on regular biomass removal, which can be achieved through mowing, grazing, or a combination of both (Jacquemyn et al., 2011; Schneider \u0026amp; Hering, 2024). Regular management of low-intensity enables the temporal and spatial coexistence of differentiated niches, promoting the co-occurrence of less competitive plants, and enhancing overall biodiversity (Pyk\u0026auml;l\u0026auml; et al., 2005; Jacquemyn et al., 2011; Doležal et al., 2019).\u003c/p\u003e \u003cp\u003eIn many regions, the demand for grassland hay is limited due to the lower livestock density on extensive farmlands. This has resulted in the abandonment of semi-natural grasslands, triggering secondary succession and consequently causing biodiversity loss (MacDonald et al., 2000; Isselstein et al., 2005; Bignal \u0026amp; McCracken, 2000; Pellaton et al., 2022). Furthermore, extensively managed grasslands provide forage with highly varied quantity and quality (Schaub et al., 2020), which is dictated by local, varied environmental conditions, temporal changes in plant species composition, and diversified maturity stages of plant species (Donath et al., 2004; Bruinenberg et al., 2002). In contrast, cost-effective, intensively managed grasslands ensure high-quality and high-yield collections, as biomass characteristics are constant and predictable due to the simplified composition of seeded plants (Nyfeler et al., 2009; Finn et al., 2024). These grasslands are typically meliorated, levelled, re-sown, and fertilised, and all provide large amounts of nutrient-rich forage but are characterised by low species richness (Isselstein et al., 2005; Stoate et al., 2009; Bignal \u0026amp; McCracken, 2000).\u003c/p\u003e \u003cp\u003eServices delivered by semi-natural grasslands reach far above forage production, yet economic aspects have always driven human decisions (Lakner et al., 2020). Where mowing is retained in semi-natural grasslands, the biomass yields typically range from 2 to 8 t ha⁻\u0026sup1; yr⁻\u0026sup1; (Gigante et al., 2024; Heinsoo et al., 2010; Swacha et al., 2023), and often exceed local utilisation capacity in extensive farmland systems. Considerable practical and economic constraints regarding biomass valorisation frequently leads either to the complete cessation of mowing or to the retention of cut material on grassland. Although leaving biomass on site hinders woodland development; the its accumulation of uncollected biomass accelerates nutrient enrichment (particularly nitrogen and phosphorus), promotes tall, competitive grasses and shade-tolerant species, and further threatens the persistence of grassland specialists (Bohner et al. 2019; Pavlů et al. 2016). In recent years, the practice of baling cut biomass and storing it on site has become increasingly common, especially on grasslands enrolled in agri-environmental schemes that compensate farmers for the management and conservation of high-nature-value sites (Stalenga et al., 2016). Because mowing is a compulsory condition for receiving payments under these schemes, biomass is often cut but not subsequently utilised.\u003c/p\u003e \u003cp\u003eTo mitigate the adverse impacts of abandonment or inappropriate management on grassland biodiversity, management strategies could prioritise reducing the proportion of biomass removed during harvest, particularly through the implementation of higher cutting heights. The retention of taller stubble has often been advocated as a conservation measure to reduce mortality and injury risks for grassland fauna (von Berg et al., 2023). However, empirical evidence on the ecological consequences of cutting height from a plant-centred perspective remains limited. Previous research has primarily examined cutting heights ranging from 2 to 15 cm, focusing only on biomass yield and forage nutritive value (Dovel, 1996; Vranić et al., 2022). Yet, Dovel (1996) demonstrated that relationships between cutting height, biomass yield, and forage quality are not uniform, but are strongly mediated by local growing conditions (e.g., moisture stress, growing season) and plant community composition (e.g., dominance of grasses versus sedges). Reconciling the dual objectives of yield optimisation and ecosystem functioning therefore remains a persistent challenge across grassland systems.\u003c/p\u003e \u003cp\u003eThis study examines the ecological implications of varying cutting heights in mesic hay meadows, which are among the most ecologically significant semi-natural grassland types (Preislerov\u0026aacute; et al., 2022; Rodr\u0026iacute;guez-Rojo et al., 2017). These grasslands are widely distributed across temperate Europe and characterised by high species richness and structural complexity, but are increasingly threatened by agricultural intensification, land-use change, and abandonment (T\u0026ouml;r\u0026ouml;k et al. 2018). Consequently, they are listed under Annex I of the EU Habitats Directive (Council Directive 92/43/EEC). Mesic temperate grasslands harbour plant species with diverse growth forms and height potentials, making them well-suited for assessing the ecological trade-offs of alternative cutting regimes.\u003c/p\u003e \u003cp\u003eIn our study, we implemented three cutting-height treatments (5 cm, 15 cm, and 25 cm). The inclusion of the 25 cm treatment was designed to test whether substantially reducing biomass removal could enhance conservation benefits and to allow for the evaluation of herbage properties across a broader range of cutting heights. Specifically, addresses the following research questions: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) How increasing cutting height (15 cm and 25 cm) alters biomass yield relative to the conventional 5 cm regime? (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Whether increasing cutting height affects herbage properties? (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) How plant species composition, expressed as the relative proportion of grasses versus forbs, and individual species contributions, influences biomass yield and herbage properties.\u003c/p\u003e"},{"header":"2. Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study site and design\u003c/h2\u003e \u003cp\u003eThe study (51.218372\u0026deg; N, 17.204805\u0026deg; E) was conducted in semi-natural grasslands near the Łosice village, Lower Silesia, Poland (Central Europe) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, B). The study site is located in a lowland area (135 m a.s.l.) within the temperate climate zone. The mean annual temperature is 10.8\u0026deg;C, with a sum of annual precipitation of 542 mm. The vegetation season lasts approximately 220 days (Karger et al. 2020). In 2023, the mean temperature in the warmest month (June) was 20.7\u0026deg;C, and in the coldest month (January) was 3.6\u0026deg;C, based on meteorological data from the Agro- and Hydrometeorology Observatory in Wrocław-Swojec, located 12.3 km from the site.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe experiment consisted of four completely randomised blocks, each containing nine 1 m\u0026sup2; plots surrounded by buffer zones. The total area of the plot, including its buffer zone, was 2 m\u0026sup2; (1.41 x 1.41 m). The blocks and the plots (including buffer zones) were separated by 2 m and 0.5 m-wide gaps, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Work presented here represent the first stage of a long-term research programme comprising three different permanent experiments established in two semi-natural grasslands.\u003c/p\u003e \u003cp\u003eThe semi-natural grassland studied has been continuously mown since the 1980s; earlier, it had been cultivated as arable land (historical topographic maps, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.wgik.dolnyslask.pl\u003c/span\u003e\u003cspan address=\"http://www.wgik.dolnyslask.pl\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Nowadays, this area (2.2 ha) is mown once per year, in the third decade of June, for horse breeding purposes. The vegetation is dominated by \u003cem\u003eHolcus lanatus\u003c/em\u003e with high coverage of \u003cem\u003eGeranium pratense\u003c/em\u003e, \u003cem\u003eArrhenatherum elatius\u003c/em\u003e, \u003cem\u003eFestuca rubra\u003c/em\u003e, \u003cem\u003eDactylis glomerata\u003c/em\u003e, and \u003cem\u003eRumex acetosa\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). According to Chytr\u0026yacute; et al. (2020) and Kącki et al. (2020), the vegetation of the grassland represents mesic grassland of the Arrhenatherion alliance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Vegetation characteristics\u003c/h2\u003e \u003cp\u003eIn the plots, the percentage cover of each plant species was visually estimated. The data on plant species composition were collected between June 26 and 29, 2023. The nomenclature was unified according to the Euro\u0026thinsp;+\u0026thinsp;Med PlantBase (Euro\u0026thinsp;+\u0026thinsp;Med, 2006). Additionally, the height of the tallest leaf and the highest inflorescence or fruit (if present) for each species was measured. The measurements were summarised in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequency (freq.), median non-zero cover (cover), vegetative height (veg. h.; height of the highest leaf), generative height (gen. h.), and phenological phase (V \u0026ndash; vegetative, Fl \u0026ndash; flowering, Fr \u0026ndash; fruiting) of all vascular plant species recorded.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003efreq.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecover [%]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eveg. h. [cm]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003egen. h. [cm]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ephase\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHolcus lanatus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFr\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGeranium pratense\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDactylis glomerata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFr\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFestuca rubra\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFr\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRumex acetosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFr\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eArrhenatherum elatius\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e111.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFr\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVeronica arvensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePlantago lanceolata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFr\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSchedonorus pratensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFr\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAchillea millefolium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVicia tetrasperma\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eArtemisia vulgaris\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRanunculus acris\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFr\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVicia hirsuta\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCirsium arvense\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePoa pratensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFr\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGlechoma hederacea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCerastium fontanum subsp. vulgare\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGalium mollugo\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVeronica serpyllifolia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eElytrigia repens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHieracium species\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePhleum pratense\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eJacobaea vulgaris\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRanunculus repens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePrunus spinosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePastinaca sativa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCrepis capillaris\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSolidago gigantea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHypericum perforatum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVeronica chamaedrys\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFr\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eArabis hirsuta\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eErigeron annuus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHypochaeris radicata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTrifolium repens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTrifolium dubium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVicia sativa subsp. nigra\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Biomass yield and herbage properties\u003c/h2\u003e \u003cp\u003eFollowing vegetation data collection, the sward in each plot was manually cut to a predetermined height (5 cm, 15 cm, or 25 cm). For each cutting height, 12 biomass samples were collected (36 samples in total). The biomass was subsequently manually separated into two functional groups: grasses and forbs.\u003c/p\u003e \u003cp\u003eAll biomass samples were dried in a forced-air circulation oven to obtain constant weight. Samples of grasses and forbs biomass from each plot were weighed separately, and then mixed and homogenised in samples representing the given plot for further analysis.\u003c/p\u003e \u003cp\u003eHomogenised biomass samples were subsequently subjected to a series of standard laboratory analyses conducted at the certified Laboratory of the Institute of Agroecology and Plant Production, Wrocław University of Environmental and Life Sciences. The laboratory analyses included: dry matter (DM) (drying at 105\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C for four h and weighting); nutrient content and nitrogen (N) concentration (Kjeldahl method, EN ISO 5983-1 standard); lipid content (defatted residue method using a Soxhlet apparatus); ash content (combustion of organic matter at 600\u0026deg;C in an electric furnace); crude fibre content (Henneberg\u0026ndash;Stohmann method using a Velp extraction apparatus); neutral detergent fibre (NDF), acid detergent fibre (ADF) fractions, and lignin content (filter bag technique with the ANKOM Fibre Analyzer 200/A2000); phosphorus (P) and magnesium (Mg) concentrations (colorimetric method with a Spekol 10 spectrophotometer); potassium (K) and calcium (Ca) concentrations (flame photometry).\u003c/p\u003e \u003cp\u003eAdditional ratios between chosen micronutrients were calculated: nitrogen-to-phosphorus ratio (N/P), nitrogen-to-potassium ratio (N/K), potassium-to-phosphorus ratio (K/P), and calcium-to-magnesium ratio (Ca/Mg).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data analysis\u003c/h2\u003e \u003cp\u003eDifferences in total biomass (TB), grass biomass (GB), and forb biomass (FB) between three cutting heights (5 cm, 15 cm, and 25 cm) were compared using a one-way ANOVA followed by Tukey\u0026rsquo;s post-hoc test. The normality of the data was confirmed using the Shapiro\u0026ndash;Wilk test. The assumption of equal variances was met according to Levene\u0026rsquo;s test. Additionally, coefficients of variation (CV; the ratio of standard deviation to mean) were calculated for FB and GB as well as for species richness and percentage cover of forbs and grasses in the plots.\u003c/p\u003e \u003cp\u003eThe relationships between the proportion of grass biomass and the corresponding herbage properties of the samples (DM, nutrient content, lipid content, ash content, crude fibre content, NDF, ADF, lignin, N, P, K, Mg, Ca, N/P, N/K, K/P, and Ca/Mg) were analysed using simple linear regression. For each response variable, a separate linear regression model was fitted. Adjusted R-squared values and \u003cem\u003ep\u003c/em\u003e-values, along with residual diagnostics, were used for assessing the fit.\u003c/p\u003e \u003cp\u003eANOVA and linear regression analyses were performed using Past 4.03 software (Hammer \u0026amp; Harper, 2001).\u003c/p\u003e \u003cp\u003eA redundancy analysis (RDA) was performed to visually explore dependencies between dominant plant species cover, cutting height, and herbage properties. The response variables datasets included values of DM, nutrient content, lipid content, ash content, crude fibre content, NDF fractions, ADF fractions, lignin content, N, P, K, Mg, Ca, N/P, N/K, K/P, and Ca/Mg. The response variables were log-transformed (log1p(x)) prior to analysis. The explanatory variables included the percentage cover of plant species with 100% frequency (present in each plot) (\u003cem\u003eDactylis glomerata\u003c/em\u003e, \u003cem\u003eFestuca rubra\u003c/em\u003e, \u003cem\u003eGeranium pratense\u003c/em\u003e, \u003cem\u003eHolcus lanatus\u003c/em\u003e, \u003cem\u003eRumex acetosa\u003c/em\u003e), and cutting height (5 cm, 15 cm, and 25 cm). The analysis was conducted using the \u003cem\u003erda\u003c/em\u003e() function from the vegan package in R (Oksanen et al., 2022). Significance of the overall model and canonical axes was tested using permutation tests (anova.cca with 999 permutations).\u003c/p\u003e \u003cp\u003eThe direct effect of cutting height on herbage properties was examined using generalised linear mixed models (GLMMs), fitted separately for each response variable representing a herbage property. Cutting height (5 cm, 15 cm, 25 cm) was included as a fixed effect, and block (\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) as a random effect. Given the distributional characteristics of the response variables, the models were specified with a Gamma distribution and a log link function. Models were fitted using the glmer() function from the lme4 package (Bates et al., 2015). The significance of fixed effects was assessed with Type II ANOVA F-tests from the car package (Fox \u0026amp; Weisberg, 2019). When a fixed effect was significant, pairwise post-hoc comparisons were performed with Tukey\u0026rsquo;s adjustment, using estimated marginal means from the emmeans() function in the emmeans package (Lenth, 2024). Figures were produced with the ggplot2 package (Wickham, 2016).\u003c/p\u003e \u003cp\u003eThe RDA and GLMMs were performed using R version 4.5.1 (R Core Team, 2024).\u003c/p\u003e \u003cp\u003eThe dataset containing herbage quantity and quality data is provided in Table A.1. Information on vascular plant species cover within the plots is presented in Table A.2. Both datasets are included in the Supplementary Material.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eMean total biomass (TB) collected from 1 m\u003csup\u003e2\u003c/sup\u003e plot decreased with increasing cutting height, from 333.3 g at 5 cm to 226.3 g at 15 cm and 156.7 g at 25 cm. A similar trend was observed for grass and forb biomass. Grass biomass (GB), with mean values of 267.3 g, 175.2 g, and 126.8 g at 5 cm, 15 cm, and 25 cm, respectively. Forb biomass (FB) also declined with increasing cutting height, with mean values of 65.9 g at 5 cm, 51 g at 15 cm, and 30 g at 25 cm. TB, GB and FB decreased significantly with cutting height. Increasing the cutting height from 5 cm to 15 cm reduced the TB by 32%, and increasing it from 5 cm to 25 cm reduced the average TB by 53%. The reductions in TB, GB, and FB were statistically significant between cutting heights (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). GB decreased by 34% and 53% when cutting height was increased from 5 cm to 15 cm and 25 cm, respectively. Similar to TB, a decrease in GB was statistically significant among the groups studied (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). FB decreased by 23% when cutting height increased from 5 cm to 15 cm, and decreased by 56% when it increased from 5 cm to 25 cm. The decrease was statistically significant between 5 cm and higher cuts, whereas it did not differ significantly between 15 cm and 25 cm cuts (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eVariation in biomass expressed by the coefficient of variation (CV) was similar across cutting heights. The variation of GB and FB was higher than the variation in the covers of the respective plant groups. This pattern was universal for all cutting heights. The highest values of variation were characteristic for FB as well as cover and richness of forbs in plots studied (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariation in biomass, vascular plant species cover and richness among plots under different cutting regimes (cuts at 5 cm, 15 cm, and 25 cm), expressed as the coefficient of variation (ratio of standard deviation to mean). The \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eunderlined\u003c/span\u003e values exceed 0.2.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eALL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eGRASSES\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eFORBS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ecutting height\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ebiomass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ebiomass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ecover*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003especies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ebiomass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ecover*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003especies\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003erichness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003erichness\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.2\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.4\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.25\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.21\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.38\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.25\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.24\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.21\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.5\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.23\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e0.28\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e*sum of percentage cover of all species of grasses or forbs\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe linear regressions revealed a statistically significant impact of the proportion of grasses on herbage properties. The forb proportion had a mirroring reverse impact on the same characteristic; therefore, it is not shown. An increasing proportion of grass in the herbage was associated with a reduction in lipid content at cutting heights of 5 cm and 15 cm (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, B), as well as a decrease in potassium (K) content at 15 cm (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). Conversely, a higher proportion of grass biomass corresponded to an increase in crude fibre content at 15 cm (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH), and in neutral detergent fibre (NDF) fractions in biomass collected from all studied cutting heights (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eJ\u0026ndash;L). The remaining relationships\u0026mdash;grass biomass and lipid content at 25 cm (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC); K at 5 cm and 25 cm (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD, F); and fibre content at 5 cm and 25 cm remained insignificant (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG, I).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe RDA model was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.14) and explained 3.3% of the total variation. The first axis accounted for 2.0% of the variation (p\u0026thinsp;=\u0026thinsp;0.07), while the second axis explained 1.4% (p\u0026thinsp;=\u0026thinsp;0.09). Among statistically significant explanatory variables were: the coverage of \u003cem\u003eFestuca rubra\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.014), and marginally significant coverage of \u003cem\u003eDactylis glomerata\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.069), \u003cem\u003eGeranium pratense\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.072).\u003c/p\u003e \u003cp\u003eStatistically significant differences in herbage properties between cutting heights, revealed by GLMMs, were observed for: N/K (χ\u0026sup2;(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;13.27, p\u0026thinsp;=\u0026thinsp;0.001), lipids (χ\u0026sup2;(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;9.31, p\u0026thinsp;=\u0026thinsp;0.01), and DM (χ\u0026sup2;(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;9.10, p\u0026thinsp;=\u0026thinsp;0.01) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). A marginal effect was found for NDF (χ\u0026sup2;(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;5.99, p\u0026thinsp;=\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). No significant effects were found for the remaining properties of herbage (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The high marginal R\u0026sup2; values for DM (0.67) and lipids (0.12) suggest that height explains a substantial proportion of the variance in these traits (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDM decreased between the 5 cm and 15 cm cutting height (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), similarly, lipid content decreased with the cutting height (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). The ratio of the N to K content increased with the cutting height (statistically significant differences between 5 cm and 25 cm cutting height; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of generalised linear mixed models (GLMMs) showing the effect of cutting height on biomass parameters. All models included block number as a random effect. Results are sorted in descending order by marginal R\u0026sup2; value. For each dependent variable, the marginal R\u0026sup2;, the conditional R\u0026sup2;, AIC, log-likelihood (logLik), and the Chi\u0026sup2; statistic from the anova Type II test are also presented.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDependent Variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarginal R\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConditional R\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003elogLik\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eChi\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-13.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elipids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-13.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eash\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-26.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-69.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN/K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e209.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-99.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efibre\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e178.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-84.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enutrients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e110.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-50.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-14.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-171.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK/P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e116.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-53.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e147.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-68.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCa/Mg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-42.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-91.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-107.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Biomass yield at different cutting heights\u003c/h2\u003e \u003cp\u003eBiomass yield decreased significantly with increasing cutting height, indicating that harvest quantity can be effectively manipulated by adjusting the cutting height (Dovel, 1996; Vranić et al., 2022). Our findings demonstrated a strong decline in total biomass (TB) with increasing cutting height, from 333.3 g at 5 cm to 226.3 g at 15 cm (\u0026ndash;32%) and 156.7 g at 25 cm (\u0026ndash;53%). These results align closely with those reported by Dovel (1996), who also found substantial yield reductions in wetland meadow communities, ranging from \u0026minus;\u0026thinsp;33% to \u0026minus;\u0026thinsp;63% when cutting height was raised from 5 to 15 cm, depending on species composition. By contrast, Vranić et al. (2022) observed only modest declines in semi-natural Croatian grasslands, with dry matter yields decreasing by approximately \u0026minus;\u0026thinsp;10% when cutting height was increased from 2 to 13 cm. Collectively, these studies suggest that the magnitude of biomass reduction with higher cutting heights is highly context-dependent. In more productive or moisture-rich systems (e.g., wetland meadows and our study), raising the cutting height can remove a substantial portion of the harvestable biomass, whereas in semi-natural temperate grasslands, the decrease in yield appears comparatively minor. This divergence likely reflects differences in plant species trait composition (height diversity among species), and ecological conditions (e.g., water and nutrients availability), which determine the concentration of biomass in lower versus upper sward strata.\u003c/p\u003e \u003cp\u003eAccordingly, considerable decrease in biomass was consistent across functional groups, both grass biomass (GB) and forb biomass (FB) declined markedly as cutting height increased. FB, as well as forb cover and species richness, varied considerably more than the GB. This confirms that, forbs in grassland communities are characterised by high functional, phylogenetic, and taxonomic diversity, and although play a key role in regulating grassland ecosystem functioning, their general contribution to ecosystem productivity is more varied than graminoids (Schaub et al., 2020; Br\u0026aring;then et al., 2021; Swacha et al. 2023).\u003c/p\u003e \u003cp\u003eThe reduction in biomass yield may represent a promising management option for grassland managers whose primary aim is to preserve species-rich grasslands included in nature-conservation schemes, as lower yields reduce the costs associated with biomass utilisation. We further emphasize that the reductions in biomass yield do not inherently correspond to decreases in herbage quality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Herbage properties at different cutting heights\u003c/h2\u003e \u003cp\u003eOur results highlighted an effect of plant species composition on herbage properties collected at three cutting heights, both at the level of functional groups (grasses vs. forbs) and individual plant species. According to general knowledge, grasses, compared with forbs, are characterized by grater proportions of cell wall fibre fractions and higher cellulose contents (Armstrong et al., 1950). Forbs, in turn, develop organs that require more stable structural support, leading to more intensive shoot lignification (Armstrong et al., 1950). Consequently, forbs are characterized by higher lignin and lignocellulosic fibre contents, as well as higher levels of fatty acids than grasses (Armstrong et al., 1950; Whetsell \u0026amp; Rayburn, 2022).\u003c/p\u003e \u003cp\u003eHigher NDF content, associated with an increasing proportion of grasses, results in higher cellulose and lower lignin concentrations in lignocellulosic biomass (Bovolenta et al., 2008; Melts et al., 2014; Meserszmit et al., 2022). In our study, we found significant positive correlations between the proportion of grass biomass and NDF content across all cutting heights. This to some extent corresponds to the findings for \u003cem\u003eAgropyron elongatum\u003c/em\u003e reported by Dickeduisberg et al. (2017), who found no significant differences in crude fibre, NDF, or ADF among single-species biomass harvested at different cutting heights, suggesting that fibre concentrations are relatively homogeneous across different plant parts. In our study, the relative proportion of grass biomass across cutting heights remained constant; therefore, the NDF concentration was influenced not by the dominant plant tissues in the herbage, but by the overall proportion of grasses relative to forbs.\u003c/p\u003e \u003cp\u003eStudies suggest that the lipid content of grassland plants depends on soil conditions, management, and the contribution of individual plant species (Dandikas et al., 2015; Duan et al., 2023). Here, proportion of grass biomass is negatively correlated with lipid content in biomass collected from 5 cm and 15 cm cut. Accordingly, lipid content decreased with cutting height in homogenised biomass samples. According to vegetation analysis presented in this study, it could be assumed that higher lipid content is associated with the proportion of \u003cem\u003eGeranium pratense\u003c/em\u003e in the sward (RDA graph, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The proportion of \u003cem\u003eG. pratense\u003c/em\u003e is lower in biomass collected from the higher levels (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Taking into consideration that forb biomass variation is the highest at the 25 cm cutting level (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), the correlation between grass biomass proportion and lipid content is not statistically significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Despite the visible effect of \u003cem\u003eG. pratense\u003c/em\u003e on lipid content, biomass quality values obtained in our study were similar to other mesic grasslands belonging to lignocellulosic feedstocks with lipid contents in the range of 1.64 to 3.17% DM (Khalsa et al. 2014, Meserszmit et al. 2024).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe concentration of key micro- and macronutrients in sward changes throughout the growing season, corresponding to overall plant maturity stages (Herrmann et al., 2014; Rodriguez et al., 2017). Specifically, the biomass of grassland plant species undergoes lignification and fibre content reduction as they mature (McEniry \u0026amp; O'Kiely, 2013; Sepp\u0026auml;l\u0026auml; et al., 2009). Our results suggest that herbage properties at different cutting heights partly reflect seasonal patterns in herbage properties throughout the growing season. These pattern is reflected in the lower DM content, and higher N:K ratios observed in herbage collected at higher cutting level, which are typically characteristic of herbage harvested at the beginning of the grassland growing season (Pavlů et al., 2021). Therefore, hay collected from greater heights yields could have even superior forage quality compared to herbage harvested through traditional mowing methods. Further testing is necessary to validate this claim, as the results could be confounded by the specific composition of plant species. Specifically, the contribution of plant tissues may vary. In mesic grasslands, the height of mature plants range from 0.11 m to over 1 m (Meserszmit et al., 2024); thus high abundance of low-growing plants that complete their annual life cycle at lower heights may further affect herbage properties and obscure the relationship observed in our study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Conservation benefits and potential ecosystem trade-offs\u003c/h2\u003e \u003cp\u003eThe alternative cutting regimes evaluated in this study present a dual-faceted opportunity for enhancing nature conservation within European agroecosystems. Maintaining higher stubble levels on grasslands has been already widely promoted as a nature conservation practice to lower mortality and injury risks for grassland fauna. For example, the Polish agri-environment methodology guidelines (MRiRW/ARiMR, 2025) recommend mowing grassland swards at a height of 5\u0026ndash;15 cm, with higher cutting heights particularly advised in habitats of rare butterflies and/or their host plants. Optimizing management parameters would reduce the energetic and logistical overhead of biomass utilisation, encouraging active management into semi-natural grasslands in regions where the demand for semi-natural grassland hay has diminished.\u003c/p\u003e \u003cp\u003eMaintaining a very high stubble height (e.g., 25 cm) is unlikely to facilitate the encroachment of shrub or forest communities. However, because a substantial proportion of the biomass remains uncut, the progressive accumulation of litter over successive years may ultimately impair ecosystem diversity and functioning. To date, the influence of cutting height on regenerative patterns has been examined in individual species, such as \u003cem\u003ePhleum pratense\u003c/em\u003e and \u003cem\u003eDactylis glomerata\u003c/em\u003e (Mislevy et al., 1977), \u003cem\u003eMedicago sativa\u003c/em\u003e (Shen et al., 2013), and \u003cem\u003eFestuca pratensis\u003c/em\u003e (Laihonen et al., 2022), but not at the grassland ecosystem level. Individual grassland plant species may respond differently to mowing at larger heights, which may depend on species-specific strategies of vegetative reproduction, phenology, and regeneration capacity. Therefore, further long-term research is being conducted to evaluate the effects of higher cutting regimes on ecosystem dynamics, including potential shifts in plant species composition and diversity, as well as changes in phenological and regenerative processes.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study examined biomass yield and herbage properties of semi-natural mesic grasslands under different cutting heights (5, 15, and 25 cm). We account for the site-specific effect of plant species composition, specifically plant functional groups (grasses vs. forbs), dominant species, and the quantitative distribution of plant parts at different stages of maturity. Increasing cutting height markedly reduced yield (by ~\u0026thinsp;50% from 5 to 25 cm). However, differences in herbage properties associated with increasing cutting height were subtle (lower dry matter content, higher N:K ratio, and lower lipid content), suggesting that herbage properties at different cutting heights partly reflect seasonal patterns in herbage quality across the growing season. The cutting schemes evaluated here could provide nature conservation benefits in European agricultural landscapes in two ways: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) through the direct positive effects of higher cutting heights on biodiversity (although further evidence is required), and (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) by expanding the area of managed grasslands through reduced costs of biomass utilisation, thereby helping to overcome utilisation constraints in regions with limited demand for semi-natural grassland hay. It should be emphasised that the data were collected over a single season at one site, which may limit the generalisability of our findings. Further studies across diverse semi-natural grassland types and agricultural landscapes are recommended.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eM.R. and G.S. conceived the study and wrote the main manuscript text. M.R. curated the data, conducted the statistical analyses, and prepared the figures. M.R. acquired institutional financial support. All authors collected field data and contributed to reviewing and editing the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis work was financially supported by the Wrocław University of Environmental and Life Sciences [grant number N060/0009/23]. We are grateful to Sebastian Świerszcz for providing drone photography of the field plots, as well as to the technicians and students who assisted us during the fieldwork.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll raw data supporting the findings of this study are provided in the Supplementary Information. Data on biomass yield and herbage properties are presented in Supplementary Table A.1, while plant species composition data are presented in Supplementary Table A.2.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArmstrong, D. G., Cook, H. \u0026amp; Thomas, B. The lignin and cellulose contents of certain grassland species at different stages of growth. \u003cem\u003eJ. 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Variation in fatty acids concentration in grasses, legumes, and forbs in the Allegheny Plateau. \u003cem\u003eAgronomy\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e (7), 1693. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/agronomy12071693\u003c/span\u003e\u003cspan address=\"10.3390/agronomy12071693\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"sward, sustainable management, mesic grassland, biodiversity, fibre, dry matter content","lastPublishedDoi":"10.21203/rs.3.rs-8618743/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8618743/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe declining demand for biomass delivered from semi-natural grasslands, driven by rapid socio-economic change, is a major threat for grassland abandonment accelerating biodiversity loss. Developing management strategies that intentionally reduce biomass removal, such as increasing cutting height, may help overcome utilisation challenges in regions with limited demand for hay. This study represents the first phase of a long-term field project established in semi-natural grasslands. We tested the effect of three cutting heights (5, 15, and 25 cm) on biomass yields and herbage properties in mesic grassland. We further assessed the effects of functional groups (grasses versus forbs) and individual plant species on these parameters to disentangle cutting height effects from site-specific variation in plant species composition. Biomass declined by ~\u0026thinsp;50% when cutting height increased from 5 to 25 cm. The proportion of grass biomass positively influenced fibre content and negatively influenced lipid concentrations, although these effects were attenuated at the highest cutting height. Despite reduced biomass, herbage nutritive value remained stable across cutting heights. We conclude that management strategies incorporating higher cutting heights can substantially reduce harvested biomass yield while maintaining herbage quality providing a practical tool to facilitate biomass utilisation and contribute to the prevention of semi-natural grassland abandonment.\u003c/p\u003e","manuscriptTitle":"Cutting height shapes biomass yield but not herbage properties in semi-natural grasslands","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-26 11:46:39","doi":"10.21203/rs.3.rs-8618743/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c2637731-4e06-447b-9b04-0211bc4ebe08","owner":[],"postedDate":"February 26th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-06T05:48:37+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":63494943,"name":"Biological sciences/Ecology"},{"id":63494944,"name":"Earth and environmental sciences/Ecology"},{"id":63494945,"name":"Earth and environmental sciences/Environmental sciences"},{"id":63494946,"name":"Biological sciences/Plant sciences"}],"tags":[],"updatedAt":"2026-05-06T05:55:56+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-26 11:46:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8618743","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8618743","identity":"rs-8618743","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}